Skip to Main content Skip to Navigation
Conference papers

Improving Wind Power Forecasting through Cooperation: A Case-Study on Operating Farms

Abstract : Concerns about climate change have never been so strong at the global level. One of the major challenges of the energy transition is dealing with the variability of renewable energies. Providing accurate production forecasts has become an important issue for the future, notably for wind energy. This paper proposes a method for wind power forecasting that focuses on interactions between neigh- boring wind turbines. The model is a multi-agent system based on a cooperative approach to improve an initial forecast. This work was carried out jointly with meteo*swift, a company specialized in wind power forecasting. The model was evaluated under real conditions on fi ve wind farms currently operated by power producers. An improvement in forecast accuracy was observed compared to the model initially used by the company.
Complete list of metadata

Cited literature [16 references]  Display  Hide  Download
Contributor : Open Archive Toulouse Archive Ouverte (oatao) <>
Submitted on : Friday, February 28, 2020 - 2:35:37 PM
Last modification on : Thursday, March 18, 2021 - 2:22:02 PM
Long-term archiving on: : Friday, May 29, 2020 - 2:40:42 PM


Files produced by the author(s)


  • HAL Id : hal-02494146, version 1
  • OATAO : 24844


Tanguy Esteoule, Carole Bernon, Marie-Pierre Gleizes, Morgane Barthod. Improving Wind Power Forecasting through Cooperation: A Case-Study on Operating Farms. 8th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2019), May 2019, Montréal, Canada. pp.1940-942. ⟨hal-02494146⟩



Record views


Files downloads