Granular Weather Forecasting Permits More Renewable Energy on Grid
IBM has created a modeling technology that combines weather prediction and analytics to forecast the availability of wind power and solar energy to enable utilities to integrate more renewable energy into the power grid.
IBM’s Hybrid Renewable Energy Forecasting (HyRef) uses weather modeling capabilities and cloud imaging technology. For wind energy, HyRef also uses sky-facing cameras to track cloud movements, while sensors on wind turbines monitor wind speed, temperature and direction. When combined with analytics technology, the data-assimilation based software can produce accurate local weather forecasts within a wind farm as far as one month in advance, or in 15-minute increments.
By utilizing local weather forecasts, HyRef can predict the performance of each individual wind turbine and estimate the amount of generated renewable energy. This level of insight will enable utilities to better manage the variable nature of wind and solar, and more accurately forecast the amount of power that can be redirected into the power grid or stored. It will also allow energy organizations to more easily integrate other conventional sources such as coal and natural gas.
State Grid Jibei Electricity Power Company Limited (SG-JBEPC), a subsidiary company of the State Grid Corporation of China is using HyRef to integrate renewable energy into the grid. This initiative led by SG-JBEPC is phase one of the Zhangbei 670 MW demonstration project, the world’s largest renewable energy initiative that combines wind and solar power, energy storage and transmission. The project contributes to China’s 5-year plan to reduce its reliance on fossil fuels. By using the IBM wind forecasting technology, phase one of the Zhangbei project aims to increase the integration of renewable power generation by 10 percent.
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