4.6 Article

Integrating the Value of Electricity Resilience in Energy Planning and Operations Decisions

Journal

IEEE SYSTEMS JOURNAL
Volume 15, Issue 1, Pages 204-214

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSYST.2019.2961298

Keywords

Resilience; Measurement; Investment; Planning; Load modeling; Adaptation models; Biological system modeling; Energy planning and operations model; energy resilience; resilience metric; value of resilience

Funding

  1. U.S. Department of Energy (DOE) [DE-AC36-08GO28308]

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This research has developed a flexible and scalable modeling method to integrate the duration-dependent value of resilience in energy decisions. Two case studies show that understanding the value of lost load can provide opportunities to reduce lifecycle costs of energy through adjusted investment or operational decisions.
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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