Power data analysis method and system based on data fusion
A data fusion and power data technology, applied in data processing applications, neural learning methods, character and pattern recognition, etc., can solve problems such as difficulty in finding abnormal power data in time, low efficiency, etc., and achieve the goal of improving automation and positioning accuracy. Effect
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Embodiment 1
[0056] For ease of understanding, see figure 1 , the present invention provides an embodiment of a data fusion-based power data analysis method, comprising the following steps:
[0057] Step 101. Acquire multi-dimensional data of large power grid regulation from multiple power dispatching systems, including PMS system, EMS system, OMS system, power distribution automation system, dispatching automation system, synchronous line loss system, and power consumption information collection Any two or more systems in system and marketing system.
[0058] It should be noted that, in the present invention, the multi-dimensional data of large power grid regulation is first obtained from multiple power dispatching systems in real time or at regular intervals. Energy Management System), OMS system (power grid dispatching management system, Outage Management System), power distribution automation system, dispatching automation system, synchronous line loss system, power consumption inform...
Embodiment 2
[0074] For ease of understanding, see figure 2 , the present invention provides another embodiment of a power data analysis method based on data fusion. When step 103 in embodiment 1 locates the fault cause of the power system as an external force cause according to the abnormal data, when performing step 104-step On the basis of step 105, step 106-step 109 is also executed at the same time to further determine whether the cause of the failure of the power system is caused by the externally damaged hidden danger object:
[0075] Step 106, acquiring multiple sets of transmission line image data combined into a live image of the transmission line from the video monitoring system of the power system.
[0076] Step 107 , performing image feature extraction on multiple sets of transmission line image data respectively to obtain feature images.
[0077] Step 108, splicing the extracted feature images and inputting them into the convolutional fusion model to obtain second fusion da...
Embodiment 3
[0094] For ease of understanding, see Figure 3 to Figure 5 , on the basis of the foregoing embodiment 1 or embodiment 2, after step 105, may also include:
[0095] Step 110, according to the cause of the failure and the risk level of the failure, designate a corresponding number of maintenance personnel to the failure point to handle the failure.
[0096] After determining the cause of the failure and the risk level of the failure, according to the corresponding relationship between the cause of the failure, the risk level of the failure and the maintenance personnel, a corresponding number of maintenance personnel can be assigned to the fault point for troubleshooting. Specifically, all maintenance personnel on duty carry mobile terminals with corresponding identifications, and the mobile terminals record the location and working status of the maintenance personnel (in maintenance operation or idle). According to the mobile terminal carried by the maintenance personnel, the...
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