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Title: Quantifying Power Distribution System Resiliency Using Code Based Metric

Abstract

It is essential to improve the resiliency of power distribution systems (PDS) given the increase in extreme weather events, number of malicious threats and consumers’ need for higher reliability. This paper provides a formal approach to evaluate the operational resiliency of PDS, and quantify the resiliency of a system using a code-based metric. A combination of steady state and dynamic simulation tools is used to determine the resiliency metric. Dynamic simulation tools help with analyzing impact of short-term events, which might affect operational resiliency in long term. A dynamic optimization algorithm for changing operating criteria to increase the sustainability of the most critical loads has been proposed. The proposed theoretical approach is validated using a simple power distribution system model and simulation results demonstrate the ability to quantify the resiliency using the proposed code-based metric. The time-dependent quantification of resiliency has been demonstrated on a test system of two connected CERTS microgrids.

Authors:
; ; ;
Publication Date:
Research Org.:
Idaho National Lab. (INL), Idaho Falls, ID (United States)
Sponsoring Org.:
USDOE Office of Nuclear Energy (NE)
OSTI Identifier:
1462756
Report Number(s):
INL/JOU-17-43304
DOE Contract Number:  
DE-AC07-05ID14517
Resource Type:
Journal Article
Journal Name:
IEEE Transactions on Industrial Applications
Additional Journal Information:
Journal Name: IEEE Transactions on Industrial Applications
Country of Publication:
United States
Language:
English
Subject:
24 POWER TRANSMISSION AND DISTRIBUTION; Distribution Systems, Distributed Energy Resources, Power System Operations, Renewable Integration, Resilience

Citation Formats

Chanda, Sayonsom, Srivastava, Anurag K, Mohanpurkar, Manish U, and Hovsapian, Rob. Quantifying Power Distribution System Resiliency Using Code Based Metric. United States: N. p., 2018. Web. doi:10.1109/TIA.2018.2808483.
Chanda, Sayonsom, Srivastava, Anurag K, Mohanpurkar, Manish U, & Hovsapian, Rob. Quantifying Power Distribution System Resiliency Using Code Based Metric. United States. doi:10.1109/TIA.2018.2808483.
Chanda, Sayonsom, Srivastava, Anurag K, Mohanpurkar, Manish U, and Hovsapian, Rob. Wed . "Quantifying Power Distribution System Resiliency Using Code Based Metric". United States. doi:10.1109/TIA.2018.2808483. https://www.osti.gov/servlets/purl/1462756.
@article{osti_1462756,
title = {Quantifying Power Distribution System Resiliency Using Code Based Metric},
author = {Chanda, Sayonsom and Srivastava, Anurag K and Mohanpurkar, Manish U and Hovsapian, Rob},
abstractNote = {It is essential to improve the resiliency of power distribution systems (PDS) given the increase in extreme weather events, number of malicious threats and consumers’ need for higher reliability. This paper provides a formal approach to evaluate the operational resiliency of PDS, and quantify the resiliency of a system using a code-based metric. A combination of steady state and dynamic simulation tools is used to determine the resiliency metric. Dynamic simulation tools help with analyzing impact of short-term events, which might affect operational resiliency in long term. A dynamic optimization algorithm for changing operating criteria to increase the sustainability of the most critical loads has been proposed. The proposed theoretical approach is validated using a simple power distribution system model and simulation results demonstrate the ability to quantify the resiliency using the proposed code-based metric. The time-dependent quantification of resiliency has been demonstrated on a test system of two connected CERTS microgrids.},
doi = {10.1109/TIA.2018.2808483},
journal = {IEEE Transactions on Industrial Applications},
number = ,
volume = ,
place = {United States},
year = {2018},
month = {2}
}