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Application of improved bat algorithm in optimal power flow problem

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Abstract

This paper proposes an improved bat algorithm to solve multi-objective optimal power flow problem (MOPF) based on the weighted method. The MOPF problem is formulated as a non-linear constrained optimization problem where two objective functions (minimization of fuel cost and emission) and various constraints are considered. After having found the Pareto solutions with the improved bat algorithm, the fuzzy set theory is used to find the compromise solution. Finally, the IEEE 57-bus system is applied to verify the performance of the proposed method for the MOPF problem. The results are compared with those obtained by the state-of-the-art optimization algorithms reported in literature. The simulation results demonstrate the superiority of the proposed method for solving the MOPF problem in terms of solution quality.

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Acknowledgments

This work was supported by National Natural Science Foundation of China (No. 51379080, No. 41571514), the Fundamental Research Funds for the Central Universities (No. 2017KFYXJJ204) and Hubei Provincial Collaborative Innovation Center for New Energy Microgrid in China Three Gorges University (2015KJX09). Yanbin Yuan and Xiaotao Wu are the Co-first authors of this paper. These authors contributed equally to this work.

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Authors and Affiliations

  1. School of Resource and Environmental Engineering, Wuhan University of Technology, 430070, Wuhan, China

    Yanbin Yuan

  2. School of Hydropower and Information Engineering, Huazhong University of Science and Technology, 430074, Wuhan, China

    Xiaotao Wu, Pengtao Wang & Xiaohui Yuan

Authors
  1. Yanbin Yuan
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  2. Xiaotao Wu
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  3. Pengtao Wang
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  4. Xiaohui Yuan
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Correspondence to Xiaohui Yuan.

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Yuan, Y., Wu, X., Wang, P. et al. Application of improved bat algorithm in optimal power flow problem. Appl Intell 48, 2304–2314 (2018). https://doi.org/10.1007/s10489-017-1081-2

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