Abstract

We examine simple yet accurate analytic procedures for designing optimal stand-alone photovoltaic power generation systems. Solar electricity systems can represent a cost-effective alternative to high cost, conventional, diesel-fired generators, particularly in developing countries where most of the population lives in rural and isolated areas. However, the lack of simple but accurate analytic design tools currently results in either (a) significant, wasteful oversizing or (b) extremely high design costs for one-of-a-kind projects. The analytic solutions discussed here can bring the price of stand-alone photovoltaic systems to economic viabilty at today's hardware and fuel prices, and can also enable local designers in developing countries to design these systems economically and on their own. The analytic models are based on the theory of stochastic processes, and stem from analyses originally developed for analogous water reservoir, queueing and insurance risk problems.

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