Optimization of Solar Hybrid Power Generation Using Conductance-Fuzzy Dual-Mode Control Method

Abstract

The functioning of a solar hybrid power system is investigated in this research using a unique fuzzy control method. Turbines, solar photovoltaics, diesel engines, fuel cells, aqua-electrolyzes, and other autonomous generation products are used in the hybrid renewable energy system. Further energy storage components of the system include the batteries, turbine, and ultracapacitor. This research incorporates a supercapacitor hybrid energy storage system (HESS) into a solar hybrid power generating system, allowing the consumption and energy storage space and power output to be significantly increased. This study’s approach incorporates a decentralized power generation system with a HESS while increasing electrical output in phases utilizing a dynamic reactive power compensation scheme and a conductance-fuzzy dual-mode control strategy. Due to a nonlinear behavior of photovoltaic (PV) devices’ power output, maximum power point tracking (MPPT) methods must be used to create the greatest power. Infrequently developing atmospheric circumstances, traditional MPPT algorithms do not work adequately. Modeling is used to determine the microgrid’s power output to the photovoltaic hybrid power generating organization, as well as the optimization method for each device in the network. The dynamic power factor correction scheme and also the conductance-fuzzy dual-mode control approach are primarily used in this study to optimize the solar hybrid renewable energy system.