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A solution network based on stud krill herd algorithm for optimal power flow problems

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Abstract

This paper presents a study based on versatile bio-inspired metaheuristic stud krill herd (SKH) algorithm to tackle the optimal power flow (OPF) problems in a power system network. SKH consists of stud selection and crossover operator that is incorporated into the original krill herd algorithm to improve the quality of the solution and especially to avoid being trapped in local optima. In order to investigate the performance, the proposed algorithm is demonstrated on the optimal power flow problems of IEEE 14-bus, IEEE 30-bus and IEEE 57-bus systems. The different objective functions considered are minimization of total production cost with and without valve point loading effect, minimization of active power loss, minimization of L-index and minimization of emission pollution. The OPF results obtained with the proposed approach are compared with the other evolutionary algorithms recently reported in the literature.

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Authors and Affiliations

  1. Electrical Engineering Department, National Institute of Technology, Hamirpur, Himachal Pradesh, 177005, India

    Harish Pulluri, R. Naresh & Veena Sharma

Authors
  1. Harish Pulluri
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  2. R. Naresh
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  3. Veena Sharma
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Correspondence to Veena Sharma.

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The authors declare that they have no conflict of interest.

Animal and human rights

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. This chapter does not contain any studies with animals performed by any of the authors.

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Informed consent was obtained from all individual participants included in the study.

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Communicated by V. Loia.

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Pulluri, H., Naresh, R. & Sharma, V. A solution network based on stud krill herd algorithm for optimal power flow problems. Soft Comput 22, 159–176 (2018). https://doi.org/10.1007/s00500-016-2319-3

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