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    Xcel Energy and NCAR power up renewable energy forecasts
  • 08May

    Xcel Energy and NCAR power up renewable energy forecasts

    MINNEAPOLIS, May 8, 2013 /PRNewswire via COMTEX/ -- Xcel Energy announced today an expanded agreement with the National Center for Atmospheric Research for sophisticated renewable energy forecasting. The agreement with the Boulder, Colo.-based center extends an existing relationship that has saved Xcel Energy's 3.4 million electricity customers in eight states millions of dollars.
    In the next two years, NCAR scientists and engineers will develop custom forecasting systems to enable Xcel Energy control centers in Minneapolis, Denver, Golden, Colo., and Amarillo, Tex., to anticipate sudden changes in wind, shut down turbines ahead of potentially damaging icing events and even predict the amount of energy generated by private solar panels.
    "Xcel Energy has been the nation's largest utility provider of wind energy for the last nine years, and as our renewable energy portfolio continues to grow, accurate forecasts become increasingly important," said Ben Fowke, chairman, president and CEO of Xcel Energy.
    The new project represents the latest venture by NCAR into renewable energy, which includes a three-year, nationwide project to create 36-hour forecasts of incoming energy from the sun for solar energy power plants.
    The systems will help Xcel Energy provide reliable power to its customers and reduce costs while moving to greater use of wind and solar. They come at a time when Xcel Energy is increasing its use of renewable energy in its territories served by Public Service Co. of Colorado, Northern States Power Co.-Minnesota, NSP-Wisconsin and Southwestern Public Service Co.
    "By creating more detailed and accurate forecasts of wind and sun, we can produce a major return on investment for utilities," said Thomas Bogdan, president of the University Corporation for Atmospheric Research, which manages NCAR on behalf of the National Science Foundation. "This type of cutting-edge research helps make renewable energy more cost competitive."
    To help utilities anticipate wind energy more reliably, NCAR began designing a wind energy prediction system for Xcel Energy in 2009 that saved the utility's customers more than $6 million in 2010 alone. The specialized system relies on a suite of tools, including highly detailed observations of atmospheric conditions, an ensemble of powerful computer models, and artificial intelligence techniques to issue high-resolution forecasts for wind farm sites.
    NCAR's new agreement with Xcel Energy focuses on the following areas:
    -- Forecasting major changes in wind energy over a few hours due to a passing front or another atmospheric event.
    -- Forecasting ice and extreme temperatures to predict the impacts of freezing rain on wind turbines, which cannot operate when coated in ice.
    -- Generating solar forecasts using a combination of computer models and specialized cloud observing tools to help Xcel Energy better anticipate when customers are getting power from their own panels.
    Some of these new systems will provide "probabilistic forecasts," estimating the chances that a particular weather event will occur. This means that utility managers will be able to make decisions based on whether there is an 80 percent chance of certain weather events at a wind farm the next day or a 20 percent chance.
    Ultimately, Xcel Energy will control the systems for ongoing operations.
    NCAR researchers plan to publish the results of these systems in peer-reviewed journals, enabling other utilities and forecast providers to learn about the technologies.
    Xcel Energy XEL -1.16% is a major U.S. electricity and natural gas company with regulated operations in eight Western and Midwestern states. Xcel Energy provides a comprehensive portfolio of energy-related products and services to 3.4 million electricity customers and 1.9 million natural gas customers through its regulated operating companies. Company headquarters are located in Minneapolis. More information is available at

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