Dongqi Wu , Xiangtian Zheng , Ali Menati , Lane Smith , Bainan Xia , Yixing Xu , Chanan Singh , Le Xie
{"title":"How much demand flexibility could have spared texas from the 2021 outage?","authors":"Dongqi Wu , Xiangtian Zheng , Ali Menati , Lane Smith , Bainan Xia , Yixing Xu , Chanan Singh , Le Xie","doi":"10.1016/j.adapen.2022.100106","DOIUrl":null,"url":null,"abstract":"<div><p>The February 2021 Texas winter power outage has led to hundreds of deaths and billions of dollars in economic losses, largely due to the generation failure and record-breaking electric demand. In this paper, we study the scaling-up of demand flexibility as a means to avoid load shedding during such an extreme weather event. The three mechanisms considered are interruptible load, residential load rationing, and incentive-based demand response. By simulating on a synthetic but realistic large-scale Texas grid model along with demand flexibility modeling and electricity outage data, we identify portfolios of mixing mechanisms that can completely avoid outages, where individual mechanisms may fail due to decaying marginal effects. We also reveal that interruptible load and residential load rationing are complementary, while incentive-based demand response exhibits counterintuitive nonlinear effects on the efficacy of other mechanisms. The quantitative results can provide instructive insights for developing demand response programs against extreme weather conditions.</p></div>","PeriodicalId":34615,"journal":{"name":"Advances in Applied Energy","volume":"7 ","pages":"Article 100106"},"PeriodicalIF":13.0000,"publicationDate":"2022-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666792422000245/pdfft?md5=9dc51b1b571609a8c481a745ac3b2c2f&pid=1-s2.0-S2666792422000245-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Applied Energy","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666792422000245","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
The February 2021 Texas winter power outage has led to hundreds of deaths and billions of dollars in economic losses, largely due to the generation failure and record-breaking electric demand. In this paper, we study the scaling-up of demand flexibility as a means to avoid load shedding during such an extreme weather event. The three mechanisms considered are interruptible load, residential load rationing, and incentive-based demand response. By simulating on a synthetic but realistic large-scale Texas grid model along with demand flexibility modeling and electricity outage data, we identify portfolios of mixing mechanisms that can completely avoid outages, where individual mechanisms may fail due to decaying marginal effects. We also reveal that interruptible load and residential load rationing are complementary, while incentive-based demand response exhibits counterintuitive nonlinear effects on the efficacy of other mechanisms. The quantitative results can provide instructive insights for developing demand response programs against extreme weather conditions.