Design of a Protection System for Distributed Energy Sources in Distribution Grids

Published by 1. Róbert Štefko1, 2. Michal Kolcun1, 3. Marek Bobček1, 4. Damian Mazur2 , 5. Bogdan Kwiatkowski2, Technical University of Košice (1), Rzeszow University of Technology (2) ORCID: 1. 0000-0002-2477-4559, 2. 0000-0002-8041-9076, 3. 0009-0004-1912-211X; 4. 0000-0002-3247-5903, 5. 0000-0001-5287-2191

Abstract. The continuous rise in electricity consumption and the integration of renewable energy sources into distribution grids are gradually posing challenges to conventional protection systems. This trend significantly impacts traditional centralized methods of electricity generation, shifting towards local production and consumption and moving closer to emerging microgrids. This aspect was specifically considered during the development of the current power system we utilize. To ensure the successful emergence of microgrids, it’s imperative to begin addressing the issue of protecting these renewable energy sources, especially considering that our current devices lack communication or remote-control capabilities. The size of the topology and the number of devices managed at each point in a microgrid will play a crucial role. Therefore, addressing the overall management of individual devices and resources within the microgrid is essential.

Streszczenie. Ciągły wzrost zużycia energii elektrycznej i integracja odnawialnych źródeł energii z sieciami dystrybucyjnymi stopniowo stawiają wyzwania konwencjonalnym systemom ochrony. Ten trend znacząco wpływa na tradycyjne scentralizowane metody wytwarzania energii elektrycznej, przesuwając się w kierunku lokalnej produkcji i zużycia oraz zbliżając się do powstających mikrosieci. Ten aspekt został szczególnie rozważony podczas opracowywania obecnego systemu energetycznego, z którego korzystamy. Aby zapewnić pomyślne powstanie mikrosieci, konieczne jest rozpoczęcie zajmowania się kwestią ochrony tych odnawialnych źródeł energii, zwłaszcza biorąc pod uwagę, że nasze obecne urządzenia nie mają możliwości komunikacji lub zdalnego sterowania. Rozmiar topologii i liczba urządzeń zarządzanych w każdym punkcie mikrosieci będą odgrywać kluczową rolę. Dlatego też zajęcie się ogólnym zarządzaniem poszczególnymi urządzeniami i zasobami w mikrosieci jest niezbędne. (Projekt systemu zabezpieczeń rozproszonych źródeł energii w sieci dystrybucyjnej)

Keywords: protection system, protection relay, distribution grids, distribution energy sources.
Słowa kluczowe: system zabezpieczeń, przekaźnik zabezpieczający, sieci dystrybucyjne, dystrybucyjne źródła energii.

Introduction

The integration of renewable energy sources (RES) into existing energy grids heralds a transformative shift, marked by reduced transmission losses and heightened operational reliability. However, this transition brings forth a host of new challenges, particularly in the realms of protection, control, and fault localization systems. Addressing these challenges necessitates ongoing research and innovation in distribution grid technology, with microgrids emerging as a beacon of promise for the future.

One of the defining characteristics of microgrids is their remarkable adaptability, seamlessly transitioning between islanded operation and grid-connected mode. This flexibility is empowered by their inherent self-control capabilities, allowing them to autonomously manage energy generation and consumption. In the event of system faults or disruptions, microgrids can swiftly switch to islanded mode, drawing upon local and renewable energy sources to maintain power supply reliability.

Despite the technical complexities inherent in microgrid design, the benefits they offer outweigh the associated concerns. An essential aspect of microgrid planning is the careful selection and integration of energy sources, balancing local generation with renewable inputs to optimize grid performance. This strategic energy mix is pivotal in mitigating control and protection system challenges within distribution grids, ensuring robust and reliable operation.

Renewable energy units embedded within microgrids fundamentally alter the traditional energy distribution paradigm. By situating energy production closer to consumption points, microgrids enable bidirectional energy flow, effectively decentralizing power generation. This paradigm shift prompts critical questions regarding energy mix optimization, sustainability, and grid flexibility, particularly in response to diverse weather conditions and demand fluctuations.

Navigating these challenges requires a reevaluation of conventional grid infrastructure. A comparative analysis, as depicted in Fig. 1, underscores the significant departure from the radial energy flow model observed in traditional power systems. In contrast, microgrids facilitate bidirectional energy flow by shortening distribution lines and integrating distributed energy sources, paving the way for a more resilient and adaptable energy landscape.

Fig.1. Illustrates the disparity in energy flow directions between conventional power systems and microgrids [1].
Definition of Microgrid

Microgrids can be defined as small local distribution grids that supply electrical energy to consumers, generating electricity through distributed energy sources. These grids must achieve self-sufficiency in electricity production, necessitating an appropriate energy mix based on geographic location to meet load demands.

According to a European Union research project, a microgrid encompasses low-voltage distribution systems with distributed energy resources, storage devices, energy storage systems, and flexible loads. These systems can operate connected or disconnected from the main grid. In essence, a microgrid is a modern autonomous energy distribution system primarily powered by local renewable energy sources [2].

Similarly, the U.S. Department of Energy defines a microgrid as a group of interconnected loads and distributed energy resources within clearly defined boundaries, acting as a single controllable unit concerning the grid. Microgrids can connect and disconnect from the grid, allowing operation in both connected and islanded modes [2].

Protection of distributed sources of electrical energy connected to the distribution grid is essential for several reasons. Inverters include a built-in protection system and perform self-checks in case of faults. Additional protection systems, such as circuit breakers, circuit protection devices, fuses, and surge protectors, are employed to safeguard the inputs. However, protective relays utilized in low-voltage grids often have limited functionality, primarily monitoring frequency and voltage, and detecting ground faults or disconnections during grid outages.

Current State of Research

Current research suggests various perspectives on the further development of smart grids and microgrids. While one of the current research trends indicates the use of Phasor Measurement Units and centralized processing of measured data, only after the development of new protective relays with enhanced mutual communication. A similar direction is also taken by article [3], in which the research team focused on introducing a new method for developing protective relays based on simulation and applying it to the development of localized devices for protecting distribution lines. Applying this method to the development of localized devices for protecting distribution lines and verifying its effectiveness and accuracy through comparing the simulated model with physical testing on relays.

The article [4], similarly to the previous one, suggests the utilization of simulation. It explores the necessity of hard-in-the-loop simulation (HILS) for cooperative protection research in meshed distribution grids. It highlights the issues with protection in these grids and proposes HILS as a solution. The authors analyse traditional testing methods and present a case study demonstrating the effectiveness of HILS. Overall, it represents an important contribution to addressing issues in the field of electrical power distribution.

The article [5] proposes an adaptive protection strategy for power distribution systems with distributed generation (DG), specifically addressing relay malfunctions in radial distribution systems integrated with photovoltaic (PV) sources. It combines Fuzzy Logic (FL) and Genetic Algorithm (GA) to dynamically adjust relay settings based on changes in PV capacity and load demand, aiming to enhance system reliability without infrastructure redesign. By analysing scenarios and comparing with traditional methods, the study demonstrates the effectiveness of FLGA in optimizing relay operation, offering a valuable solution for improving power distribution systems amidst increasing DG integration.

The article [6] examines the influence of integrating distributed photovoltaic (PV) systems on distribution grid protection, particularly regarding low voltage ride-through (LVRT) events. It points out that conventional protection methods may not adequately address the altered fault characteristics resulting from PV integration. The paper proposes a distributed PV LVRT control strategy to mitigate these impacts while providing support during faults. Through analysis and simulations, the strategy’s effectiveness is demonstrated, paving the way for improved fault management in active distribution grids.

The article [7] outlines a collaborative effort with ENEL Distribution São Paulo to enhance intelligence, automation, and protection in the low voltage (LV) overhead distribution grid. It introduces self-healing methodology for LV grids, previously utilized in medium voltage (MV) grids. The development and improvements to LV Control equipment for real-time monitoring and transformer protection are discussed, along with simulations validating the strategy’s effectiveness. The article highlights the need for advanced monitoring and protection equipment in LV grids and introduces an innovative solution to address this gap.

The article [8] addresses challenges in implementing relay protection systems in distribution grids due to the integration of distributed energy resources, proposing an automated system to adjust protection settings. It outlines an adaptive dynamic protection scheme and optimization methods, along with the development of microservices for automatic calculation and adjustment of parameters. Experimental results demonstrate the system’s effectiveness in accurately adjusting protection settings for various scenarios, highlighting its potential to enhance grid reliability. Overall, the article presents a promising solution to evolving distribution grid challenges through automated protection adjustment systems.

Protection Relays for Distribution Grids: Ensuring Electrical System Security

Programmable protective relays are electronic devices used in transmission and distribution electrical grids to detect and respond to various faults and anomalies in the system. These relays can perform various protective functions and are programmable according to specific requirements and needs of the distribution grid. Each manufacturer of these relays has its own way of setting the parameters. Their main task is to monitor electrical parameters such as voltage, current, and frequency, and in case of detecting abnormalities or faults, to trigger protective actions such as disconnecting a section using a contactor. Programmable protective relays are an important component of distribution grid protection systems and help ensure safe and reliable operation of electrical grids.

In the territory of the Slovak Republic, there are three electricity suppliers: the Western Slovak Distribution Company (ZSD), the Central Slovak Distribution Company (SSD), and the Eastern Slovak Distribution Company (VSD). These distribution companies in Slovakia manage high-voltage lines and ensure the supply of electricity to consumers. Each of the recommended protective relays according to Table 1. has been tested by VSD and meets strict requirements for response time and measurement accuracy. Currently programmable protective relays are applied in the territory of the Slovak Republic according to the requirements of the local Eastern Slovak distribution energy company (VSD) for sources exceeding 10 kW.

Table 1. Approved types of external grid protection by VSD [9]

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When connecting a larger source exceeding 10 kW, it is necessary to apply approved programmable relays as specified by the distribution company managing the area where the source will be installed. For the low-voltage level (LV), the standard wiring diagram for direct measurement by an electricity meter and a smart meter is depicted in Fig.2. Additionally, other components such as surge protectors are part of the assembly, which are additionally protected by 100A fuses, although they are not shown in the diagram in Fig. 2. For the DC part of the system, which connects to the inverter, similar protection of individual interconnected panels into so-called strings and the installation of surge protection on each such string is also necessary.

According to the current requirements of VSD, when connecting a local source to the distribution grid with a capacity up to 10 kW, it is not necessary to install external grid protection for such a source (integrated grid protection cannot be set according to VSD requirements). However, when using more than one inverter with a total installed power exceeding 10 kW, it is necessary to install external grid protection for such a source, which will control the main disconnecting point. The approved types and manufacturers of external grid protection devices according to the VSD company are shown in Table 2. along with their purchase prices [9].

Fig.2. Schematic representation of a protective system for sources from 10 kW to 50 kW connected to a LV distribution grid

Table 2. The required settings of the external gird protection according to the VSD for LV grid [9]

.

For such external grid protections, there is a relatively simple setup using only basic functions to monitor the qualitative parameters of the generated electrical energy. The settings and description are displayed in Table 2.. This external grid protection will primarily function as a monitoring relay. Upon exceeding specified limits, it will trigger a signal to change the state of the output contacts, whose condition can be set for controlling the main disconnecting point. In the context of the protective system, it’s crucial to note that the protective relay solely focuses on the main disconnecting point, neglecting to monitor the operational states of other components within the protection system. Consequently, the electricity distributor is only privy to information regarding the consumer’s electrical energy transactions with the grid – whether it be consumption from or supply to the grid. When considering the integration of distributed energy sources with a capacity of up to 110 kW, the fundamental principle aligns with the protection strategy discussed earlier.

However, a notable deviation lies in the requirement for a current instrument transformer to facilitate accurate measurement of the consumer’s production or consumption by the smart meter. This additional component, depicted in Fig. 3, plays a pivotal role in enhancing the monitoring and management capabilities of the system, ensuring efficient and reliable operation.

The installation of larger energy sources is typically addressed for industrial enterprises that possess relatively large rooftops capable of accommodating such capacity. While conventional photovoltaic stations are also situated in open fields, the prevailing trend indicates a notable increase, especially within the industrial sector. Upon connection to the medium-voltage (MV) level, consideration must also be given to the installation of a transformer and an additional protection system.

Fig.3. Schematic representation of a protective system for sources from 50 kW to 110 kW connected to a LV distribution grid

In such instances, the billing measurement responsibility shifts from the distributor to the higher voltage side, as industrial areas often incorporate their own substations on the consumer’s premises. Consequently, the addition of a voltage instrument transformer becomes necessary to enable the smart meter to measure consumption accurately.

When considering inverters larger than 110 kW, as shown in Fig. 4, the complexity of the protection system increases significantly. The distribution company now mandates monitoring the status of each protective device, necessitating the connection of all individuals signalling states of circuit breakers and fuses to the protective relay. Additionally, there is a requirement for remote monitoring capabilities through dispatching. Consequently, the use of the same protective relays as in previous cases is not feasible, as the protective relay must comply with secure protection protocols in addition to the required protective functions.

Fig.4. Schematic representation of a protective system for sources from 50 kW to 110 kW connected to a LV distribution grid

One of the most widely deployed relays in Europe in recent years is the SEL-751 digital relay, typically installed alongside the RTAC-3505 device for dispatching needs. For microgrid applications, a similar combination will be required to protect the LV level. An issue arises with the overcurrent function when the microgrid transitions from grid-connected operation to islanded operation. If the microgrid relies solely on sources with inverters, utilizing the overcurrent function becomes considerably challenging. This is since the contribution of inverters amounts to a maximum of approximately 120% of the inverter’s nominal current, sustained for a maximum of only 5 seconds [10], [11].

To address this challenge, digital protection must detect the state of control elements to adjust the settings to a more sensitive level, ensuring grid safety. However, implementing this concept in practice for fault location poses difficulties. Increasing the sensitivity of the protection may result in minimal differentiation between fault current (the starting current of the protection) and normal current or the starting current of motors in industrial areas [12].

Currently, VSD does not consider the use of local small sources during a black start due to the necessity to monitor the grid frequency for inverters during synchronization with the grid. Consequently, small renewable energy sources (RES) are automatically connected only after 300 seconds from the restoration of power by the grid [13].

Table 3. The required settings of the external gird protection according to the VSD for a power range: 100kW≤ PN≤5MW for LV grid [9]

.

Table 4. The required settings of the external gird protection according to the VSD for a power range: 100kW≤ PN≤5MW for MV grid [9]

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The comparison between Table 3. and Table 4. sheds light on the nuanced considerations required in configuring external grid protection systems. In Table 3., we find the standard settings designated for power sources ranging from 100 kW to 5 MW when integrated into the LV grid. Conversely, Table 4. offers a glimpse into settings tailored for the same power range but intended for connection to the MV grid. While exploring this comparison, it becomes evident that deviations emerge, particularly concerning the trip time setting for voltage drop or rise at the first level, as evident when comparing Table 2. and Table 3.. However, despite these discrepancies, it’s noteworthy that the remaining settings largely align between the two tables.

Moreover, the method of connection to the grid and the specific voltage level play pivotal roles in determining the appropriate settings. This becomes particularly evident when analysing the settings for indirect measurement from Table 4., where we observe identical configurations, albeit specifically designed for the secondary side measurement. Consequently, these voltage values demonstrate a notable reduction, as visually depicted in Fig. 4.

This comprehensive comparison underscores the critical importance of considering grid connection specifics and voltage levels when configuring external grid protection systems [14]. The observed discrepancies not only highlight the need for meticulous attention to detail but also underscore the necessity for tailored approaches based on the unique characteristics of the grid. By implementing customized settings that account for these nuances, it becomes possible to ensure optimal grid safety and functionality, thereby mitigating risks and enhancing overall system reliability.

Design of a Protection Relay

Currently, there is a lack of universal relays on the market that would be able to meet strict criteria for various options of connecting renewable energy sources (RES) to the distribution grid. With the future deployment of microgrids and smart grids in mind, having such universal devices becomes a crucial necessity.

These systems will need to accommodate various grid topologies, diverse characteristics of RES, and their potential impact on the operation of distribution grids. As microgrids and smart grids increasingly rely on RES, it is essential to have reliable and flexible relays capable of effectively managing and protecting these new energy systems. From the needs described in the previous chapter, it is evident that the device must provide only a few inputs and outputs.

At the same time, it is important for it to have integrated cybernetic security function in the form of Anti-Malware technology, ensuring an elevated level of security. Such a device should include a comprehensive set of security features for user access, configuration management, and monitoring. This will ensure that the system is protected against potential cyber threats and capable of maintaining the integrity and reliability of its operating environment. Each output channel is equipped with both normally open and normally closed contacts, providing both switching and break functions for enhanced versatility. This design feature ensures compatibility with a wide range of devices and systems, allowing users to adapt the device to different scenarios and operational needs easily.

The proposed device, as depicted in Fig. 5, is indeed equipped with a diverse array of communication inputs, offering enhanced flexibility and choices for the user. The USB input facilitates local configuration, permitting users to conveniently adjust settings directly on the device. Moreover, this USB input can also be linked to the internet via an RJ-45 connector, enabling remote access and configuration of the device. Additionally, there exists a communication port tailored for connecting an intelligent meter using standardized RS-232 serial communication, ensuring compatibility with both present and forthcoming systems.

Fig.5. Design of a new device for protecting RES in Distribution grid

Another notable benefit is the inclusion of HMI (HumanMachine Interface) access, which facilitates local control, settings adjustment, and device monitoring. This feature significantly improves user experience and management efficiency. Overall, this solution furnishes a comprehensive and adaptable platform for the management and safeguarding of renewable energy sources.

Further, the device is equipped with two output options, namely OUT1 and OUT2. These output channels provide versatility in connecting and controlling external devices or systems based on specific operational requirements. The availability of multiple output channels enhances the device’s utility and compatibility with various applications, offering users greater flexibility in configuring and managing their renewable energy systems. Each output channel is equipped with both normally open and normally closed contacts, providing both switching and break functions for enhanced versatility. This design feature ensures compatibility with a wide range of devices and systems, allowing users to adapt the device to different scenarios and operational needs easily.

The device evaluates input and output contacts and monitors them based on the measured input data for voltage input contacts L1, L2, L3, and N. Current inputs can be connected to I1, I2, I3, and COM. This configuration allows for comprehensive monitoring and control of the electrical parameters, ensuring efficient operation and protection of the connected renewable energy system. Of course, for a more robust system, input contacts for monitoring the status of individual protective devices will be necessary, which the device will provide in this case. There are up to eight input contacts available, labelled as IN1 to IN8, through which the status of various elements requiring attention from distribution companies when connecting larger power capacities can be detected. These input contacts enable comprehensive monitoring and control, enhancing the safety and efficiency of power distribution operations.

Conclusion

The design of a protection system for distributed energy sources in distribution grids is crucial for ensuring the reliability and safety of electricity supply, especially with the increasing integration of renewable energy sources (RES) and the emergence of microgrids and smart grids.

Addressing the challenges associated with protecting RES requires innovative solutions that cater to various grid topologies, RES characteristics, and operational needs. The proposed device offers a versatile platform equipped with advanced communication inputs, local and remote configuration capabilities, and comprehensive monitoring features.

With the inclusion of HMI access and multiple output options, the device enhances user experience and management efficiency while providing flexibility in connecting and controlling external devices. Additionally, the integration of cybernetic security features ensures the integrity and reliability of the system in the face of potential cyber threats.

Furthermore, the device’s ability to evaluate input and output contacts based on measured data enables efficient operation and protection of connected renewable energy systems. The provision of input contacts for monitoring the status of protective devices enhances safety and efficiency in power distribution operations. In conclusion, the design of a protection system for distributed energy sources in distribution grids marks a pivotal advancement in the realm of electrical grid infrastructure. As the energy landscape undergoes rapid transformation with the integration of renewable energy sources and the proliferation of microgrids and smart grids, the need for robust and adaptable protection systems becomes increasingly pronounced.

The proposed device embodies a holistic approach to addressing the multifaceted challenges posed by these developments. Its versatile architecture, encompassing a diverse array of communication inputs, local and remote configuration capabilities, and comprehensive monitoring features, positions it as a cornerstone in the transition towards a more sustainable and resilient energy ecosystem.

Moreover, the integration of cybernetic security functions underscores a proactive stance towards safeguarding critical infrastructure against emerging cyber threats, ensuring the integrity and reliability of energy distribution networks. This emphasis on security aligns with contemporary imperatives for fortifying infrastructure resilience in the face of evolving digital risks.

Furthermore, the device’s capability to evaluate input and output contacts based on measured data empowers operators with actionable insights for optimizing system performance and mitigating potential risks. By providing a seamless interface for monitoring and controlling renewable energy systems, it enhances operational efficiency and facilitates proactive maintenance strategies.

The inclusion of input contacts for monitoring the status of protective devices further enhances the device’s utility in ensuring grid reliability and resilience. This comprehensive approach to protection system design reflects a commitment to addressing the evolving needs of distribution grids while embracing the principles of sustainability, efficiency, and reliability.

In essence, the design of this protection system represents not only a technological milestone but also a testament to the collective efforts towards building a more sustainable and secure energy future. As we navigate the complexities of modern energy systems, innovations such as this serve as catalysts for progress, ushering in an era of energy resilience and sustainability for generations to come.

Acknowledgments: This work was supported by the Slovak Research and Development Agency under the contract No. APVV-21- 0312 and the Ministry of Education, Science, Research and Sport of the Slovak Republic and the Slovak Academy of Sciences under the contract no. VEGA 1/0627/24.

REFERENCES

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[2] NAREJO G.B., ACHARYA B., SINGH R.S.S. and NEWAGY F., Microgrids Design, Challenges, and Prospects, 1. Edition, 2022, USA: CRC Press. pp. 1–314. ISBN: 978-1-0004-5746-9.
[3] LIU H., WANG H., ZHU S., et al., A Simulation-Based Method for Distribution Line Localized Protection Device Development, 2023 IEEE International Conference on Advanced Power System Automation and Protection (APAP), 2023, Xuchang, China, pp. 232–236, ISBN: 979-8-3503-0666-8.
[4] NOH J., CHAE W., KIM W., et al., A Study on Meshed Distribution System and Protection Coordination Using HILS System, 2022 13th International Conference on Information and Communication Technology Convergence (ICTC), 2022, Island, Republic of Korea, pp. 344–346, ISSN: 2162-1241.
[5] CHANDRAN R.L., ANJU PARVATHY V.S., ILANGO K., MANJULA G.N., Adaptive Over Current Relay Protection in a PV Penetrated Radial Distribution System With Fuzzy GA Optimisation, 2022 IEEE 19th India Council International Conference (INDICON), 2022, Kochi, India, pp. 1–7, ISBN: 978-1-6654-7350-7.
[6] LIANG W., ZHAO Y., LIU B., WANG Y., Research on Distributed Photovoltaic Low Voltage Ride Through Control Strategy Considering Distribution Network Protection, 2023 3rd International Conference on Electrical Engineering and Mechatronics Technology (ICEEMT), 2023, Nanjing, China, pp. 550–555, ISBN: 979-8-3503-0369-8.
[7] CHAVES T.R., IZUMIDA MARTINS M.A., VINICIUS João D., et al., Study for the Application of Self Healing in the Overhead Low Voltage Distribution Grid, 2022 IEEE International Conference on Power Systems Technology (POWERCON), 2022, Kuala Lumpur, Malaysia, pp. 1–5, ISBN: 978-1-6654-1775-4.
[8] SAZANOV V.S., KOVALENKO A.I., VOLOSHIN A.A., et al., The Development of System for Automatic Adaptive Change of Relay Protection Settings in Distribution Networks, 2022 5th International Youth Scientific and Technical Conference on Relay Protection and Automation (RPA), 2022, Moscow, Russian Federation, pp. 1–15, ISBN: 979-8-3503-9991-2.
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[11] DIAHOVCHENKO I., YEVTUSHENKO I., KOLCUN M., et. al., Demand-Supply Balancing in Energy Systems with High Photovoltaic Penetration, using Flexibility of Nuclear Power Plants, 20 (2023), No. 11, Acta Polytechnica Hungarica, pp. 115–135, ISSN: 1785-8860.
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[14] Vojtek M., MASTNÝ P., MORAVEK J., et. al., Recent Challenges Regarding the Verification of Photovoltaic Inverters Properties and their Compliance with Technical Requirements, 20 (2023), No. 11, Acta Polytechnica Hungarica, pp. 63–82, ISSN 1785-8860.

Authors: Ing. Róbert Štefko, PhD., Technical University of Košice, Department of Electric Power Engineering, st. Mäsiarska 74, 040 01 Košice, E-mail: robert.stefko@tuke.sk; Dr. h.c. prof. Ing. Michal Kolcun, PhD., Technical University of Košice, Department of Electric Power Engineering, st. Mäsiarska 74, 040 01 Košice, E-mail: michal.kolcun@tuke.sk; Ing. Marek Bobček, Technical University of Košice, Department of Electric Power Engineering, st. Mäsiarska 74, 040 01 Košice, Email: marek.bobcek@tuke.sk; prof. Ing. Damian Mazur, PhD., Rzeszow University of Technology, Department of Electrical Engineering and Fundamentals of Computer Science, st. Powstańców Warszawy 12 35-959, Rzeszów, E-mail: mazur@prz.edu.pl. Ing. Bogdan Kwiatkowski, PhD., Rzeszow University of Technology, Department of Electrical Engineering and Fundamentals of Computer Science, st. Powstańców Warszawy 12 35-959, Rzeszów, E-mail: b.kwiatkowsk@prz.edu.pl.

Source & Publisher Item Identifier: PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 100 NR 9/2024. doi:10.15199/48.2024.09.53

Data Center Commissioning Case Study

Published by Dranetz Technologies, Inc. Website: Dranetz.com 

Most high reliability facilities have a significant investment in UPS systems, generators and other mitigation devices in order to prevent electrical supply problems from impacting their business. However, these mitigation devices and related equipment are complex electro-mechanical systems that are themselves susceptible to failure and often do not provide any alarms or notifications when not functioning up to manufacturers specifications. That’s where continuous power monitoring comes in.

Power Quality monitoring systems continually evaluate the health of the electrical supply at key locations within a facility including the utility supply, generators, UPS input and outputs and other critical distribution points and load. These systems have been proven to prevent problems from occurring by proactively detecting anomalies in the electrical supply before they escalate into system failures. These systems are invaluable for troubleshooting failures should they occur as well as monitoring demand, energy and environmental parameters like temperature and humidity.

The ideal time to install any electrical equipment, including power monitoring equipment, is during the initial construction phase. An often overlooked benefit of these monitoring systems is they can be an extremely valuable asset that can be used during site commissioning. During this phase the entire facility is put through its paces with each element being thoroughly tested to validate the design, see if equipment is operating to manufactures/designers specifications and that it is compatible with the overall facility. Power monitoring systems can provide significant added value not only by recording and documenting the successful commissioning of a facility but also in identifying and resolving any system failures that occur at this critical phase.

A large worldwide cable television and media company recently constructed and commissioned a state-of-the art data center and production facility. During construction, Dranetz’s Encore Series System, a permanently installed power quality monitoring system was installed to monitor 25 key locations within the data center. Monitored locations include each utility feed, generators, inputs and outputs of each UPS and critical PDU’s downstream from the UPS. Encore Series was chosen for many reasons including state-of-the-art power quality capabilities, ease of use, web browser interface and cost vs. the competition.

Wanting to take full advantage of its benefits, Encore Series was an integral part of site commissioning with recorded data continually being evaluated and compared to expected results. Among many items, the commissioning procedures included tests to evaluate the source transfer from utility (one of two utility supplies) to generators then back to utility. Unlike other test performed, this transfer test failed multiple times with the facility remaining dark and the test uncompleted as failures were detected prior to completion. Between tests one line diagrams were reviewed and compared to the actual build out in order to verify proper equipment installation and construction in attempts to locate the source of the problem. This evaluation indicated several related breakers were either tripped or in the wrong position. The final test attempted proved much more serious with a complete failure of a utility breaker which exhibited visual damage and a smoke odor.

Being commissioned prior to start of site acceptance testing Encore Series data was reviewed for forensic evidence of this failure. The monitoring system design was such that critical locations important to this test were instrumented providing extremely valuable data which resulted in the quick diagnosis of this problem. Each generator bus (Generator 1, Generator 2) and utility feed (Utility 1, Utility 2) was monitored and waveshapes recorded at locations Generator 1 and Utility 2 at the time of the last test that resulted in the breaker failure.

A close inspection of the current waveforms recorded at both Generator 1 (3000A bus) and Utility 2 (4000A bus) locations provided a key indicator of the source of the problem. Current measurements at each location were many times higher than the rated bus capacity. In fact, current waveshapes on all phases were clipped indicating a saturation of current transformers (CT’s) as a result of currents well in excess of their specifications.

Fig.1. Generator 1 (3000A bus)

Fig.2. Utility 2 (4000A bus)

The data above quickly led the team to closely review the sequence of events leading up to, and resulting from the failure at these locations. As suspected, Generator 1 and Utility 2 buses were connected together as shown in the diagram below at the time of failure. Being out of phase the resultant current draw on the system caused the related breakers to trip and ultimately led to the failure of the Generator 1 breaker. Further investigation indicated a sequencing problem in the programmable logic controller (PLC) allowing the Generator 1 and Utility 2 breakers to be closed at the same time. A programming error in the PLC was determined to be the ultimate source of the problem. The programming error was corrected, the failed breaker repaired and the tests were then successfully performed.

Source URL: https://www.dranetz.com/technical-support-request/case-studies/data-center-commissioning-case-study/

Overvoltage on the High and Low Side Electrical Network Voltage 35 kV When Appearing and Disconnecting Short Circuits of Various Forms at Its High Voltage Part

Published by Nahid MUFIDZADA1, Gulgaz ISMAYILOVA2, Azerbaijan State Oil and Industry University ORCID: 1. 0000-0003-4063-2128, 2. 0000-0003-0063-2020

Abstract. Overvoltage is explored on the 35, 10 and 6 kV sides of the electrical network where various characters short circuit occur on its highvoltage part. It has been revealed that the overvoltage which occurs during a short circuit has the highest values if the short circuit is single-phase, as expected. However, disconnecting of all types of short circuits results in higher, overvoltage because the network operates with an isolated neutral and a short circuit. Even when a short circuit occurs on the high voltage (HV) side of the transformer, it does not completely de-energize it. Breakdown occurs at such high currents that they cause excessive voltages. Protection against such high overvoltage can be provided by installing surge arresters at the inputs of 35 kV transformers.

Streszczenie. Przepięcia badane są po stronach sieci elektrycznej 35, 10 i 6 kV, gdzie w części wysokonapięciowej występują zwarcia o różnym charakterze. Stwierdzono, że przepięcie powstające podczas zwarcia ma największe wartości, jeśli zgodnie z oczekiwaniami zwarcie jest jednofazowe. Jednak odłączenie wszelkiego rodzaju zwarć powoduje wyższe przepięcia, ponieważ sieć działa z izolowanym punktem neutralnym i występuje zwarcie. Nawet jeśli zwarcie wystąpi po stronie wysokiego napięcia (HV) transformatora, nie powoduje to całkowitego odłączenia go od zasilania. Awaria następuje przy tak dużych prądach, że powodują one nadmierne napięcia. Ochronę przed tak dużymi przepięciami można zapewnić instalując ograniczniki przepięć na wejściach transformatorów 35 kV. (Przepięcie na stronie górnej i dolnej sieci elektrycznej Napięcie 35 kV Przy powstawaniu i rozłączaniu zwarć różnego rodzaju w części wysokiego napięcia)

Keywords: Overvoltage, short circuits, surge suppressors, switches with shunt resistance.
Słowa kluczowe: Przepięcia, zwarcia, zabezpieczenia przeciwprzepięciowe, wyłączniki z bocznikiem

Introduction

Electrical networks of 35 kV belong to distribution networks and operate with an isolated neutral. These networks are the most widespread and extensive, therefore more susceptible to abnormal and emergency conditions. The reliability of 6-35 kV networks determines the uninterrupted power supply to consumers. Emergency modes in these networks occur mainly during short circuits, which lead to an increase in either currents or voltages to high values, depending on the type of short circuit and the operating mode of their neutrals. Disabling a short circuit also leads to high overvoltage, in this case the magnetic energy of the cutting current is converted into electrical energy and increases the voltage. Consequently, the greater the breakdown current, the more overvoltage is created in the network. It is known that switches disconnect the short-circuit part of the network when the current in the switch passes through its zero value or close to this value. It should be noted here that when turning off and on, the switches of three phases operate simultaneously, while the currents of the three phases shifted relative to each other by 2π/3 degrees, do not simultaneously pass through their zero value, therefore, the switches of healthy phases operate at the moment when the currents in these phases have sufficiently large values, i.e. large currents are interrupted, and such current interruptions can cause large overvoltage as stated above [1-7].

With asymmetrical short circuits, the highest overvoltages are observed in healthy phases. On the damaged phase, overvoltage is also observed. These overvoltages that arise mainly depend on the instantaneous value and rate of change of the current in the switch at the moment of its break, on the instantaneous value of the voltages in the phases and the parameters of the circuit [3].

Problem setting

The question of what overvoltages can result from the interruption of large currents have quite great interest. This article is devoted to the consideration of this issue, as well as the transfer of such overvoltages to the secondary side of transformers, i.e. overvoltage on 10 kV and 6 kV bus systems when large currents break on the 35 kV side. The article examines a part of the electrical network in which there are three substations and two lines.

The first substation is a supply substation (SSub/S) with a voltage of 220/35 kV, the second (S/S-1) – 35/10 kV and the third (S/S -2) – 35/6 kV. To protect against overvoltages, surge arresters are installed in 35 kV bus systems. On the 10 kV and 6 kV sides there are corresponding loads S1, S2 – Fig. 1.

Fig.1. Diagram of the electrical network under study
Solution of problems

Various forms of short circuits – one-phase, two-phase, two-phase to ground and three-phase – were performed alternately in the gap between the transformer T1 and the switches in the substation S/S-1. The results obtained are shown in Table1, as well as in Fig. 2 – 4.

Fig.2. Overvoltages in bus systems of 35 kV substation S/S-1 when a single-phase short circuit occurs and switches off.
Fig.3. Overvoltage on the LV side of transformer T1 at occurrence and disconnection of a two-phase short circuit to ground
Fig.4. Voltage at the inputs of transformer T1 when and disconnecting three-phase short circuit.

Table 1 shows the amplitude values of the currents in the first and second lines, the currents on the primary side of transformers T1 and T2.

Table 1. Currents in lines 1 and 2, on the primary side of transformer T1 and capacitive currents of lines 1 and 2

.

In normal operation of the network, the currents in the first and second lines are equal to 400 A and 135 A, respectively, the current in the branch of transformer T1 is 265 A, and the capacitive currents of the primary and secondary lines are 0.8 A and 0.5 A, respectively. the phase voltage values in this mode are equal – at the beginning of the first line 29.32 kV, at the beginning of the second line – 27.35 kV and the end of the second line – 26.23 kV. A, the amplitude values of the phase voltages on the 10 kV and 6 kV sides are respectively equal to 7.48 kV and 4.37 kV (see Table). All these defined values correspond to their real values during normal operation of the network in question.

In the work, it was assumed that all of the above types of short circuits occurred at the moment the voltage of phase A at the short circuit point passed through its amplitude value.

With a single-phase short circuit, there is a slight increase in the phase A current (from a value of 266 A to a value of 369 A) in the branch of transformer T1 in the S/S-1, and in phases B and C there is practically no change in currents. Changes in the current values of lines 1 and 2 are small. The current passing into the ground from the short circuit point is 164 A. This current is closed through the line capacitances, which increase to 46 A.

A single-phase short circuit leads to an increase in voltage in healthy phases. As can be seen from table. 2, at the inputs of transformer T1 in phases B and C, the voltages increase by 2.4 times. Increase in voltage at the end of line 2, i.e. on the high voltage side (HV) of transformer T2 is slightly larger – 2.7 times, due to the superposition of high-frequency voltage fluctuations created on this line. Consideration of changes in voltages and currents at the beginning of the first line and at the end of the second line (in transformer T2) is aimed at determining the influence of a fault occurring in the S/S-1 substation on these values at these specified points, which are located several kilometers from the fault point.

Of interest is the transmission of such overvoltages to the 10 kV and 6 kV sides. On these sides, there is an increase in voltage in the damaged phase by more than 1.7 times, since the current of this phase in the high-voltage part has a slightly larger change. In healthy phases there is practically no increase in voltage.

With a two-phase short circuit to ground (in phases A and B), the currents in the branch of transformer T1 increase by 7 times. The voltage in the bus systems of substation S/S-1 (at the HV inputs of transformer T1) in damaged phases drops to zero, and in the healthy phase increases from a value of 27.32 kV to a value of 42.45 kV, i.e. 1.6 times. In the bus systems of the S/S-2 substation, in phase A the voltage practically does not change, in phase B it decreases by 1.5 times, and in phase C it increases by the same amount (according to the current values of these phases at the time of the short circuit). On the low side of transformer T1 in phases A and B, the voltages are reduced by half, since the short circuit is located in these phases on the high voltage side, therefore, in the high-voltage winding there are practically no currents in these phases, therefore, in the magnetic circuit, half of the magnetic flux of the current of phase C is closed through the rod of phase A, and the other half through the rod of phase B, which leads to a halving of the secondary voltage in these phases. In phase C, the secondary voltage does not change. There is no change in voltage on the low side of transformer T2 (see Table 1).

When a two-phase fault to ground is disconnected, the capacitive currents of the damaged phases of both lines increase greatly (up to 80 A). The current passing into the ground is 245 A (see Table 1).

In the HV bus systems of the S/S-1 substation, the voltage in all phases reaches quite high values, up to 91 kV, i.e. increase by 3.5 times and this is in the presence of surge arresters at this point – fig. 3.

The voltages in the damaged phases on the high side of transformer T1 remain equal to zero, and in the healthy phase they increase excessively (as in a single-phase short circuit), since the shutdown was performed at low values of the currents of the damaged phases and at this point in time the current of the healthy phase was quite large. And, also with an isolated neutral of the network, the high-voltage winding of transformer T1 is not completely de-energized during two phase short circuits. In the case under consideration, in the high-voltage windings of transformer T1, the currents of the damaged phases are almost 140 A, and the healthy phase is 280 A.

Consequently, the disruption of such large currents leads to excessively large overvoltages. Using two contact switches in this case also does not give a positive result. A decrease in overvoltage by 2–3 times is observed, but these values remain excessively high. Installing an arrester at the HV inputs of transformer T1 overcomes this problem. Moreover, these overvoltages do not exceed 99 kV, with a duration of several microseconds, as indicated in the calculations of a single-phase short circuit. In steady state, after a short circuit, the voltages in all three phases become zero [5].

Using two contact switches in this case does not give a positive result. In this case, overvoltages are reduced by 2– 3 times, but these values also remain excessively high. And, when installing an arrester at the HV inputs of transformer T1, these overvoltages are reduced to almost 99 kV, which exceeds their nominal value by 3.7 times, remaining acceptable for a voltage class of 35 kV. These overvoltages have a pulsed form with a duration of up to approximately 10 μs – Fig. 3. In steady state after disconnecting the short circuit, the voltages in all three phases become zero.

The secondary voltages of transformer T1 also increase when the two-phase short circuit is disconnected. In phases A and B, the voltages increase from 3.88 kV (at short circuit) to 9.48 kV, and in phase C from 7.85 to 18.96 kV. The curves of these overvoltages are shown in Fig. 4. In steady state, these voltages become zero.

Both in transformer T1 and in transformer T2, on the HV and LV sides, the voltages of phase A differ little from their nominal values, and the voltages of phases B and C exceed their nominal values by more than 3 times [6].

With a two-phase short circuit (also in phases A and B), the currents of the damaged phases in the branch of transformer T1 increase greatly (almost 11 times), and the change in the current of phase C is small (100 A). The short-circuit current is 2940 A. The voltage in the HV bus systems of the S/S-1 substation in the damaged phases drops from a value of 27.32 kV to a value of 15 kV and does not change in the healthy phase. The voltage changes in the HV bus systems of substation S/S-2 are the same. The voltage on the secondary side of transformers T1 and T2, in phases A and B, is reduced by half, and in phase C remains unchanged (as with a two-phase ground fault). But disconnecting such a short circuit greatly changes all the voltages in the circuit under consideration. Voltages in all phases of the 35 kV bus system of substation S/S-1 increase three times, and in the high voltage bus systems of substation S/S-2 such an increase in voltage occurs only in phases B and C. In phase A the voltage increase is small. Disabling a two-phase fault, as well as disconnecting a single-phase fault and a two-phase fault to ground, leads to excessively large overvoltage values on the primary and secondary sides of transformer T1. In the presence of surge arresters on the HV waters of transformer T1, these overvoltages are reduced on this side to 99 kV and on the LV side to 19 kV in phases A and B, and 38 kV in phase C. As can be seen, 38 kV is 5 times the nominal value of this voltage, which is quite high. On the secondary side of transformer T2, the voltages in phases B and C increase by approximately 3.5 times, and the voltage in phase A changes little. In steady state after a short circuit, the secondary voltages T1 are equal to zero, and T2 are equal to their nominal values.

Of course, a three-phase fault (and a three-phase fault to ground) does not create overvoltages, but disconnecting this type of fault leads to fairly high values of overvoltages, since the currents of a three-phase fault have the highest values compared to currents in other types of faults. In the case under consideration, the three-phase short circuit currents reach 3450 A, exceeding the rated currents by 13 times.

As can be seen from table 1, with a three-phase short circuit, in the HV bus systems of the S/S-1 substation, the voltages in all three phases drop to zero. In the HV bus systems of the S/S-2 substation, the voltage of phase A differs little from its nominal value, and the voltages of phases B and C are reduced by more than half their nominal values. This form of voltage change also occurs in the secondary winding of transformer T2. As for the secondary voltages of transformer T1, these voltages are zero, since on the high side of this transformer the voltages of all three phases are zero.

When a three-phase short circuit is disconnected, almost four times the rated voltage is set in the HV bus systems of substation S/S-1, and three times in the bus systems of substation S/S-2. The voltage at the short-circuited inputs of transformer T1 after disconnecting the short circuit increases from zero to 31.84 kV with a duration of approximately 0.1 s – Fig.4. The secondary voltages of transformer T1 are equal to zero, since the primary voltages of this transformer are equal to zero. And, the secondary voltages of transformer T2 increase significantly. The increase in phase A is approximately 2 times, in phase B – 4.3 times and in phase C 5 times. Note that with a three-phase fault to ground, due to the direct connection of the transformer T1 inputs to the ground, the voltage in them remains equal to zero when the fault is turned off [7].

Conclusions

1. Overvoltages occurring during a single-phase short circuit have higher values than overvoltages occurring during other types of short circuit. In the considered 35 kV network diagram, with a single-phase short circuit, the overvoltage factor reaches 2.4.

2. Disabling all types of asymmetrical short circuits leads to excessively high overvoltages, which have pulse forms with a very short duration.

3. When performing surge protection for 35 kV networks, one should also take into account the overvoltages that occur when disconnecting a short circuit, at which these overvoltages reach excessively high values. The use of two contact switches to interrupt faults reduces these overvoltages, but the reduced values also remain unacceptably high. Protection against such overvoltages can be achieved by installing surge arresters at the transformer inputs.

REFERENCES

[1] Florkowska B., Florkowski M., Zydroń P., Pomiary i analiza wyładowań niezupełnych w układach izolacyjnych wysokiego napięcia przy narażeniach eksploatacyjnych, Przegląd Elektrotechniczny, 2010, 4, 241-244.
[2] Florkowski M., Forkowska B., Rybak A., Zydron P., Migration effects at conductor / XLPE interface subjected to partial discharges at different electrical stresses, IEEE Trans. on Diel. and Electr. Insul., 2015, 22, 456 – 462.
[3] N.Mufidzade, G.Ismayilova, E.Huseynov. “Effect of line carnation on overvoltage in transformers of rated voltage 330 kV”. International Journal on “Technical and Physical Problems of Engineering” (IJTPE), Iss. 51, Vol. 14, № 2, Jun. 2022.
[4] A. Shimada, M. Sugimoto, H. Kudoh, K. Tamura, and T. Seguchi, “Degradation distribution in insulation materials of cables by accelerated thermal and radiation ageing,” IEEE Transactions on Dielectrics and Electrical Insulation 20, pp. 2107, 2013.
[5] A. Shimada, M. Sugimoto, H. Kudoh, K. Tamura, and T. Seguchi, “Degradation mechanisms of silicone rubber (SiR) by accelerated ageing for cables of nuclear power plant,” IEEE Transactions on Dielectrics and Electrical Insulation 21, pp.16, 2014..
[6] Kadomskaya K. P., Lavrov Yu. A., Reichertt A. Overvoltage in electrical networks for various purposes and protection against them. Novosibirsk, Publishing house of NSTU, 2004.
[7] F.Kh. Khalilov. Overvoltage classification. Internal overvoltage. Edition, Energy Training Center, St. Petersburg, 2013. 2. AC switches for voltages above 1000 V. General technical conditions. Instead of GOST-687-70 and GOST 687-67. Gos.com. USSR by standards. – M., 1979, 98 p

Source & Publisher Item Identifier: PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 100 NR 9/2024. doi:10.15199/48.2024.09.41

Power Quality & Energy Monitoring in Controlled Environment Agriculture: A New Jersey, USA Case Study

Published by Dranetz Technologies, Inc., Technical Documents – Application Note

SUMMARY

Controlled environment agriculture (CEA) relies on advanced technologies such as climate control systems, artificial lighting, and hydroponic or aeroponic growing systems. These systems, in turn, require stable, clean power. This Application Note outlines how a New Jersey-based indoor farming facility addressed persistent HVAC and VFD failures by installing a Camille Bauer PQ5000 permanent power quality and energy meter along with Dranetz master monitoring station. The meter and station setup provided insight into utility feed conditions, helped diagnose internal power events, and offered actionable data to prevent crop loss.

Indoor Cultivation Requires Reliable Power

CEA facilities typically aren’t simple greenhouses. Rather, they’re high-density industrial spaces that replicate ideal outdoor conditions, down to temperature, humidity, airflow, and CO₂ levels. And they must do it 24/7. Such a facility includes:

● High-intensity lighting systems
● HVAC systems tailored for tight humidity and temperature control
● Dehumidifiers and reheat coils
● Irrigation pumps
● CO₂ emitters
● Fans for air movement
● Automated environmental monitoring and controls

The Electrical Load Behind the CEA Facility

Keeping a CEA facility running often requires electrical engineering expertise as much as horticultural smarts. Lighting, HVAC, and environmental control systems often run on dedicated circuits and variable frequency drives (VFDs) to maintain efficiency. Many facilities also operate with year-round HVAC cycles, meaning cooling and dehumidification don’t stop, even in winter.

Key electrical demands include:

● Continuous operation of HVACD (Heating, Ventilation, Air Conditioning, Dehumidification) systems
● High wattage lighting (e.g., LED or HID systems)
● CO₂ delivery and sensor systems
● Centralized control systems and security monitoring

As a result, CEA facilities can be major utility customers. Energy usage can reach 16,000 kWh per day for mid-size operations.

Common Power Quality Challenges

With this level of electrical demand, it’s clear that power quality can directly impact yield, product quality, and profit margins. Even minor disturbances in power quality can disrupt operations. And that’s exactly what started happening at the New Jersey facility.

Power quality risks in CEA operations can include:

● Harmonic distortion: Caused by LED drivers and VFDs, leading to overheating and potential equipment failure.
● Voltage sag or drop: Especially during load start-up events.
● Power interruptions: Even brief outages can stress environmental control systems, leading to inconsistent grow conditions or system lockouts.
● Grid impact from load density: In regions where multiple, large energy consuming sites operate within the same utility zone, the collective demand can stress local distribution systems, causing grid instability and the potential for increased power outages.

These issues aren’t theoretical. At the NJ facility, the HVAC system and VFDs began failing unexpectedly, threatening their high-value crops. Without clean, consistent power, environmental parameters swung outside of acceptable ranges, forcing growers to discard product.

NJ Facility Overview
Figure 1. NJ CEA facility outdoor switchgear

This New Jersey CEA facility spans 58,000 square feet and is fed by a 480V, 8000A service, split into two 4000A services. The electrical infrastructure includes:

● Two 480V pad-mount transformers for utility power
● Outdoor switchgear
● Roof-mounted HVAC units and VFDs
● Complex lighting schedules with ~12-hour cycles
● Estimated 16,000 kWh of daily consumption

The size and complexity of the load created real vulnerability to power quality issues, especially at the utility service entrance.

Installation of the Camille Bauer PQ5000

To understand the root cause of HVAC and VFD issues, the facility team installed a PQ5000 permanent power quality monitor on one of the two 4000A service feeds. The unit was mounted with:

● Voltage disconnects
● CT shunt assembly
●Integration with a Dranetz Master Station for graphical user interface and remote monitoring via web interface

This setup allows facility engineers to:

● Continuously monitor utility feed conditions
● Capture waveform and RMS data in real time
● Proactively monitoring and analyze disturbances without waiting for failure
● Profile energy use by load and time of day

In the first two weeks of operation, the system captured normal operations and RMS startup events, confirming that load initiations weren’t to blame. The facility now has a clear baseline and is prepared to identify deviations before they lead to downtime.

Figure 2. Installed Camille Bauer PQ5000 unit
Why the PQ5000 Works for CEA Facilities

Here’s why PQ5000 is a strong fit for controlled environment facilities:

Continuous Monitoring

Power doesn’t fail on a schedule. The Camille Bauer PQ5000, coupled with the Dranetz Master Station, provides 24/7 data on:

● Voltage sags/swells
● Harmonics
● Frequency variations
● Energy utilization

Figure 3. The Dranetz Master Monitoring Station

Grid & Load Side Visibility

This setup helps separate utility-side events from internal equipment issues, a key need in determining where disturbances originate for fast resolution.

Fast, Actionable Insight

The system offers waveform capture and automated analysis. Site engineers don’t need to sift through raw data to understand what happened.

Energy Profiling

CEA facilities often operate on tight margins. The PQ5000 enables:

● Demand, kWh and other tracking
● Load pattern analysis
● Lighting schedule verification

Scalable & Future-Ready

As the NJ CEA site expands, a second PQ5000 will be added to the remaining 4000A feed. The system’s modular design and web interface support multi-site deployment and long-term scalability.

Adopting a Proactive Monitoring Approach

Power quality problems can be silent yield killers in indoor cultivation facilities. Failures in HVAC, VFDs, and other systems can damage crops before anyone notices.

By installing the PQ5000 and master monitoring station, this NJ facility moved from reacting to equipment failures to proactively monitoring the health of its electrical infrastructure. They experienced:

● Greater confidence in environmental control
● Better decision-making using power profile data
● Reduced risk of batch loss due to unknown power events

Figure 4. NJ CEA facility’s waveform summary
Ready to Get Ahead of Power Problems?

If you’re designing or running a CEA facility for high value crops, you will want to be as proactive as possible about PQ issues, like these NJ growers are. The Camille Bauer and Dranetz permanent PQ monitoring systems give you the insight to manage uptime and protect crop quality, and improve energy efficiency with data you can trust.

Visit dranetz.com/product/pq5000 to learn more or contact our team for help tailoring a monitoring plan to your facility.

Dranetz and Camille Bauer are GMC Instruments brands for power quality and energy management. GMC Instruments is a global leader in electrical measurement and testing technology. GMC Instruments Americas is the GMC Instruments sales and support center for the Americas for all GMC Instruments brands.

Website: Dranetz.com , Call 1-800-372-6832 (US and Canada) or +1-732-287-3680 (International)

Source URL: https://www.dranetz.com/wp-content/uploads/2026/01/Controlled-Environment-Agriculture-Application-Note-FINAL1.docx.pdf?mc_cid=19b1efb089&mc_eid=40400f25ee

A Hybrid Approach for Enhancing Grid Restoration

Published by Minaxi1, Sanju Saini2, Garima Tiwari3, Deenbandhu Chhotu Ram University of Science and Technology, Murthal ORCID: 1. 0000-0003-4172-725X; 2. 0000-0003-1390-4861; 3. 0000-0002-3004-0375

Abstract. Blackout restoration is crucial to energy security and infrastructure resilience. Black-start procedures must be used to restore a power grid methodically. Grid recovery requires selecting the correct unit black-start optimization methods. Each Dijkstra shortest path approach determines a unit’s optimum recovery route after a large power loss. A full indication includes unit capacity, climbing rate, beginning power, recovery time, and route recovery capacitance. An exhaustive index. This index facilitates unit startup. We end with a unit black-start strategy using the optimal recovery route, unit start sequence, and unit start limitations. This method works in the IEEE30 node system simulation. Research suggests the black-start method may boost unit recovery and success. Black-start strategy performance is assessed for two prominent graph-based algorithms, Dijkstra and A. Unit black-start analysis is assessed for Dijkstra and A algorithms. Priorities include start sequence and recovery path optimization. Grid recovery efficiency and efficacy depend on performance measures. Optimization, route length, and calculation time improve process dependability and efficiency. Dijkstra’s simple, reliable approach works well in certain situations. The heuristic A* algorithm works well in certain cases. Both strategies are used in this paper to improve system performance. Explaining the power system’s peculiarities comparatively allows for selecting an algorithm.

Streszczenie. Przywracanie po awarii ma kluczowe znaczenie dla bezpieczeństwa energetycznego i odporności infrastruktury. Procedury czarnego startu muszą być stosowane w celu metodycznego przywracania sieci energetycznej. Przywracanie sieci wymaga wybrania prawidłowych metod optymalizacji czarnego startu jednostki. Każde podejście Dijkstry do najkrótszej ścieżki określa optymalną trasę odzyskiwania jednostki po dużej utracie mocy. Pełne wskazanie obejmuje pojemność jednostki, szybkość wznoszenia, moc początkową, czas odzyskiwania i pojemność odzyskiwania trasy. Wyczerpujący indeks. Ten indeks ułatwia uruchamianie jednostki. Kończymy strategią czarnego startu jednostki, wykorzystując optymalną trasę odzyskiwania, sekwencję uruchamiania jednostki i ograniczenia uruchamiania jednostki. Ta metoda działa w symulacji systemu węzłów IEEE30. Badania sugerują, że metoda czarnego startu może zwiększyć odzyskiwanie i sukces jednostki. Wydajność strategii czarnego startu jest oceniana dla dwóch wybitnych algorytmów opartych na grafach, Dijkstry i A. Analiza czarnego startu jednostki jest oceniana dla algorytmów Dijkstry i A. Priorytety obejmują sekwencję uruchamiania i optymalizację ścieżki odzyskiwania. Efektywność i skuteczność odzyskiwania sieci zależą od miar wydajności. Optymalizacja, długość trasy i czas obliczeń poprawiają niezawodność i wydajność procesu. Proste, niezawodne podejście Dijkstry sprawdza się w pewnych sytuacjach. Heurystyczny algorytm A* sprawdza się w pewnych przypadkach. Obie strategie są używane w tym artykule w celu poprawy wydajności systemu. Wyjaśnienie osobliwości systemu energetycznego w sposób porównawczy pozwala na wybór algorytmu. (Hybrydowe podejście do poprawy odtwarzania sieci)

Keywords: Hybrid Algorithms, Grid Restoration, Black-Start Recovery, Resilience Strategy.
Słowa kluczowe: Algorytmy hybrydowe, przywracanie sieci, odzyskiwanie po czarnym starcie, strategia odporności

1. Introduction

Recently, extreme weather disasters, malfunctioning power equipment, and human mistakes have caused largescale blackouts in domestic and worldwide power networks [1], [2]. Some examples include the 2019 Argentina “6.16” blackout, which impacted the whole nation [3], the 2021 Texas “2.15” power outage, and the 2022 Taiwan “33” island-wide blackout, which caused considerable economic losses. The guarded grid must be prioritized and restored to safeguard key municipal infrastructure from catastrophic disasters and external damages. The restoration control method is complicated and time-consuming. Developing a logical unit recovery route search technique may boost risk resilience and grid recovery time, which has major research and engineering consequences. Unit-optimal recovery route management alone cannot speed up power loss recovery.

Restoring power after a blackout uses black-start power. These generators are called “self-starting generators” because they can start themselves and restore power without external power [4]. The method of “unit start-up” in power generating involves black-starting producing units that cannot start themselves after a large power loss [5]. This method allows units to be reactivated and power-generating again, enabling load recovery and network reinstatement. A unit start-up approach includes both the recovery route and the unit start-up procedure; therefore, the two options are usually interrelated [6].

Power grid management and restoration need the blackstart technique to handle a difficult energy infrastructure situation: a complete blackout or loss of electricity throughout an electrical system. After such an event, power restoration is urgent and complicated. Restoring power generation and energy delivery to end-users, industrial sectors, and vital infrastructure is the biggest challenge [7]. Electrical systems need black-start strategies to provide continuous power delivery even under challenging conditions. This is because these groups reduce the immediate effects of a power loss and maintain social stability. Actively studying and optimizing these strategies helps solve dynamic power grid issues. Current power systems are reliable, and several methods have been developed to keep them safe [8], [9]. Large traditional synchronous generating units have been replaced by smaller distributed generation (DG) units in power systems. Distributed generating units powered by intermittent renewable resources affect several system activities, including dispatch and commitment. The power system’s high renewable energy content, along with unexpected weather occurrences and human error, increases the risk of blackouts. A series of linked failures might cause major power outages [10], [11].

Power restoration after a blackout requires black-start power. Production of electricity units may start generating electricity on their own to repair the network without external power. This helps when the entire system blacks out [4]. This application defines “unit start-up” as power-generating units that cannot start independently after an extensive loss. A black-start power supply does this. This assistance helps them produce electricity again, establishing the groundwork for network restoration and electrical load recovery [12]. The sequence of starting a unit and its recovery path must be carefully considered when creating a start-up strategy. These options are interrelated inside the approach [13]. The power system restoration decision-making process has traditionally included milestone stages. One research [14] explored a unit start-up technique to reduce restoration time at each phase. The second research [15] employed sequencing and traversal approaches to determine unit startup order. This restored more non-black-start units quickly. A later study [16] examined the device’s capacity recovery. According to [17], unit start-up includes recovery route charging time in the first phase. In [18], the elements that affect the unit’s black-start recovery are covered in detail. Calculating the unit’s recovery path using the shortest route technique and reference [17]. Distant operation coverage factor, line operation length, and recovery probability are studied [19]. After developing the function that forecasts line commissioning time, the unit start-up priority index determines the start-up order. Dijkstra’s method optimizes unit recovery route introduction. According to the literature [20], start sequence selection is multi-conceptualized. A data envelopment analytic technique using a backtracking algorithm solves the later unit selection issue. Goals include reducing unit recovery time and improving recovery success. Black-start procedures are crucial for power grid management to restore electricity after a complete blackout or system failure. They are crucial to electrical system reliability and continuity.

Domestic and international professionals optimize generator-starting procedures. Unit start-up and milestone parts of a power system restoration process of selection were created to shorten restoration times at all levels [21]. The literature [15] used traversal and sequencing algorithms to find the unit start-up sequence that restored the most non-black-start units fastest. The literature [22] was also concerned with optimizing system-generating capacity within a certain timeframe. Recovery route charging time is considered in the unit’s start-up function [23]. Unit restoration accuracy during black-start and recovery routes are examined using K shortest path analysis [18]. The literature addresses line operation time, remote operation coverage, and line recovery [24]. Create a unit start-up preference index and line commencement time expectation function to determine start-up order. While waiting, Dijkstra’s algorithm optimizes the unit as the starter’s recovery path. The literature [25] states that a multi-constrained backpack problem is resolved using data envelopment analysis and a backtracking method to identify the next unit to commence.

This study aims to shorten the unit’s recovery time and speed up its recovery. Prioritizing a black-start technique that considers the unit’s recovery trajectory and reactivation process will achieve the goal. Mathematical models for black-start power units are established in this article. These models have source and non-black-start power. It then finds the best way to start units after a major power loss using Dijkstra’s and A*’s shortest route algorithms. Also included are unit capacity, climbing rate, and beginning power. A complete black-start plan considers the unit start sequence, optimal recovery path, and unit start constraints. Simulation verifies this method’s efficacy. The black-start unit was enabled initially while constructing the power system restoration method. For grid restoration, this device supplies initial electricity. After each target generator activation, a recovery plan is determined. It lists the black-start units that will recharge each non-black-start unit. This research will provide a unique contribution to power grid resilience and black-start strategy design. Assuring grid recovery reliability and efficiency via algorithmic selection is the goal.

The building of mathematical models for non-black-start power sources and black-start power units, including gas turbines, starts this study. In the second portion, Dijkstra’s shortest path approach is used to find the best recovery route for units that must be started after a large power loss. It then mixes the recovery route with the unit’s capabilities, climb rate, beginning power, and other specifications. By considering unit initiation limits, a thorough black-start approach is created. This method depends on initial unit sequence and restoration efficiency. This approach is proven via simulation. Electricity is originally supplied by the black-start unit to restart the grid. Next, black-start units charge each non-black-start unit to gradually start the target generators. So-called Power System Restoration Planning.

2. Modeling used for present work

A 30-bus IEEE test setup with Every source in [26] collects system data. This data includes generator, load, shunt capacitor, and transmission line cost and emission coefficients. To accommodate non-smooth fuel cost functions, ramp rate coefficients have somewhat adjusted IEEE-30 bus system cost coefficients. At 100 MVA, the data is expressed.

2.1 Unit Recovery Path Search Using Dijkstra

A popular method for determining the shortest route in weighted networks is Dijkstra’s algorithm. Already at the origin, this technique finds the shortest path by spreading outward till the final vertex. This method relies on breadth-first search [27]. Once the grid is separated as a topology diagram G = (V, E), where V represents the graph’s vertices and E represents its branches, its loads, generators, lines, and transformers are removed as undifferentiated nodes. Weighing the branches according to Equation (1) takes into account the line’s charging time, transformer operation time, and capacitance value to construct the weighted topology graph.

.

From nodes i to j, wij represents the branch weight. Line charging and transformer recovery periods are included in the normalized branch recovery time, tij. Normalized capacitance value cij represents the branch’s recovery success rate between nodes i and j, and equation (2) shows how the adjacency matrix A outlines the grid topology diagram’s connection link.

.

Node 1 is the black-start power node. Nodes 2–6 identify the unit to be started. Set VS = [1] contains the nodes that found the shortest route in the initial state. Vo = {2,3,4,5,6}, which includes all remaining nodes. Furthermore, D = [0,1,2,3, ∞, ∞] represents the appropriate distances between each node.

.

First, develop the adjacency matrix according to Equation (4). Node 2 is in set VS because set D shows it as the closest point to node 1. VS has [1,2], Vo has [3,4,5,6], and node 2’s shortest route is recorded.

Between the first and second nodes is 1 unit. According to the second row of the matrix of adjacency, node 2 is the intermediate node and seven distance separates nodes one to six. The initial specified D distance is greater than this figure. The distance set D now includes 0, 1, 2, 3, infinite, and 7. Set D finds node 3 closest to node 1, ignoring node 2. The quickest path to node 3 is documented by updating the VS and Vo lists to [1,2,3], [4,5,6]. The middleman is node 3. To alter D = [0,1,2,3,7,6], we add 7 and 6 from node 1 to nodes 5 and 6. Two units separate nodes 1–3. After refreshing VS = [1,2,3,4] and Vo = [5,6], node 4’s shortest route is collected. The revised D set places node 4 in Vo 3 distance from node 1. Nodes 1 and 5 are 7 distances apart because node 4 is the intermediate. The Vo node nearest to node 1 is node 6, 6 units away. We observe node 5’s shortest path and alter VS = [1,2,3,4,6] and Vo = [5]. As node 1 and node 6 are not directly connected, the quickest path from node 5 is quickly revealed. D comprises the shortest distances: [0, 1, 2, 3, 7, 6]. The process flow of pathfinding. Additionally, S is the shortest route matrix.

2.1.1. Integrated Index of Unit Start-Up Sequence

a) Index of Unit Characteristics

When selecting units to recover in order, use these criteria [28]:

1) Hot-start units are restored first to optimize hot-starting.
(2) When there is insufficient power to create electricity during system recovery, units with low starting powers are prioritized for a smooth start.
(3) For fast system recovery, units with faster-increasing rates are restored first.
(4) High-recovery units are prioritized to ensure power production capacity.

A unit characteristic index is calculated using unit capacity, climbing rate, and initial power in Equation (5).

.

The characteristic index of the kth unit is “O(k)”. “C(k)” is the normalized climb rate, “S(k)” is capacity, and “P(k)” is its beginning power. Normalization is shown in Equation (6).

.

Where, xmin, xmax, x* stand for the minimum, maximum, and normalized values of x, y, and x* respectively. This model has the following variables defined: the amount of time the device takes to start up, in seconds; tc; the moment it launches its power delivery and links to the grid; tmax, the duration of time it delivers its highest level of active power externally; K, the pace at which the unit is rising; Pst, the unit’s active power while using the plant as its power source; KN, the unit’s average climbing rate; Furthermore Pmax, the unit’s maximum active power.

.

The kth unit’s composite index is denoted by Z(k), its characteristic index is denoted by O(k), and its distance index is represented by D(k).

b) Restrictions on Unit Startup

The time constraint of a start-up:

.

The variable “tmax” represents the upper limit for the hot-start time of the unit, whereas “ts” provides the starting time of the non-black-start unit. It represents the maximum time the unit may be hot-started before failing. The unit must meet Equation (9) (minimum cold-start time) if its hot-start time exceeds it.

.

The variable “ts ” denotes the initial time of the non-black-start unit, while “tmin“ reflects the minimum time required for the non-black-start unit to reach its operating temperature.

c) Start-up power constraint

The following equation can be written as p is the system’s black-start unit count, The system’s restored non-black-start unit count is denoted by q,

.

the active power output from the ith black-start unit at time t is represented by Pi(t), the active power output from the jth non-black-start unit at time t is represented by Pj(t), and the start power needed to start the next unit is called Pst.

d) Constraints on the start/stop condition of the unit It is expected that once the unit has been started, it will continue to function without any further shutdowns. Therefore,

.

The variable Sk(t) represents the status of unit k at time t, where a value of 1 indicates that the unit has started and a value of 0 indicates the opposite.

e) Power constraints

.

where PGi denotes the generator set’s maximum active power output and Pmin denotes the lowest permitted active power output.

Gi denotes the generator set’s active power; PGi denotes the maximum permissible output of active power; QGi denotes the generator set’s reactive power; Qmin denotes the lowest permissible output of reactive power; Qmax denotes the maximum permissible output of reactive power; Li denotes the active power transmitted by the ith line; and Pmax denotes the maximum permissible power available.

f) Voltage constraints

The values of Umin, Umax, and Ui represent the lower and upper voltage limits, respectively, of the ith node, Ui being its magnitude of the voltage value.

.
2.1.2. Unit Start-Up Process The unit starts policy development.

Here’s how to start the unit. Analyze the grid’s topology and attributes. Transformers, lines, generators, and loads are branches and nodes. Weight branches by line capacitance, transformer working time, and line charging time. Weighted topology diagrams with adjacency matrix A outcome from this idea.

Dijkstra’s method is used to each non-black-start unit’s distance index to discover the unit’s recovery route’s shortest path. Look at the sequence of the units’ starts to determine which should be launched next, disregarding those with a black start. Examine power, voltage, hot-start time, and start power limits. Unqualified units are either placed at the start of the beginning sequence or through the cold start process until they fulfill the standards. Update the system’s recovery status while getting the fastest-starting units. A* (A star) is a popular algorithm used for pathfinding and optimization in various domains, including analyzing recovery paths and start sequences [29], [30]. A* is an informed search algorithm that combines the benefits of Dijkstra’s algorithm and heuristics to efficiently find the shortest path while exploring the graph [31], [32]. Here’s how A* can be applied to analyze recovery paths and start sequences:

2.1.3. Recovery Paths in a Network

In network management and fault recovery, A* can be used to find the most efficient recovery paths for restoring network connections after a failure. This involves finding a path that minimizes a specific cost while considering the network topology.

• Source Node: The point of network failure.
• Destination Node: The destination for rerouted traffic.

In both scenarios, A* is employed to efficiently find optimal paths or sequences by using heuristics to guide the search process. The choice of an appropriate heuristic can significantly impact the algorithm’s performance and accuracy in finding the optimal solution.

The aforementioned advantages make A* a powerful instrument for addressing a diverse array of issues that include the identification of the optimal route or solution inside a network or graph. The versatility, effectiveness, and assurance of optimality that it offers make it a preferred option for several applications.

2.2. Difference between Dijkstra’s and A* Algorithms

Dijkstra’s algorithm and A* (A-star) algorithm are two popular graph search algorithms used for finding the shortest path between two nodes in a graph. Here’s a tabular comparison of the main differences between these two algorithms:

Fig.1. Hybrid Dijkstra and A* Algorithm

Fig. 1 Hybrid Dijkstra and A* Algorithm 2.2.1. Unit Recovery Path Search Using Hybrid Dijkstra and A* The combination of Dijkstra’s algorithm and A* (A-star) algorithm for unit recovery path search is often referred to as the Hybrid Dijkstra-A* algorithm. Both Dijkstra’s and A* algorithms are popular pathfinding algorithms used in computer science and robotics for finding the shortest path between two points in a graph or grid. The hybrid nature of this algorithm comes into play by combining the results of Dijkstra’s and A. Instead of using A throughout the entire search, you can leverage the information obtained from Dijkstra to guide the search. During the A* search, if the algorithm encounters a node that has already been visited by Dijkstra’s and if the current path to that node is shorter than the path found by Dijkstra’s, you can update the information for that node using the shorter path. Fig 1 shows the Hybrid approach of restoring path. This way, the algorithm benefits from the efficiency of A* while incorporating the additional information provided by Dijkstra to improve the accuracy of the pathfinding.

3. Result Discussion

The result discussion serves as a A* (A-star) and Dijkstra’s algorithm are used in the hybrid method to route recovery in a system graph to maximize the shortest path search. Dijkstra’s method ensures that the shortest route is found by investigating every option, and A* employs heuristics to effectively direct the search. With g(n) standing for the cost from the start node, h(n) for the heuristic estimate to the objective, and f(n)=g(n)+h(n) for the total cost, the hybrid method preserves node information. The method updates costs and investigates neighbors while iteratively choosing nodes from a priority queue with the lowest f(n). This hybrid method effectively solves the route recovery problem in a system graph by balancing the effectiveness of A* with the dependability of Dijkstra’s.

3.1. Capacities and ON time of Each Node

Incorporating capacity values into the hybrid algorithm ensures that the path recovery process aligns with real-world resource constraints. The combination of Dijkstra’s and A* with capacity awareness leads to more efficient and practical solutions in complex network scenarios. Incorporating on-time values into the hybrid algorithm ensures that the path recovery process aligns with temporal dynamics. The combination of Dijkstra’s and A* with on-time awareness leads to more informed and adaptive pathfinding solutions in dynamic environments.

3.2. Comparison Graph

The comparison graph shows the different structures graphs and nodes explored in all three algorithms shown in figure 2 and table 1.

Table 1. Comparison of Algo with Nodes and Distances

.

Table 2. Comparison of Algo with Time

.
Fig.2. Comparison of Algo with Graphical wise

The first section compares the length of paths found by the hybrid algorithm, A, and potentially Dijkstra’s if included in the comparison. The second section compares the number of nodes explored during the pathfinding process by the hybrid algorithm, A, and Dijkstra’s. The table 2 and the time and nodes performances for each algorithm across different scenarios.

In each scenario, the hybrid algorithm provides better results, striking a balance between optimality (Dijkstra) and efficiency (A).

4. Conclusion and Future Scope

In conclusion, Dijkstra and A algorithms in black-start techniques and recovery route optimization provide grid resilience in a complex but realistic way. We improve power grid restoration efficiency, adaptability, and reliability by combining both methods, reducing downtime and strengthening the electrical infrastructure. The inclusion of cutting-edge algorithms will help our grids withstand unexpected obstacles as power system management advances and some future directions are:

1. Real-Time Data Integration
2. Quantum Computing Applications
3. Integrate cybersecurity measures into resilience plans
4. Optimize algorithms
5. Enhance Smart Grid Synergies
6. Incorporate adaptive control mechanisms into algorithms to modify performance and adaptability.
7. Community-Based Resilience Methods
8. Quantifiable Resilience measures
9. Inter-sector Integration

Future grid resilience directions strive to provide flexibility, efficiency, and security in the face of changing problems and technology.

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Source & Publisher Item Identifier: PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 100 NR 9/2024. doi:10.15199/48.2024.09.13

A New Approach for Load shedding Scheme

Published by Houria SMAIL1, Yassine BENSAFIA2, PaElectrical Engineering Department, Faculty of Sciences and Applied sciences, University of Bouira, 10000 – Algeria (1), PaElectrical Engineering Department, Faculty of Sciences and Applied sciences, University of Bouira, 10000 – Algeria (2), ORCID: 1. 0000-0001-8474-2009; 2. 0000-0003-1760-3636

Abstract. Depending on the power system condition in terms of operating reserves, and equipment availability, the severity of the disturbance may cause parts of the power system to be islanded, or to lose synchronism and enter a complete blackout. The aim of this paper is to design an automatic under frequency load shedding scheme which can be able to safeguard the power system against major disturbance involving multiple contingency events. The proposed load shedding scheme is tested on a real model of network. The simulations were performed on a dynamic model of the power system using the software package SICRE.

Streszczenie. W zależności od stanu systemu elektroenergetycznego pod względem rezerw operacyjnych i dostępności sprzętu, intensywność zakłócenia może spowodować wyspowe funkcjonowanie części systemu elektroenergetycznego lub utratę synchronizmu i całkowitą przerwę w dostawie prądu. Celem tego artykułu jest zaprojektowanie schematu automatycznego odciążania pod częstotliwością, który może zabezpieczyć system elektroenergetyczny przed poważnymi zakłóceniami obejmującymi wiele zdarzeń awaryjnych. Zaproponowany schemat odciążania testowany jest na rzeczywistym modelu sieci. Symulacje przeprowadzono na dynamicznym modelu systemu elektroenergetycznego z wykorzystaniem pakietu oprogramowania SICRE. (Nowe podejście do schematu zrzucania obciążenia)

Keywords: Shedding, defense, frequency, safeguard
Słowa kluczowe: obrona, częstotliwość, zabezpieczenie

Introduction Many studies have been implemented with the aim of power system reliability [1]. A Multi-agent method for service restoration in a complex shipboard power system [2], multi-functional flexible power conditioner [3], V2G (Vehicle to Grid) technology for power system balancing [4], network congestion assessment [5], and time-stamped synchronized measurements [6]. In [7], an algorithm for determining the polygonal and circular tripping characteristics of distance protection was presented. It was demonstrated that, the approach makes it possible to more effectively determine the protection settings that will ensure its correct functioning in an electrical power system.

When the system splits into islands due to a large disturbance, load shedding is the only possible protection. Disturbances that cause the islanding are, in most cases, a trip of a generating unit. The loss of a generating unit in such an island may represent a large percentage of an island’s generation and causes a rapid decline in the frequency. Under such conditions the primary regulation is not adequate, and so we have to use load shedding.

In order to prevent an unwanted frequency decline, we have to detect the under frequency condition and act properly. When the frequency drops to a pre-set limit the load-shedding must be triggered. The load-shedding is performed in several steps with a proper delay and with the correct amount of load being shed. The main purpose of load-shedding is to bring the frequency back to within acceptable limits.

In the first part of the paper we describe the methodology adopted for the design of settings of load shedding scheme, especially the number of load-shedding steps, the size of the load to be shed in each step and the frequency threshold.

In the second part of the paper we describe the considered data network used to test the performance of developed under frequency load shedding scheme.

The last part of the paper deals with simulations of the frequency response following the tripping of a major power plant. Simulations for different scenarios were performed on a dynamic model of the power system in isolated operation using the software package SICRE.

Methodology

In the process of determining the best under frequency load-shedding scheme, we consider the following criteria [8], [9]:

• Fmax: The value of the first threshold of the frequency is generally chosen on the basis of the network experience.

• Fmin: The minimum stage before islanding has to be sufficiently high to avoid that during the delay time of the relays the frequency does not reach the Islanding activation frequency.

Fig.1. Minimum stage before islanding

• ΔPmax: The amount of load to be shed for each stage has to face to the loss of an entire power plant of medium or large size.

• The number of stages.

.

Where Deficitmax is the maximum of load that do not cause reactive violations and over voltage on the HV level.

Deficitmax = 50% of the total load.

• The frequency threshold for each stage is calculated adopting the uniformity criterion:

.

• In order to avoid unexpected intervention of load shedding in occasion of electromechanical stable Frequency oscillations, the relay are set with a time delay of 0.1s.

Consider hypothesis

The model of the power system included all the high-voltage levels (60, 90, 150, 220 and 400kV). We assumed an isolated operation for the power system, as there is no need for underfrequency load shedding protection in an interconnected system.

The loads in the power system were modeled by a direct connection to the 60kV level, or to the 220kV, 90kV, 30kV level in some cases. The system loading corresponds to a typical winter day with peak demand.

The model of the system includes larger (1200MW) and medium (800MW) power plants which represent respectively 16% and 10% of the total generation. The data are given in the Table 1:

Table 1. Active and reactive power generation, loads and losses

.

The coefficients of the load model used in the study are given in the Table 2:

Table 2. Load components characteristics.

.

The load dependence on voltage and frequency are given by the following form [10]:

.

The settings of the turbine governor droop, used are: 5% for gas and steam power plants.

Dynamic simulations

Considering the abovementioned criteria, the settings of the proposed load shedding scheme are given as follow:

Table 3. Load shedding settings

.

In order to test the proposed under-frequency load shedding scheme we set up several simulating credible and extreme scenarios.

• Credible scenarios are aimed to test the performance of load shedding in case of the most probable events. The credible scenario selected (scenario1) is the loss of 26% of the total generation (2000MW).

• Extreme scenarios are aimed to test the performance of load shedding in case of events that causes the complete operation of the load shedding scheme (activation of all the stages of load shedding). The extreme scenario selected (scenario2) is the loss of 50% of the total generation (3840MW).

The results for each scenario are presented, respectively in Fig. 2 and Fig. 3.

In the first scenario, Fig. 2, the frequency drops to just under 49Hz. Therefore, 20% (1477MW/729MVAr) of the total load is shed and bring the frequency back above 49.7Hz.

Fig.2. System response for scenario1 ”loss of 2000MW”.

As can be seen in Fig. 3 (second scenario), the full extent of load-shedding is activated, shedding 50% (3692MW/1823MVAr) of the total load. The frequency drops to just under 48Hz, with a delay time of the relay sufficiently short to avoid that the frequency falling below the limits of 47.5Hz.

Fig.3. System response for scenario2 ”loss of 3840MW”.

The frequency stays above the limits and bringing back to within acceptable limits, so the scheme is considered successful. A schematic illustration of the amount of the load to be shed for different steps is shown in Fig.4.

Fig.4. Appropriate scheme for under frequency load-shedding

Conclusion

The aim of this paper was to design an automatic under frequency load shedding scheme which can be able to safeguard the power system against major disturbance involving multiple contingency events.

Using dynamic simulations of the power system to test the proposed load shedding scheme, the results showed that the scheme was able to prevent an intolerable frequency drop during exceptional events with a significant production deficit in the island.

REFERENCES

[1] Smail H., Alkama R., Medjdoub A., Optimal design of the electric connection of a wind farm, Energy, 165 (2018), 972-983
[2] Hengxuan L., Haishum S., Jinyu W., Wei Y., Qian W., A MultiAgent Based Method for Service Restoration in Shipboard Power System, Przegląd Elektrotechniczny, 88 (2012), nr 6, 354-359
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[6] Szewczyk M., Time synchronization for synchronous measurements in Electric Power Systems with reference to the IEEE C37.118TM Standard-selected tests and reommendations, Przegląd Elektrotechniczny, 91 (2015), nr 4, 144-148
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[8] Cignatta M., Salvetti M., Designing Defence Plans – Design Methodology. CESI, 2009.
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[10] MEDRING Project. Loads model in sicre and important parameters CESI, 2009.

Authors: Dr.Houria Smail, Bouira University 10000, Algeria, E-mail : h.smail@univ-bouira.dz ; Dr. Yassine Bensafia, Bouira University 10000, Algeria, E-mail : y.bensafia@univ-bouira.dz Or bensafiay@yahoo.fr (Corresponding author);

Source & Publisher Item Identifier: PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 100 NR 6/2024. doi:10.15199/48.2024.06.45

Analysis of Electrical Generators for Wind Electric Installations

Published by Aliashraf BAKHTIYAROV1, Gulshan ABDULLAYEVA2, Hamid PIRIYEV3, Azerbaijan State Oil and Industry University ORCID: 2. 0000-0003-0168-9623; 3. 0009-0000-2992-6358

Abstract. In today’s world, when the role of renewable energy sources is becoming increasingly important in the context of combating climate change and reducing dependence on fossil fuels, wind energy occupies a leading position. Wind turbines are becoming an increasingly common and sought-after source of clean energy, and the generator, as a key component of these systems, is becoming critical. Selecting the right generator for a wind installation is a complex process that requires careful analysis and evaluation of many factors. After all, the generator not only converts the kinetic energy of the wind into electrical energy, but also affects the efficiency of the entire system, its reliability and operating costs. This article discusses the main electrical generators that are used in wind electric installations. Block diagrams of wind turbines based on these generators are given. The advantages and disadvantages of these generators are given.

Streszczenie. W dzisiejszym świecie, gdy rola odnawialnych źródeł energii staje się coraz ważniejsza w kontekście przeciwdziałania zmianom klimatycznym i zmniejszania zależności od paliw kopalnych, energetyka wiatrowa zajmuje wiodącą pozycję. Turbiny wiatrowe stają się coraz bardziej powszechnym i poszukiwanym źródłem czystej energii, a generator, jako kluczowy element tych systemów, staje się krytyczny. Wybór odpowiedniego generatora do instalacji wiatrowej to złożony proces, który wymaga dokładnej analizy i oceny wielu czynników. Przecież generator nie tylko zamienia energię kinetyczną wiatru na energię elektryczną, ale także wpływa na wydajność całego systemu, jego niezawodność i koszty eksploatacji. W artykule omówiono główne generatory elektryczne stosowane w elektrowniach wiatrowych. Podano schematy blokowe turbin wiatrowych bazujących na tych generatorach. Podano zalety i wady tych generatorów. (Analiza generatorów elektrycznych dla instalacji wiatrowych)

Keywords: wind electric installation, generator, output voltage frequency, inverter, rotational speed, doubly-fed machine, converter
Słowa kluczowe: instalacja elektryczna wiatrowa, generator, częstotliwość napięcia wyjściowego, falownik, prędkość obrotowa

1.Introduction

Currently, a large number of designs of wind turbines are known. They are mainly classified by the location of the axis of rotation of the wind wheel, by the speed of rotation of the wind wheel, by the type of drive (direct drive or through a gearbox), by the presence of an orientation system or its absence. A significant number of design options for wind turbines makes it possible to achieve the most optimal use of wind energy in relation to each particular installation case. However, you need to understand that the wind is inherently unstable: its flow constantly changes direction and speed. Thus, wind turbines have to operate in a wide range of rotation speeds.

From the general theory of electrical machines it is well known that the rotation speed of the generator rotor directly affects the main characteristics of electricity. Thus, rotating at different speeds, the generator produces voltage with variable parameters in amplitude, frequency and phase. The main problem of wind energy is the need to convert electricity with variable parameters into electricity with standard parameters when the direction and intensity of the wind flow changes. The problem of eliminating instability of the wind flow direction is solved by using an orientation system for wind turbines with a horizontal axis of rotation and using wind turbines with a vertical axis of rotation that are insensitive to the direction of the wind.

To stabilize the frequency of the output voltage, two technical solutions are possible. The first option is a mechanical impact directly on the speed of rotation of the wind wheel, which is technically possible, for example, by changing the angle of attack of the blade. This method is called pitch regulation. The second option is the electrical conversion of non-standard energy into standard energy. This is technically realized by including electronic generator excitation control systems and electronic output energy stabilization systems in wind turbines. But it is necessary to understand that the composition and architecture of these electronic systems directly depends on the type of generating device included in the wind power plant. Accordingly, the most important issue when creating a wind turbine is the choice of generator type. When choosing a generator for a wind turbine, it is necessary to take into account the technical characteristics of the installation itself, such as its power, installation height, wind speed in a given region, as well as terrain features. Different types of generators have their own characteristics and advantages, which must be adapted to the specific conditions of the project.

Also an important factor is the economic component of choosing a generator. Installation and maintenance costs, as well as potential energy efficiency, must be carefully analyzed in order to make an informed choice that fits the project budget and provides the optimal cost-benefit ratio. In this study, we will look at various types of wind turbine generators, their features, advantages and disadvantages, and also analyze their applicability in various operating conditions. Our goal is to provide engineers, designers and developers with useful information to help them make the right generator selection and ensure efficient operation of wind power plants [1-5].

Fig.1. Wind turbine with a squirrel cage induction generator
2. Materials and methods

Of all types of electrical machines, traditionally there are several main types of generators that are used in wind turbines:

1) asynchronous generators
2) synchronous generators
3) two-speed asynchronous generator
4) asynchronized synchronous generator

Each type of generator has its own advantages and disadvantages. Therefore, we will consider each of them separately.

Asynchronous generator. These systems use squirrel cage asynchronous generators or induction generators that are directly connected to the network. The block diagram of a wind turbine based on an asynchronous generator is shown in Figure 1.

One of the disadvantages of this system is that the asynchronous generator does not have its own excitation source. Therefore, to operate, it needs to consume reactive power from the external network. Thus, when working directly with the network, this generator consumes reactive power from the network itself, which negatively affects such an important parameter as the network power factor (cos φ). To compensate for reactive power, as well as when operating in autonomous mode, wind turbines are equipped with capacitor banks, but they are quite expensive and unreliable. The second disadvantage is that the asynchronous generator operates only in certain winds, which ensure that the rotor speed exceeds the speed of rotation of the machine’s magnetic field. Asynchronous generators or induction generators with a wound rotor are also used (fig. 2), since the influence on the rotor circuit allows you to change the amount of slip [6-10].

Fig.2. Wind turbine with a wound rotor induction generator

In this case, it is possible to operate in wider speed ranges. In Europe, this system was adopted as the basis for wind generators of low and medium power, but these disadvantages relate to the nature of the electric machine itself, which does not allow intensive development of this direction.

Synchronous generator. From the very beginning of the development of wind energy, the three-phase synchronous generator has been considered as one of the main types of generators. Its designs are available with electromagnetic excitation or permanent magnets. This allows you to achieve good weight and size characteristics. The main problem with this type of electric generators is that in order to generate alternating current of certain parameters it is necessary to maintain a constant rotor speed. In the case of electromagnetic excitation, it is possible to maintain the amplitude of the generated excitation in a certain interval by changing the excitation, which is regulated by the current of the excitation winding. However, to maintain a certain voltage frequency when the rotation speed changes, it is necessary to use additional devices. The block diagram of a wind turbine based on a synchronous generator is shown in Figure 3.

As can be seen from the diagram, this wind turbine, in addition to the turbine and the generator itself, includes an electronic frequency converter. This converter initially rectifies the generated voltage, and then inverts it into alternating voltage with the specified parameters. This type of wind generators is currently quite widely used in wind turbines of various capacities. However, in high-power wind turbines, synchronous generators are rarely used due to the limited capabilities of power electronics. In addition, a large number of conversion stages leads to a decrease in the overall efficiency of the generating system.

Fig.3. The block diagram of a wind turbine based on a synchronous generator

Two-speed asynchronous generator. A two-speed asynchronous generator is a generator that can operate at two different rotor speeds. This type of generator is especially useful in wind turbines, where the rotation speed of the wind wheel can vary significantly depending on the intensity of the wind. To ensure efficient operation of the generator at different rotor speeds, a system of two independent windings is used.

Advantages of using a two-speed asynchronous generator in wind energy:

1. Increased energy efficiency: The two-speed asynchronous generator allows you to increase the energy efficiency of a wind turbine by more efficiently using wind energy at different speeds.

2. Reduce control system costs: Since the two-speed asynchronous generator can independently adjust the rotor speed depending on the wind speed, it can reduce the need for expensive control systems.

3. Increased reliability: The use of a two-speed asynchronous generator can increase the reliability of a wind turbine by reducing the load on the equipment under variable wind speeds.

Technical aspects of the use of two-speed asynchronous generator (TSAG) in wind turbines:

1. Design and integration: The use of TSAG requires specialized design and integration into the wind turbine design. This includes developing the optimal control system, adapting the transmission and selecting the optimal generator configuration.

2. Rotation speed control: To ensure optimal operation of a wind turbine, it is necessary to develop a control system that can effectively adjust the rotor speed in accordance with changes in wind speed.

3. Grid integration: TSAG must be integrated into the existing electrical network with minimal losses and surge currents. This requires matching the generator parameters with the network parameters and using specialized devices for synchronization and protection [11-15].

Asynchronized synchronous generator or doubly-fed machine. Recently, a doubly-fed induction generator or an asynchronized synchronous generator has gained particular popularity in wind turbines. By design, it is an asynchronous machine with a wound rotor. However, the method of connecting an asynchronized synchronous generator to the network is completely different. The stator winding is connected to the network directly, and the rotor winding is usually connected to the network through a frequency converter. The block diagram of a wind turbine based on this generator is shown in Figure 4.

Fig.4. The block diagram of a wind turbine based on doubly-fed induction generator

This type of generator can operate in three operating modes:

1) pre-synchronous rotor rotation speed: electrical power with the required frequency is supplied from the network to the rotor, which accordingly creates an energy flow coming from the stator winding to the network;

2) synchronous rotor speed: a constant voltage is applied to the rotor winding, and it operates in synchronous generator mode;

3) supersynchronous rotor speed: similar to the operating mode at a rotation speed less than synchronous, but the direction of rotation of the rotor field is opposite [16-20].

This electric machine has the ability to generate electrical energy with constant parameters over a wide range of rotor speeds and the ability to control reactive power flows through the excitation circuit, through which less power passes, which accordingly affects the dimensions and cost of the electronic converter. These distinctive features make the doubly-fed machine the most attractive and efficient for use in wind turbines; as a result, by 2015, asynchronized synchronous generators already occupied about 85% of the installed capacity of wind generators. The disadvantage of this type of generator is the presence of a brush contact that requires time-consuming maintenance for supplying current to the rotor circuit.

Advantages of asynchronized synchronous generators (ASG) in wind turbines:

1. Smooth connection to the grid: These generators provide smooth connection to the grid, which reduces surge currents and increases the reliability of the wind turbine.

2. Resistance to Variable Wind Conditions: asynchronized synchronous generators allow for efficient operation in variable wind speeds, providing stable power output.

3. Hybrid Systems: ASG can be integrated into hybrid systems with other energy sources such as solar power or diesel generators, increasing system reliability and flexibility.

4. Enhanced Control: ASG enable different control strategies to be implemented to optimize wind turbine performance and reliability [20-25].

5. Efficiency: Asynchronized synchronous generators can be configured to provide high efficiency in converting wind energy to electrical energy.

Technical aspects of asynchronized synchronous generators application. Application of ASG in wind turbines requires specialized design and integration. This includes designing electrical circuits, selecting control systems, and testing and maintaining equipment. The key aspects are:

1) Design and Construction: ASG must be adapted to cope with varying wind speeds and changing loads. This requires optimization of design parameters such as stator and rotor windings, as well as material selection.

2) Control and Control: Developing control systems that can ensure optimal operation of the ASG under various operating conditions is an important aspect. This includes frequency and voltage control, as well as load monitoring and overload and short circuit protection.

3) Grid integration: ASG must be integrated into existing electrical networks with minimal losses and surge currents. This requires matching asynchronized synchronous generator parameters with network parameters and using specialized devices for synchronization and protection [25- 30].

3. Conclusion.

Of the many possible types of generators for wind power plants, the best are the two-speed asynchronous generator and the asynchronized synchronous generator (double-fed machine). The first ensures the operation of the wind turbine at low wind speeds. This will increase the production of electrical energy. Therefore, the use of this generator increases the energy efficiency and reliability of wind turbines. The second allows, without additional conversion stages, to directly generate standard energy when the rotor speed changes in a wide range from 0 to supersynchronous speed. As a result, high conversion efficiency is ensured. Moreover, this generator does not consume reactive energy from the network and can itself be a source of reactive power. The conversion occurs through the excitation circuit, which reduces the size and cost of electronic equipment.

REFERENCES

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[5]. Nijat Mammadov, “Analysis of systems and methods of emergency braking of wind turbines”. International Science Journal of Engineering & Agriculture Vol. 2, № 2, pp. 147-152, Ukraine, April 2023
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[7]. T. Haidi, B. Cheddadi, “State of Wind Energy in the World: Evolution, Impacts and Perspectives”, International Journal on Technical and Physical Problem on Engineering (IJTPE), Issue 51, Vol. 14, No. 2, pp. 347-352, June 2022
[8]. N.A. Aliyev, E.N. Ahmadov, S.A. Khanahmadova, ”Improving efficiency of wind turbines with electromagnetic brakes”, IJTPE, Issue 55, Vol 15, No 2, pp. 37-43, June 2023
[9]. N.S. Mammadov, G.A. Aliyeva, “Energy efficiency improving of a wind electric installation using a thyristor switching system for stator winding of a two-speed asynchronous generator”, IJTPE, Isssue 55, Vol 15, No 2, pp. 285-290, June 2023
[10]. Nijat Mammadov, Ilkin Marufov, Saadat Shikhaliyeva, Gulnara Aliyeva, Saida Kerimova, “Research of methods power control of wind turbines”, PRZEGLAD ELEKTROTECHNICZNY, R. 100 NR 5/2024, pp. 236-239
[11]. Abdulkadyrov A.I. “A new principle of synchronization of an asynchronous motor” // Elektrotekhnika. 1998. No. 4. S. 17-20.
[12]. W. Cao, Y. Xie and Z. Tan “Wind Turbine Generator Technologies”, INTECH open science/open minds, pp-44. China, 2012 166 PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 100 NR 9/2024
[13]. Gao L, Li B, Hong J. Effect of wind veer on wind turbine power generation. Phys Fluids. 2021; 33(1):01510. DOI:10.1063/5.0033826
[14]. Mammadov Nijat, “PROSPECTS FOR THE DEVELOPMENT OF RENEWABLE ENERGY SOURCES”, The 29th International scientific and practical conference “Modern scientific trends and youth development”(July 25–28, 2023) Warsaw, Poland. International Science Group. 2023. 244 p.
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[17]. Lukutin B.V. Energy-efficient controlled generators for wind power plants / B.V. Lukutin, E. B. Shandarova, A. I. Muravlev // Izvestiya vuzov. Ser. Electromechanics. – 2008. – No. 6. – P. 63–66.
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Source & Publisher Item Identifier: PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 100 NR 9/2024. doi:10.15199/48.2024.09.30

A Solution to Renewable Energy Source Integration Challenges: Integrating Electric Vehicles into Distribution Networks

Published by Jalal Ibrahimov1, Tural Aliyev2, Ilkin Marufov3, Nijat Mammadov4, Azerbaijan State Oil and Industry University ORCID: 3. 0000-0002-3143-0113; 4. 0000-0001-6555-3632

Abstract. The widespread use of electric automobiles will lead to significant changes in instantaneous consumption values and the mechanisms that govern this consumption. Electricity demand will increase sharply and there will be fluctuations in the networks. The only way to cope with this problem is to switch to smart networks. This article examines and economically analyses the method of switching from a vehicle to a network, which is considered to be used to solve the problem of fluctuations caused by the integration of renewable energy sources into the network. For this purpose, unlike other studies in the literature, a simulation study was conducted that took into account both the battery life of the car and the driver’s behavior. The research to be done in smart networks and renewable energy sources should not be accepted only for home consumers. In terms of competitiveness, industrial consumers need to choose devices that support smart grids when developing and planning their systems. Researches on energy quality and vehicle-to-grid (V2G) is very important in this regard. In addition to engineering objectives, electric automobiles should also be looked at from an economic point of view, such as the benefits and costs they can provide due to the level of vertical integration.

Streszczenie. Powszechne wykorzystanie samochodów elektrycznych doprowadzi do znaczących zmian w wartościach chwilowego zużycia energii i mechanizmach rządzących tym zużyciem. Zapotrzebowanie na energię elektryczną gwałtownie wzrośnie, a w sieciach wystąpią wahania. Jedynym sposobem poradzenia sobie z tym problemem jest przejście na sieci inteligentne. W artykule zbadano i poddano analizie ekonomicznej sposób przejścia z pojazdu do sieci, który uważa się za stosowany w celu rozwiązania problemu wahań spowodowanych włączeniem do sieci odnawialnych źródeł energii. W tym celu, w odróżnieniu od innych badań dostępnych w literaturze, przeprowadzono badanie symulacyjne, w którym uwzględniono zarówno czas pracy akumulatora samochodu, jak i zachowanie kierowcy. Badania, jakie należy przeprowadzić w zakresie inteligentnych sieci i odnawialnych źródeł energii, nie powinny być akceptowane jedynie w przypadku odbiorców domowych. Jeśli chodzi o konkurencyjność, konsumenci przemysłowi muszą wybierać urządzenia obsługujące inteligentne sieci podczas opracowywania i planowania swoich systemów. Badania nad jakością energii i pojazdem do sieci (V2G) są w tym względzie bardzo ważne. Oprócz celów inżynieryjnych na samochody elektryczne należy patrzeć także z ekonomicznego punktu widzenia, np. korzyści i kosztów, jakie mogą zapewnić ze względu na poziom integracji pionowej. (Rozwiązanie problemów związanych z integracją odnawialnych źródeł energii: integracja pojazdów elektrycznych z sieciami dystrybucyjnymi)

Keywords: Vehicle-to-Grid, energy management, electric vehicles, PV charging, renewable energy, distribution network, V2G
Słowa kluczowe: Vehicle-to-Grid, zarządzanie energią, pojazdy elektryczne, ładowanie PV, energia odnawialna, sieć dystrybucyjna, V2G

1.Introduction

Now the whole world is making a rapid transition to renewable energy. But renewable energy systems also have many negative aspects on the network. Generally, solar and wind are the first sources of renewable energy sources. However, these sources are variable, that is, if the wind blows and the sun shines in the air, electricity is generated. On the other hand, the demand in the electricity network is very variable for every hour of the day. Electricity demand is higher during the day, and lower at night than during the day. In this case, it is not always possible to rely on renewable energy plants due to weather conditions. These power plants must also be integrated into storage systems. There are many energy storage methods. But, of course, these methods cannot be applied everywhere due to regional and financial problems, so electric vehicles can be used as a storage tool.

The number of electric vehicles on the roads is increasing every day. Along with this increase, the demand for electricity will naturally increase. Every electric vehicle on the road needs electricity to be charged. Of course, this electricity also needs to be generated from clean energy sources. Therefore, electric vehicles can be used as a complement to renewable energy plants. It can feed the network when the demand for electric vehicles is full when it is full, and it can be stored in electric vehicles when the demand is low, and it can be renewed when the demand is low [1].

Today, the increase in the number of electric vehicles creates a real opportunity for grid balancing. This opportunity can be used to help balance the electrical system and manage local ecosystems by being managed with Vehicle-to-Grid (V2G) solutions. Vehicle to Grid is a system in which plug-in electric vehicles (EV) are connected to the energy grid by transmitting electricity back to the grid or by reducing the charging rates to realize demand-side services. The basic concept of vehicle-to grid demonstrated in the Figure 1.

Fig.1. Vehicle-to-Grid conception

The Vehicle-to-Grid (V2G) system enhances electric vehicles’ storage capacity, enabling them to store or discharge electricity from renewable sources. This flexibility facilitates the integration of numerous renewable energy sources. However, additional studies are necessary to address the increased electricity consumption resulting from widespread V2G adoption. Countries need to prepare for this surge in demand. The escalating need for energy presents inevitable challenges on the production side. Renewable energy sources offer environmentally friendly solutions to augment production but come with their own set of issues. To efficiently provide services, networks must accurately estimate production volumes from alternative sources. Hybrid renewable energy applications serve as eco-friendly solutions designed for this purpose.

Post the Fukushima incident, there has been a rapid increase in the demand for alternative energy sources, with solar and wind energy being the most prevalent. However, reliability and cost pose challenges, influenced by seasonal conditions and high initial installation costs. The research aims to explore the integration of these sources into the network and assess the benefits of employing the Vehicle-to-Grid (V2G) method in conjunction with these renewables. An energy management system model combining V2G and various renewable sources has been developed and explored for different scenarios, highlighting the advantages V2G offers in renewable energy-dependent networks [2, 3].

2. Materials and methods

Vehicle-to-network power transmission. The V2G method is a new method developed in recent years. This method has many important mechanisms, such as meeting high energy demand or balancing the cost of generating electricity.

The number of electic automobiles in the transport system of many countries is growing rapidly. These cars must be connected to the mains to charge their high-capacity batteries. The problems that can arise from this type of simultaneous connection have been discussed. The fact that these cars were generally stationary during the day gave rise to the idea of using their batteries. V2G is a method that uses EA batteries to store energy and aims to create a distributed power source. Using this method, it seems possible to solve the problems of reliability of renewable energy sources in a cooperative way. V2G hybrids can be ancillary to renewable energy systems [4].

Mathematical model and computational method. The generating capacity of the network is determined by deducting the cost of production from the production of renewable energy sources and auxiliary sources. Quantity of production “P” at any “t” time calculated by:

.

Here: PG-grid production, PW-wind power generation, PS-solar power generation, PA-auxiliary production. The PC-parameter is used to indicate consumption. There are various methods for modeling wind energy, which is a variable production method. PW can be obtained using the Weibull probability distribution.

.

Here: v-wind speed, vci-wind speed at which the turbine isstarted, vco-wind speed at which the turbine is stopped, vR-wind speed at rated power. Other parameters include k: smoothing factor and λ-is a ratio used for scaling. The measured wind energy data can be approximated to the Weibull probability distribution. Different probability distributions can also be used for production and consumption data from solar energy. Instead of distributed methods, measured real data values from all sources can also be used. The contribution of backup sources varies depending on the source selected. If V2G is used, this structure is seen as a participatory system, and production capacity depends on two factors. These are; The SOC status of EA batteries and the probability of EA connecting to V2G (POP). There are several situations that affect the value of POP. The first is the importance and frequency of use of the car. The other is the motivation of vehicle owners to participate in the system. Incentive-based mechanisms can be used to increase the value of POP in an energy management system. As with DSM systems, rewards can increase the desire to participate. Presumably, unlike the POP value expressed in the range [0-1], the SOC value is expressed as a percentage (0: empty, 100: full).

.

A block diagram of a calculation method using a mathematical model is shown in Figure 2.

Fig.2. Proposed energy management system model

In the computational method, forecasting was used in the available energy capacity method to determine V2G production. This method first determines the probability of participation having the same value for all vehicles. If a different probability value is used for each vehicle, the computational complexity increases dramatically. Using the total participation probability, the share distribution can be simplified to the binomial distribution. Finally, the available energy capacity is calculated by grouping the vehicles into different groups. The SOC features of the EA are also taken into account in order to make a better assessment of the calculation method [5, 6, 7, 8].

Vehicle-to-network simulation research. In the simulation study, the POP and SOC values were taken as random values due to their uncertainties. Random POP and SOC values are given equally to each EA owner. Due to these values, the participation of vehicles in V2G is formed. The study examines three scenarios in which renewable energy sources contribute to the grid to varying degrees. Production profiles of energy sources were created using the total capacity values in Table 1 [9, 10].

Table 1. Sources used and total capacity values

.
Fig.3. Daily production profiles of wind turbines and PV panels

Figure 3 shows the daily production profiles of these sources. Production of PV panels peaks in the afternoon, and for the rest of the day, production is almost non-existent for some time. Similarly, wind energy production exhibits a non-permanent production behavior. It is not possible for the network to create a reliable power supply using only these two sources.

Figure 4 shows a description of the network’s total electricity generation for the day.

Fig.4. The daily total production profile of the network we show is an example

In many studies in the scientific literature, the probability of EA participating in V2G has been defined as a single value. Because such a hypothesis does not accurately reflect real life, each EA was given a separate opportunity to participate. The probabilities of V2G participation were determined by the intervals given in Table 2 and by scenario type.

Table 2. The probable value ranges for EA’s and V2G contributions

.

The parameters given in Table 3 are used to determine the production of renewable energy sources for different scenarios.

Table 3. Rates of reduction in production for different scenarios

.

Use of small amounts of renewable energy sources. In this scenario, renewable energy sources are likely to be more limited. The reason for this restriction may be a seasonal condition or a temporary decrease in production. As a result, in such a scenario there is a maximum and stable requirement for V2G supply. The likelihood of EA participating in V2G has also been kept high for this purpose. Figure 5 shows the impact of V2G on the network in this scenario. A more balanced production profile was obtained using V2G.

Fig.5. Impact of V2G on the network when using small amounts of renewable energy sources

Use of large amounts of renewable energy sources. In this scenario, the production of renewable energy sources is assumed to be higher than in the previous scenario. EA owners have an average motivation to participate in V2G, according to Table 2. When Figure 6 is examined, it is seen that V2G is able to balance the production profile of the network as in the previous scenario.

Fig.6. Impact of V2G on the network when large amounts of renewable energy sources are used

Use of very high amounts of renewable energy sources. In the third scenario, the contribution of energy from renewable energy sources to the grid is assumed to be very high. In such a situation, the desire to participate in V2G is kept low to avoid overproduction, and opportunities to participate are identified accordingly. As shown in Figure 7, the presence of a small amount of V2G further increased production. Due to the predominance of renewable energy sources, the network has a wavy production profile. The small contribution of V2G is very similar to the absence of V2G in the system [11, 12].

Fig.7. Impact of V2G on the network when very high amounts of renewable energy sources are used

Economic analysis and evaluation. Production using fossil fuels is generally undesirable because it is harmful to the environment. However, based on the structure of public finance, production costs are extremely important for many countries. Initial investment and maintenance costs are not taken into account when comparing V2G and fossil fuel solutions. Because taking into account the initial investment costs gives V2G an unfair advantage. In fact, the electric automobiles that make up V2G’s initial investment cost is purchased by car owners, and maintenance costs are also paid by car owners. The costs of both production methods are compared in Table 4 [13].

The most important cost area of V2G is the battery. The supply of these systems is limited by battery technology, battery health, and SOC. In order to avoid possible voltage problems, the SOC value in cars participating in the V2G system must be more than 20 percent. The main problem with the EA produced to date is that the driving distances of vehicles are not very long. No EA owner wants their car to be kept at a low SOC value by the V2G system and starts their journey that way. Therefore, in a V2G system, it is necessary to prevent SOC values from falling below 50 percent. However, this criterion may reduce the contribution of V2G to the system. Table 5 summarizes how SOC values should be interpreted for a V2G system [14].

Table 4. Comparison of the cost of fossil fuel production with V2G

.

Table 5. Meaning of SOC values for V2G

.

EA batteries today consist of electrochemical layers. The batteries have various problems due to wear, overheating, charging, and discharging. Frequent charging and discharging processes accelerate deterioration. However, even without the V2G system, the car’s battery wears out and runs out. Only the additional effects of V2G on battery life should be considered. In addition, it has been observed that the charging and discharging process at lower average SOC values prolongs battery life. As a result, an intelligent power management system must drive the cars involved in V2G, taking into account the SOC values. This section provides an economic analysis of V2G hybrid renewable energy systems and explores V2G integration. V2G is an environmentally friendly solution that promises to maximize the benefits of a hybrid renewable energy system. Renewable energy sources, such as wind and solar energy, cannot provide uninterrupted production due to external conditions. V2G can be used to overcome this continuity problem in production. However, EA batteries in the V2G system must be subjected to charging and discharging processes that often reduce their life. Despite the additional cost of the battery, a V2G system is both more economical than residual fuel alternatives and less harmful to the environment. Another important factor that will affect the success of the V2G system is the participation of vehicle owners. In cases where motivation is low, participation can be increased by using an incentive-based mechanism [15].

3. Conclusion

The study realized for the three scenarios in which renewable energy sources contribute to the grid to varying degrees. Production profiles of energy sources were created using the total capacity values that given by authors. In the applied example, it is assumed that only wind and solar energy sources are used in the network. Results were obtained according to three situation that indicated in the body of article.

1. In the scenario of small amounts of renewable energy sources because of the restriction of a seasonal condition or a temporary decrease in production, there is a maximum and stable requirement for V2G supply. The likelihood of EA participating in V2G has also been kept high for this purpose. A more balanced production profile was obtained using V2G.

2. In the scenario of many renewable energy sources, the production is assumed to be higher than in the previous scenario. EA owners have an average motivation to participate in V2G. When simulation analyzed, it is seen that V2G is able to balance the production profile of the network as in the previous scenario.

3. In the third scenario, the contribution of energy from renewable energy sources to the grid is assumed to be very high. In such a situation, the desire to participate in V2G is kept low to avoid overproduction, and opportunities to participate are identified accordingly. Due to the predominance of renewable energy sources, the network has a wavy production profile. The small contribution of V2G is very similar to the absence of V2G in the system.

REFERENCES

[1] A. Panday and H. O. Bansal, “Green Transportation: Need, Technology and Challenges”, Int. J. Global Energy Issues, Inderscience publishers, Vol. 37, No. 5/6, pp. 304-318
[2] A. Briones, J. Francfort, P. Heitmann, M. Shey, S. Shey and J. Smart, “Vehicle-to-grid (V2G) power flow regulations and building codes review by the AVTA”, INL/EXT-12-26853, September 2012
[3] R. Sioshansi and P. Denholm, “The value of plug-in hybrid electric vehicles as grid resources”, Energy Journal, vol. 31, no.3, paper no. 01/2010
[4] A. B. Rolufs, “Kansas City Plug-In Electric Vehicle Demonstration Project”, Missouri Transportation Institute, Missouri university of science and engineering
[5] T. Morgan, “Smart grids and electric vehicles: Made for each other?”, Summit Int. Transport Forum, on Seamless Transport: Making Connections, Leipzig, Germany, discussion paper no. 2012-02, OECD 2-4 may 2012
[6] S. Morash, “Vehicle to grid: plugging in the electric vehicle”, Senior Capstone Projects, paper 200
[7] W. Kempton and V. Udo, Ken Huber, K. Komara, S. Letendre, S. Baker, D. Brunner and N. Pearre, “A test of vehicle-to-grid (V2G) for energy storage and frequency regulation in the PJM system”, nov. 2008
[8] S. Han, S. Han, K. Sezaki, Development of an optimal vehicleto-grid aggregator for frequency regulation, IEEE Trans. Smart Grid 1 (1) 65-72, 2010
[9] C. Quinn, D. Zimmerle, T.H. Bradley, The effect of communication architecture on the availability, reliability, and economics of plug-in hybrid electric vehicle-to-grid ancillary services, Journal of Power Sources 195 (5) 1500-1509, 2010
[10] M.A. Fasugba, P.T. Krein, Cost benefits and vehicle-to-grid regulation services of unidirectional charging of electric vehicles, in: Proc. IEEE Energy Conversion Congress and Exposition (ECCE 2011), Phoenix, USA, Sept. 17-22, pp. 827-834, 2011
[11] A. Papavasiliou, S.S. Oren, Supplying renewable energy to deferrable loads: Algorithms and economic analysis, in: Proc. IEEE Power and Energy Society General Meeting, Minneapolis, USA, pp. 1-8 July 25-29, 2010
[12] A. Millner, “Modeling lithium ion battery degradation in electric vehicles,” 2010 IEEE Conf. Innov. Technol. an Effic. Reliab. Electr. Supply, CITRES 2010, pp. 349–356, 2010
[13] M. Yilmaz and P. T. Krein, “Review of Battery Charger Topologies , Charging Power Levels , and Infrastructure for Plug-In Electric and Hybrid Vehicles,” vol. 28, no. 5, pp. 2151–2169, 2013
[14] D. P. Tuttle, R. L. Fares, R. Baldick, and M. E. Webber, “PlugIn Vehicle to Home (V2H) duration and power output capability,” 2013 IEEE Transp. Electrif. Conf. Expo, pp. 1–7, Jun. 2013
[15] “Global ev outlook: Understanding the electric vehicle landscape to 2020”,www.iea.org, 2017

Source & Publisher Item Identifier: PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 100 NR 9/2024. doi:10.15199/48.2024.09.08

Assessment of the Danger of using Ultraviolet Lamps in Electrical Systems

Published by 1. Anatolii SEMENOV1, 2. Stanislav POPOV1, 3. Serhii YAKHIN1, 4. Bauyrzhan YELEUSSINOV2, 5.Tamara SAKHNO1, Poltava State Agrarian University (1), Branch of JSC «NCPD Orleu» Institute of professional development in Kyzylorga region (2) ORCID: 1. 0000-0003-3184-6925; 2. 0000-0003-2381-152X; 3. 0000-0002-0042-0844; 4. 0009-0005-0552-6794; 5. 0000-0001-7049-4657

Abstract. To determine the photobiological safety of UV lamps, the following measurements were carried out: spectral irradiance, total actinic irradiance in the wavelength range of 200-400 nm, and irradiance in the UVA range (320-400 nm). These parameters were measured using the optical radiation system OST-300. The photobiological safety of LUF 40-1, LE 15 lamps and their radiation risk group are established in accordance with EN 62471. The levels of UV radiation generated by LE 15 low pressure discharge lamps at a distance of 0.25 m belong to the high risk group (GR3), and LUF 40-1 – in the group of insignificant risk (GR1). Calculations and recommendations on safe radiation doses when using lamps in electrotechnical systems of photobiological influence are given

Streszczenie. W celu określenia bezpieczeństwa fotobiologicznego lamp UV wykonano pomiary: natężenia promieniowania spektralnego, całkowitego natężenia promieniowania aktynicznego w zakresie długości fal 200-400 nm oraz natężenia promieniowania w zakresie UVA (320-400 nm). Parametry te mierzono za pomocą optycznego systemu promieniowania OST-300. Bezpieczeństwo fotobiologiczne lamp LUF 40-1, LE 15 oraz ich grupa ryzyka radiacyjnego są określone zgodnie z normą EN 62471. Poziomy promieniowania UV generowane przez niskoprężne lampy wyładowcze LE 15 w odległości 0,25 m należą do grupy wysokiego ryzyka (GR3), a LUF 40-1 – w grupie ryzyka znikomego (GR1). Podano obliczenia i zalecenia dotyczące bezpiecznych dawek promieniowania przy stosowaniu lamp w elektrotechnicznych układach oddziaływania fotobiologicznego. (Ocena niebezpieczeństwa stosowania lamp ultrafioletowych w instalacjach elektrycznych)

Keywords: photobiological safety, UV irradiance, carcinogenic safety of radiation, spectral intensity.
Słowa kluczowe: bezpieczeństwo fotobiologiczne, promieniowanie UV, rakotwórcze bezpieczeństwo promieniowania, intensywność spektralna.

Introduction

Ultraviolet radiation is one of the important environmental factors that significantly affect the human body [1]. Humans are increasingly being exposed to ultraviolet rays due to the thinning of the ozone layer and its widespread use in sterilization processes, especially against the SARS-CoV-2 virus [2].

The state and environmental parameters of ultraviolet radiation are essential for its life in the inactivation of bacteria [3], irradiation of surfaces [4] and stimulation of processes [5]. In the process of evolution, under the influence of solar ultraviolet radiation in the human body, a whole complex of photobiological reactions has developed, both positively and negatively affecting its vital activity [6]. UV irradiation at doses of 10-15 J/m2 can stop the division of 90% of cells. Ultraviolet rays of different spectral ranges cause changes in cells that affect vital functions: growth, division, heredity. Therefore, radiation in the range from 320 to 400 nm causes slight erythema in humans, and radiation in the wavelength range from 290 to 320 nm and less causes burns [1]. The danger of ultraviolet radiation is also because a person does not have a sensory organ that could directly react to ultraviolet radiation.

Despite the study of the effects of UV radiation as a powerful hygienic and therapeutic factor, systematic studies of the beneficial effects of monochromatic radiation of various wavelengths have not yet been carried out. At present, there are only attempts to link the variety of beneficial effects of UV radiation with one, rather well studied function and to attribute to it the cause of integral beneficial effects [1]. The established factors of influence [7, 8] of UV radiation on cells of living organisms require detailed research and analysis to determine the photobiological safety of UV radiation on humans, depending on the spectrum and dose of radiation in various systems of ultraviolet action [9, 10]. Until recently, it was believed that UV radiation in the spectral range of 290-400 nm is useful says [1] and was considered as one that activates the defense mechanisms of the human body [11, 12].

Approximately 95% of all solar UV radiation reaching the Earth’s surface is UV-A light (320-400 nm), which causes oxidative stress and the formation of DNA photoproducts in skin cells [13]. UVA radiation does not play a significant role in the negative impact on living objects, since it is poorly absorbed by DNA cells [14]. Risk-benefit analysis of exposure to solar ultraviolet radiation is widely used in the literature [15, 16]. A review by author [17] presents a mechanistic consideration of the wavelength dependence for UVR-specific mutations and substantiates the suggestion of UVA signature mutation in addition to UV signature mutation.

Recent studies by many authors have shown that UVA radiation creates a number of negative consequences for the human body, which can lead to serious structural and functional damage to the skin, and create mutagenic effects [18]. It is also necessary to take into account the effect of UV radiation on the retina and other components of the organs of vision [19]. UV radiation (even mild – UV-A) can lead to serious damage to the visual apparatus, since the receptors of vision do not feel its influence.

One of the health problems around the world associated with ultraviolet light is cataracts [20]. It especially often occurs in rural residents who spend a lot of time in unshaded areas [21]. More than a hundred scientific papers on the impact of artificial light sources and natural UV radiation of the sun on human health have been analyzed in the studies of the international organization WHO [7].

Multiple experimental confirmations have negative effects and the evidence continues to grow. UVA radiation penetrates deeper into the skin than UVB and causes photoaging. The influence and mechanism of action of ultraviolet B (UVB) on melanin synthesis and premature aging in cells. Herewith, the melanin content first increased, and then decreased with increasing UVB exposure [22].

The harmful effects of UV-B radiation on photosynthesis and photosynthetic productivity of plants are given in [23]. UV-B radiation has been shown to damage the photosynthetic apparatus of green plants in many place [24].

The misconception that high-intensity UV-A exposure from tanning devices is safe and not associated with melanoma is being challenged. More recent data from experimental studies induced in the review [18] provide strong evidence for a strong association between UV-A and the risk of melanoma. UVA is a complete carcinogen that may play a key role in both the onset and progression of melanoma.

In research [25], was carried out that using ultraviolet lamps on devices intended for UV curing of artificial nail coatings, which are widely used in manicure salons all over the world. The photobiological safety of these devices has been reviewed in the dermatological literature [26], where two cases of non-melanoma skin cancer on the dorsum of the hand were observed in women with previous exposure to UV nail lamps. Doctors say that UV lamps for manicure can be compared to tanning devices – tanning beds, and suggest that they may also pose a risk factor for developing skin cancer [27].

The most favorable direction in the study of the photobiological safety of lamps and lamp systems is the analysis of UV systems used to obtain artificial irradiation in tanning salons, since there is regulatory documentation in EN 60335–2–27 [28] and IEC 61228 [29] and the necessary equipment allows a number of studies in this direction. In addition, a number of studies have shown that in most tanning salons, the irradiance level is above the safety limits and the ratio of UVB/UVA fluxes is significantly different from natural sunlight.

Requirements for the radiation of lamps used in photobiological systems are established in EN 60335–2–27 [28] and IEC 61228 [29], which presents the specifications of the recommended photobiological safety practice for lamps – classification and labelling of risk groups. These specifications include a risk analysis of exposure thresholds for exposure to ultraviolet radiation and subsequently adopted as international standards by the International Electrotechnical Commission (IEC). The total effective surface radiation flux density, which is estimated in accordance with the spectrum of erythema action, should be no more than 0.7 W/m2 . In addition, according to EN 60335-2-27, the radiant flux density in the spectral range of 280-400 nm should be no more than 0.3 W/m2 . Appliances for domestic use must have a total effective surface radiation flux density that does not exceed 0.15 W/m2 . The UVB/UVA ratio shows how much of the UVB region radiation, assessed by the weight function of the carcinogenic hazard, falls on the UVA region radiation. It is known that high doses of UVB radiation cause burns, so it should be limited. Erythema-weighted irradiance and the ratio ЕUVB/ЕUVA, assessed by the weight function of the carcinogenic hazard of radiation, are the main parameters of lamps, and they are communicated to consumers by labelling with a UV code. In various systems of photobiological action, depending on the design and purpose, UV lamps with a radiation spectrum are used, which significantly differs from the UV spectrum of the Sun.

In most cases, low-pressure discharge lamps are used [30]. The parameters of some types of lamps are given in Table 1.

Studies carried out by the authors [31] have shown that the level of irradiation, which is created by low-pressure discharge lamps in the UVB range, is predominantly lower, and the irradiation in the UVA range is much higher than natural. In [32, 33] it was shown that the erythema-weighted irradiation of ultraviolet systems exceeded the established requirements of European standards.

According to IEC 61228 [29], information that must be provided by the manufacturer, upon request, including data on the spectral distribution of radiation depending on the product in the form of: spectral power of radiation, or spectral intensity, or spectral illumination and power conversion factor into radiant flux. Manufacturers are also required to provide information on the potential hazards associated with UV and optical radiation [34] sources upon request.

Table 1. Characteristics of low-pressure discharge lamps

.

The need to check UV lamps used in various photobiological systems for irradiation and stimulation of processes is caused by the discrepancy between the real parameters of the lamps and the requirements of international standards. The need for research is also due to the appearance of a large number of household UVaction devices to combat viral diseases, which are not monitored for compliance with photobiological safety requirements.

Materials and methods of research

Determining the risk group of lamp radiation and studying their photobiological safety in accordance with EN 62471 was the aim of this work [35]. Research objects:

1. Erythema lamps LE 15. Allow to receive additional erythema radiation in areas where the daylight hours are shorter or where there is no natural solar radiation at all. Erythema lamps are used at agricultural enterprises to reduce ultraviolet starvation of poultry and animals.

2. Lamp ultraviolet LUF 40-1. Low-pressure discharge lamps of the LUF type are intended for operation in various irradiation installations using the photochemical and biological action of ultraviolet radiation in the 300-420nm spectral region. Lamp LUF-40 has found wide application in the printing industry.

On fig. 1 shows the markings on the samples of the studied lamps.

Fig.1. Samples of the tested lamps

Standardized methods for assessing and classifying the risks of ultraviolet blue and infrared radiation are given in the SIE S009 standard, and then adopted by the International Electrotechnical Commission in the IEC 61228 [29].

The significance function for assessing the danger of actinic UV radiation for the skin and eyes is presented in EN 62471 [35]. In EN 62471 limit values (RG) of irradiance are established, which, when using electrical devices and lamp systems, must not be exceeded. For UV lamps, the exposure limits for various groups of photobiological risks are given in table 2.

EN 62471 [35] is the only regulatory document by which the safety of UV lamps can be assessed. Spectral irradiance measurements E(λ) and calculations of the total actinic irradiance ЕUV in the wavelength range 200–400 nm and irradiance ЕUVA in the UVA range (320–400 nm) were carried out according to the method described in IEC 61228 [29] and EN 62471 [35]. The measurements were carried out using an OST-300 optical radiation system [30], which contains software for calculating the total actinic irradiance and irradiance in individual spectral ranges [36]. The program also allows you to calculate the exposure limits and the risk group.

Table 2. Exposure limits for different groups photobiological risks

.
Results of the research

The results of measuring the spectral irradiance (W/(m2.nm) of LUF 40-1 and LE 15 lamps in the wavelength range of 200-500 nm are shown in figure 2.

Fig.2. Spectral irradiance of lamps of type LUF 40-1(a) and LE 15(b)

In the studied lamps LUF 40-1 and LE 15 on the marking and in the additional information provided in the technical specifications for lamps LUF 40-1 and LE 15 there is not enough information to determine the equivalence code (UV code) according to IEC 61228 [34]. To determine the codes, it was necessary to measure and calculate the following indicators: total effective erythemal UV irradiation in the spectrum range of 250-400 nm; effective irradiation by the function of significance and carcinogenic – dangerous irradiation in the UVA (λ>320 nm) and UVB (λ<320nm) spectrum ranges; determination of the ratio of effective irradiance (irradiance) ЕUVB/ЕUVA.

The calculations were carried out in accordance with the requirements of IEC 61228 [29]. The calculation results are summarized in table 3.

Table 3. Calculation results of effective irradiance to determine the UV code of lamps according to IEC 61228

.

UV – code of the LUF 40-1 lamp: 40-O-4.0/3.6, where 40-O is a lamp without a reflector, with a power of 40 W; 4.0 – effective erythemal irradiance at a distance of 0.25 m in the spectral range of 250–400 nm; 3.6 – ЕUVB/ЕUVA.

UV code of the LE 15 lamp: 15-O-1470.0/167.8, where 15-O is a lamp without a reflector, with a power of 15 W, 1470.0 is an effective erythemal irradiance at a distance of 0.25 m in the spectral range 250–400 nm; 167.8 – ЕUVB/ЕUVA.

Calculated based on measurements, the value E(λ), ЕUV, ЕUVA for distances from the lamp of 0.25 m, as well the risk group are given below.

1. Ultraviolet lamp LUF 40-1: The total value of the ЕUV at a distance of 0.25 m is 1.33 mW/m2 . The energy illumination of the ЕUVA at a distance of 0.25 m is 2459 mW/m2 . Under these conditions, the radiation from the lamps is classified as low risk (RG1).

2. UV lamp LE 15: The total value of the ЕUV at a distance of 0.25 m is 31.9 mW/m2 . The energy illumination of the ЕUVA at a distance of 0.25 m is 214.2 mW/m2 . Under these conditions, the radiation from the lamps is classified as a high risk group (RG3).

Discussions

From the given results (table 3) it can be seen that in the spectral composition of LUF 40-1 lamps there is less radiation in the UVB range and it creates a much lower erythemal irradiance. The erythemal efficiency of LE 15 lamps are 47 times higher than that of LUF 40-1. Therefore, when using such lamps in various systems of ultraviolet exposure during human irradiation, it is necessary to take into account the obtained indicators and take the necessary safety measures [37, 38].

The maximum UV exposure time is defined as tmax=30/EUV. Limits of maximum exposure to UVA: the dose should be no more than 104 J/m2 at t<1000 s; at t>1000 s – EUVA≤10 W/m2 . The maximum UVA irradiation time (in seconds) is defined as tmax=104 /EUVA. The recommended exposure time for the first action should not exceed a dose of 100 J/m2 , for the second action the dose should not exceed 250 J/m2 , and the total dose should not exceed 3000 J/m2 .

Conclusion

Based on the results of the study, the following conclusions can be drawn:

1. The photobiological safety of LUF 40-1 lamps belongs to the low-risk group RG1, and the LE 15 lamps – to the high-risk group RG3.

2. The UV code of the LUF 40-1 lamps is 40-O-4.0/3.6 and the UV code of the LE 15 lamps is 15-O-1470.0/167.8. The erythemal efficiency of LE 15 lamps are 47 times higher than that of LUF 40-1, which requires additional safety measures.

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[17] Ikehata H. Mechanistic considerations on the wavelengthdependent variations of UVR genotoxicity and mutagenesis in skin: the discrimination of UVA-signature from UV-signature mutation, Photochemical & Photobiological Sciences, 17 (2018), 1861–1871.
[18] Khan A.Q., Travers J.B., Kemp M.G. Roles of UVA Radiation and DNA Damage Responses in Melanoma Pathogenesis, Environmental Mutagen Society, 59 (2018), No. 5, 438-460
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[28] EN 60335-2-27:2013/A2:2021-11. Household and similar electrical appliances – Safety – Part 2–27: Particular requirements for appliances for skin exposure to ultraviolet and infrared radiation
[29] IEC 61228:2020. Fluorescent ultraviolet lamps used for tanning-Measurement and specification method
[30] Semenov A., Sakhno T., Sakhno Y. Photobiological safety of lamps and lamp systems in agriculture. Journal of Achievements in Materials and Manufacturing Engineering, 106 (2021), No. 1, 34-41
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[34] Dybczyński W. Ocena zagrożenia spowodowanego promieniowaniem optycznym, Przegląd Elektrotechniczny, 01, 2003, 17-21
[35] EN 62471:2008. Photobiological safety of lamps and lamp systems (IEC 62471:2006, CIE S 009: 2002)
[36] Pawlak A. Spektroradiometryczna metoda oceny bezpieczeństwa fotobiologicznego źródeł emitujących promieniowanie, Przegląd Elektrotechniczny, 95, 2019, nr 10, 219-224
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Authors: Anatolii Semenov, professor of the Department of Mechanical and Electrical Engineering, Poltava State Agrarian University, 1/3, Skovorody, St., Poltava, 36003, Ukraine, E-mail: asemen2015@gmail.com; Stanislav Popov, professor, head of the Department of mechanical and electrical engineering, Poltava State Agrarian University, 1/3, Skovorody, St., Poltava, 36003, Ukraine, E-mail: stanislav.popov@pdaa.edu.ua; Serhii Yakhin, professor, head of the Department of Construction and Professional Education, Poltava State Agrarian University, 1/3, Skovorody, St., Poltava, 36003, Ukraine, E-mail: sergii.iakhin@pdaa.edu.ua; Bauyrzhan Yeleussinov, Director, Branch of JSC «NCPD Orleu» Institute of professional development in Kyzylorga region, 2, Aiteke bi, St. Kyzylorda, 120700, Kazakhstan, E-mail: baur_1960@mail.ru; Tamara Sakhno, professor of the Department of Biotechnology and Chemistry, Poltava State Agrarian University, 1/3, Skovorody, St., Poltava, 36003, Ukraine, E-mail: sakhno2001@gmail.com

Source & Publisher Item Identifier: PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 100 NR 2/2024. doi:10.15199/48.2024.02.31

International Standards for Power Quality Measurement Systems

Published by P Axelberg, Unipower AB, Sweden & M H. J. Bollen, Chalmers University of Technology, Sweden

I. INTRODUCTION

During the last decade, there has been an increasing focus on power quality (PQ). The interest and demand for quality assurance of electrical power has several fundamental causes. First of all, electrical power can be considered a product for which assured quality offers incentives to both buyer and seller. Secondly, large amounts can be saved by permanently keeping track of the quality of power from the electrical grid or network. Based on the analysis from the measurements, a cost effective maintenance or upgrading of transmission and distribution assets is possible. A third reason for the increased focus on power quality is the deregulation of the electrical power market, which is happening throughout the world. This has led to an increased awareness about power quality issues by customers who are now demanding better performance from electricity suppliers.

For example, in South American countries like Argentina, Chile and Peru and legislation forces the supplier to deliver a good power quality level, or otherwise pay a penalty if the quality is outside the set limits [1]. In Europe Electricité de France (EdF) offers customised power contracts in which quality of supply is specified and penalties paid for performance outside guarantee. The Victorian Regulator-General has recently introduced legislation in Australia to provide for compensation for damage caused by voltage variation outside set limits.

In summary there is a fundamental demand for measurements of power quality and to compare these with reference values. This requires that comparable results of measurements be achieved from different instruments. At present, this is not always the case.

The increasing need for PQ measurement has driven the requirement for standards that describe measuring methods and how the different power quality parameters are calculated and interpreted. There are already IEC standards that describe how harmonics (IEC 61000-4-7) and flicker (IEC 61000-4-15) should be calculated and presented. Unfortunately, there is still no overall standard available that covers the measurement techniques and calculations for other power quality parameters. This has led to the recent development of IEC 61000-4-30 (Testing and Measurement Techniques- Power Quality Measurement Methods) by the International Electrotechnical Commission.

The forthcoming IEC 61000-4-30 describes how a number of PQ parameters shall be calculated. Furthermore, it also classifies these parameters into two different classes depending on how the calculations are made. Manufacturers of power quality instruments can choose to develop instruments that are Normative (class A) or Indicative (class B). This standard will be an important document, used to spread the knowledge that PQ measurements for different purposes demand different performance from the instruments. It will also promote the achievement of comparable measurements from different products.

The purpose of this article is to give a short description of power quality issues, including application of fixed monitoring systems and outline the new standard IEC 61000-4-30 and its benefits to manufacturers and users of PQ analysers.

II. POWER QUALITY OVERVIEW

Power quality analysis is a well-established concept, used to evaluate the quality of electrical energy delivered to a customer. A simplified way to define the PQ concept is shown in Figure 1.

Figure 1. The power quality concept [2].

The electrical power grid or network should be designed in such a way that the supplier is always capable of guaranteeing a certain voltage quality. When loads are connected the power quality is influenced more or less depending on how the electrical network is designed and on the current profile of the loads. From this perspective, a number of basic parameters for power quality have been identified which can be measured and compared with reference values. The reference values may be absolute values or statistical values and may be obtained from standards or agreed in a bilateral contract between network generator and a customer.

For instance, a well recognised European norm is EN 50 160: Voltage characteristics of electricity supplied by public distribution systems [3], in which the parameters registered and being compared are the voltage magnitude, frequency, harmonic distortion, voltage unbalance, flicker, signaling voltages. EN 50 160 does not give any voltage characteristics for events like voltage dips, swells, transients etc. However, for the completeness a list of various events is mentioned together with indicative values. Note however that EN 50160 is not so much a requirement for the voltage quality but a description of the existing situation. The term “voltage characteristic” refers to the level not exceeded by 100% of customers during 50% of time. It is thus obvious that most locations have a voltage quality that is “better than the standard”. Measurements against the standard are only of use when this is taken into consideration.

III. DIFFERENT CATEGORIES OF POWER QUALITY MEASUREMENTS

Measurements in the power network can be split into different categories. The most common ones are demand analysis (power and energy measurements), measurements to detect disturbances, statistical measurements about the electrical grid, measurements according to standards (EN 50160 etc.) and measurements to be able to design components like transformers, capacitor bank filters etc. The various categories of measurement require different instruments.

With the increasing needs for PQ measurement, there is a growing need for standardisation. The future standard IEC 61000-4-30 will set a new benchmark for power quality measurements and will be important for both users and manufacturers of PQ instruments.

IV. CLASSIFICATION OF POWER QUALITY PARAMETERS

For the average user it is normally difficult to compare instruments. Will the instrument produce reliable results that are comparable with those from other makes? The longer the technical specification, the better, is a common approach. Unfortunately this has little to do with customer driven requirements. Here, IEC 61000-4-30 is offering a solution by classifying the power quality parameters into class A (Normative) and B (Indicative).

Instruments measuring for class B are used specifically for demand analysis and simple error search. They can be either single-phase or three phase with limited accuracy of say +/-1% per channel. Furthermore the indicative power network monitor measures only partly or not at all against given standards. However, the manufacturer of class B instrument shall define the measurement methods used.

Instruments that measure the power quality parameters according to class A are recognized as operating with the highest possible accuracy in all measuring environments/situations. The normative instrument can be used for the same kind of measurement as the indicative instrument but is especially designed to carry out normative measurements against recognised international or local standards or contracts.

Measurements made according to class A are required when verifying standards and when it comes to disputes between customer and supplier and when measurements have to be compared with those from other instruments.

What this means is that measurements that have been done with two different instruments according to class A will give the same result within the accuracy indicated in the standard. Instruments that measure according to class B only give indicative results, dependent on the method used to calculate the parameters, so that measurements taken at the same measuring point but with two different instruments could give different results. Class B instruments can be used for demand analysis, some easier disturbance trace measurements but only with measurements that do not demand an absolute accuracy. Therefore, a class A instrument will always be able to replace a class B instrument but not vice versa.

V. CHANGING DEMANDS FOR POWER QUALITY MEASUREMENTS

Considering electrical energy as a product it is self-evident that it must be quality assured. Traditionally this has been carried out by occasional short-term power quality measurements at isolated locations on the network using portable recorders. Some of these instruments produced reams of paper based data, which was hard to store and analyse. The application of modern electronics to high-speed data acquisition, signal processing, storage and analysis enables a more comprehensive and user-friendly approach from which a new trend is emerging.

IEC 61000-4-30 contains guidelines for contractual applications of power quality measurements. Whilst most parameters can be assessed over a survey period of one week, assuming no abnormal conditions occur such as severe weather, industrial action, third party interference, etc., voltage sags and swells must be assessed over a much longer period – one year is suggested. This makes sense, as dips are generally caused by faults on the network or customer’s installations – they are unpredictable, largely random and their distribution over a year can be very irregular. The implication for monitoring is profound.

A temporary survey using a portable analyser will be inadequate to monitor contractual obligations and permanent instrumentation will be required; especially since voltage dips are one of the most commonly complained about phenomena.

The following examples show how the application of permanent monitoring systems has been successfully used to tackle power quality issues.

A. Power Quality Monitoring on Wind Generators in Ireland

The number of wind generators in Ireland is rapidly increasing due to the suitability of the environment for this kind of power generation. In the southern part of Ireland, near the city of Cork, large wind generators can be seen, dotted around the countryside. However, it is well known that wind generators can cause power quality problems, particularly an increased level of flicker. In order to prevent PQ problems ESB (Eire Supply Board), one of the main suppliers of electricity in Ireland, has decided to install permanent power quality monitoring equipment in substations connected to the generators. The first batch of eighteen monitors is now working and more installations are planned. Not only the flicker, but also other important PQ parameters like sags, swells, transients are continuously monitored and measured data are regularly downloaded to the host computer via an ordinary modem or via a GSM modem for evaluation and presentation.

B. Co-operation between the local distributor and industry regarding power quality monitoring

The city of Linköping in Sweden has approximately 150,000 citizens. It is well known for its university as well as the large industry plants. The utility in Linköping was one of the first to install a permanent power quality monitoring system. It started as a quality issue with the university hospital in Linköping. Since the hospital has a lot of critical equipment, they were very concerned about the quality of their power supply. In cooperation with the utility, permanent power quality monitoring equipment was installed in the substation feeding the hospital. Today, the electrical power supplied to the hospital is fully quality assured.

In addition, the large industry plants were concerned about power quality. A mobile-phone plant and an aerospace plant have installed their own permanent power quality monitors, out-sourcing the evaluation of the measurements to the local utility on a consultant basis. This co-operation has indeed strengthened the relationship between the utility and the customer.

Success of the above projects and others has led to a mix of permanently installed power quality monitors and portable power network analysers. The permanently installed monitors continuously register the power quality at strategic locations in the electrical grid such as bulk supply points including transmission terminal stations and zone substations, as well as other important connection points to key customers – see Fig.2. Measured data is then transferred automatically, via LAN or modem, to a database where evaluation takes place against reference standards and norms and variations reported by exception.

Figure 2. Typical fixed PQ Normative monitor with GSM modem

Portable power network analysers are still used for occasional measurements at locations where no permanent monitors are installed, but these are now available with communication facilities and their measurements are integrated into the database. The control of power quality is becoming a fundamental and strategically important part of the electrical power suppliers’ quality assurance program. New business opportunities are being created based on guaranteeing a certain level of power quality. One opportunity is to be able to offer adjusted power quality to meet the customer’s particular demand and therefore get paid accordingly. This is something which has started to happen in the US and which is generating interest in the European market as well.

VI. THE FUTURE STANDARD IEC 61000-4-30

Now that the practical implications of the standard have been detailed, the following information provides an introduction to the forthcoming IEC 61000-4-30. For a more detailed description, refer to the original document [4].

“Measurement methods are described for each relevant type of parameter in terms that will make it possible to obtain reliable, repeatable and comparable results regardless of the compliant instrument being used, and regardless of its environmental conditions. This standard addresses instrumentation and measurement methods for in-site measurements, and applies to both portable and permanently installed instrumentation.” (IEC 61000-4-30; 1. Scope; p.9.)

The power quality parameters described are power frequency, magnitude of the supply voltage, flicker, supply voltage sags (dips) and swells, voltage interruptions, transient overvoltages, supply voltage unbalance, voltage and current harmonics, voltage interharmonics and mains signaling on the supply voltage and rapid voltage changes.

A. Class A and Class B

The standard describes how the power quality parameters fulfilling class A shall be calculated. For class B instruments, there are no restrictions as to how the parameters shall be calculated but the manufacturer shall specify the measurement methods used.

The following sections provide an overview of the relevant standards for class A instrumentation. To increase the readability of the text below, only 50 Hz are considered. Below discussions are valid also for a 60 Hz system.

B. Integration Times

For class A, the time integration window when recording shall be 10 cycles in a 50 Hz system. With this time integration window as a base, three measuring intervals are defined. These are 150 cycles, 10 minutes and 2 hours. The 150 cycles RMS value is calculated as the root mean square of fifteen 10 cycles RMS values. The windows shall be continuous and non-overlapping so it is easy to proof that the calculated 150 cycle value is the correct RMS value obtained. The aggregation from 150 cycles to 10-minutes is more complicated since the actual frequency will vary. When the system frequency is exactly 50 Hz, there are exactly 200 intervals. For a frequency of 49.5 Hz the 150 cycles become 3.03 seconds and there will be only 198 of them in a 10-minute interval. In most cases the number of intervals is not an integer number and the last interval is discarded in the calculation. Despite the discarded data, it remains safe to interpret URMS(10-min) as the RMS voltage over a 10-minute interval.

Each 10-minute interval must begin on an absolute 10- minute time clock, ± 20 ms. These intervals are used when calculating the voltage magnitude, harmonics and interharmonics and the voltage unbalance.

For frequency measurements a 10-seconds interval is used. There is no aggregation of frequency measurements.

C. Flagging concept

The ”flagged” concept avoids the counting of a single event more than once for different parameters, e.g. counting a single dip as both a dip and a frequency variation. When an event such as voltage dip, swell or a short interruption occurs the instrument shall only record that specific event. The other power quality parameters shall not be recorded. Instead, the interval will be flagged, meaning that it is marked to show the specific event and no other measured data. If a flag is set for a 10 cycles time window interval then the associated 150 cycles, 10 minutes and the 2 hours measurement intervals will also be flagged.

D. Frequency

The frequency shall be calculated every 10 second for class A instrument. To calculate the frequency the number of zero-crossings during 10 seconds is counted. The accuracy for class A shall be better or equal to ± 10 mHz and less than ±100 mHz for class B.

The frequency can be calculated by measuring the elapsed time between the first and the last voltage zero crossing within the 10-second interval. Let N be the number of zero-crossings within the interval and T the elapsed time, the frequency is obtained from:

.

Assuming that the value of N is correct, an accuracy of 10 mHz (2⋅10-4 of 50 Hz) requires an accuracy of 2⋅10-4 in the time measurement: 2 ms on 10 s.

E. Voltage RMS value

The voltage RMS value is calculated for every 10 cycles interval for class A instruments. Based on this 150 cycles, 10 minute and 2 hour interval values can be calculated. As shown in Section VIB the values can be interpreted as the RMS voltage over 10-cycles, 150-cycles, 10-minute, and 2-hour intervals. The accuracy for class A shall be better or equal to ± 0.10 % of nominal voltage and for class B ± 1.0 %.

F. Flicker

The flicker calculations for class A instruments shall follow the restrictions according to the norm IEC 61000- 4-15 (Flickermeter – functional and design specifications) [5].

G. Voltage dips (sags) and swells

The registration of sag/swell events shall be based on 1 cycle RMS values updated every ½ cycle for class A instruments. When this RMS value exceeds or fall below a stated triggering level, the instrument shall start recording and continue until the RMS values have returned to normal. The first instant is referred to as the start of the event, the second as the end of the event. The time between the start and the end of the event is called the duration of the event. The lowest RMS value for a voltage dip is called the retained voltage. The accuracy for class A instruments shall be within ± 0.2 % of the stated nominal voltage and ± 2.0 % for class B.

H. Unbalance

To fulfil the restrictions of class A, unbalance shall be calculated using the method of symmetrical components. From the measured phases, the three symmetrical components are calculated (positive-, negative- and the zero sequence component). The unbalance is then calculated as the ratio between the negative and the positive sequence component expressed as a percentage. Unbalance shall again be calculated over 10-cycle, 150- cycle, 10-minute and 2-hour intervals.

I. Voltage harmonics (harmonics and interharmonics)

To fulfil the requirements for class A the calculations shall be made according to IEC 61000-4-7. For a more detailed description see IEC 61000-4-7 (General guide on harmonics and interharmonics measurements and instrumentation, for power supply systems and equipment connected thereto) [6]. The basic interval for harmonic measurements is again the 10-cycle interval. A DFT (Discrete Fourier Transform) over a 10-cycle window gives a spectrum with a frequency resolution of 5 Hz. This implies that in between the harmonic frequencies (integer multiples of 50 Hz), nine additional values are available. The lowest and the highest of these are “added” to the (integer) harmonic. The remaining seven together form the “interharmonic”. Thus for the interval from 245 Hz to 305 Hz: 255 Hz is added to 250 Hz and 245 Hz to form the 5:th harmonic; 295 Hz, 300 Hz and 305 Hz form the 6:th harmonic. The remaining values: 260, 265, 270, 275, 280, 285 and 290 Hz form “interharmonic 6.5”.

J. Other power quality parameters

The above descriptions provide an introduction to the type of requirements stipulated by the forthcoming standard. For a description of other parameters, such as how transient overvoltages, rapid voltage changes, short voltage interruptions and signaling voltages shall be calculated see the original document IEC 61000-4- 30:2001.

VII. OTHER DEVELOPMENTS

Next to IEC, power quality standards are also developed within IEEE. In 1997 did both the IEEE Gold Book and IEEE Std.1346 give a method for assessing the compatibility between sensitive equipment and supply as far as voltage dips are concerned. The so-called “voltage sag co-ordination chart” enables a direct comparison between equipment voltage tolerance and the voltage dip frequency of the supply [7]. Work on interruptions and reliability has been part of an IEEE standard (recommended practice) since the publication of the first IEEE Gold Book in 1980. The most recent version (1997) even includes a chapter on stochastic prediction of voltage dips. However the IEEE never published a document on measurement of voltage quality. Project Group 1159 is working on such a document, but as yet without much concrete results. The most recent decision is to use IEC 61000-4-30 also within IEEE.

Recently a standard appeared on reliability indices (IEEE Std.1366) which recommends methods for quantifying the reliability of the supply (number and duration of long interruptions). Similar indices are currently under development in IEEE Project Group 1564. The most recent version of the working document of this group uses IEC 61000-4-30 as a basis and from here defines different levels of voltage dip indices.

The first level is formed by “event characteristics as a function of time”. The one used within IEC 61000-4-30 is the one-cycle RMS voltage updated every half cycle. The IEEE document aims at defining some additional event characteristics. From the event characteristics so-called “single-event indices” are calculated. In the case of IEC 61000-4-30 these are “duration” and “retained voltage” for voltage dips. Again some additional indices are defined.

The next level is formed by the “single-site indices”: typically the number of events per year within certain ranges of single-event indices: like the number of dips per year with a duration exceeding 100 ms and a retained voltage below 70%. The final level is the “system indices” being typically a weighted average of the single-site indices of all the monitor locations [8].

Work on power-quality indices (not just voltage dips but also harmonics, unbalance and harmonics) is also ongoing in CIGRE Working Group 36.07. This working group concentrates on the definition of appropriate system indices starting from existing standard documents. The working group also collects data to propose objectives for the indices.

VIII. CONCLUSIONS AND COMMENTS

Today, there are many types of power quality instrument on the market offering different performance according to their measurement techniques. In many cases the users are not aware of this and it is common for them to be misled, believing that results always are reliable and that measurements from different instruments always can be comparable. Unfortunately this is not always the case. Measured results from different power quality instruments are often not fully comparable against either another instrument or even against existing standards. With the increasing demand for accurate power quality supervision in the electrical network it is important that an international standard states how power quality should be measured and calculated, so that valid comparison is possible. This is particularly true for power companies and their customers entering into contractual relationships for the delivery of an assured quality of supply.

One step in this direction is the forthcoming IEC 61000-4- 30 norm (standard) that defines measuring methods and provides new ways to classify power quality instruments. The standard will lead to manufacturers of power quality instruments implementing the same measuring algorithms. Furthermore, it will be important for the end user giving them the full knowledge about instrument performance. IEC 61000-4-30 will therefore be beneficial for both manufacturers and users of power quality instruments.

IX. REFERENCES

[1] Axelberg P, Pool G, 2000, “Experiences from the deregulated electricity markets in South America”. Nordic Distribution Automation Conference.
[2] Bollen M.H.J, 2000, “Understanding Power Quality Problems”. New York: IEEE press. ISBN 0-7803-4713-7,.
[3] European norm EN 50 160: Voltage characteristics of electricity supplied by public distribution systems. CENELEC 1999
[4] IEC standard 61000-4-30:2001 (draft): Testing and Measurement Techniques- Power Quality Measurement Methods.
[5] IEC standard 61000-4-15: Flickermeter – functional and design specifications. IEC 1999.
[6] IEC standard 61000-4-7: General guide on harmonics and interharmonics measurements and instrumentation, for power supply systems and equipment connected thereto. IEC 2001.
[7] Bollen M.H.J, Conrad L.E., “Voltage sag coordination for reliable plant operation”, IEEE Transactions on Industry Applications, Vol.33, No.6, pp.1459-1464.
[8] IEEE, 2001, ”Voltage sag indices”. Working document for Project Group 1564, draft 2. http://grouper.ieee.org/groups/sag/.

X. BIBLIOGRAPHIES

Peter Axelberg is a senior lecturer at Högskolan i Borås, Sweden. His research activities are focused on power quality measurement techniques. He is also one of the founders of Unipower AB.

Math H. J. Bollen is professor in electric power systems at Chalmers University of Technology. Before joining Chalmers in 1996 he worked at UMIST, Manchester, UK and at Eindhoven University of Technology in The Netherlands. His research activities include various aspects of power quality. Math is co-chair of IEEE P1564 and member of CIGRE WG 36.07.

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