A novel method for sizing of standalone photovoltaic system using multi-objective differential evolution algorithm and hybrid multi-criteria decision making methods - Muhsen, Dhiaa Halboot; Nabil, Moamen; Haider, Haider Tarish; Khatib, Tamer (Energy (Oxford), 2019)
Standalone photovoltaic system is promising sustainable energy source. Accurate modeling and sizing of these systems strongly affect the system's feasibility. Thus, in this paper, optimal sizing of standalone photovoltaic system is conducted based on multi-objective differential evolution algorithm integrated with hybrid multi-criteria decision making methods. Multi-objective differential evolution algorithm is used to optimize set of configurations of a system by minimizing technical and cost objective functions simultaneously. After that, an analytical hierarchy process integrated with a technique for order preference by similarity to ideal solution are used to order preference of configurations based on the loss of load probability and life cycle cost of system. The results of the proposed sizing method are validated by a numerical method to explain the superiority of the proposed method. According to results, the proposed sizing method is faster than numerical method by around 27 times. This is because the multi-objective differential evolution algorithm requires roughly 0.23 of simulations that is required by numerical method. Furthermore, the performance of multi-objective differential evolution algorithm is evaluated by various metrics. As a result, for the adapted load demand, the optimal configuration is 63 PV modules and 66 battery unit with maximum capacity of 500 Ah. •We optimally size standalone PV system using hybrid metaheuristic algorithm.•Multi-objective DE with hybrid multi-criteria decision making algorithms are applied.•We use analytical hierarchy process to classify system's configurations based on LLP.•The proposed sizing method is faster than numerical method by around 27 times.