Abstract

Buildings consume around 70% of all domestic electricity (US EIA, How much energy is consumed in U.S. residential and commercial buildings? – FAQ – U.S. Energy Information Administration (EIA), F.A.Q.s, 2018), which is mostly generated by fossil fuel combustion in electric utility power plants. This causes buildings to have major contributions to the total greenhouse gas (GHG) emissions (REN21, Renewbles in cities – 2019 global status report, 2019). Building photovoltaics (PV) systems can provide a clean electricity source to reduce the buildings’ environmental impact. This fact and decreasing prices, market availability, and supportive policies are contributing factors for the increased interest in implementing PV systems. However, with the complexity of the built environment and the existence of different factors and several measures, the impact of PV systems may have contradicting effects on the performance of the built environment. For instance, while integrating PV systems can reduce the buildings’ GHG emissions and the energy cost for end-users, they can also affect the buildings’ energy balance and performance, the buildings’ interaction with the grid, in terms of grid stability, and the architectural aesthetic of the buildings. Thus, the impact of the PV systems integration on buildings needs to be carefully evaluated and optimized, in the design process, to account for all factors. Optimizing the PV systems’ design improves the performance of the built environment and ensures the reduction of its environmental impact. To this end, the aim of this chapter is to review the current practices for the design and implementation of PV systems in buildings and discuss their impact on the built environment’s performance. Also, the use of performance simulation, generative design, and optimization processes are reviewed to assess their potential in improving the design process of PV systems.KeywordsDistributed solar photovoltaicsUrban scaleBuilding performance simulation and optimizationEnergy supply and demand

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