In the Journal of Renewable and Sustainable Energy, by AIP Publishing, scientists at Colorado State University and the National Oceanic and Atmospheric Administration have determined that by increasing the accuracy of weather forecasts over the past decade, consumers have earned at least $ 384 million in energy savings during that time. The researchers based their predictions on NOAA’s High Resolution Rapid Refresh (HRRR) model, which provides continuous daily weather forecasts for the entire United States. Part of these predictions include wind speed and directional data, resources that they can use to measure how much power their turbines will generate.
Every few years, NOAA releases an updated version of the HRRR model and spends a year testing it while keeping the previous model in place. During that year of experimentation, NOAA researchers compared each model’s predictions with real-life scenarios to estimate how much each model had progressed over the previous one.”We’ve been able to compare these models, aside from that, and see if one model predicts better than another,” says author Martin Shields. “And what we see over time is that models are better at air forecasting, and that creates more savings for resource users.”
As expected, the new models worked better, but the team wanted to measure how much better they were. Every difference between the predicted wind speed and the estimated wind speed has a corresponding cost, ranging from unnecessary operating costs or the amount of additional electricity from the supermarket market.By looking at the differences in errors from each model, the researchers were able to set a dollar value for each developed model.During the breakthrough model in 2015 and 2017, the team calculated that if resources had used the new model instead of the old one, they would have saved millions, many of which would have been passed on to consumers.
“NOAA researchers have been struggling for a long time to put value into their predictions,” Shields said. “They know their models are getting better, they know people are using those in important economic decisions, but they find it difficult to determine the value of that.”Researchers plan to focus their attention on saving HRRR costs due to forecasts of cloud cover by solar energy.
Wind power takes up a large portion of the energy field, which comes with increasing reliability in the short-term windUtilities must be able to accurately predict wind patterns in time to determine how much extra power it should generate in others. sources. Bad predictions can cost the app a lot of money, and then those costs are passed on to consumers. Conversely, good forecasting can lead to significant savings for those same customers.
Source Journal Reference: Hwayoung Jeon, Brad Hartman, Harvey Cutler, Rebecca Hill, Yuchen Hu, Tao Lu, Martin Shields, David D. Turner. Estimating the economic impacts of improved wind speed forecasts in the United States electricity sector. Journal of Renewable and Sustainable Energy, 2022; 14 (3): 036101 DOI: 10.1063/5.0081905
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