Design Of Smart Grid High Performance Digital Waveform Recorder And Relative Compression Algorithm

Power quality events often make huge losses in morden society by the heavily relies of electric energy. High-performance Digital Waveform Recorder (HDWR) is a premis of researching and improving the power quality, as well as a foundation of building a strong Smart Grid in China. For the contradiction that exists in power quality waveform recording starting criteria between accuracy error and calculation, this paper uses Euclidean Distanse model based on the Pattern Similarity as a criterion of power quality recorder starting, and some corresponding simulation and experimental research has done in this paper.This paper describes the background and significance of the topic, and has discussed the development status quo of HDWR. Boundary conditions and detecting methods definited in the world's major Power Quality Standards are discussed, and the features and functionality of Smart Grid HDWR are also summarized.This paper describes the TMS320C6416 DSP and XC4VSX25 FPGA-based HDWR hardware and software implementation process. Hardware includes the design of Recorder data processing main board, signal conditioning and analog-digital converter board, communication board, data storage board, power board. Software includes DSP control software, communication software, FPGA sampling control and caching software.This paper generated typical power quality incidents waveforms and calculated various types of boundary conditions of the model power quality pattern similarity by simulations, and as a basis for power quality events waveform simulation of the compression and decompression. Meanwhile, the measured power quality event data were analyzed and calculated all kinds of power quality event model similarity by MATLAB, and the actual data compression and decompression.This paper, according to the design, has completed the Smart Grid HDWR system design and debugging. The system prototype has been tested with corresponding test waveforms and data. Gives relevant recommendations for improving the power quality data compression decompression algorithms based on pattern similarity in future.