“How do you reduce operational costs and increase consumer satisfaction?” asks DTE Energy’s Gary Gauthier. He posed this age-old business quandary with the authoritative tone that suggests he may already have the answer. Electricity companies, of course, can never simply starve operations. Because blackouts, angry headlines, and business disruptions would result.
But DTE Energy has applied IBM analytics and its own connected equipment intelligence to predict failure in its electricity distribution assets, such as its 1.2 million utility poles, millions of switches, and untold miles of wire. For instance, if a certain type of transformer is known to fail after a certain number of years, DTE Energy can head off trouble by replacing it. The predicted operational savings has the company looking for additional ways to apply IoT insights. “Putting these technologies in service in the real world has allowed us to derive value faster,” says Gauthier, the company’s manager of operational technologies.
Getting the jump on IoT deployment
In comparison to other industries, energy may have the jump on IoT deployment. Utility poles are conveniently spaced to gather data; smart meters are widespread. But until now, such “nodes” have been underutilized as little more than elaborate customer billing systems. Now providers such as DTE Energy are adding a cognitive and data analytics layer. This allows them to discover what Gauthier calls “the trouble behind the trouble.” When outages occur and crews head to the field, technicians can consult smart-meter-based intelligence. That allows them to discern who may still be without electricity despite a repair, saving costly return trips. To ensure long-term continuity, DTE Energy brings its experts to analyze IBM Watson intelligence. Then, they can estimate the life expectancy of various components in field assets, helping to improve maintenance efficiencies.
But what about the weather … ?
For another company in the energy space, adding real-time weather insight to IoT capability is leading to big productivity gains. Swiss robotics maker ABB expects buyers of its wind turbine equipment to see a 15 percent increase in productivity over the next few years. The company manufactures connected generators, motors, power automation systems and other turbine parts. Customers can harness a Watson-powered dynamic control platform. This brings together regional power use, real-time network feedback, and metrology forecasting. “With B2B customers, we’re seeing a need for more cognitive input and dynamic relationships,” says Doug Voda, Global Segment Leader for Smart Grid. He also noted that utilities need to make nearly instantaneous decisions to meet customer demand—or risk disruption. “They need information faster.”
Some of the operational tools energy companies have adopted—keeping watch on the grid we all rely on—include industrial IoT dashboards such as IBM’s Maximo. This allows them to extract insights from assets; Blockchain for the IoT for tracking interactions with partners; and the metrology insights from The Weather Company. IBM’s forecasting unit is a leader in real-time data and prediction nationally. That out-front position is partly thanks to the barometric pressure readings it ingests from the more than 100 million Weather Channel app users around the globe.
Creating a better plan
Looking beyond operational improvements of individual energy players, one can see an even bigger win for the environment. Electricity generation in the U.S. has always been something of a guessing game when matching production to demand, leading to inefficiencies. By harnessing IoT sensor data and artificial intelligence, providers are getting better at being able to predict and plan for demand spikes. That eliminates wasteful “spinning reserves” and other big capital expenses. “The idea is to fine tune our grid,” says Gauthier, “that way, energy generation goes where it’s needed.”
Three steps to boost energy operations through connection
Install a company-wide dashboard for industrial operations so that you can view the health of assets across the enterprise.
Set up blockchain tracking and verification across partners and vendors to ensure the security and reliability along the supply chain.
Integrate real-world intelligence, such as value-added weather predictions to the other data streams that inform your insights.
IBM and Watson IoT have the solutions for today’s energy and utility providers. That’s because data is the key to adapt to constant change. Visit our site to learn how to analyze your data better and predict performance and risk to deliver safe, reliable, affordable, and sustainable energy to your customers.
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On August 14, 2003, customers in Northeastern US and Canada experienced one of the worst blackouts on record affecting nearly 50 million people. In the U.S. alone, cost estimates ranged between $4 billion and $10 billion dollars. When the U.S.–Canada Power System Outage Task Force came back with the Final Blackout Report three years later, ...read more