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IBM 'Pulls All the Stops Out' on Wind and Solar Intermittency
Green Technology Featured Articles
August 13, 2013

IBM 'Pulls All the Stops Out' on Wind and Solar Intermittency

By Cheryl Kaften
TMCnet Contributor

Leave it to IBM (News - Alert) to come up with a quick fix for the “intermittency” issue that has impeded users of wind and solar generation to date.


On August 12, the Armonk, New York-based computer company announced a solution that combines weather prediction and analytics to accurately forecast the availability of wind power and solar energy.

The new platform—Hybrid Renewable Energy Forecasting (HyRef) — uses a combination of:

  • Weather modeling capabilities, advanced cloud imaging technology and sky-facing cameras to track cloud movements, and
  • Sensors on the turbines to monitor wind speed, temperature and direction.

When combined with analytics technology, the data-assimilation-based solution can produce accurate local weather forecasts within a wind farm as far as one month in advance, or in 15-minute increments. 

Infographic courtesy of IBM.

In addition, by accessing and using local weather forecasts, HyRef can predict the performance of each individual wind turbine on a property—and estimate the amount of renewable energy that an entire farm will generate overall. This level of insight will enable utilities to better manage the variable nature of wind and solar, and to more accurately forecast the amount of power that can be redirected into the power grid or stored. It also will enable energy distributors to easily integrate other conventional sources of power, such as coal and natural gas.

"Utilities around the world are employing a host of strategies to integrate new renewable energy resources into their operating systems in order to reach a baseline goal of a 25 percent renewable energy mix globally by 2025," commented Vice Admiral Dennis McGinn, president and CEO of the Washington, DC-based American Council On Renewable Energy (ACORE), adding, "The weather modeling and forecasting data generated from HyRef will significantly improve this process and in turn, put us one step closer to maximizing the full potential of renewable resources."

Users from China to Denmark

State Grid Jibei Electricity Power Company Limited (SG-JBEPC)—a subsidiary of the State Grid Corporation of China (SGCC)—already is using HyRef to integrate renewable energy into the grid. This initiative represents phase one of the Zhangbei 670MW demonstration project—the world's largest renewable energy initiative that combines wind and solar power, energy storage and transmission. This project contributes to China's Five-Year Plan to reduce its reliance on fossil fuels.

During phase one, the Zhangbei project aims to increase the integration of renewable power generation by 10 percent. This amount of additional energy can power roughly more than 14,000 homes. The efficient use of generated energy allows the utility to reduce wind and solar curtailment, while analytics provides the needed intelligence to enhance grid operations.

"Applying analytics and harnessing big data will allow utilities to tackle the intermittent nature of renewable energy and forecast power production from solar and wind, in a way that has never been done before," said Brad Gammons, general manager IBM's Global Energy and Utilities Industry division. "We have developed an intelligent system that combines weather and power forecasting to increase system availability and optimize power grid performance."

This project builds upon another IBM smarter analytics initiative at Randers, Denmark's Vestas Wind Systems, a manufacturer of wind power turbines. Vestas, together with IBM's big data analytics and supercomputing technology, is able to strategically place wind turbines based on petabytes of data from weather reporters, tidal phases, sensors, satellite images, deforestation maps, and weather modeling research. This insight can both deliver improvements in energy generation, and reduce maintenance and operational costs over the life of the project.





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