Guest Editors
Dr. LI Shuangqi
Email: shuangqi.li@polyu.edu.hk
Affiliation: Department of Electrical and Electronic Engineering, The Hong Kong Polytechnic University, Hong Kong, China
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Research Interests: battery modeling & health management, transportation electrification, vehicle-grid integration, cyber-physical systems, smart charging, EV flexibility markets, integrated energy systems, cyber-resilience & blockchain
Prof. XIANG Yue
Email: xiang@scu.edu.cn
Affiliation: College of Electrical Engineering, Sichuan University, Chengdu, 610065, China
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Research Interests: power system planning & optimal operation, electric vehicles & smart grid, energy modeling & market economics, data analytics in smart cities
Senior Engineer WANG Xinying
Email: wangxinying@epri.sgcc.com.cn
Affiliation: China Electric Power Research Institute, Beijing, 100192, China
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Research Interests: artificial intelligence, smart grid, energy internet, microgrids, integrated energy systems, renewable energy, power system stability, emergency control
Prof. LIU Youbo
Email: liuyoubo@scu.edu.cn
Affiliation: College of Electrical Engineering, Sichuan University, Chengdu, 610065, China
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Research Interests: power system planning & optimal operation, active distribution networks, microgrids, electric vehicles, renewable energy, energy storage, machine learning, energy markets, p2p trading, demand response, integrated energy systems, energy internet
Summary
The increasing complexity of modern energy systems, driven by high shares of renewable energy, distributed resources, and electrified demand, requires new tools for reliable and efficient operation. Artificial intelligence (AI) offers powerful methods for forecasting, optimization, and control that can improve the flexibility, reliability, and resilience of the energy systems. By enabling data-driven decision-making, AI also supports the integration of variable renewables and storage, reduces operational risks, and enhances sustainability.
This special issue focuses on advanced studies in AI-enabled energy systems, aiming to enhance flexibility, reliability, resilience, and sustainability of smart energy systems. Researchers are encouraged to contribute innovative methods in modelling, prediction, planning, scheduling, and intelligent control to overcome technical bottlenecks and accelerate next-generation energy solutions.
Topics of interest include, but are not limited to:
· AI for forecasting, scheduling, and optimization
· Data-driven modeling and control
· Reliability and resilience enhancement with AI
· Integration of renewables and distributed energy resources using AI
· AI in demand response, storage, and EV interaction
· Demonstrations, simulations, and techno-economic studies with AI
· AI-enabled energy policy, regulation, and market design
Keywords
artificial intelligence, forecasting, optimization, energy flow control, renewable integration, distributed energy resources, energy storage system, demand response, vehicle-grid integration, resilience, policy and market
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