ORIGINAL RESEARCH article
Front. Energy Res.
Sec. Smart Grids
An Artificial Intelligence Based Framework for Smart Power Grid Management Using an Autonomous and Controllable Intelligent Service Hub with Multimodal Document Processing
- FZ
Fanqiang Zeng
- HZ
Hua Zheng
- CL
Cheng Li
- JR
Jinsong Rong
- YN
Yanli Nong
China Southern Power Grid Artificial Intelligence Technology Co Ltd, Guangzhou, China
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Abstract
The growing sophistication and need to have sustainable energy systems has led to the shift of the conventional power grids to smart power grids. Such grids are equipped with innovative technologies that include digital communication, Internet of Things (IoT), and Artificial Intelligence (AI) to increase the efficiency, reliability, and scalability of energy delivery. This paper introduce an AI-based approach to smart power grid management, with the emphasis on the incorporation of an autonomous and controllable intelligent service hub that would be able to process multimodal data, such as textual reports, images, videos, and sensor data. The framework applies AI methods of machine learning, deep learning, and predictive analytics to optimize energy allocation, faults, and failure prediction with minimum human intervention. With real-time analysis, the system dynamically changes the operation of the grids with incoming data, enhancing energy efficiency and lowering the cost of operations by up to 30 percent, between $12,000 and 8,400 in the example of energy optimization. Also, the fault detection system shows a remarkable accuracy of 0.97 in terms of AUC whereas the predictive maintenance model reports an accuracy rate of 95.5. The balancing nature of the energy demand and generation provided by the framework is critical in integrating renewable energy sources since it can help in countering the problem of intermittency of the solar and wind energy. Moreover, the system has a multimodal document processing feature that increases decision-making through the synthesis of various types of data and provides a more detailed overview of grid work. This paper explains how the suggested AI-based framework can greatly improve the efficiency, reliability, and sustainability of smart power grids, which will result in the future improvements in energy management.
Summary
Keywords
artificial intelligence, Autonomous Service Hub, fault detection, Multimodal data processing, Predictive maintenance, Smart power grid
Received
25 June 2026
Accepted
31 August 2026
Copyright
© 2026 Zeng, Zheng, Li, Rong and Nong. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Fanqiang Zeng
Disclaimer
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