The increasing pressure from energy and environment protection has made the research for advanced energy infrastructures urgent, such as smart grids, intelligent transportation networks, heat and natural gas networks, and so on. To this end, Integrated Energy System (IESs), focusing on deep integration of advanced multi-energy and information technologies, is regarded as the popular form of resilient energy utilization for the future development. Through embedding advanced cooperative control and optimization strategies into IESs, the intelligent energy management will be achieved in the processes of energy generation, conversion, transmission, distribution and consumption, etc. Furthermore, the IES will generate and utilize abundant data to achieve optimal energy distribution. There are many challenges that require further research and development on the modeling, planning, control and optimization of the distributed information and energy systems, which may include interdependent infrastructures such as electricity, transportation, communication, heat and natural gas networks. This Research Topic aims to address and disseminate state-of-the-art research and opportunities regarding applications of innovative solutions to achieve the deep integration of advanced cooperative control and optimization strategies for IESs. We seek original papers with novel research contributions in all aspects of tools, models and methods of relevance and impact in IESs.
The topics of interests include, but are not limited to:
• Distributed energy management structure and framework of IESs
• Coupled mechanism modeling of IESs
• Spatiotemporal data analysis and cooperative control development of IESs.
• Optimal planning, operation and control of IESs
• Standard modeling of IESs
• Nonlinear control and optimization of IESs
• The impact of cyber and physical security on the controller and optimizer of IESs
• The application of AI and 5G technologies on the controller and optimizer of IESs
• The distributed cooperative control and optimization strategies for IESs.
The increasing pressure from energy and environment protection has made the research for advanced energy infrastructures urgent, such as smart grids, intelligent transportation networks, heat and natural gas networks, and so on. To this end, Integrated Energy System (IESs), focusing on deep integration of advanced multi-energy and information technologies, is regarded as the popular form of resilient energy utilization for the future development. Through embedding advanced cooperative control and optimization strategies into IESs, the intelligent energy management will be achieved in the processes of energy generation, conversion, transmission, distribution and consumption, etc. Furthermore, the IES will generate and utilize abundant data to achieve optimal energy distribution. There are many challenges that require further research and development on the modeling, planning, control and optimization of the distributed information and energy systems, which may include interdependent infrastructures such as electricity, transportation, communication, heat and natural gas networks. This Research Topic aims to address and disseminate state-of-the-art research and opportunities regarding applications of innovative solutions to achieve the deep integration of advanced cooperative control and optimization strategies for IESs. We seek original papers with novel research contributions in all aspects of tools, models and methods of relevance and impact in IESs.
The topics of interests include, but are not limited to:
• Distributed energy management structure and framework of IESs
• Coupled mechanism modeling of IESs
• Spatiotemporal data analysis and cooperative control development of IESs.
• Optimal planning, operation and control of IESs
• Standard modeling of IESs
• Nonlinear control and optimization of IESs
• The impact of cyber and physical security on the controller and optimizer of IESs
• The application of AI and 5G technologies on the controller and optimizer of IESs
• The distributed cooperative control and optimization strategies for IESs.