  This paper presents an event-triggered estimation strategy and a data
collection architecture for situational awareness (SA) in microgrids. An
estimation agent structure based on the event-triggered Kalman filter is
proposed and implemented for state estimation layer of the SA using long range
wide area network (LoRAWAN) protocol. A setup has been developed which can
provide enormous data collection capabilities from smart meters, in order to
realise an adequate SA level in microgrids. Thingsboard Internet of things
(IoT) platform is used for the SA visualisation with a customised dashboard. It
is shown by using the developed estimation strategy, an adequate level of SA
can be achieved with a minimum installation and communication cost to have an
accurate average state estimation of the microgrid.
