New technique for sizing optimization of a stand-alone photovoltaic system

This paper presents a method for sizing optimization in Stand-Alone Photovoltaic (SAPV) system. Evolutionary Programming (EP) was integrated in the sizing process to maximize the technical performance of the system. It is used to determine the optimal PV module, charge controller, inverter and battery such that the expected Performance Ratio (PR) of the SAPV system could be maximized. Two EP models, i.e. the Classical Evolutionary Programming (CEP) and Fast Evolutionary Programming (FEP) were tested in determining the best EP model for the EP-based sizing algorithm. In addition, an iterativebased sizing algorithm was developed to determine the optimal solution for benchmarking purposes. The results showed that CEP had outperformed the FEP by producing higher PR despite having almost similar computation time. However, the sizing algorithm using both EP models was also found to be much faster when compared to the iterative-based sizing algorithm, thus justifying the needs for incorporating EP in the sizing algorithm.

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