How much demand flexibility could have spared texas from the 2021 outage?

IF 13 Q1 ENERGY & FUELS Advances in Applied Energy Pub Date : 2022-09-01 DOI:10.1016/j.adapen.2022.100106
Dongqi Wu , Xiangtian Zheng , Ali Menati , Lane Smith , Bainan Xia , Yixing Xu , Chanan Singh , Le Xie
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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.

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有多大的需求灵活性可以使德克萨斯州免于2021年的停电?
2021年2月德克萨斯州冬季停电导致数百人死亡和数十亿美元的经济损失,主要原因是发电故障和创纪录的电力需求。在这篇论文中,我们研究了在这种极端天气事件中,需求灵活性的扩大作为避免负荷减少的一种手段。考虑的三种机制是可中断负荷、住宅负荷配给和基于激励的需求响应。通过模拟一个综合但现实的大规模德克萨斯电网模型以及需求灵活性建模和停电数据,我们确定了可以完全避免停电的混合机制组合,其中单个机制可能由于边际效应衰减而失效。研究还发现,可中断负荷和居民负荷配额制是互补的,而基于激励的需求响应对其他机制的有效性表现出反直觉的非线性效应。定量结果可以为制定针对极端天气条件的需求响应计划提供指导性见解。
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来源期刊
Advances in Applied Energy
Advances in Applied Energy Energy-General Energy
CiteScore
23.90
自引率
0.00%
发文量
36
审稿时长
21 days
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