Enhancing DC microgrid performance with fuzzy logic control for hybrid energy storage system
Author:
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11760-024-03090-8.pdf
Reference34 articles.
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2. Machado, J.E., Rinaldi, G., Cucuzzella, M., Menon, P.P., Scherpen, J.M., Ferrara, A.: Online parameters estimation schemes to enhance control performance in DC microgrids. Eur. J. Control. (2023). https://doi.org/10.1016/j.ejcon.2023.100860
3. Poursafar, N., Taghizadeh, S., Hossain, M.J., Blaabjerg, F.: An enhanced control strategy for an ultra-fast EV charging station in a DC microgrid. Int. J. Electr. Power Energy Syst. 146, 108727 (2023). https://doi.org/10.1016/j.ijepes.2022.108727
4. Liu, Y., Qie, T., Zhang, X., Wang, H., Wei, Z., Iu, H.H., Fernando, T.: A novel learning-based data-driven H∞ control strategy for vanadium redox flow battery in DC microgrids. J. Power. Sources 583, 233537 (2023). https://doi.org/10.1016/j.jpowsour.2023.233537
5. Mohammed, N., Callegaro, L., Ciobotaru, M., Guerrero, J.M.: Accurate power sharing for islanded DC microgrids considering mismatched feeder resistances. Appl. Energy 340, 121060 (2023). https://doi.org/10.1016/j.apenergy.2023.121060
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