Cognitive Computing

Girding the Grid with Cognitive Computing

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The electrical grid has become a network of billions of linked devices with highly complex energy and information flows. Add to this the elevated role of the consumer as a producer and you are looking at a massive volume, velocity and variety of data from smart meters, transformers, and substations that remains largely untapped.

One extremely interesting solution to the impending challenges is cognitive computing, which is gaining traction among industry experts as a way to better manage data and improve both operating efficiencies and customer service. According to GTM Research, applying cognitive computing is expected to deliver an estimated $121 billion global ROI on grid analytics by 2020.

There are three key areas where energy companies are already engaging with cognitive systems to experience real benefits. The first area allows companies to leverage the knowledge stored within the collective of enterprise information systems into a cohesive platform to provide insights to virtually any question or scenario. The second provides direct advice to customers through digital channels, learning over time in order to provide better end user customer service. And finally, with expanded services customers can easily monitor and control their monthly utilities consumption, to reduce costs and increase efficiency.

For example, Électricité de France S.A. (EDF), a leading energy company in France and one of the world’s largest generators of electricity, is running a pilot with a cognitive solution based on IBM Watson technology and services to test the operations and the benefits. This first experiment started in 2016 in support of its internal IT helpdesk. This year EDF is launching a taskforce around the cognitive computing strategy for the whole organization.

Between 2003 and 2012, grid outages cost the US economy $18B by conservative estimates. However, with cognitive computing utility companies realize substantial improvements is restoration response time from advanced forecasting. Combining predictive equipment maintenance, more accurate outage predictions and the application of more advance weather analytics, allows energy companies to ensure optimal uptime for the grid and reduce maintenance and service costs.

Cognitive visualization tools and image analytics are driving new solutions to detect risks, spark innovation and solve difficult problems especially in operation areas. Being able to pull actionable insights from smart meters and IOT devices, enables utility companies to better understand usage and demand, and also enables customers to easily monitor and control their monthly energy consumption particularly during peak demand. IBM client OmniEarth use aerial imagery to help water districts identify properties that use more water than necessary and help owners adjust usage.

Additionally, cognitive is having a big impact on customer service. For instance, using cognitive digital assistants or virtual agents improves productivity, agility, speed and understanding. Chatbots can generate personalized contextual recommendations and to interact naturally and contextually with customers to improve customer satisfaction and lower service costs.

This week IBM is at DistribuTECH 2017 at the San Diego Convention Center in San Diego, California to demonstrate how to leverage the power of cognitive, cloud and digital technologies to improve operational efficiency, increase customer satisfaction and reduce costs.

Vice President, IBM Energy & Utilities

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