A Fault Analysis Method Based on Association Rule Mining for Distribution Terminal Unit
Source abstract
Abstract
With the development of distribution networks, large amounts of distribution terminal units (DTU) are gradually integrated into the power system. However, limited numbers of maintenance engineers can hardly cope with the pressure brought about by the substantial increase of DTU devices. As DTU fault would pose a threat to the stable and safe operation of power systems; thus, it is rather significant to reduce the fault incidence of DTU devices and improve the efficiency of fault elimination. In this paper, a DTU fault analysis method using an association rule mining algorithm was proposed. Key factors of DTU fault were analyzed at first. Then, the main concept of the Eclat algorithm was illustrated, and its performance was compared with FP-growth and Apriori algorithms using DTU fault databases of different sizes. Afterwards, a DTU fault analysis method based on the Eclat algorithm was proposed. The practicality of this method was proven by experiment using a realistic DTU fault database. Finally, the application of this method was presented to demonstrate its effectiveness.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Data Mining Algorithms and Applications · Power Systems Fault Detection · Electricity Theft Detection Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Cyber Science and Engineering, Southeast University, Nanjing 210096, China
School of Electrical Engineering, Southeast University, Nanjing 210096, China
State Grid Nanjing Power Supply Company, Nanjing 210000, China
State Grid Corporation of China, Beijing 100032, China
Funding
State Grid Corporation of China
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