Multi-objective optimization design of high-rise high-density urban morphology and their multidimensional assessment of PV capacity

Urban morphological optimization is crucial for addressing urban energy challenges. However, previous studies have mainly focused on small to medium-sized cities, leaving a knowledge gap in large, high-rise, high-density urban contexts. This study presents a novel multi-objective optimization framework specifically tailored for high-rise, high-density urban blocks, simultaneously optimizing building energy consumption, solar radiation incidence, and total building surface area using the NSGA-II algorithm. A total of 834 feasible solutions and 114 Pareto-optimal solutions are generated. Importantly, this research uniquely evaluates the photovoltaic (PV) potential of the optimized urban forms across three distinct dimensions: physical, geographical, and technical potential. Results reveal that while Pareto-optimal solutions do not necessarily excel in surface area maximization alone, they consistently demonstrate superior PV potential after considering realistic geographic constraints and PV conversion efficiency, outperforming feasible solutions by 8.6–9.35 % (rooftops) and 22.63–23.17 % (facades). The scientific contributions of this research lie in developing an integrated multi-objective optimization framework specifically for high-density urban morphology and providing a detailed multi-dimensional analysis of PV potential, which serves as a valuable theoretical basis and practical guide for low-carbon urban planning.