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Sensors 2015, 15(2), 4302-4325; doi:10.3390/s150204302

An Overview of Distributed Microgrid State Estimation and Control for Smart Grids

Faculty of Engineering and Information Technology, University of Technology, Sydney Broadway, NSW 2007, Australia
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Received: 11 November 2014 / Accepted: 3 February 2015 / Published: 12 February 2015
(This article belongs to the Section Sensor Networks)
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Abstract

Given the significant concerns regarding carbon emission from the fossil fuels, global warming and energy crisis, the renewable distributed energy resources (DERs) are going to be integrated in the smart grid. This grid can spread the intelligence of the energy distribution and control system from the central unit to the long-distance remote areas, thus enabling accurate state estimation (SE) and wide-area real-time monitoring of these intermittent energy sources. In contrast to the traditional methods of SE, this paper proposes a novel accuracy dependent Kalman filter (KF) based microgrid SE for the smart grid that uses typical communication systems. Then this article proposes a discrete-time linear quadratic regulation to control the state deviations of the microgrid incorporating multiple DERs. Therefore, integrating these two approaches with application to the smart grid forms a novel contributions in green energy and control research communities. Finally, the simulation results show that the proposed KF based microgrid SE and control algorithm provides an accurate SE and control compared with the existing method. View Full-Text
Keywords: discrete-time algebraic Riccati equations; distributed energy resource; Kalman filter; smart grid; state estimation; wireless sensor networks discrete-time algebraic Riccati equations; distributed energy resource; Kalman filter; smart grid; state estimation; wireless sensor networks
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Rana, M.M.; Li, L. An Overview of Distributed Microgrid State Estimation and Control for Smart Grids. Sensors 2015, 15, 4302-4325.

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