低碳园区典型用能场景、多维评价与供能优化配置数据集

本数据集基于国家重点研发计划项目（2022YFE0205300），针对中国六大区域（东北、华北、华东、中南、西南、西北）的典型城市（如哈尔滨、北京、合肥、广州、武汉、贵阳），采用EnergyPlus软件平台仿真生成低碳园区典型用能场景下的冷、热、电负荷数据，包括工业、居民、商业园区及办公楼等建筑类型。数据时间精度为逐小时（8760小时/年），空间范围覆盖上述区域典型城市，空间精度为园区级。数据采集通过EnergyPlus基于ASHRAE标准模板和典型气象年（TMY）气候数据模拟生成原始负荷数据；随后使用MATLAB进行异常值检测和线性插值填补缺失值；多维评价指标集通过原始数据核算形成，包括能源、经济及环境等维度；供能优化配置结果采用优化模型计算，涵盖风机、光伏、太阳能产热等设备配置方案。数据集总容量约7MB，包括负荷参数、多园区评价数据和园区级分地区分类型的负荷数据。潜在价值在于支撑低碳园区规划、碳减排评估和能源优化决策，促进绿色转型。

This dataset is developed based on the National Key R&D Program of China (Grant No. 2022YFE0205300). Targeting typical cities in six major regions of China—Northeast China, North China, East China, Central-South China, Southwest China, and Northwest China—including Harbin, Beijing, Hefei, Guangzhou, Wuhan, and Guiyang, it generates cooling, heating, and electrical load data under typical energy-use scenarios of low-carbon parks via the EnergyPlus software platform. Covered building types involve industrial parks, residential buildings, commercial parks, and office buildings.

The temporal resolution of the dataset is hourly (8760 hours per year), with spatial coverage over the aforementioned typical cities and a spatial granularity at the park level. Raw load data was first simulated by EnergyPlus based on ASHRAE standard templates and Typical Meteorological Year (TMY) climatic data; subsequently, outlier detection and missing value imputation via linear interpolation were conducted using MATLAB. A multi-dimensional evaluation indicator set was then derived from the raw data, covering energy, economic, and environmental dimensions. Optimal energy supply configuration results were calculated using optimization models, encompassing equipment configuration schemes such as fans, photovoltaic systems, and solar heat generation units.

The total size of the dataset is approximately 7 MB, including load parameters, multi-park evaluation data, and park-level load data categorized by region and building type. Its potential value lies in supporting low-carbon park planning, carbon emission reduction assessment, and energy optimization decision-making, thereby facilitating green transition.