Outage Data Analytics for Correlating Resilience and Reliability

In the last few decades, extreme weather events (EWEs) have become more frequent, especially in the southeastern part of the U.S. These EWEs affect the distribution grid greatly, resulting in long-duration power outages. To fully understand the outcomes of these catastrophic events and to correlate the impact on the reliability and resiliency of the utility company, multiple years of historical EWE-related outage data collected from a utility company are analyzed. Moreover, this study utilizes the System Average Interruption Duration Index (SAIDI) matrix to analyze the EWEs. This study finds overgrown vegetation as one of the main reasons for outages during EWEs. Besides, loss of transmission and generation also contribute significantly to outage events resulting in a high percentage of customers being affected for long periods.

在过去几十年中，极端天气事件（EWE）变得更加频繁，尤其是在美国东南部。这些极端天气事件对配电网影响巨大，导致长时间停电。为了充分了解这些灾难性事件的后果，并关联其对公用事业公司可靠性和恢复力的影响，对从一家公用事业公司收集的多年与极端天气事件相关的停电历史数据进行了分析。此外，本研究利用系统平均停电持续时间指数（SAIDI）矩阵来分析极端天气事件。本研究发现植被过度生长是极端天气事件期间停电的主要原因之一。此外，输电和发电损失也对停电事件有重大影响，导致高比例的用户长时间受到影响。