ENDEMO-Europe: Dataset for European long-term cross-sectoral energy demand modelling

Energy demand models require a wide range of data to adequately characterize energy use across regions and consumption sectors, and to account for historical developments. The dataset we provide can serve as input for energy system modelling tools, such as the URBS model generator for cost optimization [1] and the ENDEMO framework for energy demand estimation and analysis [2, 3]. ENDEMO-Europe dataset provides processed and harmonized variables for energy demand modelling at national and NUTS 2 (county-level) scales across Europe, covering the EU-27 (excluding Cyprus and Malta), EFTA countries, the United Kingdom, and the Balkan peninsula. It spans four final consumption sectors: industry, households, commercial, trade and services (CTS), and traffic. The dataset integrates raw statistics with derived indicators, for example by combining energy per carrier, combustion efficiency, and employment data to calculate specific energy consumption per employee. Industry data include production quantities of energy-intensive subsectors, their NUTS 2 distribution, and specific energy requirements by technology, while non-energy-intensive branches are represented through GDP allocation. Household data cover floor area, hot water use, and specific energy consumption per m² or per capita; CTS data include employees per subsector and specific energy per employee; and traffic data provide passenger- and tonne-kilometres, modal split, rail electrification rate, and consumption per person- or ton-kilometre. Energy demand is distinguished by application type (heat, hydrogen, electricity), with both yearly and hourly profiles available for modelling and integrated systems analysis. Keywords: useful energy demand; analysis; forecasting; timeseries; electricity; heat; hydrogen References: [1] J. Dorfner et al., tum-ens/urbs: Zenodo, 2019. Accessed: Nov. 11 2025. [2] A. Kerekeš, L. Breuning and A. Epishev, endemo, 2025. Accessed: Dec. 3 2025. [Online]. Available: https://github.com/tum-ens/endemo [3] L. Breuning and A. Kerekeš, “endemo – Energy Demand Modeling for Europe,” in Energy Sciences for Europe’s Green Deal: 11th Colloquium of the Munich School of Engineering, Garching bei München, 2021. Accessed: Dec. 3 2025. [Online]. Available: https://mediatum.ub.tum.de/doc/1631566/0zjz35nd6rdatc8xb3cq5xkyx.pdf能源需求模型需要多维度数据，以充分刻画不同区域与消费部门的能源使用情况，并兼顾历史发展沿革。本数据集可作为能源系统建模工具的输入数据源，例如用于成本优化的URBS模型生成器[1]，以及用于能源需求估算与分析的ENDEMO框架[2, 3]。 ENDEMO-Europe数据集提供经过处理与标准化协调的变量，用于欧洲范围内国家尺度及NUTS 2（县域级）尺度的能源需求建模，覆盖欧盟27国（不含塞浦路斯与马耳他）、欧洲自由贸易联盟（European Free Trade Association, EFTA）国家、英国以及巴尔干半岛区域。该数据集涵盖四大最终消费部门：工业、居民家庭、商业贸易与服务（Commercial, Trade and Services, CTS）以及交通运输。 本数据集将原始统计数据与衍生指标进行整合，例如通过结合按能源载体划分的能耗、燃烧效率与就业数据，计算得到单位员工的单位能耗。工业数据包含高耗能子部门的产量、这些子部门在NUTS 2尺度的空间分布，以及各技术路径下的单位能源需求；而非能源密集型行业则通过GDP分配进行表征。居民家庭数据涵盖建筑面积、热水使用量以及每平方米或人均的单位能耗；CTS部门数据包含各子部门的员工数与单位员工能耗；交通运输数据则提供旅客公里数、吨公里数、运输方式分担率、铁路电气化率，以及按人公里或吨公里计算的能耗。 能源需求可按应用类型划分为热能、氢能与电力，数据集同时提供年度与逐时的能耗曲线，可用于建模与集成系统分析。 关键词：有效能源需求；分析；预测；时间序列；电力；热能；氢能 参考文献： [1] J. Dorfner 等人，tum-ens/urbs: Zenodo，2019年。访问时间：2025年11月11日。 [2] A. Kerekeš、L. Breuning 与 A. Epishev，endemo，2025年。访问时间：2025年12月3日。[在线]。可获取：https://github.com/tum-ens/endemo [3] L. Breuning 与 A. Kerekeš，"endemo – Energy Demand Modeling for Europe"，载于《欧洲绿色协议的能源科学：慕尼黑工程学院第11届学术研讨会论文集》，慕尼黑附近加尔兴，2021年。访问时间：2025年12月3日。[在线]。可获取：https://mediatum.ub.tum.de/doc/1631566/0zjz35nd6rdatc8xb3cq5xkyx.pdf