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Open AccessArticle

An Improved Artificial Bee Colony Algorithm and Its Application to Multi-Objective Optimal Power Flow

by Xuanhu He *, Wei Wang, Jiuchun Jiang and Lijie Xu
National Active Distribution Network Technology Research Center (NANTEC), Beijing JiaoTong University, Beijing 100044, China
*
Author to whom correspondence should be addressed.
These authors contributed equally to this work.
Academic Editor: Frede Blaabjerg
Energies 2015, 8(4), 2412-2437; https://doi.org/10.3390/en8042412
Received: 13 November 2014 / Revised: 14 March 2015 / Accepted: 17 March 2015 / Published: 26 March 2015
Optimal power flow (OPF) objective functions involve minimization of the total fuel costs of generating units, minimization of atmospheric pollutant emissions, minimization of active power losses and minimization of voltage deviations. In this paper, a fuzzy multi-objective OPF model is established by the fuzzy membership functions and the fuzzy satisfaction-maximizing method. The improved artificial bee colony (IABC) algorithm is applied to solve the model. In the IABC algorithm, the mutation and crossover operations of a differential evolution algorithm are utilized to generate new solutions to improve exploitation capacity; tent chaos mapping is utilized to generate initial swarms, reference mutation solutions and the reference dimensions of crossover operations to improve swarm diversity. The proposed method is applied to multi-objective OPF problems in IEEE 30-bus, IEEE 57-bus and IEEE 300-bus test systems. The results are compared with those obtained by other algorithms, which demonstrates the effectiveness and superiority of the IABC algorithm, and how the optimal scheme obtained by the proposed model can make systems more economical and stable. View Full-Text
Keywords: optimal power flow; fuzzy satisfaction-maximizing method; artificial bee colony algorithm; differential evolution algorithm; tent chaos mapping optimal power flow; fuzzy satisfaction-maximizing method; artificial bee colony algorithm; differential evolution algorithm; tent chaos mapping
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He, X.; Wang, W.; Jiang, J.; Xu, L. An Improved Artificial Bee Colony Algorithm and Its Application to Multi-Objective Optimal Power Flow. Energies 2015, 8, 2412-2437.

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