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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. • A multi-objective optimization framework for designing urban block forms is proposed. • Constructing parametric urban block models based on typical local building types. • Daylighting, energy consumption, and PV energy potential are selected as objectives. • The performance of the Pareto solutions is improved compared to the initial solution. [ABSTRACT FROM AUTHOR]

• An energy-efficient oriented multi-objective urban block form design workflow is proposed. • The relationship between urban form factors and building energy consumption, as well as solar energy potential, is explored. • Reducing energy demand, increasing energy generation, and improving environmental performance should be considered together in the design of energy-efficient blocks. • BD, OSR, SC, and PAR have significant correlations with the total EUI of the block. • FAR, BD, AF, OSR, SC, and PAR are highly correlated with rooftop PV energy generation. Urban form can significantly affect building energy consumption and solar energy potential, which is essential to sustainable urban development. However, few studies have proposed a comprehensive framework to discuss this. In addition, how to bridge the gap between theory and practice, and how to combine quantitative research results with urban form design is also a matter of concern. Based on this background, this study proposes a multi-objective urban form design optimization framework based on the Grasshopper platform. Three optimization objectives were identified: minimum building energy consumption, maximum solar potential and maximum sunlight hours. Then, taking Jianhu in China as an example, the building types are extracted from the actual urban context to create blocks. The Ladybug Tools plugin is used for performance simulation, and multi-objective optimization is run in Wallacei X. Furthermore, based on the optimization process data, a correlation analysis of urban form factors with building energy consumption and solar energy potential is conducted. Finally, the research findings are integrated, and energy-efficient urban form design strategies are proposed. The research results show that a block form with excellent energy performance in Jianhu has the following characteristics: (i) The open space is often located in the center of the block. High-rise buildings are located on the west side. (ii) The block presents a layout consisting of a low south side and high north side. (iii) The orientation of the block is 15° south by westor due south. (iv) Avoid building types with large shape coefficient such as P-4, C-1, S-3 and C-2. In addition, building density (BD), open space ratio (OSR), shape coefficient (SC) and average perimeter-area ratio (PAR) have significant correlations with the total building energy use intensity of the block. For solar potential, floor area ratio (FAR), BD, the average number of floors (AF), OSR, SC, and PAR are highly correlated with rooftop PV energy generation, and sky view factor (SVF) is significantly correlated with rooftop PV energy generation. [ABSTRACT FROM AUTHOR]

Energy-efficient urban design is an important prerequisite to sustainable urban development and reduction of greenhouse gas emissions. This study proposes an automatic framework to optimize urban design through the use of an urban building energy model. Three optimization goals were defined: maximum solar energy utilization, solar lighting of the first floor, and minimum building energy demand. Urban morphology was integrated into the optimization process as the bridge between the urban design scenario and the actual urban block. To validate the model, this study abstracted basic urban forms from actual urban contexts to generate urban blocks with the Rhino tool and run optimization in the Wallacei X, for multi-objective optimization in Rhino. The long short-term memory (LSTM) network was applied to infer energy performance of 41 actual urban blocks in Jianhu, China. In the results, the proposed framework can be validated feasibly with optimization of 100 iterations. A set of optimal results will be achieved for three goals and five clusters defined for different concerns of urban design strategies. The LSTM can achieve the best accuracy of 1.21% and 1.37% for energy generation of photovoltaic and total building energy use intensity respectively. • Low-energy urban design is important to sustainable urban development. • Enhancing solar utilization and reducing energy demand are important in urban design. • Urban building energy modeling is a popular and inspiring tool in urban design. • This study proposes an automatic low-energy urban design using simulation and data-driven approach. • The framework is validated feasibly by actual urban design and real urban blocks. [ABSTRACT FROM AUTHOR]