Special Session IX: AI-Driven Virtual Power Plants: From Intelligent Perception to Autonomous Decision-Making AI驱动的虚拟电厂：从智能感知到自主决策
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Session Chair: Assoc. Prof., Jiaqi Shi, Shenyang Institute of Engineering, China |
 Co-Chair: Lecture, Hongyang Jin, Shenyang Institute of Engineering, China |
 Co-Chair: Lecture, Shanshan Cheng, Shenyang Institute of Engineering, China |
Co-Chair: Lecture, Mingjing Ma, Shenyang Institute of Engineering, China |
Summary:
With the increasing penetration of renewable energy and the widespread integration of distributed resources such as energy storage, flexible loads, and electric vehicles, virtual power plants (VPPs) have emerged as a core enabler for aggregating and coordinating these dispersed assets. However, the inherent high uncertainty on the resource side poses significant challenges to VPPs in terms of perception, coordination, and decision-making. This session focuses on the application of advanced intelligent computing technologies across the entire VPP value chain, aiming to explore how state-of-the-art algorithms can enhance system robustness and economic performance under complex operating conditions. Topics of interest include, but are not limited to, renewable power forecasting, load situation awareness, flexibility resource assessment, optimal dispatch and operation, electricity market bidding strategies, and low-carbon emission optimization. We cordially invite contributions that offer theoretical breakthroughs or engineering validation, and we look forward to advancing the development of VPPs toward safer, more efficient, and more sustainable power systems.
随着新能源渗透率提升及储能、柔性负荷、电动汽车等分布式资源的广泛接入，虚拟电厂已成为聚合与调控这些分散资产的核心载体。然而，资源侧的强不确定性对虚拟电厂的感知、协调与决策能力提出了严峻挑战。本专题聚焦于前瞻性智能计算技术在虚拟电厂全链条中的应用，旨在探索如何利用先进算法提升系统在复杂环境下的鲁棒性与经济性。征文范围涵盖新能源功率预测、负荷态势感知、灵活性资源评估、优化调度运行、电力市场竞价策略及低碳减排优化等关键议题。我们诚挚邀请提交具有理论突破或工程验证价值的研究成果，共同推动虚拟电厂向安全、高效、可持续方向发展。
Topics of interest include, but are not limited to:
1. AI-based forecasting and flexibility assessment for VPP operation （虚拟电厂运行中的AI预测与灵活性评估）
2. Autonomous scheduling of VPPs under uncertain operating conditions （不确定环境下的虚拟电厂自主调度）
3. Intelligent coordination of flexible resources to improve VPP responsiveness （提升虚拟电厂响应能力的灵活资源智能协同）
4. Intelligent VPP bidding and trading in electricity markets （面向电力市场的虚拟电厂智能竞价与交易）
5. Risk-aware and robust decision-making for reliable VPP operation （支撑可靠运行的风险感知与鲁棒决策）
6. Carbon-aware dispatch and green certificate trading for low-carbon VPPs （面向低碳目标的碳感知调度与绿证交易）
Keywords:
Virtual Power Plant （虚拟电厂）
Artificial Intelligence （人工智能）
Renewable Energy Forecasting （新能源功率预测）
Load Forecasting （负荷预测）
Autonomous Scheduling （自主调度）
Low-Carbon Optimization （低碳优化）
Submission Deadline: October 1, 2026
