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Research Article

A hybrid approach for enhancing the dynamic stability in power system

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Received 13 Sep 2022, Accepted 16 Jul 2023, Published online: 01 Sep 2023

References

  • Abd-Elazim, S. M., & Ali, E. S. (2013). A hybrid particle swarm optimization and bacterial foraging for optimal power system stabilizers design. International Journal of Electrical Power & Energy Systems, 46, 334–341. https://doi.org/10.1016/j.ijepes.2012.10.047
  • Abd Elazim, S. M., & Ali, E. S. (2016). Optimal power system stabilizers design via cuckoo search algorithm. International Journal of Electrical Power & Energy Systems, 75, 99–107. https://doi.org/10.1016/j.ijepes.2015.08.018
  • Abido, M. A. (1999). A novel approach to conventional power system stabilizer design using tabu search. International Journal of Electrical Power & Energy Systems, 21(6), 443–454. https://doi.org/10.1016/S0142-0615(99)00004-6
  • Abido, M. A., & Abdel-Magid, Y. L. (2002). Eigenvalue assignments in multimachine power systems using tabu search algorithm. Computers & Electrical Engineering, 28(6), 527–545. https://doi.org/10.1016/S0045-7906(01)00005-2
  • Alkhatib, H., & Duveau, J. (2013). Dynamic genetic algorithms for robust design of multimachine power system stabilizers. International Journal of Electrical Power & Energy Systems, 45(1), 242–251. https://doi.org/10.1016/j.ijepes.2012.08.080
  • Butti, D., Mangipudi, S. K., & Rayapudi, S. (2021). Model order reduction based power system stabilizer design using improved whale optimization algorithm. IETE Journal of Research, 69(4), 1–20. https://doi.org/10.1080/03772063.2021.1886875
  • Dasu, B., Sivakumar, M., & Srinivasarao, R. (2019). Interconnected multi-machine power system stabilizer design using whale optimization algorithm. Protection and Control of Modern Power Systems, 4(1), 1–11. https://doi.org/10.1186/s41601-019-0116-6
  • Do Bomfim, A. L., Taranto, G. N., & Falcao, D. M. (2000). Simultaneous tuning of power system damping controllers using genetic algorithms. IEEE Transactions on Power Systems, 15(1), 163–169. https://doi.org/10.1109/59.852116
  • Farah, A., Guesmi, T., Abdallah, H. H., & Ouali, A. (2016). A novel chaotic teaching–learning-based optimization algorithm for multi-machine power system stabilizers design problem. International Journal of Electrical Power & Energy Systems, 77, 197–209. https://doi.org/10.1016/j.ijepes.2015.11.050
  • Feng, Z. K., Liu, S., Niu, W. J., Liu, Y., Luo, B., Miao, S. M., & Wang, S. (2019). Optimal operation of hydropower system by improved grey wolf optimizer based on elite mutation and quasi-oppositional learning. IEEE Access, 7, 155513–155529. https://doi.org/10.1109/ACCESS.2019.2949582
  • Islam, N. N., Hannan, M. A., Shareef, H., & Mohamed, A. (2017). An application of backtracking search algorithm in designing power system stabilizers for large multi-machine system. Neurocomputing, 237, 175–184. https://doi.org/10.1016/j.neucom.2016.10.022
  • Jain, M., Maurya, S., Rani, A., Singh, V., Thampi, S. M., El-Alfy, E. S. M., Mitra, S., & Trajkovic, L. (2018). Owl search algorithm: A novel nature-inspired heuristic paradigm for global optimization. Journal of Intelligent & Fuzzy Systems, 34(3), 1573–1582. https://doi.org/10.3233/JIFS-169452
  • Jin, Z., Sun, X., Lei, G., Guo, Y., & Zhu, J. (2021). Sliding mode direct torque control of SPMSMs based on a hybrid wolf optimization algorithm. IEEE Transactions on Industrial Electronics, 69(5), 4534–4544. https://doi.org/10.1109/TIE.2021.3080220
  • Kommula, B. N., Kota, V. R., & Tummuru, N. R. (2021, September). Maximum power point tracking for photovoltaic brushless DC motor connected water pumping system based on GBDT-BOA technique. In 2021 IEEE International Power and Renewable Energy Conference (IPRECON) (pp. 1–6). IEEE.
  • Kuttomparambil Abdulkhader, H., Jacob, J., & Mathew, A. T. (2018). Fractional‐order lead‐lag compensator‐based multi‐band power system stabiliser design using a hybrid dynamic GA‐PSO algorithm. IET Generation, Transmission & Distribution, 12(13), 3248–3260. https://doi.org/10.1049/iet-gtd.2017.1087
  • Mekki, N., & Krichen, L. (2021). Coordinated designs of fuzzy PSSs and load frequency control for damping power system oscillations considering wind power penetration. Wide Area Power Systems Stability, Protection, and Security, 1(1),167–188. https://doi.org/10.1007/978-3-030-54275-7_6
  • Mohammadi, M., & Ghadimi, N. (2015). Optimal location and optimized parameters for robust power system stabilizer using honeybee mating optimization. Complexity, 21(1), 242–258. https://doi.org/10.1002/cplx.21560
  • Othman, A. M. (2021). Synergy of adaptive super-twisting method (ASTM) and game-theory algorithm (GTA) for dynamic stability improvement of interconnected grids. Electric Power Systems Research, 192, 106919. https://doi.org/10.1016/j.epsr.2020.106919
  • Penchalaiah, G., & Ramya, R. (2022). Stability enhancement of power system based on HHO-TSA control scheme. International Journal of Electronics, 109(12), 2108–2134. https://doi.org/10.1080/00207217.2021.2001871
  • Penchalaiah, G., & Ramya, R. (2023). An EnGRFA control scheme based power system stabilizers (PSS) for the stability analysis with wind energy integration. Artificial Intelligence Review, 56(8), 1–32. https://doi.org/10.1007/s10462-022-10368-1
  • Qiu, W., Vittal, V., & Khammash, M. (2004). Decentralized power system stabilizer design using linear parameter varying approach. IEEE Transactions on Power Systems, 19(4), 1951–1960. https://doi.org/10.1109/TPWRS.2004.836269
  • Razmjooy, N., Razmjooy, S., Vahedi, Z., Estrela, V. V., & de Oliveira, G. G. (2021). A new design for robust control of power system stabilizer based on moth search algorithm. Metaheuristics and Optimization in Computer and Electrical Engineering, 1(1), 187–202. https://doi.org/10.1007/978-3-030-56689-0_10
  • Sambariya, D. K., Gupta, R., & Prasad, R. (2016). Design of optimal input–output scaling factors based fuzzy PSS using bat algorithm. Engineering Science & Technology, an International Journal, 19(2), 991–1002. https://doi.org/10.1016/j.jestch.2016.01.006
  • Sambariya, D. K., & Prasad, R. (2015). Optimal tuning of fuzzy logic power system stabilizer using harmony search algorithm. International Journal of Fuzzy Systems, 17(3), 457–470. https://doi.org/10.1007/s40815-015-0041-4
  • Sebaa, K., & Boudour, M. (2009). Optimal locations and tuning of robust power system stabilizer using genetic algorithms. Electric Power Systems Research, 79(2), 406–416. https://doi.org/10.1016/j.epsr.2008.08.005
  • Sebaa, K., Zhou, Y., Li, Y., Gelen, A., & Nouri, H. (2021). Low-frequency oscillation damping control for large-scale power system with simplified virtual synchronous machine. Journal of Modern Power Systems and Clean Energy, 9(6), 1424–1435. https://doi.org/10.35833/MPCE.2020.000340
  • Shakarami, M. R., & Davoudkhani, I. F. (2016). Wide-area power system stabilizer design based on grey wolf optimization algorithm considering the time delay. Electric Power Systems Research, 133, 149–159. https://doi.org/10.1016/j.epsr.2015.12.019
  • Sharma, K. K., Gupta, A., Kaur, G., Kumar, R., Chohan, J. S., Sharma, S. & Issakhov, A. (2021). Power quality and transient analysis for a utility-tied interfaced distributed hybrid wind-hydro controls renewable energy generation system using generic and multiband power system stabilizers. Energy Reports, 7, 5034–5044. https://doi.org/10.1016/j.egyr.2021.08.031
  • Sun, X., Jin, Z., Cai, Y., Yang, Z., & Chen, L. (2020). Grey wolf optimization algorithm based state feedback control for a bearingless permanent magnet synchronous machine. IEEE Transactions on Power Electronics, 35(12), 13631–13640. https://doi.org/10.1109/TPEL.2020.2994254
  • Sun, T. Y., Tsai, S. J., Chen, H. C., & Yang, S. M. (2006, September). Fuzzy-based error correction mechanism to improve the precision of intelligent maneuvering target tracking. In 2006 IEEE International Conference on Information Reuse & Integration (pp. 28–33). IEEE.
  • Sun, X., Zhang, Y., Tian, X., Cao, J., & Zhu, J. (2021). Speed sensorless control for IPMSMs using a modified MRAS with gray wolf optimization algorithm. IEEE Transactions on Transportation Electrification, 8(1), 1326–1337. https://doi.org/10.1109/TTE.2021.3093580
  • Wang, S. K. (2016). Coordinated parameter design of power system stabilizers and static synchronous compensator using gradual hybrid differential evaluation. International Journal of Electrical Power & Energy Systems, 81, 165–174. https://doi.org/10.1016/j.ijepes.2016.02.016
  • Wang, D., Ma, N., Wei, M., & Liu, Y. (2018). Parameters tuning of power system stabilizer PSS4B using hybrid particle swarm optimization algorithm. International Transactions on Electrical Energy Systems, 28(9), e2598. https://doi.org/10.1002/etep.2598
  • Wu, H., Tsakalis, K. S., & Heydt, G. T. (2004). Evaluation of time delay effects to wide-area power system stabilizer design. IEEE Transactions on Power Systems, 19(4), 1935–1941. https://doi.org/10.1109/TPWRS.2004.836272
  • Zhou, X., Usman, M., He, P., Mastoi, M. S., & Liu, S. (2021). Parameter design of governor power system stabilizer to suppress ultra-low-frequency oscillations based on phase compensation. Electrical Engineering, 103(1), 685–696. https://doi.org/10.1007/s00202-020-01101-8

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