Nonlinear model reduction of dynamical power grid models using\n quadratization and balanced truncation

2020/05/26 by Tobias Ritschel, Ritschel, Tobias K. S., Frances Weiß +5
Engineering · Mathematics · Physics and Astronomy · #93A15 #93B11 (Primary) #93B40 (Secondary) #93C10 #93C15 #93C95 #FOS: Electrical engineering #I.6.1 #I.6.3 #Model Reduction and Neural Networks #Numerical methods for differential equations #Power System Optimization and Stability #Systems and Control (eess.SY) #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2005.12658

openalex publication_date 2020/05/26 · openalex created_date 2022/07/26 · openalex updated_date 2026/07/28

Abstract

In this work, we present a nonlinear model reduction approach for reducing\ntwo commonly used nonlinear dynamical models of power grids: the effective\nnetwork (EN) model and the synchronous motor (SM) model. Such models are\nessential in real-time security assessments of power grids. However, as power\ngrids are often large-scale, it is necessary to reduce the models in order to\nutilize them in real-time. We reformulate the nonlinear power grid models as\nquadratic systems and reduce them using balanced truncation based on\napproximations of the reachability and observability Gramians. Finally, we\npresent examples involving numerical simulation of reduced EN and SM models of\nthe IEEE 57 bus and IEEE 118 bus systems.\n

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