In this paper, the interconnection of renewable energy sources is proposed for power quality improvement of renewable energy sources (RESs) with an energy storage system. The proposed system is the combined execution of Improved Bat Search Algorithm (IB SA) through Moth Flame Optimization Algorithm (MFOA) named as IBSMFO. The searching behaviour of the bats is modified with efficient neighborhood search functions like crossover & mutation. In the proposed method, the MFOA has handled the searching behavior of the IBSA in perspective of the minimum error objective function. The objective of the proposed IBSMFO approach was to enhance the power quality as for the real and reactive power variations. To accomplish the objective, MFOA is optimized for minimize power variations as well as the operational cost of the RESs in light of weekly and daily forecast of data for grid electricity charge, electrical load and environmental parameter. The proposed IBSMFO procedure deals with the performance of the energy storage apparatus as far as the enhancement of power in the entire system. By at that point, the proposed system is executed in MATLAB/SIMULINK working model and the execution is surveyed with the current procedure.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.