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Numerical Weather Prediction and Artificial Neural Network Coupling for Wind Energy Forecast

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Downscaling of Historical Wind Fields over Switzerland Using Generative Adversarial Networks

Anthony Christopher Davison, Ophélia Mireille Anna Miralles

Near-surface wind is difficult to estimate using global numerical weather and climate models, because airflow is strongly modified by underlying topography, especially that of a country such as Switzerland. In this article, we use a statistical approach ba ...

2022

Background During the COVID-19 pandemic there has been a strong interest in forecasts of the short-term development of epidemiological indicators to inform decision makers. In this study we evaluate probabilistic real-time predictions of confirmed cases an ...

London2022

The complex winds of the Alps: an unseen asset for the energy transition

Jérôme François Sylvain Dujardin

Wind energy has played a major role in the development of our society since 5000 BC when the first sail boats traveled the Nile River. Wind technology continued to advance with the invention of wind-powered pumps and mills in China and the Middle East as e ...

EPFL2021

Accurate building electricity load forecasts play a major role in the energy transition, as they facilitate flexibility deployment, grid stability and overall reduce costs and CO2 emissions. This research leaverages forecasting and reconciliation of tempor ...

2021

Multi-Resolution Convolutional Neural Network for High-Resolution Downscaling of Wind Fields from Operational Weather Prediction Models in Complex Terrain

Jérôme François Sylvain Dujardin

Wind modelling in complex topography remains a challenging task because operational Numerical Weather Prediction (NWP) models have a spatial resolution that is too coarse to capture all the meaningful terrain-induced phenomena like channeling, blocking, sp ...

2020

Radial wind velocity retrieval from Doppler radar and lidar measurements using Deep Learning

Maëlle Romero Grass

A Pulse-Doppler Radar Wind Profiler (RWP) is an active remote sensing instrument used in meteorology whose output product is a 3D wind field. A new method to retrieve radial wind velocity from spectrograms using Convolutional Neural Networks is introduced. ...

2020

Medium-range numerical weather prediction (NWP) is crucial to human activities. Reliable weather forecasts allow better resource management and are essential for disaster preparation. Modern NWP models provide accurate medium-range forecasts, but they requ ...

2020

The increasing share of offshore wind energy traded at the spot market requires short term wind direction forecasts to determine wake losses and increased power fluctuations due to multiple wakes in certain wind directions. The information on potential pow ...

2019

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With rising levels of wind power penetration in global electricity production, the relevance of wind power prediction is growing. More accurate forecasts reduce the required total amount of energy reserve capacity needed to ensure grid reliability and the ...

2019

The incremental deployment of decentralized renewable energy sources in the distribution grid is triggering a paradigm change for the power sector. This shift from a centralized structure with big power plants to a decentralized scenario of distributed ene ...

EPFL2019