从家庭能源管理系统到能源社区:方法和数据
Antonio Ruano1, Maria da Graça Ruano2
1IDMEC, Instituto Superior Técnico, Universidade de Lisboa, Lisboa, and Faculty of Science & Technology, University of Algarve, Faro, Portugal. aruano@ualg.pt.
Scientific data
|April 6, 2024
概括
HEMStoEC数据库提供了三年来四个葡萄牙家庭的详细能源消耗数据,包括天气,太阳能和家电使用情况. 这一宝贵的数据集支持对非侵入性负载监控和家庭能源管理系统的研究.
科学领域:
- 能源系统 能源系统
- 建筑科学 建筑科学
- 数据科学数据科学数据科学
背景情况:
- 准确的能源消耗数据对于开发有效的家庭能源管理系统 (HEMS) 至关重要.
- 现有的数据集往往缺乏先进的HEMS研究所需的细节性或全面范围.
- 在NILMforIHEM和HEMS2IEA项目中,获得了有关住宅能源使用的大量数据.
研究的目的:
- 介绍和描述HEMStoEC数据库,这是HEMS和非侵入性负载监控 (NILM) 研究的新资源.
- 提供一个全面的,多年的数据集,包括电力消耗,环境因素和设备运行.
- 通过提供带有详细元数据的原始和处理数据来促进研究.
主要方法:
- 收集了三年 (2020年1月 - 2023年2月) 的高分辨率 (1秒和1分钟) 和同步 (5分钟) 数据.
- 来自多个来源的综合数据:家庭电力消耗,当地天气,光伏和电池系统,室内气候和个人电器使用情况.
- 每月组织数据集以提高可管理性和可访问性,并注意到数据缺口和插值周期.
主要成果:
- HEMStoEC数据库包含了三年来来自葡萄牙南部四个住宅单元的同步数据.
- 数据包括颗粒式的电能消耗,天气条件,太阳能发电和储存,室内气候参数,以及特定的电器操作.
- 数据集提供了原始和处理的信息,包括识别的数据差距和数据插值周期.
结论:
- HEMStoEC数据库对家庭能源管理和NILM领域做出了重大贡献.
- 它的全面性质和长时间使它成为训练和验证能源建模和预测算法的理想选择.
- 研究人员可以利用这一数据集来推进住宅能源效率和智能电网集成的理解和优化.
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