Supervisory Control of Solar-Wind-Biomass-Fuel Cell Energy System for Optimal Performance

Abstract

Generating electricity through a hybrid renewable energy system (HRES) plays a crucial role in achieving the sustainable development goal of affordable and clean energy (SDG 7). However, designing an optimal HRES is challenging due to the fluctuating demand and intermittent nature of renewable energy sources (RES). In recent times, hybrid hydrogen-battery energy storage technologies have garnered significant attention as they offer a pathway to a sustainable HRES with zero net emissions. This research paper introduces a rule-based algorithm and a metaheuristic optimization technique called Levy Flight Algorithm (LFA) for the energy management strategy (EMS) of an independent HRES. The EMS aims to establish a sequence for power delivery among the different components within the microgrid. The LFA is employed to optimize this EMS. To account for the variability and unpredictability of renewable energy sources, the proposed EMS is evaluated across four scenarios: winter, spring, summer, and autumn. These scenarios are derived from a stochastic model of RES. The results of the evaluation demonstrate that the energy management strategy implemented to control the HRES has successfully established an environmentally friendly energy system.