A Pareto optimum approach and a power management strategy for a stand-alone wind turbine-PV-hydrogen with reformer hybrid renewable energy system
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In this study, a multi-objective and constrained optimization problem is discussed. The SAHRESOpt (multi-objective and constrained optimization algorithm for SA-HRES) which includes size optimization and minimization of the loss of power supply probability was developed based on non-dominated sorting genetic algorithm-II (NSGA-II). Additionally, a power management strategy was designed to ensure that the power flow between the system elements minimizes the unmet load and/or the excess energy. In this context, with the aim of obtaining uninterrupted hydrogen energy in the system, a reformer was used transforming methane gas produced by an anaerobic reactor into hydrogen. Thus, a stand-alone hybrid renewable energy system (SA-HRES) that does not generate CO2 emissions was designed. Furthermore, within the scope of size optimization, both the types of system elements and the numbers of them were optimized. Then, the positive effects of reformer existence on both of the objective functions, and also the effects of considering the waste energy percentage as a constraint are presented. Also, Pareto solutions of SAHRESOpt and NSGA-II are compared. Finally, a case study including photovoltaic panels, wind turbines, fuel cells, electrolyzers, hydrogen tanks, and a reformer is presented to prove the effectiveness of the presented algorithm and validate the results.