Affiliations: [a]
Department of Computer Science, Tangshan Normal University, Tangshan, Hebei, China
| [b]
Finance Department, Tangshan Normal University, Tangshan, Hebei, China
| [c] History, Culture and Law Department, Tangshan Normal University, Tangshan, Hebei, China
Correspondence:
[*]
Corresponding author. Qi Dong, Department of Computer Science, Tangshan Normal University, Tangshan, 063000, Hebei, China. E-mails: dongqi@tstc.edu.cn and dongqi0314@163.com.
Abstract: Radial distribution system is an important link connecting power supply and users, and its power supply reliability is directly related to users. Radial distribution network reconfiguration can transform the network structure by changing the switching state of the distribution network lines, and achieve the goals of reducing network operational losses, improving power quality, and power supply reliability while meeting various constraints such as radial operation, power supply and demand balance, capacity, and voltage. Radial distribution systems have the characteristics of multiple components and complex structures. How to quickly and accurately evaluate the health performance of radial distribution systems and find an optimal solution for network reconfiguration are important issues in distribution network analysis. The network health performance evaluation of radial distribution system is classical multiple attributes group decision making (MAGDM). The probabilistic hesitancy fuzzy sets (PHFSs) are used as a tool for characterizing uncertain information during the network health performance evaluation of radial distribution system. In this paper, we extend the classical grey relational analysis (GRA) method to the probabilistic hesitancy fuzzy MAGDM with unknown weight information. Firstly, the basic concept, comparative formula and Hamming distance of PHFSs are briefly introduced. Then, the definition of the score values is employed to compute the attribute weights based on the information entropy method. Then, probabilistic hesitancy fuzzy GRA (PHF-GRA) method is built for MAGDM under PHFSs. Finally, a practical case study for network health performance evaluation of radial distribution system is designed to validate the proposed method and some comparative studies are also designed to verify the applicability.
Keywords: Multiple attributes group decision making (MAGDM), probabilistic hesitant fuzzy sets, grey relational analysis method (GRA), information entropy, network health performance evaluation
