State analysis method for secondary system of smart substation based on fuzzy c-means clustering algorithm
A smart substation and secondary system technology, which is applied in computing, instruments, data processing applications, etc., can solve the problem of large information capacity of the secondary system of smart substations, multi-variation of state assessment model schemes, difficulty in meeting universal reliability requirements, etc. question
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[0039] The present invention will be further described below in conjunction with drawings and embodiments.
[0040] Based on the fuzzy C-means clustering algorithm for the state analysis method of the secondary system of the smart substation, the maximum operating temperature of the equipment, the optical transmission power and receiving sensitivity, and the insulation resistance of the equipment to the ground are selected as the key characteristic quantities that affect the operating state of the equipment. Common types of secondary system faults include communication faults, protection refusal or malfunction, and abnormal alarms.
[0041] Fuzzy C-means Clustering Algorithm
[0042] Firstly, the basic principle of C-means clustering algorithm is introduced, and then fuzzy C-means algorithm is introduced.
[0043] If N i is the i-th cluster Γ i The number of samples in , m i is the mean of these samples, namely:
[0044]
[0045] Among them, y is a d-dimensional matrix...
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