Genetic algorithm based optimization for photovoltaics integrated building envelope

Abstract

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.

Active surfaces selection method for building-integrated photovoltaics (BIPV) in renovation projects based on self-consumption and self-sufficiency

“…genetic algorithm) to maximise some parameters (i.e. annual production or profitability of the installation) [30][31][32][33]. In terms of optimisation values, these methods present a highaccuracy level, but they are not adapted to BIPV application on existing façades (where orientation and context are fixed) because the results can lead to an unrealistic repartition of the active surfaces from an operational point of view [24,25].…”

“…Some interesting studies focus on the optimisation of the building shape through shape grammars [32] and using genetic algorithms to maximise the BIPV production in new buildings [33,34]. The application of this kind of approach is however not relevant in the renovation of buildings.…”

Techno‐economic feasibility of building attached photovoltaic systems for the various climatic conditions of Iran

“…The payback period of three BIPV systems including amorphous silicon, single‐crystalline silicon, and multi‐crystalline silicon were assessed and it was found that the energy payback period of these systems are far below the LCC, suggesting that the systems are theoretically feasible . A genetic algorithm was adopted to minimize building costs and maximize BIPV efficiency considering PV configuration, building orientation and dimension, and window to wall ratio (WWR) as variables . The optimums were found to have the minimum WWR and the optimal orientation of PV systems was found to be at 90–255° azimuth angles.…”

“…21 A genetic algorithm was adopted to minimize building costs and maximize BIPV efficiency considering PV configuration, building orientation and dimension, and window to wall ratio (WWR) as variables. 22 The optimums were found to have the minimum WWR and the optimal orientation of PV systems was found to be at 90-255 azimuth angles.…”

Effect of the collector geometry in the concentrating photovoltaic thermal solar cell performance

“…This self-consistent calculation is usually associated with high computing times. Even with fast numerical simulation models (for instance, tens of seconds per structure), the use of 100 elements and 100 generations can lead to optimization processes that can last up to several days or weeks [10]. In a simplified 2-D model, sufficiently precise solutions can be guaranteed with a drastically reduced running time.…”