  In a power distribution network with energy storage systems (ESS) and
advanced controls, traditional monitoring and protection schemes are not well
suited for detecting anomalies such as malfunction of controllable devices. In
this work, we propose a data-driven technique for the detection of incidents
relevant to the operation of ESS in distribution grids. This approach leverages
the causal relationship observed among sensor data streams, and does not
require prior knowledge of the system model or parameters. Our methodology
includes a data augmentation step which allows for the detection of incidents
even when sensing is scarce. The effectiveness of our technique is illustrated
through case studies which consider active power dispatch and reactive power
control of ESS.
