Research On Power Quality Disturbances Detection And Identification Based On Hilbert-Huang Transform

In modern power system,problems of power quality become complex and outstanding.Accurately detecting the parameters of a power quality disturbance,and identifying its type,are necessary premise to realize effective governance of power quality.On the basis of predecessors' work,problems of power quality detection and disturbances identification are studied in this paper,analysis and comparison are also conducted on Fourier transform,wavelet transform,S transform,Hilbert-Huang transform or HHT for short,and other methods for power quality analysis.Then the HHT algorithm is adopted as the signal analysis method and theoretical basis of this paper.In the part of HHT theory,the two core contents,including empirical mode decomposition or EMD for short and Hilbert transform are studied,the criterion of intrinsic mode function,false components discrimination and the process to calculate the instantaneous parameters are briefly introduced at the same time.Then,the endpoint effect of HHT and the inhibition methods are emphatically discussed.The improved slope based method,or ISBM for short,is adopted to complete endpoint processing as the improved HHT algorithm in this paper,which is applied to the detection of power quality disturbances.Relevant simulation analysis,which including detection of disturbance signals based on mathematical models,and detection of disturbance signals based on power system simulation models are carried out.On the basis of power quality detection,this paper proposes a method based on the improved Hilbert-Huang transform and decision tree to classify and identify power quality disturbances.Firstly,power quality disturbance signals are analyzed through HHT algorithm with the ISBM method to inhibit the endpoint effect.The false components,which are produced through empirical mode decomposition,need removing in this process.And only the effective components go through Hilbert transformation.Then,frequency components,duration of the disturbance and the frequency during the disturbance duration can be extracted from the instantaneous frequency curve which is acquired from analysis.And from the instantaneous amplitude curve,the voltage amplitude during the disturbance duration can be obtained.Finally,by using these four characteristics as the judgment of the constructed decision tree,the disturbance signal is successfully classified and recognized.According to the mathematical models of power quality disturbance signals of eight types,such as voltage sag,harmonic,pulse,etc,a large number of testing samples are produced.Simulation tests are conducted under the condition of three kinds,including no noise,SNR of 30 db and SNR of 50 db.The classification accuracy is then recorded.The building of simulation models and programming of the improved HHT algorithm are both achieved on the platform MATLAB.Simulation results show that the method given in this paper can accurately detect the characteristic information of power quality disturbances and classify them,with high classification accuracy and a certain ability to resist noise.