AI-Driven Energy Management Systems for Microgrids: Optimizing Renewable Energy Integration and Load Balancing

AI-Driven Energy Management Systems for Microgrids: Optimizing Renewable Energy Integration and Load Balancing

The increasing adoption of microgrids, particularly with renewable energy sources, necessitates advanced energy management systems (EMS) that can efficiently handle dynamic power demands and supply fluctuations. This paper proposes an AI-driven EMS model specifically designed for optimizing energy d...

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Bibliographic Details
Main Authors: Bhardwaj Diwakar, M Shalini, Kanmani Jebaseeli S., Jadhav Swati, Alabdeli Haider, Sutar Vasundhara, Senthil Kumar R.
Format: Article
Language:English
Published: EDP Sciences 2024-01-01
Series:E3S Web of Conferences
Subjects:
ai-driven ems
microgrids
renewable energy integration
load balancing
machine learning
Online Access:https://www.e3s-conferences.org/articles/e3sconf/pdf/2024/121/e3sconf_icrera2024_01005.pdf
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https://www.e3s-conferences.org/articles/e3sconf/pdf/2024/121/e3sconf_icrera2024_01005.pdf

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