Solar Energy Forecasts Could Boost Industry Outlook

Intermittency may be the Achilles Heel of solar energy. Since the Sun doesn’t always shine and utility-scale energy storage isn’t available yet, grid operators have to rely on dispatchable generation like natural gas or coal when clouds cover up solar farms. But that may be about to change in a big way.

Solar panel with clouds image via Shutterstock

The National Center for Atmospheric Research (NCAR) has launched an ambitious three-year national project to create 36-hour solar energy forecasts. Research from government and university laboratories will be provided to utilities, grid operators, and commercial forecasters across the country.

NCAR’s prototype system will forecast sunlight and predict power every 15 minutes, giving utilities unprecedented ability to accurately plan the amount of solar power they will be able to generate across their system to meet customer demand. The system is primarily funded by a $4.1 million grant from the US Energy Department.

Since the Sun always shines, the project’s focus will be on creating detailed predictions of cloud cover and atmospheric particles that deflect incoming solar energy and affect the ability of solar panels to convert sunlight into electricity.

“It’s critical for utility managers to know how much sunlight will be reaching solar energy plants,” said Sue Ellen Haupt, lead researcher on NCAR’s solar project. “These detailed cloud and irradiance forecasts are a vital step.”

Cloud Cover’s Complicated Calculations

Predicting the weather has been a challenge for as long as humans have existed, but estimating cloud cover over specific areas may be the toughest aspect of the equation. Clouds are formed by tiny drops of water and are affected by many factors like wind, humidity, surface temperatures, geography, and airborne pollutants.

Compounding the challenge for solar forecasting, different types of clouds affect solar panel efficiency in different ways. For instance, high-altitude wispy clouds let much more sunlight hit the ground than low-altitude thick clouds.

NCAR will use a wide array of observational tools to forecast conditions, including laser-based lidar for atmospheric measurements, computer modeling, artificial intelligence, and three “total sky imagers” to triangulate cloud height and depth.

The system will be tested across the country, in vastly different geographic regions like the Northeast, Florida, Colorado, New Mexico, and California to ensure it can be applied nationwide.

Past Results Suggest Success

Even though NCAR’s system may leave some skeptics wondering if it will work, past performance indicates a sunny outlook. NCAR developed a wind forecasting system for Xcel Energy in 2011 that has increased forecast efficiency 35% and saved ratepayers $6 million dollars in just one year at wind farms across several Midwest and Mountain West states.

NCAR research has also boosted the ability of researchers to predict multiple climate change effects. Their Community Earth System Model (CESM) was developed for the UN’s Intergovernmental Panel on Climate Change (IPCC) to accurately predict changes in severe weather, ocean patterns, and ice sheet melting.

So cheer up, solar industry. Now that NCAR’s on the case, the forecast for solar energy as a stable baseload power source has just gotten a whole lot brighter.