Section: New Results

Objective 3 – Non-paramatric statistics

Production forecast errors are the main hurdle to integrate variable renewable energies into electrical power systems. Regardless of the technique, these errors are inherent in the forecast exercise, although their magnitude significantly vary depending on the method and the horizon. As power systems have to balance out these errors, their dynamic and stochastic modeling is valuable for the real time operation. The study in [23] proposes a Markov Switching Auto Regressive – MS-AR – approach. After having validated its statistical relevance, this model is used to solve the problem of the optimal management of a storage associated with a wind power plant when this virtual power plant must respect a production commitment.