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There exist various methods and tools to size solar photovoltaic systems;however, these tools rely on simulations, which do not cover all aspects of thedesign space during the search for optimal solution. In prior studies inoptimal sizing, the focus was always on criteria or objectives. Here, wepresent a new sound and automated approach to obtain optimal sizing using anunprecedented program synthesis. Our variant of counterexample guided inductivesynthesis (CEGIS) approach has two phases linking the technical and costanalysis: first we synthesize a feasible candidate based on power reliability,but that may not achieve the lowest cost; second, the candidate is thenverified iteratively with a lower bound cost via symbolic model checking. Ifthe verification step does not fail, the lower bound is adjusted; and if itfails, a counterexample provides the optimal solution. Experimental resultsusing seven case studies and commercial equipment data show that our synthesismethod can produce within an acceptable run-time the optimal system sizing. Wealso present a comparative with a specialized simulation tool over realphotovoltaic systems to show the effectiveness of our approach, which canprovide a more detailed and accurate solution than that simulation tool.

Optimal Sizing of Stand-alone Solar PV Systems via Automated Formal Synthesis