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Performance Evaluation of Superstate HMM with Median Filter For Appliance Energy Disaggregation

机译:带有中值滤波器的超级状态HMM用于设备能量分解的性能评估

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Information on electricity consumption is one of the essential elements in terms of regulating the distribution of electricity in smart micro grid. Besides, information on electricity consumption can help consumers carry out an evaluation process to reduce electricity bill costs, which indirectly affect overall energy efficiency. One method in the process of monitoring electricity consumption is Non-Intrusive Load Monitoring (NILM). The main problem in NILM is to determine the energy disaggregation consumed by several equipment by merely performing the retrieval of data from only one measuring point. We used the Superstate Hidden Markov Model as the tool for modelling and analysis. A median data filter to the input data is applied to improve the performance of the disaggregation process. Based on the results of tests conducted using the REDD, the lowest accuracy was 96.69% for all tests performed.
机译:电力消耗信息是调节智能微电网中电力分配的基本要素之一。此外,有关用电量的信息可以帮助消费者进行评估过程,以降低电费成本,从而间接影响整体能效。监视电力消耗过程中的一种方法是非侵入式负载监视(NILM)。 NILM中的主要问题是仅通过从一个测量点执行数据检索来确定多个设备消耗的能量分解。我们使用超状态隐马尔可夫模型作为建模和分析工具。对输入数据使用中值数据过滤器以提高分解过程的性能。根据使用REDD进行的测试结果,所有执行的测试的最低准确度均为96.69%。

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