• Devika Rani Motukuri

The present investigation introduces a new method for evaluating power quality that combines particle swarm optimization technique with Grey Wolf Optimization (GWO). Because it has such a direct effect on the efficiency and dependability of the grid and the functioning of different electrical equipment. Power quality assessment is an essential part of maintaining reliable and efficient electrical power systems. A lot of the older approaches to evaluating power quality use heuristic algorithms, which can have poor convergence rates and produce less-than-ideal results. To improve the efficacy and precision of power quality evaluation, this research suggests a hybrid strategy that merges GWO's advantages with particle swarm optimization (PSO). In order to improve convergence speed and solution quality, the hybridization process seeks to utilize both the exploration-exploitation balance of GWO and the diversification capabilities of particle swarm optimization. Extensive simulations and comparison with existing approaches using common power quality assessment standards show that the suggested strategy is effective. The hybrid GWO-based technique shows promise for practical use in power systems engineering and management, as it beats standard methods in convergence time, solution quality, and resilience. To lessen the impact of harmonics and voltage imbalance, the PID controller's parameters are fine-tuned using the PSO-GWO method. The results show that active filters are not cost-effective for high ratings and are complicated and cumbersome, while passive filters are large and easy to use. Therefore, MATLAB/Simulink model is used to build a hybrid structure that combines a shunt active filter for meeting the desired objective.

Power Quality,Optimization technique ,Hybridization,Covergence time,Resilience.

" HARNESSING THE POTENTIAL OF HYBRID GREY WOLF OPTIMIZATION FOR POWER QUALITY ASSESSMENT", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 2, page no.c665-c670, February-2024, Available :http://www.jetir.org/papers/JETIR2402279.pdf

" HARNESSING THE POTENTIAL OF HYBRID GREY WOLF OPTIMIZATION FOR POWER QUALITY ASSESSMENT", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 2, page no. ppc665-c670, February-2024, Available at : http://www.jetir.org/papers/JETIR2402279.pdf