IBM's SMT system uses weather patterns to collect massive data points a few weeks ago and predict how much solar and wind energy can be utilized. By predicting weather, technology can predict how much energy can be generated from solar and wind energy resources. IBM has invented a computer system that can learn the weather from massive amounts of data and predict how much energy from solar fields and wind farms can be used in the US energy network a few days or even weeks in advance. The new system is 30% more accurate than today's highest-level weather forecasting systems used by organizations such as the National Weather Service, according to data provided by the National Renewable Energy Laboratory. “It is providing forecasts of solar, wind and other environmental parameters. It is obtained from solar plants and weather stations and is constantly adapting and improving forecasts,†said Hendrik Hamann, research manager at the IBM TJ Washington Research Center. Because the system can better predict how much renewable energy is available, the country's energy grid can better fuse the power through traditional forms of energy. IBM's new computer algorithms, called autonomous learning weather models and renewable prediction techniques (thanks to SMT), use big data analytics and machine learning to improve solar forecasting systems. The system works by combining more than 1,600 meteorological monitoring stations, solar energy, wind energy plants on the continental United States, and more than 1T of data received from weather satellites. Easy Electronic Technology Co.,Ltd , https://www.pcelectronicgroup.com