LAUSR

Abstract This paper presents Firefly Algorithm-based Sizing Algorithm (FASA) for sizing optimization of a Stand-Alone Photovoltaic (SAPV) system. Firefly Algorithm (FA) was used to optimally select the model of each system component such that a technical performance indicator is consequently optimized. Prior to implementation of FASA, an Iterative-based Sizing Algorithms known as ISA had been developed to determine the optimal solutions which were used as benchmark for FASA. Although ISA was capable in determining the optimal design solutions when there are numerous models for each system component being considered, the computation time of ISA can be very long as ISA tested every possible combination of PV module, battery, charge controller and inverter during sizing process. Therefore, FASA was introduced to accelerate the sizing optimization for SAPV system. FA was incorporated into sizing algorithm with the technical performance indicator was set to optimize the Loss of Power Supply Probability (LPSP). Besides that, two design cases of PV-battery system, i.e. system with standard charge controller denoted as Case 1 and system with MPPT-based charge controller denoted as Case 2 were investigated. The results showed that FASA had successfully found the optimal LPSP in all design cases. In addition, sizing algorithm with FA was also discovered to outperform sizing algorithm with selected computational intelligence in producing the lowest computation time in the sizing optimization.