Considering district shading in solar potential optimization of residential nearly zero energy buildings (NZEBs): A case study of Jinan city

Existing studies on performance optimization of residential buildings are mostly conducted in ideal environments. However, in actual conditions, surrounding buildings will have an impact on their performance. Taking Jinan, a cold region of China, as a representative case, this study proposed a framework for optimizing the performance of residential buildings that considered district shading effects. Design parameter ranges were determined through a practical survey. Machine learning models were employed instead of physical models. Interpretable analysis was used to reveal the effects of design parameters on performance, and the best optimization strategies were determined by optimization algorithms and multi-criteria decision making. Results showed that surrounding shading decreased photovoltaic solar irradiation by 35.9 % and improved useful daylight illuminance by 20.9 % compared with ideal environments. Although the energy consumption has only increased by 2.7 %, the heating energy consumption has increased by 10.7 % and the cooling energy consumption has decreased by 4.6 %. The framework enhanced photovoltaic solar irradiation by 135.7 % and 26.8 %, reduced energy consumption by 5.8 % and 2.7 %, and improved useful daylight illuminance by 13.6 % and 15.0 % for new-build and retrofit schemes. This study offers a practical, interpretable framework for optimizing building performance under district shading in new-build and retrofit scenarios.