Abstract
In the intelligent distribution network, various faults of the distribution network still frequently occur during the operation of the distribution network, which normally appears at the weak points of various types of electrical equipment. The basic concepts and practical application significance of the three judgment indicators of support, confidence, and imbalance ratio in association rules are proposed in this paper; subsequently, the collection and sorting of fault data in the distribution network are mentioned, and the subsequent fault data of the association rules are performed as well. The preprocessing was implemented, and the weak point analysis model of the distribution network was established. Finally, the analysis and verification were carried out through the calculation example, which proved the feasibility and accuracy of the association rule data mining algorithm FP-network in the analysis and diagnosis of the weak point of the distribution network. The results show that the accuracy of the proposed method in identifying weak points in the distribution network can reach more than 90%. Therefore, the application of this algorithm in the monitoring of weak points in the distribution network has better performance.
Highlights
With the continuous advancement of the construction of intelligent distribution networks and the continuous improvement of information systems, how to integrate large-scale information and deal with them gradually becomes a key issue to be well solved
The weak point analysis involved3,4 focuses on the use of operational reliability models and complex network theory, and other mathematical theories and methods for research and analysis; the research on data mining algorithms5–7 mainly involves the identification of faulty lines in the power system and the distributed cluster monitoring of fault data
The Apriori, FP-Growth, FP-network, and other data mining algorithms8 are adopted to perform big data analysis on a large amount of data collected during the operation of the power system that has gradually become a mainstream method
Summary
With the continuous advancement of the construction of intelligent distribution networks and the continuous improvement of information systems, how to integrate large-scale information and deal with them gradually becomes a key issue to be well solved. The Apriori, FP-Growth, FP-network, and other data mining algorithms are adopted to perform big data analysis on a large amount of data collected during the operation of the power system that has gradually become a mainstream method.. An adaptive distributed quasiNewton (A-DQN) algorithm with an optimal step size tuning strategy for MASE in power systems was proposed in Ref. 16. This method is based on the point-to-point communication paradigm, providing accurate estimation results and considering the area coupling between while maintaining the privacy and independence of each area. The potential connection between two things or multiple things can be obtained according to the frequent item sets that have been excavated so that it can predict what may happen in the future
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