# Turbine location-aware multi-decadal wind power predictions for Germany using CMIP6

arXiv: https://arxiv.org/abs/2408.14889 · HTML: https://mlsanity.com/paper/2408.14889/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 56 references that are in the map.
- First posted on arXiv 27 Aug 2024.

## Builds on (most cited first, 5 of 5)

- [Tackling Climate Change with Machine Learning](https://mlsanity.com/paper/1906.05433/) (2019)
- [Physics-Informed Gaussian Process Regression Generalizes Linear PDE Solvers](https://mlsanity.com/paper/2212.12474/) (2022)
- [Deconditional Downscaling with Gaussian Processes](https://mlsanity.com/paper/2105.12909/) (2021)
- [A Collection and Categorization of Open-Source Wind and Wind Power Datasets](https://mlsanity.com/paper/2202.08524/) (2022)
- [Modeling Climate Change Impact on Wind Power Resources Using Adaptive Neuro-Fuzzy Inference System](https://mlsanity.com/paper/2001.04279/) (2020)

## Built on by (most cited first, 1 of 1)

- [Assessing the risk of future Dunkelflaute events for Germany using generative deep learning](https://mlsanity.com/paper/2509.24788/) (2025)

## Abstract (arXiv)

Climate change will impact wind and therefore wind power generation with largely unknown effect and magnitude. Climate models can provide insights and should be used for long-term power planning. In this work we use Gaussian processes to predict power output given wind speeds from a global climate model and compare the aggregated predictions to actual power generation. Analyzing past climate model data supports the use of CMIP6 climate model data for multi-decadal wind power predictions and highlights the importance of being location-aware. Our predictions up to 2050 reveal only minor changes in yearly wind power generation. We find that wind power projections of the two in-between climate scenarios SSP2-4.5 and SSP3-7.0 closely align with actual wind power generation between 2015 and 2023. Our analysis also reveals larger uncertainty associated with Germany's coastal areas in the North as compared to Germany's South, motivating wind power expansion in regions where future wind is likely more reliable. Overall, our results indicate that wind energy will likely remain a reliable energy source in the future.