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EN
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.
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