Control Methods for Horizontal Axis Wind Turbines (HAWT): State-of-the-Art Review

被引:22
作者
Elkodama, Amira [1 ]
Ismaiel, Amr [1 ]
Abdellatif, A. [2 ]
Shaaban, S. [2 ]
Yoshida, Shigeo [3 ,4 ]
Rushdi, Mostafa A. [3 ]
机构
[1] Future Univ Egypt FUE, Fac Engn & Technol, New Cairo 11835, Egypt
[2] Arab Acad Sci Technol & Maritime Transport, Mech Engn Dept, Cairo 11799, Egypt
[3] Kyushu Univ, Res Inst Appl Mech RIAM, 6-1 Kasugakoen, Kasuga, Fukuoka 8168580, Japan
[4] Saga Univ, Inst Ocean Energy IOES, Saga 8408502, Japan
关键词
pitch control; renewable energy; torque control; wind turbine; yaw control; MODEL-PREDICTIVE CONTROL; PITCH-ANGLE CONTROLLER; VARIABLE-SPEED; YAW CONTROL; TORQUE CONTROL; NONLINEAR CONTROL; POWER EXTRACTION; OPTIMIZATION; DESIGN; SYSTEM;
D O I
10.3390/en16176394
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
In recent years, the increasing environmental problems, especially the issue of global warming, have motivated demand for a cleaner, more sustainable, and economically viable energy source. In this context, wind energy plays a significant role due to the small negative impact it has on the environment, which makes it among the most widespread potential sustainable renewable fuel nowadays. However, wind turbine control systems are important factors in determining the efficiency and cost-effectiveness of a wind turbine (WT) system for wind applications. As wind turbines become more flexible and larger, it is difficult to develop a control algorithm that guarantees both efficiency and reliability as these are conflicting objectives. This paper reviews various control strategies for the three main control systems of WT, which are pitch, torque, and yaw control, in different operational regions considering multi-objective control techniques. The different control algorithms are generally categorized as classical, modern (soft computing) and artificial intelligence (AI) for each WT control system. Modern and soft computing techniques have been showing remarkable improvement in system performance with minimal cost and faster response. For pitch and yaw systems, soft computing control algorithms like fuzzy logic control (FLC), sliding mode control (SMC), and maximum power point tracking (MPPT) showed superior performance and enhanced the WT power performance by up to 5% for small-scale WTs and up to 2% for multi-megawatt WTs. For torque control systems, direct torque control (DTC) and MPPT AI-based techniques were suitable for reducing generator torque fluctuations and estimating the torque coefficient for different wind speed regions. Classical control techniques such as PI/PID resulted in poor dynamic response for large-scale WTs. However, to improve classical control techniques, AI algorithms could be used to tune the controller's parameters to enhance its response, as a WT is a highly non-linear system. A graphical abstract is presented at the end of the paper showing the pros/cons of each control system category regarding each WT control system.
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页数:32
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