- Tytuł:
- Reactive power convex optimization of active distribution network based on Improved GreyWolf Optimizer
- Autorzy:
-
Li, Yuancheng
Yang, Rongyan
Zhao, Xiaoyu - Powiązania:
- https://bibliotekanauki.pl/articles/140678.pdf
- Data publikacji:
- 2020
- Wydawca:
- Polska Akademia Nauk. Czytelnia Czasopism PAN
- Tematy:
-
active distribution network (ADN)
Improved Grey Wolf Optimizer (IGWO)
reactive power optimization
second-order cone relaxed convex model - Opis:
- The smart grid concept is predicated upon the pervasive With the construction and development of distribution automation, distributed power supply needs to be comprehensively considered in reactive power optimization as a supplement to reactive power. The traditional reactive power optimization of a distribution network cannot meet the requirements of an active distribution network (ADN), so the Improved Grey Wolf Optimizer (IGWO) is proposed to solve the reactive power optimization problem of the ADN, which can improve the convergence speed of the conventional GWO by changing the level of exploration and development. In addition, a weighted distance strategy is employed in the proposed IGWO to overcome the shortcomings of the conventional GWO. Aiming at the problem that reactive power optimization of an ADN is non-linear and non-convex optimization, a convex model of reactive power optimization of the ADN is proposed, and tested on IEEE33 nodes and IEEE69 nodes, which verifies the effectiveness of the proposed model. Finally, the experimental results verify that the proposed IGWO runs faster and converges more accurately than the GWO.
- Źródło:
-
Archives of Electrical Engineering; 2020, 69, 1; 117-131
1427-4221
2300-2506 - Pojawia się w:
- Archives of Electrical Engineering
- Dostawca treści:
- Biblioteka Nauki
Artykuł