通过时间序列利用可持续的家庭能源和环境资源管理
José Cecílio1, Tiago Rodrigues2, Márcia Barros2
1LASIGE, University of Lisbon, Lisbon, Portugal. jmcecilio@ciencias.ulisboa.pt.
Scientific data
|March 23, 2025
概括
一个新的数据集将家庭能源使用,太阳能生产和天气联系起来. 这些数据有助于可再生能源预测和实现碳中和的可持续能源战略.
科学领域:
- 环境科学 环境科学
- 能源系统工程 能源系统工程
- 数据科学数据科学数据科学
背景情况:
- 了解住宅能源消耗和太阳能生产对于可持续能源转型至关重要.
- 现有的数据集往往缺乏整合的,颗粒状的数据,将能源使用,成本,太阳能发电和环境因素联系起来.
- 实现可持续发展目标 (SDG) 7,9,11和13需要可靠的数据来做出明智的决策.
研究的目的:
- 介绍新的太阳能,家庭能源和环境研究指标 (SHEERM) 数据集.
- 提供一个全面的,横截面数据集,将电荷,能源成本,太阳能生产,太阳辐射和天气参数联系起来.
- 促进可再生能源预测,电网管理和能源政策制定方面的研究.
主要方法:
- 从13个家庭收集了近三年的数据.
- 综合电力负载,能源成本,现场太阳能生产,太阳辐射和天气参数.
- 使用已建立的机器学习模型验证了数据集.
主要成果:
- SHEERM数据集提供了住宅能源和环境数据的独特组合.
- 机器学习模型被成功应用来验证数据并证明其实用性.
- 该数据集可以进行多方面的分析,以优化能源利用和预测.
结论:
- SHEERM数据集是推动可再生能源研究和实施的宝贵资源.
- 它支持新能源系统的设计,以加强可持续能源战略.
- 数据集可以加速向碳中和和提高能源效率的过渡.
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