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November 25, 2014
Intelligent Outage Analytics Significantly Improves Utilities’ Capability of Handling Massive Outages under the Extreme Weather Conditions
By: Jianhua Zhang

The extreme weather conditions, such as hurricane, snow and ice storm, could have significant impacts on the safe operation of electrical distribution grid and could lead to serious, sometimes cascading, outages in the large scale area(s). Therefore, it is a major concern by the utility companies and the local government entities. Although the industry has realized the importance of intelligent outage pre-warning before the upcoming events and the need of enhancing the capability of quick service restoration after the major storm to improve the system reliability and customer satisfaction level, the reality is that there is a lack of solutions to help the utilities to predict the possible damages caused by the extreme weather conditions, to prepare the resources in advance, and to minimize the service restoration time during and after the storm.

Intelligent outage analytics is a concept and a solution that Accenture Smart Grid Services (ASGS) team and Accenture Technology Labs (ATL) plan to introduce to Accenture’s utility clients to address the challenges brought by the extreme weather conditions. This concept includes a few key features.

  • First, for a particular type of extreme weather condition, a storm pre-warning model should be established using the weather forecast data. Based on the mathematical statistics and probability theory and the combination with the power grid asset information, this pre-warning model could predict the possible equipment damage caused by the up-coming extreme weather conditions.

  • Second, based on the predicted possible grid equipment failures, a methodology and analytics model shall be developed to estimate the possible outage area(s) and the amount of customers being affected, such that the power-off notifications could be published to the possible outage customers timely. Also, based on the estimated customer outage information, an optimization model shall be developed for the optimal pre-allocating of maintenance crews, preparing maintenance supplies and improving asset utilization. All of these works help to reduce the maintenance and operating costs.

  • Third, after the storm rolls over, an Estimated Restoration Time (ERT) engine is needed to help the utility to calculate an initial ERT, providing a quick and rough outlook of the overall restoration progress. In the following days, this ERT engine should also make reliable estimations on the time of outage clearance and the full recovery of the power supply both at the system level and the individual customer level. Utilizing the ERT engine, utilities could make the ERT information available to the public in real time and dynamically update it as the system recovery progresses.

Based on the above mentioned innovation concept and by working together with ASGS team, the smart grid research team of ATL has developed an Intelligent Outage Analytics solution. This solution utilizes the big data technology and integrates the weather forecasting data, the power grid equipment asset information, and the AMI data to establish the hurricane and snow/ice storm impact models, the blackout pre-warning and pre-allocation model, and the ERT optimization model, respectively. The R&D innovations of this solution include advanced power grid disaster pre-warning, resources pre configuration, initial resource optimal scheduling and active asset assessment. A demo system has been developed such that the ASGS and utility practice teams could showcase Accenture’s Intelligent Outage Analytics solution on the client sites.

Accenture’s Intelligent Outage Analytics solution

From technology development perspective, this solution combines the operational technology (OT) system (outage management, distribution management, and energy management) with the information technology (IT) system (customer information, work management, meter data management). It provides intelligent and more effective management for the business of smart distribution grid operation and maintenance to meet consumer’s growing demands on the quality of the service and to effectively address the threat posed by the natural disasters.

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