碳中和愿景下基于计算性思维的绿色校园规划设计动态优化研究——以粤港澳大湾区为例

大学校园是运行中的绿色发展实验室，也是绿色发展理念最理想的教育基地，更是能耗大户和节能减排的巨大潜力场所，因此在“2030碳达峰，2060碳中和”的战略目标下，大学绿色校园的设计和建设备受关注。本项目基于“两观三性”设计理论等的理论指引，探索碳中和愿景下基于计算性思维的绿色校园规划设计动态优化方法。基于TOPSIS算法建立绿色校园低碳化水平评价体系，构建校园碳排放快速耦合动态预测模型，得到直观的动态低碳化水平指标；引入“计算智能”（CI）这一前沿创新驱动，基于“低碳化水平—增量成本”多目标优化模型，通过智能优化算法的迭代和寻优，甄选平衡经济性和减排绩效的优化方案。针对大湾区湿热气候，从需求减量、能效提升、能源替代的碳中和路径优化设计策略组合。该成果将成为校园“碳中和”动态平台，为高校“碳中和”计划的制定提供科学的指导依据，为绿色校园规划优化设计提供评估手段和决策支持，助力提升校园绿色性能。

University campuses are active labs for green development, the most ideal education bases for promoting green development concept, and more importantly, venues of huge potential to address energy efficiency and emission reduction of large energy consumers. Therefore, the green university campus design and development are receiving wide attention in China under the central government’s strategic goal to "peak carbon dioxide emissions by 2030 and achieve carbon neutral by 2060". This project, following the design theories including the Two Concepts (holistic and sustainable concepts) and Three Features (place, culture and time), seeks to gain insight into dynamic optimization of green campus planning and design based on computational thinking under the vision of carbon neutral. First, the dynamic low-carbon level index of the campus is obtained by establishing a rating system for the low-carbon level of green campus and a fast-coupling model for predicting carbon emission on the campus; then the "computational intelligence" (CI) is brought into the study as a cutting-edge innovation drive, which, aided by the “incremental cost and low carbon level” synergetic optimization model, optimizes the green campus planning and design and realizes the optimal environment performance campus-wide; finally, case studies are conducted on university campus planning and design in Guangdong-Hong Kong-Macao Greater Bay Area, and a portfolio of optimization strategies are proposed in view of the hot and humid climate to balance multiple objectives from the perspective of carbon neutral, such as demand reduction, energy efficiency improvement and alternative energy. This research outcome is of great significance for enriching the researches on green campuses in China and enhancing the green performance of university campuses.