article

A statistical model for risk management of electric outage forecasts

Authors:

L. A. Treinish,

J. R. M. HoskingAuthors Info & Claims

IBM Journal of Research and Development, Volume 54, Issue 3

Pages 315 - 325

https://doi.org/10.1147/JRD.2010.2044836

Published: 01 May 2010 Publication History

Abstract

Risk management of power outages caused by severe weather events, such as hurricanes, tornadoes, and thunderstorms, plays an important role in electric utility distribution operations. Damage prediction based on weather forecasts on an appropriate spatial scale can improve the efficiency of risk management by reducing the economic and societal costs associated with restoration efforts. We have developed a method of predicting the number of outages in a fashion that is suitable for use by electric utilities by using a Poisson regression model for spatial data in a Bayesian hierarchical framework. Particular attention is given to building models that incorporate uncertainty in the outage data from the perspective of multiple spatial resolutions and spatial correlation in the outage data. The outage-prediction model was developed using historical outage data from an electric utility company in the northeastern part of the United States. The model is being used by that company in the operations of its overhead electrical distribution system and emergency management operations. We discuss results to date and how the model is being applied. In addition to the damage forecasts, we have developed tools for risk visualization by displaying the uncertainty of the damage forecasts on geographic maps.

References

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Cited By

Mukherjee SNarayanam KAggarwal NBose DSinghee A(2021)Robust resource demand estimation using hierarchical Bayesian model in a distributed service systemProceedings of the 3rd ACM India Joint International Conference on Data Science & Management of Data (8th ACM IKDD CODS & 26th COMAD)10.1145/3430984.3431003(350-358)Online publication date: 2-Jan-2021
https://dl.acm.org/doi/10.1145/3430984.3431003
Treinish LCipriani JPraino ASinghee AWang HSinn MLonij VFiot JChen B(2016)Enabling coupled models to predict the business impact of weather on electric utilitiesIBM Journal of Research and Development10.1147/JRD.2015.248947860:1(5:1-5:10)Online publication date: 1-Jan-2016
https://dl.acm.org/doi/10.1147/JRD.2015.2489478
Treinish LPraino ACipriani JMello UMantripragada KVilla Real LSesini PSaxena VGeorge TMittal R(2013)Enabling high-resolution forecasting of severe weather and flooding events in Rio de JaneiroIBM Journal of Research and Development10.1147/JRD.2013.226341457:5(7-7)Online publication date: 1-Sep-2013
https://dl.acm.org/doi/10.1147/JRD.2013.2263414

A statistical model for risk management of electric outage forecasts
1. Applied computing
  1. Physical sciences and engineering

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cover image IBM Journal of Research and Development

IBM Journal of Research and Development Volume 54, Issue 3

May 2010

119 pages

ISSN:0018-8646

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IBM Corp.

United States

Publication History

Published: 01 May 2010

Accepted: 22 May 2009

Received: 19 March 2009

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Cited By

Mukherjee SNarayanam KAggarwal NBose DSinghee A(2021)Robust resource demand estimation using hierarchical Bayesian model in a distributed service systemProceedings of the 3rd ACM India Joint International Conference on Data Science & Management of Data (8th ACM IKDD CODS & 26th COMAD)10.1145/3430984.3431003(350-358)Online publication date: 2-Jan-2021
https://dl.acm.org/doi/10.1145/3430984.3431003
Treinish LCipriani JPraino ASinghee AWang HSinn MLonij VFiot JChen B(2016)Enabling coupled models to predict the business impact of weather on electric utilitiesIBM Journal of Research and Development10.1147/JRD.2015.248947860:1(5:1-5:10)Online publication date: 1-Jan-2016
https://dl.acm.org/doi/10.1147/JRD.2015.2489478
Treinish LPraino ACipriani JMello UMantripragada KVilla Real LSesini PSaxena VGeorge TMittal R(2013)Enabling high-resolution forecasting of severe weather and flooding events in Rio de JaneiroIBM Journal of Research and Development10.1147/JRD.2013.226341457:5(7-7)Online publication date: 1-Sep-2013
https://dl.acm.org/doi/10.1147/JRD.2013.2263414

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