Optimizing operation of a photovoltaic/diesel generator hybrid energy system with pumped hydro storage by a modified crow search algorithm

In a hybrid energy system composed of photovoltaic (PV), diesel generator and pumped hydro storage (PHS), to attain minimum fuel consumption, system operation should be optimized. This paper focuses on optimizing operation of a PV/diesel/PHS hybrid energy system by a modified crow search algorithm (CSA). For this aim, fuel consumption during the considered period is defined as the objective function. At deficit conditions (when PV generation is less than load demand), percent of deficit power which should be supplied by PHS is considered as decision variable. To effectively solve this difficult optimization problem, CSA with an adaptive chaotic awareness probability (CSA(AC-AP)) has been proposed. Simulated results reveal that the proposed CSA(AC-AP) produces more accurate and robust results than genetic algorithm (GA), particle swarm optimization (PSO) and original CSA. Moreover, optimal sharing of deficit power between diesel generator and PHS leads to having minimum operation cost.