APPLYING ARTIFICIAL INTELLIGENCE TO IMPROVE SAFETY AND THE MICROGRID CONTROLLING SYSTEM

Authors

  • Musulmonkul Imomali ugli Mamadaliyev Farg‘ona politexnika instituti assistenti
  • Tillokhon Abdusalyamova Farg‘ona politexnika instituti assistenti

Keywords:

microgrid, artificial intelligence, control systems, energy resilience, predictive analysis, machine learning, adaptive control, real-time monitoring.

Abstract

Microgrids, a newer form of power grid architecture, are gaining popularity among researchers and enterprises. The ability to integrate renewable generation, electric vehicles (EV), energy storage, and distributed energy resources into the power grid and connect them with effective communication links gives a potential to increase power grid efficiency.                                                                

References

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Usmonov, S., Iqbal, A., Saleem, A., Khosiljonovich, K. I., Odiljanovich, U. M., Khojiakbar, E., Ugli, A., Musulmonkul, M., & Ugli, I. (2024). Modelling and implementation of a photovoltaic system through improved voltage control mechanism. International Journal of Power Electronics and Drive Systems (IJPEDS), 15(1), 412–421. https://doi.org/10.11591/ijpeds.v15.i1.pp412-421

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Султанов Рузимаджон Анваржон Угли Рекомендации по выработке электроэнергии и компенсации потерянной энергии с помощью системы охлаждения электродвигателей // Вестник науки и образования. 2019. №19-3 (73). URL: https://cyberleninka.ru/article/n/rekomendatsii-po-vyrabotke-elektroenergii-i-kompensatsii-poteryannoy-energii-s-pomoschyu-sistemy-ohlazhdeniya-elektrodvigateley (дата обращения: 01.12.2023).

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Published

2023-12-22

How to Cite

Mamadaliyev , M. I. ugli, & Abdusalyamova , T. (2023). APPLYING ARTIFICIAL INTELLIGENCE TO IMPROVE SAFETY AND THE MICROGRID CONTROLLING SYSTEM. Educational Research in Universal Sciences, 2(17 SPECIAL), 801–804. Retrieved from http://erus.uz/index.php/er/article/view/5301