Optimal Observer Synthesis for Microgrids With Adaptive Send-on-Delta Sampling Over IoT Communication Networks

State estimation is one of the main challenges in the microgrids, due to the complexity of the system dynamics and the limitations of the communication network. In this regard, a novel real-time event-based optimal state estimator is introduced in this article, which uses the proposed adaptive send-on-delta (SoD) nonuniform sampling method over wireless sensors networks. The proposed estimator requires low communication bandwidth and incurs lower computational resource cost. The threshold for the SoD sampler is made adaptive based on the average communication link delay, which is computed in a distributed form using the event-based average consensus protocol. The SoD nonuniform signal sampling approach reduces the traffic over the wireless communication network due to the events transmitted only when there is a level crossing in the measurements. The state estimator structure is extended on top of the traditional Kalman filter with the additional stages for the fusion of the received events. The error correction stage is further improved by optimal reconstruction of the signals using projection onto convex sets algorithm. Finally, an Internet of things (IoT) experimental platform based on LoRaWAN and IEEE 802.11 (WiFi) protocols are developed to analyze the performance of the state estimator for the IEEE 5 Bus case study microgrid.