Name
Abstract | ||
|---|---|---|
Fine operating rules for security control and an automatic system for their online discovery were developed to adapt to the development of smart grids. The automatic system uses the real-time system state to determine critical flowgates, and then a continuation power flow-based security analysis is used to compute the initial transfer capability of critical flowgates. Next, the system applies the Monte Carlo simulations to expected short-term operating condition changes, feature selection, and a linear least squares fitting of the fine operating rules. The proposed system was validated both on an academic test system and on a provincial power system in China. The results indicated that the derived rules provide accuracy and good interpretability and are suitable for real-time power system security control. The use of high-performance computing systems enables these fine operating rules to be refreshed online every 15 min. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/TNNLS.2015.2390621 | IEEE Trans. Neural Netw. Learning Syst. |
Keywords | Field | DocType |
total transfer capability.,online security analysis,automatic learning,smart grid,knowledge discovery,critical flowgate | Interpretability,Security controls,Feature selection,Smart grid,Computer science,Electric power system,Electric power transmission,Real-time computing,Security analysis,Artificial intelligence,Linear least squares,Machine learning | Journal |
Volume | Issue | ISSN |
PP | 99 | 2162-2388 |
Citations | PageRank | References |
3 | 0.53 | 4 |
Authors | ||
8 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hongbin Sun | 1 | 285 | 51.80 |
| Feng Zhao | 2 | 6 | 1.30 |
| Hao Wang | 3 | 3 | 0.87 |
| Kang Wang | 4 | 3 | 0.53 |
| Weiyong Jiang | 5 | 3 | 0.53 |
| Qinglai Guo | 6 | 52 | 13.42 |
| Boming Zhang | 7 | 72 | 11.82 |
| Louis Wehenkel | 8 | 1497 | 99.37 |