Resiliency-based optimization of restoration policies for electric power distribution systems

•Develops, analyses and tests new resiliency metrics for power distribution systems.•Operational and hardening measures are optimized in response to extreme weather.•Creates the resiliency frontier to compare performance of restoration strategies.•Reliability-based metrics are suboptimal compared to...

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Bibliographic Details
Published inElectric power systems research Vol. 161; pp. 188 - 198
Main Authors Figueroa-Candia, Marcelo, Felder, Frank A., Coit, David W.
Format Journal Article
LanguageEnglish
Published Elsevier B.V 01.08.2018
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ISSN0378-7796
1873-2046
DOI10.1016/j.epsr.2018.04.007

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Summary:•Develops, analyses and tests new resiliency metrics for power distribution systems.•Operational and hardening measures are optimized in response to extreme weather.•Creates the resiliency frontier to compare performance of restoration strategies.•Reliability-based metrics are suboptimal compared to optimization approaches. A modeling framework based on resiliency is proposed for the evaluation and optimization of restoration policies for electric power distribution systems subject to extreme weather events. In order to quantify resiliency, understood as a property of a power distribution system that allows it to be restored from a disrupted state to a predefined level of normal operating conditions, a set of evaluation metrics is defined. A multi-dimensional resiliency measure is considered that includes response-time components, information availability, and quality of service. The concept of resiliency frontier is presented as an upper bound for system resiliency for a given set of possible restoration prioritization strategies. Optimization is performed over the set of feasible restoration policies, information investments, and human resource availability to determine optimal customer and system-wide monetary utility. The methodology is tested in medium-sized power distribution systems to obtain optimal restoration policies and determine resource allocation.
ISSN:0378-7796
1873-2046
DOI:10.1016/j.epsr.2018.04.007