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

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.

[1]  J. J. Ancona A framework for power system restoration following a major power failure , 1995 .

[2]  B. N. Suddeth,et al.  Interruption costs, customer satisfaction and expectations for service reliability , 1996 .

[3]  S. S. Venkata,et al.  Distribution system reliability assessment: momentary interruptions and storms , 1997 .

[4]  Rachel A. Davidson,et al.  Electric Power Distribution System Performance in Carolina Hurricanes , 2003 .

[5]  Haibin Liu,et al.  Statistical Forecasting of Electric Power Restoration Times in Hurricanes and Ice Storms , 2007, IEEE Transactions on Power Systems.

[6]  D. Reed Electric utility distribution analysis for extreme winds , 2008 .

[7]  Devika Subramanian,et al.  Performance assessment of topologically diverse power systems subjected to hurricane events , 2010, Reliab. Eng. Syst. Saf..

[8]  Seth D Guikema,et al.  Comparison and Validation of Statistical Methods for Predicting Power Outage Durations in the Event of Hurricanes , 2011, Risk analysis : an official publication of the Society for Risk Analysis.

[9]  Richard J. Campbell,et al.  Weather-Related Power Outages and Electric System Resiliency , 2012 .

[10]  Anya Castillo,et al.  Risk analysis and management in power outage and restoration: A literature survey , 2014 .

[11]  Seth D. Guikema,et al.  Predicting Hurricane Power Outages to Support Storm Response Planning , 2014, IEEE Access.

[12]  Changyong Cao,et al.  Quantitative Analysis of VIIRS DNB Nightlight Point Source for Light Power Estimation and Stability Monitoring , 2014, Remote. Sens..

[13]  Seth D. Guikema,et al.  Forecasting hurricane-induced power outage durations , 2014, Natural Hazards.

[14]  Roshanak Nateghi,et al.  Power Outage Estimation for Tropical Cyclones: Improved Accuracy with Simpler Models , 2014, Risk analysis : an official publication of the Society for Risk Analysis.

[15]  Min Ouyang,et al.  Multi-dimensional hurricane resilience assessment of electric power systems , 2014 .

[16]  D. Wanik,et al.  Storm outage modeling for an electric distribution network in Northeastern USA , 2015, Natural Hazards.

[17]  D. Wanik,et al.  Using vegetation management and LiDAR-derived tree height data to improve outage predictions for electric utilities , 2017 .

[18]  D. Wanik,et al.  Nonparametric Tree‐Based Predictive Modeling of Storm Outages on an Electric Distribution Network , 2017, Risk analysis : an official publication of the Society for Risk Analysis.

[19]  Robert E. Griffin,et al.  Synergistic Use of Nighttime Satellite Data, Electric Utility Infrastructure, and Ambient Population to Improve Power Outage Detections in Urban Areas , 2017, Remote. Sens..

[20]  D. Wanik,et al.  A Case Study on Power Outage Impacts from Future Hurricane Sandy Scenarios , 2018 .