栗然,靳保源,严敬汝,童煜栋.基于改进泰尔熵和熵度的电力系统关键节点识别[J].电测与仪表,2018,55(15):42-46. Li Ran,Jin Baoyuan,Yan Jingru,Tong Yudong.The identification of key nodes of power system based on improved Theil entropy and entropy degree[J].Electrical Measurement & Instrumentation,2018,55(15):42-46.
基于改进泰尔熵和熵度的电力系统关键节点识别
The identification of key nodes of power system based on improved Theil entropy and entropy degree
The Theil entropy is introduced and improved to identify key nodes of power system ,which make up for the deficiency calculating Shannon entropy using monotonous factor. The lines parted according to the load rate and then the contribution ratios of parted sections to uniform degree of power flow distributed of system are calculated, respectively. Then the load rate is used to weighted the results of the same part and the improved Theil entropy index of node is obtained. In order to make the result close to engineering practice, the entropy degree is used to evaluate the importance of position of nodes. Base on this, comprehensive evaluation index of nodes is proposed, which taking into account the importance of position of nodes in the network and the influence of power change on the power flow. The simulation of IEEE-39 node system is done, and the feasibility and validity of the proposed method are proved.
