Abstract
This paper presents a comparison study for various types of battery technologies using selected BESS parameters in a hybrid PV and wind power plant (HPP), taking the aging of the batteries into account. The optimization problem was reformulated as a Mixed Integer Linear Programming (MILP) problem, with the aim being to minimize the overall operating cost. IBM CPLEX was used to solve the problem. For forecasting, two techniques, i.e., the persistence and Elman Neural Network, were applied for both day-ahead and hour-ahead forecasting. Moreover, four case studies were performed, including the scenario without battery, day-ahead dispatch, day-ahead dispatch with a rolling horizon and hour-ahead dispatch. The simulation results showed that hour-ahead dispatch demonstrated the highest profitability. Furthermore, among different battery technologies, lithium-ion batteries resulted in the highest operating profits, whereas lead-acid batteries had the shortest payback period and vanadium redox flow batteries demonstrated the least degradation from cycling.
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