A Novel Adaptive Controller with Lyapunov Analysis for Strategy Grid Intelligent Integrated Wind Turbine Maximum Power Point Tracking System
Keywords:
Fire Hawk Optimization, Dynamic evolving neural fuzzy controller, Wind turbine system, Maximum Power Point TrackingAbstract
By continuously changing the operating point to the maximum power point (MPP) of the turbine, the Maximum Power Point Tracking (MPPT) control approach has been widely used in wind turbine (WT) systems to improve the generated power. The power production, however, fluctuates since the present MPPT systems have trouble adjusting to shifting wind speeds, turbulence, and other factors. To overcome these issues, a novel hybrid adaptive controller integrating the Fire Hawk Optimizer (FHO) with a Dynamic evolving neural fuzzy controller (DENFC) for a wind turbine MPPT system was proposed in this article. A power converter, a wind turbine generating model, and an MPPT control technique make up the three primary parts of the suggested model. The proposed adaptive controller can handle uncertainties in the wind speed and other system parameters and track the MPP of the wind turbine. Furthermore, a Lyapunov analysis was utilized to analyze the stability of the closed-loop system and to design the adaptive law for the controller. The simulation outcomes prove that the proposed approach is effective in tracking the MPP of the wind turbine system and potentially improves the performance and stability of the WT system.
Downloads
References
Tehreem, Hafiza Samina, et al. "Impact of average temperature, energy demand, sectoral value-added, and population growth on water resource quality and mortality rate: it is time to stop waiting around." Environmental Science and Pollution Research 27 (2020): 37626-37644.
McGee, Julius Alexander, and Patrick Trent Greiner. "Renewable energy injustice: The socio-environmental implications of renewable energy consumption." Energy Research & Social Science 56 (2019): 101214.
Yi, Sun, et al. "Environmental concerns in the United States: Can renewable energy, fossil fuel energy, and natural resources depletion help?." Gondwana Research 117 (2023): 41-55.
Teff-Seker, Y., et al. "Noise pollution from wind turbines and its effects on wildlife: A cross-national analysis of current policies and planning regulations." Renewable and Sustainable Energy Reviews 168 (2022): 112801.
Antzaras, Andy N., and Angeliki A. Lemonidou. "Recent advances on materials and processes for intensified production of blue hydrogen." Renewable and Sustainable Energy Reviews 155 (2022): 111917.
Baloch, Zulfiqar Ali, et al. "A multi-perspective assessment approach of renewable energy production: policy perspective analysis." Environment, Development and Sustainability (2021): 1-29.
Gulagi, Ashish, et al. "Transition pathway towards 100% renewable energy across the sectors of power, heat, transport, and desalination for the Philippines." Renewable and Sustainable Energy Reviews 144 (2021): 110934.
Apata, O., and D. T. O. Oyedokun. "An overview of control techniques for wind turbine systems." Scientific African 10 (2020): e00566.
Zhang, Lanbin, et al. "Galloping triboelectric nanogenerator for energy harvesting under low wind speed." Nano Energy 70 (2020): 104477.
Chen, Hao, et al. "Improved torque compensation control based-maximum power point tracking strategy for large scale floating offshore wind turbines." Ocean Engineering 273 (2023): 113974.
Zhang, Xinge, et al. "Maximum power point tracking algorithms for wind power generation system: Review, comparison and analysis." Energy Science & Engineering 11.1 (2023): 430-444.
Kumar, Ravinder, et al. "Maximum power point tracking in wind energy conversion system using radial basis function based neural network control strategy." Sustainable Energy Technologies and Assessments 36 (2019): 100533.
Chen, Hao, et al. "Improved torque compensation control based-maximum power point tracking strategy for large scale floating offshore wind turbines." Ocean Engineering 273 (2023): 113974.
El Mourabit, Youness, et al. "Nonlinear backstepping control for PMSG wind turbine used on the real wind profile of the Dakhla‐Morocco city." International Transactions on Electrical Energy Systems 30.4 (2020): e12297.
Belaid, Saloua, et al. "A power management control and optimization of a wind turbine with battery storage system." Journal of Energy Storage 45 (2022): 103613.
Billel, Meghni, et al. "An in-depth study of robust MPPT for extend optimal power extraction using wind speed compensation technique of wind generators." Electrical Engineering (2023): 1-24.
Lai, Zhihui, et al. "A hybrid piezo-dielectric wind energy harvester for high-performance vortex-induced vibration energy harvesting." Mechanical Systems and Signal Processing 150 (2021): 107212.
Hiremath, Ravikiran, and Tukaram Moger. "Comprehensive review on low voltage ride through capability of wind turbine generators." International Transactions on Electrical Energy Systems 30.10 (2020): e12524.
Apata, O., and D. T. O. Oyedokun. "An overview of control techniques for wind turbine systems." Scientific African 10 (2020): e00566.
Pan, Lin, and Chengpeng Shao. "Wind energy conversion systems analysis of PMSG on offshore wind turbine using improved SMC and Extended State Observer." Renewable Energy 161 (2020): 149-161.
Meghni, Billel, Mehdi Ouada, and Salah Saad. "A novel improved variable-step-size P&O MPPT method and effective supervisory controller to extend optimal energy management in hybrid wind turbine." Electrical Engineering 102.2 (2020): 763-778.
Chen, Jian, et al. "Adaptive active fault-tolerant MPPT control of variable-speed wind turbine considering generator actuator failure." International Journal of Electrical Power & Energy Systems 143 (2022): 108443.
Ahmed, Marwa M., et al. "Proposing and evaluation of MPPT algorithms for high-performance stabilized WIND turbine driven DFIG." Alexandria Engineering Journal 59.6 (2020): 5135-5146.
Balbino, Anderson José, Bruno da S. Nora, and Telles B. Lazzarin. "An improved mechanical sensorless maximum power point tracking method for permanent-magnet synchronous generator-based small wind turbines systems." IEEE Transactions on Industrial Electronics 69.5 (2021): 4765-4775.
Wu, Di, et al. "Modeling and simulation of novel dynamic control strategy for PV–wind hybrid power system using FGS− PID and RBFNSM methods." Soft Computing 24 (2020): 8403-8425.
Kumar, GB Arjun. "Optimal power point tracking of solar and wind energy in a hybrid wind solar energy system." International Journal of Energy and Environmental Engineering 13.1 (2022): 77-103.
Eltamaly, Ali M., Mohamed A. Mohamed, and Ahmed G. Abo-Khalil. "Maximum power point tracking strategies of grid-connected wind energy conversion systems." Control and Operation of Grid-Connected Wind Energy Systems (2021): 193-225.
Wang, Jie, et al. "Maximum power point tracking control for a doubly fed induction generator wind energy conversion system based on multivariable adaptive super-twisting approach." International Journal of Electrical Power & Energy Systems 124 (2021): 106347.
Joo, Y. H. "Integral sliding mode control for increasing maximum power extraction efficiency of variable-speed wind energy system." International Journal of Electrical Power & Energy Systems 139 (2022): 107958.
Prajapat, Ganesh P., N. Senroy, and I. N. Kar. "Estimation based enhanced maximum energy extraction scheme for DFIG-wind turbine systems." Sustainable Energy, Grids and Networks 26 (2021): 100419.
Waheeb , M. Q. ., SANGEETHA, D., & Raj , R. . (2021). Detection of Various Plant Disease Stages and Its Prevention Method Based on Deep Learning Technique. Research Journal of Computer Systems and Engineering, 2(2), 33:37. Retrieved from https://technicaljournals.org/RJCSE/index.php/journal/article/view/30
Sharma, S. ., Kumar, N. ., & Kaswan, K. S. . (2023). Hybrid Software Reliability Model for Big Fault Data and Selection of Best Optimizer Using an Estimation Accuracy Function . International Journal on Recent and Innovation Trends in Computing and Communication, 11(1), 26–37. https://doi.org/10.17762/ijritcc.v11i1.5984
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
All papers should be submitted electronically. All submitted manuscripts must be original work that is not under submission at another journal or under consideration for publication in another form, such as a monograph or chapter of a book. Authors of submitted papers are obligated not to submit their paper for publication elsewhere until an editorial decision is rendered on their submission. Further, authors of accepted papers are prohibited from publishing the results in other publications that appear before the paper is published in the Journal unless they receive approval for doing so from the Editor-In-Chief.
IJISAE open access articles are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. This license lets the audience to give appropriate credit, provide a link to the license, and indicate if changes were made and if they remix, transform, or build upon the material, they must distribute contributions under the same license as the original.
