Renewable Energy Sources (RES) has grown remarkably in last few decades. Compared to conventional energy sources, renewable generation is more available, sustainable and environment-friendly - for example, there is no greenhouse gases emission during the energy generation. However, while electrical network stability requires production and consumption equality and the electricity market constrains producers to contract future production a priori and respect their furniture commitments or pay substantial penalties, RES are mainly uncontrollable and their behavior is difficult to forecast accurately. De facto, they jeopardize the stability of the physical network and renewable producers competitiveness in the market. The Winpower project aims to design realistic, robust and stable control strategies for offshore networks connecting to the main electricity system renewable sources and controllable storage devices owned by different autonomous actors. Each actor must embed its own local physical device control strategy but a global network management mechanism, jointly decided between connected actors, should be designed as well.We assume a market participation of the actors as an unique entity (the coalition of actors connected by the Winpower network) allowing the coalition to facilitate the network management through resources aggregation, renewable producers to take advantage of controllable sources flexibility to handle market penalties risks, as well as storage devices owners to leverage their resources on the market and/or with the management of renewable imbalances. This work tackles the market participation of the coalition as a Cooperative Virtual Power Plant. For this purpose, we describe a multi-agent architecture trough the definition of intelligent agents managing and operating actors resources and the description of these agents interactions; it allows the alliance of local constraints and objectives and the global network management objective.We formalize the aggregation and planning of resources utilization as a Markov Decision Process (MDP), a formal model suited for sequential decision making in uncertain environments. Its aim is to define the sequence of actions which maximize expected actual incomes of the market participation, while decisions over controllable resources have uncertain outcomes. However, market participation decision is prior to the actual operation when renewable generation still is uncertain. Thus, the Markov Decision Process is intractable as its state in each decision time-slot is not fully observable. To solve such a Partially Observable MDP (POMDP), we decompose it into a classical MDP and an information state (a probability distribution over renewable generation errors). The Information State MDP (IS-MDP) obtained is solved with an adaptation of the Backwards Induction, a classical MDP resolution algorithm.Then, we describe a common simulation framework to compare our proposed methodology to some other strategies, including the state of the art in renewable generation market participation. Simulations results validate the resources aggregation strategy and confirm that cooperation is beneficial to renewable producers and storage devices owners when they participate in electricity market. The proposed architecture is designed to allow the distribution of the decision making between the coalition’s actors, through the implementation of a suitable coordination mechanism. We propose some distribution methodologies, to this end.