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A nonintrusive power load monitoring method using coupled allocation mechanism

机译:一种使用耦合分配机制的非蓄电功率负荷监测方法

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摘要

For non-intrusive power load monitoring problem, the key trouble is that there contains complex multiple types of appliances in a power load environment. In this study, two key suppositions are firstly introduced: (1) the signal characteristics should keep stable for each load appliance with a same running state in continuous times; (2) there is at most one running state change at an enough small monitoring period. Then, we consider that a probabilistic label value for each possible load can be evaluated according to a probabilistic clustering principle. Moreover, a coupled allocation mechanism on mixed probabilistic labels is introduced, in which an iterative filtering strategy is designed to estimate the optimal state combination of different loads. By performing professional load scenario simulations, the algorithm performance is effectively examined. The corresponding results indicate that better comprehensive performance can be obtained by the proposed method compared to the latest hidden Markov model and fuzzy clustering method.
机译:对于非侵入式电力负荷监测问题,关键问题是在电力负载环境中包含复杂多种类型的设备。在这项研究中,首先介绍了两个关键假设:(1)信号特性应在连续时间内与相同的运行状态保持稳定; (2)在足够的小监测期间,最多有一个运行状态发生变化。然后,我们认为可以根据概率聚类原理评估每个可能负载的概率标签值。此外,引入了混合概率标签上的耦合分配机制,其中迭代滤波策略旨在估计不同负载的最佳状态组合。通过执行专业负载方案模拟,可以有效地检查算法性能。相应的结果表明,与最新隐马尔可夫模型和模糊聚类方法相比,所提出的方法可以获得更好的全面性能。

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