Hybrid MPPT Control: P&O and Neural Network for Wind Energy Conversion System
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B. Sarsembayev, K. Suleimenov, B. Mirzagalikova, and T. D. Do, “SDRE-Based Integral Sliding Mode Control for Wind Energy Conversion Systems,” IEEE Access, vol. 8, pp. 51100–51113, 2020, doi: 10.1109/access.2020.2980239.
J. Jurasz, F. A. Canales, A. Kies, M. Guezgouz, and A. Beluco, “A review on the complementarity of renewable energy sources: Concept, metrics, application and future research directions,” Solar Energy, vol. 195, pp. 703–724, Jan. 2020, doi: 10.1016/j.solener.2019.11.087.
M. Daneshvar, B. Mohammadi-Ivatloo, M. Abapour, S. Asadi, and R. Khanjani, “Distributionally Robust Chance-Constrained Transactive Energy Framework for Coupled Electrical and Gas Microgrids,” IEEE Transactions on Industrial Electronics, vol. 68, no. 1, pp. 347–357, Jan. 2021, doi: 10.1109/tie.2020.2965431.
S. Pira, "The Importance of Renewable Energies with Emphasize on Wind Power," International Journal of Engineering Research & Technology (Ijert), vol. 9, no. 6, 2020.
M. Chentouf and M. Allouch, “Analysis of environmental impacts of renewable energy on the Moroccan electricity sector: A System Dynamics approach,” E3S Web of Conferences, vol. 37, p. 03002, 2018, doi: 10.1051/e3sconf/20183703002.
A. Zhour, G. Sihem, and D. Djalel, “A New Approach to Fault Detection in the Power Converter in Wind Turbine Conversion Systems,” International Journal of Robotics and Control Systems, vol. 1, no. 4, pp. 428–439, Oct. 2021, doi: 10.31763/ijrcs. v1i4.443.
R. Alayi and J. Javad Velayti, “Modeling / Optimization and Effect of Environmental Variables on Energy Production Based on PV / Wind Turbine Hybrid System,” Jurnal Ilmiah Teknik Elektro Komputer dan Informatika, vol. 7, no. 1, p. 101, Apr. 2021, doi: 10.26555/jiteki. v7i1.20515.
T. Güney, “Non-renewable energy and sustainable development,” International Journal of Sustainable Development & World Ecology, Vol. 26, pp.389-397, 2019. https://doi.org/10.1080/13504509.2019.1595214
X. Zhou, M. Liu, Y. Ma, and S. Wen, “Improved Linear Active Disturbance Rejection Controller Control Considering Bus Voltage Filtering in Permanent Magnet Synchronous Generator,” IEEE Access, vol. 8, pp. 19982–19996, 2020, doi: 10.1109/access.2020.2967395.
J.-S. Lee, K.-B. Lee, and F. Blaabjerg, “Predictive Control With Discrete Space-Vector Modulation of Vienna Rectifier for Driving PMSG of Wind Turbine Systems,” IEEE Transactions on Power Electronics, vol. 34, no. 12, pp. 12368–12383, Dec. 2019, doi: 10.1109/tpel.2019.2905843.
K. Okedu, “Impact of power converter size on variable speed wind turbines,” Onshore Wind Farms, pp. 7-1-7–8, 2021, doi: 10.1063/9780735422995_007.
W. Yang and J. Yang, “Advantage of variable-speed pumped storage plants for mitigating wind power variations: Integrated modelling and performance assessment,” Applied Energy, vol. 237, pp. 720–732, Mar. 2019, doi: 10.1016/j.apenergy.2018.12.090.
M. Ayadi, “High-order sliding mode control for variable speed PMSG wind turbine based disturbance observer,” International Journal of Modelling, Identification and Control, vol. 1, no. 1, p. 1, 2019, doi: 10.1504/ijmic.2019.10023119.
C. Hung Tran, F. Nollet, N. Essounbouli, and A. Hamzaoui, “Maximum power point tracking techniques for wind energy systems using three levels boost converter,” IOP Conference Series: Earth and Environmental Science, vol. 154, p. 012016, May 2018, doi: 10.1088/1755-1315/154/1/012016.
S. Rhaili et al., “Robust Sliding Mode Control with Five Sliding Surfaces of Five-Phase PMSG Based Variable Speed Wind Energy Conversion System,” International Journal of Intelligent Engineering and Systems, vol. 13, no. 4, pp. 346–357, Aug. 2020, doi: 10.22266/ijies2020.0831.30.
Y. Yusong and E. Solomin, “The Control Strategy and Simulation of the Yaw System for MW Rated Wind Turbine,” 2020 Russian Workshop on Power Engineering and Automation of Metallurgy Industry: Research & Practice (PEAMI), Sep. 2020, doi: 10.1109/peami49900.2020.9234343.
A. S. Samosir and A. Riszal, “The effect analysis of wind speed variation to the horizontal axis wind turbine design with Q-blade,” IOP Conference Series: Materials Science and Engineering, vol. 1173, no. 1, p. 012009, Aug. 2021, doi: 10.1088/1757-899x/1173/1/012009.
P. Sudwilai, “A Design and Development of P I Controlled Based MPPT for Photovoltaic Systems,” 2018 21st International Conference on Electrical Machines and Systems (ICEMS), Oct. 2018, doi: 10.23919/icems.2018.8549278.
M. Hannachi, O. Elbeji, M. Benhamed, and L. Sbita, “Maximum power point tracking of a PMSG wind turbine with On-Off control-based particle swarm optimization,” 2019 International Conference on Signal, Control and Communication (SCC), Dec. 2019, doi: 10.1109/scc47175.2019.9116142.
F. Mohd Zaihidee, S. Mekhilef, and M. Mubin, “Robust Speed Control of PMSM Using Sliding Mode Control (SMC)—A Review,” Energies, vol. 12, no. 9, p. 1669, May 2019, doi: 10.3390/en12091669.
S. G. Karad and R. Thakur, “Fractional order controller based maximum power point tracking controller for wind turbine system,” International Journal of Electronics, vol. 109, no. 5, pp. 875–899, Jul. 2021, doi: 10.1080/00207217.2021.1941296.
X. Zhang, Z. Zhang, J. Jia, and L. Zheng, “A Maximum Power Point Tracking Control Method Based on Rotor Speed PDF Shape for Wind Turbines,” Applied Sciences, vol. 12, no. 18, p. 9108, Sep. 2022, doi: 10.3390/app12189108.
A. E. Yaakoubi, L. Amhaimar, K. Attari, M. H. Harrak, M. E. Halaoui, and A. Asselman, “Non-linear and intelligent maximum power point tracking strategies for small size wind turbines: Performance analysis and comparison,” Energy Reports, vol. 5, pp. 545–554, Nov. 2019, doi: 10.1016/j.egyr.2019.03.001.
M. B. Hemanth Kumar, B. Saravanan, P. Sanjeevikumar, and F. Blaabjerg, “Review on control techniques and methodologies for maximum power extraction from wind energy systems,” IET Renewable Power Generation, vol. 12, no. 14, pp. 1609–1622, Sep. 2018, doi: 10.1049/iet-rpg.2018.5206.
K. Palanimuthu, G. Mayilsamy, S. R. Lee, S. Y. Jung, and Y. H. Joo, “Comparative analysis of maximum power extraction and control methods between PMSG and PMVG-based wind turbine systems,” International Journal of Electrical Power & Energy Systems, vol. 143, p. 108475, Dec. 2022, doi: 10.1016/j.ijepes.2022.108475.
M. Hannachi, O. Elbeji, M. Benhamed, and L. Sbita, “Comparative study of four MPPT for a wind power system,” Wind Engineering, vol. 45, no. 6, pp. 1613–1622, May 2021, doi: 10.1177/0309524x21995946.
C. Voloşencu, “A Comparative Analysis of Some Methods for Wind Turbine Maximum Power Point Tracking,” Mathematics, vol. 9, no. 19, p. 2399, Sep. 2021, doi: 10.3390/math9192399.
M. El Malah, A. Barazzouk, E. Abdelmounim, and M. Madark, “Robust Nonlinear Sensorless MPPT Control with Unity Power Factor for Grid Connected DFIG Wind Turbines,” International Review on Modelling and Simulations (IREMOS), vol. 11, no. 5, p. 313, Oct. 2018, doi: 10.15866/iremos.v11i5.15018.
M. Karabacak, “A new perturb and observe based higher order sliding mode MPPT control of wind turbines eliminating the rotor inertial effect,” Renewable Energy, vol. 133, pp. 807–827, Apr. 2019, doi: 10.1016/j.renene.2018.10.079.
M. G. Mousa, S. M. Allam, and E. M. Rashad, “Maximum power extraction under different vector-control schemes and grid-synchronization strategy of a wind-driven Brushless Doubly-Fed Reluctance Generator,” ISA Transactions, vol. 72, pp. 287–297, Jan. 2018, doi: 10.1016/j.isatra.2017.10.005.
E. Kandemir, S. Borekci, and N. S. Cetin, “Conventional and Soft-Computing Based MPPT Methods Comparisons in Direct and Indirect Modes for Single Stage PV Systems,” Elektronika ir Elektrotechnika, vol. 24, no. 4, Aug. 2018, doi: 10.5755/j01.eie.24.4.21477.
Y. Sahri, S. Tamalouzt, and S. Belaid Lalouni, “Enhanced Direct Power Control Strategy of a DFIG-Based Wind Energy Conversion System Operating Under Random Conditions,” Periodica Polytechnica Electrical Engineering and Computer Science, vol. 65, no. 3, pp. 196–206, Jun. 2021, doi: 10.3311/ppee.16656.
J. Castelló, J. M. Espí, and R. García-Gil, “Development details and performance assessment of a Wind Turbine Emulator,” Renewable Energy, vol. 86, pp. 848–857, Feb. 2016, doi: 10.1016/j.renene.2015.09.010.
Errami, M. Ouassaid, and M. Maaroufi, “Optimal Power Control Strategy of Maximizing Wind Energy Tracking and Different Operating Conditions for Permanent Magnet Synchronous Generator Wind Farm,” Energy Procedia, vol. 74, pp. 477–490, Aug. 2015, doi: 10.1016/j.egypro.2015.07.732.
J. Liu, H. Meng, Y. Hu, Z. Lin, and W. Wang, “A novel MPPT method for enhancing energy conversion efficiency taking power smoothing into account,” Energy Conversion and Management, vol. 101, pp. 738–748, Sep. 2015, doi: 10.1016/j.enconman.2015.06.005.
B. Meghni, H. Chojaa, and A. Boulmaiz, “An Optimal Torque Control based on Intelligent Tracking Range (MPPT-OTC-ANN) for Permanent Magnet Direct Drive WECS,” 2020 IEEE 2nd International Conference on Electronics, Control, Optimization and Computer Science (ICECOCS), Dec. 2020, doi: 10.1109/icecocs50124.2020.9314304.
O. Zebraoui and M. Bouzi, “Comparative study of different MPPT methods for wind energy conversion system,” IOP Conference Series: Earth and Environmental Science, vol. 161, p. 012023, Jun. 2018, doi: 10.1088/1755-1315/161/1/012023.
Pande, P. Nasikkar, K. Kotecha, and V. Varadarajan, “A Review of Maximum Power Point Tracking Algorithms for Wind Energy Conversion Systems,” Journal of Marine Science and Engineering, vol. 9, no. 11, p. 1187, Oct. 2021, doi: 10.3390/jmse9111187.
D. Kumar and K. Chatterjee, “A review of conventional and advanced MPPT algorithms for wind energy systems,” Renewable and Sustainable Energy Reviews, vol. 55, pp. 957–970, Mar. 2016, doi: 10.1016/j.rser.2015.11.013.
K. Karthi, R. Radhakrishnan, JM. Baskaran, and L. S. Titus, “Analysis of Adaptive MPPT Control Algorithm for Direct Driven Permanent Magnet Synchronous Generator,” 2019 2nd International Conference on Power and Embedded Drive Control (ICPEDC), Aug. 2019, doi: 10.1109/icpedc47771.2019.9036708.
D. Cortes-Vega, F. Ornelas-Tellez, and J. Anzurez-Marin, “Comparative analysis of MPPT techniques and Optimal Control for a PMSG-based WECS,” 2019 IEEE 4th Colombian Conference on Automatic Control (CCAC), Oct. 2019, doi: 10.1109/ccac.2019.8921183.
M. Zine, A. Chemsa, C. Labiod, M. Ikhlef, K. Srairi, and M. Benbouzid, “Coupled Indirect Torque Control and Maximum Power Point Tracking Technique for Optimal Performance of 12/8 Switched Reluctance Generator-Based Wind Turbines,” Machines, vol. 10, no. 11, p. 1046, Nov. 2022, doi: 10.3390/machines10111046.
M. B. Hemanth Kumar, B. Saravanan, P. Sanjeevikumar, and F. Blaabjerg, “Review on control techniques and methodologies for maximum power extraction from wind energy systems,” IET Renewable Power Generation, vol. 12, no. 14, pp. 1609–1622, Sep. 2018, doi: 10.1049/iet-rpg.2018.5206.
M. Hossam H. H., A.-R. Youssef, and M. Essam E. M., “Improved Perturb and Observe MPPT Algorithm of Multi-Phase PMSG Based Wind Energy Conversion System,” 2019 21st International Middle East Power Systems Conference (MEPCON), Dec. 2019, doi: 10.1109/mepcon47431.2019.9008004.
S. Azzouz, S. Messalti, and A. Harrag, “A Novel Hybrid MPPT Controller Using (P&O)-neural Networks for Variable Speed Wind Turbine Based on DFIG,” Modelling, Measurement and Control A, vol. 92, no. 1, pp. 23–29, Mar. 2019, doi: 10.18280/mmc_a.920104.
K. Saidi, M. Maamoun, and M. Bounekhla, “Simulation and analysis of variable step size P&O MPPT algorithm for photovoltaic power control,” 2017 International Conference on Green Energy Conversion Systems (GECS), Mar. 2017, doi: 10.1109/gecs.2017.8066265.
P. K. Gupta, “Optimized Fuzzy Logic Solar Module MPPT Controller Modelling using PSO,” International Journal of Emerging Trends in Engineering Research, vol. 8, no. 8, pp. 4220–4225, Aug. 2020, doi: 10.30534/ijeter/2020/30882020.
Soedibyo, M. Ridwan, A. Pradipta, S. Anam, and M. Ashari, “Comparison of P&O and inceremental conductance based maximum power point tracking for wind turbine application in remote area (Case study: Gili genting Island, Madura, East Java, Indonesia),” 2018 IEEE International Conference on Innovative Research and Development (ICIRD), May 2018, doi: 10.1109/icird.2018.8376298.
A. Borni, N. Bouarroudj, A. Bouchakour, and L. Zaghba, “P&O-PI and fuzzy-PI MPPT Controllers and their time domain optimization using PSO and GA for grid-connected photovoltaic system: a comparative study,” International Journal of Power Electronics, vol. 8, no. 4, p. 300, 2017, doi: 10.1504/ijpelec.2017.085199.
A. Harrag and S. Messalti, “Variable step size modified P&O MPPT algorithm using GA-based hybrid offline/online PID controller,” Renewable and Sustainable Energy Reviews, vol. 49, pp. 1247–1260, Sep. 2015, doi: 10.1016/j.rser.2015.05.003.
A. G. Abo-Khalil, A. M. Eltamaly, P. R.P., A. S. Alghamdi, and I. Tlili, “A Sensorless Wind Speed and Rotor Position Control of PMSG in Wind Power Generation Systems,” Sustainability, vol. 12, no. 20, p. 8481, Oct. 2020, doi: 10.3390/su12208481.
H. H. H. Mousa, A.-R. Youssef, and E. E. M. Mohamed, “Hybrid and adaptive sectors P&O MPPT algorithm based wind generation system,” Renewable Energy, vol. 145, pp. 1412–1429, Jan. 2020, doi: 10.1016/j.renene.2019.06.078.
I. Toumi et al., “Robust Variable-Step Perturb-and-Observe Sliding Mode Controller for Grid-Connected Wind-Energy-Conversion Systems,” Entropy, vol. 24, no. 5, p. 731, May 2022, doi: 10.3390/e24050731.
X. Zhang, D. Gamage, B. Wang, and A. Ukil, “Hybrid Maximum Power Point Tracking Method Based on Iterative Learning Control and Perturb & Observe Method,” 2021 IEEE Power & Energy Society General Meeting (PESGM), Jul. 2021, doi: 10.1109/pesgm46819.2021.9638241.
M. Mohammadinodoushan, R. Abbassi, H. Jerbi, F. Waly Ahmed, H. Abdalqadir kh ahmed, and A. Rezvani, “A new MPPT design using variable step size perturb and observe method for PV system under partially shaded conditions by modified shuffled frog leaping algorithm- SMC controller,” Sustainable Energy Technologies and Assessments, vol. 45, p. 101056, Jun. 2021, doi: 10.1016/j.seta.2021.101056.
H. H. H. Mousa, A.-R. Youssef, and E. E. M. Mohamed, “State of the art perturb and observe MPPT algorithms based wind energy conversion systems: A technology review,” International Journal of Electrical Power &Energy Systems, vol. 126, p. 106598, Mar. 2021, doi: 10.1016/j.ijepes.2020.106598.
H. E. Aissaoui, A. E. Ougli, and B. Tidhaf, “Neural Networks and Fuzzy Logic Based Maximum Power Point Tracking Control for Wind Energy Conversion System,” Advances in Science, Technology and Engineering Systems Journal, vol. 6, no. 2, pp. 586–592, Mar. 2021, doi: 10.25046/aj060267.
A. Asgharnia, R. Shahnazi, and A. Jamali, “Performance and robustness of optimal fractional fuzzy PID controllers for pitch control of a wind turbine using chaotic optimization algorithms,” ISA Transactions, vol. 79, pp. 27–44, Aug. 2018, doi: 10.1016/j.isatra.2018.04.016.
H. Gouabi, A. Hazzab, M. Habbab, M. Rezkallah, and A. Chandra, “Experimental implementation of a novel scheduling algorithm for adaptive and modified P&O MPPT controller using fuzzy logic for WECS,” International Journal of Adaptive Control and Signal Processing, vol. 35, no. 9, pp. 1732–1753, Jun. 2021, doi: 10.1002/acs.3288.
M. J. Khan, “An AIAPO MPPT controller based real time adaptive maximum power point tracking technique for wind turbine system,” ISA Transactions, vol. 123, pp. 492–504, Apr. 2022, doi: 10.1016/j.isatra.2021.06.008.
R. Tiwari, K. Krishnamurthy, R. Neelakandan, S. Padmanaban, and P. Wheeler, “Neural Network Based Maximum Power Point Tracking Control with Quadratic Boost Converter for PMSG—Wind Energy Conversion System,” Electronics, vol. 7, no. 2, p. 20, Feb. 2018, doi: 10.3390/electronics7020020.
A. V. Hemeyine, A. Abbou, A. Bakouri, M. Mokhlis, and S. M. ould M. El Moustapha, “A Robust Interval Type-2 Fuzzy Logic Controller for Variable Speed Wind Turbines Based on a Doubly Fed Induction Generator,” Inventions, vol. 6, no. 2, p. 21, Mar. 2021, doi: 10.3390/inventions6020021.
K. J. Rathi and M. S. Ali, “Neural Network Controller for Power Electronics Circuits,” IAES International Journal of Artificial Intelligence (IJ-AI), vol. 6, no. 2, p. 49, Jun. 2017, doi: 10.11591/ijai.v6.i2.pp49-55.
W. I. Hameed, B. A. Sawadi, and A. Muayed, “Voltage Tracking Control of DC- DC Boost Converter Using Fuzzy Neural Network,” International Journal of Power Electronics and Drive Systems (IJPEDS), vol. 9, no. 4, p. 1657, Dec. 2018, doi: 10.11591/ijpeds.v9.i4.pp1657-1665.
J. E. Sierra-Garcia and M. Santos, “Improving Wind Turbine Pitch Control by Effective Wind Neuro-Estimators,” IEEE Access, vol. 9, pp. 10413–10425, 2021, doi: 10.1109/access.2021.3051063.
S. E. RHAILI, A. ABBOU, N. E. HICHAMI, and S. MARHRAOUI, “A New Strategy Based Neural Networks MPPT Controller for Five-phase PMSG Based Variable-Speed Wind Turbine,” 2018 7th International Conference on Renewable Energy Research and Applications (ICRERA), Oct. 2018, doi: 10.1109/icrera.2018.8566822.
A. Dahbi, N. Nait-Said, and M.-S. Nait-Said, “A novel combined MPPT-pitch angle control for wide range variable speed wind turbine based on neural network,” International Journal of Hydrogen Energy, vol. 41, no. 22, pp. 9427–9442, Jun. 2016, doi: 10.1016/j.ijhydene.2016.03.105.
T. K. Nizami and A. Chakravarty, “Neural Network Integrated Adaptive Backstepping Control of DC-DC Boost Converter,” IFAC-PapersOnLine, vol. 53, no. 1, pp. 549–554, 2020, doi: 10.1016/j.ifacol.2020.06.092.
P. Bhatia, S. Mittal, S. Raizada, and V. Verma, “Hybrid ANN based Incremental Conductance MPPT-Current Control Algorithm for Constant Power Generation of PV fed DC Microgrid,” 2020 IEEE First International Conference on Smart Technologies for Power, Energy and Control (STPEC), Sep. 2020, doi: 10.1109/stpec49749.2020.9297751.
S. Srinivasan, R. Tiwari, M. Krishnamoorthy, M. P. Lalitha, and K. K. Raj, “Neural network based MPPT control with reconfigured quadratic boost converter for fuel cell application,” International Journal of Hydrogen Energy, vol. 46, no. 9, pp. 6709–6719, Feb. 2021, doi: 10.1016/j.ijhydene.2020.11.121.
M. Fathi and J. A. Parian, “Intelligent MPPT for photovoltaic panels using a novel fuzzy logic and artificial neural networks based on evolutionary algorithms,” Energy Reports, vol. 7, pp. 1338–1348, Nov. 2021, doi: 10.1016/j.egyr.2021.02.051.
H. Chojaa, A. Derouich, S. E. Chehaidia, O. Zamzoum, M. Taoussi, and H. Elouatouat, “Integral sliding mode control for DFIG based WECS with MPPT based on artificial neural network under a real wind profile,” Energy Reports, vol. 7, pp. 4809–4824, Nov. 2021, doi: 10.1016/j.egyr.2021.07.066.
S. Afrasiabi, M. Afrasiabi, B. Parang, M. Mohammadi, M. M. Arefi, and M. Rastegar, “Wind Turbine Fault Diagnosis with Generative-Temporal Convolutional Neural Network,” 2019 IEEE International Conference on Environment and Electrical Engineering and 2019 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe), Jun. 2019, doi: 10.1109/eeeic.2019.8783233.
M. Lwin and H. Lin, “Neural network based high-performance double boost DC-DC converter in using renewable energy system,” Int. Journal of Science, Engineering and Technology Research, vol. 7, is. 5, pp. 337– 339, 2018.
H. Gaied et al., “Comparative analysis of MPPT techniques for enhancing a wind energy conversion system,” Frontiers in Energy Research, vol. 10, Aug. 2022, doi: 10.3389/fenrg.2022.975134.
A. G. Abo-Khalil, A. Sobhy, and K. Sayed, “Multiple Linear Regression Approach for Sensorless MPPT of PMSG Wind Power Generation Systems,” Nov. 2022, doi: 10.21203/rs.3.rs-2250710/v1.
Y. Belgaid, M. Helaimi, R. Taleb, and M. Benali Youcef, “Optimal tuning of PI controller using genetic algorithm for wind turbine application,” Indonesian Journal of Electrical Engineering and Computer Science, vol. 18, no. 1, p. 167, Apr. 2020, doi: 10.11591/ijeecs. v18.i1. pp167-178.
S. Subramanian, C. Sankaralingam, R. M. Elavarasan, R. R. Vijayaraghavan, K. Raju, and L. Mihet-Popa, “An Evaluation on Wind Energy Potential Using Multi-Objective Optimization Based Non-Dominated Sorting Genetic Algorithm III,” Sustainability, vol. 13, no. 1, p. 410, Jan. 2021, doi: 10.3390/su13010410.
S. Hadji, J.-P. Gaubert, and F. Krim, “Real-Time Genetic Algorithms-Based MPPT: Study and Comparison (Theoretical an Experimental) with Conventional Methods,” Energies, vol. 11, no. 2, p. 459, Feb. 2018, doi: 10.3390/en11020459.
N. Priyadarshi, S. Padmanaban, M. S. Bhaskar, F. Blaabjerg, and J. B. Holm‐Nielsen, “An improved hybrid PV‐wind power system with MPPT for water pumping applications,” International Transactions on Electrical Energy Systems, vol. 30, no. 2, Nov. 2019, doi: 10.1002/2050-7038.12210.
K. Premkumar, M. Vishnupriya, T. Thamizhselvan, P. Sanjeevikumar, and B. Manikandan, “PSO optimized PI controlled DC‐DC buck converter‐based proton‐exchange membrane fuel cell emulator for testing of MPPT algorithm and battery charger controller.” International Transactions on Electrical Energy Systems, vol. 31, no. 2, 2020, doi: 10.1002/2050-7038.12754.
D. Wang, D. Tan, and L. Liu, “Particle swarm optimization algorithm: an overview,” Soft Computing, vol. 22, no. 2, pp. 387–408, Jan. 2017, doi: 10.1007/s00500-016-2474-6.
N. Bounar, S. Labdai, and A. Boulkroune, “PSO–GSA based fuzzy sliding mode controller for DFIG-based wind turbine,” ISA Transactions, vol. 85, pp. 177–188, Feb. 2019, doi: 10.1016/j.isatra.2018.10.020.
Y. Mokhtari and D. Rekioua, “High performance of Maximum Power Point Tracking Using Ant Colony algorithm in wind turbine,” Renewable Energy, vol. 126, pp. 1055–1063, Oct. 2018, doi: 10.1016/j.renene.2018.03.049.
N. Priyadarshi, V. Ramachandaramurthy, S. Padmanaban, and F. Azam, “An Ant Colony Optimized MPPT for Standalone Hybrid PV-Wind Power System with Single Cuk Converter,” Energies, vol. 12, no. 1, p. 167, Jan. 2019, doi: 10.3390/en12010167.
A. H. Sule, “Optimal PI Pitch Control of Doubly-Fed Induction Generator Wind Turbine for Enhancing Dynamic Stability Using Grey Wolf Optimizer,” Direct Research Journal of Engineering and Information Technology, vol. 9, no. 1, p. 1, Feb. 2022, doi: 10.26765/drjeit13263772.
I. Dagal, B. Akın, and E. Akboy, “MPPT mechanism based on novel hybrid particle swarm optimization and salp swarm optimization algorithm for battery charging through simulink,” Scientific Reports, vol. 12, no. 1, Feb. 2022, doi: 10.1038/s41598-022-06609-6.
S. Sabzevari, A. Karimpour, M. Monfared, and M. B. Naghibi Sistani, “MPPT control of wind turbines by direct adaptive fuzzy-PI controller and using ANN-PSO wind speed estimator,” Journal of Renewable and Sustainable Energy, vol. 9, no. 1, p. 013302, Jan. 2017, doi: 10.1063/1.4973447.
A. Loukatou, S. Howell, P. Johnson, and P. Duck, “Stochastic wind speed modelling for estimation of expected wind power output,” Applied Energy, vol. 228, pp. 1328–1340, Oct. 2018, doi: 10.1016/j.apenergy.2018.06.117.
G. Notton et al., “Intermittent and stochastic character of renewable energy sources: Consequences, cost of intermittence and benefit of forecasting,” Renewable and Sustainable Energy Reviews, vol. 87, pp. 96–105, May 2018, doi: 10.1016/j.rser.2018.02.007.
I. L. R. GOMES, R. MELICIO, V. M. F. MENDES, and H. M. I. POUSINHO, “Wind Power with Energy Storage Arbitrage in Day-ahead Market by a Stochastic MILP Approach,” Logic Journal of the IGPL, vol. 28, no. 4, pp. 570–582, Dec. 2019, doi: 10.1093/jigpal/jzz054.
M. Á. Rodríguez-López, E. Cerdá, and P. del Rio, “Modeling Wind-Turbine Power Curves: Effects of Environmental Temperature on Wind Energy Generation,” Energies, vol. 13, no. 18, p. 4941, Sep. 2020, doi: 10.3390/en13184941.
Louassa, O. Guerri, A. Kaabeche, and N. Yassaa, “Effects of local ambient air temperatures on wind park performance: case of the Kaberten wind park,” Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, pp. 1–14, Oct. 2019, doi: 10.1080/15567036.2019.1673509.
S. Ghoudelbourk, D. Dib, A. Omeiri, and A. T. Azar, “MPPT control in wind energy conversion systems and the application of fractional control (PIα) in pitch wind turbine,” International Journal of Modelling, Identification and Control, vol. 26, no. 2, p. 140, 2016, doi: 10.1504/ijmic.2016.078329.
Y. Song, J. Chen, M. Beer, and L. Comerford, “Wind Speed Field Simulation via Stochastic Harmonic Function Representation Based on Wavenumber–Frequency Spectrum,” Journal of Engineering Mechanics, vol. 145, no. 11, Nov. 2019, doi: 10.1061/(asce)em.1943-7889.0001666.
A. T. Azar and F. E. Serrano, “Design and Modeling of Anti Wind Up PID Controllers,” Studies in Fuzziness and Soft Computing, pp. 1–44, Nov. 2014, doi: 10.1007/978-3-319-12883-2_1.
S. Das, I. Pan, S. Das, and A. Gupta, “A novel fractional order fuzzy PID controller and its optimal time domain tuning based on integral performance indices,” Engineering Applications of Artificial Intelligence, vol. 25, no. 2, pp. 430–442, Mar. 2012, doi: 10.1016/j.engappai.2011.10.004.
O. Carranza, E. Figueres, G. Garcerá, and R. Gonzalez-Medina, “Analysis of the control structure of wind energy generation systems based on a permanent mag-net synchronous generator,” Applied Energy, vol. 103, pp. 522–538, Mar. 2013, doi: 10.1016/j.apenergy.2012.10.015.
M. Carpintero‐Renteria, D. Santos‐Martin, A. Lent, and C. Ramos, “Wind turbine power coefficient models based on neural networks and polynomial fitting,” IET Renewable Power Generation, vol. 14, no. 11, pp. 1841–1849, Jul. 2020, doi: 10.1049/iet-rpg.2019.1162.
B. Majout et al., “A Review on Popular Control Applications in Wind Energy Conversion System Based on Permanent Magnet Generator PMSG,” Energies, vol. 15, no. 17, p. 6238, Aug. 2022, doi: 10.3390/en15176238.
A. Herizi and R. Rouabhi, “Hybrid Control Using Sliding Mode Control with Interval Type-2 Fuzzy Controller of a Doubly Fed Induction Generator for Wind Energy Conversion,” International Journal of Intelligent Engineering and Systems, vol. 15, no. 1, pp. 550-564, Feb. 2022, doi: 10.22266/ijies2022.0228.50.
M. Zafran, L. Khan, Q. Khan, S. Ullah, I. Sami, and J.-S. Ro, “Finite-Time Fast Dynamic Terminal Sliding Mode Maximum Power Point Tracking Control Paradigm for Permanent Magnet Synchronous Generator-Based Wind Energy Conversion System,” Applied Sciences, vol. 10, no. 18, p. 6361, Sep. 2020, doi: 10.3390/app10186361.
E. H. Dursun and A. A. Kulaksiz, “Second-order sliding mode voltage-regulator for improving MPPT efficiency of PMSG-based WECS,” International Journal of Electrical Power & Energy Systems, vol. 121, p. 106149, Oct. 2020, doi: 10.1016/j.ijepes.2020.106149.
O. Apata and D. T. O. Oyedokun, “An overview of control techniques for wind turbine systems,” Scientific African, vol. 10, p. e00566, Nov. 2020, doi: 10.1016/j.sciaf.2020.e00566.
M. J. Khan and L. Mathew, “Comparative Study of Optimization Techniques for Renewable Energy System,” Archives of Computational Methods in Engineering, vol. 27, no. 2, pp. 351–360, Dec. 2018, doi: 10.1007/s11831-018-09306-8.
R. B. Bollipo, S. Mikkili, and P. K. Bonthagorla, “Critical Review on PV MPPT Techniques: Classical, Intelligent and Optimisation,” IET Renewable Power Generation, vol. 14, no. 9, pp. 1433–1452, Jun. 2020, doi: 10.1049/iet-rpg.2019.1163.
A. Rezvani, A. Esmaeily, H. Etaati, and M. Mohammadinodoushan, “Intelligent hybrid power generation system using new hybrid fuzzy-neural for photovoltaic system and RBFNSM for wind turbine in the grid connected mode,” Frontiers in Energy, vol. 13, no. 1, pp. 131–148, Mar. 2017, doi: 10.1007/s11708-017-0446-x.
S. Motahhir, A. El Hammoumi, and A. El Ghzizal, “The most used MPPT algorithms: Review and the suitable low-cost embedded board for each algorithm,” Journal of Cleaner Production, vol. 246, p. 118983, Feb. 2020, doi: 10.1016/j.jclepro.2019.118983.
DOI: https://doi.org/10.18196/jrc.v4i1.16770
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Journal of Robotics and Control (JRC)
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