Best battery storage technologies of solar photovoltaic systems for desalination plant using the results of multi optimization algorithms and sustainable development goals

Abstract

In this paper, the optimization and multiple-criteria decision analysis (MCDA) of a stand-alone photovoltaic and battery energy system (PV-BES) has been used to supply power to a desalination plant in the United Arab Emirates (UAE). To provide a continuous power supply, different types of battery technologies have been used as a renewable energy storage system in this study as Nickel Iron (NiFe), Lithium Iron Phosphate (LiFePO4), and Lead Acid (PbSO4) with three different depths of discharges. Six different configurations of the PV-BES were modeled. In total, nine metaheuristic optimization algorithms were used in the MATLAB environment to provide an optimal sizing of the PV-BES. The mayfly optimization algorithm has provided the best optimal Annual Levelized Cost (ALC) values compared with the remaining algorithms. The mayfly algorithm has more robustness and faster convergence in providing the optimal global best values. Furthermore, three different approaches of MCDA and weights methods were used. The inputs and the results for the optimization process in addition to the sustainable development goal (SDGs) from the united nation (UN) were used as criteria for MCDA. The PV-Li-ION at 50 % depth of discharge (DOD) was the best option among all cases based on the six configurations and nine optimization algorithms.