Study On Power Quality Detection And Assessment Methods In Power System

With the development of electric power technology and deepening of the marketeconomy, users and researchers have been paid more attention to power quality.Comprehensive evaluation of power quality also becomes a topic which is being stueiedby scholar. Power quality assessment is a complex and dynamic process. How to establishreasonable power quality evaluation model is an important precondition to assess powerquality.Power quality synthesized assessment provides a charges for power companies,What’s more, it provides basis for users who want to buy electricity on their demand.Therefore, this paper builds the power quality assessment system. The disturbance signalof power quality is analyzed to get the position of singular point and amplitude changes,then, we get the power quality disturbance classification and grading. Finally, we can docomprehensive assessment to power quality.Firstly, according to existing power quality assessment system, this paper investigatesthe indicators of power quality, introduces the meaning of every indicator, establishespower quality assessment model. According to the national institute of standards, levellimit value of each indicator is divided. This paper adds some transient power indicatorsinto power quality assessment model as much as possible to ensure that the evaluationmodel can contain the complete power quality indicators.Secondly, this paper investigates db4lifting wavelet and lifting steps. UsingMATLAB to analysis the power quality signals, which are collected from a steel plant. Inthe electricity market, transient power quality accounts for a large proportion, we analysisof voltage dips and voltage interruption, shows disturbance starting position and amplitudevariation. Using wavelet packet transform analysis harmonic problem, in addition, takinginto account the real power system, it existes noise interference, this paper analysis theway to denoised.The simulation results show that it is effective for transient disturbancesignals to use db4lifting wavelet. Accurately featuring extraction of power qualitydisturbance signal, which is a good foundation for the comprehensive assessment of powerquality. Finally, power quality indicators are fused by D-S evidence theory. In this paper, webuild a power quality recognition framework. In order to overcome the uncertainty of thepower quality problem, the researcher constructed a basic belief function based on thecombination rule of D-S evidence theory. At last, we can get only grading. While ensuringgood result, the uncertainty reduced sharply. The uncertainty is too tiny to be ignored. Thesimulation results show that it is effective and scientific way to evaluate power quality.