Optimal Sizing and Energy Management of Hybrid Renewable Energy Systems With Pumped Hydro Storage for Remote Off‐Grid Microgrids

Abstract

This article presents the optimal design, energy management, and feasibility analysis of a photovoltaic (PV), wind energy (WE), and pumped hydro storage plant (PSP)‐based off‐grid microgrid at low air density, located in hilly terrain. The optimized size of PV, WE, capacity of upper reservoir (UPR), and inverter is determined by minimizing the cost of energy (COE) subject to the loss of power supply probability (LPSP) constraint. The popular metaheuristic optimization algorithms, namely particle swarm optimization (PSO), differential evolution (DE), grey wolf optimization (GWO), sine‐cosine algorithm (SCA), whale optimization algorithm (WOA), and Moth‐flame optimization (MFO) algorithm, are used to minimize the COE. With the help of different statistical analyses, such as normality tests using the Shapiro–Wilk test and nonparametric tests such as Friedman–ANOVA and Mann–Whitney tests, it indicates that PSO provides the most reliable, optimal, accurate, and lowest COE, whereas DE takes the least simulation time. The COE obtained at 0% maximum allowed limits of LPSP (LPSP mxi ) and 5% LPSP mxi is 0.2128 and 0.2041 $/kWh, respectively, indicating electricity is available at an economical price, keeping 100% and 95% supply reliability, respectively. The optimized sizes obtained at 0% LPSP mxi are PV 875 units, WE 100 units, inverter 60 units, and V UPR 7657 m 3 . Similarly, the optimized sizes at 5% LPSP mxi are PV 745 units, WE 100 units, inverter 60 units, and V UPR 7169 m 3 . The model is analyzed sensitively, which reflects that the size of microgrid systems varies with changes in P L , and the COE also changes significantly. Thus, the optimally designed PV‐WE‐PSP‐based off‐grid microgrid ensures feasibility in low air density areas, achieves high supply reliability through an efficient energy management strategy, and delivers a 100% renewable energy supply.