M.S. Rahman Tito, Tek T. Lie, and Timothy Anderson
Wind–PV hybrid renewable energy system (HRES), genetic algorithm (GA), PV module, random load
This paper presents results for the optimization of two wind–photovoltaic (PV) hybrid renewable energy systems (HRES). In the first, optimization of a wind–PV hybrid system was carried out with a fixed daily load profile and a combination of non-identical commercially available PV modules. The results showed that using a combination of different module ratings could match the given load and provide lower cost of the system. In the second case, a genetic algorithm (GA) method was used to determine the optimal size of a wind–PV hybrid system experiencing a randomly varied load. It was shown that individual runs of the GA optimization procedure for randomly varied loads result in different optimization values. The worst case optimization result may be selected for randomly varied load for desired reliability where the loss of power supply probability was considered as the reliability index for both simulations.
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