Abstract
The traditional high voltage switchgear (HVS) state evaluation model mostly adopts electrical test, live detection and historical data, neglecting the influence of real-time operation data of HVS composition equipment on the state evaluation results. This paper proposes a HVS operation state evaluation model based on fuzzy set-valued statistics method and kernel vector space model based on electrical test data and on-line monitoring data. First of all, according to the components of high voltage switchgear, the operation state of HVS is described and the evaluation index system is established. Secondly, the fuzzy set-valued statistics method is used to construct the mathematical model of evaluation index weight. Then, the kernel vector space model is introduced, and the Gaussian kernel function is used to map the sample to the features of the high-dimensional feature space. The indicator vector of the sample data and the ideal indicator vector of the high-voltage switchgear operation status level standard are defined in the high-dimensional feature space, and the angle-weighted cosine between the two vectors is calculated as the closeness of the sample to the standard status level, and then the high-voltage switchgear operation status level is obtained. Finally, the real data of a power supply company in western China are simulated. The results show that the greater the closeness degree is, the closer the HVS corresponding to the sample is to the normal state, on the contrary, the smaller the closeness degree is, the closer the HVS is to the fault state.
Highlights
With the rapid development of new energy technology, energy storage technology and computer technology, the urban distribution system is highly intelligent [1,2]
Based on the standard of State Power Grid Company, the electrical test index and on-line monitoring index of high voltage switchgear (HVS) are determined, and the weight of evaluation index is determined by fuzzy set value statistics method, and the closeness degree between sample data index and ideal index of standard grade is obtained by using kernel vector space model, which can reflect the real operation of HVS
Based on the electrical test and on-line monitoring data of switchgear, the comprehensive evaluation model of HVS operation state is established by using fuzzy setvalued statistics method and kernel vector space model in this paper. the conclusions are as follows: (1) The running state of HVS is described, and a comprehensive evaluation index system of HVS is established
Summary
With the rapid development of new energy technology, energy storage technology and computer technology, the urban distribution system is highly intelligent [1,2]. The above research results have important guiding significance for switchgear condition maintenance, but they are based on experimental data or historical data, ignore the small but important parameters of HVS operation, and do not consider the electromagnetic field, operating environment and other factors in real time operation of switchgear, and the state evaluation results are lack of integrity. In this paper, based on fuzzy set-valued statistics method and kernel vector space model, a mathematical model for evaluating the operation state of HVS is established. Based on the standard of State Power Grid Company, the electrical test index and on-line monitoring index of HVS are determined, and the weight of evaluation index is determined by fuzzy set value statistics method, and the closeness degree between sample data index and ideal index of standard grade is obtained by using kernel vector space model, which can reflect the real operation of HVS. The proposed method provides a new idea for real-time state evaluation of HVS
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