An Enhancement of Grid Integration in Renewable Energy Systems Using Multi- Objective Multi-Verse Optimization

Going by the recent trends, the application of Renewable Energy Sources (RESs) has grown significantly across the world. Still, the integration of grid with photovoltaic (PV), wind and battery, remains a critical challenge as it results into power quality issues. To address the increasing need for electricity caused by industrialization and growing population, hybrid PV, wind, and battery combinations are used in this study. To accomplish an optimal energy management, this research proposes the multi- objective multi-verse optimization (MOMVO) approach, along with the modified perturb and observe (MP&O) technique. The proposed MOMVO-MP&O controller operates between the wind turbine and the battery storage system, for providing optimal power distribution and stability. The suggested model is evaluated alongside three other popular controller combinations that are, multi-verse optimization-perturb and observe (MVO-P&O), MVO-MP&O, and MOMVO-P&O. A comparative analysis is conducted, with existing methods namely, Modified-Fuzzy Direct Power Control (MF-DPC) and Adaptive Neuro-Fuzzy Inference System (ANFIS) also. From the analyzed results of this comparison, the proposed MOMVO-MP&O achieves lesser Total Harmonic Distortion (THD) of 1.86%, which demonstrates its efficiency in addressing power quality issues using hybrid RES systems.