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PQ data compression algorithm with modified quantizer and adaptive band logic using DTCWT

Prathibha E., Manjunatha A., Raj C. P.

Archives of Electrical Engineering

2018

Vol. 67, nr 1

207--223

Abstract:With growing demand for energy, power generated in renewable sources at various locations are distributed throughout the power grid. The power grid known as the smart grid needs to monitor power generation and its smart distribution. Smart meters provide solutions for monitoring power over smart grids. Smart meters need to continuously log data and at every source there is a large amount of data generated that needs to be compressed for both storage and transmission over the smart grid. In this paper, a novel algorithm for PQ data compression is proposed that uses the Dual Tree Complex Wavelet Transform (DTCWT) for sub-band computation and a modified quantizer is designed to reduce subband coefficient limits to less than 4 bits. The Run Length Encoding (RLC) and Huffman Coding algorithm encode the data further to achieve compression. The performance metrics such as a peak-signal-to-noise ratio (PSNR) and compression ratio (CR) are used for evaluation and it is found that the modified DTCWT (MDTCWT) improves PSNR by a factor of 3% and the mean squared error (MSE) by a factor of 16% as compared with the DTCWT based PQ compression algorithm.

DSP-FPGA beads real-time power quality disturbances classifier

Ming Z., Kaicheng L., Yisheng H.

Metrology and Measurement Systems

2010

Vol. 17, nr 2

205-215

This paper describes a real-time classification method of power quality (PQ) disturbances based on DSP-FPGA. The proposed method simultaneously uses the results obtained in the application of a series of RMS values and the discrete Fourier transform to the power signal waveform. A series of RMS values are used for estimation of the time-related parameters of the PQ disturbances and the discrete Fourier transform is used for confirmation of the frequency-related parameters of the PQ disturbances. Without adding the computational burden, both the elementary parameters of the power signal and the type of PQ disturbance are obtained easily. A simple and effective methodology for classification of nine typical kinds of PQ disturbances is proposed in this paper. Five distinguished time-frequency statistical features of each type of PQ disturbances are extracted. Using a rule-based decision tree (RBDT), the PQ disturbances pattern can be recognized easily and there is no need to use other complicated classifiers. Finally, the method is also tested using both simulated disturbances and disturbances measured using an initial development instrument. Different experimental results show the good performance of this proposed approach. Real-time calculating time based on DSP is also taken into consideration to show the effectiveness of the proposed method.