Hybrid Interconnection of Iterative Bidding and Power Network Dynamics for Frequency Regulation and Optimal Dispatch

This paper considers a real-time electricity market involving an independent system operator (ISO) and a group of strategic generators. The ISO operates a market, where generators bid prices at which they are willing to provide power. The ISO makes power generation assignments with the goal of solving the economic dispatch problem and regulating the network frequency. We propose a multirate hybrid algorithm for bidding and market clearing that combines the discrete nature of iterative bidding with the continuous nature of the frequency evolution in the power network. We establish sufficient upper bounds on the interevent times that guarantee that the proposed algorithm asymptotically converges to an equilibrium corresponding to an efficient Nash equilibrium and zero frequency deviation. Our technical analysis builds on the characterization of the robustness properties of the continuous-time version of the bidding update process interconnected with the power network dynamics via the identification of a novel local input-to-state Lyapunov function. Simulations on the IEEE 14-bus system illustrate our results

Energy-based analysis and control of power networks and markets:Port-Hamiltonian modeling, optimality and game theory

This research studies the modeling, control and optimization of power networks. A unifying mathematical approach is proposed for the modeling of both the physical power network as well as market dynamics. For the physical system, several models of varying complexity describing the changes in frequency and voltages are adopted. For the electricity market, various dynamic pricing algorithms are proposed that ensure a optimal dispatch of power generation and demand (via flexible loads). Such pricing algorithms can be implemented in real-time and using only local information that is available in the network (such as the frequency). By appropriately coupling the physical dynamics with the pricing algorithms, stability of the combined physical-economical system is proven. This in particular shows how real-time dynamic pricing can be used as a control method to achieve frequency regulation and cost efficiency in the network