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IBM’s Hybrid Renewable Energy Forecasting Integrates Weather Data into Power Projects

Paul Nastu

Hybrid Renewable Energy ForecastingIBM has released an advanced power and weather modeling technology that will help utilities increase the reliability of renewable energy resources. The system combines weather prediction and analytics to accurately forecast the availability of wind power and solar energy.

The “Hybrid Renewable Energy Forecasting” is expected to enable utilities to integrate more renewable energy into the power grid.

The system uses weather modeling capabilities, advanced cloud imaging technology and sky-facing cameras to track cloud movements. Sensors on the turbines 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.

By using local weather forecasts, HyRef can predict the performance of each individual wind turbine and estimate the amount of generated renewable energy, IBM said.

In practice, China’s State Grid Jibei Electricity Power Company Limited (SG-JBEPC), uses HyRef to integrate renewable energy into the grid in 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. With the IBM wind forecasting technology, this phase of the project aims to increase the integration of renewable power generation by 10 percent, IBM said.



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