Review of the Modern Maximum Power Tracking Algorithms for Permanent Magnet Synchronous Generator of Wind Power Conversion Systems

被引:20
作者
Le, Xuan Chau [1 ]
Duong, Minh Quan [2 ]
Le, Kim Hung [2 ]
机构
[1] Naval Acad, 30 Tran Phu St, Nha Trang City 550000, Vietnam
[2] Univ Da Nang, Univ Sci & Technol, Fac Elect Engn, 54 Nguyen Luong Bang St, Da Nang 550000, Vietnam
关键词
coventional MPPT; DPC; hybrid MPPT algorithms; intelligent MPPT; IPC; PMSG; WT; TIP-SPEED RATIO; ENERGY-CONVERSION; POINT TRACKING; TURBINE SYSTEM; POPULATION INTERACTION; SENSORLESS CONTROL; MPPT; EFFICIENCY; EXTRACTION; CONTROLLER;
D O I
10.3390/en16010402
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 conversion systems (WECSs) are considered green generators, environmentally friendly, and fully suitable energy sources to replace fossil energy sources. WECS's output power is hugely dependent on the random nature of the wind. There are many solutions to improve the output power for WECSs, such as adjusting the profile of turbine blades, locating installation places, improving generators, etc. Nevertheless, maximum power point tracking (MPPT) algorithms for WECSs are optimal and the most effective because they are flexible in controlling different variable wind speeds and match all types of WECS. The parameters on the generator side control or the grid side control will be adjusted when MPPT algorithms are used, allowing the output power of WECSs to be maximized while maintaining stability in variable-speed wind. There are various MPPT algorithms, but the current problem is their efficiency and whether it requires deep knowledge to select the best MPPT solutions because each method has different advantages and disadvantages. This study has implemented an overview of modern maximum power tracking algorithms applied to permanent magnet synchronous generators in WECS with MPP methods based on speed convergence, efficiency, self-training, complexity, and measurement of wind parameters.
引用
收藏
页数:25
相关论文
共 87 条
[1]  
Abdullah MA, 2014, AUSTR UNIV POWER ENG
[2]  
Abdullah MA, 2012, 2012 IEEE INTERNATIONAL CONFERENCE ON POWER AND ENERGY (PECON), P65, DOI 10.1109/PECon.2012.6450296
[3]   A review of maximum power point tracking algorithms for wind energy systems [J].
Abdullah, M. A. ;
Yatim, A. H. M. ;
Tan, C. W. A. ;
Saidur, R. .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2012, 16 (05) :3220-3227
[4]  
Abdullah M. A., 2011, 2011 IEEE Conference on Clean Energy and Technology, P321, DOI 10.1109/CET.2011.6041484
[5]   Towards Green Energy for Smart Cities: Particle Swarm Optimization Based MPPT Approach [J].
Abdullah, Majid Abdullateef ;
Al-Hadhrami, Tawfik ;
Tan, Chee Wei ;
Yatim, Abdul Halim .
IEEE ACCESS, 2018, 6 :58427-58438
[6]   MPPT Based PMSG Wind Turbine System Using Sliding Model Control (SMC) and Artificial Neural Network (ANN) Based Regression Analysis [J].
Agarwal, Nirmal Kumar ;
Sadhu, Pradip Kumar ;
Chakraborty, Suprava .
IETE JOURNAL OF RESEARCH, 2022, 68 (03) :1652-1660
[7]   Improvement in Perturb and Observe Method Using State Flow Approach [J].
Ahmed, Rana ;
Namaane, A. ;
M'Sirdi, N. K. .
MEDITERRANEAN GREEN ENERGY FORUM 2013: PROCEEDINGS OF AN INTERNATIONAL CONFERENCE MGEF-13, 2013, 42 :614-623
[8]  
Ahmed S, 2019, ENG LET, V27, P822
[9]  
Aicha A, 2017, 2017 5TH INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING - BOUMERDES (ICEE-B)
[10]   Variable step size PO MPPT algorithm using model reference adaptive control for optimal power extraction [J].
Ali, Mustafa M. ;
Youssef, Abdel-Raheem ;
Ali, Ahmed S. ;
Abdel-Jaber, G. T. .
INTERNATIONAL TRANSACTIONS ON ELECTRICAL ENERGY SYSTEMS, 2020, 30 (01)