%0 Journal Article
%9 Article
%W National Agricultural Library
%~ PubAg
%B Energy
%T An improved NSGA-III integrating adaptive elimination strategy to solution of many-objective optimal power flow problems
%A Zhang, Jingrui
%A Wang, Silu
%A Tang, Qinghui
%A Zhou, Yulu
%A Zeng, Tao
%V 2019 v.172
%K algorithms
%K electric potential
%K emissions
%K energy costs
%M 6307169
%X 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.
%D 2019
%= 2019-04-23
%G
%8 2019-04-01
%V v. 172
%P pp. 945-957
%R 10.1016/j.energy.2019.02.009