2022/08/30 by Nicolai Lorenz‐Meyer, Lorenz-Meyer, Nicolai, René Suchantke +3
Computer Science · Engineering · Mathematics · #Algorithm #Artificial intelligence #Bounded function #Computational Physics and Python Applications #Computer science #Control (management) #Control theory (sociology) #Electric power system #Estimation theory #FOS: Electrical engineering #Generator (circuit theory) #Mathematics #Noise (video) #Phasor #Phasor measurement unit #Power (physics) #Power System Optimization and Stability #Smart Grid and Power Systems #State (computer science) #Systems and Control (eess.SY) #Units of measurement #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2208.14511
openalex publication_date 2022/08/30 · openalex created_date 2022/09/02 · openalex updated_date 2026/07/28
Dynamic state and parameter estimation methods for dynamic security assessment in power systems are becoming increasingly important for system operators. Usually, the data used for this type of applications stems from phasor measurement units (PMUs) and is corrupted by noise. In general, the impact of the latter may significantly deteriorate the estimation performance. This motivates the present work, in which it is proven that the state and parameter estimation method proposed by part of the authors in [1] and extended in [2] features the property that the estimation errors are ultimately bounded in the presence of PMU measurement data corrupted by bounded noise. The analysis is conducted for the third-order flux-decay model of a synchronous generator and holds independently of the employed automatic voltage regulator and power system stabilizer (if present). The analysis is illustrated by simulations.