用算法优化建筑节能设计，能耗降三成，舒适度提升。
Application of Algorithms in Energy-Efficient Design Platforms for Green Building
- 融合BIM与传感器数据，用进化算法多目标优化建筑能耗。
- 40轮优化后每平米年耗能降至223千瓦时，降幅29.3%。
- 适合建筑节能设计者、可持续工程师快速决策参考。
绿色建筑设计中，计算机辅助能源评估被广泛用于提升效率并实现整体优化。本文提出一个整合建筑信息模型（BIM）、传感器运行数据及先进仿真流程的平台，采用多层服务架构，通过高性能C++核心与自适应代理模型连接，实现动态能源模拟与进化多目标优化。以一栋中高层办公楼为案例，选取五个代表性区域采集围护结构特征与人员活动模式数据。预处理后，缺失传感器数据占全年记录的3.2%，所有变量采用15分钟插值标准化。经40轮优化后，单位面积年能耗由315 kWh/m²降至223 kWh/m²，降幅达29.3%；全生命周期成本仅增加3.7%，不适感小时数降至每年70小时以下。帕累托最优解分析显示，围护结构传热系数U值范围为1.05–1.57 W/m²K，夜间通风率在2.1–3.6 h⁻¹之间，均与能效密切相关。结果表明，该集成算法框架具备良好可扩展性、强性能和工程可行性，为设计工程师与可持续实践者提供可靠的数据驱动决策支持工具。
原文摘要 · Abstract (English)
During green building design, computer-aided energy assessment is widely used to improve efficiency and achieve overall optimization. This paper presents a platform that combines Building Information Modeling (BIM), sensor operational data, and advanced simulation workflows using robust algorithms. The platform uses a multi-layer service architecture with dynamic energy simulation and evolutionary multi-objective optimization, connected via a high-performance C++ core and adaptive agent models. A mid-rise office building was selected as the case study. Five representative areas were chosen to collect data on building envelope characteristics and occupancy patterns. After preprocessing, missing sensor data accounted for 3.2% of annual records, and all variables were standardized using 15-minute interpolation. After 40 optimization rounds, annual energy consumption per square meter dropped by 29.3% from 315 kWh/m2 to 223 kWh/m2. The lifecycle cost increase for occupants was limited to 3.7%, and discomfort hours were reduced to under 70 hours per year. Analysis of Pareto optimal solutions shows that the envelope U-value ranges from 1.05 to 1.57 W/m2K, and nighttime ventilation rate ranges from 2.1 to 3.6 h-1, both closely linked to energy performance. The results confirm that the integrated algorithm framework offers good scalability, strong performance, and technical feasibility for green building design. This platform provides a reliable decision-support tool for design engineers and sustainability practitioners, enabling accurate, data-driven delivery of energy-efficient buildings.
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