识别停电热点,以支持风险管理规划
Kaia Stødle1, Roger Flage1, Seth D Guikema2
1Department of Safety, Economics and Planning, University of Stavanger, Stavanger, Norway.
概括
本研究介绍了一种方法,使用空间统计学来识别停电热点. 这有助于电力公司将资源集中在问题区域,以提高电网可靠性.
科学领域:
- 电气工程 电气工程
- 空间统计的空间统计.
- 风险管理 风险管理
背景情况:
- 可靠的电力系统对社会和经济至关重要.
- 现有的研究往往侧重于预测与天气有关的停电,忽视了经常出现的停电地点.
- 识别停电热点对于有效的公用事业风险管理至关重要.
研究的目的:
- 调整现有的空间统计数据以识别停电热点.
- 为电力公用事业提供一种实用的方法,以精确确定高频中断位置.
- 支持数据驱动的决策,优先考虑电网维护和加强.
主要方法:
- 利用莫兰的I空间统计,特别是当地的莫兰的I.
- 在网格单元级计算统计数据以进行细粒度分析.
- 应用了一组标准来过和确认已识别的热点电网单元.
主要成果:
- 成功地调整了Moran's I以使用实用公用事业数据识别停电热点.
- 展示了一种方法,用于精确定位具有统计学上显著的断电集群的网格单元.
- 为公用事业公司提供了一个明确,可操作的方法来定位有问题的系统区域.
结论:
- 经过调整的Moran's I统计提供了一个可访问和有效的工具,用于识别停电热点.
- 这种方法使公用事业公司能够更有效地将资源分配到关键区域.
- 优先检查和加强已识别的热点可以提高电力系统的整体可靠性和弹性.
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