Below are three situations aviation teams often face, and how the HDPQ Xplorer 400 helps resolve them.
Jetway keeps resetting when an aircraft connects
What’s happening: During bridge movement or aircraft power-up, the 400 Hz supply dips. Sometimes it is a brief sag, other times a fast transient that trips protection.
How the HDPQ helps: The analyzer locks to 400 Hz and records synchronized waveforms, RMS trends, and an event list with timestamps. You see whether the disturbance is a sag, swell, interruption, or inrush, and how deep and long it lasted.
Outcome: Maintenance can point to a specific root cause, such as a voltage sag to 86 percent for 6 cycles during bridge travel, instead of a generic “power issue.” Fixes are targeted and repeat calls drop.
Disputes about parked aircraft energy usage at the gate
What’s happening: Finance wants real numbers for billing or cost allocation, but estimates vary by aircraft type and turn length.
How the HDPQ helps: You get true 400 Hz measurements for kW, kWh, power factor, and demand across a full turn. Results can be grouped by aircraft family and dwell time, with easy-to -read charts.
Outcome: Contract discussions shift from estimates to measured profiles. One hub used profiles to update agreements and reduced variance between billed and actual significantly.
Proving savings after upgrades to support systems
What’s happening: A facilities project replaces conveyors with higher efficiency equipment, and wants to document the manufacturer’s energy savings claim.
How the HDPQ helps: Comparable pre- and post-data sets confirm changes in kW, kWh, demand peaks, and power factor. High-speed capture also shows if inrush or switching transients improved, which affects nuisance trips.
Outcome: Engineering delivers a simple before-versus-after story. The project team validates the savings and identifies additional tweaks, like adjusting start sequences to lower demand spikes.
Why these teams choose the HDPQ Xplorer 400
• Correct 400 Hz synchronization for trustworthy frequency, RMS, and timing • High-speed event capture that surfaces short sags, transients, and inrush • Remote viewing from phones, tablets, PCs, and Macs so supervisors can monitor without crowding the gate
Automatic setups and dashboards that keep field work moving and make results easy to share
Published by Elshad Safiyev1, Sona RZAYEVA2, Rashida KARIMOVA3, Azerbaijan State Oil and Industry University (1, 2, 3) ORCID: 1. 0009-0005-4971-1721; 2.0000-0001-7086-9519
Abstract. This article discusses the importance of diagnostics of electrical equipment in thermal power plants to ensure the reliability of power systems. Electrical equipment is a key component in the production and transmission of electricity, and its reliable operation is essential to prevent emergency situations and ensure stable operation of power systems. The article discusses diagnostic methods and technologies used to assess the condition of electrical equipment, as well as identify potential problems. The importance of regular maintenance and monitoring of electrical equipment is emphasized to prevent failures and increase the reliability of power systems.
Streszczenie. W artykule omówiono znaczenie diagnostyki urządzeń elektrycznych w elektrowniach cieplnych dla zapewnienia niezawodności systemów elektroenergetycznych. Urządzenia elektryczne są kluczowym elementem wytwarzania i przesyłu energii elektrycznej, a ich niezawodne działanie jest niezbędne, aby zapobiec sytuacjom awaryjnym i zapewnić stabilną pracę systemów elektroenergetycznych. W artykule omówiono metody i technologie diagnostyczne stosowane do oceny stanu urządzeń elektrycznych, a także identyfikacji potencjalnych problemów. Podkreśla się znaczenie regularnej konserwacji i monitorowania urządzeń elektrycznych dla zapobiegania awariom i zwiększania niezawodności systemów elektroenergetycznych. (Znaczenie diagnostyki urządzeń elektrycznych w elektrowniach cieplnych dla zapewnienia niezawodności systemów energetycznych)
Keywords: infrared thermography, ultrasound diagnostics, thermal imagers, monitoring system, diagnostics. Słowa kluczowe: termowizja w podczerwieni, diagnostyka ultradźwiękowa, kamery termowizyjne, system monitorowania, diagnostyka.
Introduction
Electrical equipment plays a key role in the operation of thermal power plants, providing power supply, process automation, safety and equipment control. It is used to supply electricity to all components of the installation, including security, control and monitoring systems. Automation of processes such as fuel regulation, temperature and pressure control is carried out using electrical systems. Electrical equipment also plays a role in ensuring plant safety through emergency shutdown, fire extinguishing and equipment condition monitoring systems [1]. In modern installations, energy-saving technologies and electrical-based energy management systems help reduce energy consumption and improve overall system efficiency. Thus, electrical equipment is an integral part of thermal power plants, ensuring their stable, safe and efficient operation.
Equipment failures in thermal power plants can have a serious impact on production processes and safety. Firstly, they can lead to a decrease in productivity or a complete shutdown of the installation, which in turn can cause losses in energy production and a decrease in the efficiency of the entire system. This can result in increased downtime, lost revenue, and increased equipment recovery costs.
The impact of equipment failures on safety is also extremely serious. Failures can disrupt the normal functioning of safety systems such as fire extinguishing systems, emergency lighting, gas leak prevention systems, etc. This creates potential dangers for workers, the environment and society as a whole. In some cases, equipment failures may be associated with emergency situations, such as accidents with the release of harmful substances or fires, which threaten not only the safety of personnel, but also the surrounding area and population.
Thus, equipment failures in thermal power plants have serious consequences for both production processes and safety, and require careful monitoring, maintenance and updating of equipment to prevent negative consequences [2-5].
Problem setting
Visual methods for checking equipment condition.
Visual methods are indispensable for maintaining equipment functionality and ensuring operational safety in various industries. Engineers rely on these techniques to visually inspect equipment for signs of wear, damage, or irregularities, while also considering environmental factors. For instance, they meticulously scrutinize surfaces for cracks, corrosion, leaks, or other indicators of potential issues.
Moreover, comparing the current state of equipment to established standards is another vital aspect of visual inspection. Engineers assess characteristics like color, shape, size, and position, aligning them with prescribed safety and efficacy criteria. For instance, in examining a piping system, engineers meticulously look for signs of play, cracks, or leaks, comparing them against predetermined thresholds.
Incorporating specialized equipment, such as infrared thermal cameras or ultrasonic flaw detectors, further enhances visual inspection capabilities. These tools enable the detection of latent problems that may elude normal visual scrutiny. By swiftly pinpointing potential malfunctions, engineers can intervene preemptively, mitigating the risk of serious incidents or accidents.
Using Thermal Imaging Cameras to Detect Overheating.
Thermal imaging cameras serve as invaluable tools for detecting overheating in various systems, including thermal power plants. These cameras utilize infrared radiation to visualize temperature variations across object surfaces. Overheating often signals underlying issues like poor connections, overload, component wear, or cooling system inefficiencies.
Engineers leverage thermal imaging cameras to swiftly scan equipment, pinpointing areas of elevated temperature that may signify trouble. For instance, heightened temperatures at electrical connections could indicate overloads or inadequate contacts, while overheating on pipe surfaces might signal heat transfer or cooling system issues. By promptly detecting such anomalies, engineers can proactively address potential problems, averting serious damage or accidents.
In essence, the use of thermal imaging cameras for overheating detection proves highly effective in diagnosing equipment conditions within thermal power plants. This proactive approach enables the timely identification of potential issues, thereby preempting adverse consequences and ensuring operational integrity.
Application of ultrasonic flaw detectors to detect cracks and defects.
Ultrasonic flaw detectors play a pivotal role in identifying cracks and flaws within diverse materials and structures, including equipment found in thermal power plants. These devices harness ultrasonic waves to penetrate materials, gauging the time taken for wave reflections from internal imperfections. By utilizing ultrasonic flaw detectors, even minuscule cracks and defects, alongside inclusions, pores, or density alterations, can be detected.
In the realm of thermal power plants, these flaw detectors are deployed to assess the integrity of materials utilized in crucial components like boilers, piping, and tanks. They excel in identifying imperfections that may escape visual detection, swiftly highlighting potential issues such as fatigue cracks, corrosion, or structural alterations.
Ultrasonic flaw detectors offer several advantages, including heightened sensitivity across a spectrum of defects, the capability to conduct in-depth examinations, and their non-intrusive nature, ensuring equipment integrity and safety. Incorporating such defect detection methodologies into maintenance protocols is vital, fostering prolonged service life and secure operation of equipment within thermal power plants.
Monitoring and diagnostic systems based on IoT (Internet of Things) and data collection.
Monitoring and diagnostic systems leveraging IoT (Internet of Things) technology and data collection are pivotal in enhancing the efficiency, reliability, and safety standards of thermal power plants. By employing sensors, data acquisition devices, and interconnected networks, these systems ensure continuous monitoring of equipment performance and environmental conditions.
IoT systems enable real-time data collection and transmission to remote servers for analysis and processing. This facilitates prompt responses to fluctuations in equipment condition, enabling the timely identification of potential issues and accident prevention. For instance, IoT systems can monitor parameters like temperature, pressure, vibration, and substance levels in cooling systems or fuel tanks.
Moreover, IoT-based monitoring and diagnostic systems harness machine learning algorithms and big data analysis to predict equipment conditions. This proactive approach optimizes maintenance schedules, offers early fault warnings, and minimizes plant downtime.
Examples of practical application
Diagnostics of turbines, generators and transformers.
Diagnostics of turbines, generators and transformers in thermal power plants is an important maintenance step and ensures the reliable operation of these key components. For turbines, such diagnostics include checking the condition of the blades, rotor, casing, seals and bearings to identify wear, damage or other problems that may affect their operation and efficiency. For generators, it is important to diagnose the stator and rotor windings, insulation, cooling system, bearings and other key components to identify potential problems such as short circuits, insulation defects or wear. And for transformers, diagnostics include checking the condition of the windings, insulation, cooling system, oil level and other parameters to identify problems such as short circuits, oil leaks or thermal anomalies.
Various methods and technologies can be used to diagnose these components, including visual inspection, temperature measurement, oil analysis, ultrasonic testing, vibration analysis, thermal imaging and others. For example, thermal imaging can be used to detect overheating in the internal components of turbines, generators and transformers, while ultrasonic testing can detect hidden defects in windings or bearings [6-8].
When checking electric motors, you need to pay maximum attention to the following elements:
• bearings – assess their defectiveness by temperature; • ventilation ducts – check their permeability; • windings – make sure that there are no turn short circuits.
An example of a thermogram of electric motors is shown in Figure 1.
Fig.1. Example of thermogram of electric motors
Inspecting a generator using a thermal imager involves several key steps to ensure thorough evaluation:
1. Checking Stator Steel for Defects: The thermal imager is used to examine the stator steel for any irregularities or defects that may affect performance or safety.
2. Determining Device Temperature and Identifying Abnormal Heating Zones: By measuring temperatures across the device, abnormal heating zones can be identified, which may indicate potential issues such as overload or insulation breakdown.
3. Assessing Solder Insulation Surface Temperature: The thermal imager is utilized to determine the temperature of the solder insulation surface, helping to detect any areas of overheating or degradation.
4. Measuring Brush Heating Temperature: Brush heating temperature is determined using the thermal imager, allowing for the identification of any excessive heat generation that could lead to brush wear or malfunction.
5. Evaluating Thermal State of Excitation System Devices: The thermal imager is employed to assess the thermal condition of excitation system devices, helping to detect any abnormalities or overheating that may affect performance or reliability.
By following these steps and utilizing thermal imaging technology, engineers can effectively inspect generators, identify potential issues, and take preventive measures to ensure optimal performance and safety [9-12].
Detection and analysis of defects in electrical circuits and connections.
Detection and analysis of defects in electrical circuits and connections within thermal power plants are crucial for maintaining equipment safety and reliability. These defects, including overheating, corrosion, insulation faults, breaks, and short circuits, can arise from factors like improper installation, material degradation, or environmental exposure.
A variety of methods and technologies are employed for defect detection and analysis. These encompass visual inspections, resistance measurements, thermographic and thermal imaging assessments, ultrasonic testing, insulation testing, among others. For instance, thermal imaging cameras are effective in identifying overheating in connections or circuit components, indicating potential issues like improper contact or overload. Ultrasonic inspection can detect hidden defects such as cracks or corrosion that may elude visual inspection.
Innovative solutions like DJI’s thermal imaging drones are increasingly utilized worldwide to enhance productivity and safety in defect detection (Figure 2). These drones are equipped with specialized thermal imaging cameras featuring lenses that capture infrared frequencies. The thermal sensor and image processor within the camera, housed protectively, detect infrared wavelengths and convert them into electronic signals. The resulting thermographic image, or thermogram, displays a color map representing various temperature values, aiding in defect identification and analysis [13-16].
By leveraging these advanced technologies, thermal power plants can effectively detect and analyze defects in electrical circuits and connections, ensuring enhanced safety and reliability of equipment operations.
The temperature sensor, also known as a microbolometer, plays a critical role in thermal imaging technology. Its intricate structure enables it to absorb infrared energy and subsequently generate a thermogram based on its measurements.
Analyzing the data acquired through diagnostics of electrical circuits and connections enables the identification of problematic areas, the assessment of their severity, and the implementation of corrective measures. Regular diagnostics and maintenance of these components are imperative to prevent accidents, ensure personnel safety, and uphold the reliable operation of thermal power plants.
Monitoring the insulation and thermal conditions of equipment stands as a pivotal aspect of maintenance and safety protocols in thermal power plants. Adequate insulation of electrical systems is essential for averting short circuits and potential accidents. Additionally, thermal control of equipment aids in preventing overheating and damage to components, thus safeguarding the integrity and efficiency of plant operations.
Fig.2. Drones with thermal imaging from DJMonitoring of insulation and thermal conditions of equipment
Insulation monitoring is typically conducted through regular measurements of insulation resistance using specialized testers. This practice enables the detection of potential insulation defects such as damage, moisture ingress, or contamination, which can lead to current leaks and safety hazards. By promptly identifying such issues, corrective actions such as replacing damaged insulation sections can be taken.
Equipment thermal monitoring involves continuous measurement and analysis of temperatures in critical system components and assemblies. Thermal imaging cameras, thermocouples, thermistors, and other temperature measurement tools are utilized for this purpose. Continuous thermal monitoring facilitates the early detection of potential problems such as overheating, inadequate cooling, or thermal imbalances, allowing for appropriate interventions such as optimizing cooling systems or adjusting equipment operating modes.
Overall, monitoring insulation and thermal conditions in thermal power plant equipment is vital for accident prevention, ensuring personnel safety, and maintaining operational reliability. Preventing emergencies and mitigating risks in thermal power plants relies on a multifaceted approach:
1. Monitoring and diagnostic systems, including IoT systems, thermal imaging cameras, and ultrasonic flaw detectors, enable the swift identification of potential issues before they escalate into emergencies. Regular maintenance and diagnostics allow for the early detection and resolution of problems, preventing further escalation.
2. Adherence to strict safety regulations and standards, alongside comprehensive safety protocols, forms the foundation for accident prevention. This entails providing regular training to staff on equipment safety procedures and maintaining workplace safety protocols.
3. Utilizing modern technologies and equipment that adhere to high safety standards and ensure reliable operation is crucial. Regular equipment updates and modernization efforts help minimize the risk of emergencies and uphold safety levels in thermal power plants.
By integrating these approaches, thermal power plants can effectively mitigate risks, prevent accidents, and ensure the safety and reliability of their operations
Conclusions
Increasing the service life of equipment and reducing maintenance costs are crucial objectives for ensuring the efficient and reliable operation of thermal power plants. Achieving these goals involves employing various strategies and methods:
Regular Maintenance and Preventive Maintenance: Conducting regular inspections, replacing worn parts, lubricating, and adjusting mechanisms help prevent premature wear and prolong the service life of equipment.
Utilization of Modern Technologies: Implementing innovative solutions such as IoT-based monitoring and diagnostic systems enables quick identification and resolution of potential problems, thus extending equipment service life and reducing maintenance costs.
Personnel Training and Compliance with Operating and Safety Regulations: Ensuring personnel are well-trained and adhering to safety protocols minimizes equipment damage and reduces the likelihood of accidents, ultimately increasing equipment service life and reducing maintenance costs.
Optimizing Production Processes and Improving Energy System Efficiency: Enhancing economic efficiency and competitiveness in thermal power plants involve various strategies:
Introduction of Modern Control and Automation Systems: Optimizing production processes, managing equipment operating modes, and maximizing resource utilization through automation reduces energy, raw material, and labor costs while improving process accuracy and reliability.
Utilization of Modern Technologies and Equipment: Incorporating renewable energy sources such as cogeneration units, solar panels, and wind generators increases energy efficiency, reduces dependence on traditional energy sources, and lowers energy costs while mitigating environmental impact.
Implementation of Advanced Management and Production Planning Methods: Optimizing production processes and enhancing power system efficiency through data analysis and modern management techniques identify opportunities for process improvement and cost reduction, thereby enhancing productivity and competitiveness in the energy market.
In summary, increasing equipment service life and reducing maintenance costs in thermal power plants are achieved through a combination of regular maintenance, utilization of modern technologies, personnel training, and adherence to safety regulations. Similarly, optimizing production processes and improving energy system efficiency involve leveraging modern technologies, automation, renewable energy sources, and advanced management methods to enhance productivity, efficiency, and competitiveness in the energy sector.
REFERENCES
[1]. Lina Y, Lia C, Yanga Y, Qina JF, Sub X, Zhanga H, Zhangao W, “Automatic Display Temperature Range Adjustment for Electrical Equipment Infrared Thermal Images”, The 4th International Conference on Power and Energy Systems Engineering 2017, CPESE 2017, 454-459, Berlin, Germany, 25-29 September 2017. [2]. Afonin AV, Newport RK, Polyakov VS, et al., “Fundamentals of Infrared Thermography”, Mining Science and Technology, p. 240, Moscow, Russia, 2004. [3]. S.A. Bazhanov, “Infrared Diagnostics of Electrical Equipment of Switchgears”, Mining Science and Technology, p. 76, Moscow, Russia, 2000. [4]. Y. Luo, Zh. Li, H. Wang, “A Review of Online Partial Discharge Measurement of Large Generators”, MDPI Energies, Issue 10, Vol. 11, No. 1694, pp. 1-32. Basel, Switzerland, October 2017. [5]. M. Sasic, C. Chan, “Using Measurement Results to Diagnose the Condition of High-Voltage Rotating Machines Part 1 and 2”, Industry Topics, Iris Power, pp. 1-9, Canada, 2019 [6]. Mohamed ES. Development and analysis of a variable position thermostat for smart cooling system of a light duty diesel vehicles and engine emissions assessment during NEDC. Applied Thermal Engineering 2016; 99: 358–372. https://doi.org/10.1016/j.applthermaleng.2015.12.099 [7]. Rzayeva SV, Ganiyeva NA, Piriyeva NM. Modern methods of diagnostics of electric power equipment. The 19th International Conference on” Technical and Physical Problems of Engineering 2023; Т. 31. 105-110. [8]. S.V. Rzayeva, N.A. Ganiyeva, N.M. Piriyeva Modern approaches to electrical equipment diagnostics. International Journal on “Technical and Physical Problems of Engineering” (IJTPE), Issue 58, Volume 16, Number 1, March 2024, pp.182-189 [9]. Rahimli I, Bakhtiyarov A, Abdullayeva G, Rzaeva S, Application Of Optical Current Sensors In Electric Substations Przeglad Elektrotechniczny 2024; 2, pp. 132-134 DOI: 10.15199/48.2024.02.26 [10]. Rahimli NI, Rzayeva SV, Aliev HZ. Diagnostics and monitoring of power transformers. Universum: technical sciences 2022; (11-6 (104)): 32-35. [11]. Alimamedova S.J. Some issues in diagnostics of electric motors. Vestnik nauki 2024; 4.1(70): 528-535. DOI 10.24412/2712-8849-2024-170-528-535 [12]. Mammadov N. Analysis of systems and methods of emergency braking of wind turbines. International Science Journal of Engineering & Agriculture 2023; 2(2): 147-152/ doi: 10.46299/j.isjea.20230202.14 [13]. Pirieva NM, Guseinov ZH. Fault Analysis in Power Transformers. Vestnik nauki 2023; T4, 7(64), 297-304. DOI 10.24412/2712-8849-2023-764-297-304 [14]. Mamedova GV, Pirieva NM, Shirinova MCh Diagnostics of power transformers. Internauka: electron. scientific magazine 2023; 6(276), 31-34 DOI:10.32743/26870142.2023.6.276.352720 [15]. Walentynowicz J, Krakowski R. Modeling of the higher pressure cooling system for transport vehicles engines. Transport Problems 2010; 5(4): 39-47. https://doi.org/10.20858/tp.2010.5.4.5. [16]. Agarwal N, Chiara F, Canova M. Control-Oriented Modeling of an Automotive Thermal Management System. 2012 Workshop on Engine and Powertrain Control, Simulation and Modeling. The International Federation of Automatic Control RueilMalmaison 2012; 23-25: 392-399. https://doi.org/10.3182/20121023-3-FR-4025.00051
Source & Publisher Item Identifier: PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 100 NR 9/2024. doi:10.15199/48.2024.09.23
Published by Nijat Mammadov1, Najiba Piriyeva2, Shukufa Ismayilova3, Azerbaijan State Oil and Industry University ORCID: 1. 0000-0001-6555-3632; 2. 0000-0002-8990-1803
Abstract. The purpose of this study is to analyze the lightning protection systems of wind turbines. One of the main causes of damage to wind electric installations is lightning strikes. In order to reduce the likelihood of damage to these installations, it is necessary to improve the performance that is associated with lightning protection. Early shutdown of a wind turbine to protect against lightning damage can result in a reduction in utilization that must be prevented. Therefore, in order to improve the lightning protection characteristics of wind power installations, it is necessary to study the mechanism of lightning strikes. In this article, two main systems are considered for the analysis of lightning protection systems for wind turbines. This is a grounding system and a system for detecting thunderclouds near wind turbines. This article provides some grounding measures that include modifying the receptor, laying an insulated cable on the down conductor to increase the likelihood of a lightning strike on the receptor. The article also presents a scheme of the formation of thunderstorm leaders and response leaders emanating from the wind turbine blade receptors. The characteristics of wind rotation speed during normal operation, before and after a lightning strike are given. The main types of lightning detection devices are considered. The article presents modern methods and technologies for lightning protection of wind turbines.
Streszczenie. Celem pracy jest analiza systemów ochrony odgromowej turbin wiatrowych. Jedną z głównych przyczyn uszkodzeń instalacji wiatrowych są uderzenia piorunów. Aby zmniejszyć prawdopodobieństwo uszkodzenia tych instalacji, należy poprawić wydajność związaną z ochroną odgromową. Wcześniejsze wyłączenie turbiny wiatrowej w celu ochrony przed uszkodzeniami spowodowanymi przez wyładowania atmosferyczne może skutkować zmniejszeniem wykorzystania, któremu należy zapobiegać. Dlatego w celu poprawy właściwości odgromowych instalacji wiatrowych konieczne jest zbadanie mechanizmu uderzeń pioruna. W tym artykule rozważono dwa główne systemy do analizy systemów ochrony odgromowej turbin wiatrowych. Jest to system uziemiający oraz system wykrywania chmur burzowych w pobliżu turbin wiatrowych. W tym artykule opisano pewne środki uziemiające, które obejmują modyfikację receptora i ułożenie izolowanego kabla na przewodzie odprowadzającym, aby zwiększyć prawdopodobieństwo uderzenia pioruna w receptor. W artykule przedstawiono także schemat powstawania liderów burzowych i liderów reakcji pochodzących z receptorów łopatek turbiny wiatrowej. Podano charakterystykę prędkości wirowania wiatru w czasie normalnej pracy, przed i po uderzeniu pioruna. Rozważono główne typy urządzeń do wykrywania wyładowań atmosferycznych. W artykule przedstawiono nowoczesne metody i technologie ochrony odgromowej turbin wiatrowych. (Badania systemów ochrony odgromowej instalacji wiatrowych)
Keywords: wind electric installation, lighting strike, thunderstorm, receptor, wind rotation speed, grounding system, overvoltage Słowa kluczowe: instalacja elektryczna wiatrowa, uderzenie pioruna, burza, odbiornik, prędkość wiatru, instalacja uziemiająca, przepięcie
1. Introduction
Wind turbines on the horizon hold the potential not only for clean energy production, but also for possible lightning related risks. Providing effective lightning protection for wind turbines becomes a prerequisite to ensure the safety, reliability and long life of these economic activity systems. A thunderstorm is a dynamic meteorological process involving various atmospheric phenomena such as strong winds, rain and lightning. During a thunderstorm, intense movements of air masses occur, accompanied by the formation of clouds and precipitation. However, one of the most exciting and dangerous aspects of a thunderstorm is the lightning. Lightning is a phenomenon associated with electrical discharges in the atmosphere. It occurs as a result of the accumulation and discharge of electrical charge between clouds or between a cloud and the ground. Within the thunderstorm region, various charge zones are formed, where negative and positive charges accumulate in the upper and lower layers of the atmosphere, respectively.
It is important to understand that intense vertical air movements occur inside a thundercloud. Rising currents of warm, moist air can collide with falling currents of cold air, which contributes to the formation and strengthening of an electrical charge. This process leads to further formation of lightning discharges within the cloud and between the cloud and the ground. Sharp objects, such as tall buildings, trees, or mountain peaks, can greatly amplify the electric field and attract lightning. When lightning strikes such objects, energy is rapidly released, which can cause fires, destruction or injury. Modern technologies make it possible to develop structures that are resistant to lightning strikes, such as wind turbines. Manufacturers use a variety of methods to minimize the risk of lightning damage, including conductive mesh, lightning rods, and special grounding systems. However, lightning remains a powerful and unpredictable phenomenon, and the risk of a lightning strike cannot be completely eliminated. It is important to take appropriate precautions during thunderstorms to minimize the risk of injury and damage from lightning [1, 2, 6].
Lightning protection for wind turbines is an important aspect of their safety. Wind turbines taller than 30 meters are more susceptible to lightning strikes because they protrude above the surrounding area and attract lightning strikes. Here are a few precautions and lightning protection systems that can be applied to wind turbines:
1) Grounding: The grounding system is the basis of lightning protection. Wind turbines must have reliable grounding, including deeply driven ground electrodes connected to the main structures of the wind turbine.
2) Lightning rods: Installation of lightning rods helps to attract lightning and discharges past the very structure of the wind turbine. Lightning rods may consist of metal rods or conductors installed at a height and near the wind turbine.
3) Surge protection system: In addition to lightning rods, wind turbines must have surge protection systems to prevent damage to electrical equipment in the event of a direct lightning strike.
4) Lightning protection management: Wind turbines must be equipped with lightning protection management systems that can detect the presence of lightning in the vicinity and take appropriate action, such as shutting down electrical equipment or switching to backup power.
5) Regular maintenance: It is important to carry out regular maintenance of lightning protection systems, including checking the grounding, lightning rods and control systems, to ensure that they are working properly.
Let’s consider the general lightning protection system for wind turbines. The electronic systems in the nacelle body are sensitive to voltage surges or current pulses. Therefore, the body of the gondola, if conductive, can be used as a Faraday cage that protects electronic systems. If the material of the gondola is non-conductive, to create a Faraday cage, it is necessary to use metal meshes from a metal that has a high electrical conductivity. Distribution cabinets, control cabinets and connecting cables located in the nacelle must also be shielded.
Fig.1. Scheme of the formation of thunderstorm leaders and response leaders emanating from the wind turbine blade receptors
Receptors are receivers that are used to protect the blades of a wind turbine, located at the end of the blades of a wind turbine (Fig.1). The lightning current that enters the receptor is diverted through the descending wire in the blade, gondola, tower and through the grounding system goes into the ground. The blade rarely suffers serious damage if lightning hits the receiver, but the receptor is likely to be damaged if the lightning current is high. For such cases, receivers made of materials with high thermal conductivity have been developed. Not all lightning strikes in wind turbines rush to the receptor. There are cases when lightning penetrates the blade and the discharge reaches the descending conductor inside the blade. This discharge method damages the surface of the blade and, in some cases, can shatter it, resulting in damage to the wind turbine caused by parts of the delaminated blade. Therefore, a lightning protection system for the blades is needed to minimize the possibility of such damage. Some lightning strikes the surface of the blade and directly penetrates the downward conductor inside the blade, resulting in severe damage to the blade. In addition, it has been recorded that lightning strikes to wind turbines are concentrated in areas located approximately 5 mm from the end of the blade. To avoid this, all metal parts are treated with an insulating coating. Some blade manufacturers have developed blades that use insulated wires as down conductors internally. This reduces the likelihood of a lightning strike in the area near the receptor [5, 8-11].
Wind turbine operation before and after a lightning strike. The performance of a wind turbine before and after a lightning strike can vary significantly depending on the damage caused to the structure and its components. Before a lightning strike, the wind turbine operates within normal operating parameters. The blades rotate under the influence of the wind, driving a generator to produce electricity. Control systems monitor wind speed and automatically adjust turbine operation for optimal operation under design conditions. After a lightning strike, the condition of a wind turbine can change significantly. Damage can affect a variety of components, including the blades, electrical system, control equipment, and other parts of the turbine. If the damage was minimal and limited to mechanical components only, the wind turbine can continue to operate with relatively few changes. However, if the electrical system or control components are damaged, the operation of the wind turbine may be impaired. In some cases, the turbine may be disabled to prevent further damage or to ensure the safety of maintenance personnel. After a lightning strike, a thorough inspection and damage assessment must be carried out to determine the extent of the restoration work and ensure the continued operation of the wind turbine is safe [3, 4, 7]. Figure 2 shows the characteristics of wind rotation speed on normal operation, before lightning strike and after lightning strike.
Fig.2. Characteristics of wind rotation speed on normal operation, before lightning strike and after lightning strike
2. Materials and Methods
Grounding system. The grounding system of a wind turbine (Fig.3) plays a key role in ensuring safety and protecting the equipment from lightning strikes and surges. It consists of a series of grounding conductors and electrodes that direct electrical current from structures and equipment to the ground. When lightning strikes a receiver, such as a wind turbine blade, the grounding system provides an efficient path for the lightning current, directing it to the ground. This prevents equipment damage and minimizes the risk of fire or electrical shock.
Fig.3. Grounding system for wind electric installations
Key components of a grounding system include grounding fixtures at the base of the tower or pole, as well as additional grounding devices, such as ring or deep electrodes, that are installed in the ground around the base of the structure. This creates a low ground resistance, which allows lightning current to be effectively discharged and prevents the rise of ground potential around the wind farm. Additionally, the wind turbine grounding system may include monitoring equipment to monitor the condition of the grounding. This allows any grounding problems to be quickly identified and corrective action taken, thereby reducing the likelihood of equipment damage and ensuring personnel safety. Moreover, wind farm design engineers take into account factors such as local climate conditions and geological features when designing the grounding system. This allows you to adapt the design and location of grounding elements to specific operating conditions, providing optimal protection against lightning and surges.
Overall, a wind turbine’s grounding system is an essential component for ensuring safe and reliable operation during thunderstorms and lightning, and its effectiveness has a direct impact on the protection of equipment, personnel and the environment [12-15].
Lightning detection devices. There are four main types of lightning detection devices:
These devices use current sensors that measure lightning current and detect when a wind turbine has been struck by lightning.
Tower type solenoid coil. It is usually installed in a lightning detection device. When lightning strikes a wind turbine, the equipment detects a transient magnetic field created by the lightning current flowing through the installation tower. Due to the low cost and ease of installation, this type of device is the most popular, but it has its drawbacks. If lightning does not hit the wind turbine itself, but in the areas surrounding it, then a voltage appears between the output terminals of the solenoid coil. This voltage may exceed the detection threshold, the device may incorrectly detect both wind blow and installation blow. Manufacturers of this type of equipment have raised the detection threshold to reduce the number of such errors, but the problem still persists.
Coil Rogowski tower type. The coil is placed around the tower and is used as a sensor that detects the lightning current flowing through the tower. The sensor does not respond to lightning strikes in the areas adjacent to the wind turbine, which means it allows you to more accurately determine the presence of a lightning strike in the wind turbine. Due to the wide frequency band from 0.1 Hz to 0.96 MHz, the coil can collect lightning current parameters related to turbine damage, such as the maximum lightning current and electric charge. This type of device is expensive. In recent years, functional limitations have been introduced, so its price has come down [16-18].
Rogowski coil (for ground wire). The coil is installed on the ground wire of the grounding system and detects the shunt current when lightning strikes the wind turbine, thereby revealing that the turbine has been struck. Before using the equipment, it is necessary to determine the relationship between the lightning current flowing through the wind turbine and the shunt current flowing through the ground wire on which the coil is installed. Based on this dependence, the detection threshold is set. It must be taken into account that the wind turbine has power electronics and other devices that create noise and in many places constant noise is superimposed on the ground line. Therefore, it is not advisable to use this type of equipment when the noise current exceeds the current threshold.
Rogowski coil (for descending conductor). The coils are attached to the descending (from the receptors) conductors in the blades. When lightning strikes, a current is detected in the wind turbine and it is possible to determine which blade was struck. There are, however, some drawbacks. First, the sensors are installed in the rotating section of the wind turbine, which means that the measuring equipment is required to be attached to the blade conductor inside and fixed at the hub. Secondly, in some wind turbines, the hubs and blades are sealed, so it is necessary to develop a way to communicate between the transmitters installed in them and the receiver located in the nacelle [19-22].
Systems for detecting thunderclouds near wind turbines. Storm cloud detection systems near wind turbines are critical to ensuring the safety of personnel and equipment. Here are some of the main components and methods that can be used in such systems:
1. Lightning detection radar systems: Installation of specialized radar systems that detect lightning near wind turbines. These systems can accurately determine the location of lightning and its proximity to an installation.
2. Meteorological sensors: Placement of meteorological sensors on wind turbines to continuously monitor atmospheric parameters such as pressure, humidity, temperature and wind speed. This data can be used to detect approaching thunderclouds.
3. Equipment condition monitoring systems: Using equipment condition monitoring systems that can detect electromagnetic interference caused by lightning and automatically take measures to protect the equipment.
4. Automated control systems: Development of automated control systems that can automatically adjust the operation of wind turbines in the event of lightning activity, for example, reducing the speed of rotation of the blades or temporarily stopping the operation of the installation [23-25].
There are two main approaches to detecting thunderclouds near wind turbines. The first approach is based on measuring the electrostatic field around the turbine. As a thunderstorm approaches, this field increases. Research has shown that there is a relationship between this electrostatic field and the likelihood of lightning striking a turbine, and in 85% of cases the plant can be shut down before a lightning strike if the field threshold is determined accurately. However, reducing the threshold value may reduce the likelihood of lightning striking the turbine, but will lead to increased downtime and reduced turbine utilization. The second approach is based on a lightning location system. This system monitors lightning strikes near wind turbines and detects approaching thunderclouds. This method can detect thunderstorms that originate far from the turbines, giving more time to decide whether to shut down the plant. However, for winter thunderstorms, which rarely result in lightning strikes but can develop quickly near turbines, the first method, based on measuring localized electrostatic fields, may be more effective [26-28]. The purpose of these systems is to ensure reliable operation of wind turbines in lightning conditions, minimize risks and increase the safety of personnel and equipment.
3. Conclusion.
In the absence of a lightning protection system for a wind turbine, a lightning discharge may result in damage to control systems, electrical systems, blades, and other mechanical parts. Therefore, when designing wind turbines, it is necessary to carefully consider and identify potential risks and pay special attention to the lightning protection system. For this purpose, an efficient system has been developed using numerical analysis of the electromagnetic field in the grounding structure. In addition, an automatic detection system is proposed that accurately detects lightning strikes, determines the level of damage from the strike, and tells whether the turbine needs to be repaired, whether it is able to continue working. Studies have been carried out to detect the approach of thunderclouds, to determine the probability of impact in wind turbines. The proposed measures make it possible to improve the performance of protection of wind turbines from lightning.
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Source & Publisher Item Identifier: PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 100 NR 9/2024. doi:10.15199/48.2024.09.38
Published by 1. Marwan R. Abed, 2. Oday A. Ahmed, 3. Ghassan A. Bilal, University of Technology Iraq, Baghdad, ORCID: 1. 0000-0002-1257-2810; 2. 0000-0001-7214-3412; 3. 0000-0002-5090-103X
Abstract. When implementing a DC distribution network, it is much easier to integrate distributed energy sources than it is with an ac grid. Furthermore, the efficiency and reliability of DC distribution networks outperform those of AC systems. The protection of the DC distribution networks, particularly the interruption and isolation of short-circuit fault currents, is still a major problem. Traditional mechanical and hybrid circuitbreakers for DC fault protection have the disadvantage of being sluggish to operate, necessitating the use of high-power equipment. The Solid-State Circuit Breaker is the best choice for quick fault interruption. Since they employ thyristors, Impedance-Source Circuit Breakers are among those that provide automated fault detection and clearing. In this work, a new DC circuit breaker based Δ-impedance source configuration is proposed for medium and low voltage DC distribution networks to provide the bidirectional operation which has also become the general requirement for the modern power system. The proposed topology uses three-coupled windings with one capacitor and four SCR thyristors to facilitate the bidirectional operation. MATLAB/Simulink environment is used to analyze and evaluate the performance of the proposed DC circuit breaker to protect the 240V DC microgrid configuration with different fault conditions and locations. The results obtained prove that the proposed DC circuit breaker has a good performance in protecting the DC distribution networks.
Streszczenie. Wdrażając sieć dystrybucyjną prądu stałego, znacznie łatwiej jest zintegrować rozproszone źródła energii niż z siecią prądu przemiennego. Ponadto wydajność i niezawodność sieci dystrybucyjnych prądu stałego przewyższa sieci prądu przemiennego. Ochrona sieci dystrybucyjnych prądu stałego, w szczególności przerywanie i izolowanie prądów zwarciowych, nadal stanowi poważny problem. Tradycyjne mechaniczne i hybrydowe wyłączniki automatyczne do ochrony przed zwarciami prądu stałego mają tę wadę, że działają wolno, co wymaga użycia sprzętu o dużej mocy. Wyłącznik półprzewodnikowy to najlepszy wybór do szybkiego przerywania zwarć. Ponieważ wykorzystują tyrystory, wyłączniki źródła impedancji należą do tych, które zapewniają automatyczne wykrywanie i usuwanie usterek. W tej pracy zaproponowano nową konfigurację źródła Δ-impedancji opartą na wyłączniku prądu stałego dla sieci dystrybucyjnych prądu stałego średniego i niskiego napięcia, aby zapewnić dwukierunkową pracę, która stała się również ogólnym wymogiem dla nowoczesnego systemu elektroenergetycznego. Proponowana topologia wykorzystuje trzy sprzężone uzwojenia z jednym kondensatorem i czterema tyrystorami SCR, aby ułatwić pracę dwukierunkową. Środowisko MATLAB/Simulink jest wykorzystywane do analizy i oceny wydajności proponowanego wyłącznika prądu stałego w celu ochrony konfiguracji mikrosieci 240 V DC z różnymi warunkami i lokalizacjami uszkodzeń. Uzyskane wyniki dowodzą, że proponowany wyłącznik prądu stałego ma dobrą skuteczność w zabezpieczaniu sieci dystrybucyjnych prądu stałego. (Zabezpieczenie mikrosieci DC za pomocą ΔCB)
Keywords: DC microgrid protection; Coupled inductor; DC circuit breaker; Bidirectional operation; Impedance source circuit breaker Słowa kluczowe: ochrona mikrosieci prądu stałego; cewka sprzężona; wyłącznik prądu stałego; Działanie dwukierunkowe
Introduction
The twentieth century began with a critical discussion over the form of energy supply and its essential elements. When Nikola Tesla with George Westinghouse argued for Alternating Current (AC) while Thomas Edison argued for Direct Current (DC). It was evident that the generation of DC power was restricted to a low voltage, and the voltage drop was a key concern. As a result, Edison’s power plants had to be used locally, which meant that loads had to be near the generating stations. The success of this fundamental milestone in the history of electricity notably ushered in the era of central power generation (power plants) and the global spread of AC transmission and distribution systems. In addition, power plants fuelled by fossil fuels (gas and coal) have risen to prominence as a source of electricity. To this time, AC power systems have lasted for even more than a century, and AC loads have ruled the market. However, high energy prices, as well as a lack of funds to build new big power stations with long-distance transmission networks, are some of the limitations to meet rising energy demand. Furthermore, ageing power system infrastructures, global warming, increased awareness of restricted power generation resources, higher power consumption requirements, and growth in the use of DC loads due to improvements in power electronics all indicate that transformation of the existing energy system is unavoidable [1, 2].
DC sources have been subjected to many developments causing an increment in the efficiency and live time of these sources, also the use of various DC loads, and the use of energy storage devices have led the way to use the of DC microgrids (DC MG). Harmonic, Ferranti, and skin effects are essentially non-existent in the DC-MG. As a consequence, DC MG will be better suited for new power systems than AC MG. The DC-MG idea may be viewed as a master foundation for using Smart Grid (SG) technologies [3]. The main problem in these DC MG is that the zerocrossing point is not present, so modern protection devices are needed to limit and interrupt the high fault current rapidly without producing sparks [4, 5].
The traditional mechanical DCCBs have many disadvantages such as Low current interruption abilities, slow response time, and low durability [5, 6], so a faster solid-state DCCBs have been suggested, these breakers provide a higher reliability and longer lifetime. The main disadvantage of such types of DCCBs are the demand for an additional forced commutation and sensing elements, which cause an increase in the circuit complexity and cost and also the high on-resistance (Ro) of the semiconductor switches [4-9].
The Impedance source DCCB is suggested as a faster response that isolates faults in microseconds and has an automatic turn-off because of its natural commutation principle [5, 10, 11].
In [11] produced the first unidirectional impedance source DCCB, consisting of one thyristor (SCR) and two capacitors and inductors which had been arranged as a cross shape. The absence of a common ground in the cross DCCB is solved by introducing the series ZCB in [10, 12]. Other research is done to reduce the reflecting current to zero and reduce the size and response time using coupled inductors in DCCBs as in [13]. In [14, 15] producing a symmetrical bidirectional ZCB with coupled-inductors. In [16, 17], a unidirectional Gamma DCCB (ГCB) was present. Also, in [18-22] presented the T-shape DCCBs (TCB). In [23-25] introduced a Y-shape DCCB (YCB), which consisted of a single capacitor and three coupled-inductors. The most important advantage of this configuration is the higher reflected current gain which produced by the secondary windings, as well as the three inductors’ turn ratios.
In this paper, a new symmetrical bi-directional with delta-shape coupled-inductors (ΔCB) is used in the protection of a DC MG, the following sections will introduce the new circuit breaker and test the protection of a 240V DC MG.
Configuration of the suggested ΔCB
A new circuit breaker with three coupled inductors configuration, in which the inductors are connected in a delta shape, is introduced as a new impedance source CB. It also consists of a single capacitor and four SCRs arranged in two back-to-back switch pairs, as shown in Fig.1. The direction of power flow in the ΔCB is selected by the two switches in the gate circuit S1 and S2 as shown in Table.1.
Fig.1. The suggested ΔCB configuration
Table.1. Switches states of Gate circuit
.
Table.2. The values of the parameters of the proposed ΔCB
.
Operation principle of the ΔCB
During steady state, the power flows from V1 to V2 through T1, L1, L2, L3, and T3, as shown in Fig.2. While the power flows from V2 to V1 through T4, L1, L2, L3, and T2 during opposite power flow direction, as illustrated in Fig.3. In the event of a transient situation, such as a short circuit fault or under sudden load change, the capacitor will act as the source that fed the transient current through the three delta-coupled inductors.
Fig.2. Power flow direction in case of steady state (V1 to V2)
Fig.3. Power flow direction in case of a steady state (V2 to V1)
Fig.4. Transient current direction during a fault condition
As shown in Fig.4, these inductors also act as a channel for the reflected current. If this reverse current is equal to a certain value of the forward current, it will force the thyristors to turn off immediately, causing an interruption to the source current.
Input-to-output current response
By driving the current transfer relation of the ΔCB from the three loop equations, So the input-to-output current relation is shown in Eq.(1):
Where: Zc: The total impedance of the capacitor By using the parameters in Table.2 to plot the bode plot of this relation, as shown in Fig.5:
Fig.5. Input-to-output Frequency response of ΔCB
The figure shows a negative amplitude and higher value than the amplitude in low frequencies (steady state) with 180⁰ in phase. This reverse current will cause in a decrement in the first thyristor current making it lower than latching current, so the thyristor will turn-off causing in an interruption in the circuit breaker.
Simulation Results
The ΔCB should be used to protect a DC microgrid (DCMG) from a short circuit fault. A MATLAB tool is used in this test. The simulation type is discrete of 5µs sampling time. A hybrid power supply system is constructed from three power sources: a connected AC grid, wind energy, and solar panels. The battery bank is 24v and used for transient cases during the changing from source to source and in an emergency. Every single source of the three power sources is regulated by a controller in order to provide a continuous supply to the load [26]. The sequence of the power source work in this simulation:
1. AC grid: From 0s to 1.5s. 2. Solar panel: From 1.5s to 3s. 3. Wind turbine: From 3s to 4s.
The schematic diagram of the used DCMG is shown in Fig.6. The bus voltage of the DCMG is 250V and the load consists of four parallel loads 30Ω, 20Ω, 20Ω, and 30Ω (the total load is equal to 6Ω), the load is connected to the DC bus.
Fig.6. Schematic diagram of the selected DCMG
Check the System Protection Under Fault in Parallel to Load
a) The CB is in series with the load
The system is tested under normal operation and records the voltage and current of each power source, bus voltage, and load current (Ibus=ILoad). The simulation time is 5s. The steady-state results are obtained Fig.7.
Fig.7. The steady-state waveforms of the IBus, VBus, PBus, VGrid, irradiation, wind speed, and battery SOC.
Three different fault cases will be tested, as follows:
The first fault case: By inserting the fault after one second from a run during the period of the AC grid supply source, The AC is converted to DC through the rectifier and the inductive filter, and the load current shows the isolation of the breaker in about 10µs as shown in Fig.8 (Ibus=ILoad), and the other results are obtained as shown in Fig.9.
The second case: By inserting the fault after two seconds from the simulation run during the PV panel (solar panel) supply source period, Also, the load current shows the isolation of the breaker in about 10µs as shown in Fig.10, and the results are obtained as shown in Fig.11.
Fig.8. The load current of the DCMG during the first case (normal and zoomed figure).
Fig.9. The first case waveforms of the ILoad, VLoad, VGrid, PV irradiation, wind speed, and battery SOC
Fig.10. The load current of the DCMG during the second case (normal and zoomed figure)
Fig.11. The Second case waveforms of the ILoad, VLoad, VGrid, PV irradiation, wind speed, and battery SOC
Fig.12. The load current of the DCMG during the third case (normal and zoomed figure)
Fig.13. The third case waveforms of the ILoad, VLoad, VGrid, PV irradiation, wind speed, and battery SOC
The third case: By inserting the fault after three seconds from a run during the period of the wind turbine and its rectifier as a supply source, the load current shows the isolation of the breaker in about 10µs as shown in Fig.12, and the results are obtained as shown in Fig.13.
b) The CB is in series with the rectifier of the AC Grid
The ΔCB is connected in series with the filter of the AC grid, as shown in Fig.14. The fault occurs after 0.5 seconds, and the source current of the ΔCB interrupted after 4.1ms with an overshoot during transient, as shown in Fig.15. The delay in isolation time and the increment in the current overshoot are because of the ripple in the rectified power and the effect of the inductor used as a filter.
Fig.14. The schematic diagram of the selected DCMG with ΔCB
Fig.15. The source current waveform of the AC-grid rectified under fault
Adding a capacitor in parallel with the input of this ΔCB of 220µF will illuminate the overshoot problem, and the isolation time will be reduced to 35µs, as shown in Fig.16.
Fig.16. The source current waveform of the AC-grid rectified under fault by adding an input capacitor
Fig.17. The source current of ΔCB in case of step load change
Conclusion
MATLAB/Simulink environment is used to analyze and evaluate the performance of the proposed DC circuit breaker to protect the 240V DC microgrid configuration with different fault conditions and locations. The results prove that the proposed DC circuit breaker is well at protecting the DC distribution networks. It shows a faster isolation time of 10µs and no negative part in the source current. That makes it the better choice for protecting DC microgrids. Finally, the result shows that ΔCB could distinguish between fault and step load change.
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Zha, “A New Efficient Bidirectional T-source Circuit Breaker for Flexible DC Distribution Networks,” IEEE Journal of Emerging and Selected Topics in Power Electronics, 2020. [23] H. Al-Khafaf and J. Asumadu, “Bi-directional Y-Source DC Circuit Breaker Design and Analysis Under Different Conditions of Coupling,” in 2018 9th IEEE International Symposium on Power Electronics for Distributed Generation Systems (PEDG), 2018: IEEE, pp. 1-6. [24] H. Al-khafaf and J. Asumadu, “Efficient Protection Scheme Based on Y-Source Circuit Breaker in Bi-Directional Zones for MVDC Micro-Grids,” Inventions, vol. 6, no. 1, p. 18, 2021. [25] H. Al-khafaf and J. Asumadu, “Y-source bi-directional dc circuit breaker,” in 2018 International Power Electronics Conference (IPEC-Niigata 2018-ECCE Asia), 2018: IEEE, pp. i-v. [26] D. SHAH. “DESIGN OF DC MICROGRID.” MathWorks. https://www.mathworks.com/matlabcentral/fileexchange/104120-design-of-dc-microgrid (accessed March 4, 2023).
Source & Publisher Item Identifier: PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 99 NR 11/2023. doi:10.15199/48.2023.11.25
Published by Dranetz Technologies, Inc., Case Study
Utility energy and demand costs have a direct impact on a company’s bottom line. In fact, a typical commercial or industrial facility can save from 10% to as much as 35% annually on energy costs by implementing a comprehensive energy management plan. And while each facility will require an organized approach to recognize those savings, facilities first need to understand their power consumption, location of major loads, electric demand usage patterns, and associated costs.
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The cost of energy is one of the most commonly mismanaged expenses, regardless of a company’s size or the industry represented. Often, energy is purchased in one department, consumed in another, with energy management systems operated and maintained by still another. Since each facility’s energy situation is dynamic and interdependent, it requires continuous monitoring and management action to avoid escalating costs. The web-based Signature System™ enables users to continuously monitor and store power consumption and quality information in real time-to capture those savings and improve profitability. Customers use the System for:
Power cost management: By looking at time of day, peak load and aggregated energy usage, customers can reduce their costs by rescheduling loads, making sure unneeded equipment is shut off when not in use, or installing energy-efficient equipment. Historical load profile data can be used to develop price/risk curves for evaluating energy purchase agreements.
Power factor: Many customers pay a penalty to the utility for inefficient use of energy, or the ratio of power consumed to power delivered. Monitoring is a necessary tool for understanding the processes within a facility that impact power factor, to improve energy efficiency and reduce or eliminate any surcharges.
Curtailment Rate Structure: Many customers have agreed to reduce (curtail) load at the request of their utility supplier in exchange for lower energy rates. Plus, non-essential loads can be shed or distributed generation brought on line to reduce consumption and/or participate in utility-sponsored demand reduction programs. Monitoring can help determine which loads on which circuits can be curtailed, as well as to certify compliance with curtailment requests.
Allocate Costs and Perform Activity-based Costing: Track energy-related costs by department, tenant or process. Use the Signature System’s Energy Usage and Expense Reporting AnswerModule® to track, compare and document those costs against scheduled rates, and from one time period to another.
Load profiling: Adding or upgrading equipment, computers and processes will impact the power requirements of a facility. Monitoring the existing load on circuits lets you know the impact of those changes and how much new load can be added to an existing circuit or facility.
Lost power costs: Improper load balance grounding may not always be obvious. By monitoring, lost energy can be identified and minimized.
Published by Dranetz Technologies, Inc., Technical Documents
he HDPQ Family of products have a number of trigger mechanisms for capturing different types of power quality phenomena. Most users are familiar with settings for sags and swells, but those typical limits usually don’t capture the “blinky lights” problems. While the Pst (perceptibility short term) parameter will indicate whether the voltage supply is likely to produce light flicker when the Pst is close or above 1, it doesn’t help determine where it comes from or what the source is since it is a ten-minute journal value. The graph below illustrates such.
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The voltage and current plots show that it is an increase in current over 100A that results in the voltage decreasing by 5-8V every 15 minutes. The rms variation limit for sags is set to 90% of the nominal 120V or 108V, so no sag was reported. In above example, the red dotted line is that sag limit. Yet the residents complained of “blinky lights” while the Pst does increase to 0.8 each time, not over 1.
The rms deviation transient trigger is one method to capture such as an event. However, there is a parameter that is included in the IEC and IEEE standards that was defined just for such disturbances. It is the RVC or Rapid Voltage Change. It looks for a sudden change in the voltage from one steady state value, waits for stability in any continued variations until stable at another steady state voltage value for 1 second or more. The delta change limit is typically set to 2-3%. Since the variation shown in the data above was 4-7%, this mechanism was ideal for capturing and reporting each time that it happened. An example at 22:189:54 is shown below. The rms deviations and wave shape triggers also captured the event, but they also triggered on other disturbances that weren’t part of the investigation, which produced extra data to sort through.
#39 10/03/2017 22:02:05.297 AV Misc at 0.8 Deg #40 10/03/2017 22:02:05.297 BV Misc at -179.1 Deg #41 10/03/2017 22:02:05.306 AVRmsDev Normal To High #42 10/03/2017 22:02:05.306 BVRmsDev Normal To High #44 10/03/2017 22:02:05.323 AVRmsDev High To Normal #45 10/03/2017 22:02:05.323 BVRmsDev High To Normal #48 10/03/2017 22:18:54.874 AV Misc at 0.7 Deg #49 10/03/2017 22:18:54.874 BV Misc at -179.0 Deg #50 10/03/2017 22:18:54.874 AVRmsDev Normal To High #51 10/03/2017 22:18:54.874 BVRmsDev Normal To High #52 10/03/2017 22:18:54.883 A Delta V RVC Rapid Voltage Change 0.175 Sec. #53 10/03/2017 22:18:54.883 B Delta V RVC Rapid Voltage Change 0.259 Sec.
The right tool for the right job has always been a wise adage. Setting the right tool up with the right limits on the right parameters to help solve the customer’s problems is an extension of that idea that can help get the answer quickly and clearly. By the way, the answer here was a common answer for such problems. The HVAC unit was causing the blinky lights.
Publised by Oleh HOLOVKO1, Adam KONIECZKA2, Adam DĄBROWSKI3, Politechnika Poznańska, Wydział Automatyki, Robotyki i Elektrotechniki (1, 2, 3) ORCID: 2. 0000-0002-0362-3006; 3. 0000-0002-9385-6080O
Abstract. This paper proposes a method for evaluating the efficiency of passive cooling systems of solar panels in a type of radiator using CFD simulations. The movement of air through the cooling system and the dependence of the thermal state of the radiator on its shape, wind speed, and ambient temperature were analyzed. A mathematical analysis was made that takes into account the average temperature drop of a solar panel connected to a ribbed heat sink. Experimental measurements of the temperature of the solar panel were performed.
Streszczenie. W artykule zaproponowano metodę oceny wydajności pasywnych układów chłodzenia paneli fotowoltaicznych bazujących na radiatorach z wykorzystaniem symulacji CFD. Przeanalizowano ruch powietrza w układzie chłodzącym oraz zależność temperatury radiatora od jego kształtu, prędkości wiatru i temperatury otoczenia. Przeprowadzono analizę matematyczną uwzględniającą spadek średniej temperatury panelu fotowoltaicznego połączonego z żebrowym radiatorem. Wykonano eksperymentalne pomiary temperatury panelu fotowoltaicznego. (Modelowanie systemów chłodzenia pasywnego paneli fotowoltaicznych).
Słowa kluczowe: panel solarny; wydajność paneli solarnych; radiator; symulacje CFD. Keywords: solar panel; efficiency of solar panels; heat sink; CFD simulations.
1. Introduction
According to [1], an increase in the installed capacity of photovoltaics in Poland amounted in 2021 to 3.7 GW. Data from the end of the first quarter of 2022 indicates the installed power of 9.4 GW. The global success of the solar industry is due to many factors but reduction of the cost of the generated electricity is crucial: according to [2] (Fig. 1), the cost of solar energy over the past 10 years has fallen 7.5 times.
Fig.1. Cost of solar energy (USD/MWh) compared to other energy sources in 2009‒2020 [2]
The second reason is versatility: from small housing systems to large enterprises. In addition, unlike fossil-fuel electricity generation, solar energy causes no environment damage.
The main task with the use of solar radiation is to increase the efficiency of solar panels. The efficiency of commonly used photovoltaic panels is between 17 and 24% [3]. Most commonly used solar cells use wavelength range of 250 to 1100 nm to generate electricity. The remaining radiation is reflected or absorbed by the cells as heat. The temperature of the solar panel is influenced by external climatic variables such as wind speed, humidity, atmospheric temperature and concentrated dust [4]. The heat emission from the roof surface also plays an important role. The absorbed heat may raise the panel temperature even up to 70‒80°C. The result is a significant decrease in the output power.
The amount of energy loss of photovoltaic modules as a result of overheating shall be determined during the production tests. The thermal power loss in different models of silicon-crystalline batteries (according to the manufacturers’ catalog data) is on average within the limits of 0.45 to 0.50%/°C. Thin-film (amorphous) solar panels are more resistant to temperatures. Their thermal loss performance is about 0.2–0.3%/°C [5]. A way to improve the performance of solar panels is to keep their temperature within the optimum range. This method will not only increase electricity generation but also extend the life of the modules, which currently stands at 25 years.
There are many ways to cool solar panels:
1) Active cooling is carried out by forced air or liquid in both the area of the panel itself and the heat exchangers installed on the panels [6]. Problems with the use of active systems are mainly related to: additional equipment, which, as a rule, is not agreed upon with the manufacturer and additional costs of calculations, installation, maintenance. When using liquid-cooled systems, there is a problem of maintaining the installation in the winter to avoid damage.
2) Passive methods include panel cooling using phase conversion materials, heat pipes and radiators: conventional and micro-channel heat exchangers, nanofluids, spectral filters, and thermoelectric, evaporative and radiation cooling [6].
The method of natural cooling has great potential, does not require energy supply and is reliable and simple. In [7], based on the modeling results, the area of an additional surface needed to compensate for the heating of a solar panel was calculated. The size of the additional surface area should be 5‒5.5 times the size of the solar cell. However, the performed calculations do not take the shape of the cooling surface and the relative direction of the wind into account.
According to [8‒11], the use of a passive cooling system in the form of a radiator (aluminum or copper fins mounted on the back of the solar panel) allows the average temperature of the solar panel to be reduced by 2 to 7°C, thus raise its efficiency by 2‒4%.
In [12, 13] the efficiency of a radiator with perforated ribs was considered, and in [14‒17], a study of inclined and complex-shaped ribs was carried out. Depending on the geometry of the structure and wind speed, the temperature of the solar panel decreases by 4‒12 degrees. It should be noted that the measurements and calculations in the mentioned works were carried out for specific locations of solar panels and cannot be applied to other places and conditions.
The degree of the temperature drop depends on the characteristics and location of the panel, stochastic climatic conditions, the design used and the material of the cooling system. In order to estimate the magnitude of the temperature drop of a photovoltaic panel achieved with a heat sink, a full detailed analysis of the airflow shall be carried out, taking the effect of gravity into account, the design of the heat sink, the position and orientation of the panel and other objects near the panel.
CFD (Computational Fluid Dynamics) method can be used for modeling active and passive cooling systems. This method needs numerical analysis to analyze and solve fluid flow problems. In papers [18–21] thermal analysis of the heat sink in the conditions of air convection was considered. In [19] the CFD simulation results were compared with experimental results. Heat transfer tests were carried out for various shapes of radiators (solid pin fins, perforated pin fins, solid flat plate, and perforated flat plate). The achieved results show that the base temperature for experiment is typically 6.05% to 9.52% higher than the base temperature of the CFD simulation. Therefore, the use of CFD software for modeling parameters of heat transfer in passive cooling of solar panels in real conditions can be reasonable.
Section 2 presents the methodology for estimating and theoretical calculations of the temperature drop of a solar panel with a passive cooling system depending on the type of heat sink and external conditions (wind direction and speed). For this purpose the CFD modeling software Solidworks Flow Simulation was used. It allows for performing a simulation of fluid flow, advanced thermal analysis, and study of heat exchange between the designed components and the predefined medium.
Section 3 presents experimental verification of the temperature dependence of a photovoltaic panel without cooling and with a passive cooling system in the form of a rib radiator on external climatic conditions. A thermal imaging camera was used for experimental testing.
A brief summary and conclusions are provided in Section 4.
Table 1. Selected theoretical and statistical models to determine the temperature of a photovoltaic cell
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2. Calculation of solar panel temperature and evaluation of effect of radiator shape on heat exchange efficiency
When calculating the temperature of the solar panel, the most influential factors are usually taken into account: the power of the solar radiation falling on the surface of the module, the ambient temperature and the wind speed. To determine the T୮ (temperature of the photovoltaic cell), various theoretical and statistical models have been proposed, determining the appearance, respectively [22‒28]. Table 1 shows commonly used T୮ calculation equations. However (according to [29]) depending on the chosen thermal model, the average error between the calculations and the measured value of the solar panel temperature can reach more than 30 percent.
The choice of a model and appropriate coefficients depends on the type of the panel and the conditions under which the panel is located. It can be determined from experimental data [30].
To analyze radiator performance, various ribbed radiators were modeled in Solidworks 3D CAD (2017), assuming that they are made of 5052-type aluminum alloy (thermal conductivity 140 W/mK (T=273K), density ‒ 2680 kg/m3 , specific heat ‒ 921 J/kg·K) [31].
During modeling, the following parameters were determined:
• P [W] ‒ total heat transfer capacity, • Q [W/m2] ‒ the amount of heat distributed by the radiator surface unit, • T [°C] ‒ initial temperature of the front surface of the heat sink, • Tm [°C] ‒ average temperature of the heat sink, • Tmin [°C] ‒ m
An example of the simulation obtained for a rib radiator is shown in Fig. 2.
Fig.2. Simulation of air flow and temperature distribution for a radiator measuring 35×75×100 mm (s=0.063 m2). Rib thickness 1 mm. Initial temperature of the front surface of the module T=60°C, ambient temperature Ta = 20°C. Wind direction along the Z axis. Wind speed v=5 m/s
Geometric dimensions of the heat sink affect the amount of dissipated heat. The purpose of the prepared tests is to perform a comparative analysis of heat exchange efficiency for the rib-type radiators with different rib heights ‒ L [mm].
Figure 3 summarizes the heat transfer efficiency of radiators of different shapes. The wind speed varied within 0‒ 20 m/s, the direction of air flow was perpendicular to the ribs at the rear, overheating of the front of the module in relation to the environment is 40°C.
Analysis of the dependence of the heat dissipation power on the surface of the radiator shows that under certain conditions the most efficient are radiators with a rib height of 20‒35 mm, providing a decrease in the module temperature on average from 5.74 to 11.8°C.
Compared to a flat plate of 5052-type aluminum alloy, the average heat dissipation power of the radiator increases 3.13 and 3.30 times, respectively. No further increase in the dimensions is recommended, since a significant part of the radiator does not participate in heat exchange with the environment.
Fig.3. Dependence of the size of the heat transfer capacity P [W] on the module surface for radiators with different rib heights L mm. Front panel temperature T=60°C, ambient temperature ‒ Ta =20°C, wind speed v=0‒20 m/s, wind direction along the Z axis
Further tests shall aim to determine the optimum position of the radiator relative to the wind direction at different initial temperatures of the front panel.
Analysis of the heat dissipation efficiency of an unshielded radiator Q [W/m2] (Fig. 4) shows that the most efficient system is one in which the flows are directed perpendicular to the radiator from the ribs (100%) or along the ribs (99%). Changing the wind direction – from the front of the photo module (direction Z) or perpendicular to the ribs (direction X) – causes a decrease in efficiency by 55% and 40%, respectively.
Fig.4. Dependence of the heat flux Q [W/m2] through the radiator surface 35×75×100 mm (s=0,063 m2) on the wind speed v [m/s], direction of the wind along the Z, Y, X axis). Initial temperature of the front surface T=40°C, T=60°C
The reason for such a decrease in the efficiency of the radiator as a cooling system is a significant decrease in wind speed in the area of the ribs. Figure 5 shows an example of the temperature distribution on the surface of the radiator and wind speed values in the radiator area.
In the next step, the dependences of the average temperature of the heat sink on the temperature difference between the heat sink and the surrounding air, wind speed and direction at the location of the panel were analyzed.
Figure 6 shows an illustrative calculation of the average heat sink temperature Tm[°C] for a radiator of dimensions 35×75×100 mm (s=0,063 m2) as a function of the initial temperature of the front surface T[°C] of the solar panel and wind speed. The influence of the thermal resistance between the solar panel and the radiator has not been taken into account.
Fig.5. Temperature distribution on the surface of the radiator and wind speed values in the radiator area of 35×75×100 mm (s=0.063 m2), initial wind speed v=5 m/s, wind direction along the X axis. Initial temperature of the front surface T=60°C
Fig.6. Dependence of the average temperature Tm [°C] of the module on the temperature T [°C] of the initial front surface and the wind speed v [m/s], (wind direction along the Z axis)
The magnitude of the decrease in the average temperature of the radiator can be described using a mathematical function. Considering the above simulation, the decrease in the average temperature dTm[°C] at different temperatures T[°C] of the initial front surfaces can be described using the proposed mathematical expression
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where σ, τ [°C ∙ s/m], λ[s/m] , m, n are determined using nonlinear regression of CFD simulation results.
Fig.7. Proposed mathematical expression and simulation dependence of the decrease of the average temperature dT [°C] for a radiator of dimensions 35×75×100 mm (s=0,063 m2) on the wind speed v (wind direction along the Z axis).
For example, when using a radiator with the rib thickness of 1 mm, the rib height of 35 mm, the distance between the ribs of 7.5 mm and the wind direction perpendicular to the radiator from the side of the ribs, the coefficients have the following values:
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Figure 7 for a radiator (35×75×100 mm s=0.063 m2) shows the simulation dependence and proposed mathematical expression of the decrease in the average temperature of the dT[°C] on the wind speed, the temperature T[°C] of the initial front surface.
3. Experimental verification of the temperature dependence of a solar panel with passive cooling system on external climatic conditions
The Sandia thermal model [23] was used to calculate the theoretical temperature, which corresponds to experimental data for a SYP-S05V5W solar panel used in research [31].
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The corresponding coefficients for a panel with a polymer substrate are: ε = 1 [K∙m2/W], a = -3.56, b = -0.075 s/m [23].
For an unshielded photovoltaic panel installed at an angle of 45°, taking into account the average wind direction in the Wielkopolska ‒ region south-west (at an angle of 45° at the rear of the solar panel), the coefficients in equation (1) (according to the next Solidworks Flow Simulation) determining the temperature decrease have the following values:
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The use of an additional cooling module reduces the average temperature of the entire system (panel and heatsink). In this work a proportional dependence of the change in the average temperature of the solar panel with the cooling system on the temperature of the illuminated side it is assumed. This change can be recorded with a thermal imaging camera.
An experimental verification of the temperature dependence of a photovoltaic panel without heat sink and with a passive cooling system on external climatic conditions was carried out on 17th January 2022 in a place with coordinates 52.4028 and 16.9537 [31].
A radiator with dimensions of (35×75×100 mm) was vertically placed on the right hand side of the solar panel type SYP-S05V5w, the angle of inclination of the panel was 40°, the wind speed during the day varied within the limits (6‒12 m/s). The temperature during the day varied between +2 and +11°C, with an average of +8°C. Information about the level of solar radiation, ambient temperature, and wind speed comes from the internet weather service [32] and additionally from the NASA MERRA-2 model [33].
A detailed temperature measurement of the panel and radiator was performed using the Seek Thermal ShotPRO thermal imaging device. Figures 8 and 9 show a photo of the solar panel taken with a thermal imaging camera.
Fig.8. Experimental verification of the temperature dependence of the solar panel with a passive cooling system (on the right side) and without them (on the left side) on external conditions ‒ front view
Fig. 9. Experimental verification of the temperature dependence of the solar panel ‒ rear view
The reduction of the mean temperature of the solar panel was calculated according to model (1) for the uncovered ribbed radiator (2).
Figure 10 shows theoretical calculations of the temperature of the panel without cooling and with a passive cooling system during the day and experimental measurements of the temperature of the solar panel using the above thermal imaging camera. Analysis of this chart shows a good match between the theoretical calculations and the experimental data.
Fig.10. Experimental verification of the temperature dependence of the solar panel with the passive cooling system on external conditions
The average temperature of the module during the day without a cooling system is 12.3°C, while with the cooling system the theoretical temperature is 11.0°C and the experimental temperature is 10.2°C.
4. Summary and conclusions
The use of Solidworks Flow Simulation to CFD modeling of solar panels allows one to evaluate the thermal state of photovoltaic panels and the effectiveness of a passive cooling system of any material, size and shape.
The coefficients σ, τ,λ, m, n in expression (1) determining the temperature drop using a radiator are depending on its design, the angle of inclination of the solar panel, the direction of the wind at the location of the panel, the distance to the limiting planes (other panels) and can be determined on the basis of the performed simulation.
Application of the proposed method for estimation of the thermal state of solar panels with a passive cooling system enables estimation of the energy production of solar panels installed in any location at a defined time.
The research was financed by a research grant 0211/SBAD/0223.
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[29]Yang R., Tiepolo G.,Tonolo E.,Junior J.,Souza M., Photovoltaic Cell Temperature Estimation for a Grid-Connect Photovoltaic Systems in Curitiba, Brazilian Archives of Biology and Technology. Vol.62 no.spe: e19190016, 2019 http://www.scielo.br/babt [30] Oh J., Pavgi A., Tamizhmani G., Determination of Empirical Coefficients and ΔT for Sandia Thermal Model: Dependence on Backsheet Type, proc. of 7th World Conference on Photovoltaic Energy Conversion (WCPEC-7), 2018, pp. 442-446. [31] Holovko O., Badanie efektywności energetycznej systemu pasywnego chłodzenia paneli słonecznych w klimatycznych warunkach regionu Kujawsko-Pomorskiego (Research on the energy efficiency of a passive cooling system for solar panels in the climatic conditions of the Kuyavian-Pomeranian region). master thesis, Wyższa Szkoła Gospodarki w Bydgoszczy, 2022. [32] MSN Weather, https://www.msn.com/pl-pl/pogoda/prognoza/inPoznan, access: 17.01.2022. 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Authors: M.Sc. Oleh Holovko, Poznan University of Technology, Institute of Automatic Control and Robotics, 3a Piotrowo Street, 61- 138 Poznań, E-mail: oleh.holovko@put.poznan.pl; PhD Eng. Adam Konieczka, Poznan University of Technology, Institute of Automatic Control and Robotics, 3a Piotrowo Street, 61-138 Poznań, E-mail: adam.konieczka@put.poznan.pl; prof. dr hab. Eng. Adam Dąbrowski, Poznan University of Technology, Institute of Automatic Control and Robotics, 3a Piotrowo Street, 61-138 Poznań, E-mail: adam.dabrowski@put.poznan.pl.
Source & Publisher Item Identifier: PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 99 NR 10/2023. doi:10.15199/48.2023.10.54
Published by 1. Stojan MALCHESKI1, 2. Sime KUZAREVSKI1, 3. Jovica VULETIC2, 4. Jordanco ANGELOV2, 5. Mirko TODOROVSKI2, Macedonian Transmission System Operator (MEPSO) (1), University of Ss. Cyril and Methodius, Faculty of Electrical Engineering and Information Technologies, Power Systems Department (2) ORCID: 1. /; 2. /; 3. 0000-0002-1009-7315; 4. 0000-0002-8749-6306;
Abstract. With the European aim to reduce the carbon footprint of the European energy sector by 2030 North Macedonia strategic framework set an ambitious goal to decommission its coal-fired power plants and replace them with renewable energy sources. The future flexibility and inertia states of the power system are assessed using a Monte Carlo market model calculation and multiple scenarios. On a mid-term planning horizon, this paper employs various metrics to derive a comprehensive estimation of the system’s inertia and flexibility requirements for the Macedonian power system.
Streszczenie. Realizując europejski cel zmniejszenia śladu węglowego europejskiego sektora energetycznego do 2030 r., w ramach strategicznych Macedonii Północnej wyznaczono ambitny cel likwidacji elektrowni węglowych I zastąpienia ich odnawialnymi źródłami energii. Przyszłe stany elastyczności i bezwładności 138 ystemu elektroenergetycznego są oceniane za pomocą obliczeń modelu rynkowego Monte Carlo i wielu scenariuszy. W horyzoncie planowania średniookresowego niniejszy138ystem138tt wykorzystuje różne wskaźniki w celu uzyskania kompleksowego oszacowania wymagań dotyczących bezwładności i elastyczności 138 ystemu dla macedońskiego 138 ystemu elektroenergetycznego. (Ocena elastyczności systemu elektroenergetycznego pod kątem przyszłych potrzeb w zakresie elastyczności: wysokopoziomowa metoda przesiewowa macedońskiego systemu elektroenergetycznego)
Keywords: power system flexibility, power system inertia, Monte Carlo method, long-term planning. Słowa kluczowe: elastyczność 138 ystemu elektroenergetycznego, bezwładność 138 ystemu elektroenergetycznego, metoda Monte Carlo, planowanie długoterminowe.
Introduction
In the coming years, the Macedonian power sector will be reshaped by the introduction of variable renewable energy sources (VRES), and the decommissioning of the lignite and oil power plants envisioned in the national strategy framework [1-3]. The current investment interest in VRES will result in an increased need for flexibility and the planed decommissioning’s will further reduce the system inertia. In the future, the flexibility and inertia needs will become dependent on the intermittency and weather dependency of VRES. This paper employs an analysis method based on a Monte Carlo market simulation that considers the randomness of system outages and the weather dependencies of VRES, hydro power plants and system loads.
There are multiple approaches to assess the flexibility and inertia of a power system varying in their complexity and computation resource requirements. So far, in academia and the power sector, there is no consensus on the best approach to tackle this problem since power system flexibility and inertia are system-specific [4]. This paper assesses the inertia and flexibility of the Macedonian power system based on the net load, which represents the difference between system load and non-dispatchable power generation [5-6]. Specifically, the research focuses on the following flexibility metrics: the renewable penetration index (RPI) and renewable energy penetration index (REPI) [7], the system probability for VRES curtailment (LORE) [8], and the system inertia metric SNSP [9].
The analysis and parameter calculations were performed using a regional perfect spot market model of Southeast Europe (SEE), where each country is modelled with one or multiple areas on the copper plate principle. This principle aggregates the total production and load on a power system level to the area(s) representing a given country and interconnects them with other neighbouring countries on NTC-based interfaces [10].
The paper is organized as follows: Section 2 gives overview of the market model and analysis scenarios, Section 3 explains the methodology, Section 4 presents the analysis results, and Section 5 summarizes the findings.
Market Analysis and Scenarios
The market model is for a mid-term time horizon (2030), based on the Energy Market Initiative Data Base (EMIDB) developed by USEA, [11], as well as the Pan-European Market Model Data Base (PEMMDB) and Pan-European Climate Database (PECD) developed by ENTSOE, [10]. The EMIDB contains data on a unit-by-unit basis for the thermal and hydropower plants, data for the installed capacity of VRES, data for demand, and data for the net transmission capacities on an interface level between the countries of SEE. The PECD dataset contains weather data for Europe from 1982 to 2016. Each country in the market model is represented by a single area where all generation technologies as well as the load time series are modelled on a system basis. Figure 1 shows the modelling scope of the market model.
Fig.1. Modelling scope of the Regional Market Model
Table 1 shows the installed capacity for each country in SEE while Table 2 shows the capacities for both directions on the NTC-interfaces between the countries.
Table 1. Installed capacities in MW for the six national scenarios
.
Table 2. NTC-interfaces capacity in MW
.
The Macedonian power system was modelled with multiple scenarios which differ in the installed capacity of thermal power plants (TPP), hydro power plants (HPP) and VRES. In total, six scenarios were analysed as a combination of conventional power plants (business-asusual (BC), investment in gas (wTPP), and pump-storage HPP (PSP) scenarios (wPSP)) and two VRES development profiles with high and low installed VRES capacity (H-RES and L-RES). Table 3 presents the installed capacity for all six development scenarios for North Macedonia (MK).
Table 3. Installed capacities in MW for the six national scenarios
.
Table 4. Flexibility parameters of the hydro and thermal power plants in MK
.
In this paper, for the flexibility analysis of the Macedonian power system, it is considered that only the HPP and gas-fired combined heat and power thermal power plants (CHP) can provide system flexibility. Table 4 presents the flexibility parameters for the Macedonian power system.
For each TPP in the model the marginal price (MP) was calculated using (1) as:
.
where VOM are the variable operation and maintenance cost in €/MWh, COE are the TPP CO2 emission rate in kg/Net GJ, FP is the fuel price in €/GJ, EFF is the TPP efficiency in percent, and the coefficient 3.6 is the conversion factor between GJ and MWh. COP is the CO2 price and in this model its value is 66 €/t. The economic parameters used in the market model for the TPPs are given in Table 5, [11].
Table 5. Economic parameters
.
For all other power plants, the production price is equal to the MP calculated by the simulation tool ANTARES. The Monte Carlo based optimization algorithm is explained in detail in [12]. The Monte Carlo optimization was carried out by simulating 700 Monte Carlo Years as a combination of 35 climatic years (CY) from PECD and 20 random outage patterns of the generators from EMIDB. CY represents a unique combination of the production of wind, solar, hydro and system load on hourly basis based on a historical weather pattern presented in PECD.
The forced outage rate in percent and the forced and planned outage duration in days for different TPPs are given in Table 6.
Table 6. Forced and planned outage rates per TPP fuel type
.
Flexibility and inertia metrics The assessment of power system flexibility and inertia is quantified by calculating the value of four metrics: RPI, REPI, LORE, and SNSP.
RPI is calculated in two steps as:
Step 1: Calculate RPI using (2) on hourly basis ∀CY as:
.
where W is the wind production, P is the photovoltaic production, and L is the system load.
Step 2: RPI is equal to the maximum hourly value from all calculated values in Step 1.
REPI is calculated in two steps as:
Step 1: Calculate REPI using (3) on annual basis ∀CY as
.
Step 2: Calculate REPI using (4) as:
.
The LORE metric is calculated based on six-step procedure:
Step 1. Calculate the Net Load (NL) ∀CY as:
.
where MR represents all the must-run generation1 in the market simulation.
Step 2. Calculate Net Load Ramp (NLR) ∀CY as:
.
and split the values calculated with (6) in two subsets, positive or upward net load ramps, NLR+(t), and negative or downward net load ramps, NLR–(t).
Step 3. Calculate the probability for VRES curtailment due to NL value being below zero as:
.
Step 4. Calculate the probability for VRES curtailment due to NLR+(t) being greater than the ramp-up capability of the Macedonian power system as:
.
where RU(t) is the remaining ramp-up capability of the power plants in Table 4 based on the dispatch results of the Monte Carlo simulation.
Step 5. Calculate the probability for VRES curtailment due to the absolute value of NLR–(t) being greater than the absolute value of the ramp-down capability of the Macedonian power system as:
.
where RD(t) is the remaining ramp-down capability of the power plants in Table 4 based on the dispatch results of the Monte Carlo simulation.
Step 6. Calculate LORE based on (8) as:
.
Finally, SNSP is calculated using (9) as:
.
where E is the exported power from the analysed system on hourly basis. SNSP is calculated for each hour, ∀CS.
Simulation Results and Discussion
From the analysis four metrics were calculated for the Macedonian power system: RPI, REPI, LORE, and SNSP, as described in Section 3.
Table 2 and Table 3 show the minimum, maximum, average value, and standard deviation for RPI and REPI, for the L-RES and H-RES scenarios respectively.
Table 7. RPI for the Macedonian power system
.
1 Must-run generation is all generation that must be dispatched each hour based on the hourly time-series with which the generation technology is modeled.
From Table 2 and Table 3 we can conclude that for both RES development scenarios the distributions are similar and cantered around the mean. The values of Table 3 for the H-RES scenario are in line with the European strategic framework where the mean value of the total production is around 49 % of the total load. Since high RPI values were noted for both L-RES and H-RES, in the future, to avoid VRES production curtailment, the Macedonian strategic framework should be reworked to consider different energy storage technologies or a shift from a fossil fuel-powered industry to an electricity-powered industry to increase the overall load profile [13].
Table 8. REPI for the Macedonian power system
.
Table 4 shows the loss of renewable energy estimation (LORE) for the six analysed scenarios as well as the results for the three different periods of interest. From the three period only Periods 1 and 2 have a the most significant impact. From the results we can conclude that the commissioning of new TPPs and a PSP is crucial to reduce the curtailment probability. Period 1 contributes the most significantly to LORE in the H-RES scenarios due to the relatively low demand profile. In the future, to lower the probability of RES curtailment storage technologies should be included in the energy and power mix.
Table 9. LORE for the Macedonian power system
.
It is important to note that the results from the market model did not show curtailment of VRES because of the well-developed interconnections in the region of interest, but at the same time, the installed VRES capacities in the neighbouring countries are quite modest, with exception to the installed capacities in Romania, Greece, and the rapid development VRES scenarios for MK.
Figure 5 shows the SNSP density for the analysed scenarios of the Macedonian power system. In comparison to the L-RES scenario has insignificant effect on system inertia compared to H-RES. In the H-RES scenarios we can note that system inertia get quite low for MK. Since all countries will follow a similar development trend it is expected that all countries in SEE will experience similar or worse trends. Consequently, each country in SEE as well as MK should focus on alternative ways for system inertia provision such as synthetic inertia provision from VRES power plants or subsidization of conventional power plants so they will provide system inertia during hours of high VRES production.
Conclusions
The flexibility analysis for the Macedonian power system was done using a probabilistic market-based calculation on an SEE market model. For MK, six national scenarios were analysed as a combination of three development scenarios for the conventional power plants and two VRES development scenarios. The flexibility was assessed by computing the RPI, REPI, LORE, and SNSP metrics.
Fig.2. Installed capacity per generation technology for the six Macedonian market scenarios
The introduction of VRES to the system leads to a high ratio between RPI and REPI as presented in Table 7 and Table 8, which is mainly driven by the low load levels during the periods where the VRES production is highest. Moreover, as shown in Table 9, the LORE parameter increases as more VRES are introduced to the system, which means that the risk for VRES curtailment in the future will be high. Since the flexibility needs are dependent on the regional evolution of the generation profiles in the neighbouring countries, it is expected that as more VRES are introduced, the curtailment risk in MK and the region will be even higher. To alleviate the possibility for VRES curtailment in MK and in SEE each country should focus on further electrification of the energy sector so to increase the base load. Furthermore, each TSO should focus on national and regional flexibility studies so to assess the need for flexibility means such as storage technologies.
The combination of decommissioning of conventional power plants with a rapid introduction of VRES in the generation mix will have detrimental effects on the system inertia as presented on Figure 2. Since the countries in SEE will follow similar trend to the one presented for MK it is expected that system inertia will drop on regional level. To increase system inertia the focus should be on development of national and regional markets so to facilitate synthetic inertia provision from the VRES power plants. Moreover, the feasibility of renumeration mechanisms for inertia provision from conventional power plants should be further explored for periods of high VRES production.
The metrics in this paper are relatively easy to compute, and their computation isn’t computationally intensive compared to other more detailed methods. On the other hand, the market simulations take 24 hour each due to the complexity of the model. The obtained results represent a first-of-a-kind screening of the future flexibility needs in the Macedonian power sector, and they pave the way for future developments in this field on a national level.
Acknowledgement – We express our sincere gratitude to United States Energy Association (USEA) for their unwavering support in the development of this work.
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Authors: Stojan M. and Sime K. are with the Macedonian Transmission System Operator, department of power system planning, ul. Maksim Gorki no.4, e-mails: stojan.malcheski- @mepso.com.mk and sime.kuzarevski@mepso.com.mk; Jovica V., Jordanco A. and Mirko T. are with the University of st. Cyril and Methodius, Faculty of Electrical Engineering and Information Technology, Rugjer Boshkovikj, e-mails: jovicav@pees-feit.edu.mk, jordanco@pees-feit.edu.mk, and mirko@pees-feit.edu.mk.
Source & Publisher Item Identifier: PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 99 NR 6/2023. doi:10.15199/48.2023.06.28
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