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Adaptive Huffman Coding-Based Approach to Reduce the Size of Power System Monitoring Parameters

机译:基于自适应的霍夫曼编码的方法,以减小电力系统监测参数的大小

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For maintaining power system stability, several parameters like voltage, frequency, etc. are monitored sequentially at regular intervals by SCADA, and the informations are transmitted to data centre through suitable communication schemes. If the volume of data can be reduced, then it is possible to reduce the energy and space requirement. This paper emphasizes on the development of an algorithm to compress the monitoring parameters using Adaptive Huffman Coding in MATLAB environment. The compression ratio obtained by this approach is better than what is obtained by other data compression techniques. This results in the reduction of memory requirement by about 60%, thereby enabling it suitable for the data handling of a large volume of monitoring data encountered frequently in a power system.
机译:为了维持电力系统稳定性,通过SCADA定期监视电压,频率等的几个参数,并且通过合适的通信方案将信息传输到数据中心。 如果可以减少数据量,则可以降低能量和空间要求。 本文强调了在MATLAB环境中使用自适应霍夫曼压缩监测参数的算法的开发。 通过该方法获得的压缩比优于其他数据压缩技术获得的压缩比。 这导致记忆要求的降低约60%,从而使其能够适用于在电力系统中经常遇到的大量监测数据的数据处理。

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