In 2013 we reported on an improved solar forecasting system under development by researchers from the U.S. National Centre for Atmospheric Research (NCAR).
Three years later, the team have unveiled their cutting-edge Sun4Cast technology; which has the potential to save the US solar industry hundreds of millions of dollars by improving predictions of clouds and other atmospheric conditions that adversely affect the output of solar panels.
Research behind the technology has been highlighted in more 20 peer-reviewed papers and the system put through comprehensive testing across states with widely varying weather conditions; including Long Island, New York; the Colorado mountains; and coastal California.
Apparently, Sun4Cast has proved to be 50 percent more accurate than the solar forecasting options currently available for utilities deploying solar power. Analysis by NCAR economist Jeffrey Lazo shows utilities across the United States could save roughly $455 million (AUD $596 million) as the use of solar grows.
“These results can help enable the nation’s expanding use of solar energy, said Sue Ellen Haupt, director of NCAR’s Weather Systems and Assessment Program, who led the research team. “More accurate predictions are vital for making solar energy more reliable and cost effective.”
In order to accurately predict solar irradiation levels, the Sun4Cast system relies on a vast array of observational tools, including satellite-and-sky imaging, weather radars, tailored computer software and artificial intelligence-driven mathematics. A key driver of the platform is a new atmospheric model that simulates solar irradiance based on meteorological conditions.
Dubbed WRF-Solar – from the NCAR-based Weather Research and Forecasting (WRF) computer model used by weather agencies around the world – it enables the Sun4Cast system to provide utilities with spot-on 0-6 hour “nowcasts” of solar levels as well as power outputs at specific solar power plants. Other forecasts available will extend out to 72 hours.
“We have to provide utilities with confidence that the system maintains a high degree of accuracy year-round in very different types of terrain,” said Branko Kosovic, NCAR Program Manager for Renewable Energy.
Xcel Energy has begun using the Sun4Cast system at several of its major solar power plants.
Closer to home, a significant solar project in Australia featuring another cutting-edge Cloud Predictive Technology (CPT) system is about to hit prime-time. The 1MW solar farm at Karratha Airport in Western Australia – an Energy Matters project – will soon be completed.
Top Right Image Credit: BigStock
