Optimum sizing of stand-alone microgrids: Wind turbine, solar photovoltaic, and energy storage system

Abstract

The growing energy demand and rising fossil fuel expenses in isolated and remote regions have increased interest in renewable energy sources (RESs). However, RESs such as photovoltaics (PVs) and wind turbines (WTs) are intermittent and fluctuating; hence reliability is a major concern. The hybridization of RESs with energy storage systems can effectively address their fluctuations and intermittency and enhance overall efficiency; however, the corresponding system cost is a primary concern. Thus, determining the optimal sizing of a hybrid system is the major challenge. Previous studies have suggested metaheuristic algorithms that rely on specific parameters to find an optimal solution. To address this issue, a hybrid algorithm, namely JGWO, which combines JAYA and grey wolf optimizer (GWO), has been proposed. The aim is to solve the unit sizing problem of a hybrid system (PV-WT-battery) that can meet consumers’ demands at the lowest total annual cost (TAC) while considering the maximum allowable probability of power supply loss (LPSPmax) to ensure system reliability. The JGWO is compared to JAYA, GWO, genetic optimization algorithm (GOA), and teaching-learning based optimization (TLBO) in reliability and TAC. Findings reveal that JGWO outperforms existing algorithms at LPSPmax values of 0%, 1%, 3%, 2%, and 5%, yielding TAC of 66542, 61102, 50247, 43046, and 34464 USD, respectively, for a hybrid system (PV-WT-battery). The results also show that the proposed hybrid PV-WT-battery system is more cost-efficient than PV-battery and WT-battery systems, regardless of the LPSPmax value.