Synthesis of Solar Photovoltaic Systems: Optimal Sizing Comparison

Abstract

In the current scenario, energy demand rises by 1.3% each year to 2040, and photovoltaic (PV) systems have emerged as an alternative to the fossil or nuclear fuel energy generation. The use of formal methods for PV systems is a new subject with significant research spanning only five years. Here we develop and evaluate an automated synthesis technique to obtain optimal sizing of PV systems based on Life Cycle Cost (LCC) analysis. The optimal solution is the lowest cost from a list of equipment that meets the electrical demands from a house, plus the replacement, operation, and maintenance costs over 20 years. We propose a variant of the counterexample guided inductive synthesis (CEGIS) approach with two phases linking the technical and cost analysis to obtain the PV sizing optimization. We advocate that our technique has various advantages if compared to off-the-shelf optimization tools available in the market for PV systems. Experimental results from seven case studies demonstrate that we can produce an optimal solution within an acceptable run-time; different software verifiers are evaluated to check performance and soundness. We also compare our approach with a commercial tool specialized in PV systems optimization. Both results are validated with commercial design software; furthermore, some real PV systems comparison are used to show our approach effectiveness.