Cornell researchers have found a way to better measure the effect of wildfire smoke on solar panel performance, according to TechXplore.
By using historical data from events such as the Canadian wildfires of 2023, researchers have been able to train a new predictive model that can anticipate solar power output on an hourly basis. Previously, this kind of prediction only provided daily average values.
These projections are vital for ensuring utility operators can secure an electrical supply to meet demand. Energy use is climbing steadily, so these kinds of infrastructure tools are becoming increasingly important in managing the grid.
Solar panel technology is essential to transitioning away from polluting fossil fuel sources. Use of coal and gas power is exacerbating extreme weather patterns, which include a heightened frequency of wildfires. By switching to solar and managing it with better models like this one, we can also mitigate glacier melts, rising sea levels, and ocean warming and acidification.
If you're eager to help build a greener future and save a few bucks on your utility bills, EnergySage has a free online tool to connect you with vetted local solar installers who can give you a quote on a solar system that's a good fit for your home and needs. Best of all, they can help slash up to $10,000 on installation costs with the help of rebates and incentives.
Cornell researchers were ready to put their new predictive model to work.
"Everything reported in our paper is operational," said author Max Zhang, per TechXplore. "All the inputs we use in the model are forecast products. That's what power system operators need. And it can be used anywhere.
"This is just the start. We are improving the model while creating pathways for adoption by system operators. The better the forecast, the more reliable the power system."
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