vix.ing · top · new · best · stats · spec

Approximations for Optimal Experimental Design in Power System Parameter Estimation

2022/03/26 by Xu Du, Alexander Engelmann, Du, Xu +5
Engineering · Physics and Astronomy · #Control Systems and Identification #FOS: Electrical engineering #Model Reduction and Neural Networks #Real-time simulation and control systems #Systems and Control (eess.SY) #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2203.14011

openalex publication_date 2022/03/26 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

This paper is about computationally tractable methods for power system parameter estimation and Optimal Experiment Design (OED). Here, the main motivation is that OED has the potential to significantly increase the accuracy of power system parameter estimates, for example, if only a few batches of data are available. The problem is, however, that solving the exact OED problem for larger power grids turns out to be computationally expensive and, in many cases, even computationally intractable. Therefore, the present paper proposes three numerical approximation techniques, which increase the computational tractability of OED for power systems. These approximation techniques are bench-marked on a 5-bus and a 14-bus case studies.

Related