Optimal Design of Isolated Hybrid Renewable Energy Systems for Sustainable Water Desalination

This study explores the renewable energy sources (RESs) integration for sustainable water desalination in remote zones. It presents an isolated hybrid renewable energy system (IHRES) optimized through a novel metaheuristic called quadratic interpolation optimization (QIO). The system includes wind turbines (WTs), solar photovoltaic (PV), batteries, and a diesel generator (DG). This design aims to deliver unremitting power for both electrical load and a reverse osmosis desalination plant (RODP), ensuring system resilience against RESs intermittency while enhancing sustainability and freshwater production. The QIO algorithm addresses multi-objective optimization challenges, focusing on minimizing the cost of energy (COE), enhancing the loss of power supply possibility (LPSP), and reducing excess energy within established constraints. The proposed system is optimized for a coastal residential community in Yanbu, Saudi Arabia. To safeguard the stability, accuracy, and robustness of the proposed QIO technique, rigorous statistical validation is performed, demonstrating its effectiveness in solving the optimization problem. Moreover, the study includes a detailed comparative analysis with other established algorithms, such as whale optimizer algorithm (WOA) and grey wolf optimizer (GWO). This comparative study assesses the impact of reliability indices on the optimal IHRES sizing, highlighting that the QIO algorithm excels in identifying the most efficient system to be the most cost-effective and eco-friendly choice.