The use of tens of thousands of power electronic equipment and large-scale new energy has already caused tens of thousands of harmonics into the traditional power system, which has brought challenges to the monitoring of electrical quantities in the power system. Aiming at the problem that the measurement accuracy of traditional wide-frequency measurement algorithms is greatly lost in complex situations such as wide-frequency oscillation, a time-frequency domain dynamic phasor estimation method based on Window Interpolation FFT and Taylor Least Squares is proposed. First, a fast Fourier transform is performed on the electrical signal to sense the spectrum range of the signal, and then the dominant frequency band is obtained based on energy screening, according to which the sampling rate and model order of the Taylor least squares algorithm is selected. Next, the amplitude and phase position of each component is obtained by Taylor’s least squares. Finally, the simulation is carried out under steady and dynamic conditions concerning the IEEE standard of the fundamental wave, and it is proved that the algorithm can accurately obtain the time domain index and change trend of each harmonic and has strong practicability, which provides an effective means for the analysis of power grid wide-frequency oscillation.
KEYWORDS: Data storage, Data communications, Data transmission, Control systems, Databases, Visualization, Data conversion, Design and modelling, Data centers, Classification systems
Full-view Synchronized Measurement System (SYMS) realizes the dynamic monitoring of electronic power system. At present, the main station of SYMS can receive real-time phasor data from all over the country with SMD for loads(SML), which is independently developed. In this paper, after the master station of SYMS system is confronted with massive data access, openPDC data center cannot be compatible with SML data, openHistorian database cannot classify and recognize massive phase-quantity data, and it is difficult to read and call historical data. An adaptive method of openPDC and SML based on GSF framework is proposed, as well as a real-time phase classification algorithm for openHistorian and SML data, which realizes real-time data transmission from SML to openPDC, and real-time sorting and reading of SML data by openHistorian. A historical data storage algorithm based on.NET framework has been proposed to solve the problem of accessing and calling phasor historical data in openHistorian. The test results show that the proposed algorithm improves the data processing capability of SYMS system.
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