Design of Distribution Network Project Planning System Based on NSGA-II Algorithm

This paper presents a lean management monitoring system for distribution network projects based on big data and computational technologies. The system integrates, validates, and structures data from distribution networks, planning processes, and service provider evaluations. By applying advanced analytics, it processes data into actionable outputs with digital visual representations. Core modules include data validation, electronic demand submission, automated project screening, precise investment management, and demand execution monitoring. An investment optimization model for urban distribution networks is proposed, utilizing an enhanced NSGA-II algorithm to generate optimal investment curves for grids. These curves guide a dynamic allocation framework, ensuring efficient and precise investment in distribution projects. Through a typical urban distribution network case, the planning efficiency and optimization effect of the system are verified, and compared and analyzed with existing methods. Simulation results validate the system's performance, showing over 98% accuracy in data verification, a 15% improvement in resource allocation efficiency, and a 25% reduction in project preparation time. The system enables precise investment planning, optimizes workflows, and improves operational efficiency in managing distribution networks.