Switching Strategies of Single Stage Battery based Microgrid

Published by Sudhakiran Ponnuru1, Ashok Kumar R1, Jothi Swaroopan NM2, Annamalai University (1), RMK Engineering College (2), India

ORCID: 1. 0000-0002-5345-5709, 2. 0000-0001-6994-7591, 3. 0000-0001-7671-5190

Abstract. Renewable sources creates new opportunity when it is integrated with the microgrid increasing the energy efficiency of the system. This paper focuses on the adaptive control strategies which utilizes different energy management system for single stage PV based battery management system connected with the microgrid which operates on maximum power. The proposed system is carried in MATLAB/Simulink 2017B and its performance measures is demonstrated for different scenarios.

Streszczenie. Źródła odnawialne stwarzają nowe możliwości, gdy są zintegrowane z mikrosiecią zwiększając efektywność energetyczną systemu. Niniejszy artykuł koncentruje się na adaptacyjnych strategiach sterowania, które wykorzystują różne systemy zarządzania energią dla jednostopniowego systemu zarządzania baterią PV, połączonego z mikrosiecią, która działa z maksymalną mocą. Proponowany system jest realizowany w MATLAB/Simulink 2017B, a jego mierniki wydajności są demonstrowane dla różnych scenariuszy. (Strategie przełączania mikrosieci opartej na baterii jednoetapowej)

Keywords: Microgrid, Maximum Power Point Tracking, Battery, Voltage source converter.
Słowa kluczowe: mikrosieć, zarządzanie energią, baterias.

Introduction

The performance of the renewable system created major concern among the researchers to improve its functionality based on the available resources [1]. Due to fast depletion of the non-renewable resources [2], there needs a solution to move on with alternative sources of energy such as Wind Energy Systems (WES) [3], Fuel cellbased storage systems [4], Biomass Plants [5, 6], Solar Photovoltaic (SPV) systems [7-10] and Hybrid Power Plants [11]. The primary concern is to integrate microgrid [12] with these alternative distributed sources. These distributed sources are connected with the microgrid to supply power due to increasing demand which is a major concern in developing nations. Generally, microgrids are connected either in Standalone mode or Grid connected mode during operational condition [13]. Whenever distributed sources of energy are integrated with microgrid system, one has to ensure its reliability [3, 6] and adaptability [5] with the system until normal operation is carried out. Usage of power electronic devices across Point of Common Coupling (PCC) with the grid creates non-linear load. The quality of power delivered to the microgrid should be checked before it is connected. This can be attained by using different control strategies which are efficient for smooth functioning of the grid [14].

Fig.1. Grid Integrated System

Replacement of passive components with power electronic switches creates non-linearity in the system. This affects the quality of the power to be non-linear while delivering to the grid. Usually, the harmonic currents are generated using non-linear loads such as printers, Switched Mode Power Supply (SMPS) used in computers, electronic ballasts, refrigerators, Televisions and other switching devices. As per the latest regulation of IEEE standard 519- 2014 for Total Harmonic Distortion (THD) [15-17], when the operating bus voltage is around 69kV and below; the maximum individual harmonic component should be around 3% whereas the maximum THD should be around 5%. When the bus voltage is around 115kV and 161kV, then the maximum individual harmonic component should be around 1.5% whereas the maximum THD should be around 2.5%. When the operating bus voltage is above 161kV, then the maximum individual harmonic component should be around 1% whereas the maximum THD should be around 1.5%. These standards should be met in order to solve power quality problems while connecting with the grid.

Fig.2. Battery Storage System based microgrid

Another problem while integrating the renewable sources with the grid is output fluctuation. This is generally experienced in Wind Generation Systems (WGS) and Solar Photovoltaic System. Voltage fluctuation in WGS causes voltage swell and Sag during the switching operation of WGS. In SPV systems, the fluctuations are due to hotspots, irradiance and shading effect. Introduction of Battery storage system would reduce the problem of output fluctuations while connecting with the grid [18-20]. So, requirement of an adaptive control strategies using Battery Storage system would compensate the energy utilization to the grid [21]. These control strategies would help in maintaining stability of the grid. The performance of the grid is measured based on the two distinct modes of operation. The microgrid is generally operated either in Grid connected mode or Islanded connected mode [22]. When the microgrid is operated in grid connected mode, then it acts as a current controller which injects power based on the power generated to the main [23-25]. When the system has multiple distributed generators (DG) units are available in grid connected mode then droop control strategy is best suitable [26-28]. When the microgrid is operated in islanded connected mode, then it acts as a voltage controller where the voltage and frequency regulation of the system dominate by the microgrid during grid outage. Above Fig.1 provides the basic details of input sources connected with grid integrated system and Fig. 2 highlights the battery storage system based microgrid.

Performance and Control Strategies of Grid System

The performance analysis is carried based on the system behaviour under grid connected mode and islanded connected mode for different scenarios such as input variations, load variations, stability conditions, voltage ride through capability issues which are analysed by implementing it in MATLAB/ Simulink.

Grid connected mode

When the microgrid is operating in grid-connected mode, it acts as a current controller and feeds energy into the grid based on the energy generated. If the system has multiple DG’s available in online mode, it is best to adopt a voltage drop strategy. When the grid is available, an adaptive control of the grid and the battery will supply power to the load through the photovoltaic array. Voltage source converter uses photovoltaic cells to power the load, maintain network quality on the network side, and charge the battery. Maximum Power Point Tracking (MPPT) [29, 30] algorithm is used to monitor the changes in DC bus voltage across battery. When the photovoltaic output reaches below the threshold value, the remaining energy used to power the load will be obtained from the grid. when the overall power generation exceeds the load, the photovoltaic field starts to supply power to the grid and batteries.

Islanded connected mode

When the microgrid operates in islanded mode, it acts as a voltage controller. In the event of a grid interruption, the system voltage and frequency regulation will control the microgrid. In the islanded mode, the load is only borne by the photovoltaic field and the battery. The Point of Common Coupling (PCC) voltage and its frequency are maintained using voltage source converter. The battery is charging because the load is the same and the power generation has exceeded the load. Due to the corresponding change in the intermediate circuit voltage, the photovoltaic field operates in MPPT mode. Without changing the solar radiation, if the load is reduced to half of its value. If the power generation exceeds the load condition, then the intermediate circuit voltage will increase with time. However, the converter will start regulating constant current. As a result, the battery starts to absorb the excess energy, and the intermediate circuit voltage returns to its original value.

Simulation Results of Grid System

The proposed system uses control scheme which has the ability to operate the battery even during absence or presence of the grid. In this mode of operation, battery storage devices are used in order to maintain DC-link voltage constant. In case of battery storage devices are absent, then load follower can be used to operate under single stage PV based system. This paper focuses only the single stage battery based system. Incase if single stage PV based system is used, then MPPT algorithm is to be carried out using Perturb and Observe method (P&O) or any other optimization tools need to be used. In this case the battery voltage (Vbat) is ascertained and correlate with the measured DC link voltage (VDC).

Fig.3. Schematic approach of the system

The proposed system uses boost converter which is integrated with the voltage source converter (VSC) [31]. Pulse Width Modulation (PWM) technique [32] is used for control pulses for the boost converter. Proportional-Integral-Derivative (PID) controller [33] is used to obtain the current reference for the battery. The power quality issues across the grid side are controlled through VSC in grid connected mode. It also helps in battery charging during this mode. Point of common coupling voltage and frequency issues are controlled in Standalone mode. The availability of the grid is first checked by using passive method which is indicated in eq. (1)-(2)

.

During the availability of the grid, the grid voltage is sensed based on the templates generated by active and reactive power. Fig.3 indicates the schematic approach of the system and Fig. 4 provides the simulated diagram of the system. The proposed system uses Lease Mean Square (LMS) adaptive control algorithm in order to reduce power quality issues in the grid side. Voltage source converter are divided into two major subparts which as unit template estimation (ut) and terminal voltage estimation (Vt). Unit template estimation is calculated using template voltage (Vt) and grid voltage (vg) which is indicated in eq. (3)–(4).

.
Fig.4. Simulated diagram of the proposed system
Fig.5. Flowchart of MPPT algorithm

The flowchart of the MPPT algorithm is shown in Fig.5 which provides the switching operation of T1.The gating pulses for the switches S1-S4 for voltage source converter are generated by comparing the reference VSC current with actual VSC current.

Fig.6 indicates the simulated Phase-Locked Loop (PLL) circuitry done using MATLAB software and Fig.7 shows the simulated PID controller for tuning the system. Table 1 provides the information about the simulated specifications carried for the proposed system.

Fig.6. PLL circuitry of the simulated system

Table 1. System Specifications

.
Fig.7. PID controller values of simulated system
Fig.8. Simulated voltage and current response of Battery, Converter and Grid
Fig.9. Simulated results of grid voltage and current with active and reactive power components

The test results in Fig. 8 confirm the transmission of active energy from the battery side to the grid side. The test results include grid power (Pg), load power (PL) and photovoltaic solar energy. (Ppv), power supply VSC (Pvsc). The reactive power of the load is provided by the VSC, and the reactive power of the network is regarded as zero, so the system maintains a power factor of 1. As shown in Fig. 9, in the system under non-linear load, the THD of the line current is 5.2%, while the THD of the VSC current and the THD of the load current are 15.8% and 23.4%, respectively. Thus, the simulation results comply with power quality standard of IEEE 519.

An improved photovoltaic system with a single-phase grid based on the least squares method was implemented, and tests were conducted for various changes in solar radiation and load. The convergence speed of the proposed algorithm is higher than that of the standard LMS algorithm.

Conclusion

In the grid-connected mode and the islanded mode, the single-stage control of the micro-grid based on photovoltaic cells is introduced. The proposed control scheme makes it possible to control the photovoltaic field in the MPPT independently of the presence or absence of the network without using a special boost converter for the photovoltaic field. The analysis is only done in simulation from MATLAB/Simulink and the performance of the system looks to be satisfactory when connected with the grid.

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Authors: Sudhakiran Ponnuru, Research Scholar, Department of Electrical Engineering, Annamalai University, Chidambaram, Tamilnadu, India, sudhakiran.pon.annamalai@gmail.com
Ashok Kumar R, Professor, Department of Electrical Engineering, Annamalai University, Chidambaram, Tamilnadu, India, ashokraj_7098@rediffmail.com
Jothi Swaroopan NM, Professor, Electronics and Instrumentation Engineering, RMK Engineering college, Chennai, Tamilnadu, India, jothi.eee@rmkec.ac.in

Source & Publisher Item Identifier: PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 97 NR 9/2021. doi:10.15199/48.2021.09.26

Differential Relay Protection for Prototype Transformer

Published by Bashar M. SALIH, Mohammed A. IBRAHIM, Ali N. HAMOODI, Northern Technical University

Abstract. This paper represents the differential protection relay that used to protect the prototype-Terco power transformer. Matlab/Simulink is used to simulate the protection system. The power differential protection algorithm has been simulated and tested on a 2KVA power transformer under different faults. During normal operating conditions, current will flow through all phase of the power transformer within predesigned values which are appropriate to these elements rating and the faults can be classified as the flow of a massive current. the results signify suitable completion.

Streszczenie. W artykule przedstawiono zabezpieczenie różnicowe, które jest używane do ochrony transformatora mocy prototypu Terco. Algorytm zabezpieczenia różnicowego mocy został zasymulowany i przetestowany na transformatorze mocy o mocy 2 kVA przy różnych uszkodzeniach. W normalnych warunkach pracy prąd przepływa przez wszystkie fazy transformatora mocy w ramach wstępnie zaprojektowanych wartości, które są odpowiednie dla tych elementów znamionowych, a zwarcia można sklasyfikować jako przepływ prądu o dużej wartości. (Zabezpieczenie transformatora przy wykorzystaniu przekaźnika różnicowego)

Keywords: Power transformer, Differential protection, Fault conditions, Differential relay.
Słowa kluczowe: transformator mocy, zabezpppieczenie, przekażniki różnicowe

Introduction

Transformer protection methods are focused on differential protection and the attempts to improve the transformer protection, were based on a comparison between no fault and interior fault [1-2]. As the fault is occurred, transformer must be out of operating zone as fast as to prevent or to reduce potential destruction and coils harm. Repairing transformer damage associated cost is very high. Also, unplanned outage of a power transformer may be costly and economically useless. Accordingly, high demands are imposed on power transformer protection system. The differential protection wards the fault that happened in the protection zone can be determined by the differential protection and gives a correct action to disconnect the zone. Due to hefty sensitivity and austerely, these types of relays are used to protect the electrical equipment [3].

Differential protection technique which is basically consisting of differential relay depends on the fact that the input power of the transformer identical to the output power. At appropriate flow of the secondary currents, under standard conditions, there is no current running the coil of the relay. At each time of fault occurs, the currents equilibrium will not happen and the relay connections must be closed to give a trip order signal to activate the circuit breakers and separating the faulty mechanism [4].

The transformer is considered among the most main parts of electrical transmission system therefore, many types of prevention varieties and detecting arrangements must be established. The nature of the transformer function can not be isolated from the other equipment of electrical power transmission system. Therefore, the other parts and equipment and their functionality behave should be considered as it is in coupled and direct communicates with each other to prevent the overall transmission system from shut down or sever damage [5].

The researcher had chosen the Department Electrical Power Engineering Technology – Technical College of Engineering – Mosul / Northern Technical University (NTU), to apply a differential relay application in a laboratory prototype board.

Proposed methodology

The aim of this work is to study:

• Faults and classifications.
• Transformer protection.
• Select the protection zone.
• Discuss and compared the results for each type of faults.

Literature review

Raju and K. Ramamohan Reddy (2012), studied the reliability implement enhancement of power transformer based differential relay at internal and external fault. They applied Fourier series method for sine and cosine factors necessary for odd harmonics and fundamental. They concluded that the advanced scheme offers a good discrimination between the magnetizing and the inner fault currents [6].

The proposed method

The variance between the primary and secondary for (CTs) must be equal to zero, that means the transformer does not distinguish a fault. No lessees in the perfect power transformer, there for no operating current. Practically on eddy current and core losses appeared in the transformer [8-9].

Figure (1) illustrates single phase of a three-phase differential protection system (DPS). The protection equipment was enclosed by a couple of (CTs). Because of the (CTs) natural propensity, differential relay protection will not offer back up protection as a ratio to the rest of the system equipment, for this reason, this form of protection diagram is commonly favoring as a unit protection schedule. At no fault conditions, the current IP is similar to that get out from the protection equipment at each instant. When respecting the (CTs) A, the aviator wire of (CTs) A is lambing a current equal to:

(1) IAS = αA Ip – IAe

Also, for (CT) B, the equation as shown below:

(2) IBS = αB Ip – IBe

Fig.1. Differentials relay current at the time for out of zone.

Considering equal ratio of (CT) A and B, αA= αB=α, the Iop is:

(3) IAS = αA Ip – IAe

For out-of-zone, the operating current of the relay is extremely small, but doesn’t equal zero. When internally fault occurs (inside zone), the input current is differed from the output current and the differential relay send a trip to the circuit breaker as shown in figure (2) [10-12].

(4) Iop = α(IF1 + IF2) – IAe – IBe

Fig.2. Equivalent circuit of differential relay for single phase
Fig.3. Differential relay characteristics
Fig.4. Flowchart of the differential relay for single line

In terms of operation relay characteristics, its bias is used for power transformer protection. Figure (3) illustrates relationship between the differential current and the restring current (operation relay characteristics) [13].

When the ratio of the pickup is bigger than the bias setting therefor, this ratio value will fall in the tripping region (positive region), otherwise if this ratio is smaller than the bias setting then this ratio value located fall in the blocking region (negative reign) [14-15]. In the types of relay, the operation coil connected in parallel with restarting coils conflicting torque is obtained by the effect of restraining coils to the operating coils, when the faults occur out of zone, in this case the restraining torque so that the relay is not going to operate point. When fault occurs within the zone (internal fault), the operating torque will become higher than the bias torque and the relay will operate. The bias torque is adapted by conversion the number of turns on the restraining coils [16-17]. Figure (4) represents an algorithm of deferential relay protection for power transformer.

Materials and methods

Data for this work was taken from Sweden transformer company (terco company). A 2KVA power transformer as shown in figure (5) was depended in this work and its data are illustrated in table (1).

Fig.5. Terco-prototype 2KVA power transformer

Table 1. Terco power transformer (MV1915) specifications

.

The protection method that used for power transformer depends on the transformer ratings. Mechanical relays are widely used to protect the transformer. Differential protection provides the best overall protection. Biased current differential protection provides the best overall protection [18-19]. Matlab/Simulink environment is used to model the transformer protection system. The following components are the fault simulation model are given as:

• Three-phase source.
• Three-phase C.B.
• Three-phase transformer.
• Three-phase V-I measurement.
• Subsystem.
• RLC series branch.
• Scope
• Current measurement.
• Three-phase fault.

To design a relay protective scheme, a power transformer model is essential to produce the fault records that required adjusting the fault detection system [20-21]. The implementation is completed by using Matalb/Simulink environment.

Research method

Figure (6) shows the simulated conventional relay system. In which a 3-phase, 2KVA, 50 to 60 Hz, 230/2 * 66.5 V/phase transformer were used. The designated differential relay consists of two input signals Ip and Is, where, Ip and Is are the output currents of the measurements respectively. These two input signals would be distributed into three parallel paths in order to be analyzed. The second three signals of the secondary current will subtract from the first three signals at the primary current and the results obtained will be compared with the reference current by using comparator block [22- 23].

Fig.6. Modeling circuit of differential relay protection
Fig.7. Scheme of differential relay subsystem

After the comparator output signals go to the flip-flop latch, the output signals of the flip-flop latch will multiply by AND gate and the final signal send to circuit breaker. Figure (7) illustrates the contents of differential relay subsystem block [24-26].

Results and discussion

Case No.1: At no fault (normal operation):

The simulation results of voltages and currents for primary and secondary are shown in figures (8 – 11).

Fig.8. Primary voltage at no fault
Fig.9. Primary current at no fault
Fig.10. Secondary voltage at no fault
Fig.11. Secondary current at no fault

At normal cases, no fault occurred, the secondary voltage and current are at the designated operating values according to the transformer turn ration (2:1).

Case No. 2: External fault (out of zone):

The simulation results for differential relay output signal. At external fault occurs the primary and secondary currents are given in figures (12-14). A unit step function is applied to the three-phase fault icon.

Fig.12. Differential relay output signal
Fig.13. Primary current at external fault
Fig.14. Secondary current at external fault

At external fault, no trip signal sent from the differential relay to the circuit breaker because the fault occurred out of the transformer protected zone as the turn ratio is the same. This can be shown in figures (12-14).

Case No.3: Internal faults (inside zone):

The differential relay output signal when fault occurred at time 0.1 (sec) is given in figure (15).

Fig.15. Differential relay output signal

Line-to-ground fault:

The current signals of relay line-to-ground fault is shown in figure (16).

Fig.16. Current at line-to-ground fault

Line-to-line-to-ground fault:

The current signals of relay line-to-line-to-ground fault is shown in figure (17)

Fig.17. Current at line-to-line-to-ground fault

Triple-to-ground fault:

The current signals of relay triple-to-ground fault are shown in figure (18).

Fig.18. Current at three phase-to-ground fault

Line-to-line fault:

The current signals of relay line-to-line fault is displayed in figure (19).

Fig.19. Current at line-to- line fault

At internal fault, when fault occurred at 0.1sec as shown in figure (15), a trip signal delivered from the differential relay to operate the circuit breaker. As the circuit breaker be opened, the current will be zero after the fault time occurred. This can be shown in figures (16-19).

Conclusions

In this paper, the differential relay characteristics are simulated using Matlab/Simulink. The performance characteristics of differential relay were evaluated at a location with three phase faults, and also study the various faults that occur in the power transformer, such as L-G fault, L-L-G fault, L-L-L-G faults, L-L fault and L-L-L fault. MV1915 2KVA power transformer Sweden transformer company (terco company). The analysis and results demonstrate that the projected differential relay denotes a suitable solution. The proposed relay was capable to distinguish the no-fault and fault situations. From the results we conclude that the transient response for all type taken within same time and peak impulse value.

As shown from figures (13 and 14), when external (out of zone) fault occurred, the current wave form signals for the primary current are similar to that obtained from secondary current that due to no operation of relay and the crest value of the current in one phase reached approximately to 10A.

As shown from figures (18 and 19), the currents value in two phases after fault occurred in line-to-line-to-ground were equally (5A), but these values different in line-to-line case.

Acknowledgment: The authors would like to thank Northern Technical University -Technical College of Engineering / Mosul, to provide a simulation package for us to finish our work.

List of Symbols
CT: Current Transformer
αA: Ratio of (CT) A
IAe: Excitation current of secondary (CT) A
αB: Ratio of (CT) B
IBe: Excitation current of secondary (CT) B
Iop: Relay operating current
Id: Differential current
Ir: Restrain current
IF1: Primary fault current
IF2: Secondary fault current

REFERENCES

[1] Poljak, M., N. Kolibas, Computation of Current Transformer Transient Performance, IEEE Trans., vol. 3, no.4, pp. 1816, 2010.
[2] Usama Khaled, Mohamed Qais, Saad Alghuwainem, Abderrahmane Beroual, Security Enhancement of Differential Protection of Power Transformers Based on Second Order Harmonics, vol. 4, no. 1, 2017, pp. 9-15.
[3] P. N. Upadhayaya and V. H. Makwana, “Modelling & simulation of transformer biased differential protection scheme in laboratory environment,” 2017 Int. Conf. Intell. Comput. Instrum. Control Technol. ICICICT 2017, vol. 2018-Janua, pp. 68–73, 2018, doi: 10.1109/ICICICT1.2017.8342536.
[4] Ênio C. Segatto and Denis V. Coury, A Differential Relay for Power Transformers Using Intelligent Tools, IEEE Trans., vol. 21, no. 3, pp. 1154-1162, 2006.
[5] Ling Liu, Fault Detection Technology for Intelligent Boundary Switch, Archives of electrical engineering, vol. 68(3), pp. 657–666, 2019.
[6] Raju, K. Ramamohan Reddy, Differential Relay Reliability Implement Enhancement of Power Transformer, International journal of modern engineering Research, vol. 2, issue 5, pp. 3612-3618, 2012.
[7] Ihedioha Ahmed C., Differential Protection for Power Transformer Using Relay, International Journal of Trend in Research and Development, vol. 3(1), pp. 281-285, 2016.
[8] Mr. Jadhav Nilesh S., Prof. Thorat A. R., Design of a Differential Relay for 1000-kV Transmission Line using MATLAB, IEEE, pp. 1164-1168, 2013.
[9] Lubomir Sevov, Umar Khan Zhiying Zhang, Enhancing Power Transformer Differential Protection to Improve Security and Dependability, IEEE Transactions on Industry Applications, doi 10.1109/TIA.2017.2670525.
[10] Mladen Kezunovic, Yong Guo, Modeling and Simulation of the Power Transformer Faults and Related Protective Relay Behavior, IEEE Trans. on power delivery, vol. 15, no. 1, 2000.
[11] Armando Guzmán, Stan Zocholl, , Gabriel Benmouyal, Héctor J. Altuve, A Current-Based Solution for Transformer Differential Protection—Part I: Problem Statement, IEEE Trans. vol. 16, no. 4, 2001.
[12] Harjit Singh Kainth, Gagandeep Sharma, A New method for differential protection in Power transformer, Journal of Electrical and Electronics Engineering, vol. 9, Issue 2, ver. IV, 2014, PP 64-70.
[13] F. Namdari, S. Jamali, P.A. Crossley, Power differential based wide area protection, Electric Power Systems Research, 77 (2007) 1541–1551.
[14] Javad Azarakhsh, The Power Transformer Differential Protection Using Decision Tree, Bulletin de la Société Royale des Sciences de Liège, vol. 86, special edition, 2017, p. 726 – 738.
[15] Ashesh Mukeshbhai Shah, Bhavesh Bhalja, A New Adaptive Differential Protection Scheme for Tap Changing Power Transformer, International Journal of Emerging Electric Power Systems, doi: 10.1515/ijeeps-2015-0005, 2015.
[16] Abdulfetah Shobole, Mustafa Baysal, Mohammed Wadi, Mehmet Rida Tur, Protection Coordination in Electrical Substation Part-2 Unit Protections (Differential and Distance Protection) – Case Study of Siddik Kardesler Substation (SKS), Istanbul, Turkey, Journal of Science, GU J Sci 30(4): 163-178, 2017.
[17] M. Rasoulpoor, M. Banejad, A. Ahmadyfard, Discrimination between Inrush and Short Circuit Currents in Differential Protection of Power Transformer Based on Correlation Method Using the Wavelet Transform, doi: 10.5829/idosi.ijee.2011.02.04.3139.
[18] Fyodor Romanyuk, Ivan Novash, Mikhail Loman, Paweł Wegierek, Marek Szrot, Validation of Mathematical Model of Differential Protection, Przegland Elektrotechniczny, doi:10.12915/pe.2014.
[19] Taiying Zheng, Seung-Tae Cha, Yeon-Hee Kim, Peter A. Crossley, Sang Ho Lee, Yong Cheol Kang, Design and Evaluation of a Protection Relay for a Wind Generator Based on the Positive- and Negative-Sequence Fault Components, J Electr Eng Technol, vol. 8, no. 5, pp. 1029-1039, 2013.
[20] E. Ali, A. Helal, H. Desouki, K. Shebl, S. Abdelkader, O.P. Malik, Power transformer differential protection using current and voltage ratios, Electric Power Systems Research, doi: 10.1016/j.epsr.08.026 0378-7796, 2017.
[21] Bahman Bahmanifirouzi, Masoud Jabbari and Mehdi Nafar, A Sensitive Method for Identifying Winding Turn to Turn Faults in Power Transformer, Australian Journal of Basic and Applied Sciences, vol. 5(7), pp. 303-307, 2011.
[22] R. B. Dhumale, S. D. Lokhande, N. D. Thombare, M. P. Ghatule, Fault Detection and Diagnosis of High Speed Switching Devices in Power inverter. International Journal of Research in Engineering and Technology, vol: 04 issue: 02, pp. 253-257, 2015.
[23] Borivoje Nikolic, Vojin G. Oklobdzija, Vladimir Stojanovic, Wenyan Jia, Member, James Kar-Shing Chiu, Michael MingTak Leung, Improved Sense-Amplifier-Based Flip-Flop: Design and Measurements, IEEE Journal of Solid-State Circuits, vol. 35, no. 6, pp. 876-884, 2000.
[24] Burcu Sakallıoglu, Burak Esenboga, Tugçe Demirdelen, Mehmet Tümay, Performance evaluation of phase-shifting transformer for integration of renewable energy sources, Electrical Engineering, doi:10.1007/s00202-020-01011-9, 2020.
[25] Abdelkader Abdelmoumene, Rachid Bouderbala, and Hamid Bentarzi, Design and Evaluation of a DSP Based Differential Relay of Power Transformer, Algerian journal of signals and systems, vol. l, issue 1, pp. 69-78, 2016.
[26] Oluwagbade Z.V., Wara S.T, Adejumobi, I.A., Mustapha, A.O., Effect of Unified Power Flow Controller on Power System Performance: A Case Study of Maryland 132/33/11 kv Transmission Station, vol. 5, Issue 6, June 2015.

Authors: Bashar M. Salih, basharms_tecm@ntu.edu.iq. Mohammed A. Ibrahim, mohammed.a.ibrahim1981@ntu.edu.iq. Ali N. Hamoodi, ali_n_hamoodi74@ntu.edu.iq. Northern Technical University, Technical College of Engineering /Mosul.

Source & Publisher Item Identifier: PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 97 NR 6/2021. doi:10.15199/48.2021.06.30

Residual Current Devices in Installations with PV Energy Sources

Published by Stanislaw CZAPP, Gdańsk University of Technology. ORCID: 0000-0002-1341-8276

Abstract. The paper presents the principles of residual current devices (RCDs) application in photovoltaic (PV) installations. Provisions of standards in this regard are commented on, in particular, attention is drawn to the lack of obligation to use of RCDs in PV installations. The issue of the shape of the earth fault current and the level of leakage currents in such installations are discussed. These factors influence the selection of RCDs in terms of their rated residual operating current as well as the type of tripping characteristic.

Streszczenie. W artykule przedstawiono zasady stosowania wyłączników różnicowoprądowych (RCDs) w instalacjach fotowoltaicznych (PV). Skomentowano zapisy norm w tym zakresie, w szczególności zwrócono uwagę na brak obowiązku stosowania takich zabezpieczeń w instalacjach PV. Omówiono problematykę kształtu prądu ziemnozwarciowego oraz poziom prądów upływowych charakteryzujący te instalacje – są to czynniki wpływające na dobór znamionowego prądu różnicowego oraz typu charakterystyki wyzwalania wyłączników różnicowoprądowych. (Wyłączniki różnicowoprądowe w instalacjach z fotowoltaicznymi źródłami energii).

Keywords: photovoltaic installations, protection against electric shock, residual current devices.
Słowa kluczowe: instalacje fotowoltaiczne, ochrona przed porażeniem elektrycznym, wyłączniki różnicowoprądowe.

Introduction

The principles of protection against electric shock in low-voltage installations are included in particular in standard PN-HD 60364-4-41:2017-09 [1]. When considering photovoltaic (PV) installations, the provisions of standards PN-HD 60364-7-712 [2-3] and IEC 60364-7-712:2017-04 [4] should also be taken into account. Standards [2-4] provide a guide for protective measures against electric shock to be used on the DC side and the AC side of installations containing PV energy sources. These standards also contain some guidelines on the use of residual current devices (RCDs). However, the guidelines are quite general and require more detailed comments. Based on the works related to high-frequency earth fault currents [5, 6] and especially waveforms with harmonics [7-10], as well as verification of RCDs [11], the proper operation of RCDs strongly depends on their correct matching to the expected shape of the earth fault current. This is one of the most important aspects that should be considered when selecting RCDs in PV installations.

Therefore, the provisions of standards relating to the protection against electric shock and selection of RCDs in PV installations are presented and commented on below. The problems of RCDs operation in such installations, when DC component in the earth fault current occurs, are also discussed.

Provisions of standards

A characteristic feature of PV installations is, among others, that they include both DC voltage and AC voltage circuits. The PN-HD 60364-7-712:2016-05 [3] standard defines permissible measures of protection against electric shock separately for the DC side and the AC side of the installation. Tabl. 1 specifies these measures of protection.

Comparison of the data in Tabl. 1 with the provisions of the standard PN-HD 60364-4-41:2017-09 [1] leads to the conclusion that in PV installations the use of the following protection measures is not allowed:

• for basic protection – obstacles, placing out of reach; (both on DC and AC sides),

• for protection in case of a fault – the automatic disconnection of supply on the DC side, electrical separation on the DC side, non-conducting location (both on DC and AC sides).

With reference to the RCDs’ application, the standard [3] delivers only short provisions in the following clauses:

• 712.53 Protection, isolation, switching, control and monitoring,
• 712.531 Devices for fault protection by automatic disconnection of supply,
• 712.532 Devices for protection against the risk of fire.

Therefore, RCDs may be used on the AC side of PV installations as part of the measure automatic disconnection of supply. They may also be used for protection against the risk of fire. In the aforementioned clauses it is stated that if the RCD is used, its type shall be of B, unless:

• at least a simple separation between the AC side and the DC side is provided by the inverter, or

• at least a simple separation between the RCD and the inverter by a transformer is provided, or

• the construction of the inverter ensures that B-type RCD is not necessary; it should be stated by the inverter’s manufacturer.

Table 1. Measures of protection against electric shock allowed in PV installations, according to PN-HD 60364-7-712:2016-05 [3]

.

Based on these provisions, it can be concluded that RCDs are not mandatory in PV installations. The point is that if the designer decided to use an RCD in a PV installation without simple separation (but there is no obligation to use RCDs), i.e., in practice in an installation without a transformer, then this RCD should be B-type. Such a type because there may be unidirectional residual currents of low pulsation and other residual current devices (except type B+, which has enhanced residual current detection capabilities in relation to B-type) will not respond to such currents. Examples of simplified earth-fault current waveforms that can be expected in photovoltaic installations are shown in Fig. 1.

Fig.1. Simplified earth fault current waveforms i(t) in case of the earth fault on the DC side in a PV installation; according to [12]. Waveforms containing: a) sinusoidal component and smooth DC, b) pulsating DC (half-wave) and smooth DC (both components of the same polarity), c) pulsating DC (half-wave) and smooth DC (components with opposite polarity)

Table 2. Types of RCDs due to the ability to detect a specific waveform shape of the residual current [13, 14] and their usefulness in PV installations

.

Tabl. 2 shows the types of RCDs and normative shapes of the residual current under which these RCDs are tested. Comments referring to their usefulness in PV installations are included in Tabl. 2 as well.

In the provision of the standard [3], the requirement concerning RCDs does not refer to the obligation to use RCDs in PV installations. It relates to the type of the RCD if it is decided to install it (type B is required to be used, not, for example, type A or type AC).

RCDs, if installed, are usually utilized to ensure the automatic disconnection of supply in case of an insulation fault. In the event of an earth fault in the point indicated in Fig. 2, a circuit-breaker MCB1 or an optional RCD has to disconnect the supply. There are no requirements as to the rated residual operating current of the RCD in a PV installation between the inverter and the busbars of the AC distribution board.

Fig.2. Sample installation with PV energy sources. RCD – residual current device, MCB – miniature circuit-breaker

In the TN system, the following condition of the effectiveness of protection against electric shock is to be fulfilled:

.

where: Zs – the earth fault loop impedance, Uo – the line-to-earth nominal voltage, Ia – the current giving disconnection of supply with the required time.

Moreover, the circuit with the inverter (Fig. 2) can be considered as a distribution circuit and the automatic disconnection of supply in a TN should occur within a time not exceeding 5s (not 0.4s as for final circuits). This circuit does not require additional protection in the case of direct contact, e.g., such as in typical socket-outlet circuits having a rated current In ≤ 16 A. Therefore, there is also no need to install RCDs of IΔn ≤ 30 mA. Such RCDs may trip unnecessarily due to the high natural leakage currents in the PV system and interrupt the power supply. According to the data included in [15], the leakage currents of a set of PV modules with a rated power of several kilowatts can be within the range 9–45 mA. For this reason, inverters’ manufacturers indicate in their manuals that the rated residual operating current of RCDs in PV installations should not be less than 100 mA or 300 mA. In the case of high-power PV installations, with three-phase inverters, the recommended rated residual operating current may even be higher than 300 mA [16].

If the designer of the electrical installation recommends the application of RCDs for fire protection purposes, then, in accordance with the standards PN-HD 60364-4-42 [17] and PN-HD 60364-5-53 [18], they shall have a rated residual operating current no higher than 300 mA, and shall be installed at the origin of the protected circuit.

It should also be noted that in TN and TT systems, according to PN-HD 60364-4-41 [1] and PN-HD 60364-5-53 [18], the following devices that ensure disconnection of the power supply in the event of a single fault may be used

• overcurrent protective devices (circuit-breakers, fuses),
• residual current devices.

Residual current monitors (RCMs), in principle, give only a signal and are not considered sufficient to provide single fault protection. The standard IEC 62020-1 [19], dedicated to RCM devices, states that the purpose of these devices is only to warn in the event of a residual current exceeding a certain level – they are not protective devices disconnecting the power supply. Monitoring devices (RCMs) embedded in PV inverters are therefore not sufficient for residual current protection if one is to be used in this installation for protection by automatic disconnection of supply. The embedded RCD can be considered a sufficient device and the inverter’s manufacturer should inform about its presence.

Testing of RCDs

If a DC component appears in the residual current waveform, it influences the tripping threshold of RCDs. For this reason, the standard [3] contains a provision that in some cases it is necessary to use B-type RCDs (as given in section ”Provisions of standards”).

Laboratory tests of tripping of RCDs at the residual current containing DC component have been performed. The RCDs have been tested in the presence of the following waveforms:

• AC sinusoidal with superimposed smooth DC component,
• pulsating DC (half-wave) with superimposed smooth DC component.

It was investigated how the tripping threshold of the RCDs changes if a smooth DC component of various values appears in the residual current. The DC component was adjusted to the following values: 0, 6, 15, 30, 60, 90, 150 mA. After adjusting one of the aforementioned values of the DC component, the other component of the residual current (AC sinusoidal or pulsating DC/half-wave) was increased to the point of tripping of the tested RCD.

Fig. 3 shows the results of tests of three A-type RCDs with a rated residual operating current of IΔn = 30 mA. In the cases presented in Fig. 3a, there is a noticeable influence of the DC component – the tripping threshold of RCDs increases, but each of the tested RCDs reacted. The best properties has the RCD2. The rms value of the sinusoidal component at which RCD2 tripped did not exceed 30 mA, even when the DC component was 90 mA. The test results presented in Fig. 3b show that the residual current waveform composed of a pulsating DC (half-wave) and a smooth DC component creates more difficult conditions for tripping of RCDs than in the case of a waveform with a sinusoidal component and a smooth DC component. The RCD3 tripped only when the smooth DC component did not exceed 60 mA, and its real tripping current at this value significantly exceeded IΔn. The RCD1 reacted only when the DC component did not exceed 30 mA.

Fig.3. The tripping current of three A-type RCDs of IΔn = 30 mA (RCD1, RCD2, RCD3) under the residual test current composed of: a) AC sinusoidal and smooth DC components, b) pulsating (halfwave) and smooth DC components. The smooth DC component has the following values: 0, 6, 15, 30, 60, 90, 150 mA

The results of similar tests of RCDs with a rated residual operating current of 300 mA show (Fig. 4) that the influence of the smooth DC component of the above-mentioned values is significantly lower on these RCDs (compared to the 30 mA RCDs). Their real tripping current did not exceed the value of IΔn = 300 mA, even for a DC component equal to 150 mA.

This is due to the fact that for RCDs with IΔn = 300 mA, the DC component 150 mA is only 50% of the rated value IΔn. In the case of RCDs of IΔn = 30 mA, it is as much as 500% (150 mA/30 mA = 5). So, for a given value of the DC component, an RCD with a relatively higher-rated residual operating current (e.g., 300 mA) will behave better than the one of IΔn = 30 mA.

The indicated rising of the RCD tripping threshold is related to the influence of the DC component on the induced voltage in the secondary winding of the current transformer of the RCD. In order for RCD to operate, the secondary current isec of a sufficiently high value has to flow through the relay RE (Fig. 5). This current depends on the induced voltage esec, and that in turn depends on the value, the shape of the residual iΔ (primary ipri) current and the properties of the iron core of the current transformer CT.

Fig.4. The tripping current of two A-type RCDs of IΔn = 300 mA (RCD4, RCD5) under the residual test current composed of: a) AC sinusoidal and smooth DC components, b) pulsating (half-wave) and smooth DC components. The smooth DC component has the following values: 0, 6, 15, 30, 60, 90, 150 mA

Fig.5. A simplified structure of the RCD. CT – current transformer, RE – relay, iΔ(ipri) – residual (primary) current, isec – secondary current, esec – induced secondary voltage

Figs 6-8 show the primary current ipri and induced voltage esec oscillograms when:

• there is no smooth DC component superimposed on the half-wave residual/primary waveform (Fig. 6),
• a constant component of 150 mA is superimposed on the half-wave residual/primary waveform (Fig. 7),
• a constant component of 300 mA is superimposed on the half-wave residual/primary waveform (Fig. 8).

Fig.6. Oscillogram of the primary current (half-wave) of the RCD’s current transformer and oscillogram of its induced secondary voltage. No smooth DC component superimposed on the halfwave. Current transformer from an RCD of A-type and IΔn = 300 mA

Fig.7. Oscillogram of the primary current (half-wave and superimposed smooth DC) of the RCD’s current transformer and oscillogram of its induced secondary voltage. Smooth DC component of value 150 mA. Current transformer from an RCD of A-type and IΔn = 300 mA

Fig.8. Oscillogram of the primary current (half-wave and superimposed smooth DC) of the RCD’s current transformer and oscillogram of its induced secondary voltage. Smooth DC component of value 300 mA. Current transformer from an RCD of A-type and IΔn = 300 mA

In the case of the last-mentioned composite waveform, a clear change in the shape of the induced voltage can be seen (Fig. 8). This voltage has the lowest value (compared to the waveforms shown in Fig. 6 and Fig. 7), which adversely affects the RCDs’ tripping threshold.

Conclusions

Residual current devices in PV installations are not mandatory equipment. However, if it has been decided to use RCDs, attention should be paid to recommendations of the inverters’ manufacturers regarding the value of the rated residual operating current of RCDs. This value must not be very low to prevent unnecessary disconnection of the PV system, due to leakage currents. The type and properties of the inverter should be analyzed, and the absence or presence of a transformer that galvanically separates the DC side from the AC side should be found, because it may have an influence on the type of the RCD to be used in the PV installation. As can be seen from the analysis presented in this paper, the selection of an RCD of an inappropriate type (e.g., A-type instead of B-type when the DC component has a high value) may result in the lack of effective protection against electric shock in the PV installation – the RCD may have an increased tripping threshold at a high DC component or it may not react at all.

REFERENCES

[1] PN-HD 60364-4-41:2017-09 Low-voltage electrical installations – Part 4-41: Protection for safety – Protection against electric shock
[2] PN-HD 60364-7-712:2006 Electrical installations of buildings – Part 7-712: Requirements for special installations or locations – Solar photovoltaic (PV) power supply systems
[3] PN-HD 60364-7-712:2016-05 Low-voltage electrical installations – Part 7-712: Requirements for special installations or locations – Photovoltaic (PV) systems
[4] IEC 60364-7-712:2017-04 Low-voltage electrical installations – Part 7-712: Requirements for special installations or locations – Solar photovoltaic (PV) power supply systems
[5] Czaja P., Examination of the impact of design of a residual current protective device on the release frequency range, Progress in Applied Electrical Engineering (PAEE), Koscielisko, Poland (2017)
[6] Slangen T. M. H., Lustenhouwer B. R. F., Ćuk V., Cobben J. F. G., The effects of high-frequency residual currents on the operation of residual current devices, 19th Int. Conf. on Renewable Energies and Power Quality (ICREPQ’21), Almeria, Spain (2021)
[7] Sutaria J., Espín-Delgado Á., Rönnberg S., Measurements and modeling of the frequency behavior of residual current devices- from 4 Hz to 40 kHz, Electric Power Systems Research, 209 (2022), 108052
[8] Czapp S., The effect of earth fault current harmonics on tripping of residual current devices, Przeglad Elektrotechniczny, 85 (2009), No. 1, 196-201
[9] Czapp S., The effect of PWM frequency on the effectiveness of protection against electric shock using residual current devices, International School on Nonsinusoidal Currents and Compensation (ISNCC), Lagow, Poland (2010), doi: 10.1109/ISNCC.2010.5524515
[10] Czapp S., Horiszny H., Simulation of residual current devices operation under high frequency residual current, Przeglad Elektrotechniczny, 88 (2012), No. 2, 242-247
[11] Czapp S., Fault loop impedance measurement in low voltage network with residual current devices, Elektronika ir Elektrotechnika, 122 (2012), No. 6, 109-112, doi: https://doi.org/10.5755/j01.eee.122.6.1833
[12] Davids S., Grünebast G., Residual Currents in Photovoltaic Installations, Version 1.1, 2011, Doepke Schaltgeräte
[13] PN-EN 61008-1:2013-05 Residual current operated circuitbreakers without integral overcurrent protection for household and similar uses (RCCBs) – Part 1: General rules
[14] PN-EN 62423:2013-06 Type F and type B residual current operated circuit-breakers with and without integral overcurrent protection for household and similar uses
[15] Leading Leakage Currents. Version 2.6, SMA Solar Technology AG, https://files.sma.de/downloads/Ableitstrom-TIen-26.pdf, accessed on: 24.02.2022
[16] RCD Selection for SolarEdge Inverters – Application Note. SolarEdge, March 2018
[17] PN-HD 60364-4-42:2011 Low-voltage electrical installations – Part 4-42: Protection for safety – Protection against thermal effects
[18] PN-HD 60364-5-53:2016-02 Low-voltage electrical installations – Part 5-53: Selection and erection of electrical equipment – Switchgear and controlgear
[19] IEC 62020-1:2020-04 Electrical accessories – Residual current monitors (RCMs) – Part 1: RCMs for household and similar uses

Author: dr hab. inż. Stanisław Czapp, prof. PG, Gdańsk University of Technology, Faculty of Electrical and Control Engineering, ul. G. Narutowicza 11/12, 80-233 Gdańsk, Poland, E-mail: stanislaw.czapp@pg.edu.pl

Source & Publisher Item Identifier: PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 98 NR 12/2022. doi:10.15199/48.2022.12.25

Total Harmonic Distortion (THD) and Power Factor Calculation

Published by Alex Roderick, EE Power – Technical Articles: Total Harmonic Distortion (THD) and Power Factor Calculation, May 10, 2021.

In this article, we will discuss how to measure total harmonic distortion and the power factor calculations utilized.

Total harmonic distortion (THD) is the amount of harmonics on a line compared to the line fundamental frequency, e.g., 60Hz. The THD considers all of the harmonic frequencies on a line. THD can be related to either current harmonics or voltage harmonics, The following equation can be used to calculate the distortion of the line voltage: 

Figure 1. Total harmonic distortion (THD) should be measured at the transformer, not at the load.

where Vn_rms is the RMS voltage of the nth harmonic and Vfund_rms is the RMS voltage of the fundamental frequency. The THD of a pure sine waveform with no higher harmonics, such as the ideal voltage supply, is 0%. A value of THD greater than zero means the sine waveform has become distorted. THD is often given as a percentage, such as 5% or 50%. THD can be measured for current and voltage.

Current harmonics are caused by non-linear loads for example those that draw pulses of current. Voltage harmonics are caused by the harmonic currents flowing through different system impedances. The current flowing through a transformer causes a voltage drop across the coil. When current flows in pulses, the voltage will also be in pulses. High voltage distortion is a problem because voltage distortion becomes a carrier of harmonics to linear loads such as motors. Voltage harmonics cause problems (extra heat) in the power distribution system and to the loads connected to the system.

Measuring THD

When troubleshooting a circuit for harmonics, the voltage THD and the current THD should be measured. For best results, the voltage THD should not exceed 5%, and the current THD should not exceed 20% of the fundamental frequency. THD should be calculated at the transformer rather than at the harmonic-generating loads for an accurate calculation of THD in a system (see Figure 1). Measuring THD at the loads provides the highest THD reading because THD cancellation has not occurred along the system. 

Figure 1. Total harmonic distortion (THD) should be measured at the transformer, not at the load.

When THD current is measured during full load, the THD is approximately equal to the total demand distortion (TDD). Total demand distortion (TDD) is the ratio of the current harmonics to the maximum load current. A THD measurement is taken when testing or troubleshooting a system. The TDD is different from the THD because TDD is referenced to the maximum current measurement taken over time. The THD is a measurement of current on a power line only at the specific time of the measurement. The purpose of the TDD measurement is to account for situations where the THD is relatively high, but the total load is fairly low. In this type of situation, the TDD is relatively low, and overheating is minimized.

Power Factor

Power factor is the ratio of true power to apparent power in a circuit or distribution system. Any AC circuit consists of real, reactive, harmonic, and apparent (total) power. True power is the power, in W or kW, used by motors, lights, and other devices to produce useful work. Reactive power is the power, in VAR or kVAR, stored and released by inductors and capacitors. Reactive power shows up as a phase displacement between the current and voltage waveforms. Harmonic power is power, in VA or kVA, lost to harmonic distortion. Apparent power is the power, in VA or kVA, that is the vector sum of true power, reactive power, and harmonic power. Apparent power is not a simple summation but a vector summation.

The displacement power factor is the ratio of true power to apparent power due to the phase displacement between the current and voltage (see Figure 2). Capacitors can usually be added to a circuit or distribution system to correct the displacement power factor. The displacement power factor is calculated as follows:

PF = cos(θ)

where
PF = displacement power factor
θ = Difference between the phase of the voltage and the phase of the current (phase displacement) in degrees.
Note: DPF or PFD are sometimes used instead of PF to describe displacement power factor.

Figure 2. The displacement power factor can be used to calculate the amount of power that is actually available for a load.

The presence of harmonics complicates the discussion of the power factor. The distortion power factor is the ratio of true power to apparent power due to THD. Capacitors cannot be added to a circuit to compensate for the distortion power factor. The impedance of capacitors decreases with frequency. Therefore, a capacitor can become a sink for high-frequency harmonics. Special types of transformers or tuned harmonic filters consisting of capacitors and inductors are used to correct distortion power factor. The distortion power factor is calculated as follows:

.

where
PFTHD = distortion power factor
THD = total harmonic distortion

The total power factor is the product of the displacement power factor and the distortion power factor and is calculated as follows:

PFTot = PF × PFTHD

where
PFTot = total power factor
PF = displacement power factor
PFTHD = distortion power factor

For example, what is the total power factor when the displacement between voltage and current is 25°, and the THD is 49% (0.49)? The displacement power factor is calculated as follows:

PF = cos(θ)
PF = cos (25°)
PF = 0.906

The distortion power factor is calculated as follows:

.

The total power factor is calculated as follows:

PFTot = PF × PFTHD
PFTot = 0.906 × 0.898
PFTot = 0.814

It is important to know the total power factor because it relates to apparent power. Apparent power is used to size the elements of a power distribution system.

Current Crest Factor

The current crest factor is the peak value of a waveform divided by the rms value of the waveform. The purpose of a current crest factor is to give an idea of how much distortion is occurring in a waveform. The current crest factor is calculated as follows:

.

where
CCF = current crest factor
Ipeak = peak value (in A)
Irms = root mean square value (in A)

For example, what is the current crest value of a perfect sine waveform? In a perfect sine waveform with a peak value of 1, the rms value is 0.707.

.

A high current crest factor can cause overheating of circuits and devices. A typical distorted current waveform on a 120 V circuit supplying digital devices like computers may have a current crest factor of about 2 to 6 (see Figure 3). In general, a circuit with a higher current crest factor has more energy contained in the higher harmonics. 

A power source must be able to supply the maximum power required by the circuit at the required voltage and current. A typical backup power system, such as a computer uninterruptible power source, has the capability of supplying a current crest factor of 3 at full load but can exhibit higher crest factors at lower loads.

Figure 3. The current crest factor comparison

Source Impedance

Source impedance has an effect on the crest factor created by a non-linear load. Once the voltage rises to a predetermined point, the power supply starts charging a smoothing capacitor. The current drawn by the capacitor is high when the source impedance is low, and the charging cycle is short. Higher impedance limits the amount of current that can be drawn, extending the time it takes to charge the capacitor. The extended charge time has the effect of reducing the crest factor. The source impedance can be increased by adding line reactors or drive isolation transformers.

Author: Alex earned a master’s degree in electrical engineering with major emphasis in Power Systems from California State University, Sacramento, USA, with distinction. He is a seasoned Power Systems expert specializing in system protection, wide-area monitoring, and system stability. Currently, he is working as a Senior Electrical Engineer at a leading power transmission company.

Source URL: https://eepower.com/technical-articles/total-harmonic-distortion-thd-and-power-factor-calculation/

Short-Term Forecasting of Photovoltaic Power Generation

Published by Roman KORAB1, Tomasz KANDZIA2, Tomasz NACZYŃSKI3, Silesian University of Technology, Department of Power Systems and Control.

ORCID: 1. 0000-0002-6844-1342; 3. 0000-0001-6271-0516

Abstract. In this article, a method for short-term forecasting of photovoltaic (PV) generation was proposed. The proposed method belongs to the group of physical methods and is based on numerical weather forecasts. The generation forecast was determined using the PV source model in the OpenDSS software. The results of calculations were compared with the results of measurements from the operating PV micro-installations.

Streszczenie. W artykule zaproponowana została metoda krótkoterminowego prognozowania generacji źródła fotowoltaicznego (PV). Metoda ta należy do grupy tzw. metod fizycznych i bazuje na numerycznych prognozach pogody. Do wyznaczenia prognozy generacji zastosowano model źródła fotowoltaicznego wchodzący w skład pakietu OpenDSS. Wyniki prognoz zostały porównane w wynikami pomiarów pochodzących z działających mikroinstalacji PV. (Krótkoterminowe prognozowanie generacji źródła fotowoltaicznego)

Keywords: photovoltaic source, prosumer, generation forecasting, physical method, numerical weather forecast, OpenDSS
Słowa kluczowe: źródło fotowoltaiczne, prosument, prognozowanie generacji, metoda fizyczna, numeryczna prognoza pogody, OpenDSS

Introduction

The increasing power of renewable energy sources [1], especially prosumer photovoltaic (PV) micro-installations [2], changes the operating conditions of the power grid. Distribution system operators are increasingly reporting emerging problems in the operation of the low-voltage (LV) grid. These problems mainly concern an increase in voltage above the permissible limit, the appearance of the reverse power flow from the LV network to the medium-voltage (MV) network, an increase in voltage asymmetry, and a higher load of some network elements. The described phenomena occur locally, in places where a large number of PV micro-installations have been connected [3]. The risk of exceeding the normal operating conditions of the LV network increases as the power of PV sources increases [4].

Excessive power of PV sources connected locally to the LV grid also affects the situation of prosumers, especially during periods of high solar irradiation, when they produce the majority of the energy. Due to the low demand that usually occurs at this time, most of the energy produced is transmitted to the grid. This raises the voltage at the prosumer’s connection point. Once the voltage exceeds the permissible limit, the inverter turns off and no energy is produced despite favorable weather conditions. As a result, the prosumer suffers a measurable loss. The situation described is illustrated in Figure 1.

Fig.1. Phase voltages and power generated by a PV micro-installation belonging to one of the authors of the article (measurements from May 15, 2022; visible interruptions in production caused by switching off the inverter due to exceed the voltage limit)

The standard method to improve the operating conditions of the LV grid with connected PV micro-installations is its modernization. Modernization usually consists in increasing the power of the MV/LV transformer and the cross section of the conductors, as well as shortening the LV circuits [5]. However, this is a costly method and takes a long time to implement the investment. An alternative solution is to increase the consumption of energy at the place where it is generated, at the same time as this generation occurs, i.e., to increase self-consumption. This can be achieved by appropriate control of selected household electrical appliances owned by the prosumer and using energy storages, connected in the prosumer’s power supply system [6]. Proper determination of the operating schedule of these devices during the day requires a forecast of the generation of the PV source.

Numerous studies have reviewed various PV power forecasting methodologies [7-11]. These works classify PV power forecasting mainly depending on the forecasting horizon and methods used to forecast. The duration of time for which the forecasting of the PV power output is performed is called the forecasting horizon [8, 10]. Based on the time horizon, forecasting of PV power generation can be generally divided into three categories: long-term (done from one month to several years), medium-term (done for more than one week to one month), and short-term (done for one hour, several hours, one day or up to seven days). Long-term forecasts are used to plan the development of electricity generation, transmission, and distribution. Medium- term forecasts are important for planning the maintenance of power plants and networks in a cost-effective way. Short-term forecasts of PV generation are useful in unit commitment and dispatching of electrical power, as well as in scheduling of spinning reserves and demand response. These types of forecasts are also helpful in designing a PV integrated energy management system for buildings.

There are two main methods used for forecasting PV generation, namely statistical and physical [7, 9, 11]. Statistical approach consists in predicting the power output using historical data. Therefore, the quality of the data is essential for an accurate forecast. Statistical methods require a large historical dataset (meteorological and power measurements) to correctly define the correlation among them. The selection of a suitable training dataset becomes crucial for the accuracy. The statistical approach includes artificial neural networks, support vector machines, Markov chain, autoregressive, and regression models. Statistical models do not need any technical information from the PV system to model them. In contrast, the second approach, i.e., physical methods (also known as PV performance models), uses analytical equations and technical data to model the PV system. These methods use forecasted meteorological data to calculate PV production. The main advantage of physical methods over the statistical methods is that no historical data are needed. However, the major disadvantage of these models is the high dependence on weather forecast, especially the forecast of solar irradiance. Physical methods include numerical weather forecasts, sky imagery, and satellite-imaging models.

In this article, we propose a physical method for short-term forecasting of a PV generation, based on numerical weather forecasts. We determine the generation forecast using the PV source model in the OpenDSS software. We compare the results of the calculations with the results of measurements from the operating PV micro-installations.

Model of a PV source

The PV source model used by OpenDSS [12] is presented in Figure 2 [4]. To parameterize the model, we first define the rated power of the PV panels PrPV under standard test conditions. The power generated by the PV panels is determined for a given level of solar irradiance and is dependent upon the panel temperature, so the obtained power value must be corrected accordingly. The temperature of the PV panels is calculated using an external model based on ambient temperature, solar irradiance intensity, and wind speed. The DC power generated PDC is then converted according to the efficiency characteristic of the inverter, for which the rated power Sr, the rated voltage Ur, and the power factor pf are given. The active power P and the reactive power Q generated by the PV source are calculated at the output of the inverter.

Fig.2. The PV source model used by OpenDSS [4]

In the following part of the article, the PV source model will be validated using the measurements for the PV installation operating at the Silesian University of Technology.

The PV micro-installation at the Silesian University of Technology (SUT)

The SUT PV micro-installation is located on the roof of the building of the Faculty of Automatic Control, Electronics and Computer Science (Fig. 3). This building is equipped with three PV installations. Installation no. 3 was selected for the tests, because in the other two there was periodic shading of the PV panels by building elements. The selected installation is characterized by the same angle of inclination and orientation of all panels towards the cardinal directions. The installation consists of 66 NeMo 60 P modules with a rated power of 265 W, which gives a total installed power of 17.49 kW. It is based on the SolarEdge system, consisting of 33 power optimizers (P600) and an inverter (SE17K) with a rated power of 17 kVA.

Fig.3. PV installation on the roof of the building of the Faculty of Automatic Control, Electronics, and Computer Science of the Silesian University of Technology in Gliwice, Poland

Adjacent to the PV installation, there is a weather station measuring ambient temperature and wind speed. The weather station is also equipped with an external temperature sensor for PV temperature measurement. The solar irradiance is measured with a pyranometer. The PV installation is equipped with a SCADA (Supervisory Control And Data Acquisition) system that records the weather conditions and generated power with an one-minute resolution.

Weather conditions during the selected days

Two random days from 2021 were selected for the analysis. These days differed primarily in the intensity of solar irradiation. The first day, June 27, was a sunny day with temporary clouds. The second day, September 29, was cloudy with varying degrees of cloud cover. The weather conditions on selected days are illustrated in Figures 4 and 5. These figures also show the recorded temperature variability of the PV panels.

Fig.4. Solar irradiance, ambient temperature, PV module temperature
(a), and wind speed (b) on June 27, 2021
Fig.5. Solar irradiance, ambient temperature, PV module temperature
(a), and wind speed (b) on September 29, 2021
Correction of solar irradiance

Figures 4a and 5a show the measured intensity of solar irradiation falling on a horizontal surface. On this basis, the intensity of solar irradiation incident on the surface of PV modules, that are inclined to the horizontal at an angle of 12° and tilted from the north-south axis by 35° in the eastern direction, was determined. The calculations used a procedure according to PN-EN ISO 52010-1:2017-09, as described in the article [13]. Parameters that define the position of the sun relative to the PV panels were determined using the NOAA Solar Calculator [14]. Figures 6 and 7 compare the measured and corrected solar irradiance. The corrected solar irradiance will be used to calculate the generation of PV panels.

Fig.6. Solar irradiance on sloped surface (corrected) vs. solar irradiance on a horizontal surface (measured) on June 27, 2021
Fig.7. Solar irradiance on sloped surface (corrected) vs. solar irradiance on a horizontal surface (measured) on September 29, 2021

Estimation of the PV module temperature

The operating temperature of the PV panel has a direct influence on power output. As the temperature increases, power generation decreases. The power temperature coefficient for PV panels in considered micro-installation was equal to 0.42%/°C. This means that a 10°C increase in temperature results in a 4.2% reduction in generated power. In the article, a dynamic thermal model proposed in [15] was used to determine the temperature of PV panels. This model is based on the finite difference method and uses data on ambient temperature, solar irradiation, and wind speed. The measured and calculated daily variation of PV panels temperature is shown in Figures 8 and 9. The temperature estimation error did not exceed 9°C on June 27 and 5°C on September 29.

Fig.8. Temperature of a PV module calculated using the finite
difference model vs. measured temperature – atmospheric conditions
on June 27, 2021
Fig.9. Temperature of a PV module calculated using the finite
difference model vs. measured temperature – atmospheric conditions
on September 29, 2021
Validation of the PV source model

The PV source model was parameterized according to the technical data for the analyzed SUT PV micro-installation. Subsequently, corrected solar irradiance (Figures 6 and 7) and calculated PV panel temperature (Figures 8 and 9) were entered into the model. On this basis, the generation of the micro-installation was calculated for the two days analyzed. The results of the calculation were compared with the generation measured on those days. The results are presented in Figures 10 and 11.

Fig.10. Generation of PV installation calculated using the PV
source model vs. measured power – atmospheric conditions on
June 27, 2021
Fig.11. Generation of PV installation calculated using the PV
source model vs. measured power – atmospheric conditions on
September 29, 2021

Comparing the results obtained using the PV source model with the measurements (Figs. 10 and 11), a high accuracy of estimation of the PV generation can be observed. The quality of PV model can be evaluated applying the mean absolute percentage error (MAPE) defined as:

.

where: Pm(t) – measured PV generation at time interval t, in kW, Pc(t) – calculated PV generation at time interval t, in kW, n – the total number of time intervals in analyzed period (1440). The values of MAPE errors for both days analyzed, as well as the measured and calculated amount of a daily energy production, are given in Table 1.

Table 1. Daily energy production and MAPE

.

The applied model of the PV source turned out to be less accurate for a day with a higher level of solar irradiance. An in-depth analysis of the results allowed us to conclude that the largest difference between the measured and calculated PV generation occurs for the morning hours (up to 6.00) and the afternoon hours (after 16.00). If only hours from 6.00 to 16.00 are considered for the assessment of the model accuracy (approximately 90% of the daily energy is generated during this period), the error values are significantly smaller (see Table 2).

Table 2. Energy production and MAPE – hours from 6.00 to 16.00

.

The described model can also be used to determine the forecasted generation of the PV source. For this purpose, numerical weather forecasts should be used as input to the model.

Fig.12. Numerical weather forecast from the platform A for June
27, 2021 (hourly resolution)
Fig.13. Numerical weather forecast from the platform B for June
27, 2021 (hourly resolution)
Fig.14. Numerical weather forecast from the platform B for June
27, 2021 (5 minute resolution)
Fig.15. Numerical weather forecast from the platform A for September
29, 2021 (hourly resolution)
Fig.16. Numerical weather forecast from the platform B for September
29, 2021 (hourly resolution)
Fig.17. Numerical weather forecast from the platform B for September 29, 2021 (5 minute resolution)

Numerical weather forecasts

The numerical weather forecasts used in the calculations came from two internet platforms (A and B). Both platforms provide information about the forecasted ambient temperature, wind speed, and solar irradiation through the API (application programming interface). The geographic resolution for platform A is 4 km and for platform B is 2 km. Platform A allows to download data in hourly resolution, while platform B in hourly and five-minute resolution. The weather forecasts from both platforms for the two days analyzed in the article are shown in Figures 12-17.

PV generation forecasts

Using the procedure described in the previous sections, and based on the numerical weather forecasts presented in Figures 12-17, appropriate forecasts of the generation of the PV source with an installed capacity of 17.49 kW were determined. The calculation results are shown in Figures 18-23 and Table 3.

Fig.18. Forecast of PV generation based on the platform A weather
forecast (1 h) vs. measured power on June 27, 2021
Fig.19. Forecast of PV generation based on the platform B weather
forecast (1 h) vs. measured power on June 27, 2021
Fig.20. Forecast of PV generation based on the platform B weather
forecast (5 min) vs. measured power on June 27, 2021
Fig.21. Forecast of PV generation based on the platform A weather
forecast (1 h) vs. measured power on September 29, 2021
Fig.22. Forecast of PV generation based on the platform B weather
forecast (1 h) vs. measured power on September 29, 2021
Fig.23. Forecast of PV generation based on the platform B weather
forecast (5 min) vs. measured power on September 29, 2021

Table 3. Forecast of daily energy production and MAPE

.

The obtained generation forecasts differ from the actual production of the analyzed PV source. The accuracy of the forecasts is different for both the days considered and for different numerical weather forecasts. The forecasts obtained for the numerical weather forecasts from platform A are characterized by the lowest accuracy. The highest accuracy was obtained for platform B weather forecasts with a five-minute resolution. In the best case, the difference between the forecast and the actual generation was 3.6%, and the MAPE error did not exceed 27%.

In the following section, weather forecasts in five-minute resolution from platform B will be used to forecast the generation of prosumer micro-installations.

Generation forecast for a prosumer PV installations

The developed method was used to calculate the generation forecast for two prosumer micro-installations. The first is located in Koszęcin (Silesian Voivodeship). It is a household PV installation with an installed power of 7.32 kW. The installation consists of 24 IBC Solar PV panels with a power of 305 W and a Fronius Symo 6.0-3M inverter with a rated power of 6 kW. In the analyzed installation, the panels face south-west and are inclined at an angle of 35°. The forecast was developed using the numerical weather forecast for June 10, 2022 (Fig. 24). The results are shown in Figure 25 and Table 4.

Fig.24. Numerical weather forecast from the platform B for June
10, 2022 (5 minute resolution)
Fig.25. Forecast of PV generation based on the platform B weather
forecast (5 min) vs. measured power on June 10, 2022

Table 4. Daily energy production and MAPE

.

The second micro-installation is located in Łącza (Silesian Voivodeship). The installation consists of 20 LONGI Solar LR6-60PE modules with a rated power of 305 W, which gives a total power of 6.1 kW. The panels are connected to the Fronius Symo 5.0-3M inverter with a rated power of 5 kW. In the analyzed installation, the panels face south and are inclined at an angle of 15°. The forecast was prepared for June 16, 2022, also using the numerical weather forecast from platform B in a five-minute resolution (Fig. 26). The calculation results are shown in Figure 27 and Table 5.

Fig.26. Numerical weather forecast from the platform B for June
16, 2022 (5 minute resolution)
Fig.27. Forecast of PV generation based on the platform B weather
forecast (5 min) vs. measured power on June 10, 2022

Table 5. Daily energy production and MAPE

.
Conclusions

The article presents a method of forecasting the generation of a PV source using numerical weather forecasts including the forecast of solar irradiation, ambient temperature, and wind speed. The possibility of using hourly and five-minute weather forecasts from two meteorological platforms was analyzed. The results of the forecasts were compared with the actual generation of three operating PV micro-installations.

The accuracy of PV generation forecasts depends on the source of the numerical weather forecasts and their resolution, as well as on the nature of the weather on the analyzed day, in particular on the nature of cloud cover. In the article, days with highly variable cloudiness were selected for analysis. From the point of view of forecasting the generation of a PV source, these are days for which forecasting is very difficult. The analyzes performed indicate that much higher accuracy was obtained for weather forecasts with a five-minute resolution. This type of PV source generation forecast is characterized by sufficient accuracy to be used to determine the operating schedule of the selected household electrical appliances and energy storages owned by prosumers in order to increase the self-consumption of the produced energy.

LITERATURA

[1] pse.pl/dane-systemowe/funkcjonowanie-kse/raporty-roczne-zfunkcjonowania-kse-za-rok/raporty-za-rok-2021 (in Polish)
[2] ptpiree.pl/energetyka-w-polsce/energetyka-w-liczbach/mikroinstalacje-w-polsce (in Polish)
[3] Topolski Ł., Schab W., Flirt A., Piątek K.: Analysis of the impact of dispersed generation on selected aspects of power quality in a low-voltage electricity network located in the area of energy cluster Virtual Green Ochotnica Power Plant. Przegląd Elektrotechniczny, vol. 3 (96), 2020, doi: 10.15199/48.2020.03.05 (in Polish)
[4] Korab R., Połomski M., Smołka M.: Evaluating the Risk of Exceeding the Normal Operating Conditions of a Low-Voltage Distribution Network due to Photovoltaic Generation. Energies 2022, 15, 1969, doi:10.3390/en15061969
[5] Adamek S.: Methods to reduce adverse impact of prosumer microinstallations on LV distribution systems. Rynek Energii, vol. 6 (163), 2022 (in Polish)
[6] Naczyński T., Korab R.: Possibilities of forming the electricity balance of an individual customer equipped with a photovoltaic source. Przegląd Elektrotechniczny, vol. 11 (97), 2021, doi:10.15199/48.2021.11.38 (in Polish)
[7] Antonanzas J., Osorio N., Escobar R., Urraca R., Martinez-de-Pison F.J., Antonanzas-Torres F.: Review of photovoltaic power forecasting. Solar Energy, vol. 136, 2016, doi:10.1016/j.solener.2016.06.069
[8] Das U.K., Tey K.S., Seyedmahmoudian M., Mekhilef S., Idris M.Y.I., Van Deventer W., Horan B., Stojcevski A.: Forecasting of photovoltaic power generation and model optimization: A review, Renewable and Sustainable Energy Reviews, vol. 81, part 1, 2018, doi:10.1016/j.rser.2017.08.017
[9] Sobri S., Koohi-Kamali S., Rahim N.A.: Solar photovoltaic generation forecasting methods: A review. Energy Conversion and Management, vol. 156, 2018, doi:10.1016/j.enconman.2017.11.019
[10] Akhter M.N., Mekhilef S., Mokhlis H., Shah N.M.: Review on forecasting of photovoltaic power generation based on machine learning and metaheuristic techniques. IET Renewable Power Generation, 2019, 13, doi:10.1049/iet-rpg.2018.5649
[11] Wu Y.K., Huang C.L., Phan Q.T., Li Y.Y.: Completed Review of Various Solar Power Forecasting Techniques Considering Different Viewpoints. Energies 2022, 15, 3320, doi:10.3390/en15093320
[12] EPRI: OpenDSS PVSystem Element Model. Version 1. February 23, 2011. http://www.epri.com/pages/sa/opendss
[13] Michalak P.: Modelling of solar irradiance incident on building envelopes in Polish climatic conditions: the impact on energy performance indicators of residential buildings. Energies 2021, 14, 4371. https://doi.org/10.3390/en14144371
[14] NOAA Solar Calculator, gml.noaa.gov/grad/solcalc/index.html
[15] Korab R., Połomski M., Naczyński T., Kandzia T.: A dynamic thermal model for a photovoltaic module under varying atmospheric conditions. Energy Conversion and Management, vol. 280, 2023, doi.org/10.1016/j.enconman.2023.116773

Autorzy: dr hab. inż. Roman Korab prof. PŚ; E-mail: roman.korab@polsl.pl, Politechnika Śląska, Katedra Elektroenergetyki i Sterowania Układów, ul. B. Krzywoustego 2, 44- 100 Gliwice; mgr inż. Tomasz Kandzia, Politechnika Śląska, Wydział Elektryczny, absolwent 2022, E-mail: tomaszkandzia@protonmail.com; mgr inż. Tomasz Naczyński – Politechnika Śląska, Wspólna Szkoła Doktorów, doktorant; E-mail: tomasz.naczynski@polsl.pl;

Source & Publisher Item Identifier: PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 99 NR 9/2023. doi:10.15199/48.2023.09.06

Impact of EV Charging Stations Integration on Power System Performance

Published by Wisam Mohamed Najem1, Shaker M. Khudher2, Omar Sh. Alyozbaky3, Department of Electrical Engineering, College of Engineering, University of Mosul, Iraq (1,2,3)

ORCID: 1.0000‐0002‐9611‐6416; 2.0000‐0003‐3158‐7900; 3.0000‐0002‐9735‐1469

Abstract. Electric vehicles partner with clean energy to prevent carbon emissions attributed to internal combustion engine-powered traditional vehicles, gas-based power plants, and other environmental pollution sources. At the same time, using electric vehicles adversely affects power infrastructure; hence, analytical research is crucial to assess such effects. This paper is based on several scenarios comprising a rising number of vehicles connected to the electrical system. The adverse effects of electric vehicle charging stations connected to the electrical infrastructure were diagnosed. MATLAB/Simulink was used for simulation and modelling to highlight any effects. Vehicle charging points and their impact on the electrical system’s total harmonic distortion were studied; a single-vehicle connected to the system added 2.44% to the THD, which increased to 12.69% when twelve vehicles were connected simultaneously. Moreover, charging operations breached the recommended voltage standards; a 0.95 P.U. voltage was recorded. Additionally, charging station integration reduced the power factor of the electrical system; this phenomenon was assessed.

Streszczenie. Pojazdy elektryczne współpracują z czystą energią, aby zapobiegać emisjom dwutlenku węgla przypisywanym tradycyjnym pojazdom napędzanym silnikami spalinowymi, elektrowniom gazowym i innym źródłom zanieczyszczenia środowiska. Jednocześnie korzystanie z pojazdów elektrycznych niekorzystnie wpływa na infrastrukturę energetyczną; stąd kluczowe znaczenie dla oceny takich efektów mają badania analityczne. Niniejszy artykuł opiera się na kilku scenariuszach obejmujących rosnącą liczbę pojazdów podłączonych do systemu elektrycznego. Zdiagnozowano niekorzystne skutki stacji ładowania pojazdów elektrycznych podłączonych do infrastruktury elektrycznej. MATLAB/Simulink został wykorzystany do symulacji i modelowania w celu podkreślenia wszelkich efektów. Zbadano punkty ładowania pojazdów i ich wpływ na całkowite zniekształcenia harmoniczne układu elektrycznego; pojedynczy pojazd podłączony do systemu dodał 2,44% do THD, które wzrosło do 12,69%, gdy dwanaście pojazdów było jednocześnie podłączonych. Ponadto operacje ładowania naruszyły zalecane normy napięcia; 0,95 j.m. rejestrowano napięcie. Dodatkowo integracja stacji ładowania zmniejszyła współczynnik mocy systemu elektrycznego; zjawisko to zostało ocenione. (Wpływ integracji stacji ładowania pojazdów elektrycznych na wydajność systemu zasilania)

Keywords: Charging station; Electric Vehicles; Total Harmonic Distortion; Power System
Słowa kluczowe: Stacja ładowania; Pojazdy elektryczne; Całkowite zniekształcenia harmoniczne; System zasilania

Introduction

Presently, the transportation sector primarily relies on fossil fuels. It is a major emitter that significantly increases global [1]–[3] fuel-based vehicles at the individual level consume more than 50% of the energy used by the overall transportation system, causing significant emissions [4]. Hence, several nations have had a policy shift that focuses on newer technologies. Such shift includes electric vehicles entirely powered by batteries, hence designated battery-powered vehicles (Battery electric vehicles) or hybrid electric vehicles (Hybrid electric vehicles) that cause relatively less pollution and emissions [5]–[7]. Sectoral developments indicate that electric vehicle adoption will increase due to novel vehicle charging technologies and advancements in battery manufacturing, e.g., lithium batteries that can be charged numerous times [8]. Electric vehicles are powered by batteries recharged by power electronic devices that converting an alternating current to direct current [9].

Electric vehicles are advantageous from an environmental perspective because of lesser pollution and emission; moreover, these vehicles are moveable energy storage systems [10], [11]. However, the electrical system is adversely affected when such vehicles are connected for recharging. For instance, more electric vehicles charging from the network increase energy demand [12], [13]; these vehicles’ circuits are non-linear electrical loads that introduce harmonics in the electrical system, leading to decreased power factor [14], [15], higher voltage deviations [16], [17], and faster cable and transformer ageing [18]. An increase in total harmonic distortion reduces power quality due to suddenly voltage changes [19], causing improper functioning of protection relays [20], [21].

This research assesses the consequences of electric vehicle charging on the power infrastructure and discusses changes to voltage characteristics, power factor, and total harmonic distortion. This paper is structured as specified: the first section comprises an introduction, followed by the electric vehicle charging station configuration in section two. Research criticality is presented in section three, followed by system simulation, modelling, and analysis in section four. Lastly, section five presents the conclusions.

Vehicle charger configuration

Hybrid and battery-powered electric vehicles rely on rechargeable batteries as critical energy sources. Battery charging differs based on vehicle and battery types. Several researchers have expressed interest in devising advanced battery charging technologies. Battery chargers can be integrated with the vehicle (on-board charger), or external chargers can be used (off-board charger) [22]. Batteries are charged at specific voltages that can be produced using single- or three-phase rectifier diode-based configurations [23] and thyristor or IGBT-based controlled rectifiers [24].

Fig.1. depicts several charger categories

Power transfer direction is commonly used to classify electric vehicle charging stations, indicating whether the power electronics on the charger and electric vehicle can transfer current unidirectional or bidirectional. Unidirectional chargers may use diodes (valves); non-directional chargers have a straightforward and uncomplicated operation.

Bidirectional chargers require sophisticated control mechanisms that allow charging and discharging modes, helping the power system; however, such operations might cause battery deterioration [25]. Fig. 2, depicts charging station topology for directional and non-directional systems.

Fig.2. General topology for directional and non-directional charging systems.

This study intends to assess the consequences of integrating electric vehicles with the electrical infrastructure, considering the rapid increase in electric vehicles. Hence, it is critical to assess the challenges these vehicles may create. This data can be used to devise approaches to adapt and augment electrical systems to handle vehicle charging station integration. The objectives of this paper are listed below:

• Using MATLAB to simulate and model electric vehicle charging stations
• Assessing changes to total harmonic distortion due to electric vehicle charging
• Assessing changes to the power factor due to electric vehicle charging.

System modelling and simulation

Due to the extensive rise in electric vehicle use worldwide, electrical grids are under immense load. Some challenges include higher network harmonic distortion, higher power demand, lower power factor, and power quality challenges. Hence, researchers are trying to assess the consequences of connecting such charging systems to the electric network so that optimal approaches can be devised to reduce concerns. This research uses the model depicted using Fig. 3 [26]–[28].

Fig.3. The network model evaluated in this study

The model suggested in the Figure is created using MATLAB; the electrical loads are indicated below:

• The first load is a 560 kVA industrial load placed on the first bus

• The second load is a combined 112 kVA domestic load placed on the second bus

• Electric vehicle load is set at 34 kW, connected to the grid using an 11 kV/0.4 kV step-down transformer The electrical system is simulated as specified below:

• The system is evaluated without an electric vehicle charging load, and the power factor and harmonic distortion are specified.

• Electric vehicles are integrated to the proposed model, and the network is analysed.

Case study

This section discusses several simulations and network models to evaluate the adverse outcomes of connecting electric vehicles to the power system. This section is split into five cases, as specified below.

• Case A: The electrical system is assessed without electric vehicles to understand system characteristics in its initial state. The power network was simulated and modelled, as depicted in Fig. 4. System characteristics were set as indicated in section four.

Fig.4. Electrical network without electric vehicles

• Case B: The system was assessed by adding one electric vehicle load amounting to 34 kW to the second bus added to the load as in the first scenario. This system comprises an electric vehicle configured to draw 75 amps at 450 volts, allowing its 300-volt 50 amp-hour battery to charge in the fast mode. This scenario is devised and simulated with one vehicle attached to the second bus, as depicted in Fig.5.

Fig.5. Network with one connected electric vehicle

• Case C: This scenario considers a charging station connected to the electrical system; the station is configured with four electric vehicles. The station is attached to the second bus. System model and simulation are performed using the electric vehicles and charging stations, as depicted in Fig.6. This scenario used four electric vehicles to understand the consequences of higher vehicle loads on the electrical system.

Fig.6. A four-vehicle charging station

• Case D: This scenario considers a higher electric vehicle load by connecting another charging station comprising four vehicles; hence, the electrical system powers eight electric vehicles. Here, the tow charging stations are connected on the second bus, and the model is created and simulated. This scenario provides data about the electrical system, voltages, harmonic distortion, and power factor when the system is under a more significant load.

• Case E: The last scenario deals with twelve connected electric vehicles. The subsequent section presents the simulation outcomes for all specified cases. Simulation outcomes and discussion This section discusses the simulation outcomes for all scenarios described in the previous section.

A. First case

The first case was simulated using MATLAB, depicted using Fig. 4, and simulation outcomes are listed in Table 1.

Table 1. First case simulation outcomes

.

The standard conditions were assessed to record system voltages without electric vehicle load. As indicated in Table 1, the first and second bus voltage levels are within the recommended thresholds (0.95 < V < 1.05) [16]. The currents drawn from the system without electric vehicle loads are indicated in Table 1. It is noteworthy that this situation has zero total harmonic distortion owing to completely linear loading.

B. Second case

Fig. 5 depicts this scenario comprising one connected vehicle. Table 2. lists the simulation outcomes for this case. Table 2. indicates that this scenario has 2.435% total harmonic distortion compared to zero in the first case. Similarly, the second bus records 10.74% total harmonic distortion (THD). Power factor follows a similar trend, decreased to 0.8996 in this case, compared to 0.9039 for the first. The second bus follows similar trends due to nonlinear electrical loading by the vehicles, increasing system THD, and reducing the power factor, as specified in Table 2. When the electric vehicle is connected to the system, the second bus voltage reduces slightly, as specified in Table 2.

Table 2. Second case simulation results

.

A slight change is observed because a single electric vehicle is connected. In contrast, the vehicle load might introduce harmonics in the electrical system, as depicted in the first and second bus current waveforms in Fig.7.

Fig.7. Current values for phase A, buses 1 and 2

Fig. 7 highlights that the second bus current waveform is distorted due to the electric vehicle load connected to it. In contrast, their effect was relatively minor concerning the current in the first bus, which was mildly affected due to a one-vehicle load.

Fig. 8 presents instantaneous values of phase A current to ascertain the presence of harmonics introduced by the vehicle connected to the second bus.

Fig.8. Analysis of second bus current (instantaneous values)

Fig. 8 indicates that the second bus has 10.74% total harmonic distortion due to one vehicle’s current drawn from the second bus. The first harmonic is most significant, compared to the relatively minor seventh and eleventh. The vehicle load introduces harmonics in the system, reducing the overall power factor, and deteriorating power quality. C. Third case This scenario considers one charging station and four vehicles connected to the second bus. The model was created and simulated, and its outcomes are specified in Table 3.

Table 3. Third case simulation results

.

Table 3. indicates that this scenario has higher total harmonic distortion than the second scenario; the first bus records 7.394% THD compared to 2.435% in the previous case. The observations are similar for the second bus, where 21.2% THD is recorded.

Power factor also degrades, reducing from 0.8996 in the previous case to 0.8888 for the third case corresponding to the first bus. Similarly, the second bus also recorded a power factor reduction from 0.8743 to 0.849. Connecting a charging station reduces second bus voltage, corresponding to a final value of 0.9765 P.U. from 0.9867 P.U., as specified in Table (3,2).

D. Fourth case

Here, the second bus powered two charging stations; the system model and simulation outcomes are specified in Table 4.

Table 4. Fourth case simulation results

.

Table 4, indicates that total harmonic distortion degrades further, i.e., from 7.394% in case three to 10.87% for the first bus in the present case. The second bus has similar observations, where THD degrades to 23.66%, indicating higher total harmonic distortion as the connected electric vehicle load increases. The system power factor degrades to 0.8812 in the current scenario, from 0.8888 in the previous observation corresponding to the first bus. In the case of the second bus, we see that the distortion power factor deteriorated to 0.9731 in the fourth scenario from 0.9783 in the second. The higher power actual in the second case is attributed to the higher active power drawn by the system than the more reactive power drawn by the electric vehicle charger. In the second bus context, connecting the charging station reduced voltage to 0.9646 P.U. from 0.9765 P.U., as highlighted in Table (3,4).

E. Fifth case

This scenario considers twelve electric vehicle drawing power from the electrical network. This scenario was simulated, indicating the first bus total harmonic distortion to increase to 12.69%, compared to 10.87% in the previous scenario. Similarly, the power factor degraded to 0.8774 from 0.8812, indicating adverse effects on power factor and THD as more vehicles started charging on the network. Moreover, as more electric vehicles are connected to the system (penetration level), the acceptable voltage threshold is breached. The overall voltage delivered to the vehicle dropped to 0.95 P.U. These evaluated scenarios and observations indicate that electric vehicle connections introduce harmonics in the power network, adversely affecting the system and lowering the power factor. Moreover, higher use levels (penetration level) cause voltage deviations beyond acceptable thresholds, as indicated for load additions in Fig. 9.

Fig. 9, indicates that when no vehicles are being charged, the voltage levels on the electrical network are within acceptable limits. one-vehicle addition caused the voltage to reduce to 0.9867 P.U., while the voltage fell further to 0.9765 P.U. on the second bus as four electric vehicles were connected to the network. Moreover, voltage levels of 0.95 P.U. are observed when twelve vehicles charge using the power system; this is a critical measure that falls beyond the acceptable limit. Put differently, a higher number of connected vehicles cause a more significant voltage deviation, triggering unacceptable voltages.

Fig.9. Network voltage drop as more vehicles charge from the network

Fig. 10, depicts the relationship between total harmonic distortion of the network as a function of the number of vehicles charging on the network. An electrical system free from non-linear load does not create any harmonic distortion. One vehicle adds 2.44% THD, which increases to 7.39% for four vehicles, and further degrades to 12.69% for twelve vehicles. Hence, the harmonic distortion in the electrical network correlates directly with the number of connected vehicles.

Fig.10. Total harmonic distortion of the network as a function of the number of connected vehicles

Fig. 11, depicts the relationship between network power factor as a function of electric vehicle count. If the network is free of electric vehicles, a 0.9039 power factor is observed, which deteriorates to 0.8996 for a single connected vehicle. It reduced further to 0.8888 with more vehicles, while the overall power factor was 0.8774 when the maximum number of vehicles were connected. It suggests that a higher number of vehicles cause the power factor to drop.

Fig.11. Power factor as a function of electric vehicle count

A higher number of connected vehicles raises power demand; hence, the current requirement increases linearly. Fig. 12, depicts the current drawn as a function of the increase of connected vehicles. The second bus supplied a 5.812 A current without any electric vehicle on the network; however, a one vehicle addition increased current to 8.01 A, while 32.14 A was drawn when twelve vehicles were connected.

Fig.12. Current drawn (load) as a function of the electric vehicle count connected to the network

Conclusion

This paper evaluated several scenarios to understand power network characteristics with increasing electric vehicles. A higher number of connected vehicles introduced more significant total harmonic distortion that breached the acceptable threshold; the system power factor was also reduced. THD values were 2.44% and 12.69% for one and twelve vehicles. Voltage dropped to 0.95 P.U. when twelve vehicles were drawing power. Hence, the adverse effects of electric vehicle charging must be regulated using charging control mechanisms, organised charging approaches, limiting electric vehicle purchase in a particular area, and electrical network augmentation, including filtering systems that eliminate harmonics from the electrical network.

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Source & Publisher Item Identifier: PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 99 NR 3/2023. doi:10.15199/48.2023.03.40

Analysis of Faults on High Voltage Direct Current HVDC Transmissions System

Published by Alya Hamid AL-RIFAIE1, Sanabel Muhson ALHAJ ZBER2, Noha Abed-AL-Bary AL-JAWADY3, Ahmed A. Abdullah AL-KARAKCHI4, Northern Technical University, Iraq.

ORCID: 1. 0000-0002-7978-2193; 2. 0000-0003-0232-9064; 3. 0000-0002-0275-2527; 4. 0000-0003-1151-3015

Abstract. High Voltage Direct Current (HVDC) Transmission with Voltage Source Converters (VSC) is gaining substantial interest from several utilities for various applications as compared to traditional HVDC transmission rely on thyristor technique. The paper presents analysis of three-level VSC-HVDC system during faults on the AC part. The system model is simulated in MATLAB/Simulink, with various faults analysed, such as single line to ground, line to line and double line to ground fault. The results obtained show that the control system respond well to all fault conditions.

Streszczenie. Transmisja wysokiego napięcia prądu stałego (HVDC) za pomocą konwerterów źródła napięcia (VSC) zyskuje duże zainteresowanie ze strony kilku zakładów użyteczności publicznej do różnych zastosowań w porównaniu z tradycyjną transmisją HVDC opierającą się na technice tyrystorowej. W artykule przedstawiono analizę trójpoziomowego systemu VSC-HVDC podczas zwarć na części AC. Model systemu jest symulowany w programie MATLAB/Simulink, z analizowanymi różnymi zwarciami, takimi jak zwarcie pojedyncze linia-ziemia, linia-linia i podwójne zwarcie linia-ziemia. Uzyskane wyniki pokazują, że układ sterowania dobrze reaguje na wszystkie stany awaryjne. (Analiza błędów prądu stałego w systemie przesyłowym wysokiego napięcia HVDC)

Keywords: HVDC, PWM, IGBT and VSC.
Słowa kluczowe: sieci HVDC, błędy prądu, IGBT.

Introduction

The High voltage direct current (HVDC) transmission system has advanced and gained widespread acceptance. Technical progress is mainly due to high voltage converters and high voltage devices [1-3]. The use of HVDC over the past thirty years has become an available method for transmitting energies in large quantities over long distances. Today HVDC is recognized as effective method for transmitting large power on overhead lines. Since HVDC is such a massive power transmission system, short-term breakdowns might result in complete darkness in the supplied area [4, 5]. In some renewable energy sources, wind energy takes the advantages of HVDC technologies to transmit energy and improve system performance. There are two technologies for HVDC transmission system [6-8] :

1- The Line Commutated Converter (LCC) is a thyristor-based technology.

2- Pulse Width Modulation (PWM) technology is used in the Voltage Source Converter (VSC) technology, which is based on IGBT.

VSC based HVDC systems are the preferred technology for effective network. In addition to lower harmonic generation, this integral allows for rapid and precise control of real and reactive power across both ways. Which improves power goodness and system reliability [9, 10]. The division of converters into two categories must be distinguished by their principle of operation. To function, the first category requires an AC system. Point wave suppression can be investigated using controlled semiconductors such as thyristors, when the AC system voltage drives current to move from phase to phase. As a result, the converter may control the energy exchanged between the AC and DC systems [11]. The second category of converters does not require an AC power source to function. As a result, they are known as self-switching converters. This category can also be separated into converters of current and voltage (CSCs) (VSC), depending on the DC circuit’s design. The CSC uses DC current with a reactor, whereas the VSC uses a steady DC voltage given by storage capacity [12]. This work presents analysis of the demeanour of the 3-level VSC-HVDC during failures on the AC side. The selected model is simulated in MATLAB/Simulink, with various faults analysed, such as line-line fault, single-line to ground fault and double-line to ground fault at the AC side of the system.

Design of HVDC System

Figure (1) demonstrates the simulation’s HVDC transmission model, which contain the following main components:

1- Transformer: To achieve the best voltage conversion, a type of transformer (wye grounded/delta) has been used. The current winding configuration prevents (filters) the third harmonics produced by the converter. The transformer ratios are at the rectifier side (the transmitter side) 0.915 and 1.1015 from the inverter’s side (the receiving side). Because of the converter reactor and transformer leakage reactors, the VSC’s output voltage can fluctuate in magnitude and phase from the alternating current system. In addition, the converter’s active and reactive power outputs are controlled.

2- AC filer: AC filters are an essential part of the connection model, the filter components are connected in parallel, either the side of the alternating current system or the side of the converter transformer. Due to high arrangement of PWM, the harmonics will be increased. With simplified filter design, the unwanted harmonics caused by switching action will be removed.

3- DC capacitor: This is linked to the VCS terminals, as far as the DC voltage is concerned with minimal ripple, the DC capacitor through the converter terminal may remove this noise and result in steady DC voltage. The capacitor shouldn’t be too large when system is interrupted due to turbulence, when the system is disrupted owing to turbulence, this ensures reliable steady-state performance.

4- DC Filter: The third harmonic is controlled in the DC side filters that block the high frequency, which is the primary harmonic found in the anode and cathode voltages. DC harmonics represent zero-sequence harmonics (odd multiple) that are moved to the DC side to maintain balance on this side. The difference between the electrode voltage must be controlled and kept to zero.

Fig.1. Two terminal HVDC System [6].

VSC Control System

The VSC is connected to the main circuit as shown in Figure (2), the design of the converter 1 and converter 2 is same. The two controllers are separated, there is no connection among them. Every variant had two degrees of freedom, in our state this controller is utilized as follows:

1- Station 1 (rectifier): P&Q
2- Station 2 (inverter): Vdc &Q

Fig.2. Connection of the main circuit to the VSC control system.

In this model, the control strategy uses the PWM technicality. The rectifier and the inverter give a various control model, in which case the model ought ever to meet the energy equilibrium as shown in equation (1)

.

where IDC represents DC bus current and Icap is the DC capacitive current.

The AC system must pump enough power (Pac) to charge the DC capacitor until Vdc reaches the specific level. The power flow may be controlled via controlling the DC voltage through changing the phase shift, assigned into equation (2). This control mode is specified into the rectifier and Figure (3) illustrates the control strategy for both ends of HVDC system.

.

In terms of time, the total power is expressed in equation (3) [13,14].

.

and

.

Equation (4, 5) propose that if Vq = 0, then the components of real and reactive power are commensurate into id, iq respectively. This feature is vastly used into controlling the three-phase VSC system which connected to the grid, it shows that switching to the periodic coordinate system leads to the possibility of controlling the id, iq independently. Thus, real and reactive power may be separately controlled.

Fig.3. Control Strategy for both terminal HVDC System [10].

Dynamic Execution

The dynamic execution in the transmission system is proved via simulating and monitoring as:

1- Dynamic response into step variations used in the main regulator references, DC voltage and active/reactive power are examples.

2- Recuperating from small and large AC system disturbances.

Matlab/Simulink used to represent and analyse the transmission system as shown in Figure (4) that indicate a schematic exemplification of VSC-HVDC system for length of (175km) between AC system 1 and AC system 2.

Fig.4. A Schematic exemplification of VSC-HVDC System.

Steady-State and Step Response

The results indicated in figures (5, 6) represent the dynamic responses of VSC-HVDC.

Station 1, which controls an active power converter, is unlocked at t=0.3s, and the power must tardily increase by 3 p.u. . while station 2 converter that control the DC voltage is unlocked at t=0.1s. At approximate t=1.3s steady state is achieved at both stations. In addition, the DC voltage equal to 1.8 p.u. at station 2 and the power of station 1 is equal to 3 p.u. . The reactive power flow is equal -0.1 p.u. in station 1 and a null value in station 2 system that controlled by both converters.

After reaching steady state, a -0.3 p.u. step is applied to the reference active power to converter 1 at t=1.5s, followed by a -0.1 p.u. step to the reference reactive power at t=2s. The dynamic response of the regulators are spotted.

Fig.5. Start up and P&Q step responses in station 1.
Fig.6. Start up and Vdc step responses in station 2.

Approximately, stability time is equal 0.3s. Similarly, figures including reference control current Id.

AC Side Disturbances to ground

At station 2, a slight and significant disturbance occurs in the normal situation. Three types of faults were tested:

1- Single Line fault (S.L.G.)
2- Line- Line fault (L.L)
3- Double-Line to ground fault (D.L.G.)

The system retrieval from the disturbances would be fast and stable as explained below.

Single Line to Ground Fault

Figure (7) shows the S.L.G. fault, in which the DC power transferred is decreased by 50% and the DC voltage raised to 2.2 p.u. . As a result of this, the capacitance on the DC side has been overcharged. To sustain the DC voltage within a steady state, station 1’s controller controls the active power output. After the fault, the system is retrieval good after 1.3s. The reactive power shows damped fluctuations about 10Hz.

Fig.7. Single line to ground fault results.
Fig.8. Line to Line fault results.
.
Fig.9. Double Line to ground fault results
Line-Line fault

The L.L. fault is depicted in Figure (8). It’s important to note that the transferred DC power is decreased by 90% and the DC voltage raised toward (3 p.u.). The capacitance on the DC side has been overcharged as a result. As part of the active power control (at station 1), a special function called “DC Voltage Control Exceeds” attempts to keep the DC voltage within a certain range at all times. After 1.3 seconds, the system has been restored to full functionality. The reactive power shows damped fluctuations at 10 Hz.

Double-Line to Ground Fault

Figure (9) show the D.L.G. fault, It is worth noting that the L.L fault reduces the transmitted DC power by 90% while increasing the DC voltage to (2.3 p.u.). The capacitance on the DC side is being overcharged. The active power control (in station 1) has a function (DC Voltage Control Exceeds) that seeks to keep the DC voltage constant. After the fault, the system is retrieval good after 1.3s. In the reactive power, note the damped oscillations at 10Hz.

Conclusions

This paper presents the stable condition and dynamic performance of VSC in HVDC transmission systems over progressive variations of active and reactive powers. These analyses are performed under balance and unbalanced faults conditions. In each state, the suggested control strategy was found to satisfy dynamic responses of the suggested system. By simulation, it has been shown that VSC-HVDC can achieve fast response control of the bidirectional power transfer. It may also be noted that for S.L.G faults, the DC power transmitted is decreased by 50% while the DC voltage tend to rise. Also, during L.L. and D.L.G. faults, the DC power transmitted is decreased by 90% when the DC voltage rises. The system is fully recovered after the fault, within 1.3 s.

REFERENCES

[1] Mohammed A. Ibrahim, Waseem Kh Ibrahim, and Ali N. Hamoodi. “Design and Implementation of Overcurrent Relay to Protect the Transmission Line.” International Journal of Engineering Research and Technology 13.11 (2020).
[2] Ahmed M. T. Ibraheem, Mohammed A. Ibrahim, and Abdullah K. Shanshal. “PLC Based Overcurrent Protection of Threephase Transmission Line.” (2020).
[3] Bashar M. SALIH, Mohammed A. IBRAHIM, and Ali N. HAMOODI. “Differential Relay Protection for Prototype Transformer.”
[4] Polewaczyk, Mateusz, and Sylwester Robak. “Analiza interakcji w układach hybrydowych MIDC.” Przegląd Elektrotechniczny 95 (2019).
[5] POLEWACZYK, Mateusz, and Sylwester ROBAK. “Układy HVDC we współczesnych systemach elektroenergetycznych.” Organ 7 (2016): 16.
[6] Vasquez-Arnez, Ricardo L., Jose A. Jardini, and Marcos T. Bassini. “Dynamic Performance of Line Commutated Converter-Based Multiterminal HVDC Systems.” Przegląd Elektrotechniczny 91.9 (2015): 247-253.
[7] Ali M. ELTAMALY, Y. SAYED and AMER NASR A. ELGHAFFAR ,”HVDC SYSTEM OPERATION AND FAULT ANALYSIS” , ANNALS of Faculty Engineering HunedoaraInternational Journal of Engineering Tome xv 2017-Fascicule 4
[November].
[8] Raheel Muzzammel, Ali Raza, Mohammad Rashid Hussain and et. “MT-HVdc Systems Fault Classification and Location Methods Based on Traveling and Non-Traveling Waves—A Comprehensive Review” , Applied sciences,2019,9,4760.
[9] MUJIB J. PATHAN, Dr. V. AKULKARNI, “FAULT ANALYSIS OF HVDC TRANSMISSION SYSTEMS” , International Journal of Electrical Engineering & Technology(IJEET) , Volume 7, Issue3,May-June, 2016, pp.106-116, Article ID:
IJEET_07_03_009.
[10] Ashwini K. Khairnar, Dr. P. J. Shah, “ DC LINE-TO-LINE FAULT ANALYSIS FOR VSC BASED HVDC TRANSMISSION SYSTEM”, International Journal of Advance Research in Science and Engineering, Vol. NO.6,Issue No.07,July 2017.
[11] Dr. Adil Hameed Ahmed, Ahmed Saeed Abdul-Sada, “ HVDC Transmission Systems based Multi-level Voltage Source Converters for Iraqi Super Grid” , Eng.& Tech.Journal , Vol.32 , Part(A), No.7 , 2014.
[12] Ahmed A. Elserougi, Ayman S. Abdel-Khalik, A New Protection Scheme for HVDC Converters against DC-Side Faults with Current Suppression Capability, IEEE transactions on power delivery, 29(4), August 2014.
[13] Manickam KARTHIKEYAN, Yew Ming YEAP and Abhisek, “Simulation and Analysis of Faults in High Voltage DC (HVDC) Power Transmission” , Conference Paper, October 2014.
[14] Amirnaser Yazdani and Reza Iravani, “voltage-sourced converters in power system modeling, control, and applications”, John Wiley & Sons, Inc., 2010.

Authors: Alya Hamid Al-Rifaie1, E-mail: alya.hamid@ntu.edu.iq; Sanabel Muhson Alhaj Zber2, E-mail: sanabel.m.mohammed@ntu.edu.iq; Noha Abed-AL-Bary Aljawady3, E-mail: Noha.m.aljwady@ntu.edu.iq; Dr. Ahmed A. Abdullah Al-Karakchi4, E-mail: ahmedalkarakchi@ntu.edu.iq;

Source & Publisher Item Identifier: PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 98 NR 2/2022. doi:10.15199/48.2022.02.10

Physical Model of Power Circuit of Three-Phase Electric Arc Furnace

Published by Mirosław WCIŚLIK, Paweł STRZĄBAŁA, Kielce University of Technology, Department of Electric Engineering, Automatic Control and Computer Science

Abstract. The paper deals a model of the circuit arc furnace designed for electrotechnology or fundamentals of electrical engineering laboratory. This model works at low currents, without high temperature components. In this way, the cooling and dissipation of energy are avoided. This model allows the study of the impact of the supply system restrictions, reactive power compensation problems, harmonic propagation in the system and characteristics verification designated analytically or by simulation.

Streszczenie. W pracy przedstawiono model obwodu pieca łukowego przeznaczony do laboratorium elektrotechnologii lub podstaw elektrotechniki. Model ten pracuje przy niskich prądach, bez elementów o wysokiej temperaturze. W ten sposób unika się układów chłodzenia i rozpraszania energii. Umożliwia on badanie wpływu ograniczeń układu zasilania, problemów kompensacji mocy biernej, generacji harmonicznych w systemie oraz weryfikację charakterystyk wyznaczanych analitycznie lub symulacyjnie. Model fizyczny obwodu elektroenergetycznego trójfazowego pieca łukowego.

Keywords: arc furnace, nonlinear load, rectifier, physical model.
Słowa kluczowe: piec łukowy, obciążenie nieliniowe, prostownik, model fizyczny

Introduction

The quantity of iron and steel production is still an economic potential measure of the country’s development. Industrial steel production started at around 1740 when the crucible process was used. In the steel production market, between 1940 and 1970, four different technologies competed simultaneously in deliveries of steel. Currently, two technologies are used, what follows from the needs of the market. Diffusion of the electric steel process results from scrap recycling, the use of continuous casting of steel and possibilities of steel grades production on request. It is related to far-reaching changes in the structure of the steel industry, due to the small size of the production installation, the availability of steel scrap as a raw material and better energy efficiency compared to the previous open hearth process. About 70% of demand of steel is met by the iron ore reduction process and the carbon-rich melted iron processed into steel using oxygen in the basic oxygen oxide converter process. The process is marked as BOS, BOF or LD. This process is an improved Bessemer process. The open hearth and Bessemer processes were completely replaced by LD and the arc processes arc [1].

The economics aspects of the operation of the furnace, i.e. the reduction of the power consumed by the device per tonne of steel, reduced consumption of the lining and electrodes have been extended to research into ensuring good power quality [2],[3]. This is due to the fact that the arc furnace is a high power load of a stochastic variable nature. As a result, there are frequent changes in the power consumed by the device, which cause flickers. These phenomena occur mainly in the melting phase, and their frequency has range from 0.5 to 30 Hz. As a result of studies it was found that voltage changes of only 0.5% in the range of 6-10 Hz cause flickering of incandescent and discharge lamps perceptible by man. The second unfavourable phenomenon that occurs during the operation of an arc device is related to the high non-linearity of load – electric arcs. As a consequence, higher harmonics are propagated to the mains.

Technical solutions used in modern arc furnaces require the cooperation of specialists in many fields such as metallurgy, electro heating, automatics, power engineering, environmental protection. In the electric steel process, metallurgists have play a dominant role. They are responsible for the final technology of the electro-steel process. However, you should ask the question: Have all the problems of the furnace been resolved? The answer is not positive. The importance of some of them was reduced: using computer control, foamed slag, and liquid metal lake. These problems are particularly related to the electric circuit of the arc furnace. The problems interactions arc furnaces during the smelting process on the energy system and the operating characteristics of the power circuit are still open. In the positioning of the electrodes, complex algorithms are used, not taking into account the feedback circuit and arc voltage measurement accuracy. In order to stabilize phase currents of AC arc furnaces, averaged for a few minutes the measured currents is often used. Therefore, we can speak rather of avoiding problems than solving them.

There is a need to do this research in physical form. Therefore, the main objective is to develop an equivalent model of an arc furnace in physical form. The physical model should enable the analysis of the phenomena of higher harmonic propagation and flickering of light in supply network. Such model is proposed. The analyses will be conducted in low-power circuits, thus increasing the safety of persons and reducing the economic costs of conducting research experiments. This model will be useful both for research and teaching purposes.

Physical model of the arc furnace

The electro-energy model of the arc furnace is difficult to implement in simple laboratory conditions. The electric arc furnace is characterized by variable parameters of its operation, chemical and thermal influences harmful to the environment. Therefore an equivalent physical model of such circuit can be useful. In [5] the electronic welding arc imitator was proposed for applications in diagnostics of welding sources. The executive element is controlled by a programmable unit with a mathematical electric arc model. The electric arc characteristics are obtained digitally. As a result it is possible to carry out research in a wide range of currents (without the need to exchange electrodes), with a high speed, easier automation and the lower qualifications of staff. The use of such imitator has many advantages, but in [5] the author focused only on mathematical modeling of electric arc similar as in [6], omitting the problems of physical accomplishment of the model.

To meet these requirements the electrical diagram of the balanced three-phase circuit with nonlinear load is analysed – figure 1. The circuit has not neutral wire. Nonlinear elements in each phase are electric arcs models in the arc furnace. The voltage Uo(t) is the instantaneous value of the potential difference between the star centers of the load and the power source.

Fig.1. The scheme of a three-phase circuit with non-linear load [7]

Analysis of this circuit with non-linear electric arc model was conducted in [7]. In order to implement of physical model of such a circuit, the nonlinear element in each phase is replaced by Graetz bridge with parallel output capacitor C, isolated DC/DC converter and resistive load RL. The diagram of such circuit is shown in figure 2.

Fig.2. The three-phase circuit diagram of non-linear load in the form of bridge rectifiers

Nonlinear load is described by signum function:

.

where: k = 1,2,3 is the phase number, Ud – forward voltage of rectifier diode.

For balanced three phase circuit from figure 2, the equations for circuit can be obtain on the basis equation for single phase. The equation for one phase can be written in the following form:

.

where Rd is series resistance of the rectifier diode.

The supply voltage is described:

.

where Ѱ is the phase shiftment angle between supply voltage and first harmonics of the load voltages. The voltage U0(t) is:

.

Connecting the resistance load RLk to the rectifier output without DC-DC converter the second equation has the form:

.

Waveforms of circuit for single phase shown in the figure 3. The output voltage fluctuations are small for a large capacitor. The voltage on the rectifier as seen from the power supply terminals is similar to the signum function.

Fig.3. The waveforms voltages and currents in single phase of the circuit from figure 2

For elimination of interference and separation of electrical ground, isolated DC/DC converter is used. Isolated DC-DC converter with push-pull topology is shown in figure 4. The DC voltage VIN is converted to the high frequency AC voltage by using SN6501 module and next converted to the voltage level in the transformer Tr1 with split winding. This circuit is called a DC/DC transformer driver. Secondary voltages of transformer Tr1 are rectified and filtered in a low pass LC filter [8].

Fig.4. The diagram of isolated push-pull DC-DC converter with integrated circuit SN6501 to control transformer with split primary and secondary winding

The control block SN6501 is a specialized integrated circuit manufactured by Texas Instruments, equipped with power transistors Q1 and Q2, cooperating with a transformer with divided primary and secondary winding [9]. Asynchronous frequency divider generates two complementary output signals with input frequencies fOSC. The logical BBM (break-before-make) protects against simultaneous switching on of two transistors and ensures dead time between transistor switching on.

Simulation of circuit in MATLAB/Simulink

Simulation of circuit from figure 2 was carried out in MATLAB/Simulink system. The SimPowerSystem package was used. The diagram of circuit created in Simulink is shown in figure 5. Blocks MGraetza_L1, MGraetza _L2 and MGraetza _L3 include bridge rectifiers connected in star. Rectifiers are supplied from balanced source AC voltage through inductances Lk and resistance Rk, where k = 1,2,3 and is the phase number. Balanced three-phase voltage source created with voltages source and phase shiftment equal 120°. The output ports Ivec, Uvec, Uo – are respectively vectors of instantaneous values phase current, voltages on the rectifier by AC side and voltage potential difference between the center points of the power source and the load. The DC-DC converters are denoted by Conv1,Conv2 and Conv3 blocks. The outputs of these converter are loaded by resistors RL1, RL2 and RL3. These resistive loads are connected by common ground, isolated from rest of the circuit. The diagram of isolated DC/DC converter from figure 3 in Simulink is presented in figure 6.

Fig.5. Model of circuit form figure 2 in Simulink
Fig.6. Model of push-pull DC-DC converter in Simulink

The transformer driver circuit is performed by pulse generator, Pulse1 and Pulse2, which control power transistor T1 and T2. The ideal multi-winding transformer was used, without taking into account the saturation phenomenon of the core.

Waveforms of voltages and currents in analysed circuit

The waveforms of voltages and currents in circuit are shown in figures 7-9. The circuit parameters are as follows: supply voltage Es=24V, series inductance Lk=30mH and Rk=1mΩ in each phase. It was assumed that C1=C2=C3=2mF and RL1=RL1=RL1=15Ω. Forward voltage of the diodes are 0,7V. The switching frequency of the transistors T1 and T2 is equal 10 kHz with duty cycle 50 %. Series resistance of the transistors and diodes is 0,1 Ω. Simulations were carried out with a constant step time equal to 1μs.

Fig.7. Waveforms current of circuit in each phase

Transient processes are visible at the moment turn on power supply. The peak currents are higher than in steady state. In the steady state, the shape of currents is similar to sinusoidal. The waveforms of voltages U1, U2, U3 on the nonlinear loads in each phase are similar to signum function. Amplitude of signum function in this case is sum of output voltage and forward voltage of two diodes. These waveforms are rectangular wave with accuracy to the fluctuations of the output voltage rectifiers.

Fig.8. Voltages on the nonlinear loads similar to signum function
Fig.9. The instantaneous voltage of the potential difference between the zero points of the load and the power source

The obtained instantaneous waveforms of the circuit for resistive load, prove that power circuit of arc furnace may be modelled using bridge rectifiers. Characteristics of bridge rectifier as seen from AC voltage source is signum function of supply current. This characteristic can be further shaped by replacing the resistive load with the computer controlled transistor.

Conclusions

Physical model of the three phase circuit allowing analysis interaction of arc furnace and power system we can realize modeling arc furnace by using simple elements, bridge rectifier and isolated DC/DC converter. Characteristics of such load are similar to signum function. The model can be used in the laboratory and is a basis for analysis of the impact of such load on the power system. The components are designed to work at low currents and without the use of high temperature components. Therefore, cooling systems is not necessary. The resulting instantaneous waveforms of currents and voltages in this circuit are similar to the waveforms in electric arc real circuit.

REFERENCES

[1] Teoh L.L.: Improving environmental performance in mini-mills, Steel Times Intemational, March 1991
[2] Wciślik M., Kazała R.: Symulacja wpływu zakłóceń długości łuku na charakterystyki obwodu pieca łukowego. Zeszyty Naukowe Politechniki Świętokrzyskiej: Elektryka 38, Kielce 2000.
[3] Gomez A., Durango J., Mejia A.: Electric Arc Furnace Modeling for Power Quality Analysis, IEEE ANDESCON 2010
[4] Warecki J., Gajdzica M.: Załączanie transformatora pieca łukowego w sieci z układem filtrów wyższych harmonicznych. Przegląd Elektrotechniczny, ISSN 0033-2097, R. 91 NR 4/2015
[5] Sawicki A.: Imitatory łuków w diagnostyce źródeł spawalniczych, XLIX Międzyuczelniana Konferencja Metrologów MKM 2017. Zeszyty naukowe Wydziału Elektrotechniki i Automatyki Politechniki Gdańskiej Nr 54, s. 195-198, 2017
[6] Wciślik M.: Analityczne modele łuku elektrycznego, Przegląd Elektrotechniczny, ISSN 0033-2097, R. 84 NR 7/2008.
[7] Wciślik M.: Elektrotechnika pieców łukowych prądu przemiennego – zagadnienia wybrane. Politechnika Świętokrzyska, Kielce 2011
[8] Dokic B. L., Blanusa B.: Power Electronics Converters and Regulators, Springer, Switzerland 2015
[9] Texas Instruments: SN6501 Transformer Driver for Isolated Power Supplies, 2014

Authors: Professor Mirosław Wciślik, Kielce University of Technology, Department of Electric Engineering, Automatic Control and Computer Science, al. Tysiąclecia Państwa Polskiego 7, 25- 314 Kielce, E-mail: wcislik@tu.kielce.pl; MSc Paweł Strząbała, Kielce University of Technology, Department of Electric Engineering, Automatic Control and Computer Science, al. Tysiąclecia Państwa Polskiego 7, 25-314 Kielce, E-mail: pstrzabala@tu.kielce.pl

Source & Publisher Item Identifier: PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 94 NR 4/2018. doi:10.15199/48.2018.04.26

Inter-Turns Short Circuits in Stator Winding of Squirrel-Cage Induction Motor

Published by Maciej ANTAL, Wrocław University of Science and Technology, Department of Electrical Machines, Drives and Measurements

Abstract. A physical model of a squirrel-cage induction drive, allowing to stimulate coil short circuits in the front part of the motor, was used to investigate the phenomena accompanying short circuits. Assuming that a short circuit occurs during motor operation, phase stator current time waveforms, current in short-circuited coils and instant power were measured. Various cases of coil short circuits were analysed. The influence of the resistance value of the short-circuit point and short-circuit magnitude on electromechanical phenomena occurring during a stator winding short circuit was investigated.

Streszczenie. Za pomocą modelu fizycznego klatkowego silnika indukcyjnego umożliwiającego symulowanie zwarć zwojowych w strefie czołowej silnika, zbadano przebieg zjawisk towarzyszących zwarciom. Zakładając, że zwarcie następuje w czasie pracy silnika, zmierzono przebiegi czasowe prądów fazowych stojana, prądu w zwojach zwartych oraz mocy chwilowej. Rozpatrzono różne przypadki zwarć zwojowych. Zbadano wpływ wartości rezystancji punktu zwarcia oraz rozmiaru zwarcia na przebieg zjawisk elektromechanicznych podczas zwarcia uzwojeń stojana maszyny. (Zwarcia zwojowe w uzwojeniu stojana klatkowego silnika indukcyjnego).

Keywords: induction motor, stator winding faults, measurements, coils short circuits
Słowa kluczowe: silnik indukcyjny, uszkodzenia uzwojenia stojana, pomiary, zwarcia zwojowe

Introduction

Electrical faults of stator windings in induction motors are the second most frequently occurring faults after bearing defects [1, 2]. The reason for this fault is usually winding insulation degradation resulting from difficult operating conditions, or a long exploitation time. The possible faults encompass winding, coil and interphase short circuits, as well as earth faults. The detection and diagnostics of such faults has been extensively described in literature [e.g. 3, 4, 5, 6, 7]. The most considerable interest was aroused by winding short circuits because in their initial phase they are very hard to detect, and their local impact is extremely destructive. Interesting results were obtained from the field circuit analysis of faulty induction motors [8, 9]. Current density in short-circuited turns may reach very high values (even up to 75 A/mm2 with negligible resistance of the short circuit point), which means the risk of quick burning out of these turns. This may result in switching off the shorted turns or interrupting the phase. Long-term short circuits, which are possible when the resistance of a short circuit point is high, increase the temperature in the short-circuit area and consequently lead to insulation overheating and short circuit growth.

Each, even very small, electric fault of motor winding is easily observable in the three-phase instantaneous power waveform. During a fault, the variable component with a frequency of 100Hz, whose amplitude is the measure of fault size, becomes more evident.

Stator winding faults result not only in the disturbances of torque, speed, power or current waveforms, but they are also the reason for motor overheating. Excessive heating refers to stator winding and also other key motor elements: the rotor cage and stator core. It is confirmed by the heating curves of these elements determined for a motor with four shorted stator windings [10]. The investigation of 30-second short circuits of larger size windings showed that both the temperature increase in stator windings and the rotor cage grow nonlinearly along with the number of shorted turns of stator phase winding. The increase in the defect is followed by a faster winding temperature gain.

Hence, it seems reasonable to verify the phenomena accompanying coils short circuits using a physical model. Such a model allows to observe the consequences of short circuits in real power supply conditions.

Tested motor

The experimental tests were conducted at an experimental setup for electromechanical research on low-power machines. The measurement apparatus installed at the setup allows to record both static and dynamic electrical values (current, voltage, power) and also mechanical ones (torque, speed).

The research was conducted on a specially rewound motor allowing to model coils short circuits in its front part. The beginnings and ends of particular stator winding coils were installed on the connector board (Fig.1). In addition to this, one of the coils was divided into a few groups of windings. The thus prepared physical model allows to simulate short circuits of whole coils and a few windings of one coil. A short circuit was induced by a contactor being a part of the shorted circuit. Converter clamps enabled recording currents in shorted turns.

Fig.1. Induction motor for coils short circuit simulation

Research results

Using the above described experimental setup and the machine model, the investigations of coils short circuits in a small power motor were conducted. The influence of the resistance value of the short circuit point and the fault size on the phenomena accompanying short circuits was analysed. During the research, the values of voltage, currents, torque and machine speed were recorded. In the monitoring of machine condition the most important factor is observing phase-currents and instantaneous power, thus a harmonic analysis of their waveforms was conducted. The waveforms currents in shorted turns are also presented as their value provides the information on heating and a possible fault development.

Fig.2. a) Currents in squirrel cage motor shorted phase during single coil short circuit at various values of short circuit resistance, b) fragment

Fig.3. a) Current in shorted circuit with one shorted coil at various values of short circuit resistance, b) fragment

Figures 2 – 7 present the results of research on the influence of the value of short circuit point resistance on the phenomena accompanying these short circuits. In the investigations, the most extreme short circuit states which could be obtained with the used model were selected: four shorted turns and the whole shorted coil (51 turns). Figures 2 – 4 present the research on the influence of the values of the short circuit resistance point on waveforms in the motor with a single shorted coil, and Figs. 5 – 7 in a motor with four shorted turns.

Fig.4. a) Instantaneous power of motor during single coil short circuit at various values of short circuit resistance, b) fragment

Fig.5. a) Currents in squirrel cage motor shorted phase during short circuit of four turns at various values of short circuit resistance, b) fragment

Fig.6. a) Currents in a shorted circuit with four shorted turns at various values of short circuit resistance, b) fragment

Fig.7. a) Instantaneous power in a motor with four shorted turns at various values of short circuit resistance, b) fragment

In the case of a motor with a shorted coil, three recordings were made for shorting resistance values of 0.005; 1 and 2Ω. In the case of a motor with four shorted turns, four recordings were made for shorting resistance values of 0.005; 0,1; 0.2 and 0.5Ω. In both cases the shorting resistance increase decreases disturbances caused by a short circuit. All values of the phase currents of a shorted phase (Figs. 2 and 5), currents in shorted turns (Figs. 3 and 6), and also the mean value of instantaneous power input to the motor (Figs. 4 and 7). When a fault is small, as is the case of four shorted turns, these phenomena are hard to observe in both phase currents (Fig. 5) and power used by the motor (Fig. 7).

Another tested value was the influence of a stator winding fault size on the phenomena existing in a machine by simulating a short circuit of four, twelve, twenty two and fifty one turns (whole coil) with a resistance of 0.005Ω.

Fig.8. a) Current in the phase when short circuit occurs during short circuits of various values (shorting resistance value: 0.005Ω), b) fragment

Fig.9. a) Current in shorted turns during short circuits of various values (shorting resistance value: 0.005Ω), b) fragment

Fig.10. a) Instantaneous power of motor during short circuits of various values (shorting resistance value: 0.005Ω), b) fragment

Global values, such as current in a shorted phase (Fig. 8) or power used by a motor (Fig. 10) in the steady state after the fault clearly grow along with fault increase. However, such an increased could not be observed in the waveforms of shorted circuit currents (Fig. 9).

Due to the fact that in the research the same resistance value of the short circuit point was used for all analysed shorted circuits, its ratio to particular resistance values in shorted turns varies. This is why currents flowing through shorted turns achieve various values and are not proportional to the fault size.

Summary

The presented research results confirm the field circuit calculations conducted earlier and, above all, they prove that as a result of coils short circuits truly dangerous phenomena (current in shorted turns) are hardly observable and or even invisible in the waveforms of recorded, external physical values. However, it is possible to observe the asymmetry of stator currents, significant pulsations of instantaneous power and incremental increase in the average value of instantaneous power at the moment when a short circuit occurs. The detection of coils short circuits is particularly desirable at the stage before short circuits cause significant damage to windings. A coils short circuit may last for some time without extending and thus damaging new turns when it encompasses a small number of turns or the resistance value of the short circuit point is significant in comparison with the resistance value of shorted turns.

To sum up the results of the research on coils short circuits, one can conclude that they remain nearly invisible in phase current and instantaneous power waveforms. The earlier research on the influence of machine load on fault detection indicate that a small coils short circuit seems easier to detect when the machine is in a neutral gear position. Short circuits encompassing a larger number of turns are easier to detect. Regardless of size, coils short circuits are signalled in instantaneous power time waveforms. In the waveform the constant and variable components with double current and voltage frequencies dominate. Both of these components grow incrementally as a result of a coils short circuit and this change is noticeable even when the number of shorted turns is small. The growth of instantaneous power is also highly dependent on the resistance value of the short circuit point. The deformation of supply voltages does not have any influence on the detectivity of coils short circuits.

REFERENCES

[1] Pietrowski W., Górny K., Detection of inter-turn short-circuit at start-up of induction machine based on torque analysis, Open Physics, Volume 15, Issue 1, 29 Dec 2017
[2] Sahraoui M., Zouzou S. E., Guedidi S., A new method to detect inter-turn short-circuit in induction motors, The XIX International Conference on Electrical Machines – ICEM 2010, 2010
[3] Wolkiewicz M., Tarchała G., Orłowska-Kowalska T., Kowalski Cz., Online stator interturn short circuits monitoring in the DFOC induction-motor drive. IEEE Transactions on Industrial Electronics. 2016, vol. 63, nr 4, s. 2517-2528
[4] M’hamed Drif, Antonio J. Marques Cardoso, Stator Fault Diagnostics in Squirrel Cage Three-Phase Induction Motor Drives Using the Instantaneous Active and Reactive Power Signature Analyses, IEEE Transactions on Industrial Informatics, 2014, vol. 10, Issue: 2
[5] Maryam Eftekhari, Mehdi Moallem, Saeed Sadri, Online Detection of Induction Motor’s Stator Winding Short-Circuit Faults, IEEE Systems Journal. 2014, vol. 8, Issue: 4
[6] Rama Devi N., Siva Sarma D. V. S. S., Ramana Rao P. V., Diagnosis and classification of stator winding insulation faults on a three-phase induction motor using wavelet and MNN, IEEE Transactions on Dielectrics and Electrical Insulation, 2016, vol. 23, Issue: 5
[7] Dorrell D. G., Makhoba K., Detection of Inter-Turn Stator Faults in Induction Motors Using Short-Term Averaging of Forward and Backward Rotating Stator Current Phasors for Fast Prognostics, IEEE Transactions on Magnetics, 2017, vol. 53, Issue: 11
[8] Antal M., Antal L., Zawilak J., Badania uszkodzeń uzwojenia stojana klatkowego silnika indukcyjnego, Maszyny Elektryczne Zeszyty Problemowe, 2007, nr 76, 83-88
[9] Fireteanu V., Constantin A-I., Romary R., Pusca R., Ait-Amar S., Finite element investigation of the short-circuit fault in the stator winding of induction motors and harmonics of the neighboring magnetic field, 9th IEEE International Symposium on Diagnostics for Electric Machines, Power Electronics and Drives, 2013
[10] Antal L., Gwoździewicz M., Marciniak T., Antal M., Badania skutków cieplnych zwarć zwojowych w uzwojeniach stojana silnika indukcyjnego, Prace Naukowe Instytutu Maszyn, Napędów i Pomiarów Elektrycznych Politechniki Wrocławskiej. Studia i Materiały, (2012), nr 32, 316-324

Author: Maciej Antal, PhD Eng. Wrocław University of Science and Technology, Department of Electrical Machines, Drives and Measurements, Smoluchowskiego 19, 50-372 Wrocław, Poland, E-mail: maciej.antal@pwr.edu.pl

Source & Publisher Item Identifier: PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 97 NR 1/2021. doi:10.15199/48.2021.01.15

Laboratory Research of Non-Overvoltage Transistors Control Method in AC Voltage PWM Controller

Published by Andrzej KANDYBA1, Marian HYLA2, Igor KURYTNIK3,
The Polish Engineers and Technicians Association SIMP Group Silesia (1), Silesian University of Technology, Faculty of Electrical Engineering (2), State School of Higher Education in Oświęcim (3)

Abstract. Method of controlling transistors in AC voltage PWM controller aimed at eliminating commutation overvoltages is presented in the paper. The method is based upon keeping continuity of load current; this is achieved by appropriate control of transistors on the basis of detecting voltage sign (polarity) at the supply terminal and detecting load current sign (polarity). This type of control does not depend on character of the load and it makes possible increase of converter’s efficiency by elimination of RC circuits protecting transistors from overvoltages. The scheme of main circuit is shown as well as waveforms demonstrating the control principle. Four different characteristic operating conditions are discussed. Measurements have been done to verify the method with real three-phase AC converter with RL-type load and next non-thermic plasma.

Streszczenie. W artykule przedstawiono metodę sterowania tranzystorów regulatora napięcia przemiennego pozwalającą na wyeliminowanie przepięć komutacyjnych. Metoda bazuje na zachowaniu ciągłości prądu obciążenia; co jest osiągane za pomocą odpowiedniego sterowania tranzystorów na podstawie detekcji znaku napięcia zasilania i znaku prądu obciążenia. Sterowanie jest niezależne od charakteru obciążenia i pozwala na wzrost sprawności przekształtnika poprzez eliminacje obwodów RC zabezpieczających tranzystory przed przepięciami. Przedstawiono schemat obwodów głównych oraz przebiegi ilustrujące metodę sterowania. Omówiono cztery charakterystyczne przypadki pracy. W celu zweryfikowania metody przeprowadzono pomiary dla trójfazowego regulatora napięcia przemiennego z obciążeniem typu RL oraz przy zasilaniu plazmotronu plazmy nietermicznej. (Badanie bezprzepięciowej metody sterowania tranzystorami regulatora napięcia przemiennego w warunkach laboratoryjnych).

Keywords: AC-AC PWM voltage controller, power electronics, power system, switching surges
Słowa kluczowe: energoelektronika, układy zasilania, sterowanie impulsowe

Introduction

Power electronics AC voltage controllers are present in, for instance, drive systems, electric heating engineering, power engineering. They are used as power controllers, active filters and elements of power conditioners [1, 3, 4, 6, 7, 8, 9,10,11]. In drive systems they are used in soft-start circuits, in speed control or power control at machine shaft, in electric heating engineering mostly in power or temperature control circuits, and in power engineering in active filters systems. Due to their specific characteristics [1, 10], transistor AC voltage converters present an alternative to thyristor circuits. These converters are also used as supply systems for non-thermal plasma generators, which in turn are used in the process of purifying the air (by eliminating toxic compounds) during varnishing (in paint shops), in fossil fuel burning processes, in IC engines, or during some chemical reactions [2].

The main goal of PWM control in AC voltage controllers is control of output voltage fundamental harmonic value by changing pulse-duty factor of control impulses, where frequency is much higher than frequency of supply voltage. Pulse-duty factor of the impulse is the control quantity. In standard PWM control method, in order to avoid shortcircuiting of the circuit, dead times are introduced between switching the transistors in different branches of the converter. In this case, with RL-type load, when all transistors in the circuit are switched off, overvoltages are generated due to self-induction phenomenon. This effect of course enforces the application of special surge protection circuits. However, it is possible to use a specific method of PWM control, without using dead times, when commutation overvoltages at load side will not be generated.

Presented control method was used to supply of three-phase plasmatron of non-thermal plasma.

Control algorithm

To discuss the control method we shall use a single-phase voltage controller shown in Figure 1. The current flow may be bi-directional in all converter branches. In addition, circuits detecting voltage sign (polarity) at supply terminal Du and detecting load current sign (polarity) Dio are required. Signals of voltage sign signu and load current sign ssigni0 are input into the control circuit US; this circuit generates impulses T1, T2, T3, T4 controlling transistor switching, and the switching sequence depends on current values of functions signu and signi0. Capacitor C protects the circuit against circuit break at the supply side.

Fig. 1. Scheme of single-phase AC voltage controller; control circuit US is shown

In the control circuit (Fig. 1), the load current flows in the loop consisting of either supply source-horizontal branch-load or load-vertical branch. At the same time, short-circuiting between horizontal and vertical branches must be avoided. The characteristic feature of proposed control method lies in eliminating the necessity of using dead times during transistor switching. This is achieved by pulse switching of one transistor only in a given operating mode, while the control signals of other transistors ensure the continuity of load current flow. Switching the second transistor on or off (this is transistor ensuring current flow in the circuit) is achieved spontaneously, due to voltage distribution in the circuit, when current in the pulsed transistor either decays or appears again.

Table 1 shows different states of signals controlling the transistors, in accordance with supply voltage and load current signs. The arrows mark the direction of transition between different operating conditions of the circuit.

Table 1. States of transistor control signals

.

Detection of supply voltage and load current signs is the starting point for controlling the circuit. In real (actual) converters, these sign detection signals may not be generated at the precise time instants when they occur; this may lead to short-circuiting or overvoltages in the circuit. In order to avoid this danger, a short time delay has been introduced for switching transistor control signals, when the control circuit receives information on change in voltage or current sign. Change in load current sign results in delay in switching transistors T1, T2 of horizontal branch, and voltage sign change results in delay in switching transistors T3, T4 of vertical branch. Figure 2 demonstrates the control method and supply voltage and load current waveforms; u – supply voltage, io – load current, signu – detection signal of supply voltage sign (polarity), signio – detection signal of load current sign (polarity), T1, T2, T3, T4 – transistor control signals, Δt – transistor switching delay interval. The delay time Δt has been set as equal to switching period. When load current sign assumes positive value and supply voltage is positive, then transistor T3 is switched off, and when delay time Δt is over, then transistor T2 is also switched off and pulse signal is input to transistor T1. When transistor T1 conducts, the current flows in the loop T1 – D2 – load Zo; when transistor T1 is switched off, then supply voltage sign is reversed and this results in forward bias of transistor T4; load current is taken over by transistor T4 and diode D3. When transistor T1 is switched on again, the positive voltage appears at load terminals; this leads to reverse polarization of T4 transistor and T4 current is turned off. When voltage sign becomes negative, while load current is positive, transistor T1 is switched on by a continuous signal, and when delay time Δt is over, then transistor T3 is switched on by a continuous signal and pulse signal is input to transistor T4.

When transistor T4 conducts, the current flows in the loop T4 – D3 – load Zo. The load voltage is negative; this is the sum of voltage drops across conducting transistor T4 and diode D3. In this mode negative voltage is present at transistor T1 and this prevents current flow through this transistor.

When transistor T4 is switched off, the load voltage starts to increase until supply voltage value is reached. When load voltage begins to exceed supply voltage, T1 transistor goes into a forward bias, and this results in load current taken over by transistor T1 and diode D2. When transistor T4 is switched on again, transistor T1 is polarized in reverse direction and current flowing through transistor T1 is turned off. Similar situations take place in remaining operating conditions. The proposed control method does not require synchronisation of the pulse signal with frequency of supply voltage fundamental harmonic.

Fig.2. Waveforms illustrating control method

Testing of control method The control method has been tested using simulation tool Matlab-Simulink. Model used in the tests has been described in [4, 8]. This model makes it possible to set any (arbitrary) transistor switch-on time and this facilitates testing the method for controllers using different types of transistors. In order to check the resistance of control method to expected (in actual circuits) inaccuracies of detecting changes of supply voltage and load current signs, a series of simulation tests has been run. Results of analysis were presented in [6]; on the basis of this analysis we may distinguish four characteristic cases:

– detection circuit indicates change of sign of supply voltage too soon (i.e. at first information about sign change is obtained, and only then actual change takes place). This is an inadmissible case, since it results in a through short-circuit of transistors in both vertical and horizontal branches of the circuit during those time intervals, when detection of supply voltage sign is inaccurate and incorrect,

– detection circuit indicates change of sign of supply voltage too late (i.e. at first the actual change of supply voltage sign takes place, and only then information about sign change appears). The delay of voltage sign detection in relation to actual change in supply voltage results in deformation of load current during those time intervals, when detection of supply voltage sign is inaccurate and incorrect. This, however, does not pose any danger of damage to converter’s transistor switches,

– detection circuit indicates change of sign of load current too soon (i.e. at first information about sign change is obtained, and only then actual change in current flow takes place). This is an inadmissible case, since it results in generation of overvoltage across load inductance and, at the same time, a through short-circuit of transistors in both vertical and horizontal branches of the circuit occurs during those time intervals, when load current is turned off,

– detection circuit indicates change of sign of load current too late (i.e. at first actual change of load current sign takes place, and only then information about sign change appears). The delay of current sign detection in relation to actual change in load current results in deformation of load current during those time intervals, when detection of load current sign is inaccurate and incorrect. This, however, does not pose any danger of damage to converter ‘s transistor switches.

Experimental verification

The proposed control method has been applied in three-phase AC voltage controller with zero lead. This controller consists of three identical circuits shown in Figure 1. The tests have been run for different load parameters, transistor pulse frequencies and pulse-duty factors of control signals. The load currents (1,2,3) for different phases as well as load voltage (4) corresponding to load current (1) are shown in Figure 3. The tests have been conducted for transistor pulse frequency equal to 2 kHz, pulse-duty factor of control impulses equal to 25%, and time delay of transistor switching in relation to supply voltage and load current signs detection signals equal to 1 ms.

Fig.3. Measurement of output waveforms: phase currents (1, 2, 3 – 50 A/div) and load voltage (4 – 200 V/div) for RL-type load (4 ms/div)

During another research the converter was loaded with non-thermal plasmatron through steep up matching transformer (1:8 ratio). Scheme of system is shown in Figure 4, where: UZ – transistor converter AC-AC, Td – matching transformer in star-delta connection, P – plasmatron.

Fig.4. Simplified scheme of plasmatron power supply

In Figure 5 output phase currents and phase-to-phase voltage waveforms were presented.

Fig.5. Measurement of AC converter output waveforms: phase currents (1, 2, 3 – 50 A/div) and phase-to-phase voltage (4 – 200 V/div) supplying the plasmatron (200 ms/div)

In Figures 6-7 currents and phase-to-phase arc voltage were presented.

Fig.6. Measurement of arc waveforms: phase currents (1, 2, 3 – 10 A/div) and phase-to-phase voltage (4 – 1 kV/div) for full work cycles (200 ms/div)

Fig.7. Measurement of arc waveforms: phase currents (1, 2, 3 – 5 A/div) and phase-to-phase voltage (4 – 1 kV/div) for part of work cycle (4 ms/div)

Figure 6 presents the typical plasmatron operation cycle: ignition, work and extinction of the arc.

Waveforms presented in Figure 7 show the typical voltage and current waveforms during the discharge of the arc.

Fig.8. Examples of plasmatron work cycle

The sequence of the plasmatron work cycle were presented in Figure 8. Pictures were made under the conditions show in Figures 6-7.

Plasmatron is based on quartz tube with 3 steel work and two ignition electrodes inside. Plasmatron is adjusted to work in vertically position and is equipped with gas flow speed adjuster.

Presented plasmatron along with power supply is dedicated to electrochemical process application, mainly for disposal of low concentration toxic gases from the air.

Application of current arc regulator in plasmatron power supply circuit allows to control energy in arc circuit and parameters of electrochemical process.

Conclusions

The proposed pulse control method of AC voltage controllers makes it possible to get rid of dead time between different transistors switching’s as well as to eliminate commutation overvoltages due to the effect of self-induction in RL-type loads. This is achieved by introducing time delays for transistor control signals, when change of sign of supply voltage or load current is detected. In accordance with adapted control method and non-zero dynamics of the switches, the pulse-duty factor may vary from time delay value Δt to time corresponding to 100% pulse-duty factor minus time Δt. Since current supplied by the source is pulsing, commutation overvoltages may be due to the inductance of the supply line itself. In this case, surge protection circuits at the supply side are indispensable. The proposed method does not depend on type of load.

Proposed control method was verified by experiments for converter with RL-type load and next non-thermal plasma plasmatron.

Performed research indicated that type of load don’t disturb proposed transistors control method.

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Authors: dr inż. Andrzej Kandyba, The Polish Engineers and Technicians Association SIMP Group Silesia, 25 Górnych Wałów St., 44-100 Gliwice, Poland, e-mail: akandyba@grupasilesiasimp.pl
dr inż. Marian Hyla, Silesian University of Technology, Faculty of Electrical Engineering, Department of Power Electronics, Electrical Drives and Robotics, 2 Krzywoustego St., 44-100 Gliwice, Poland, e-mail: marian.hyla@polsl.pl
prof. dr hab. inż. Igor Kurytnik, State School of Higher Education in Oświęcim, 8 Kolbego St., 32-600 Oświęcim, Poland, e-mail: ikurytnik@outlook.com

Source & Publisher Item Identifier: PRZEGLĄD ELEKTROTECHNICZNY, ISSN 0033-2097, R. 92 NR 7/2016. doi:10.15199/48.2016.07.21