Eight recipients will share $12m as part of the US Department of Energy's Solar Forecasting 2 funding round, aimed at improving solar forecasting technology six hours in advance of real time, and 24-48 hours ahead. The projects will cover three key areas: evaluating and comparing the performance of solar irradiance and solar power forecasting models; developing improved tools to predict how much light will reach solar panels; and integrating solar forecasting technologies with grid operators’ energy management systems. “Today’s announcement is a major step forward for our nation’s solar industry,” said DOE Secretary Steven Chu.
Eight recipients will share $12m as part of the US Department of Energy's Solar Forecasting 2 funding round, aimed at improving solar forecasting technology six hours in advance of real time, and 24-48 hours ahead. The projects will cover three key areas: evaluating and comparing the performance of solar irradiance and solar power forecasting models; developing improved tools to predict how much light will reach solar panels; and integrating solar forecasting technologies with grid operators’ energy management systems. IBM's machine-learning Watt-Sun programme is among the projects.