Stability enhancement of power system based on HHO-TSA control scheme

References

• Abd‐Elazim, S. M., & Ali, E. S. (2015). A hybrid particle swarm optimization and bacterial foraging for power system stability enhancement. Complexity, 21(2), 245–255. https://doi.org/10.1002/cplx.21601
   Web of Science ®Google Scholar
• AbdElazim, 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
   Web of Science ®Google Scholar
• Abdulkhader, H. K., Jacob, J., & Mathew, A. T. (2019). Robust type-2 fuzzy fractional order PID controller for dynamic stability enhancement of power system having RES based microgrid penetration. International Journal of Electrical Power & Energy Systems, 110, 357–371. https://doi.org/10.1016/j.ijepes.2019.03.027
   Web of Science ®Google Scholar
• 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
   Web of Science ®Google Scholar
• 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
   Web of Science ®Google Scholar
• Anderson, P. M. (1977). Power System Control and Stability: Vol. I. Science Press.
   Google Scholar
• Dasu, B., Kumar, M. S., & Rao, R. S. (2019). Design of robust modified power system stabilizer for dynamic stability improvement using Particle Swarm Optimization technique. Ain Shams Engineering Journal, 10(4), 769–783. https://doi.org/10.1016/j.asej.2019.07.002
   Web of Science ®Google Scholar
• Devarapalli, R., Bhattacharyya, B., Sinha, N., & Dey, B. (2021). Amended GWO approach based multi-machine power system stability enhancement. ISA Transactions, 109, 152–174. https://doi.org/10.1016/j.isatra.2020.09.016
   PubMed Web of Science ®Google Scholar
• 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
   Web of Science ®Google Scholar
• Hussain, K., Zhu, W., & Salleh, M. N. M. (2019). Long-term memory Harris’ hawk optimization for high dimensional and optimal power flow problems. IEEE Access, 7, 147596–147616. https://doi.org/10.1109/ACCESS.2019.2946664
   Web of Science ®Google Scholar
• Hwang, G. H., Kim, D. W., Lee, J. H., & An, Y. J. (2008). Design of fuzzy power system stabilizer using adaptive evolutionary algorithm. Engineering Applications of Artificial Intelligence, 21(1), 86–96. https://doi.org/10.1016/j.engappai.2006.11.008
   Web of Science ®Google Scholar
• Jokarzadeh, M., Abedini, M., & Seifi, A. (2019). Improving power system damping using a combination of optimal control theory and differential evolution algorithm. ISA Transactions, 90, 169–177. https://doi.org/10.1016/j.isatra.2018.12.039
   PubMed Web of Science ®Google Scholar
• Kundur, P., Balu, N. J., & Lauby, M. G. (1994). Power system stability and control (Vol. 7). McGraw-hill.
   Google Scholar
• Malik, S., & Nehra, V. (2017). An efficient block matching algorithm for fast motion estimation using new three step search and Tabu search algorithm. International Journal of Scientific Research and Management, 5(7), 6257–6264. https://doi.org/10.18535/ijsrm/v5i7.58
   Google Scholar
• Mir, A. S., Bhasin, S., & Senroy, N. (2019). Decentralized nonlinear adaptive optimal control scheme for enhancement of power system stability. IEEE Transactions on Power Systems, 35(2), 1400–1410. https://doi.org/10.1109/TPWRS.2019.2939394
   Web of Science ®Google Scholar
• 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
   Web of Science ®Google Scholar
• Mythili, S., Thiyagarajah, K., Rajesh, P, Shajin, F. H., K, T., & Shajin, F. H. (2020). Ideal position and size selection of unified power flow controllers (UPFCs) to upgrade the dynamic stability of systems: An antlion optimiser and invasive weed optimisation algorithm. HKIE Transactions, 27(1), 25–37. https://doi.org/10.33430/V27N1THIE-2018-0024
   Google Scholar
• Naresh, G., Raju, M. R., & Narasimham, S. V. L. (2016). Coordinated design of power system stabilizers and TCSC employing improved harmony search algorithm. Swarm and Evolutionary Computation, 27, 169–179. https://doi.org/10.1016/j.swevo.2015.11.003
   Web of Science ®Google Scholar
• Rajesh, P., & Shajin, F. (2020). A multi-objective hybrid algorithm for planning electrical distribution system. European Journal of Electrical Engineering, 22(4–5), 224–509. https://doi.org/10.18280/ejee.224–509
   Google Scholar
• 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
   Web of Science ®Google Scholar
• Sambariya, D., & Prasad, R. (2014). Robust tuning of power system stabilizer for small signal stability enhancement using metaheuristic bat algorithm. International Journal of Electrical Power & Energy Systems, 61, 229–238. https://doi.org/10.1016/j.ijepes.2014.03.050
   Web of Science ®Google Scholar
• 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
   Web of Science ®Google Scholar
• Shajin, F., & Rajesh, P. (2020). Trusted secure geographic routing protocol: Outsider attack detection in mobile ad hoc networks by adopting trusted secure geographic routing protocol. International Journal of Pervasive Computing and Communications. Advance online publication. https://doi.org/10.1108/IJPCC-09-2020-0136
   Web of Science ®Google Scholar
• Singh, M., Patel, R. N., & Neema, D. D. (2019). Robust tuning of excitation controller for stability enhancement using multi-objective metaheuristic Firefly algorithm. Swarm and Evolutionary Computation, 44, 136–147. https://doi.org/10.1016/j.swevo.2018.01.010
   Web of Science ®Google Scholar
• Soliman, H., Bayoumi, E., & Hassan, M. (2008). Power system stabilizer design for minimal overshoot and control constraint using swarm optimization. Electric Power Components and Systems, 37(1), 111–126. https://doi.org/10.1080/15325000802322053
   Web of Science ®Google Scholar
• 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
   Web of Science ®Google Scholar
• Zhou, Y., Guo, Q., Sun, H., Yu, Z., Wu, J., & Hao, L. (2019). A novel data-driven approach for transient stability prediction of power systems considering the operational variability. International Journal of Electrical Power & Energy Systems, 107, 379–394. https://doi.org/10.1016/j.ijepes.2018.11.031
   Web of Science ®Google Scholar