NDLI: Outage predictions of electric power systems under Hurricane winds by Bayesian networks

Content Provider	IEEE Xplore Digital Library
Author	Mensah, A.F. Duenas-Osorio, L.
Copyright Year	2014
Description	Author affiliation: Civil & Environ. Eng., Rice Univ., Houston, TX, USA (Mensah, A.F.; Duenas-Osorio, L.)
Abstract	The stability and reliability of electric power grids are essential to the continuous operation of modern cities as well as for the mitigation, preparedness, response and recovery in disaster management. Power systems must be assessed in order to identify and address component and system-level weaknesses while supporting their rapid restoration. This paper proposes a Bayesian Network (BN)-based framework to predict outages in an electric power grid that is exposed to a hurricane event. The inherent capabilities of BNs, including its intuitive and graphical representation of probabilistic information, and its ability to allow information updating with ease, make it an effective tool for this application. The framework is coupled with a DC-flow model that captures the physics of the electrical system and also reduces the computational complexity of building conditional probability tables needed in the BN model. The framework relies on component fragilities and topology of the grid, and predicts outages at substations and distribution points within the electric power system. Its application is demonstrated using Harris County's electric power system under the 2008 Hurricane Ike winds that battered the Gulf Coast of the United States. The model captured well the field system response, where low outage probabilities are observed in the transmission system while the outage risks at distribution load points are significantly higher. The developed BN framework can seamlessly integrate transmission and distribution systems, inform disaster management, and suggest restoration strategies, while supporting decision-making for pre- or post-event intervention actions.
Starting Page	1
Ending Page	6
File Size	595761
Page Count	6
File Format	PDF
ISBN	9781479935611
DOI	10.1109/PMAPS.2014.6960677
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-07-07
Publisher Place	UK
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Bayesian Networks Substations Computational modeling Performance assessment Hurricanes Power outage predictions Bayes methods Reliability Hurricane Load modeling Electric Power systems
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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