Functional Uncertainty Analysis of Phasor Measurement Unit Using Fuzzy Hidden Markov Model
Functional Uncertainty Analysis of Phasor Measurement Unit Using Fuzzy Hidden Markov Model
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DOI：
10.1080/03772063.2017.1344109
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发表时间：
2018-01
影响因子：
1.5
通讯作者：
Soumita Ghosh;D. Ghosh;D. Mohanta
中科院分区：
文献类型：
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作者：
Soumita Ghosh;D. Ghosh;D. Mohanta
摘要相量测量单元（PMU）是一种新型的测量设备，它可以在电网的选定位置提供电流和电压的频率测量和时间对准相量（同步相量）。这些设备不断发展，以满足日益增长的智能电网需求。一般来说，PMU故障是隐藏的，需要适当的建模。由于它们是具有稀疏随机故障数据库的新设备，不同模块的功能集成具有偶然性和认知不确定性。然而，PMU是数字记录器的后代，因此由于先前的应用，不同功能模块的可靠性参数已经是已知的。因此，进行功能分析的不确定性，使我们能够详细了解他们的功能和子功能。本文采用模糊隐马尔可夫模型进行功能不确定性分析。该方法为隐藏故障提供了最佳路径，以减轻功能块之间的不确定性传播。
ABSTRACT The phasor measurement units (PMUs) are new age measurement devices that provide frequency measurements and time-aligned phasors (synchrophasors) of current and voltage at selected locations of the electric power grid. These devices are continuously evolving to cater for the growing need of smart grids. In general, the PMU failures are hidden which require appropriate modelling. As they are recent devices with sparse database of stochastic failures, the functional integration of different modules has aleatory and epistemic uncertainties. However, PMUs are descendants of digital recorders and thus reliability parameters of different functional modules are already known due to prior applications. Therefore, performing functional analysis with uncertainties enables us for detailed understanding of their functions and sub-functions. This paper embarks on functional uncertainty analysis using fuzzy hidden Markov model. The methodology provides with optimal path for hidden failures to mitigate propagation of uncertainty amongst the functional blocks.