Approximations for optimal experimental design in power system parameter estimation

Publikationstyp
Conference Paper
Date Issued
2022-01-01
Sprache
English
Author(s)
Du, Xu
Engelmann, Alexander
Faulwasser, Timm  
Houska, Boris
TORE-URI
https://hdl.handle.net/11420/46013
Volume
2022-December
Start Page
5692
End Page
5697
Citation
61st IEEE Conference on Decision and Control (CDC 2022)
Contribution to Conference
IEEE 61st Conference on Decision and Control, CDC 2022  
Publisher DOI
10.1109/CDC51059.2022.9993237
Scopus ID
2-s2.0-85147041406
Publisher
IEEE
ISBN
9781665467612
This paper is about computationally tractable methods for power system parameter estimation and Optimal Experiment Design (OED). The main motivation of OED is to increase the accuracy of power system parameter estimates for a given number of batches. One issue in OED, however, is that solving the OED problem for larger power grids turns out to be computationally expensive and, in many cases, 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 benchmarked on a 5-bus and a 14-bus case study.
Subjects
Admittance Estimation
Optimal Experiment Design
Parameter Estimation
Power Systems
DDC Class
004: Computer Sciences
510: Mathematics