A NOVEL CONTROL STRATEGY TO ENHANCE THE DYNAMIC RESPONSE OF THE WIND ENERGY CONVERSION SYSTEM USING A DOUBLY FED INDUCTION GENERATOR BASED ON AN INTELLIGENT FUZZY-PI CONTROLLER
This paper introduces an effective and simple power control method for wind energy conversion systems based on a doubly-fed induction generator. Due to the limitations of traditional proportional-integral controllers when the parameters of the doubly-fed induction generator and wind speed vary, fuzzy control theory is applied to overcome these challenges. First, a detailed mathematical model of the induction generator in the d-q domain is provided. Then, based on the characteristics of the doubly-fed induction generator, an enhanced mathematical model is presented along with a vector control model for the generator. Subsequently, the mathematical model for the wind turbine and the fuzzy controller based on the proportional-integral controller are developed and implemented in MATLAB/Simulink for simulation and performance evaluation. Simulation results indicate that the proposed method for controlling the doubly-fed induction generator can significantly improve the dynamic response performance under varying generator parameters and wind speed conditions.
Tài liệu tham khảo
Abolhassani, M. T., Enjeti, P., & Toliyat, H. (2008). Integrated doubly fed electric alternator/active filter (IDEA), a viable power quality solution, for wind energy conversion systems. IEEE Transactions on Energy Conversion, 23(2), 642-650.
Ackermann, T. (2012). Wind power in power systems. John Wiley & Sons.
Bensahila, B., Allali, A., Merabet Boulouiha, H., & Denai, M. (2020). Modeling, Simulation and Control of a Doubly-Fed Induction Generator for Wind Energy, Conversion Systems. International Journal of Power Electronics and Drive Systems (IJPEDS).
Boutoubat, M., Mokrani, L., & Machmoum, M. (2013). Control of a wind energy conversion system equipped by a DFIG for active power generation and power quality improvement. Renewable Energy, 50, 378-386.
Dai, L., & Pham, H. T. (2023). A Feasible MPPT Algorithm for the DC/DC Boost Converter: An Applied Case for Stand-Alone Solar Photovoltaic Systems. International journal of electrical and computer engineering systems, 14(6), 713-724.
Dai, L., & Tung, D. (2017). Modeling for Development of Simulation Tool: A Case Study of Grid Connected Doubly Fed Induction Generator Based on Wind Energy Conversion System. International Journal of Applied Engineering Research, 12(11), 2981-2996.
Iov, F., Hansen, A. D., Sørensen, P., & Blaabjerg, F. (2004). Wind turbine blockset in Matlab/Simulink-general overview and description of the models.
Jain, A. K., & Ranganathan, V. (2008). Wound rotor induction generator with sensorless control and integrated active filter for feeding nonlinear loads in a stand-alone grid. IEEE Transactions on Industrial electronics, 55(1), 218-228.
Jazaeri, M., Samadi, A., Najafi, H., & Noroozi-Varcheshme, N. (2012). Eigenvalue Analysis of a Network Connected to a Wind Turbine Implemented with a Doubly-Fed Induction Generator (DFIG). Journal of applied research and technology, 10(5), 791-811.
Kenza, M., Lamia, Y., Farid, N., & Mihai, C. (2024). Fuzzy Based Vector Control Strategy for a Doubly Fed Induction Motor. 2024 12th International Conference on Smart Grid (icSmartGrid),
Krause, P. (2002). Analysis of Electric Machinery and Drive Systems. IEEE Press google schola, 2, 203-210.
Liserre, M., Cardenas, R., Molinas, M., & Rodriguez, J. (2011). Overview of multi-MW wind turbines and wind parks. IEEE Transactions on Industrial electronics, 58(4), 1081-1095.
Mehdipour, C., Hajizadeh, A., & Mehdipour, I. (2016). Dynamic modeling and control of DFIG-based wind turbines under balanced network conditions. International Journal of Electrical Power & Energy Systems, 83, 560-569.
Miller, N. W., Price, W. W., & Sanchez-Gasca, J. J. (2003). Dynamic modeling of GE 1.5 and 3.6 wind turbine-generators. GE-Power systems energy consulting(3.0).
Mohamed, A. Z., Eskander, M. N., & Ghali, F. A. (2001). Fuzzy logic control based maximum power tracking of a wind energy system. Renewable Energy, 23(2), 235-245.
Pena, R., Clare, J., & Asher, G. (1996). Doubly fed induction generator using back-to-back PWM converters and its application to variable-speed wind-energy generation. IEE Proceedings-Electric power applications, 143(3), 231-241.
Phung, B. N., Wu, Y.-K., & Pham, M.-H. (2024). Novel Fuzzy Logic Controls to Enhance Dynamic Frequency Control and Pitch Angle Regulation in Variable-Speed Wind Turbines. Energies, 17(11), 2617.
Singh, M., & Chandra, A. (2010). Application of adaptive network-based fuzzy inference system for sensorless control of PMSG-based wind turbine with nonlinear-load-compensation capabilities. IEEE transactions on power electronics, 26(1), 165-175.
Tohidi, A., Abedinia, O., Bekravi, M., & Ojaroudi, N. (2016). Multivariable adaptive variable structure disturbance rejection control for DFIG system. Complexity, 21(4), 50-62.
Yang, X., Liu, G., Li, A., & Le, V. D. (2017). A predictive power control strategy for DFIGs based on a wind energy converter system. Energies, 10(8), 1098.
