Optimal design of a grid-connected desalination plant powered by renewable energy resources using a hybrid PSO-GWO approach

This paper presents a grid-connected hybrid renewable energy integrated with a reverse osmosis desalination plant to provide fresh water for a residential community. The hybrid energy system comprises a photovoltaic module and wind turbine as the main source of energy, and battery storage systems or hydrogen storage systems are used as an energy storage system, while a diesel generator is used as a backup energy source. A new multi-objective hybrid Particle Swarm Optimization - Grey Wolf Optimizer (PSO-GWO) optimization method is used to obtain the optimal size of the different system components to minimize both the total cost of fresh water production and, at the same time, CO2 emissions, for a period of 20 years. Moreover, a comparison is done between the PSO-GWO optimization method and the use of PSO alone and the use of GWO alone. The solar radiation, temperature and wind speed of the residential community are measured using the weather station system. A comparison between different hybrid system configurations using three different optimization methods is presented. The complete model for energy management strategies and the optimization models for this study are programmed using MATLAB software. The results show that the proposed PSO-GWO hybrid performs better at determining the optimization parameters than either of the same optimization methods used in isolation. The optimization results indicate that a battery storage system is more economical than a hydrogen storage system. Further reduction in cost can be achieved by incorporating a diesel generator into the hybrid system. Finally, sensitivity analyses are performed to show how varying certain parameters affects total investment cost. Such analyses have shown that the variation in annual solar irradiance has a greater impact on the total investment cost than wind speed variation.