Modeling Power Grid Recovery and Resilience Post Extreme Weather Events

Modeling Power Grid Recovery and Resilience Post Extreme Weather Events
Author :
Publisher :
Total Pages : 196
Release :
ISBN-10 : OCLC:1183049966
ISBN-13 :
Rating : 4/5 (66 Downloads)

Book Synopsis Modeling Power Grid Recovery and Resilience Post Extreme Weather Events by : Priyadharshini Kumaravelan

Download or read book Modeling Power Grid Recovery and Resilience Post Extreme Weather Events written by Priyadharshini Kumaravelan and published by . This book was released on 2019 with total page 196 pages. Available in PDF, EPUB and Kindle. Book excerpt: The traditional N-1 power grid system is inadequate as it cannot withstand extreme weather events like hurricane, flooding, earthquake etc. Extreme event analysis reports by NERC, BPU, and ERCOT state that failure of outdoor grid components like distribution lines, transformers and generators lead to majority of the power outages where millions of customers get affected. This research addresses the problem of power grid resilience post an extreme weather event and how the grid recovery can be planned and executed. We propose a repair and recovery model for transmission lines for the case of Hurricane Harvey and analyze how the repair rate and the failure rate affect various performance metrics. We analyze how electric vehicles (EV) can be used as a potential alternative to build resilience of a power system in contingency. A mathematical model is developed for the EV battery swap process and the minimum spare battery requirement is analyzed for various scenarios. We present a Vehicle-to-Grid (V2G) based resilience model for critical loads like manufacturing facility during an extreme event. The main goal of this model is to determine the sizing and siting of the wind- and solar-based microgrid to ensure power resilience through island operations. Through this model, we analyze how the number of EVs, battery capacities, industrial production loss and the V2G service cost affect the levelized cost of energy (LCOE) in extreme weather condition.


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