New design of robust PID controller based on meta-heuristic algorithms for wind energy conversion system

被引:49
作者
Elsisi, Mahmoud [1 ,2 ]
机构
[1] Natl Taiwan Univ Sci & Technol, Ind Implementat Ctr 4 0, Taipei, Taiwan
[2] Benha Univ, Fac Engn Shoubra, Elect Engn Dept, 108 Shoubra St,POB 11241, Cairo, Egypt
关键词
frequency-domain constraints; meta-heuristic algorithms; robust PID controller; wind energy conversion system; PARTICLE SWARM OPTIMIZATION; POWER-SYSTEMS; TURBINE; STABILITY; FREQUENCY; MODEL;
D O I
10.1002/we.2439
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
This paper proposes a new robust control method for a wind energy conversion system. The suggested method can damp the deviations in the generator speed because of the penetration of wind speed and load demand fluctuations in the electrical grid. Furthermore, it can overcome the uncertainties of the plant parameters because of load demand fluctuations and the errors of the implementation. The new method has been built based on new simple frequency-domain conditions and the whale optimization algorithm (WOA). This method is utilized to design a robust proportional-integral-derivative (PID) controller based on the WOA in order to enhance the damping characteristics of the wind energy conversion system. Simulation results confirm the superiority and robustness of the proposed technique against the wind speed fluctuations and the plant parameters uncertainties compared with other meta-heuristic algorithms.
引用
收藏
页码:391 / 403
页数:13
相关论文
共 36 条
[1]   A VARIABLE-STRUCTURE STABILIZER FOR WIND TURBINE GENERATORS [J].
ABDELMAGID, YL ;
ALHAMOUZ, ZM ;
BAKHASHWAIN, JM .
ELECTRIC POWER SYSTEMS RESEARCH, 1995, 33 (01) :41-48
[2]   Adaptive output feedback controller for wind turbine generators using neural networks [J].
Al-Duwaish, HN ;
Al-Hamouz, ZM ;
Badran, SM .
ELECTRIC MACHINES AND POWER SYSTEMS, 1999, 27 (05) :465-479
[3]   Speed control of induction motor supplied by wind turbine via Imperialist Competitive Algorithm [J].
Ali, Ehab S. .
ENERGY, 2015, 89 :593-600
[4]   Optimizing connection weights in neural networks using the whale optimization algorithm [J].
Aljarah, Ibrahim ;
Faris, Hossam ;
Mirjalili, Seyedali .
SOFT COMPUTING, 2018, 22 (01) :1-15
[5]  
[Anonymous], 2009, MODERN CONTROL ENG
[6]  
[Anonymous], 2000, THEORY MATRICES
[7]  
ARGOUN MB, 1990, IEEE T AUTOMAT CONTR, V35, P180, DOI 10.1109/9.45174
[9]   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