Dynamic reactive power optimization of distribution network with distributed generation based on fuzzy time clustering
In order to solve the coordinated optimization problem of distributed generation (DG), on‐load tap changer (OLTC) and capacitor banks, a dynamic reactive power optimization (DRPO) method based on fuzzy time clustering is proposed. In the method, fuzzy time clustering algorithm is used to cluster the...
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| Veröffentlicht in: | IET generation, transmission & distribution Jg. 16; H. 7; S. 1349 - 1363 |
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| Hauptverfasser: | , , , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
Wiley
01.04.2022
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| ISSN: | 1751-8687, 1751-8695 |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | In order to solve the coordinated optimization problem of distributed generation (DG), on‐load tap changer (OLTC) and capacitor banks, a dynamic reactive power optimization (DRPO) method based on fuzzy time clustering is proposed. In the method, fuzzy time clustering algorithm is used to cluster the static optimal switching sequence of OLTC and capacitor banks. The time decoupling of control variables is realized and it meets the constraints of the maximum switching times. Next, the influencing factors of DG reactive power limit are analysed. Considering the control ability of OLTC, capacitor banks and DG in voltage and reactive power optimization, a coordinated optimization method is proposed. Since the adjustment of OLTC tap position directly affects the voltage and reactive power distribution of the whole line, the switching time and tap position of OLTC are determined based on the static optimization results of each time and fuzzy time clustering algorithm. Then, the switching time of capacitor banks is determined by fuzzy time clustering algorithm. At last, the switching capacity of capacitor banks and DG reactive power are jointly optimized to get the final control scheme. The proposed method demonstrated good performance in the modified IEEE33 node system and two actual power grid examples. |
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| Bibliographie: | Funding information National Natural Science Foundation of China (51707176), the Scientific and Technological Research Project of Henan Province (212102210257), the Science and Technology Project of State Grid Henan Electric Power Company (5217I020000G), and the High School Key Research Program of Henan Province (20A470014) |
| ISSN: | 1751-8687 1751-8695 |
| DOI: | 10.1049/gtd2.12370 |