Study On Transient Power Quality Problems Of Power System

Electrical energy is the broadest used energy in modern society. Its application levelis a main development level symbol of a country. With the development andpopularization of computer, power electronic and information technology, higher andhigher request is proposed about power quality. More and more attentions are paid totransient power quality disturbance by power unit and consumers. Analyzing andevaluating power quality is the premise of adopting appropriate measures to improvepower quality and reduce the influences brought by disturbances.This paper aims at transient power quality problems, has done some researches onpower quality disturbance detection, sources locating of disturbance, disturbanceclassification, disturbance data compression and signal de-noising. Someimprovements have been achieved.Because the calculation quantity and redundancy of continuous wavelet transformis big. Binary wavelet transform is adopted to detect power quality disturbance basedon wavelet transform local modulus maximum theory, which corresponding to thesingular point of signal. Simulation results indicate that relative exact detection can beacquired at decomposition scale one. A New criterion for capacitor switching disturbance sources is proposed. Theenergy of three-phase instantaneous power is calculated based on the disturbancepower and Parseval's theorem. With the polarity of energy change during thedisturbance and the polarity of initial disturbance power peak, a new criterion isproposed, which can determine the relative location of the capacitor switching.Simulation results confirm the effectiveness of the method. A new power quality disturbance classification method is proposed based onwavelet packet decomposition, using entropy feature vectors to acquire power qualitydisturbances feature, combining with pattern recognition technology to classifydisturbances. Fisher piecewise linear classifier and Bayes classifier are usedrespectively. Simulation results show that the classification method, in which theentropy is used as feature vector, possesses higher classification correctnesscomparing with energy feature vector. An energy threshold method is proposed based on Multi-resolution Analysistheorem. Computing the energy need save to reduce wavelet coefficients, and thencombining with adaptive arithmetic encoding to compress disturbance data further.Typical power quality disturbances are used to test the proposed method. Simulationresults show that the compression effectiveness is improved comparing with waveletcoefficients threshold method.Based on wavelet transform soft-threshold de-noising method, an improvedsoft-threshold de-noising method to de-noise power quality disturbance signal isproposed. Considering the noise of power system is Gauss white noise commonly,which obey normal distribution. 3σ principle of normal distribution is used in theimproved method. Comparing with universal soft-threshold de-noising method,simulation results show that de-noising effectiveness is improved by this method.