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Главный редактор
НИКИФОРОВ
Владимир Олегович
д.т.н., профессор
Партнеры
doi: 10.17586/2226-1494-2023-23-3-635-645
УДК 004.94
Сравнительный анализ производительности DVR и DSTATCOM для распределенной генерации с алгоритмом гравитационного поиска
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Язык статьи - английский
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Аннотация
Ссылка для цитирования:
Бхавья К., Рама Рао П.В.В., Рави Шринивас Л. Сравнительный анализ произво дительности DVR и DSTATCOM для распределенной генерации с алгоритмом гравитационного поиска // Научно технический вестник информационных технологий, механики и оптики. 2023. Т. 23, № 3. С. 635–645 (на англ. яз.). doi: 10.17586/222614942023233635645
Аннотация
Развитие области силовых электронных преобразователей вызвало увеличение количества защитных устройств для распределительной системы. Это привело к созданию ассортимента гибких устройств передачи, направленных на повышение стабильности системы при проблемах с качеством электроэнергии, и на обеспечение гибкой бесперебойной передачи энергии во время турбулентности. Рассмотрены возможности использования двух пользовательских силовых устройств: динамического восстановителя напряжения (Dynamic Voltage Restorer, DVR) и распределительного статического компенсатора (Distribution Static Compensator, DSTATCOM). Применение силовых устройств предназначено для решения проблем качества электроэнергии, связанных с системами распределенной генерации. Проведен анализ производительности предложенных пользовательских устройств напряжения питания с применением алгоритмов: гравитационного поиска, летучих мышей (BAT) и муравьиного алгоритма (ANT) для повышения стабильности системы питания. Предложенная система протестирована с различными распределенными системами и условиями отказа. Выполнена оценка выбранных алгоритмов с точки зрения напряжения питания, тока питания, активной мощности, реактивной мощности и коэффициента мощности. Проектирование и анализ всей системы осуществлены с использованием пакета MATLAB/Simulink.
Ключевые слова: динамический восстановитель напряжения, распределительный статический компенсатор, алгоритм гравитационного поиска
Список литературы
Список литературы
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2. Afzal M.J., Arshad A., Ahmed S., Tariq S.B., Kazmi S.A.A. A review of DGs and FACTS in power distribution network: methodologies and objectives // Proc. of the 2018 International Conference on Computing, Mathematics and Engineering Technologies (ICOMET). 2018. P. 1–7. https://doi.org/10.1109/Icomet.2018.8346405
3. Remya V.K., Parthiban P., Ansal V., Chitti Babu B. Dynamic Voltage Restorer (DVR) – A review // Journal of Green Engineering. 2018. V. 8. N 4. P. 519–572.
4. Khatoon N., Shaik S. A survey on different types of flexible ac transmission systems (FACTS) controllers // International Journal of Engineering Development and Research. 2017. V. 5. N 4. P. 796–814.
5. Bharti H., Arya J.S., Arya A.K. Power loss minimization with multiple DGs in distribution system using gravitational search algorithm // International Journal of Engineering Development and Research. 2018. V. 6. N 3. P. 101–106.
6. Kumar L., Kumar S., Kumar Gupta S., Raw B.K. Optimal location of FACTS devices for loadability enhancement using gravitational search algorithm // Proc. of the IEEE 5th International Conference for Convergence in Technology (I2CT). 2019. P. 1–5. https://doi.org/10.1109/I2CT45611.2019.9033561
7. Zhang J., Liu K., Liu Y., He S., Tian W. Active power decoupling and controlling for single-phase FACTS device // The Journal of Engineering. 2019. N 16. P. 1333–1337. https://doi.org/10.1049/joe.2018.8823
8. Therattil J.P., Jose J., Prasannakumari R.P.N., Abo‐khalil A.G., Alghamdi A.S., Rajalekshmi B.G., Sayed K. Hybrid control of a multi-area multi-machine power system with FACTS devices using non-linear modelling // IET Generation, Transmission & Distribution. 2020. V. 14. N 10. P. 1993–2003. https://doi.org/10.1049/iet-gtd.2019.1165
9. Geleta D.K., Manshahia M.S. Gravitational search algorithm‐based optimization of hybrid wind and solar renewable energy system // Computational Intelligence. 2022. V. 38. N 3. P. 1106–1132. https://doi.org/10.1111/coin.12336
10. Rayudu K., Yesuratnam G., Jayalaxmi A. Bat algorithm and ant colony optimization based optimal reactive power dispatch to improve voltage stability // European Journal of Engineering Research and Science. 2017. V. 2. N 6. P. 27–35. https://doi.org/10.24018/ejers.2017.2.6.378
11. Nagaraju G., Shankar S. Gravitational search algorithm for power quality improvement of WECS with UPQC // International Journal of Intelligent Engineering and Systems. 2019. V. 12. N 1. P. 133–141. https://doi.org/10.22266/ijies2019.0228.14
12. Chawda G.S., Shaik A.G., Mahela O.P., Padmanaban S., Holm-Nielsen J.B. Comprehensive review of distributed FACTS control algorithms for power quality enhancement in utility grid with renewable energy penetration // IEEE Access. 2020. V. 8. P. 107614–107634. https://doi.org/10.1109/ACCESS.2020.3000931
13. Peres W. Robust design of modern multi-band PSS using gravitational search algorithm // Proc. of the 2018 Simposio Brasileiro de Sistemas Eletricos (SBSE). 2018. P. 1–6. https://doi.org/10.1109/SBSE.2018.8395558
14. Zhu L., He S., Wang L., Zeng W., Yang J. Feature selection using an improved gravitational search algorithm // IEEE Access. 2019. V. 7. P. 114440–114448. https://doi.org/10.1109/ACCESS.2019.2935833
15. Pervez I., Sarwar A., Tayyab M., Sarfraz M. Gravitational search algorithm (GSA) based maximum power point tracking in a solar PV based generation system // Proc. of the 2019 Innovations in Power and Advanced Computing Technologies (i-PACT). 2019. P. 1–6. https://doi.org/10.1109/i-PACT44901.2019.8960130
16. Dorigo M., Stützle T. Ant Colony Optimization. Cambridge, MA: MIT Press, 2004. 305 p.
17. Dorigo M. Optimization, learning and natural algorithms: PhD thesis. Dipartimento di Elettronica, Politecnico di Milano, Italy, 1992. (in Italian)
18. Dorigo M., Maniezzo V., Colorni A. Ant system: Optimization by a colony of cooperating agents // IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics). 1996. V. 26. N 1. P. 29–41. https://doi.org/10.1109/3477.484436
19. Bullnheimer B., Hartl R., Strauss C. A new rank based version of the Ant System: A computational study // Central European Journal for Operations Research and Economics. 1999. V. 7. N 1. P. 25–38.
20. Yang X.-S., He X. Bat algorithm: literature review and application // International Journal of Bio-Inspired Computation. 2013. V. 5. N 3. P. 141–149. https://doi.org/10.1504/ijbic.2013.055093
