TY - JOUR
DP - National Agricultural Library
DB - PubAg
JO - Energy
TI - An improved NSGA-III integrating adaptive elimination strategy to solution of many-objective optimal power flow problems
A1 - Zhang, Jingrui
A4 - Zhang, Jingrui
A4 - Wang, Silu
A4 - Tang, Qinghui
A4 - Zhou, Yulu
A4 - Zeng, Tao
EP - 2019 v.172
KW - algorithms
KW - electric potential
KW - emissions
KW - energy costs
AN - 6307169
AB - 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.
PY - 2019
LA -
DA - 2019-04-01
VL - v. 172
SP - pp. 945-957
DO - 10.1016/j.energy.2019.02.009
ER -