Multi-objective planning for voltage sag compensation of sparse distribution networks with unified power quality conditioner using improved NSGA-III optimization

Abstract

Aiming at the voltage sag compensation of the long-distance sparse distribution network, this paper proposed a multi-objective optimization method based on improved S-CDAS dominance and NSGA-III genetic algorithm. Firstly, aiming at the difficulty of solving the power flow for distribution network with unified power quality conditioners (UPQC), an alternating iteration algorithm of power flow calculation was presented. Secondly, this paper proposed an adaptive controlling of dominance based on extreme solutions. The algorithm dynamically fitted the Pareto frontier according to the extreme solutions in the iterative process to strengthen the dominance region of the optimal set. The algorithm results showed that the improved S-CDAS dominance could improve the convergence speed and result of NSGA-III algorithm while preserving its diversity. Finally, through PSCAD simulation, the effectiveness of the proposed algorithms was proved, and the effect of UPQC on voltage sag in long-distance sparse distribution network was verified. In conclusion, the UPQC configuration method proposed in this paper can consider the diversity of convergence direction and speed, which plays an effective role in the voltage sag compensation of long-distance sparse distribution network.