Joint Planning of Natural Gas and Electric Power Transmission with Spatially Correlated Failures

Wenjing Su, Seth Blumsack

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

We develop and illustrate a method for the joint planning of natural gas and electric power systems that are subject to spatially correlated failures of the kind that would be expected to occur in the case of extreme weather events. Our approach utilizes a two-stage stochastic planning and operations framework for a jointly planned and operated gas and electric power transmission system. Computational tractability is achieved through convex relaxations of the natural gas flow equations and the use of a machine learning algorithm to reduce the set of possible contingencies. We illustrate the method using a small test system used previously in the literature to evaluate computational performance of joint gas-grid models. We find that planning for geographically correlated failures rather than just random failures reduces the level of unserved energy relative to planning for random (spatially uncorrelated failures). Planning for geographically correlated failures, however, does not eliminate the susceptability of the joint gas-grid system to spatially uncorrelated failures.

Original languageEnglish (US)
Title of host publicationProceedings of the 55th Annual Hawaii International Conference on System Sciences, HICSS 2022
EditorsTung X. Bui
PublisherIEEE Computer Society
Pages3599-3609
Number of pages11
ISBN (Electronic)9780998133157
StatePublished - 2022
Event55th Annual Hawaii International Conference on System Sciences, HICSS 2022 - Virtual, Online, United States
Duration: Jan 3 2022Jan 7 2022

Publication series

NameProceedings of the Annual Hawaii International Conference on System Sciences
Volume2022-January
ISSN (Print)1530-1605

Conference

Conference55th Annual Hawaii International Conference on System Sciences, HICSS 2022
Country/TerritoryUnited States
CityVirtual, Online
Period1/3/221/7/22

All Science Journal Classification (ASJC) codes

  • General Engineering

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