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.