Impacts of GSL Research - Wind Forecasts and Energy Savings
How NOAA's Rapid Refresh wind forecasts result in $150 million in energy savings each year and pave the way for other renewables
There are over 70,000 wind farms in the United States. These farms, scattered from the east to west coast, contribute substantially to the country's efforts to use clean and renewable energy. The average single wind turbine generates 843,000 kWh each month , which is enough energy for more than 940 homes. There are on average 150 turbines per farm, meaning one farm can power over 140,000 homes.
Map of the top wind farms in the United States with an installed capacity greater than 500 Megawatts. Wind farms labeled green have an installed capacity greater than 1000 MW, those in yellow have capacities of 700 - 999 MW, those in orange have capacities of 500 - 699 MW.
NOAA GSL's High Resolution Rapid Refresh offers accurate forecasts that save consumers money and sets the path for fortifying prediction services for other renewables.
Consumer Savings
Wind forecasts play a crucial role in how utility managers gauge the amount of energy that will be produced on wind farms. The forecasts are used to determine when it is necessary to generate or purchase energy from other sources besides wind. This has a major impact on consumer costs: forecasts that overpredict wind lead to unnecessary purchasing of energy, while those that under-predict wind lead to the burning of fossil fuels in order to compensate for the disparity. As a result, poor predictions lead to increased costs for the utility. These costs are effectively passed down to consumers, increasing their financial burden.
A decision tree showing how utility decisions are made based off of wind predictions and the implications of the decisions.
The relationship between forecasts and costs has been known for some time, but a recent study from NOAA GSL and Colorado State University actually quantified the impact . The study found that the NOAA GSL-developed High Resolution Rapid Refresh (HRRR) wind forecasts resulted in $150 million in energy savings each year.
The HRRR is an hourly-updating atmospheric model which predicts weather on a 3-km grid. It can predict wind speed and direction at 50 different levels of the atmosphere, among other weather elements.
An example of HRRR wind forecasts from January 2022
The study examined changes in costs associated with the accuracy of forecasts. From 2014 to 2020, GSL transitioned upgraded versions of the HRRR into operations every two years. To assess cost savings, the study compared older versions of GSL's HRRR with newer versions to see how cost varied with changes in accuracy. When compared by side-by-side, researchers could identify instances in which one model performed better than the other. The study then assigned cost to every deviation in predicted versus measured winds, so that each model had an associated dollar amount with it.
From HRRR1 to HRRR2 in 2015 and HRRR2 to HRRR3 in 2017, using a newer HRRR version would have saved consumers $384 million dollars. This comes to nearly $150 million dollars in consumer savings each year.
As we rely more on renewable energy and wind farms become more common, accurate forecasts are key in maximizing efficiency and minimizing costs.
Moving forward with other renewables
The research also has the potential to yield savings in solar energy. Using similar frameworks and technologies, researchers are investigating how accurate cloud cover forecasts could yield similar savings with solar energy. The next generation of high resolution models are expected to be able to better predict wind ramps - when wind speeds change rapidly. This would make models even more accurate, further increasing savings for customers.
