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IBM's Smarter Energy Research Institute Looks to Give Power Utilities Better Storm Damage Prediction
Nov 14, 2012
Since Hurricane Sandy struck the eastern United States more than two weeks ago, Green & Clean has been examining possible energy solutions to mitigate power outages and thus business losses when extreme weather strikes the power grid. These include the use of fuel cells as well as the establishment of so-called distributed microgrids that run on wind, solar or biomass sources. Another solution is to make traditional grid operators smarter when facing an imminent catastrophe. For most of its storied history, IBM has been on the cutting edge of technology and business performance improvement. IBM believes that the brand-new Smarter Energy Research Institute can help utilities and local governments mitigate more effectively damage from catastrophic weather events, through new technologies. "We don't control nature, but there are so many things that companies and authorities can do to help prevent some of this devastation," says Brian Gaucher, an IBM manager and the technical coordinator of the Smarter Energy Research Institute. "What we're starting to see is that we have the ability to control and observe things you could never see before, and learning to manage those in a new way is what we're trying to do." The institute was launched three weeks ago -- coincidentally, just before Sandy hit the East Coast -- with its first three partners/clients: Canadian electric utility Hydro-Quebec, Netherlands power utility Alliander, and DTE Energy, the U.S.-based diversified energy company. The new IBM lab, Gaucher explains to Green & Clean, had been in the works for years, with IBM communicating with its roster of energy and utility clients on how to improve their smart energy operations. The idea of forming the institute was born as IBM looked to help clients with the "big-picture," in areas like feedback and control systems and energy generation, distribution and consumption. "There are a lot of tools to help you manage those areas, but there aren't a lot of ways to look at the whole package," Gaucher says. "We wanted to create an institute where we could provide the utilities with a multitude of solutions and try to solve problems on a grand scale, and share all that information with our clients and the world." The most timely part of the Smarter Energy Research Institute is certainly the idea of "creating a smarter energy enviroment," where Gaucher says the creation of "coupled-predictive models" could be used to prepare for, and then minimize, damaging superstorms that seem to be occurring with yearly regularity thus far this century. One area where the institute will continue to improve on is its weather forecasting computer, called Deep Thunder, which identifies on a micro level where the worst damage from a storm will occur. For example, Gaucher says, a micro-forecast might tell local utilities and officials that the winds in the northwestern part of an affected region are going to be much stronger, thereby allowing the local energy company to make better preparations (e.g., sending larger work crews) in advance of the storm. Deep Thunder can also give energy companies advance data on exactly when and where the storm will hit, allowing them to proactively determine the equipment they'll need to deal with storm damage. This kind of technology would certainly have helped the Long Island Power Association (LIPA), which has come under heavy scrutiny for its slow emergency response and antiquated equipment in the wake of Sandy. For example, Gaucher says that during Hurricane Irene, which caused massive flooding and damage in the Northeast in the summer of 2011, Deep Thunder was 91 percent accurate in predicting power outages. Deep Thunder is currently being used by some governments and utility companies. Gaucher identifies other areas of predictive modeling that the Smarter Energy Research Institute will be working on for utility clients, including:
- Asset management optimization: improving the allocation of capital and operational expenses in upgrades and maintenance
- Integration of renewable and distributed energy resources: meeting renewable integration and distributed energy resource regulatory targets while ensuring system stability
- Wide-area situational awareness (i.e., a continental scale view of the energy grid): detecting anomalies across the grid in real time to improve resiliency, reliability and energy quality
- Participatory network, referred to as "social energy": using a social engagement model to transform relationships with consumers. This involves consumers with smart meters sharing information with utilities, which may then be able to help them become more energy efficient.