Frontier Research and Application of Energy Based on Artificial Intelligence
Special Issue Editors
Junfeng Miao
Institutions: Henan Normal University
Title: Associate Professor, Master's Supervisor
Email: miaojunfengwu@gmail.com
Research Fields: Artificial intelligence, information security
En Zhang
Institutions: Henan Normal University
Title: Professor, Master's Supervisor
Email: zhangenzdrj@163.com
Research Fields:Network security, privacy protection
Yingpeng Hao
Institutions: China National Petroleum Corporation Planning Institute
Title: Senior Engineer
Email: haoyingpeng@petrochina.com.cn
Research Fields: Integration of natural gas and new energy
Special Issue Information
With the rapid development of the global economy and the continuous growth of population, energy demand has sharply increased. At the same time, the extraction and use of traditional energy sources have brought serious environmental problems, such as greenhouse gas emissions and resource depletion. Therefore, developing new energy, improving energy utilization efficiency and optimizing energy allocation have become major challenges facing the world today. In recent years, the rapid development of artificial intelligence (AI) has provided unprecedented opportunities for innovation in the energy sector. AI, with its powerful data processing, pattern recognition and decision optimization capabilities, is profoundly changing the way energy is produced, transmitted, distributed and consumed. In recent years, breakthroughs in AI such as deep learning, reinforcement learning and natural language processing have driven the application of AI in various fields. Especially in areas such as big data analysis, predictive model construction and real-time optimization control, AI has shown tremendous potential.
However, with the widespread application of AI technology in the energy field, including load forecasting, fault prediction and diagnosis, market optimization, etc., a large amount of sensitive data is collected and analyzed. How to ensure the security and privacy protection of these data has become an urgent problem to be solved. Secondly, the complexity and uncertainty of the energy system pose higher requirements for the generalization ability and adaptability of AI models. How to build AI models that can adapt to different scenarios and improve the robustness and reliability of the models, is currently the focus of research. Finally, how to ensure that AI technology can provide personalized energy-saving suggestions through deep learning and analysis of user energy consumption behavior, and guide users to form more green and low-carbon energy consumption habits, is the current problem that needs to be solved. Therefore, researchers are actively exploring technologies and methods based on artificial intelligence for energy data processing, security protection, identification and prediction, maintenance and management, etc.
This special issue provides a platform for researchers, scholars, and professionals to showcase their research work in the field of energy. By exploring the latest developments, innovations and applications in energy based on artificial intelligence, our goal is to solve the latest problems encountered both internally and externally in the field of energy. The topics of interest include but are not limited to:
- AI-based energy load forecasting model
- Application and Practice of AI in Smart Grid
- Deep learning in renewable energy generation prediction
- Application of AI technology in optimizing energy storage systems
- Dynamic optimization control of energy systems based on reinforcement learning
- Privacy protection and security of energy big data
- Generalization ability and adaptability analysis of AI models in energy systems
- Intelligent optimization algorithms for energy storage technology
- Application and Challenges of AI Technology in Distributed Energy Management
- AI-based energy system fault diagnosis and prediction
- Energy network security protection technology
- AI-based energy consumption pattern recognition and prediction
- Application of AI in energy equipment maintenance and management
- AI-based energy system risk assessment and early warning mechanism
- AI-based energy system simulation
Submission Deadline: July 1st 2025
