  In a microgrid, real-time state estimation has always been a challenge due to
several factors such as the complexity of computations, constraints of the
communication network and low inertia. In this paper, a real-time event-based
optimal linear state estimator is introduced, which uses the send-on-delta data
collection approach over wireless sensors networks and exhibits low computation
and communication resources cost. By employing the send-on-delta event-based
measurement strategy, the burden over the wireless sensor network is reduced
due to the transmission of events only when there is a significant variation in
the signals. The state estimator structure is developed based on the linear
Kalman filter with the additional steps for the centralized fusion of events
data and optimal reconstruction of signals by projection onto convex sets. Also
for the practical feasibility analysis, this paper developed an Internet of
things prototype platform based on LoRaWAN protocol that satisfies the
requirements of the proposed state estimator in a microgrid.
