If there were improvements in wind and sun forecasts, green energy could get a new lease on life.
Improving renewable energy forecasting by 10 to 20 percent could result in a savings of between $140 million to $975 million.
Better sensors to monitor solar radiation and atmospheric conditions that generate wind are needed.
Better satellite imaging can also help, as well as better sensing technology, such as solar imagers and cup anenometers (wind).
One of the biggest strikes against renewable energy is its unpredictability.
The vagaries of wind and sunshine makes it tough for utilities to plan when these forms of green power will be available to customers on the electric grid, so they often need to have a backup power source ready to burn, usually a more polluting coal- or gas-fired fossil fuel plant.
"The wind is variable, the sun doesn't shine all the time," said Phil Larochelle, a researcher at the Department of Energy's Advanced Research Projects Agency - Energy (ARPA-E).
But Larochelle and a growing number of scientists say they may have the answer. What if you could improve forecasts of both the wind and sun not just hours but days ahead of time? This sun-cast or wind-cast would introduce stability and reliability to the nation's energy grid and maybe give renewables a new and more competitive lease on life.
Current forecasts are problematic, explained Larochelle at ARAP-E's recent technology summit in Washington, DC, and errors can be anywhere from 3 to 30 percent.
"Bad forecasting leads to firing up a gas plant to pick up the slack," Larochelle said. "When the wind does come, you can't ramp down the coal, gas or nuclear fast enough. This is what we are seeing in Texas and in Europe."
Improving renewable energy forecasting by 10 to 20 percent could result in between $140 million to $975 million in utility savings annually. But ARPA-e officials want to challenge inventors, software engineers and scientists to figure out a way to boost existing forecasting by up to 40 percent.
They want better sensors to monitor solar radiation and atmospheric conditions that generate wind. They also want better computer models to crunch the tons of observational data once it's collected. These models then have to be turned into customized, local forecasts for power producers.
"Right now there's a growing demand for solar forecasting," said Manajit Sengupta, senior scientist at the National Renewable Energy Laboratory in Golden, Colo. Current weather forecasts are being used to generate solar forecasts, but the errors are high. "We can bring them down," Sengupta said.
The biggest errors come from benign situations, such as totally clear skies versus fluffy clouds, the fair weather cumulus that dot the sky on a sunny day.
Better satellite imaging can help, as well as better sensing technology, such as solar imagers and cup anenometers (wind).
The Wind Forecasting Improvement Project has set up 125 towers with a suite of sensors from 90 to 250 feet tall (the height of wind turbines) around a five-state area of the Northern Great Plains, and a large area of West Texas. The project is a partnership with DOE, the National Oceanic and Atmospheric Administration and several private firms.
Project manager Kirsten Orwig says the goal of the DOE/NOAA wind project is to boost both the science and economics of wind forecasts. That will lead to better solar power projections as well.
"The wind and sun are connected," Orwig said.