An Improved NSGA-III Approach to Many-Objective Optimal Power Flow Problems

The optimal power flow (OPF) plays one of the most important roles in power systems operation. This paper formulates the OPF problem as a many-objective OPF (MaOPF) 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. Then an improved non-dominated sorting genetic algorithm III (I-NSGA-III) is proposed to solve this Ma-OPF problem. In the proposed I-NSGA-III, an elimination mechanism instead of the original selection mechanism in the environmental selection operation is proposed to reduce selection efforts. Furthermore, a mixed multi-constraints handling mechanism including repair strategy and constrain-domination principle is used to enhance the feasibility of the final solutions. IEEE 30 buses system is employed to test the feasibility and effectiveness of the proposed algorithm. The obtained results demonstrate its competitiveness with comparisons to the original NSGA-III.