A bad data detection and identification method suitable for large power grids
A technology of bad data and identification method, applied in the fields of electrical digital data processing, data processing application, special data processing application, etc., can solve the problems of residual submergence, slow calculation speed, influence estimation effect, etc., to improve the accuracy and calculation effect of speed, increased sensitivity and accuracy, and increased computational precision
Active Publication Date: 2017-11-03
STATE GRID CORP OF CHINA +2
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Problems solved by technology
Possible shortcomings in the above detection and identification methods: residual pollution and residual submersion may occur, resulting in missed or false detections, affecting the identification effect and further affecting the estimation effect
The disadvantage of this type of method is that the amount of calculation is large and the calculation speed is slow; if the number of detections is limited, residual pollution and residual submersion are prone to occur, resulting in missed or false detections and affecting the identification effect
Especially in the case of less measurement data and inaccurate and unreliable data values (such as in the distribution network), the phenomenon of residual pollution and residual submersion is more serious
[0005] Power system state estimation has been developed for decades at home and abroad, and the research on bad data detection and identification has never stagnated, but an effective method for detecting and identifying bad data has not yet been proposed. A method suitable for large power grids is proposed Bad data detection and identification methods to overcome the above defects
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Embodiment 1
[0074] like Figure 1-2 As shown, the invention of this example is a bad data detection and identification method suitable for large power grids, and the method is used in the state estimation process of the power system; the method includes the following steps:
[0075] (1) Determine the suspicious data set SUS of the whole network;
[0076] (2) determine the associated suspicious data set sus[n] in the suspicious data set;
[0077] (3) Identify the bad data in the associated suspicious data set sus[n].
[0078] The determination process of described step (1) is:
[0079] (1-1) Perform state estimation of the entire network.
[0080] (1-2)r n Detection method to identify suspicious data set SUS
[0081] The step (1-1) performs a state estimation of the whole network from the original measurement.
[0082] the r n The detection process of the detection method is:
[0083]
[0084] In the formula, H 0 The i-th measurement data is not suspicious measurement data, H ...
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The invention relates to a bad data detection and recognition method suitable for a large power grid. The method is applied to evaluation of the state of an electric power system. The method comprises the following steps that bad data are detected, and suspect data sets in the bad data are determined; related suspect data sets in the suspect data sets are determined; bad data in the suspect data sets are determined; the bad data in the suspect data sets are deleted. The method is widely applied to current provincial-level power grids and a national power grid, can be adaptive to online analysis requirements of the large power grid in the future, and can quickly and accurately delete bad data in measurement information, and improve state evaluation precision.
Description
Technical field: [0001] The invention relates to a bad data detection and identification method, and more particularly to a bad data detection and identification method suitable for large power grids. Background technique: [0002] Power system state estimation is an important part of modern energy management systems, and most of its measurement data come from SCADA systems. In addition to normal measurement noise, the information may also contain bad data. The existence of bad data will lead to contamination of estimation results and even serious distortion. The detection and identification of bad data is one of the important functions of power system state estimation. [0003] The power system state estimation is to use the redundancy of the real-time measurement system to improve the data accuracy, eliminate the error information caused by random interference, and then estimate or predict the operating state of the system. The methods of bad data detection and identific...
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IPC IPC(8): G06F17/30G06Q50/06
CPCG06F16/90335G06Q50/06
Inventor 赵昆窦成龙颜磊邹昱徐杰张印
Owner STATE GRID CORP OF CHINA