Superior performances strategies of different hybrid renewable energy systems configurations with energy storage units

The essential function of a hybrid renewable energy system is to produce an adequate electrical supply to the load demand with low cost. This paper proposes the optimization and operation of the renewable energy power sources for electrification of isolated rural city in Algeria desert. For this purpose, a system composed by PV panel (PV), Wind Turbine (NT), Battery Bank (BB) for storage of the electrical energy and Fuel Cell (FC) with hydrogen tank (H-2 Tank) and electrolyzer (Elect) system for storage of the chemical energy is used to fulfill the need of the load. In the present paper we are interested in evolutionary algorithms for solving optimization problem of hybrid configuration of power system. However, a new heuristic algorithm namely whale optimization algorithm (WOA) is used to obtained the best solution of multi-objective optimization system of cost of energy (COE), total net present cost (T-NPC) and loss power supply probability (LPSP). Two recent algorithms, particle swarm optimization (PSO) and grey wolf optimizer (GWO) are also implemented in this work. Seven cases studies have been tested for examining the efficient of proposed optimization technique. The suggested whale optimization algorithm, as demonstrated by simulations and comparisons with existing methods, solves the problem of multi-objective optimization of hybrid power system configurations with high accuracy and validity.

Automated summary

This paper discusses the optimization and operation of hybrid renewable energy systems for electrification of isolated rural cities in the Algerian desert. The study proposes the use of evolutionary algorithms, including the whale optimization algorithm, to solve the multi-objective optimization problem of the power system configurations. Simulations and comparisons with existing methods demonstrate the high accuracy and validity of the proposed whale optimization algorithm.