Power quality plays a critical role in the reliability of power networks. The monitoring of power quality, however, is a non-trivial task due to the high cost of measurement devices and the requirement on real-time responses. As a result, we need fast algorithms to estimate the power quality in various segments of a power network, using only a small number of measurement points. In this paper, we propose a maximum-entropy (MaxEnt) based approach to estimating power quality in smart microgrid. Compared to other existing methods such as Monte Carlo Expectation Maximization (MCEM), the MaxEnt based approach is much faster.
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