DTE Energy manages electric grid assets with Internet of Things data

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It is an exciting time to work for a utility company. The electric grid and utility sector is undergoing the most massive change since Thomas Edison invented the light bulb in 1879. It's safe to say that the technology innovation occurring in the electric grid over the next decade will likely dwarf many of the changes that occurred during the previous century.

"It is a very exciting time," says Gary Gauthier, manager of IT Research & Strategy for Electric Reliability at DTE Energy in Detroit. "When I first got involved in electric reliability and research, it was obvious to me that this is a great time because there is such a convergence of IT and operational technology occurring in the electric business."

Embracing the Internet of Things is leading the charge on several initiatives, including coupling Internet of Things solutions and data analytics to better manage electric grid assets, and monitoring the infrastructure to enable improved efficiencies and better customer service. Early this year, DTE began deploying asset health solutions throughout its service territories. By mid-September, the company plans to have all of its distribution assets, including poles, transformers and cables, outfitted with sensors that will send valuable data back for analysis. By studying that data, DTE will be able to make real-time decisions about the health of its distribution assets.

Every utility has to deal with equipment failures from unpreventable incidents such as broken tree limbs or windstorms. Innovative utilities are harnessing the power of data analytics to predict failure rates for controllable incidents, such as overloading during peak usage times. By examining data provided by sensor technology, DTE hopes to better predict when a circuit might blow. This can be used during a heat wave to alert the company that the transformer on the circuit is close to being loaded beyond its rated capacity. Utilities can predict circuits at high risk for failure by tracking the current flowing through switches and other devices.

Armed with the risk profiles for certain assets and the number of customers who would be impacted by a failure, utilities can create a prioritized list of which assets require maintenance before they fail. In addition, energy providers can use the data to compare against an asset's life expectancy and create an investment profile for the future. For DTE, the data provides a window into how much the company needs to invest in utility poles or transformers over the next five years, helping it to better manage cash flow and expenditures and move from a preventive to predictive maintenance model.

Edison would be proud

By better understanding asset health, utilities can also optimize response weather damage response plans. By applying data analytics, utilities can determine which poles or transformers are the weakest and assign crews to that area during a strong windstorm or blizzard. Similarly, if a utility has old transformers operating in an area in which air conditioner usage is expected to peak during an extended heat wave, utilities can target those assets before they fail at the most inopportune time.

According to Gauthier, DTE is using analytics to make decisions about long-term distribution investments. He says the company realizes "that incorporating remote devices will fundamentally change our response time, reduce the number of customers impacted by outages and reduce our operating costs."

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