Robust Decentralized Secondary Frequency Control in Power Systems: Merits and Trade-Offs

Weitenberg, Erik; Jiang, Yan; Zhao, Changhong; Mallada, Enrique; De Persis, Claudio; Dorfler, Florian

doi:10.1109/TAC.2018.2884650

Title: Robust Decentralized Secondary Frequency Control in Power Systems: Merits and Trade-Offs

Journal Article · Mon Jan 01 00:00:00 EST 2018 · IEEE Transactions on Automatic Control

DOI:https://doi.org/10.1109/TAC.2018.2884650· OSTI ID:1485772

Weitenberg, Erik ^[1]; Jiang, Yan ^[2]; Zhao, Changhong ^[3]; Mallada, Enrique ^[4]; De Persis, Claudio ^[1]; Dorfler, Florian ^[5]

Univ. of Groningen, Groningen (Netherlands)
Johns Hopkins Univ., Baltimore, MD (United States). Dept. of Electrical and Computer Engineering
National Renewable Energy Lab. (NREL), Golden, CO (United States). Power Systems Engineering Center
Johns Hopkins Univ., Baltimore, MD (United States). Electrical and Computer Engineering
Federal Inst. of Technology, Zurich (Switzerland). Electrical Engineering and Information Technology

Frequency restoration in power systems is conven- tionally performed by broadcasting a centralized signal to local controllers. As a result of the energy transition, technological advances, and the scientific interest in distributed control and optimization methods, a plethora of distributed frequency control strategies have been proposed recently that rely on communication amongst local controllers. In this paper we propose a fully decentralized leaky integral controller for frequency restoration that is derived from a classic lag element. We study steady-state, asymptotic optimality, nominal stability, input-to-state stability, noise rejection, transient performance, and robustness properties of this controller in closed loop with a nonlinear and multivariable power system model. Here, we demonstrate that the leaky integral controller can strike an acceptable trade-off between performance and robustness as well as between asymptotic disturbance rejection and transient convergence rate by tuning its DC gain and time constant. We compare our findings to conventional decentralized integral control and distributed- averaging-based integral control in theory and simulations.

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