能源管理的每日数据:可再生能源的生产,消费和储存.
Tayenne Dias de Lima1, Bruno Ribeiro1, Pedro Faria1
1Intelligent Systems Associate Laboratory (LASI), GECAD, ISEP - Polytechnic of Porto, Porto, 4200-072, Portugal.
Data in brief
|June 19, 2025
概括
这一数据集为电力系统规划提供了关键数据,包括可再生能源场景和实际电池使用情况. 它有助于管理能源不确定性和优化电池存储系统,以改善电网运行.
科学领域:
- 电力系统工程 电力系统工程
- 整合可再生能源的整合
- 数据科学用于能源的数据科学
背景情况:
- 可再生能源的变化和需求的不确定性对电力系统的规划和运行构成重大挑战.
- 随机编程模型需要具有代表性的数据来有效地纳入不确定性.
- 现实世界的电池充/放电数据对于开发储能解决方案至关重要.
研究的目的:
- 提供一个全面的数据集,解决可再生能源发电和需求的不确定性.
- 为储能研究提供现实世界的电池运行数据.
- 支持制定可靠的电力系统规划和运营战略.
主要方法:
- 使用k-medoid集群和动态时间扭曲 (DTW) 来生成太阳能,能源价格和需求的代表性场景.
- 从运营用途收集和分析实际电池充电和放电数据.
- 在季节性数据块 (冬季,春季,夏季,秋季) 中整合时间相关性.
主要成果:
- 一个数据集,包括每小时的太阳能发电量,能源价格和需求场景,以捕捉历史变化.
- 一个详细介绍电池实际充/放电模式,持续时间和深度的数据集.
- 证明数据适用于基于场景的随机编程和电池存储系统研究.
结论:
- 该数据集为增强电力系统规划和运营决策提供了宝贵的资源.
- 它通过解决变化和不确定性来促进可再生能源的整合.
- 它支持电池存储系统研究和电网集成方面的进展.
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