Consumer Phase Identification of LVDNs with Green Energy Based on Weighted Least Squares Driven by Improved PSO Algorithm

To improve the accuracy of consumer phase intelligent identification (CPII) in low-voltage distribution networks, this paper proposes a novel phase identification method based on Weighted Least Squares driven by improved Particle Swarm Optimization (PSO) algorithm. Firstly, a data screening scheme is introduced to remove abnormal data. Then, the individual update scheme of the PSO algorithm is improved. Subsequently, a weighted least squares method driven by the improved PSO algorithm is designed for CPII to reduce the impact of grey data. Finally, simulations are conducted on an actual low-voltage distribution network topology, and the results show that the proposed method enhances identification accuracy.