The increasing pressure from energy crisis and environment pollution has led to the urgency of energy structure and technology upgrade. As the future energy development trend, Cyber-Energy System (CES) focuses on deeply integrating multiple types of energy resources (including electricity power, heat, cool and gas, etc.) and advanced communication technology to improve the energy utilization efficiency, reduce the costs and emissions and increase the proportion of renewable energy resources. Since AI technology is both suitable for solving model-driven and data-driven research problems, it fits well with the feature of CES with diversified information date and interdependent infrastructures. By reasonably utilizing AI and multi-energy conversion technology, it is entirely possible for CES to achieve low (even zero) operation in the processes of energy generation, conversion, transmission, distribution and consumption, etc. Meanwhile, zero carbon of CES requires innovation in many aspects, including policy, markets, modeling, planning, control and operation, which brings many new challenges.
The aim of the Research Topic is to address and disseminate state-of-the-art research and opportunities regarding application of AI and multi-energy conversion technology to achieve low/zero system operation for CES. We seek original papers with novel research contributions in all aspects of tools, models and methods, etc.
The topics of interests include, but are not limited to:
• Policy on zero-carbon CES
• Analysis of zero-carbon energy markets for CES
• Energy management architecture and framework of zero-carbon CES
• Stability analysis of zero-carbon CES
• AI-driven data analysis and model development of zero-carbon CES
• AI-driven dispatch, control and operation of zero-carbon CES
• AI-driven forecasting of zero-carbon CES
• Simulation analysis and verification of zero-carbon CES.
The increasing pressure from energy crisis and environment pollution has led to the urgency of energy structure and technology upgrade. As the future energy development trend, Cyber-Energy System (CES) focuses on deeply integrating multiple types of energy resources (including electricity power, heat, cool and gas, etc.) and advanced communication technology to improve the energy utilization efficiency, reduce the costs and emissions and increase the proportion of renewable energy resources. Since AI technology is both suitable for solving model-driven and data-driven research problems, it fits well with the feature of CES with diversified information date and interdependent infrastructures. By reasonably utilizing AI and multi-energy conversion technology, it is entirely possible for CES to achieve low (even zero) operation in the processes of energy generation, conversion, transmission, distribution and consumption, etc. Meanwhile, zero carbon of CES requires innovation in many aspects, including policy, markets, modeling, planning, control and operation, which brings many new challenges.
The aim of the Research Topic is to address and disseminate state-of-the-art research and opportunities regarding application of AI and multi-energy conversion technology to achieve low/zero system operation for CES. We seek original papers with novel research contributions in all aspects of tools, models and methods, etc.
The topics of interests include, but are not limited to:
• Policy on zero-carbon CES
• Analysis of zero-carbon energy markets for CES
• Energy management architecture and framework of zero-carbon CES
• Stability analysis of zero-carbon CES
• AI-driven data analysis and model development of zero-carbon CES
• AI-driven dispatch, control and operation of zero-carbon CES
• AI-driven forecasting of zero-carbon CES
• Simulation analysis and verification of zero-carbon CES.
