Distributed optimal control of a network of virtual power plants with dynamic price mechanism

This paper addresses a distributed control problem faced by a network of virtual power plants (VPPs). The VPP can be represented as a distributed energy management system tasked to aggregate distributed generations (DGs), loads and storage facilities to operate as a unique power plants regardless of their locations. In this framework, the main decisions that need to be established by the VPP decision maker are: 1) to decide how to fulfill its related electric demand including bilateral contracts and 2) to bid in multi-level negotiation schemes to minimize (maximize) in a cooperative way the power bought (sold) from (to) other interconnected VPPs. The proposed approach is based on a team theory framework and on dynamic price mechanism, where all VPPs' agents cooperate on the accomplishment of a common goal which is function of the subsystem state and of some controls which are shared with other subsystems. A distributed control strategy is proposed, and that includes problems in which each agent is able to communicate with other agents. Agents of the VPPs compute the control inputs at discrete time steps based on the information available to them. An example is presented to show the practical use of the method.