IBM Forecasts To Help U-M In Solar Car Race

ANN ARBOR — In an era when solar power is being integrated into the nation’s energy grid, IBM is developing technology to help forecast solar power output.

Now, that technology is helping the University of Michigan power its solar car in the Bridgestone World Solar Challenge, an 1,800-mile (3,000-kilometer) race across the Australian Outback that begins Oct. 18.

The UM student team will use IBM Research’s computing expertise to gain real-time insights into conditions such as cloud cover and wind patterns, to help determine how much solar power will be available to fuel their car along the course race.

Since the car is solely powered by solar energy, more accurate forecasts can help the UM students decide how to drive their car more efficiently and improve their chances for winning.

IBM researchers are using machine learning to blend data from sensor networks and local weather stations, cloud motion physics derived from sky cameras and satellite observations, and multiple weather prediction models. IBM says that’s superior to most current forecasting techniques, which rely on individual weather models that offer a less comprehensive view of the variables that affect the availability of renewable energy such as solar.

IBM developed the technology through a program supported by the U.S. Department of Energy’s SunShot Initiative to find new ways to improve the accuracy of solar forecasts that can then be used to optimize solar grid resources. By using machine learning and other cognitive computing technologies, IBM scientists can generate solar and wind forecasts that are up to 30 percent more accurate than ones created using conventional approaches, whether minutes or days in advance.

“Our goal is to design, engineer, and race the best solar-powered vehicle in the world,” said Leda Daehler, chief strategist on the UM Solar Car Team. “Predicting solar radiation plays a huge part in designing a strategy for solar car racing. IBM’s forecasting technology will help our team adapt and optimize our approach in real-time, and we expect it to provide a true advantage over the course of the race.”

The UM Solar Car Team is one of the world’s most successful solar race teams, holding numerous championships. This year the team is confident that IBM’s solar forecasting technology will help them make better decisions in their racing strategy when their car, Aurum, competes over four days in the World Solar Challenge.

The team will use two kinds of forecasts provided by IBM’s solar forecasting technology.

One technique enables the students to obtain more accurate forecasts on the race route two or three days ahead. The technology continuously monitors weather conditions and analyzes the data to forecast how much solar energy will be available at different locations and times. It incorporates a large number of weather and solar prediction models, which it blends through machine learning to produce a supermodel. The system learns from a large amount of historical data as well as data gathered along the race course.

The second forecasting technique applies to near real-time conditions. In the World Solar Challenge, the UM Solar Car Team will have a sky camera mounted on the hood of two scout cars that run ahead of their car. The system developed by IBM plots the location and the transparency of clouds, so the team can decide the speed the car should go to get maximum solar energy. Simulations have shown that this technique could gain the team up to 15 minutes per day.

“The University of Michigan has been competing in solar car races for 25 years,” said Pavan Naik, program manager for the UM Solar Car Team. “In the past, we have not been able to capture and analyze the variety and amount of cloud data needed to confidently impact our race strategy. This year, IBM’s solar forecasting technology will allow us to know where the clouds are, where they are going, and where we should go faster in order to chase the sun.”

The collaboration with the UM Solar Car Team provides IBM scientists a unique environment to continue to develop their solar forecasting technology and to learn new techniques that can help improve forecasting accuracy. These advances are important to the future of alternative energy and every industry that is susceptible to the impact of weather on operations and how they conduct their business.

Said Dario Gil, vice president of science and technology at IBM Research: “We are using physical analytics to combine our understanding of the physical world with two of the most exciting fields in computer science – data analytics and machine learning — which will lead to new innovations that can transform industries.”

To learn more on how IBM helped the UM Solar Car Team prepare for the 2015 World Solar Challenge and to join them on their journey, visit http://ibm.co/solarforecasting and http://umicheng.in/solar25 for behind-the-scenes coverage and live updates from Australia.

Other American college teams in the global race include the Massachusetts Institute of Technology, Stanford, the University of Minnesota and Principia College of Elsah, Ill.

Since 1990, the UM Solar Car Team has been designing, building, and racing America’s best solar vehicles, with five consecutive national championships among eight overall, five top three world finishes and one international championship. This year, UM celebrates 25 yaers of solar car racing. For more information, visit http://www.solarcar.engin.umich.edu/.

This year’s Bridgestone World Solar Challenge is the event’s 13th crossing of Australia. Forty-six teams from 25 countries are striving to make the Darwin start line on Sunday Oct. 18, in their bid to deliver the world’s most efficient electric car. For more information, visit http://www.worldsolarchallenge.org.

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