Introducing a New Method for Tracking and Transmitting Maximum Power of a Wind Power Plant to the Grid During Wind Shortages

Document Type : Original Article


Department of Electrical Engineering, Mahdishahr Branch, Islamic Azad University, Mahdishahr, Iran


The present paper proposes a novel vector control based method to connect a wind plant equipped with a Doubly-Fed Induction Generator to the grid. It also provides separate control capacity of injection power to the grid under wind shortages in addition to optimum performance in normal climatic conditions. The mathematical modeling of converters of the grid and rotor side is presented, which provides such a control tool. The idea of using an energy storage system has been presented to reduce power swings of the wind plant to grid in the dc-link of back-to-back converter of the rotor side. In order to achieve an optimal control system, the strategy of maximum wind power tracking and unit power factor of the wind farm are included in the control system. However, the power exchange strategy with the unit power factor is related to the type of operation of the grid, and reactive injection power can also be controlled when needed. Finally, a simulation of the studied system and the proposed control system in the SIMULINK environment of MATLAB software is presented, which provides a powerful tool for these types of systems. The results obtained from the conducted studies on a sample system demonstrate the efficiency and accuracy of the proposed method.


1. Weiss, H. and Jian, X., “Fuzzy system control for     combined
wind and solar power distributed generation unit”, In IEEE
International Conference on Industrial Technology, Vol. 2,
(2003), 1160-1165. 
2. Li, R. and Wang, X., “Status and challenges for offshore wind
energy”, In International Conference on Materials for
Renewable Energy & Environment, Vol. 1, (2011), 601-605.  
3. Abbey, C. C., Katiraei, F., Brothers, C., Dignard-Bailey, L. and
Joos, G., “Integration of distributed generation and wind
energy in Canada”, In IEEE Power Engineering Society
General Meeting, (2006), 7-13. 
4. Sorensen, P., Cutululis, N. A., Lund, T., Hansen, A. D.,
Sorensen, T., Hjerrild, J., Heyman Donovan, M., Christensen,
L. and Kraemer Nielsen, H., “Power quality issues on wind
power installations in Denmark”, In IEEE Power Engineering
Society General Meeting, Vol. 14, (2007), 1-6. 
5. Linh, N. T., “Power quality investigation of grid connected
wind turbines”, In 4th IEEE Conference on Industrial
Electronics and Applications, Vol. 11, (2009), 2218-2222. 
6. Jahanpour-Dehkordi, M., Vaez-Zadeh, S. and Ghadamgahi, A.,
“An Improved Combined Control for PMSG-Based Wind
Energy Systems to Enhance Power Quality and Grid
Integration Capability”, In 10th International Power
Electronics, Drive Systems and Technologies Conference
(PEDSTC), Vol. 18, (2019), 566-571. 
7. Melendez, C., Diaz, M., Rojas, F., Cardenas, R. and Espinoza,
M., “Control of a Double Fed Induction Generator based Wind
Energy Conversion System equipped with a Modular
Multilevel Matrix Converter”, In Fourteenth International
Conference on Ecological Vehicles and Renewable Energies
(EVER), Vol. 24,  (2019), 1-11. 
8. Dahbi, A., Hachemi, M., Nait-Said, N. and Nait-Said, M. S.,
“Realization and control of a wind turbine connected to the grid
by using PMSG”, Energy Conversion and Management, Vol.
84, (2014), 346-353. 
9. Singh, B. and Kasal, G. K., “Voltage and frequency controller
for a three-phase four-wire autonomous wind energy
conversion system,” IEEE Transactions on Energy
Conversion, Vol. 23, No. 2, (2008), 509-518. 
10. Reddy, G. P. R., Ranga, G. P. and Kumar, M. V.,
“Implementation of matrix converter based PMSG for Wind
Energy Conversion System”, In  th International Conference on
Intelligent Systems and Control (ISCO), Vol. 13, (2013), 115120.
11. Abouheaf, M., Gueaieb, W. and Sharaf, A., “Model-free
adaptive learning control scheme for wind turbines with doubly fed induction generators”, IET Renewable Power Generation,
Vol. 12, No. 14, (2018), 1675-1686.  
12. Lele, N., Wang, X., Wu, L., Yan, F. and Xu, M., “Review of
low voltage ride-through technology of doubly-fed induction
generator”, The Journal of Engineering, Vol. 8, No. 16,
(2019), 3106-3108.  
13. Sadeghi, R., Madani Mohammad Ataei, S. M., Agha
Kashkooli, M. R. and Ademi, S., “Super-twisting sliding mode
direct power control of a brushless doubly fed induction
generator”,  IEEE Transactions on Industrial
Electronics, Vol. 65, No. 11, (2018), 9147-9156.  
14. Chikha, S., “Active and Reactive Power Management of Wind
Farm Based on a Six Legs Tow Stages Matrix Converter
Controlled By a Predictive Direct Power Controller”, Iranian
Journal of Electrical & Electronic Engineering, Vol. 14, No.
3, (2018), 245-258. 
15. Chitsazan, M. A.,  Fadali, M. S.,  Trzynadlowski, A.  M. and
Amin, M., “Wind speed and wind direction forecasting using
echo state network with nonlinear functions”, Renewable
Energy, Vol. 131, (2019), 879-889.  
16. Heydari, E., Rafiee, M. and Pichan, M., “Fuzzy-Genetic
Algorithm-Based Direct Power Control Strategy for DFIG”,
Iranian Journal of Electrical & Electronic Engineering, Vol.
14, No. 4, (2018), 353-361. 
17. Bedoud, K., Rhif, A., Bahi, T. and Merabet, H., “Study of a
double fed induction generator using matrix converter: case of
wind energy conversion system”, International Journal of
Hydrogen Energy, Vol. 43, No. 25, (2018), 11432-11441.  
18. Ibrahim, A., Solomin, E. and Miroshnichenko, A., “Control
Strategy for Maximum Power Point Tracking of Doubly Fed
Induction Motor for Wind Turbine”, In 2018 International Ural
Conference on Green Energy (UralCon), Vol .2, No. 1, (2018),
19. Javad, S. and Amini Badr, A., “Dynamic   Modeling and
Optimal Control of a Wind Turbine with Doubly Fed Induction
Generator using imperialist competitive and artificial bee
colony algorithms”, Journal of Circuits, Systems and
Computers, Vol. 28 No. 4, (2019), 1950070.  
20. Fouzia, A. and Mendil, B. “Wind speed forecasting techniques
for maximum power point tracking control in variable speed
wind turbine generator”, International Journal of Modelling
and Simulation, Vol. 10, No. 3, (2019), 1-10. 
21. Ahmadi, H., Rajaei, A., Nayeripour, M. and Ghani, M.,
“Hybrid Control Method to Improve LVRT and FRT in DFIG
by Using the Multi-Objective Algorithm of Krill and the Fuzzy
Logic”, Iranian Journal of Electrical & Electronic
Engineering, Vol. 14, No. 4, (2018), 330-341.  
22. Ouada, L., Benaggoune, S. and Belkacem, S., “Neuro-fuzzy
Sliding Mode Controller Based on a Brushless Doubly Fed
Induction Generator”, International Journal of Engineering-
Transactions B: Applications, Vol. 33, No. 2, (2020), 248-256. 
23. Douadi, T., Harbouche, Y., Abdessemed, R. and Bakhti, I.,
"Improvement performances of active and reactive power
control applied to DFIG for variable speed wind turbine using
sliding mode control and FOC" International Journal of
Engineering- Transactions A: Basics, Vol. 31, No. 10, (2018),