This paper focuses on the speed control of a mill driven by an Asynchronous Motor (AM) powered by a solar photovoltaic energy source. As solar energy gains importance in the energy transition, artisanal mills are showing promise in improving rural life. However, speed variations caused by solar irradiance can affect their efficiency. The study proposes a comprehensive modeling of the system and explores advanced control strategies and optimization methods to optimize the performance. Traditional control approaches based on Foc and scalar strategies are examined, and the optimization considers the control and design parameters of the photovoltaic system. The results obtained by simulations in Simulink confirmed the performance of the strategies with good speed control regardless of the variation of load and irradiation.
References
[1]
Aouchiche, N., Aït Cheikh, M.S. and Malek, A. (2021) Tracking the Maximum Power Point of a Photovoltaic System by the Methods of Conductance Incrementation and Perturbation & Observation. Renewable Energy Review, 16, 485-498.
[2]
Doumbia, M.L. and Traoré, A. (2000) Modelling and Simulation of an Asynchronous Cage Machine Using Matlab/Simulink Software. https://ro.scribd.com/document/502417279/01-9
[3]
Robyns, B., Francois, B., Degobert, P. and Hautier J.P. (2018) Vector Control of Induction Machines. Springer. https://doi.org/10.1007/978-0-85729-901-7
[4]
Fatima, M. and Assia, H. (2024) Performances of an Asynchronous Motor Powered by a Photovoltaic Generator. Journal of Electrical Systems, 20, 2899-2908. https://journal.esrgroups.org/jes/article/view/7971
[5]
Yahya, A.O.M., Ould Mahmoud, A. and Youm, I. (2020) Study and Modeling of a Photovoltaic Generator. Renewable Energy Review, 11, 473-483.
[6]
Diop, M., Thiaw, L., Thiam, M., Mbodji, M. and Diaw, N. (2016) Efficient Control of a Three Induction Motor Driving a Craft Mill of Millet. International Journal of Scientific & Technology Research, 5, 88-91.
[7]
Ouali, A. and Tahri, M. (2018) Scalar Control of an Asynchronous Motor. https://dspace.ummto.dz/items/49a2d1ca-f111-4abe-803b-6771d287abff
[8]
Essakhi, H. and Farhat, S. (2019) Modeling and Simulation of a Photovoltaic Module. 5th International Materials and Environment Days (JIME 2019). https://www.researchgate.net/publication/332846895
[9]
Diop, M., Ba, O., Niang, B., Ngom, I. and Thiaw, L. (2020) A Methodology for Modeling Cereal Milling System. 2020 International Conference on Electrical, Communication, and Computer Engineering (ICECCE), Istanbul, 12-13 June 2020, 1-5. https://doi.org/10.1109/icecce49384.2020.9179182
[10]
Xu, D., Wang, B., Zhang, G., Wang, G. and Yu, Y. (2018) A Review of Sensorless Control Methods for AC Motor Drives. CES Transactions on Electrical Machines and Systems, 2, 104-115. https://doi.org/10.23919/tems.2018.8326456
[11]
Kurani, A., Doshi, P., Vakharia, A. and Shah, M. (2021) A Comprehensive Comparative Study of Artificial Neural Network (ANN) and Support Vector Machines (SVM) on Stock Forecasting. Annals of Data Science, 10, 183-208. https://doi.org/10.1007/s40745-021-00344-x
[12]
Sathishkumar, H. (2019) Performance Analysis of Speed Controller for 3hp and 150hp Three Phase Induction Motors Being Used in Cable Industry Applications. Asian Journal of Electrical Sciences, 8, 7-14. https://doi.org/10.51983/ajes-2019.8.1.2339
[13]
Akkouchi, K., Rahmani, L. and Lebied, R. (2021) New Application of Artificial Neural Network-Based Direct Power Control for Permanent Magnet Synchronous Generator. Electrical Engineering & Electromechanics, 6, 18-24. https://doi.org/10.20998/2074-272x.2021.6.03
[14]
Ali, A.J., Farej, Z. and Sultan, N. (2019) Performance Evaluation of a Hybrid Fuzzy Logic Controller Based on Genetic Algorithm for Three Phase Induction Motor Drive. International Journal of Power Electronics and Drive Systems (IJPEDS), 10, 117-127. https://doi.org/10.11591/ijpeds.v10.i1.pp117-127
[15]
Latif, S., Zou, Z., Idrees, Z. and Ahmad, J. (2020) A Novel Attack Detection Scheme for the Industrial Internet of Things Using a Lightweight Random Neural Network. IEEE Access, 8, 89337-89350. https://doi.org/10.1109/access.2020.2994079
[16]
Dybkowski, M. and Klimkowski, K. (2019) Artificial Neural Network Application for Current Sensors Fault Detection in the Vector Controlled Induction Motor Drive. Sensors, 19, Article 571. https://doi.org/10.3390/s19030571
[17]
Alhajeri, M.S., Luo, J., Wu, Z., Albalawi, F. and Christofides, P.D. (2022) Process Structure-Based Recurrent Neural Network Modeling for Predictive Control: A Comparative Study. ChemicalEngineeringResearchandDesign, 179, 77-89. https://doi.org/10.1016/j.cherd.2021.12.046
[18]
Mesai-Ahmed, H., Bentaallah, A., Cardoso, A.J.M., Djeriri, Y. and Jlassi, I. (2021) Robust Neural Control of the Dual Star Induction Generator Used in a Grid-Connected Wind Energy Conversion System. MathematicalModellingofEngineeringProblems, 8, 323-332. https://doi.org/10.18280/mmep.080301
[19]
Zeb, K., Uddin, W., Haider, A., Belal, S., Mehmood, C.A., Khan, M.A., et al. (2017) Robust Speed Regulation of Indirect Vector Control Induction Motor Using Fuzzy Logic Controllers Based on Optimization Algorithms. ElectricalEngineering, 100, 787-802. https://doi.org/10.1007/s00202-017-0553-z
[20]
Bana, P.R. and Amin, M. (2021) Adaptive Vector Control of Grid-Tied VSC Using Multilayer Perceptron-Recurrent Neural Network. IECON 2021—47th Annual Conference of the IEEE Industrial Electronics Society, Toronto, 13-16 October 2021, 1-6. https://doi.org/10.1109/iecon48115.2021.9589975
[21]
Benayad, N. and Tria, T.E. (2020) Application of Advanced Techniques for the Control of an Asynchronous Machine. University Echahid Cheikh Larbi Tebessi. http://oldspace.univ-tebessa.dz:8080/xmlui/handle/123456789/7266
[22]
Venu Gopal, B.T. and Shivakumar, E.G. (2018) Design and Simulation of Neuro-Fuzzy Controller for Indirect Vector-Controlled Induction Motor Drive. In: Nagabhushan, P., Guru, D., Shekar, B. and Kumar, Y., Eds., Data Analytics and Learning, Springer, 155-167. https://doi.org/10.1007/978-981-13-2514-4_14
[23]
Gupta, H., Varshney, H., Sharma, T.K., Pachauri, N. and Verma, O.P. (2021) Comparative Performance Analysis of Quantum Machine Learning with Deep Learning for Diabetes Prediction. Complex&IntelligentSystems, 8, 3073-3087. https://doi.org/10.1007/s40747-021-00398-7
[24]
Hannan, M.A., Ali, J.A., Ker, P.J., Mohamed, A., Lipu, M.S.H. and Hussain, A. (2018) Switching Techniques and Intelligent Controllers for Induction Motor Drive: Issues and Recommendations. IEEEAccess, 6, 47489-47510. https://doi.org/10.1109/access.2018.2867214
[25]
Khoei, H.R. and Zolfaghari, M. (2016) New Model Reference Adaptive System Speed Observer for Field-Oriented Control Induction Motor Drives Using Neural Networks. BulletinofElectricalEngineeringandInformatics, 5, 25-36. https://doi.org/10.11591/eei.v5i1.520
