A modified dragonfly algorithm and recurrent neural network based mppt in hybrid solar and wind power system

Abstract

iii newlineABSTRACT newlineNowadays, the power generation from the renewable resources newlinesuch as solar and wind sources is increased since their operation yields less newlinepollution and also due to the minimal operational costs.. But the fluctuating newlinenature of the wind and solar resources makes the generation sector to generate newlineinefficient output. The hybridization of the resources such as solar and wind newlinepower system can improve the efficiency of the output to some extent. In newlineorder to attain maximum available power from the solar and wind energy newlinesystem, Maximum Power Point Tracking (MPPT) Controllers are usually newlineused. The different Power Electronic Converter (PEC) components are used newlineto design the hybrid Renewable Energy Source (RES) system. The DC-DC newlinepower converters are widely utilized to control the output from the solar and newlinewind power system and hence the system does not require a high frequency newlinetransformer. The controllers are incorporated with various algorithms which newlinein turn control the duty cycle of the dc to dc converter thereby controlling the newlineoverall output power from the system. The soft computing techniques have newlinenowadays been widely used to track the maximum power point of the system newlineand the overall system efficiency gets improved. newline