向数据驱动的电力管理:多区域统一的数据和知识图
Vid Hanžel1, Blaž Bertalanič2, Carolina Fortuna2
1Jozef Stefan Institute, Ljubljana, 1000, Slovenia. vid.hanzel@gmail.com.
Scientific data
|January 9, 2025
概括
这项研究解决了对家庭电力消费数据的需求,以应对气候变化. 它介绍了一个新的多区域数据集和知识图,以实现更好的分析和数据驱动的能源效率政策.
科学领域:
- 能源政策 能源政策
- 数据科学数据科学数据科学
- 环境科学 环境科学
背景情况:
- 全球电力消耗量正在增加,原因是人口和技术.
- 住宅部门占全球电力使用量的25%,提供了显著的效率潜力.
- 缺乏统一的,多区域的家庭数据阻碍了气候变化缓解努力.
研究的目的:
- 引入家庭电力消耗的标准化,多区域数据集.
- 为增强数据分析和互操作性开发一个RDF知识图.
- 促进能源部门的数据驱动政策和商业发展.
主要方法:
- 汇编了来自多个地区的公开可用的家庭电力消费数据.
- 将标准化数据转化为统一的格式,以确保可访问性.
- 开发了一个资源描述框架 (RDF) 知识图,以结构化和语境化消费数据.
主要成果:
- 创建了一个新的家庭电力消费的多区域数据集.
- 建立了一个RDF知识图,将消费数据与家庭财产联系起来.
- 启用机器学习应用程序,如分类和需求预测.
结论:
- 新的数据集和知识图表解决了能源研究中的关键数据缺口.
- 结构化数据支持能源利益相关者进行先进的分析和知情决策.
- 促进与现有的开放知识库的互操作性,以获得更广泛的影响.
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