Optimizing methodologies of hybrid renewable energy systems powered reverse osmosis plants

Based on a systematic and bibliometric review, the combined use of Portfolio Theory (PT) and Particle Swarm Optimization (PSO) is proposed for the energy management of a Hybrid Renewable Energy System (HRES) powered reverse osmosis (RO) plant. PT-PSO combined use aims a Multi-Objective Optimization (MOO), decreasing the Drinking Water Cost (DWC) and increasing the system reliability and components lifetime. HRES optimization is crucial to meet the RO demand, considering that the sources intermittence can lead to a reduction of the lifetime of RO membranes and other components. Initially, a systematic and bibliometric review is conduced to identify the strengths and weakness of the existing HRES optimization methodologies. The review reveals that HOMER is the most used software for hybrid plants sizing and optimization; however, HOMER shows some constraints, such as a limited range of the components nominal power and a high computational cost associated with the inclusion of hydrogen production and storage. In contrast, optimization methods based on PSO show a lower computational cost, delivering robust results. Additionally, PSO can be used with other methodologies, such as the PT; traditionally applied in the economy sector to improve investment portfolios, PT recently has been used in the energy sector for wind and solar forecasting; PT use for HRES energy management is innovative.