Controlling Techniques for STATCOM using Artificial Intelligence
Keywords:
STATCOM, AI, Control Strategies, Grid connected systems, DSTATCOMAbstract
The static synchronous compensator (STATCOM) is a power electronic converter designed to be shunt-connected with the grid to compensate for reactive power. Although they were originally proposed to increase the stability margin and transmission capability of electrical power systems, there are many papers where these compensators are connected to distribution networks for voltage control and power factor compensation. In these applications, they are commonly called distribution static synchronous compensator (DSTATCOM). In this paper we have focussed on STATCOM and the controlling techniques which are based on artificial intelligence.
References
Shahgholian, G., Fazeli-Nejad, S., Moazzami, M., Mahdavian, M., Azadeh, M., Janghorbani, M., & Farazpey, S. (2016). Power system oscillations damping by optimal coordinated design between PSS and STATCOM using PSO and ABC algorithms. 2016 13th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON 2016, 0–5. https://doi.org/10.1109/ECTICon.2016.7561458
Choubey, A., & Singh, G. (2016). A Survey on STATCOM Techniques. 4(4), 452–463.
Nusair, K. N., & Alomoush, M. I. (2017). Optimal reactive power dispatch using teaching learning based optimization algorithm with consideration of FACTS device “STATCOM.” 2017 10th Jordan International Electrical and Electronics Engineering Conference, JIEEEC 2017. https://doi.org/10.1109/JIEEEC.2017.8051398
Atyia, H., & Mete, A. (2018). Shuffled Frog Leap Algorithm , and Genetic Algorithm Based. 2018.
Bakir, H., & Kulaksiz, A. A. (2020). Modelling and voltage control of the solar-wind hybrid micro-grid with optimized STATCOM using GA and BFA. Engineering Science and Technology, an International Journal, 23(3), 576–584. https://doi.org/10.1016/j.jestch.2019.07.009
Saxena, N. K., & Kumar, A. (2016). Reactive power control in decentralized hybrid power system with STATCOM using GA, ANN and ANFIS methods. International Journal of Electrical Power and Energy Systems, 83, 175–187. https://doi.org/10.1016/j.ijepes.2016.04.009
Yu, L., Zhang, J., & Jiang, C. (2012). D-STATCOM control based on self-tuning PI with neural networks. China International Conference on Electricity Distribution, CICED, 5–6. https://doi.org/10.1109/CICED.2012.6508649
Shinde, S. U., Sharmila, M., Patil, R. S., & Malkhede, D. V. (2016). Performance comparison of PI & ANN based STATCOM for 132 KV transmission line. International Conference on Electrical, Electronics, and Optimization Techniques, ICEEOT 2016, Fig 1, 2730–2734. https://doi.org/10.1109/ICEEOT.2016.7755191
Ma, Y., Huang, A., & Zhou, X. (2015). A review of STATCOM on the electric power system. 2015 IEEE International Conference on Mechatronics and Automation, ICMA 2015, 162–167. https://doi.org/10.1109/ICMA.2015.7237475
Kow, K. W., Wong, Y. W., Rajkumar, R. K., & Rajkumar, R. K. (2016). A review on performance of artificial intelligence and conventional method in mitigating PV grid-tied related power quality events. Renewable and Sustainable Energy Reviews, 56, 334–346. https://doi.org/10.1016/j.rser.2015.11.064
Chau, T. K., Yu, S. S., Fernando, T., Iu, H. H. C., & Small, M. (2018). A Load-Forecasting-Based Adaptive Parameter Optimization Strategy of STATCOM Using ANNs for Enhancement of LFOD in Power Systems. IEEE Transactions on Industrial Informatics, 14(6), 2463–2472. https://doi.org/10.1109/TII.2017.2767069
Khan, M. T., & Siddiqui, A. S. (2016). FACTS device control strategy using PMU. Perspectives in Science, 8, 730–732. https://doi.org/10.1016/j.pisc.2016.06.072
Farahani, S. S. S., Hemati, R., & Nikzad, M. (2009). Comparison of Artificial Intelligence Strategies for STATCOM Supplementary Controller Design. World Applied Sciences Journal, 7(11), 1428–1438.
Mopidevi, R., Srinivas, L. R., babu, B. M., & Tulasiram, S. S. (2014). AI Based STATCOM for Power Quality Enhancement. International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, 03(08), 11315–11324. https://doi.org/10.15662/ijareeie.2014.0308054
Yenealem, M. G., Ngoo, L. M. H., Shiferaw, D., & Hinga, P. (2020). Management of voltage profile and power loss minimization in a grid-connected microgrid system using fuzzy-based STATCOM controller. Journal of Electrical and Computer Engineering, 2020. https://doi.org/10.1155/2020/2040139
Jin, Y., Xiao, Q., Jia, H., Mu, Y., Ji, Y., Teodorescu, R., & Dragicevic, T. (2021). A Dual-Layer Back-Stepping Control Method for Lyapunov Stability in Modular Multilevel Converter based STATCOM. IEEE Transactions on Industrial Electronics, 0046(c). https://doi.org/10.1109/TIE.2021.3063973
Alskran, F., & Simoes, M. G. (2021). Multilevel current source converter-based STATCOM suitable for medium-voltage applications. IEEE Transactions on Power Delivery, 36(2), 1222–1232. https://doi.org/10.1109/TPWRD.2020.3004419
Dilshad, S., Abas, N., Farooq, H., Kalair, A. R., & Memon, A. A. (2020). Neurofuzzy wavelet based auxiliary damping controls for STATCOM. IEEE Access, 8, 200367–200382. https://doi.org/10.1109/ACCESS.2020.3031934
Khurana, B. V., & Titare, L. S. (2020). Improvement of power flow and voltage stability using UPFC with artificial neural network in Matlab. Proceedings - 2020 IEEE International Symposium on Sustainable Energy, Signal Processing and Cyber Security, ISSSC 2020, 5–8. https://doi.org/10.1109/iSSSC50941.2020.9358842
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2022 Vidhyavati Suryawanshi, Dr. Surbhi Gupta
This work is licensed under a Creative Commons Attribution 4.0 International License.
