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| Content Provider | IET Digital Library |
|---|---|
| Author | Liu, Xingjie Yan, Liang Liu, Yadong Zhao, Liquan Jie, Jinxing |
| Abstract | In order to obtain the parameters of excitation system accurately, and improve the accuracy and efficiency of parameter identification much further, an improved niche genetic algorithm was adopted, which can overcome local convergence of genetic algorithm by the fitness sharing mechanism that could increase population diversity. Moreover, the proposed algorithm could avoid the disadvantage of usual niche genetic algorithm that is difficult in determining the niches. By using the method of fuzzy clustering, niche groups can be created dynamically. In addition, regarding the problem that the partial parameters of excitation system cannot identify stably because of the relevance among these parameters, this study analysed the identifiability of excitation system model primarily, separated associated parameters into several parameter sets then. This type of relevance would be removed by assigning typical values to representative parameters, which belong to different sets. Identifiability analysis can not only avoid identifying parameters blindly, but also increase the credibility of the results. The test study shows that the proposed method can acquire accurate and reliable parameter values. |
| Starting Page | 1580 |
| Ending Page | 1584 |
| Page Count | 5 |
| Volume Number | 2019 |
| e-ISSN | 20513305 |
| Issue Number | Issue 16, Mar (2019) |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/joe/conferences/cn-adc-2018 |
| Alternate Webpage(s) | https://digital-library.theiet.org/content/journals/10.1049/joe.2018.8816 |
| Journal | The Journal of Engineering |
| Publisher | The Institution of Engineering and Technology |
| Publisher Date | 2018-10-23 |
| Access Restriction | Open |
| Rights License | Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) |
| Subject Keyword | Combinatorial Mathematics Convergence Excitation System Model Fitness Sharing Mechanism Fuzzy Clustering Fuzzy Set Theory Genetic Algorithm Identifiability Analysis Improved Niche Genetic Algorithm Based Parameter Identification Optimisation Technique Parameter Identifiability Partial Parameter Pattern Clustering Power System Economics Power System Identification Power System Managemen Power System Operation |
| Content Type | Text |
| Resource Type | Article |
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