Optimizing Urban Morphology: A Multi-Objective Approach to Energy Efficiency, Heat Management, and Photovoltaic Integration

With the acceleration of urbanization, sustainable urban development faces significant challenges, including energy consumption, urban heat island effects, and the utilization of renewable energy. This paper proposes a multi-objective optimization framework for urban morphology design, aiming to reduce building energy consumption, mitigate urban heat island effects, and enhance photovoltaic generation efficiency by optimizing parameters such as building layout, density, height, and orientation. The framework employs the Rhino and Grasshopper platforms, using the NSGA-II genetic algorithm to optimize urban block morphology, and simulates optimization objectives with Ladybug, Honeybee, and Dragonfly tools. The results indicate that this framework effectively reduces energy consumption and urban heat island effects while increasing photovoltaic output. The study finds that urban forms characterized by predominantly low-rise buildings, lower building density, reasonable orientation, and good ventilation perform better in terms of sustainability.