Research on zone-optimized control of low-voltage line voltage quality in distribution networks based on the NAOA algorithm

Addressing voltage fluctuations and insufficient zoning control accuracy in low-voltage distribution networks, this study constructs an optimized voltage quality zoning control model based on the NAOA algorithm. The algorithm incorporates a neural adaptive mechanism to dynamically adjust inertia weights and learning factors, achieving efficient convergence and global optimization for multi-objective functions. Experimental validation on the IEEE 33-node system demonstrates that this method significantly outperforms traditional PSO and WOA algorithms in convergence speed, stability, and voltage balance. Average voltage deviation is reduced by 34.4%, and network losses decrease by 13.7%. These findings provide computational intelligence support for voltage optimization and intelligent control in distribution networks.