The quest for accurate and efficient Power forecasting keeps goes on as IBM announced its own proprietary “Hybrid Renewable Energy Forecasting” (HyRef) solution.
The solution as stated in IBM’s PR uses weather modeling capabilities, advanced cloud imaging technology and sky-facing cameras to track cloud movements, while 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 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 easily integrate other conventional sources such as coal and natural gas.
IBM HyRef joins other services which try to improve the renewable power forecasting quality in order to achieve better efficiency and profitability.
It would be interesting to learn what bench mark does the new Hybrid system sets compared to others, and what level of on-the-ground intervention and investment it requires.
The Hybrid solution is an interesting concept, combining real time measurements with big data analysis, and it falls in the middle between existing solutions, where the common forecasting solution is based on meteorological analysis combined with measurements on the ground and the approach Meteo-Logic is pushing which is based on big data only with no requirements for real time measures.