Name
Title | ||
|---|---|---|
Clustering Based Online Identification Of Secondary Dynamic Parameters For Measurement Based Composite Load Modeling |
Abstract | ||
|---|---|---|
Accurate modeling and parameter identification of electrical load is always a difficult problem, remaining unsolved but critical for stability analysis, prediction and decision-making of power systems. The development of wide area measurement system (WAMS) provides possible way's to further address the challenge. In this work, based on an existing load modeling method for online identification of dominant parameters, we put forward an improvement with the clustering method, to get the reactance of the composite load model as a secondary dynamic parameter. Corresponding theoretical analysis, design principles and system implementation are presented. The reactive power damping time constant during disturbance is chosen as the clustering feature. Simulation results show effectiveness of our improvement with satisfactory accuracy. |
Year | Venue | Keywords |
|---|---|---|
2015 | 2015 IEEE POWER & ENERGY SOCIETY INNOVATIVE SMART GRID TECHNOLOGIES CONFERENCE (ISGT) | parameter identification, clustering, secondary dynamic parameters, WAMS, composite load modeling |
Field | DocType | Citations |
Reactance,Algorithm design,Electrical load,System of measurement,Control theory,Electric power system,Control engineering,AC power,Implementation,Engineering,Cluster analysis | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shuqing Zhang | 1 | 0 | 1.01 |
| Xiaofei Liu | 2 | 0 | 0.34 |
| Junwei Cao | 3 | 935 | 70.95 |
| Guoyu Tu | 4 | 0 | 0.34 |
| Yuxin Wan | 5 | 0 | 1.35 |