Optimized network selection for data flow transmission in electricity distribution systems with multi-modal communication networks

Efficient data flow transmission in electricity distribution systems is critical for modern power systems. This paper proposes a novel network selection framework to optimize data transmission for diverse power services. A comprehensive evaluation index system is established, incorporating economic, technical, and security metrics. Weights are derived using the entropy weight method and best-worst method (BWM), integrated via the measurement of alternatives and ranking according to the compromise solution (MARCOS) method to rank alternative networks. A Gale-Shapley many-to-one matching algorithm is then developed, which assigns services to networks, prioritizing high-priority tasks while ensuring adaptability. Simulation results demonstrate that the proposed approach outperforms traditional methods in service completion rate, bandwidth utilization, and communication efficiency, especially under bandwidth constraints.