Can wind power generation forecasts be forecasted at seasonal timescales?

While forecasts of wind power generation at lead times from minutes and hours to a few days ahead have been produced with very advanced methodologies (e.g. dynamical downscaling, machine learning or statistical downscaling [ 17 ]), a number of difficulties make the provision of generation forecasts at seasonal timescales challenging.

Why do we need seasonal wind energy forecasts?

Great Plains. Hence, these accurate seasonal wind energy forecasts hold the potential to yield significant benefits in optimizing the production, distribution, and allocation of wind energy resources, ultimately contributing to the enhancement of a sustainable and reliable energy supply.

What is the correlation between seasonal mean wind speed and wind power?

The simplest method, using the seasonal mean wind speed to forecast the seasonal mean wind power, has a correlation of 0.40, as shown in Fig. 7. The second method uses the seasonal mean of the cube of the instantaneous wind speeds.

Which season has the best wind energy and wind speed predictions?

Interestingly, spring exhibits the highest skill of wind energy and wind speed predictions concentrated over the southern Great Plains across all seasons with anomaly correlation coefficient (ACC) exceeding 0.7 at 1-month lead, while the model shows moderate skill with significant ACC around 0.4–0.6 over the western Great Plains during winter.

Why is seasonal wind energy utilization a key challenge?

A key challenge with the wind energy utilization is that winds, and thus wind power, are highly variable on seasonal to interannual timescales because of atmospheric variability. There is a growing need of skillful seasonal wind energy prediction for energy system planning and operation.

Can a seasonal wind energy prediction predict peak energy production seasons?

In the Southern Great Plains, the model can predict strong year-to-year wind energy changes with high skill multiple months in advance. Thus, this seasonal wind energy prediction capability offers potential benefits for optimizing wind energy utilization during peak energy production seasons.