Genetic algorithm based optimization for photovoltaics integrated building envelope

A growing attention has been paid to building integrated photovoltaics (BIPV) when designing net-zero-energy buildings. Envelope features of large commercial buildings can be properly designed to both enhance PV integration and reduce building energy use. Many studies have been focused on predicting PV performance of designed systems or optimizing building envelope properties to reduce energy consumption. This study introduces an optimization framework using genetic algorithm (GA) via the GenOpt program to determine the best options for building envelope designs to reduce net building energy cost and increase PV utilization capacity/efficiency. A set of envelope design features were tested in this study, such as, building dimensions, window-to-wall-ratio (WWR), orientation, and PV integration placement, upon which the associated PV and building energy cost are evaluated and compared. Cubic commercial buildings commonly found in Egypt were used to demonstrate the application of the proposed optimization process. The developed tool can help designers to determine the optimal envelopes with appropriate BIPV options from both energy and economic perspectives.