Extreme learning machine-based alleviation for overloaded power system

被引：7
|
作者：
Labed, Imen [1 ]
Labed, Djamel [1 ]
机构：
[1] Univ Constantine 1, Dept Elect Engn, Lab Elect Engn, Constantine, Algeria
来源：
IET GENERATION TRANSMISSION & DISTRIBUTION | 2019年 / 13卷 / 22期
关键词：
power transmission control; learning (artificial intelligence); wind power plants; power system simulation; load flow; load shedding; load flow control; power system harmonics; flexible AC transmission systems; least squares approximations; extreme learning machine-based alleviation; overloaded power system; corrective method; electric system overload; wind farm; distribution system; congestion cost; transmission lines; unified power flow controller device; extremely fast training; excellent generalisation performance; extreme learning machine algorithm; fundamental point; transmission line alleviation; load shedding avoidance; transmission overloads; 22-bus system; power system behaviour; STABILITY ASSESSMENT;
D O I：
10.1049/iet-gtd.2019.0531
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
The present study proposes a corrective method of electric system overload provided that the wind farm is integrated into the distribution system, taking into account the congestion cost. The authors attempted to mitigate the overload and to monitor flow over transmission lines. Unified power flow controller device was the first suggestion utilised to solve this problem, then due to its extremely fast training and the excellent generalisation performance, extreme learning machine algorithm is employed. The fundamental point is the transmission line alleviation. In addition, other targets are realised: the load shedding avoidance, minimisation of losses and congestion cost. This study is also designed to utilise PowerWorld Simulator and MATLAB software to demonstrate methods for relieving transmission overloads. The accuracy of the proposed approach has been tested for Algerian (Adrar) 22-bus system. Obtained results showed an improvement in power system behaviour. Simulation results are exposed, discussed and compared at the end of this study.
引用
收藏
页码：5058 / 5070
页数：13
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