DocumentCode :
3729690
Title :
Kalman filter based distributed state estimation with communication systems
Author :
Md Rana;Li Li;Steven Su
Author_Institution :
Faculty of Engineering and Information Technology, University of Technology, Sydney, Broadway, NSW 2007, Australia
fYear :
2015
Firstpage :
1
Lastpage :
5
Abstract :
The internet of things (IoT) has been a prevalent research topic in recent years in both academia and industry. The main idea of this framework is the integration of physical objects into a global information network. The vision of the IoT is to integrate and connect anything at any time and any place. For this reason, it is being applied in various areas such as power system monitoring, environment monitoring, network control system, smart health care, military, smart cities management and industry revolution. To achieve the goals, the fifth generation (5G) technology will be the potential infrastructure that will assist the visions of the IoT. This paper proposes a distributed approach for microgrid state estimation. First of all, the modelling of a microgrid is presented. The microgrid state-space model is linearized around the operating point, so that the proposed distributed state estimation using the IoT with 5G networks can be applied. Moreover, we peropose a wireless sensor network based communication network to sense, transmit and estimate the microgrid states. Furthermore, this technical note proposes a novel distributed state estimation method. At the end, the simulation results show that the proposed method can successfully estimate the DER states using the IoT with 5G networks.
Keywords :
"State estimation","Microgrids","5G mobile communication","Density estimation robust algorithm","Smart grids","Covariance matrices"
Publisher :
ieee
Conference_Titel :
Power and Energy Engineering Conference (APPEEC), 2015 IEEE PES Asia-Pacific
Type :
conf
DOI :
10.1109/APPEEC.2015.7380988
Filename :
7380988
Link To Document :
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