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

State Monitoring for Situational Awareness in Rural Microgrids Using the IoT Infrastructure