Cooperative day-ahead bidding strategies for demand-side expected cost minimization

The envisioned smart grid aims to improve the interaction between the supply- and the demand-side of the electricity network, resulting in a great optimization potential. In this paper, we propose a holistic-based, distributed day-ahead demand-side management method that is suitable for energy markets subject to an external regulation. Here, active subscribers solve the nonconvex problem of deriving the bidding strategies that minimize their overall expected monetary expense and simultaneously optimize eventual dispatchable energy generation and storage strategies. We show that, when such users collaborate, they achieve greater saving with respect to the corresponding user-oriented, selfish optimization. In this setting, we propose a cooperative, distributed, and iterative algorithm providing the optimal bidding, production, and storage strategies of the users, along with its convergence properties.