Improving Dynamic Stability of deregulated power system

被引:3
|
作者
Rouhani, Seyed Hossein [1 ]
Ahmadiahangar, Roya [2 ,3 ]
Haring, Tobias [2 ,3 ]
Rosin, Argo [2 ,3 ]
机构
[1] Univ Guilan, Fac Engn, Rasht, Iran
[2] Tallinn Univ Technol, Smart City Ctr Excellence Finest Twins, Tallinn, Estonia
[3] Tallinn Univ Technol, Dept Elect Power Engn & Mechatron, Tallinn, Estonia
基金
欧盟地平线“2020”;
关键词
deregulated environments; random variable load (RVL); renewable energy; wind turbine with DFIG; Load frequency control (LFC); intelligent algorithm's (ICA; GA; PSO); AVR-P; IMPERIALIST COMPETITIVE ALGORITHM; PRICE-BASED OPERATION; WIND TURBINES; AGC SIMULATOR; OPTIMIZATION; CONTROLLER;
D O I
10.1109/RTUCON51174.2020.9316618
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
One of the most important problems in the daily function of the power system is generation programming and its control. The primary purpose of Automatic Generation Control (AGC) is balancing the whole generation system against load variations and system losses. In a power system, any unpredictable variations of consumption load will cause fluctuation in frequency and the current power between the lines. Load frequency control is one of the main problems in the power system which synchronizes with automatic generation control. In this paper, a three area power system in a deregulated environment with the participation of the hybrid generation wind turbine with Doubly Fed Induction Generator (DFIG), hydro, and thermal power plants is studied. The load in this power system is considered a random variable form that periodically and randomly has a frequency of 0.25% around the nominal amount. One of the consequences of using Doubly Fed Induction Generator and variable load in the Restructured Power Systems is the frequency of oscillation. To reduce this fluctuation the Automatic Voltage Regulator (AVR) equipped by Power System Stabilizer (PSS), FACTs devises and PID controller has been used. PID controller parameters have been optimized by Imperialist Competitive, genetic and Particle swarm optimization algorithm.
引用
收藏
页数:6
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