Micro-Grid Wind Energy Conversion Systems: Conventional and Modern Embedded Technologies - A Review
Main Article Content
Keywords
Artificial Neural Network, Wind Energy Conversion System, modern technologies, conventional methods
Abstract
This study assesses the effectiveness of an electric microgrid wind energy conversion system using both traditional techniques and contemporary embedded systems, such as artificial neural network-based control mechanisms and fuzzy logic control. The text compares and lists the advantages and disadvantages of various types of wind turbines (WTs). Moreover, this control falls into one of two groups: conventional power control or non-traditional power control. On the other side, conventional control describes methods of control such as manually controlling the turbine rotor's rotation speed and using computational analysis. The current work, in contrast, investigates and evaluates contemporary embedded control techniques used in wind energy conversion systems (WECS), including maximum power point tracking, Artificially intelligent control systems, in relation to the control mechanism, provide complete control over the pitch angle, power coefficient, and tip speed ratio for the best possible wind energy extraction. This makes a direct comparison possible. Nonetheless, there are a few drawbacks and difficulties with the two widely utilized contemporary techniques for power quality extractions: artificially intelligent neural networks and their embedded control systems. However, combining contemporary technology with integrated artificial intelligence controllers may be a workable strategy to lessen and even eliminate these difficulties, as well as advantageous for upcoming studies.
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References
References
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[1] Elgendi, M., AlMallahi, M., Abdelkhalig, A., & Selim, M. Y. (2023). A review of wind turbines in complex terrain. International Journal of Thermofluids, 17, 100289.
[2] Syahputra, R. (2013). A neuro-fuzzy approach for the fault location estimation of unsynchronized two-terminal transmission lines. International Journal of Computer Science & Information Technology, 5(1), 23.
[3] Rodriguez, J., Blaabjerg, F., & Kazmierkowski, M. P. (2023). Energy transition technology: The role of power electronics. Proceedings of the IEEE, 111(4), 329-334.
[4] Ajewole, T. O. (2010). Fault Analysis on Grid-Integrated Photovoltaic Power System''. Unpublished Master of Science Thesis, Faculty of Technology, Obafemi Awolowo University, Ile-Ife, Nigeria.
[5] Karimi, O., Koopaee, M. K., reza Tavakolpour-Saleh, A., & Hosseini, S. E. (2023). Investigating Overlap Ratio Effect on Performance of a Modified Savonius Wind Turbine: An Experimental Study.
[6] Junejo, A. R., Gilal, N. U., & Doh, J. (2023). Physics-informed optimization of robust control system to enhance power efficiency of renewable energy: Application to wind turbine. Energy, 263, 125667.
[7] Aghaei, V. T., Ağababaoğlu, A., Bawo, B., Naseradinmousavi, P., Yıldırım, S., Yeşilyurt, S., & Onat, A. (2023). Energy optimization of wind turbines via a neural control policy based on reinforcement learning Markov chain Monte Carlo algorithm. Applied Energy, 341, 121108.
[8] Sharma, R. K. (2023, March). Renewable energy systems with improved power quality in smart grid using fuzzy logic method. In 2023 2nd International Conference for Innovation in Technology (INOCON) (pp. 1-7). IEEE.
[9] Tiwari, R., & Babu, N. R. (2016). Recent developments of control strategies for wind energy conversion system. Renewable and Sustainable Energy Reviews, 66, 268-285.
[10] Adekoya, L. O., & Adewale, A. A. (1992). Wind energy potential of Nigeria. Renewable energy, 2(1), 35-39.
[11] Momoh, J. A. (2012). Smart grid: fundamentals of design and analysis (Vol. 33). John Wiley & Sons.
[12] Weedy, B. M. (2012). Electric power systems. Wiley.
[13] Abad, G., Lopez, J., Rodriguez, M., Marroyo, L., & Iwanski, G. (2011). Doubly fed induction machine: modeling and control for wind energy generation. John Wiley & Sons.
[14] Wu, B., Lang, Y., Zargari, N., & Kouro, S. (2011). Power conversion and control of wind energy systems. John Wiley & Sons.
[15] Barzola, J., Simonetti, D. L., & Fardin, J. F. (2015, October). Energy storage systems for power oscillation damping in distributed generation based on wind turbines with PMSG. In 2015 CHILEAN Conference on Electrical, Electronics Engineering, Information and Communication Technologies (CHILECON) (pp. 655-660). IEEE.
[16] Raouf, A., Tawfiq, K. B., Eldin, E. T., Youssef, H., & El-Kholy, E. E. (2023). Wind energy conversion systems based on a synchronous generator: comparative review of control methods and performance. Energies, 16(5), 2147.
[17] Zhou, F., & Liu, J. (2018). Pitch controller design of wind turbine based on nonlinear PI/PD control. Shock and Vibration, 2018(1), 7859510.
[18] González, L. G., Figueres, E., Garcerá, G., & Carranza, O. (2010). Maximum-power-point tracking with reduced mechanical stress applied to wind-energy-conversion-systems. Applied Energy, 87(7), 2304-2312.
[19] Memije, D., Rodriguez, J. J., Carranza, O., & Ortega, R. (2016, November). Improving the performance of MPPT in a wind generation system using a wind speed estimation by Newton Raphson. In 2016 IEEE International Autumn Meeting on Power, Electronics and Computing (ROPEC) (pp. 1-6). IEEE.
[20] Dani, A., Benlamlih, M., Mekrini, Z., El Mrabet, M., & Boulaala, M. (2024). Wind Energy Conversion Technologies and Control Strategies: A Review. International Journal of Renewable Energy Research (IJRER), 14(1), 140-154.
[21] Chen, Y., Shaheed, M. H., & Vepa, R. (2023). Active blade pitch control and stabilization of a wind turbine driven PMSG for power output regulation. Wind Engineering, 47(1), 126-140.
[22] Arifujjaman, M., Iqbal, M. T., & Quaicoe, J. E. (2006, December). Maximum power extraction from a small wind turbine emulator using a DC-DC converter controlled by a microcontroller. In 2006 International Conference on Electrical and Computer Engineering (pp. 213-216). IEEE.
[23] Bhayo, M. A., Yatim, A. H. M., Khokhar, S., Aziz, M. J. A., & Idris, N. R. N. (2015, October). Modeling of Wind Turbine Simulator for analysis of the wind energy conversion system using MATLAB/Simulink. In 2015 IEEE Conference on Energy Conversion (CENCON) (pp. 122-127). IEEE.
[24] Morgan, E. F., Abdel-Rahim, O., Megahed, T. F., Suehiro, J., & Abdelkader, S. M. (2022). Fault ride-through techniques for permanent magnet synchronous generator wind turbines (PMSG-WTGs): a systematic literature review. Energies, 15(23), 9116.
[25] Iqbal, A., Ying, D., Saleem, A., Hayat, M. A., & Mehmood, K. (2020). Efficacious pitch angle control of variable-speed wind turbine using fuzzy based predictive controller. Energy Reports, 6, 423-427.
[26] Pourrajabian, A., Dehghan, M., Rahgozar, S., & Wood, D. (2022, May). Effect of tip speed ratio on the aerodynamic noise of a small wind turbine: An optimization study. In Journal of Physics: Conference Series (Vol. 2265, No. 4, p. 042076). IOP Publishing.
[27] Bourhis, M., Pereira, M., & Ravelet, F. (2023). Experimental investigation of the effect of blade solidity on micro-scale and low tip-speed ratio wind turbines. Experimental Thermal and Fluid Science, 140, 110745.
[28] Li, S., Haskew, T. A., Swatloski, R. P., & Gathings, W. (2011). Optimal and direct-current vector control of direct-driven PMSG wind turbines. IEEE Transactions on power electronics, 27(5), 2325-2337.
[29] Mousa, H. H., Youssef, A. R., & Mohamed, E. E. (2020). Optimal power extraction control schemes for five-phase PMSG based wind generation systems. Engineering science and technology, an international journal, 23(1), 144-155.
[30] Rekioua, D., & Rekioua, D. (2014). Modeling of Storage Systems. Wind Power Electric Systems: Modeling, Simulation and Control, 107-131.
[31] Wei, C., Zhang, Z., Qiao, W., & Qu, L. (2015). Reinforcement-learning-based intelligent maximum power point tracking control for wind energy conversion systems. IEEE Transactions on Industrial Electronics, 62(10), 6360-6370.
[32] Hwangbo, H., Johnson, A., & Ding, Y. (2017). A production economics analysis for quantifying the efficiency of wind turbines. Wind Energy, 20(9), 1501-1513.
[33] Nouira, I., Khedher, A., & Bouallegue, A. (2012). A contribution to the design and the installation of a universal platform of a wind emulator using a DC motor. International Journal of renewable energy research, 2(4), 797-804.
[34] Lubosny, Z., & Lubosny, Z. (2003). Wind turbine operation in electric power systems: advanced modeling (p. 259). Berlin: Springer.
[35] Castillo, O. C., Andrade, V. R., Rivas, J. J. R., & González, R. O. (2023). Comparison of power coefficients in wind turbines considering the tip speed ratio and blade pitch angle. Energies, 16(6), 2774.
[36] Palanimuthu, K., Mayilsamy, G., Lee, S. R., Jung, S. Y., & Joo, Y. H. (2022). Fault ride-through for PMVG-based wind turbine system using coordinated active and reactive power control strategy. IEEE Transactions on Industrial Electronics, 70(6), 5797-5807.
[37] Khajuria, S., & Kaur, J. (2012). Implementation of pitch control of wind turbine using Simulink (Matlab). International Journal of Advanced Research in Computer Engineering & Technology, 1(4), 196-200.
[38] Apata, O., & Oyedokun, D. T. O. (2020). An overview of control techniques for wind turbine systems. Scientific African, 10, e00566.
[39] Yilmaz, O. (2022). Increasing power coefficient of small wind turbine over a wide tip speed range by determining proper design tip speed ratio and number of blades. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 236(23), 11211-11230.
[40] Tirandaz, M. R., Rezaeiha, A., & Micallef, D. (2022). Towards smart blades for vertical axis wind turbines: different airfoil shapes and tip speed ratios. Wind Energy Science Discussions, 2022, 1-22.
[41] Pehlivan, A. S., Bahceci, B., & Erbatur, K. (2022). Genetically optimized pitch angle controller of a wind turbine with fuzzy logic design approach. Energies, 15(18), 6705.
[42] Brandetti, L., Liu, Y., Mulders, S. P., Ferreira, C., Watson, S., & Van Wingerden, J. W. (2022, May). On the ill-conditioning of the combined wind speed estimator and tip-speed ratio tracking control scheme. In Journal of Physics: Conference Series (Vol. 2265, No. 3, p. 032085). IOP Publishing.
[43] Marchewka, E., Sobczak, K., Reorowicz, P., Obidowski, D., & Jóźwik, K. (2022, November). Influence of Tip Speed Ratio on the efficiency of Savonius wind turbine with deformable blades. In Journal of Physics: Conference Series (Vol. 2367, No. 1, p. 012003). IOP Publishing.
[44] Hosseini, A., Cannon, D. T., & Vasel-Be-Hagh, A. (2022). Tip speed ratio optimization: More energy production with reduced rotor speed. Wind, 2(4), 691-711.
[45] Ajewole, T., Agboola, M., Hassan, K., Alao, A., & Momoh, O. (2023). Neural Network Approach to Pitch Angle Control in Wind Energy Conversion Systems for Increased Power Generation. Journal of Digital Food, Energy & Water Systems, 4(2).
[46] Rawa, M., Mohamed, H. N., Al-Turki, Y., Sedraoui, K., & Ibrahim, A. M. (2023). Dynamic voltage restorer under different grid operating conditions for power quality enhancement with the deployment of a PI controller using gorilla troops algorithm. Ain Shams Engineering Journal, 14(10), 102172.
[47] Kani, S. P., & Ardehali, M. M. (2011). Very short-term wind speed prediction: A new artificial neural network–Markov chain model. Energy Conversion and Management, 52(1), 738-745.
[48] Karabacak, K., & Cetin, N. (2014). Artificial neural networks for controlling wind–PV power systems: A review. Renewable and Sustainable Energy Reviews, 29, 804-827.
[49] Carrasco, J. M., Franquelo, L. G., Bialasiewicz, J. T., Galván, E., PortilloGuisado, R. C., Prats, M. M., ... & Moreno-Alfonso, N. (2006). Power-electronic systems for the grid integration of renewable energy sources: A survey. IEEE Transactions on industrial electronics, 53(4), 1002-1016.
[50] Chen, Z., Guerrero, J. M., & Blaabjerg, F. (2009). A review of the state of the art of power electronics for wind turbines. IEEE Transactions on power electronics, 24(8), 1859-1875.
[51] de Freitas, T. R., Menegáz, P. J., & Simonetti, D. S. (2016). Rectifier topologies for permanent magnet synchronous generator on wind energy conversion systems: A review. Renewable and Sustainable Energy Reviews, 54, 1334-1344.
[52] Varalakshmi, K., Bharathi, B. K., & Himaja, T. (2021, August). Study of Soft-Starter Based Induction Generator for Wind Energy Conversion System. In 2021 Asian Conference on Innovation in Technology (ASIANCON) (pp. 1-4). IEEE.
[53] Meegahapola, L., Sguarezi, A., Bryant, J. S., Gu, M., Conde D, E. R., & Cunha, R. B. (2020). Power system stability with power-electronic converter interfaced renewable power generation: Present issues and future trends. Energies, 13(13), 3441.
[54] Dall’Asta, M. S., & Lazzarin, T. B. (2024). A Review of Fast Power-Reserve Control Techniques in Grid-Connected Wind Energy Conversion Systems. Energies, 17(2), 451.
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Dec 27, 2024
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Micro-Grid Wind Energy Conversion Systems: Conventional and Modern Embedded Technologies - A Review. (2024). Journal of Digital Food, Energy & Water Systems, 5(2). https://doi.org/10.36615/89s85625
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Author Biographies
Mutiu AGBOOLA, +2348060737510
M.K. Agboola is a principal technologist at Federal Polytechnic Ede, in Nigeria, currently a PhD student at Osun State University, Nigeria
K.A. HASSAN
K.A Hassan is a Assistance chief instructor at federal polytechnic ede, in Nigeria, currently a phd student at osun state university, Nigeria
T.O. AJEWOLE
T.O. Ajewole, is currently an Associate professor at osun state university, Nigeria, a member of many professional body both local and international, with a reputable number of publications.
How to Cite
Micro-Grid Wind Energy Conversion Systems: Conventional and Modern Embedded Technologies - A Review. (2024). Journal of Digital Food, Energy & Water Systems, 5(2). https://doi.org/10.36615/89s85625