Local bus frequency estimation using Gaussian belief propagation

Electric Power Systems Research, vol. 262, pp. 113586

Abstract

The increased penetration of inverter-based resources is reducing system inertia and challenging traditional frequency modeling approaches based on a single global frequency. Accurate estimation of local bus frequencies has therefore become essential for dynamic analysis and control. This paper proposes a near real-time bus frequency estimation framework that combines the analytical structure of the frequency divider (FD) formulation with the distributed inference capability of the Gaussian belief propagation (GBP) algorithm. By representing the power system as a factor graph, the proposed method enables iterative and fully distributed computation of bus frequencies without matrix inversion. The proposed algorithm enables estimation on a much smaller time scale than classical approaches, allowing faster detection of frequency deviations. Simulation studies on standard test systems demonstrate that the GBP framework achieves the same accuracy as the classical FD, while offering improved scalability and suitability for distributed implementation.

Authors 4

1. Armin Teskeredžić corresponding Aachen Institute for Automation of Complex Power Systems

   RWTH Aachen University

   Affiliation as printed

   Institute for Automation of Complex Power Systems, RWTH Aachen University, Aachen, Germany

2. Georgii Tishenin Aachen Institute for Automation of Complex Power Systems

   RWTH Aachen University

   Affiliation as printed

   Institute for Automation of Complex Power Systems, RWTH Aachen University, Aachen, Germany

3. Mirsad Ćosović

   University of Sarajevo · Istraživačko-razvojni institut za veštačku inteligenciju Srbije

   Affiliation as printed

   Faculty of Electrical Engineering, University of Sarajevo, Sarajevo, Bosnia and Herzegovina

   Institute for Artificial Intelligence Research and Development of Serbia, Novi Sad, Serbia

4. Antonello Monti Aachen Institute for Automation of Complex Power Systems

   Fraunhofer Institute for Applied Information Technology · RWTH Aachen University

   Affiliation as printed

   Fraunhofer FIT Center for Digital Energy, Aachen, Germany

   Institute for Automation of Complex Power Systems, RWTH Aachen University, Aachen, Germany