The Research Of Grid Single Large Disturbance Online-Detection Method Based On WAMS

With the expansion of the scale of power system,the probability of large disturbance in the power network is also growing.When the disturbance occures,if not be found and treated in a timely manner,it will even causing massive regional blackout,bring disastrous consequences.Existing disturbance detection methods are mostly based on the original SCADA system uploads the amplitude information to detect analysis,but these methods have many shortcomings,such as:data upload interval longer,operation process is more complex,algorithm running time long,no uniform time mark for data.It is these shortcomings that led to the traditional methods can not meet the requirement of power on-line detection.WAMS system uploads data marked with a uniform and high density upload,transfer speed,While the data is uploaded as phasor.So it is of great practical significance to realize the on-line detection of the disturbance of power network using the information of WAMS.This article is based on WAMS system uploaded information on the electricity grid disturbances in on-line detection for research,the main work is as follows:(1)To extract the data contains noise problem,Using wavelet analysis to data remove noise processing.Wavelet decomposition of the noisy data in the low resolution,retains its full decomposition.Set a threshold for the high resolution decomposition value.Completely retain above a threshold value of the coefficient,reconstruction of the wavelet coefficients using inverse transform for wavelet transform to get the data after denoised.This method not only can eliminate most useless information in the data,the complete data features preserved as much as possible before and after the disturbance.(2)For the existing detection method only used the signal amplitude easy to have the mistake,selected the two signal voltage of amplitude and phase to determine whether the disturbance occurs.Using SVM to detect the time of disturbances.Carries on the perturbation simulation to 3 machine 9 node systems,through the observation perturbation around data change,has established the new perturbation criterion.The problem of disturbance detection is considered as the problem of single valued classification,through perturbation values before and after training,Establish normal operation of the power grid mode,The model can distinguish whether the input data is within the normal range of the system.When the data goes beyond the normal range,the system alarms and displays the specific time of the data mutation.Using three machines nine node systems to verify,Taking two kinds of disturbance as an example of cutting machine and cutting load,The time of the disturbance is 1.00 S and 3.71 S.It shows that the largedisturbance detection method applied to the requirements of on-line inspection.(3)Due to the grid has fewer PMU measuring points,the information of power network is not comprehensive and the upload data may have errors,so use D-S evidence theory based on multi-source information fusion to fuse the WAMS and SCADA information,determining whether there are errors and disturbances.The WAMS and SCADA results are used as independent evidence to construct credibility distribution function,at the same time,constructing the information fusion model based on D-S evidence theory,according to the decision criterion,it is finally determined whether the disturbance occurred in the power network and reduce mistakes and probability of miscalculations.through three machines nine nodes system,selecting the signal with mistakes and no mistakes to verify.The signal without mistake has a disturbance in 3.71 s,but the error upload information can correct the error,and then give the result of the right disturbance.(4)This paper presents the basic process of a single large disturbance detection based on WAMS and make a disturbance detection program.The method is applied to the detection of the single large disturbance in the oil field power network.Select the voltage amplitude and phase angle as object disturbance detection.Train the voltage amplitude and voltage phase angle and then establish the disturbance detection model.When the disturbance occurred in the North ten substation,the detection results are disturbance of the system in 19:41:07.When the PMU upload data contains certain error information,according to the results of information fusion,there is no disturbance in the power network,PMU upload information is wrong.The results show that compared with the traditional disturbance detection method,the large disturbance detection method has the advantages of small calculation,relatively simple programming and fast calculation speed,more accurate detection results and so on.