Reactive power optimization based on improved bacteria foraging optimization algorithm
- 10.2991/iccia-17.2017.36How to use a DOI?
- Reactive power optimization, bacteria foraging optimization algorithm, chaos theory, migration operation
Bacteria foraging optimization algorithm have the disadvantages of falling into optimal local optimum easily, and the speed of convergence become to decline obvious in later optimization, this paper established a mathematical model based on minimize the loss of the power network and maintain a good voltage level ,to solve the problem of reactive power optimization for electric power system. Proposed an improved bacteria foraging algorithm, combining the chaotic theory to initialize the basic population of bacteria, so as to improve their global search ability, and adjust the migration operation adaptively, optimizing the efficiency of late convergence, Finally, test on the IEEE -14 node power system, the result improved that the algorithm proposed in this paper has Faster convergence and higher accuracy in the process of the problem of reactive optimization
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Ying Aa AU - Yuanjie Gao AU - Hui Sun AU - Jiwei Zhu AU - Lizhi Cao PY - 2016/07 DA - 2016/07 TI - Reactive power optimization based on improved bacteria foraging optimization algorithm BT - Proceedings of the 2nd International Conference on Computer Engineering, Information Science & Application Technology (ICCIA 2017) PB - Atlantis Press SP - 217 EP - 221 SN - 2352-538X UR - https://doi.org/10.2991/iccia-17.2017.36 DO - 10.2991/iccia-17.2017.36 ID - Aa2016/07 ER -