Leveraging Seasonal Predictions to Anticipate Wind Energy Returns
Seasonal production forecasts are emerging as a helpful tool to anticipate wind energy fluctuations and improve planning. Our case study on Costa Rica’s 2024 wind drought illustrates how these forecasts can be turned into actionable insights, anticipating reduced power generation months in advance. Through the use of machine learning for model post-processing and the generation of confidence intervals, the forecast accurately predicted the significant wind production drop in the region six months ahead while providing a reliable measure of uncertainty. Ultimately, these results offer a realistic example of how long-range forecasting might benefit planning and resilience in wind energy operations.
By Yazmina Zurita Martel, R&D Data Scientist, Nebbo Weather, Spain
How Seasonal Forecasts Predict Wind Patterns
Seasonal forecasts help us prepare for future weather conditions up to seven months in advance. Unlike daily forecasts that help us decide whether we will need an umbrella tomorrow, seasonal forecasts take a step back to look at the bigger picture. They offer a glimpse of what the overall weather patterns might be like over an entire month, helping us understand general trends rather than specific day-to-day conditions.[1]
