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

Jingrui Zhang, Silu Wang, Qinghui Tang, Yulu Zhou and Tao Zeng

Energy, 2019, vol. 172, issue C, 945-957

Abstract: 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.

Keywords: Ma-OPF problem; Improved NSGA-III; Adaptive elimination; Boundary and closer point (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (19)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:172:y:2019:i:c:p:945-957

DOI: 10.1016/j.energy.2019.02.009

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