Name
Abstract | ||
|---|---|---|
The problem of generator model calibration in power plants has been widely investigated. However, most of the methods relies on a nonlinear parameter estimation algorithm for curve fitting using single event data. Most of these estimation algorithms with curve fitting objective are sensitive to local minimum since the solution is non unique. To overcome these issues, a modified nonlinear least squares algorithm is first given to improve the search direction while calibrating with single event data. A sequential training approach is proposed to effectively utilize multiple disturbance event for model calibration in order to minimize the mismatch between the true and simulated system responses for all disturbance events. The proposed approaches were tested on Kundur's 2-area test system to verify the effectiveness of the proposed approaches. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/ISGT45199.2020.9087727 | 2020 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT) |
Keywords | DocType | ISSN |
Model Calibration,Model Validation,Syn-chrophasor,Nonlinear least Squares (NLS),Multiple Events | Conference | 2167-9665 |
ISBN | Citations | PageRank |
978-1-7281-3104-7 | 0 | 0.34 |
References | Authors | |
0 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kaveri Mahapatra | 1 | 3 | 1.42 |
| Honggang Wang | 2 | 0 | 0.34 |