基于TOPSIS的复杂电网节点重要性评估

本文利用复杂网络理论构建了江西电网拓扑模型,对其网络特性进行分析,通过TOPSIS(technique for order preference by similarity to ideal solution)算法评估电网中的重要节点,并利用SIR(susceptible infected recovered model)模型对重要节点的传播影响力进行仿真分析。结果表明江西电网节点度分布服从幂律分布,网络呈现出无标度和小世界特性。网络中的重要度排名前10的节点分别为罗坊、抚州、梦山、鹰潭、乐平、永修、南昌、文山、赣州和红都。SIR仿真结果说明重要节点对网络的传播影响力极大,其中TOPSIS方法下的最终节点感染规模相比单一指标至少有5%的增幅。

Importance Evaluation of Complex Power Network Nodes Based on TOPSIS

In this paper, the complex network theory is used to construct the topology model of Jiangxi power grid, and the network characteristics are analyzed. The important nodes in the power network are evaluated by TOPSIS (technique for order preference by similarity to ideal solution) algorithm, and the propagation influence of important nodes is simulated and analyzed by SIR (susceptible infected recovered model) model. The results show that the node degree distribution of Jiangxi power network follows the power-law distribution, and the network presents scale-free and small-world characteristics. The top 10 important nodes in the network are Luofang, Fuzhou, Mengshan, Yingtan, Leping, Yongxiu, Nanchang, Wenshan, Ganzhou and Hongdu. SIR simulation results show that important nodes have great influence on network propagation, and the final node infection scale under TOPSIS method is at least 5% higher than that of single index.