A real-time control framework for smart power networks: Design methodology and stability

Demand response is being actively considered as a useful mechanism for balancing supply and demand in the future power network. Relevant research to date has paid little attention to the interaction of this mechanism with the dynamics of the power network, focusing mainly on solving an appropriately formulated optimization problem. However, the coupling between the two should not be ignored due to fluctuations resulting from increased distributed energy resources and variability in both supply and demand. In this paper, we present a distributed control architecture that implements real-time economic optimization for the power network under exogenous disturbances. In particular, we consider a transmission level network with tree topology. Motivated by optimization decomposition methods, we first formulate a constrained Optimal Power Flow (OPF) problem and then use a primal–dual decomposition approach to design a dynamic feedback controller. We prove the asymptotic stability of the equilibria of the overall system. Numerical investigations illustrate that the proposed controller balances power flow in the network quickly, and achieves OPF in the steady state, even in the face of disturbances and contingencies.