Modeling Regional Distribution Network Planning and Investment Strategies for Population Migration

This paper constructs a regional distribution network planning and investment strategy model for the dynamic characteristics of population migration, integrates the key elements of population forecast, load evolution and grid resource allocation, and introduces the improved NSGA-II algorithm to realize the dynamic solution on the basis of multi-objective optimization theory. The model is empirically applied in a new suburban district of a provincial capital city, and the results show that compared with the traditional static planning scheme, the dynamic optimization strategy can reduce the total investment cost by about $10.8 \%$, the average load factor decreases to $71.3 \%$, the system reliability index improves to 0.95, and the payback period is shortened by 1.1 years. The study verifies the effectiveness and economy of the model in coping with load uncertainty under migration drive.