Distribution system state estimation-A step towards smart grid

被引:123
作者
Ahmad, Fiaz [1 ]
Rasool, Akhtar [1 ]
Ozsoy, Emre [2 ]
Rajasekar, S. [3 ]
Sabanovic, Asif [1 ]
Elitas, Meltem [1 ]
机构
[1] Sabanci Univ, Fac Engn & Nat Sci, Istanbul, Turkey
[2] Istanbul Tech Univ, Dept Control & Automat Engn, Istanbul, Turkey
[3] NEC Labs, Smart Energy Div, Singapore, Singapore
关键词
Distribution system state estimation; DSSE; Smart grid; Microgrid Distributed energy sources (DERs); Energy management system; Distribution management system; RECURSIVE BAYESIAN-APPROACH; BAD DATA DETECTION; ESTIMATION ALGORITHM; POWER-SYSTEMS; KALMAN FILTER; LOAD; NETWORK; IDENTIFICATION; PLACEMENT; ERRORS;
D O I
10.1016/j.rser.2017.06.071
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
State estimation (SE) is well-established at the transmission system level of the electricity grid, where it has been in use for the last few decades and is a most vital component of energy management systems employed in the monitoring and control centers of electric transmission systems. However, its use for the monitoring and control of power distribution systems (DSs) has not yet been widely implemented because DSs have been majorly passive with uni-directional power flows. This scenario is now changing with the advent of smart grid, which is changing the nature of electric distribution networks by embracing more dispersed generation, demand responsive loads, and measurements devices with different data rates. Thus, the development of distribution system state estimation (DSSE) tool is inevitable for the implementation of protection, optimization, and control techniques, and various other features envisioned by the smart grid concept. Due to the inherent characteristics of DS different from those of transmission systems, transmission system state estimation (TSSE) is not applicable directly to DSs. This paper is an attempt to present the state-of-the-art on DSSE as an enabler function for smart grid features. It broadly reviews the development of DSSE, challenges faced by its development, and various DSSE algorithms. Additionally, it identifies some future research lines for DSSE.
引用
收藏
页码:2659 / 2671
页数:13
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