Optimal bidding and worst case pricing under dynamic integration mechanism for LQG power networks

We investigate an optimal bidding and an optimal and worst case pricing under a dynamic integration mechanism for linear quadratic Gaussian (LQG) power networks. The participant of the dynamic integration mechanism is divided into two kind of players, that are generators and/or consumers, called agents, and one public commission, called utility. In the mechanism, each agent decides private control to minimize his/her own cost functional, and the utility decides prices and incentives to minimize a public cost functional. The dynamic integration mechanism satisfies both public optimality by private optimal controls of each agent and incentive compatibility. In this setting, we present an optimal bidding strategy under the condition such that each agent selects his/her preference from a set of his/her preferences and reports his/her state truthfully. Based on the proposed optimal bidding strategy, each agent can select his/her optimal preference which minimizes his/her minimal private cost. In addition, we discuss optimal pricing and worst case pricing for the whole power networks.