{"title":"飓风后洪水对电力系统恢复影响的统计评估","authors":"Grant Cruse, A. Kwasinski","doi":"10.1109/RWS52686.2021.9611804","DOIUrl":null,"url":null,"abstract":"Historically, hurricanes have been a major cause of devastation and widespread power outages in many areas of the United States. Since the 1970s, several popular methods for estimating hurricane intensity have been developed, but these have tended to focus solely on the amount of damage and outages that can be expected rather than the amount of time that will be required to restore power. Additionally, these methods allow for the inclusion of only a small number of variables, such as wind speeds and storm surge. In the past, four metrics that describe the damage sustained by and the restoration times required for power systems that are affected by hurricanes were proposed as alternatives to the existing methods for estimating hurricane damage. These were maximum outage incidence, restoration times for 95% and 98% of the total number of outages, and average outage duration. Regression curves were generated by relating these indices to four variables that describe the intensity of the storms. The results showed that the generated curves fit the measured data very well, but they also seemed to suggest that there are other factors that may affect the metrics. In this work, three additional variables were included in the models to examine the impact of flooding on the metrics, particularly the amount of time that is required to restore outages. These were the flooded area in a county, the time until flood waters in a county receded, and the total area flooded by the hurricane.","PeriodicalId":294639,"journal":{"name":"2021 Resilience Week (RWS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Statistical Evaluation of Flooding Impact on Power System Restoration Following a Hurricane\",\"authors\":\"Grant Cruse, A. Kwasinski\",\"doi\":\"10.1109/RWS52686.2021.9611804\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Historically, hurricanes have been a major cause of devastation and widespread power outages in many areas of the United States. Since the 1970s, several popular methods for estimating hurricane intensity have been developed, but these have tended to focus solely on the amount of damage and outages that can be expected rather than the amount of time that will be required to restore power. Additionally, these methods allow for the inclusion of only a small number of variables, such as wind speeds and storm surge. In the past, four metrics that describe the damage sustained by and the restoration times required for power systems that are affected by hurricanes were proposed as alternatives to the existing methods for estimating hurricane damage. These were maximum outage incidence, restoration times for 95% and 98% of the total number of outages, and average outage duration. Regression curves were generated by relating these indices to four variables that describe the intensity of the storms. The results showed that the generated curves fit the measured data very well, but they also seemed to suggest that there are other factors that may affect the metrics. In this work, three additional variables were included in the models to examine the impact of flooding on the metrics, particularly the amount of time that is required to restore outages. These were the flooded area in a county, the time until flood waters in a county receded, and the total area flooded by the hurricane.\",\"PeriodicalId\":294639,\"journal\":{\"name\":\"2021 Resilience Week (RWS)\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-10-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 Resilience Week (RWS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RWS52686.2021.9611804\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 Resilience Week (RWS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RWS52686.2021.9611804","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Statistical Evaluation of Flooding Impact on Power System Restoration Following a Hurricane
Historically, hurricanes have been a major cause of devastation and widespread power outages in many areas of the United States. Since the 1970s, several popular methods for estimating hurricane intensity have been developed, but these have tended to focus solely on the amount of damage and outages that can be expected rather than the amount of time that will be required to restore power. Additionally, these methods allow for the inclusion of only a small number of variables, such as wind speeds and storm surge. In the past, four metrics that describe the damage sustained by and the restoration times required for power systems that are affected by hurricanes were proposed as alternatives to the existing methods for estimating hurricane damage. These were maximum outage incidence, restoration times for 95% and 98% of the total number of outages, and average outage duration. Regression curves were generated by relating these indices to four variables that describe the intensity of the storms. The results showed that the generated curves fit the measured data very well, but they also seemed to suggest that there are other factors that may affect the metrics. In this work, three additional variables were included in the models to examine the impact of flooding on the metrics, particularly the amount of time that is required to restore outages. These were the flooded area in a county, the time until flood waters in a county receded, and the total area flooded by the hurricane.