  As the distribution grid moves toward a tightly-monitored network, it is
important to automate the analysis of the enormous amount of data produced by
the sensors to increase the operators situational awareness about the system.
In this paper, focusing on Micro-Phasor Measurement Unit ($\mu$PMU) data, we
propose a hierarchical architecture for monitoring the grid and establish a set
of analytics and sensor fusion primitives for the detection of abnormal
behavior in the control perimeter. Due to the key role of the $\mu$PMU devices
in our architecture, a source-constrained optimal $\mu$PMU placement is also
described that finds the best location of the devices with respect to our
rules. The effectiveness of the proposed methods are tested through the
synthetic and real $\mu$PMU data.
