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The paper presents a feasibility computing approach to solve the optimal planning problem applied to Stand-alone Photovoltaic (SPV) system by considering the reliability requirement and economical performance. Evaluation technique based on genetic algorithm to get global optimum capacity of solar array and battery in a SPV system is more efficiently. Explicit strategy selects proper values of systems' parameters improving local exploration and avoiding trapped in local optimum. Different requirements of system reliability are investigated to achieve the optimal planning of a SPV system. Sensitivity analysis of components' cost and load profiles are conducted to demonstrate the impacts of system uncertainty. The solar radiation and temperature data from the Central Weather Bureau of Taiwan at four different locations were used.

Economic and Feasibility Analysis for Stand–alone Solar Photovoltaic Generation System