Optimal generation in structure-preserving power networks with second-order turbine-governor dynamics

Recently we have been exploring the role of passivity and the internal model principle in power network control in the presence of uncertainties due to unmeasured demand and supply. In this work we continue this line of research and extend our results to include more complex dynamics at the generation side. Namely, we study frequency stabilization by primary control and frequency regulation by optimal generation control, where we additionally incorporate second-order turbine-governor dynamics. The power network is represented by the structure-preserving Bergen-Hill model [1]. Distributed controllers that require local frequency measurements are proposed and are shown to minimize the generation costs. Asymptotic convergence is proven when the generators satisfy a local matrix condition. The effectiveness of proposed controllers is demonstrated in a case study

Distributed Optimal Frequency Control Considering a Nonlinear Network-Preserving Model

This paper addresses the distributed optimal frequency control of power systems considering a network-preserving model with nonlinear power flows and excitation voltage dynamics. Salient features of the proposed distributed control strategy are fourfold: i) nonlinearity is considered to cope with large disturbances; ii) only a part of generators are controllable; iii) no load measurement is required; iv) communication connectivity is required only for the controllable generators. To this end, benefiting from the concept of 'virtual load demand', we first design the distributed controller for the controllable generators by leveraging the primal-dual decomposition technique. We then propose a method to estimate the virtual load demand of each controllable generator based on local frequencies. We derive incremental passivity conditions for the uncontrollable generators. Finally, we prove that the closed-loop system is asymptotically stable and its equilibrium attains the optimal solution to the associated economic dispatch problem. Simulations, including small and large-disturbance scenarios, are carried on the New England system, demonstrating the effectiveness of our design

Passivity-Based Design of Sliding Modes for Optimal Load Frequency Control

This paper proposes a distributed sliding mode (SM) control strategy for optimal load frequency control (OLFC) in power networks, where besides frequency regulation, minimization of generation costs is also achieved (economic dispatch). We study a nonlinear power network of interconnected (equivalent) generators, including voltage and second-order turbine-governor dynamics. The turbine-governor dynamics suggest the design of a sliding manifold such that the turbine-governor system enjoys a suitable passivity property, once the sliding manifold is attained. This paper offers a new perspective on OLFC by means of SM control, and in comparison with the existing literature, we relax required dissipation conditions on the generation side and assumptions on the system parameters

A distributed scheme for secondary frequency control with stability guarantees and optimal power allocation

We consider the problem of distributed secondary frequency regulation in power networks such that stability and an optimal power allocation are guaranteed. This is a problem that has been widely studied in the literature, where two main control schemes have been proposed, usually referred to as 'Primal-Dual' and 'distributed averaging proportional-integral (DAPI)' respectively. However, each has its limitations, with the former incorporating additional information flow requirements which may limit its applicability, and with the existing literature on the latter relying on static models for generation and demand, which is restrictive. We propose a novel control scheme that aims to overcome these issues by making use of generation measurements in the control policy. In particular, our controller relies on practical measurements and allows distributed stability and optimality guarantees to be deduced for a broad range of linear generation dynamics, that can be of higher order. We show how the controller parameters can be selected in a computationally efficient way by solving appropriate linear matrix inequalities (LMIs). Furthermore, we demonstrate how the proposed analysis applies to various examples of turbine governor dynamics by using realistic numerical data. The practicality of our analysis is demonstrated with numerical simulations on the Northeast Power Coordinating Council (NPCC) 140-bus system that verify that our proposed controller achieves convergence to the nominal frequency, an economically optimal power allocation, and improved performance compared to existing schemes used in the literature.ERC starting grant 67977