4.7 Article

An improved NSGA-III integrating adaptive elimination strategy to solution of many-objective optimal power flow problems

期刊

ENERGY
卷 172, 期 -, 页码 945-957

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2019.02.009

关键词

Ma-OPF problem; Improved NSGA-III; Adaptive elimination; Boundary and closer point

资金

  1. National Natural Science Foundation of China [61403321]
  2. Natural Science Foundation of Fujian Province of China [2018J01098]
  3. Natural Science Foundation of Guangdong Province of China [2014A030310003, 2017A010101003]

向作者/读者索取更多资源

This paper formulates the OPF problem as a many-objective OPF (Ma-OPF) problem with consideration of minimizing many objective functions including the total fuel cost (TFC), total emissions (TE), voltage magnitude deviation (VMD), active power loss (APL) and Line-index (L-index) and multiple complicated constraints. An improved NSGA-III (I-NSGA-III) in which an elimination mechanism instead of the original selection mechanism is employed to reduce selection efforts in environment selection operation is proposed to solve this Ma-OPF problem. An adaptive elimination strategy is also introduced to determine which individuals should be eliminated. In addition, I-NSGA-III integrates a boundary and closer point preservation strategy to get better extreme solutions and obtain population diversity. Furthermore, a mixed multi-constraints handling mechanism is used to enhance the feasibility of solutions. The proposed I-NSGA-III and original NSGA-III are compared and tested on IEEE 30-bus, IEEE 57-bus and IEEE 118-bus test systems with different cases and the experimental results demonstrate the competitiveness and effectiveness of the proposed algorithm. (C) 2019 Elsevier Ltd. All rights reserved.

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