Multi-objective optimization framework of photovoltaic glazing based on indoor daylight, power generation and energy consumption under urban context

Photovoltaic (PV) glazing in building facades is essential to building energy efficiency and high-density environmental design. This study, with Hong Kong as a case study, proposed a multi-objective optimization (MOO) framework for optimizing the window to wall ratio (WWR), PV glazing's location, area and transparency based on indoor daylight performance, net electricity consumption and in various urban contexts. The impact of peripheral building on the MOO results was first studied in this study by examining three building density scenarios (high, medium, low), each considering both cases with and without the influence of peripheral buildings. Honeybee integrated with Radiance, EnergyPlus and Openstudio engine was employed for simulating daylight, energy consumption and electricity generation while Wallacei was applied to find Pareto solutions. Considering surrounding buildings, net energy consumption (NEC) increases by 20.58 % in the high-density scenario, while the increase is smaller at 11.86 % in the medium-density scenario and 0.81 % in the low-density scenario. Similarly, sDA decreases by −86.34 % in the high-density scenario, with smaller reductions of −61.22 % in the medium-density scenario and −2.17 % in the low-density scenario. PV glazing with low transparency of 0.1 was preferred in the solutions with minimum NEC in all scenarios except for Assessed scenario 1, with maximum sDA ranges from 0.105 to 0.673, while high transparency of 0.7 was used to enhance daylight performance. WWR ranged from 0.8 to 0.9 under energy and daylight objectives, but lower (0.1–0.4) when optimizing glare.