Dispatching end grid fault diagnosis method based on wide-area fault recording information

Abstract

The invention discloses a dispatching end grid fault diagnosis method based on wide-area fault recording information. The method comprises the following steps that when a grid breaks down, fault data of a primary system of the grid are recorded according to a certain sampling frequency mode and are sent to a dispatching main station end through a fault recording networking system; the mapping relation between a basic data platform of grid equipment and a fault recording system is established through CT identification; different sampling frequencies of a fault recorder are unified to be the same sampling frequency according to an interpolation method; a differential-current out-of-limit value is set and independent grid equipment serves as a calculation unit to carry out differential-current calculation; whether the differential-current value is out of limit is confirmed to position fault places and confirm protection actions. The dispatching end grid fault diagnosis method has the advantages of solving the key problems that sampling frequency of the fault recorder is different and data are hard to synchronize, and achieves fault diagnosis application functions such as system operation state monitoring, protection behavior analyzing and accurate fault positioning through the fault recording information only.

Description

technical field [0001] The invention relates to the field of a grid fault diagnosis system at a dispatching end, in particular to a fault diagnosis method for a grid at a dispatching end based on wide-area fault recording information. Background technique [0002] With the strengthening of grid connection, the grid structure is more reasonable, and the transmission capacity has been effectively improved, but the probability of expanding the scope of accidents that may be caused by bad weather and local grid failures is also greatly increased. The amount of information generated when a fault occurs greatly increases, which will objectively increase the time required for grid operators to judge the nature of the accident, deal with the fault, and restore power supply. [0003] In order to quickly analyze the cause of the fault, accurately determine the location of the fault and take corresponding measures, each company has intensified the construction of the fault recording ne...

AI Technical Summary

Problems solved by technology

[0003] In order to quickly analyze the cause of the fault, accurately determine the location of the fault and take corresponding measures, each company has intensified the construction of the fault recording network system. When the power grid fails, the relevant fault recording information can be uploaded to the dispatching end in time. Due to the different sampling frequencies of oscilloscopes and difficulty in synchronization, the dispatcher cannot effectively integrate the fault current vectors in the relevant areas and use the differential principle to accurately locate the fault area, especially when multiple interval trips occur at the same time. Operators cannot intuitively judge the nature of the fault, which greatly affects the rapid restoration of power supply and the safe operation of the power grid.

[0004] Many scholars at home and abroad use the principles of Petri nets, rough sets, genetic algorithms, artificial intelligence and other principles to diagnose faults in power grids, and have achieved good results. However, the required fault information is more and the criteria are more complicated, and the practical application of engineering has certain limitations. : ①The model needs to be established in advance. For example, the construction of the model based on Bayesian network and Petri net is the operation mode before the failure, which is no longer applicable to the cascading failure model; When the time constraint characteristic is used, the time coordination relationship of the protection action adopted is fixed and single. When complex faults occur, this constraint characteristic will no longer hold true, and it is possible that some complex faults may not be able to obtain clear diagnostic results; The confidence interval setting adopted when the amount of reported information is small, for simple faults where the protection / circuit breaker basically operates normally and the signal is normal, the ideal result can be obtained when the confidence interval is set to a larger value, but for protection and In complex situations such as protection / circuit breaker refusal or misoperation, signal omission or false alarm, etc., wrong diagnosis results may be obtained

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