Special Session 10

Session 10: Coordinated optimization method for computing, electricity, and carbon in multi-agent smart city energy system
“多智能体智慧城市能源系统的算-电-碳协同优化方法”

The smart city energy system exhibits significant distributed coupling characteristics of multi-energy flow interweaving, multi-agent participation, and multi-objective optimization. It faces multiple complex optimization challenges such as optimal allocation of computing resources, dynamic balance of energy supply and demand, and refined control of carbon emissions. Multi-agent technology, by constructing a distributed decision-making framework, achieves consensus coordination of global objectives based on ensuring local optimization of each energy subsystem through communication protocols, thereby significantly enhancing the overall operational efficiency and reliability of the system. The collaborative optimization strategy of computing-electricity-carbon maximizes the comprehensive benefits of the smart city energy system by coordinating the rational allocation of computing resources, precise matching of electricity supply and demand, and market-oriented operation of carbon emission trading. This session will delve into how to promote the stable operation of the smart city energy system towards low-carbon, high-efficiency, and economic directions through dynamic game mechanisms among agents, efficient information sharing models, and flexible strategy coordination methods.  

智慧城市能源系统具有显著的多能流交织、多主体参与、多目标优化的分布式耦合特性,面临算力资源优化配置、能量供需动态平衡、碳排放精细化管控等多重复杂优化挑战。多智能体技术通过构建分布式决策框架,在确保各能源子系统实现局部最优化的基础上,依托通信协议实现全局目标的一致性协同,进而显著提升系统的整体运行效率与可靠性。算-电-碳协同优化策略通过统筹算力资源的合理分配、电力供需的精准匹配以及碳排放权交易的市场化运作,可实现智慧城市能源系统综合效益的最大化。本次论坛将深入探讨如何通过智能体间的动态博弈机制、高效信息共享模式以及灵活策略协调方法,推动智慧城市能源系统向低碳化、高效化及经济化方向稳健运行。  

Topics (Including but not limited to)

  • 1. Design of the computing-electricity-carbon market mechanism in multi-energy coupling system
    多能源耦合系统中的算-电-碳市场机制设计。
  • 2. Mathematical modeling methods and digital twin technology for smart city energy system
    智慧城市能源系统的数学建模方法与数字孪生技术
  • 3. Hierarchical distributed architecture and communication protocol design for multi-agent energy system
    多智能体能源系统的分层分布式架构及通信协议设计
  • 4. Game strategy and dynamic adjustment method for computing-electricity-carbon trading in distributed energy system
    分布式能源系统的算-电-碳交易博弈策略及动态调整方法
  • 5. Computing power migration strategy based on demand response and interaction mechanism with electricity market
    基于需求响应的算力迁移策略与电力市场交互机制
  • 6. Optimization scheduling method for multi-agent energy system based on carbon quota constraints
    基于碳配额约束的多智能体能源系统优化调度方法
  • 7. Blockchain-based energy trading and carbon footprint tracking technology
    基于区块链的能源交易与碳足迹追踪技术
  • 8. Collaborative control and optimization algorithms for multiple agents in smart city energy systems
    智慧城市能源系统中多智能体的协同控制与优化算法

Chair: Assoc. Prof. Haoran Li, Shandong University of Finance and Economics, China

Haoran Li is an associate professor of Shandong university of finance and economics, Jinan, China, as well as the Shandong Provincial Key Laboratory of Blockchain Finance. He received the Ph.D. degree in Control Theory and Control Engineering from Shandong University and completed his postdoctoral research at the School of Electrical Engineering at Shandong University. His research interest includes the integrated energy system, low carbon smart city, and trusted data space.

 

Co-chair: Assoc. Prof. Chunyang Liu, Shandong University, China

Liu Chunyang is an Associate Professor at Shandong University. He holds a Ph.D. from Xi'an Jiaotong University and was a Visiting Scholar at the Illinois Institute of Technology, USA. His research focuses on planning of power system, operation optimization of energy storage system and integrated energy systems, and microgrid energy management. He has undertaken 3 national and over 10 research projects, and received 1 provincial-level scientific and technological award, He has published over 50 SCI/EI papers.

 

Co-chair: Dr. Hang Tian, University of Jinan, China

Hang Tian is currently a Lecturer at the School of Electrical Engineering, University of Jinan, China. He received his M.E. degree in Electrical Engineering from University of New South Wales, Australia in 2017, and the Ph.D. degree in Electrical Engineering from Shandong University, China in 2024. His research interests include simulation, optimization and uncertainty analysis of power system and integrated energy systems.


Critical Dates/重要日期

Submission of Full Paper:   July 15th, 2026  
投稿截止日:  2026年7月15日 
Notification Deadline  August 15th, 2026 
通知书发送:  2026年8月15日 
Registration Deadline:  August 30th, 2026 
注册截止日:  2026年8月30日  

Submission Guideline / 投稿指南

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2026 the 10th International Conference on Smart Grid and Smart Cities (ICSGSC)