论文标题
使用中断并恢复过程统计数据从分销公用事业数据中提取弹性指标
Extracting resilience metrics from distribution utility data using outage and restore process statistics
论文作者
论文摘要
弹性曲线跟踪事件在电网上的事件中的中断的积累和恢复。我们表明，从实用程序数据产生的弹性曲线始终可以分解为中断过程和恢复过程，并且这些过程通常会在时间上重叠。我们使用真实实用数据中的许多事件来表征这些过程的统计数据，并根据这些统计数据得出公式，以获取弹性指标，例如恢复持续时间，未服务的客户时间以及中断和恢复速率。该公式表达这些指标的平均值与事件中的中断数量的函数。我们还为恢复持续时间的变异性提供了一个公式，这使我们能够以95％的置信度预测最大还原持续时间。总体而言，我们提供了一种简单而通用的方法，将弹性曲线分解为中断和还原过程，然后展示如何使用这些过程从标准分配系统数据中提取弹性指标。
Resilience curves track the accumulation and restoration of outages during an event on an electric distribution grid. We show that a resilience curve generated from utility data can always be decomposed into an outage process and a restore process and that these processes generally overlap in time. We use many events in real utility data to characterize the statistics of these processes, and derive formulas based on these statistics for resilience metrics such as restore duration, customer hours not served, and outage and restore rates. The formulas express the mean value of these metrics as a function of the number of outages in the event. We also give a formula for the variability of restore duration, which allows us to predict a maximum restore duration with 95% confidence. Overall, we give a simple and general way to decompose resilience curves into outage and restore processes and then show how to use these processes to extract resilience metrics from standard distribution system data.
