Error-Based Active Disturbance Rejection Control for Pitch Control of Wind Turbine by Improved Coyote Optimization Algorithm

被引：35
作者：
Huang, Congzhi [1 ,2 ]
Zhuang, Jini [2 ]
机构：
[1] North China Elect Power Univ, Sch Control & Comp Engn, Beijing 102206, Peoples R China
[2] North China Elect Power Univ, Key Lab Power Stn Energy Transfer Convers & Syst, Beijing 102206, Peoples R China
来源：
IEEE TRANSACTIONS ON ENERGY CONVERSION | 2022年 / 37卷 / 02期
基金：
中国国家自然科学基金;
关键词：
Active disturbance rejection control (ADRC); coyote optimization algorithm (COA); error-driven; extended state observer (ESO); FAST simulator; pitch control; wind turbine; POWER-CONTROL; DESIGN; SPEED;
D O I：
10.1109/TEC.2021.3124941
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：
Wind energy systems are expected to supple the majority of future generation from renewables due to the maturity of technology and the availability of energy resources. In this paper, in order to improve the ability of tracking a desired power reference at high wind speed region, a pitch control strategy based on error-based active disturbance rejection control (ADRC) approach is proposed for variable speed wind turbine system, providing a novel practically appealing control structure. The stability analysis of the proposed pitch controller based on singular perturbation theory is provided. Next, an improved coyote optimization algorithm (COA) fused with L e vy flight and Sinusoidal map is proposed to address the controller parameters tuning issue. Then, the effectiveness of the proposed solution is verified on a 1.5 MW FAST simulator taking into account both multi-step and IEC turbulence wind conditions. Finally, an analysis in frequency domain of the pitch control system with the proposed control strategy is presented.
引用
收藏
页码：1394 / 1405
页数：12
相关论文
共 46 条
[1]  
[Anonymous], 1992, Measure theory and fine properties of functions
[2]   Load mitigation of a class of 5-MW wind turbine with RBF neural network based fractional-order PID controller [J].
Asgharnia, A. ;
Jamali, A. ;
Shahnazi, R. ;
Maheri, A. .
ISA TRANSACTIONS, 2020, 96 :272-286
[3]   Performance and robustness of optimal fractional fuzzy PID controllers for pitch control of a wind turbine using chaotic optimization algorithms [J].
Asgharnia, Amirhossein ;
Shahnazi, Reza ;
Jamali, Ali .
ISA TRANSACTIONS, 2018, 79 :27-44
[4]   Fault-Tolerant Individual Pitch Control for Load Mitigation in Wind Turbines With Actuator Faults [J].
Badihi, Hamed ;
Zhang, Youmin ;
Pillay, Pragasen ;
Rakheja, Subhash .
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2021, 68 (01) :532-543
[5]   Sliding mode power control of variable-speed wind energy conversion systems [J].
Beltran, Brice ;
Ahmed-Ali, Tarek ;
Benbouzid, Mohamed El Hachemi .
IEEE TRANSACTIONS ON ENERGY CONVERSION, 2008, 23 (02) :551-558
[6]   Validation of Individual Pitch Control by Field Tests on Two- and Three-Bladed Wind Turbines [J].
Bossanyi, Ervin A. ;
Fleming, Paul A. ;
Wright, Alan D. .
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY, 2013, 21 (04) :1067-1078
[7]   Enhancing Frequency Response Control by DFIGs in the High Wind Penetrated Power Systems [J].
Chang-Chien, Lee-Ren ;
Lin, Wei-Ting ;
Yin, Yao-Ching .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2011, 26 (02) :710-718
[8]  
Fernando D.B., 2006, Wind turbine control systems: principles, modelling and gain scheduling design (advances in industrial control)
[9]  
Gao ZQ, 2003, P AMER CONTR CONF, P4989
[10]   A novel particle swarm optimization algorithm with Levy flight [J].
Hakli, Huseyin ;
Uguz, Harun .
APPLIED SOFT COMPUTING, 2014, 23 :333-345
12345