Abstract

AbstractIn this manuscript, a novel control scheme is proposed to achieve the power quality (PQ) enhancement of renewable energy sources (RES), such as photovoltaic (PV), wind turbine (WT), fuel cell (FC), and battery. The proposed hybrid technique is the consolidation of both the Improved Bat Algorithm (IBat) and Moth Flame Optimization Algorithm (MFOA), therefore it is known as Improved Bat search Algorithm with Moth Flame Optimization Algorithm (IBatMFOA) control strategy. The crossover and mutation function is utilized to modify the bats search behavior function. Here, MFOA is utilized to enhance the searching behavior of IBat technique by reducing the error function. The main goal of proposed IBatMFOA approach is “to enhance the PQ depending on active with reactive power varience.” To attain the target, MFOA is optimized to lessen the power variation. Moreover, the functioning cost of RESs is diminished based on daily with weekly data forecast, like grid electricity price, electrical load, environmental parameters. By using IBatMFOA technique, the entire system efficiency is enhanced. By then, the proposed method is activated in MATLAB site, then the performance is examined with existing methods, like artificial bee colony, Gravitational Search Algorithm, and Firefly algorithm. The active power controller parameters of proposed technique are 8.8554 and 1.8569. The reactive power controller parameters of proposed technique are 8.1657 and 1.5698.

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