A multi-objective optimization framework for designing urban block forms considering daylight, energy consumption, and photovoltaic energy potential

Abstract

Urban form significantly influences building energy consumption. However, most research has primarily focused on quantifying the relationship between the two factors, with limited exploration of optimizing urban form to enhance building energy performance. Moreover, studies often fail to consider multiple performance objectives simultaneously. This study proposes a multi-objective optimization framework for early urban design stage to improve energy and environmental performance in residential block layouts. The performance objectives include energy consumption, photovoltaic energy potential, and sunlight hours. The framework is implemented using the parametric platform Rhino & Grasshopper, where a parametric model controls the layout of blocks. Ladybug Tools plugin is employed for performance simulation, and Wallacei is used for optimization. An ideal residential block in Jianhu City, China, is taken as a case study. The study generates a total of 1896 valid solutions, including 58 Pareto solutions. The performance of the Pareto solutions demonstrates considerable improvements, indicating the effectiveness of optimizing urban form for enhancing energy and environmental performance. Compared to the initial solution, a typical Pareto solution showcases a 1.5% reduction in energy consumption, a 52.7% increase in photovoltaic energy potential, and a 50% increase in sunlight hours. These findings underscore the pivotal role of urban block morphology in influencing energy consumption, photovoltaic potential, and daylighting. The proposed multi-objective framework in this study enhances and facilitates sustainable block form design, which is expected to provide technical support for energy-efficient or low-carbon urban design.