An increasingly large share of the energy landscape has been occupied by wind energy, which comes with a growing reliance on the intermittent nature of wind.
Image Credit: Shutterstock.com/ Oleksii Sidorov
Utilities should have the potential to anticipate wind patterns precisely and far in advance to identify how much extra energy they must generate from other sources. A bad prediction could cost the utility huge amounts of money. Also, those costs are then passed on to consumers, thus, on the contrary, a good prediction could lead to considerable savings for those same customers.
Researchers from Colorado State University and the National Oceanic and Atmospheric Administration identified that by increasing the precision of weather forecasts over the past 10 years, consumers netted a minimum of $384 million in energy savings during that time.
The study has been reported in the Journal of Renewable and Sustainable Energy, by AIP Publishing.
The researchers relied on their predictions on NOAA’s High-Resolution Rapid Refresh (HRRR) model. This offers daily weather forecasts for each part of the United States. Part of these predictions include wind speed and direction data, which utilities can apply to gauge how much energy will be produced by their turbines.
Once every few years, NOAA liberates an updated version of the HRRR model and spends around a year testing it out while retaining the earlier model in place. At the time of that testing year, NOAA scientists make a comparison of each model’s forecasts to real conditions to quantify just how much every model improved over its predecessor.
We were able to compare these models, side by side, and see when one model makes a better prediction than the other. And what we see over time is that the models get better at predicting wind, and that generates additional savings for utility consumers.
Martin Shields, Study Author, Colorado State University
As anticipated, better performance was shown by the newer models. However, the team wished to measure just how much better. Every variation between an anticipated wind speed and a quantified wind speed consists of a cost associated with it, regardless of the operational charges or the price of additional electricity from the wholesale market.
By looking at the variation in errors from every model, the scientists were able to put a dollar amount on every upgraded model.
At the time of the overlap model period in 2015 and again in 2017, the team assessed that if utilities had been making use of the newer model rather than the older one, they would have saved millions, the majority of which would have been passed on to consumers.
The researchers at NOAA have been struggling for a long time to put a value on their forecast. They know their models are getting better, they know that people use those in important economic decisions, but they have a hard time quantifying exactly what the value of that is.
Martin Shields, Study Author, Colorado State University
The scientists plan to divert their attention to HRRR’s cost savings as a result of cloud cover predictions on solar power.
Journal Reference:
Jeon, H., et al. (2022) Estimating the economic impacts of improved wind speed forecasts in the United States electricity sector. Journal of Renewable and Sustainable Energy. doi.org/10.1063/5.0081905.