Lfc Enhancement in Dg System Penetrated With Pv-wind and Integrated Battery Charging Station Using Enhanced Gorilla Troop-marine Predator Optimisation

Adaptation of Electric vehicles (EV) increases, it tends to generate a surplus amount of electrical power to satisfy the load demand and power generation during peak load periods. The penetration of Renewable Energy Sources(RES) plays a vital role in increasing the overall power demand for supplying energy to Electric Vehicle Charging stations (EVCS). With different charging patterns of EVs and penetration of intermittent sources like solar and PV, overall power demand and generation lead to instability. Load Frequency Control(LFC) with an optimized PID controller must reach stability under different frequency-deregulated environment conditions. LFC controller with various optimization techniques was analysed in this research. The stabilization of the grid with RES with EV integration becomes more challenging. In this research, the proposed model is analyzed with different unique optimization techniques like hybrid Enhanced Gorilla Troop Optimisation-Marine Predator Algorithm(EGTO-MPA),Pufferfish Optimisation(PFO), Botox(BTO) optimization, Artificial gorilla troop optimization algorithm combining sine cosine Cauchy variations(AGTO-SCCV), and Secretary Bird Optimisation Algorithm(SBOA) for tuning LFC to attain stability. However, EGTO-MPA provides better stability than other algorithms and the EVCS integrated grid which is penetrated with PV-wind attains stability in frequency regulated environment during load disturbances and different source pattern variations. This proposed research work deals with the analysis of enhancement of LFC performance with the hybrid EGTO-MPA optimization algorithm for 146- Indian Utility Bus system which are analysed as four control areas and examined with penetration of renewable energy sources and EVCS integration with the hydrothermal system. Settling time and Integral Time Absolute Error(ITAE) with the EGTO-MPA optimization method provide very excellent performance for system load variations and different charging patterns of EV and intermittent source variations.