A real-time control framework for smart power networks with star topology

Real-time price-based control is expected to play a key role in the operation of the future power network. Recently developed price-based control schemes, despite the fact that they are real-time, pay little attention to their interaction with the dynamics of the power network, focusing mainly on the solution of an appropriately formulated optimization problem. However, the coupling between the solution of the optimization problem and the dynamics of the network should not be ignored as this could result in instability with disastrous consequences. In this paper, we present a decentralized feedback architecture that considers the interaction between the dynamics of the power market and network, and implements real-time control for power networks with star topology. Motivated by optimization decomposition methods, we design a possible control scheme: we first formulate a constrained Optimal Power Flow (OPF) problem, then use a primal-dual decomposition approach to design a dynamic feedback controller for the power network and prove the asymptotic stability of the overall system in a scalable fashion. With the proposed controller, the operation of the network is completely decentralized that all decisions are made locally. Numerical investigations illustrate the performance of the controller.