弹性(材料科学)
持续时间(音乐)
网格
投资(军事)
投资决策
环境经济学
可扩展性
电
价值(数学)
风险分析(工程)
计算机科学
业务
工程类
经济
财务
机器学习
热力学
艺术
几何学
文学类
行为经济学
数据库
政治
政治学
法学
物理
数学
电气工程
作者
Kate Anderson,Xiangkun Li,Sourabh Dalvi,Sean Ericson,Clayton Barrows,Caitlin C. Murphy,Eliza Hotchkiss
出处
期刊:IEEE Systems Journal
[Institute of Electrical and Electronics Engineers]
日期:2020-01-09
卷期号:15 (1): 204-214
被引量:48
标识
DOI:10.1109/jsyst.2019.2961298
摘要
Recent increase in the number of natural disasters resulting in widespread, long-duration, and costly outages have brought the energy system resilience to the forefront. As system owners and operators seek to improve the system resilience, they often find it challenging to assess the costs and benefits of resilience investments. Costs are fairly well understood and measured, but benefits are less so. There are many resilience metrics that attempt to measure resilience benefit, but the existing methods for calculating metrics and incorporating value of resilience in energy decisions are not easily executed. To address this, we developed a method for modeling the value of resilience that is flexible and scalable across multiple types of models. This article describes a framework for incorporating duration-dependent customer damage functions (CDFs) into grid- and campus-scale planning and operations models. In two case studies, we consider how the duration-dependent value of resilience influences the investment and operation decisions. We find that in both cases, knowledge of the value of lost load provides opportunities to reduce the lifecycle cost of energy through adjusted investment or operational decisions. The primary contribution of this research is to integrate the duration-dependent value of resilience in energy decisions. This study will be useful to grid operators interested in reducing the value of customer losses during grid outages, as well as campus or site owners evaluating resilience investments.
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