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智能电网分布式微电网状态估计与控制综述。

An overview of distributed microgrid state estimation and control for smart grids.

作者信息

Rana Md Masud, Li Li

机构信息

Faculty of Engineering and Information Technology, University of Technology, Sydney Broadway, NSW 2007, Australia.

出版信息

Sensors (Basel). 2015 Feb 12;15(2):4302-25. doi: 10.3390/s150204302.

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.

摘要

鉴于对化石燃料碳排放、全球变暖和能源危机的重大担忧,可再生分布式能源资源(DER)将被整合到智能电网中。这种电网可以将能源分配和控制系统的智能从中央单元扩展到远距离偏远地区,从而实现对这些间歇性能源的精确状态估计(SE)和广域实时监测。与传统的SE方法不同,本文提出了一种基于新型精度相关卡尔曼滤波器(KF)的微电网SE,用于使用典型通信系统的智能电网。然后,本文提出了一种离散时间线性二次调节器,以控制包含多个DER的微电网的状态偏差。因此,将这两种方法应用于智能电网,在绿色能源和控制研究领域形成了新的贡献。最后,仿真结果表明,所提出的基于KF的微电网SE和控制算法与现有方法相比,提供了更精确的SE和控制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4b4d/4367413/0ca658249639/sensors-15-04302f1.jpg

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