Application of Artificial Intelligent Techniques for Power Quality Improvement in Microgrid System
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Abstract
This paper focuses on modeling, control and power quality improvement of a microgrid connected system. This last was designed as a multi-converter system with Wind Turbine driven Permanent Magnet Synchronous Generator, and lithium ion Battery Storage Energy System. These sources are connected by a continuous bus to a nonlinear load through a DC /AC converter and three-phases multi-functional voltage source inverter. Where, wind systems are considered as primary power resource, and the grid is used for the effect of consumption of the overage power available from sources, when the battery has been fully charged. Multi Functional Voltage Source Inverter is used to ameliorate the performance of the proposed system, guaranteeing both reactive power and harmonic compensation. Moreover an intelligent control by fuzzy logic control algorithm are managed In order to extract the maximum power from wind turbine, to guarantee an effective storage management, this about the DC side. For the AC side a direct power control strategy with fuzzy logic algorithm have been used. The simulation of the system solution is carried out in Matlab/Simulink. The obtained simulation results show that the technique of fuzzy logic furnish the best solution in term of robustness, optimization performance, low THD and fast dynamic response.
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References
Adineh, B., Keypour, R., Davari, P., & Blaabierg, F. (2021). Review of Harmonic mitigation Methods in Microgrid : From a Hierarchical Control Perspective. IEEE Journal of Emerging and Selected Topics in Power Electronics, 9(3), 3044-3060. https://doi.org/10.1109/JESTPE.2020.3001971
Aissou, S., Rekioua, D., Mezzai, N., Rekioua, T., & Bacha, S. (2015). Modeling and control of hybrid photovoltaic wind power system with battery storage. Energy Conversion and Management, 89 615-625. https://doi.org/10.1016/j.enconman.2014.10.034
Das, S. R., Mishra, A. K., Ray, P. K., Salkuti, S. R., & Kim, S.-C. (2022). Application of Artificial Intelligent Techniques for Power Quality Improvement in Hybrid Microgrid System. Electronics, 11(22), 3826. https://doi.org/10.3390/electronics11223826
Debbouche, N., Laid, Z., Ali, C., & Ouchen, S. (2022). DPC-SVM Controlled Strategy for a Three-level Shunt Active Power Filter Grid Connected photovoltaic system Optimized by super TwistingSliding Mode technique. In M. Hatti (Ed), Artificial Intelligence and Heuristics for Smart Energy Efficiency in Smart Cities (vol. 361, p. 245-255). Springer international publishing. https://doi.org/10.1007/978-3-030-92038-8_25
Feng, W., Sun, K., Guan, Y., Guerrero, J. M., & Xiao, X. (2018). Active power quality Improvement Strategy for Grid-Connected Microgrid Based on hierarchical Control. IEEE Transactions on Smart grid, 9(4), 3486-3495. https://doi.org/10.1109/TSG.2016.2633298
Gajewski, P., & Pienkowski, K. (2021). Control of the Hybrid Renewable Energy System with Wind Turbine, Photovoltaic Panels and Battery Energy Storage. Energies, 14(6), 1595. https://doi.org/10.3390/en14061595
Lee, H.-J., Vu, B. H., Zafar, R., Hwang, S.-W., & Chung, I.-Y. (2021). Design Framework of a Stand-Alone Microgrid Considering Power System Performance and Economic Efficiency. Energies, 14(2), 457. https://doi.org/10.3390/en14020457
Madaci, B., Chenni, R., Kurt, E., & Hemsas, K. E. (2016). Design and control of a stand-alone hybrid power system. International Journal of Hydrogen Energy, 41(29), 12485-12496. https://doi.org/10.1016/j.ijhydene.2016.01.117
Mezzai, N., Rekioua, D., Rekioua, T., Mohammedi, A., Idjdarane, K., & Bacha, S. (2014). Modeling of hybrid photovoltaic/wind/fuel cells power system. International Journal of Hydrogen Energy, 39(27), 15158-15168. https://doi.org/10.1016/j.ijhydene.2014.06.015
Vlad, C. (2013). Commande prédictive des systèmes hybrides et application à la commande de systèmes en électronique de puissance. [Phdthesis, Supélec]. https://tel.archives-ouvertes.fr/tel-00817487