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

Author:
Zhang, Jingrui, Wang, Silu, Tang, Qinghui, Zhou, Yulu, Zeng, Tao
Source:
Energy 2019 v.172 pp. 945-957
ISSN:
0360-5442
Subject:
algorithms, electric potential, emissions, energy costs
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.
Agid:
6307169