Published on 27 May 2014
“ This technology demonstrated how we could quickly, efficiently and economically route the right crew to the right place and perform maintenance instead of responding after the fact. ”
William Bell, Technology Director, Analytics and Data Services, CenterPoint Energy, Grid and Market Operations
Energy and Utilities
Houston-based energy company CenterPoint Energy serves more than five million electric and natural gas customers primarily in Arkansas, Louisiana, Minnesota, Mississippi, Oklahoma and Texas.
The company’s smart grid program, deployed in the Houston area, includes advanced meters (or smart meters) and intelligent grid technologies that help it improve electric power reliability, speed service restoration in the event of an outage, and foster energy efficiency. These smart grid technologies are streaming millions of messages. And for CenterPoint Energy to gain new insight from this data, it must be able to analyze it in near-real time.
To help the company’s business units better utilize this data, CenterPoint Energy’s Analytics and Data Services staff in conjunction with their partners in IT launched a Proof of Concept project using powerful analytics technology that will help operators detect and respond to minute changes in its infrastructure before customers are affected.
Will enable staff to improve prediction and prevention of operational issues. Will improve outage communication and response to enhance the customer experience. Will help CenterPoint Energy deploy the right crew to the right place at the right time with the right information about the situation. Will enable near real-time automation with the ability to process logic, identify conditions, and interface with other systems right crew to the right place at the right time with the right information about the situation.
IBM products and services that were used in this case study.
InfoSphere Streams, E&U: Transmission and Distribution Operations (TD Ops), E&U: Intelligent Utility Network (IUN), Smarter Planet, Automation, Big Data & Analytics, Big Data, Information Management Foundation, Big Data & Analytics: Financial processes
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