Name
Abstract | ||
|---|---|---|
The integration of renewables into electrical grids calls for novel control schemes, which usually are model based. Classically, for power systems parameter estimation and optimization-based control are often decoupled, which may lead to increased cost of system operation during the estimation procedures. The present work proposes a method for simultaneously minimizing grid operation cost and estimating line parameters. To this end, we rely on methods from optimal design of experiments. This approach leads to a substantial reduction in cost for optimal estimation and in higher accuracy in the parameters compared with standard combination of optimal power flow and maximum-likelihood estimation. We illustrate the performance of the proposed method on simple benchmark system. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.23919/ACC50511.2021.9482814 | 2021 AMERICAN CONTROL CONFERENCE (ACC) |
Keywords | DocType | ISSN |
Optimal Experiment Design, Power System Parameter Estimation, Admittance Estimation, Optimal Power Flow | Conference | 0743-1619 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xu Du | 1 | 37 | 15.92 |
| Alexander Engelmann | 2 | 1 | 3.74 |
| Timm Faulwasser | 3 | 194 | 27.39 |
| Boris Houska | 4 | 214 | 26.14 |