Estimated Time of Restoration (ETR) Guidance for Electric Distribution Networks

David Wanik; Emmanouil Anagnostou; Brian Hartman; Thomas Layton

doi:10.1515/jhsem-2016-0063

Article

Estimated Time of Restoration (ETR) Guidance for Electric Distribution Networks

David Wanik , Emmanouil Anagnostou , Brian Hartman and Thomas Layton

Published/Copyright: January 30, 2018

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From the journal Journal of Homeland Security and Emergency Management Volume 15 Issue 1

Abstract

Electric distribution utilities have an obligation to inform the public and government regulators about when they expect to complete service restoration after a major storm. In this study, we explore methods for calculating the estimated time of restoration (ETR) from weather impacts, defined as the time it will take for 99.5% of customers to be restored. Actual data from Storm Irene (2011), the October Nor’easter (2011) and Hurricane Sandy (2012) within the Eversource Energy-Connecticut service territory were used to calibrate and test the methods; data used included predicted outages, the peak number of customers affected, a ratio of how many outages a restoration crew can repair per day, and the count of crews working per day. Data known before a storm strikes (such as predicted outages and available crews) can be used to calculate ETR and support pre-storm allocation of crews and resources, while data available immediately after the storm passes (such as customers affected) can be used as motivation for securing or releasing crews to complete the restoration in a timely manner. Used together, the methods presented in this paper will help utilities provide a reasonable, data-driven ETR without relying solely on qualitative past experiences or instinct.

Keywords: electric reliability; ETR; outage; restoration; severe weather

Acknowledgements

We gratefully acknowledge the support of Eversource and the Eversource Energy Center at the University of Connecticut, which provided funding and data for this research.

References

Abrams, R., and B. Lawsky. 2013. Moreland Commission on Utility Storm Preparation and Response: Final Report. Available online at https://www.moreland.ny.gov/sites/default/files/MACfinalreportjune22.pdf. Accessed September 15, 2017.Search in Google Scholar

Ancona, J. J. 1995. “Framework for Power System Restoration Following a Major Power Failure.” IEEE Transactions on Power Systems 10 (3): 1480–1485.10.1109/59.466500Search in Google Scholar

Brown, R. E., S. Gupta, R. D. Christie, and S. S. Venkata, R. 1997. “Fletcher. Distribution System Reliability Assessment: Momentary Interruptions and Storms.” IEEE Transactions on Power Delivery 12 (4):1569–1574.10.1109/61.634177Search in Google Scholar

Campbell, R. J. 2013. Weather-Related Power Outages and Electric System Resiliency. Electricity Reliability in the United States: Select Research, 127–147.Search in Google Scholar

Cao, C., and Y. Bai. 2014. “Quantitative Analysis of VIIRS DNB Nightlight Point Source for Light Power Estimation and Stability Monitoring.” Remote Sensing 6: 11915–11935.10.3390/rs61211915Search in Google Scholar

Caron, M. A., A. H. House, J. W. Betkowski, J. Buckingham, and K. Braffman. 2013. PURA Investigation into the Performance of Connecticut’s Electric Distribution Companies and Gas Companies in Restoring Service Following Storm Sandy. Report No.: Docket 12-11-07.Search in Google Scholar

Castillo, A. 2014. “Risk Analysis and Management in Power Outage and Restoration: A Literature Survey.” Electric Power Systems Research 107: 9–15.10.1016/j.epsr.2013.09.002Search in Google Scholar

Cole, T., D. W. Wanik, A. Molthan, M. Roman, and E. Griffin. 2017. “Synergistic Use of Nighttime Satellite Data, Electric Utility Infrastructure, and Ambient Population to Improve Power Outage Detections in Urban Areas.” Remote Sensing 9 (3): 286.10.3390/rs9030286Search in Google Scholar

Connecticut Light and Power. 2014. Transmission and Distribution Reliability Performance Report. Regulatory Compliance. Berlin, CT: Connecticut Light & Power.Search in Google Scholar

Davidson, R. A., H. Liu, K. Sarpong, P. Sparks, and D. V. Rosowsky. 2003. “Electric Power Distribution System Performance in Carolina Hurricanes.” Natural Hazards Review 4 (1): 36–45.10.1061/(ASCE)1527-6988(2003)4:1(36)Search in Google Scholar

Edison Electric Institute. 2014. Understanding the Electric Power Industry’s Response and Restoration Process. Washington D.C.: Edison Electric Institute; May 2014. Report No.: MA_101.Search in Google Scholar

Guikema, S., S. R. Han, and S. Quiring. 2008. Estimating Power Outages During Hurricanes Using Semi-Parametric Statistical Methods. 2008 Structures Congress – Structures Congress 2008: Crossing the Borders; 24 April 2008 through 26 April 2008; Vancouver, BC.10.1061/41016(314)189Search in Google Scholar

Guikema, S. D., R. Nateghi, S. M. Quiring, A. Staid, A. C. Reilly, and M. Gao. 2014a. “Predicting Hurricane Power Outages to Support Storm Response Planning.” IEEE Access 2: 1364–1373.10.1109/ACCESS.2014.2365716Search in Google Scholar

Guikema, S. D., R. Nateghi, and S. M. Quiring. 2014b. Storm Power Outage Prediction Modeling. European Safety and Reliability Conference, ESREL 2013, Amsterdam: shers; 29 September 2013 through 2 October 2013.Search in Google Scholar

He, J., D. W. Wanik, B. M. Hartman, E. N. Anagnostou, M. Astitha, and M. E. B. Frediani. 2016. “Nonparametric Tree-Based Predictive Modeling of Storm Outages on an Electric Distribution Network.” Risk Analysis 37 (3): 441–458.10.1111/risa.12652Search in Google Scholar

Liu, H., R. A. Davidson, and T. V. Apanasovich. 2007. “Statistical Forecasting of Electric Power Restoration Times in Hurricanes and Ice Storms.” IEEE Transactions on Power Systems 22 (4): 2270–2279.10.1109/TPWRS.2007.907587Search in Google Scholar

McGee, J., J. Skiff, P. Carozza, T. Edelstein, L. Hoffman, S. Jackson, R. McGrath, F. McGroarty, and C. Osten. 2012. Report of the Two Storm Panel. State of Connecticut.Search in Google Scholar

Mensah, A. F., and L. Duenas-Osorio. 2014. Outage Predictions of Electric Power Systems Under Hurricane Winds by Bayesian Networks. 2014 International Conference on Probabilistic Methods Applied to Power Systems, PMAPS 2014; 7 July 2014 through 10 July 2014; Institute of Electrical and Electronics Engineers Inc.10.1109/PMAPS.2014.6960677Search in Google Scholar

Nateghi, R., S. D. Guikema, and S. M. Quiring. 2011. “Comparison and Validation of Statistical Methods for Predicting Power Outage Durations in the Event of Hurricanes.” Risk Analysis 31 (12): 1897–1906.10.1111/j.1539-6924.2011.01618.xSearch in Google Scholar

Nateghi, R., S. Guikema, and S. M. Quiring. 2014a. “Power Outage Estimation for Tropical Cyclones: Improved Accuracy with Simpler Models.” Risk Analysis 34 (6): 1069–1078.10.1111/risa.12131Search in Google Scholar

Nateghi, R., S. D. Guikema, and S. M. Quiring. 2014b. “Forecasting Hurricane-Induced Power Outage Durations.” Natural Hazards 74 (3): 1795–1811.10.1007/s11069-014-1270-9Search in Google Scholar

Ouyang, M., and L. Dueñas-Osorio. 2014. “Multi-Dimensional Hurricane Resilience Assessment of Electric Power Systems.” Structural Safety 48: 15–24.10.1016/j.strusafe.2014.01.001Search in Google Scholar

Reed, D. A. 2008. “Electric Utility Distribution Analysis for Extreme Winds.” Journal of Wind Engineering and Industrial Aerodynamics 96 (1): 123–140.10.1016/j.jweia.2007.04.002Search in Google Scholar

Sullivan, M. J. 1996. “Interruption Costs, Customer Satisfaction and Expectations for Service Reliability.” IEEE Transactions on Power Systems 11 (2): 989–995.10.1109/59.496185Search in Google Scholar

Wanik, D. W., E. N. Anagnostou, B. M. Hartman, M. E. B. Frediani, and M. Astitha. 2015. “Storm outage modeling for an electric distribution network in Northeastern USA.” Natural Hazards 79 (2): 1359–1384.10.1007/s11069-015-1908-2Search in Google Scholar

Wanik, D. W., J. R. Parent, E. N. Anagnostou, and B. M. Hartman. 2017a. “Using Vegetation Management and LiDAR-Derived Tree Height Data to Improve Outage Predictions for Electric Utilities.” Electric Power Systems Research 146: 236–245.10.1016/j.epsr.2017.01.039Search in Google Scholar

Wanik, D. W., E. N. Anagnostou, M. Astitha, B. M. Hartman, G. M. Lackmann, J. Yang, D. Cerrai, J. He, and M. E. B. Frediani. 2017b. “A Case Study on Power Outage Impacts from Future Hurricane Sandy Scenarios.” Journal of Applied Meteorology and Climatology. Early Online Release. Available from https://doi.org/10.1175/JAMC-D-16-0408.1. Published online: 2 October 2017.10.1175/JAMC-D-16-0408.1Search in Google Scholar

Winkler, J., L. Dueñas-Osorio, R. Stein, and D. Subramanian. 2010. “Performance Assessment of Topologically Diverse Power Systems Subjected to Hurricane Events.” Reliability Engineering and System Safety 95 (4): 323–336.10.1016/j.ress.2009.11.002Search in Google Scholar

Published Online: 2018-01-30

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https://doi.org/10.1515/jhsem-2016-0063

Keywords for this article

electric reliability; ETR; outage; restoration; severe weather