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Review of distributed control and optimization in energy internet: From traditional methods to artificial intelligence-based methods

Published version
Peer-reviewed

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Abstract

Abstract: Energy internet (EI) can alleviate the arduous challenges brought about by the energy crisis and global warming and has aroused the concern of many scholars. In the research of EI control systems, the access of distributed energy causes the power system to exhibit complex nonlinearity, high uncertainty and strong coupling. Traditional control and optimization methods often have limited effectiveness in solving these problems. With the widespread application of distributed control technology and the maturity of artificial intelligence (AI) technology, the combination of distributed control and AI has become an effective method to break through current research bottlenecks. This study reviews the research progress of EI distributed control technologies based on AI in recent years. It can be found that AI‐based distributed control methods have many advantages in maintaining EI stability and achieving optimal energy management. This combination of AI and distributed control makes EI control systems more intelligent, safe and efficient, which will be an important direction for future research. The purpose of this study is to provide a reference as well as useful research ideas for the study of EI control systems.

Description

Keywords

4007 Control Engineering, Mechatronics and Robotics, 40 Engineering, Machine Learning and Artificial Intelligence, 7 Affordable and Clean Energy

Journal Title

IET Cyber-Physical Systems: Theory and Applications

Conference Name

Journal ISSN

2398-3396
2398-3396

Volume Title

6

Publisher

Institution of Engineering and Technology (IET)
Sponsorship
Fundamental Research Funds for the Central Universities of China (B200201071)
BNRist Program (BNR2021TD01009)