Optimal sizing of hybrid solar/wind/hydroelectric pumped storage energy system in Egypt based on different meta-heuristic techniques

Providing access to clean, reliable, and affordable energy by adopting hybrid power systems is important for countries looking to achieve their sustainable development goals. This paper presents an optimization method for sizing a hybrid system including photovoltaic (PV), wind turbines with a hydroelectric pumped storage system. In this paper, the implementation of different optimization techniques has been investigated to achieve optimal sizing of grid-connected hybrid renewable energy systems. A comprehensive study has been carried out between Whale Optimization Algorithm (WOA), Water Cycle Algorithm (WCA), Salp Swarm Algorithm (SSA), and Grey Wolf optimizer (GWO) to validate each one. Moreover, the optimal sizing of the system's components has been studied using real-time information and meteorological data of Ataka region located in Egypt. The purpose of the optimization process is to minimize the cost of energy from this hybrid system while satisfying the operation constraints including high reliability of the hybrid power supply, small fluctuation in the energy injected to the grid, and high utilization of the photovoltaic and wind complementary properties. MATLAB software package has been used to evaluate each optimization algorithm for solving the considered optimization problem. Simulation results proved that WOA has the most promising performance over other techniques.