A Genetic Algorithm Based Feeder-User Connection Mapping Method with Limited Meter Data in Distribution Networks

The dynamic topology of urban distribution power systems poses a significant challenge in accurately mapping energy supply districts, critical for illustrating feeder-household connections and ensuring efficient energy matching. Traditional approaches rely heavily on comprehensive smart meter data or the installation of new monitoring equipment, both of which are costly. This research proposes a novel genetic algorithm-based mapping technique that requires only energy consumption data. This approach leverages historical consumption patterns to produce feeder-user connection maps with high precision. A case study confirms the effectiveness of the algorithm in feeder-user connection mapping, and shows its potential for utility management optimization.