Research on Fault Monitoring Technology of Distribution Network Based on Fuzzy Association Rules Mining

Abstract

In order to monitor the operation status of distribution network in real time and ensure the security and stability of distribution internet of things, a fault monitoring method based on fuzzy association rule mining was proposed. Fuzzy association rules mining was used to build the normal state parameter model of distribution network. The degree of interest index replaced the traditional index, aiming to improve the association degree between the rule parameters and form an effective expert knowledge base. According to the rules in the expert knowledge base, the normal state data of distribution network were obtained by fuzzy reasoning. Further, the state similarity function between the monitoring states and the normal states was used as the state judgement index. When the similarity is lower than the threshold, the fault alert should be triggered. Taking the single-phase ground fault data of distribution network simulated by MATLAB Simulink as an example, it was verified that the proposed method can effectively monitor the single-phase ground fault.

[Retracted] Using Clustering Analysis and Association Rule Technology in Cross‐Marketing

“…However, the latent trait model proposed by Chen et al [17] requires enterprises to understand the situation that each user consumes the business of their own enterprises and competitors, which is difficult to achieve in reality. erefore, literature [18] puts forward a comprehensive data factor analysis model to deal with the extended data, mainly according to the sample survey data to deal with the investigated samples. In its extended model, four different types of power exponential function distribution models are used, namely, Bernoulli distribution is used to represent binary service use items, the binomial distribution is used to represent satisfaction ranking, the Poisson distribution is used to represent service use frequency, and the normal distribution is used to represent transaction volume.…”

Fault Location for Distribution Smart Grids: Literature Overview, Challenges, Solutions, and Future Trends

“…The use of modern monitoring technologies with artificial intelligence data processing techniques enhances online fault detection and fault location [96][97][98][99]. Based on decision tree algorithm (DTA), the authors in [96] develop a fault monitoring system for electrical automation equipment.…”

“…However, the efficiency of handling faults on standard cloud service platforms may decline because of changes in SG or MG topology. Hierarchical fault monitoring [98] and artificial intelligence solutions [99] might increase efficiency.…”

“…The suggested hierarchical fault monitoring and control system is depicted in Figure 10. The authors of [99] proposed a fuzzy association rule-based fault monitoring system that can assess the system's fault condition. This technique improved the performance in monitoring alarms and fault judgment accuracy by utilizing edge computing technology and an expert knowledge base.…”

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