Thomas Anthony, P.E.Industry Intelligence

ManagerOncor Electric Delivery Co.

USA

Thomas DamonAssistant VP–Smart Grid

Science Applications International Corporation

USA

Failure Detection and Predictive Analytics System

• Tom Anthony

• Industry intelligence manager with a U.S.-based electric utility

• Currently deploying 3.1 million smart meters

• Tom Damon

• System developer who uses power system engineering expertise to assist utilities in optimizing business processes by leveraging their technology investments

Project Background

• U.S. Department of Energy’s Modern Grid Initiative

• Knowledge transfer opportunities

• Leverage existing data sources to improve analytics and predictive capabilities

• Use the cloud to control data processing costs

Experience on Smart Grid Technology Demonstration and R&D Project

• Located in West Virginia

• Integration of distributed resources and advanced technologies

• Included fault location and prediction• Advanced fault location

• Neural network methodologies to identify pre-fault conditions and anticipate failures

Feeders and zones

The Utility Found the Effort Promising

• Continue enhancing its smart grid abilities

• Collaborate with a company that could develop needed algorithms and software for the fault detection and prediction system

• Analyze existing data from the utility’s broadband-over-powerline (BPL) system to automatically identify pattern interruptions and threshold breaches that might indicate incipient customer issues within the distribution system

A Two-Phase Project

1. Develop an initial “proof-of-concept” data analysis application and build a prototype

2. Develop a functioning data analysis tool and install it in the utility’s data center

Phase 1: Develop Prototype

Phase 2: Develop and Install Tool

Data Analysis Tool: Issues Screen

Data Analysis Tool: Work Request Screen

Data Analysis Tool: Details Screen

What the Future Holds

• Both the utility and the tool development company will continue to invest resources to develop the data analysis tool, part of an overall smart grid deployment program

• The utility plans to install the data analysis tool in the second quarter of 2011, after completion of its data center move

• Once the tool is installed and operational, the process of automating the recognition of actual issues on the BPL system will begin

• If the tool proves its value on the BPL system, it should easily be able to be adapted to other future remote data acquisition platforms

What We Have Learned

• The value of applying analytic algorithms to grid data analysis has been proven

• Predictive analytics is a core ingredient in future system integration programs

• Real-time analysis is necessary for high-value devices

• This effort increased the data sources to build a neural network capability to improve maintenance prescription and failure prediction