Configuring Optimal Hybrid RE System with the Aid of Efficient Social Spider Optimization (ESSO)

Abstract

The significant purpose of this research is to configure a hybrid renewable power generation unit to compensate for power demand in economic cost. This system configuration incorporates solar photovoltaic cells, wind energy generation, and battery units as backup power supply.  To configure optimal sizing, RE (RE)power generation manually, take a long time to compute. This prohibition urges the incorporation of optimization techniques to predict/set optimal RE generating units and battery backup units.  Investigation utilizes various optimization techniques along with Efficient Social Spider Optimization (ESSO) to configure optimal generating and backup units. Association of Cauchy distribution called evolutionary strategy with swarm intelligence (SSO) unveils superior results over contest techniques. ESSO reveals optimal sizing as 32 solar photovoltaic power-generating units, two-wind power-generating units, and 14 battery backup units cost $7003.075. This configuration obtains from ESSO has quite evident results over contest techniques in the context of compensating power demand in economic cost.

Keywords: Solar photovoltaic cells, Wind energy, Hybrid RE, Battery and Efficient Social Spider Optimization (ESSO).