Microgrid Optimal State Estimation Over IoT Wireless Sensor Networks With Event-Based Measurements
| Autor: | Kamyar Mehran, Mehrnaz Javadipour, Seyed Amir Alavi |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
0209 industrial biotechnology
Event (computing) Computer science business.industry 020209 energy Real-time computing Systems and Control (eess.SY) 02 engineering and technology Kalman filter Electrical Engineering and Systems Science - Systems and Control Telecommunications network 020901 industrial engineering & automation Transmission (telecommunications) FOS: Electrical engineering electronic engineering information engineering 0202 electrical engineering electronic engineering information engineering Wireless Microgrid State (computer science) business Wireless sensor network |
| Zdroj: | IECON |
| DOI: | 10.1109/iecon.2019.8927727 |
| Popis: | 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. Comment: Published in IECON 2019, Lisbon, Portugal. arXiv admin note: text overlap with arXiv:1906.00437 |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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