Statistical Estimation Framework for State Awareness in Microgrids Based on IoT Data Streams
Statistical Estimation Framework for State Awareness in Microgrids Based on IoT Data Streams
- Author(s): S. A. Alavi 1 ; A. Rahimian 2 ; K. Mehran 3
- DOI: 10.1049/icp.2021.1090
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- Author(s): S. A. Alavi 1 ; A. Rahimian 2 ; K. Mehran 3
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View affiliations
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Affiliations:
1:
School of Electronic Engineering and Computer Science, Queen Mary University of London , London , UK ;
2: School of Engineering, Ulster University , Newtownabbey , UK ;
3: School of Electronic Engineering and Computer Science, Queen Mary University of London , London , UK
Source:
The 10th International Conference on Power Electronics, Machines and Drives (PEMD 2020),
2021
p.
855 – 860
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Affiliations:
1:
School of Electronic Engineering and Computer Science, Queen Mary University of London , London , UK ;
- Conference: The 10th International Conference on Power Electronics, Machines and Drives (PEMD 2020)
- DOI: 10.1049/icp.2021.1090
- ISBN: 978-1-83953-542-0
- Location: Online Conference
- Conference date: 15-17 December 2020
- Format: PDF
This paper presents an event-triggered statistical 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 provides enormous data collection capabilities from smart meters in order to realize an adequate level of SA in microgrids. Thingsboard Internet of things (IoT) platform is used for the SA visualization with a customized dashboard. It is shown that 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.
Inspec keywords: state estimation; statistical analysis; distributed power generation; wide area networks; power engineering computing; Kalman filters; Internet of Things; protocols
Subjects: Protocols; Distributed power generation; Power engineering computing; Protocols; Other topics in statistics; Mobile, ubiquitous and pervasive computing; Computer communications; Optimisation techniques; Other computer networks; Other topics in statistics; Simulation, modelling and identification; Information networks