Special Session 5

Session 5: Artificial Intelligence-based Low Carbon Operation and Planning Research for Integrated Energy System
“基于人工智能的综合能源系统低碳运行与规划研究”

The transition towards a sustainable energy future and the pursuit of carbon neutrality goals have positioned Integrated Energy Systems (IES) – integrating electricity, heating, cooling, gas, and other energy vectors – as a critical solution due to their potential for multi-energy complementarity and efficiency. However, the operation and planning of IES face significant challenges stemming from high uncertainties in renewable generation and multi-energy loads, complex interactions within multi-energy flows, and stringent low-carbon constraints. Artificial Intelligence (AI) offers powerful capabilities to address these complexities. This research focuses on developing an Artificial Intelligence-based Low Carbon Operation and Planning Strategy for Integrated Energy Systems. It leverages advanced AI techniques, including deep learning, reinforcement learning, and optimization algorithms, to deeply analyze system operational patterns, accurately forecast multi-energy demands and renewable outputs, dynamically optimize the coordinated dispatch of energy flows and equipment operation, and strategically plan long-term system capacity expansion and network configuration. By establishing AI-driven intelligent decision-making models, this research aims to significantly reduce carbon emission intensity while ensuring system security, reliability, and cost-effectiveness. The ultimate goal is to enhance overall energy utilization efficiency and renewable energy accommodation, thereby providing core technological and strategic support for building a clean, low-carbon, safe, and efficient modern energy infrastructure.  

随着能源结构转型和“双碳”目标的深入推进,综合能源系统(Integrated Energy System, IES)因其多能互补、高效协同的优势,成为实现能源清洁低碳转型的关键载体。然而,IES涉及电、热、冷、气等多种异质能源的耦合,其运行与规划面临源荷双侧强不确定性、多能流复杂交互以及低碳目标约束等多重挑战。人工智能(AI)技术为解决上述挑战提供了强大工具。本专题聚焦于基于人工智能的综合能源系统低碳运行与规划策略,旨在利用深度学习、强化学习、优化算法等AI技术,深入挖掘系统运行规律,精准预测多元负荷与可再生能源出力,动态优化多能流协同调度与设备启停,并前瞻性地规划系统容量配置与网络拓扑。通过构建AI驱动的智能决策模型,本研究力求在保障系统安全可靠与经济性的前提下,显著降低碳排放强度,提升能源利用效率与可再生能源消纳能力,为构建清洁低碳、安全高效的现代能源体系提供核心技术与策略支撑。  

Topics (Including but not limited to)

  • AI-Driven Uncertainty Modeling for Renewable Integration in Integrated Energy Systems
    基于AI驱动的综合能源系统中可再生能源与负荷的不确定性建模
  • Reinforcement Learning for Real-Time Low-Carbon Dispatch of Multi-Energy Integrated Energy Systems
    基于强化学习的多类型能源综合能源网络实时低碳调度
  • Optimal Planning of Integrated Energy Systems with AI-Based Carbon-Emission Constrained Capacity Allocation
    面向碳中和的综合能源系统规划:人工智能驱动的容量配置与碳约束优化
  • Digital Twin-Enabled Intelligent Decision Framework for Integrated Energy Systems Operation under Multi-Scale Uncertainties
    基于数字孪生的综合能源系统多尺度不确定性运行决策框架
  • Blockchain-AI Fusion for Carbon-Credit Trading in Multi-Stakeholder IES
    基于区块链与人工智能融合的多主体综合能源系统碳交易机制

Chair: Prof. Bo Yang, Kunming University of Science and Technology, China

Prof. Bo Yang received his Ph.D. degree from the University of Liverpool in 2015 supported by China Scholarship Council (CSC). He has authored two Chinese monographs as the first author and published over 180 SCI journal papers (including 11 ESI papers and 3 hot papers) and over 30 EI journal papers. He has led 36 research projects, including two National Natural Science Foundation of China and three Yunnan Province basic Research Programs. He has received numerous awards, including the First Prize for Technological Innovation from the China Electricity Council in October 2018, the Second Prize for Innovation in Industry-Academia-Research Cooperation in December 2018, and the First Prize for Scientific and Technological Progress from the Yunnan Power Grid Company in December 2023. He was awarded as the "Yunnan Province Ten Thousand Talents Program-Young Top Talents" (provincial level) in December 2018, Highly Cited Chinese Scientist from 2021-2024 by Elsevier, top 2% of scientists globally in terms of lifetime scientific impact and annual influence from 2022-2024, as well as China Knowledge Network Top 1% of Highly Cited Scholars for 2024. From October 2023 to January 2024, he was fully funded by the to conduct research as a visiting scholar at the University of Liverpool. He also serves on the Youth Working Committee of the Eighth Council of the China Electrotechnical Society, as an executive director of the IEEE PES China Energy Informatics and Systems Technology Subcommittee and the Dynamic Power System Artificial Intelligence Applications Technology Subcommittee. He has been playing General Chair of IEEE International Conference on Power Science and Technology (ICPST 2023-2025), indexed by EI).


Critical Dates/重要日期

Submission of Full Paper:   September 15th, 2025  
投稿截止日:  2025年9月15日 
Notification Deadline  September 30th, 2025 
通知书发送:  2025年9月30日 
Registration Deadline:  October 15th, 2025 
注册截止日:  2025年10月15日  

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2025 the 9th International Conference on Smart Grid and Smart Cities (ICSGSC)