专题会议（一）：新型电力系统的智能传感与分析

Track 1: Smart Sensing and Analysis for Modern Power Systems

栾文鹏

Wenpeng Luan

天津大学

Tianjin University

在"双碳"目标驱动下，能源系统正加速向更加电气化、分布式的方向转型。这一过程要求新型电力系统能够高效接纳可再生能源、电动汽车充电设施等新型资源，并充分挖掘柔性负荷等需求侧资源的调节潜力。随着分布式电源渗透率不断提高，电力系统运行面临诸多新的挑战，同时也为电网企业利用先进技术提升系统运行水平带来了新的机遇，例如智能感知技术、创新分析方法以及人工智能算法等。

本专题旨在为国内外科研人员、工程技术人员和产业界专家提供交流平台，共同分享和探讨高比例分布式电源接入背景下电力系统智能感知与创新分析领域的最新研究进展、关键技术、解决方案及工程应用实践。

Driven by the "dual carbon" goals, the energy system is accelerating its transformation towards greater electrification and decentralization. This requires modern power systems to efficiently integrate renewable energy, electric vehicle charging facilities, and other emerging resources, while fully leveraging the regulatory potential of flexible loads and other demand-side resources. As the penetration of distributed generation continues to increase, power system operation faces numerous new challenges, while also bringing new opportunities for grid enterprises to leverage advanced technologies such as smart sensing, innovative analytical methods, and artificial intelligence algorithms to enhance system operational capabilities.

This track aims to provide a platform for domestic and international researchers, engineers, and industry experts to share and discuss the latest research progress, key technologies, solutions, and engineering applications in the field of smart sensing and innovative analysis for power systems with high penetration of distributed generation.

专题会议（二）：新能源与储能协同运行与主动支撑

Track 2: Collaborative Operation and Active Support of Renewable Energy and Energy Storage

秦世耀

Shiyao Qin

中国电力科学研究院

China Electric Power Research Institute

在"双碳"目标的引领和推动下，我国新型电力系统建设进入加速转型期，新能源渗透率持续提升并逐步成为第一大电源，随之带来的电网支撑能力不足、系统强度下降、惯量降低等问题亟待破解。储能作为优化系统调节能力的核心技术，与新能源的协同运行仍面临诸多挑战。本专题分会场围绕新能源与储能协同稳定机理与建模、多种场景下新能源与储能稳定运行与协同支撑控制、新型储能与新能源的适配性与支撑能力分析、单元-场站-集群多层级构网控制、新能源与储能稳定运行关键装备研发、面向并网性能验证的电网宽频动态模拟与试验技术、新能源与储能主动支撑及构网能力评估及应用实证等方向征集研究成果，聚焦新能源与储能协同主动支撑技术开展研讨，推动新能源与储能协同控制、试验与评估技术工程化落地，支撑新型电力系统高质量建设。

Guided and driven by the "dual carbon" goals, China's modern power system construction has entered an accelerated transformation phase. The penetration rate of renewable energy continues to increase and is gradually becoming the largest power source, which brings challenges such as insufficient grid support capacity, reduced system strength, and decreased inertia that need to be addressed. As a core technology for optimizing system regulation capabilities, energy storage still faces many challenges in collaborative operation with renewable energy. This track focuses on the collection of research results in areas such as the collaborative stability mechanism and modeling of renewable energy and energy storage, stable operation and collaborative support control of renewable energy and energy storage in various scenarios, adaptability and support capacity analysis of new energy storage and renewable energy, multi-level grid-forming control from unit to station to cluster, research and development of key equipment for stable operation of renewable energy and energy storage, grid broadband dynamic simulation and testing technology for grid-connected performance verification, active support and grid-forming capability evaluation of renewable energy and energy storage, and application demonstrations. It focuses on the discussion of collaborative active support technologies for renewable energy and energy storage, promoting the engineering implementation of collaborative control, testing, and evaluation technologies for renewable energy and energy storage to support the high-quality construction of modern power systems.

专题会议（三）：面向智慧电力与能源系统的输电、配电与微电网协同调度控制

Track 3: Collaborative Dispatch and Control of Transmission, Distribution and Microgrids for Smart Power and Energy Systems

高文忠

Wenzhong Gao

武汉大学

Wuhan University

郑涛

Tao Zheng

华北电力大学

North China Electric Power University

王帅

Shuai Wang

中国电力科学研究院有限公司

China Electric Power Research Institute

梁顺

Shun Liang

中国电力科学研究院有限公司

China Electric Power Research Institute

随着新能源、分布式能源、储能系统、柔性负荷和微电网的大规模接入，现代电力系统正逐步演化为输电、配电与微电网高度耦合的新型运行形态。这一转变加剧了源荷时空不匹配问题，提高了系统运行的不确定性，也对跨层级信息共享、协同调度和安全控制提出了新的挑战。因此，亟需发展面向输电、配电与微电网协同运行的先进调度控制理论与技术。

本专题将围绕输电、配电与微电网多层级协同调度控制的关键理论、方法与应用展开讨论。首先，专题将讨论跨层级感知与建模方法，包括输配微一体化潮流分析、分布式能源聚合建模以及分层状态估计等内容。其次，专题将关注正常运行状态下的优化调度与控制策略，涵盖广域功率平衡、配电网优化运行、微电网能量管理、需求响应以及储能协同控制等方向。最后，专题将探讨主动支撑与韧性提升技术，包括自上而下的分层调度、自下而上的灵活性支撑、人工智能辅助决策以及协同应急控制等内容。

本专题旨在为相关领域的科研人员、工程技术人员和产业专家提供交流平台，集中展示输电、配电与微电网协同调度控制方面的最新进展，为提升新能源消纳能力、系统运行安全性、供电可靠性以及智慧电力与能源系统低碳转型提供技术支撑。

With the large-scale integration of renewable energy, distributed energy, energy storage systems, flexible loads, and microgrids, modern power systems are gradually evolving into a new operational form with highly coupled transmission, distribution, and microgrids. This transformation exacerbates the spatio-temporal mismatch between supply and demand, increases operational uncertainties, and poses new challenges to cross-level information sharing, collaborative dispatch, and security control. Therefore, it is urgent to develop advanced dispatch and control theories and technologies for the collaborative operation of transmission, distribution, and microgrids.

This track will discuss the key theories, methods, and applications of multi-level collaborative dispatch and control for transmission, distribution, and microgrids. Firstly, the track will discuss cross-level sensing and modeling methods, including integrated transmission-distribution-microgrid power flow analysis, distributed energy aggregation modeling, and hierarchical state estimation. Secondly, the track will focus on optimal dispatch and control strategies under normal operating conditions, covering wide-area power balance, distribution network optimal operation, microgrid energy management, demand response, and energy storage collaborative control. Finally, the track will explore active support and resilience enhancement technologies, including top-down hierarchical dispatch, bottom-up flexibility support, AI-assisted decision-making, and collaborative emergency control.

This track aims to provide a platform for researchers, engineers, and industry experts in related fields to exchange ideas, showcase the latest progress in collaborative dispatch and control for transmission, distribution, and microgrids, and provide technical support for improving renewable energy integration capacity, system operation security, power supply reliability, and low-carbon transformation of smart power and energy systems.

专题会议（四）：新型电力系统下的数据中心能源供给与互动

Track 4: Energy Supply and Interaction for Data Centers in Modern Power Systems

袁宇波

Yubo Yuan

国网江苏电力有限公司电力科学研究院

State Grid Jiangsu Electric Power Research Institute

缪惠宇

Huiyu Miao

国网江苏电力有限公司电力科学研究院

State Grid Jiangsu Electric Power Research Institute

随着人工智能、云计算和数字基础设施的快速发展，数据中心正逐渐成为新型电力系统中大规模、高耗能且高度动态的负荷。其不断增长的用电需求和严格的可靠性要求，对供电安全、能源效率和电网运行提出了新的挑战。与此同时，数据中心也可通过工作负载调度、制冷调节、储能、备用电源以及可控电力电子接口提供可观的灵活性。本专题聚焦新型电力系统下数据中心的能源供应与互动。主要议题包括网荷互动、需求响应、可再生能源消纳、智慧运行、算力-制冷-电力协同管理以及低碳能源优化。通过融合先进预测、感知、人工智能和优化技术，数据中心可由被动用电负荷转变为主动灵活资源，为削峰填谷、阻塞缓解、应急响应以及安全低碳的电网运行提供支撑。基于固态变压器的供电装备也是未来数据中心的重要支撑技术。凭借灵活的电压变换能力、快速可控性、直流配电兼容性以及多端口能源集成能力，固态变压器能够提升下一代数据中心能源系统的灵活性、效率和电网友好互动能力。

With the rapid development of artificial intelligence, cloud computing, and digital infrastructure, data centers are gradually becoming large-scale, high-energy-consuming, and highly dynamic loads in modern power systems. Their growing power demand and strict reliability requirements pose new challenges to power supply security, energy efficiency, and grid operation. At the same time, data centers can provide considerable flexibility through workload scheduling, cooling adjustment, energy storage, backup power supplies, and controllable power electronic interfaces. This track focuses on energy supply and interaction for data centers in modern power systems. Key topics include grid-load interaction, demand response, renewable energy integration, smart operation, collaborative management of computing-cooling-power, and low-carbon energy optimization. By integrating advanced prediction, sensing, artificial intelligence, and optimization technologies, data centers can transform from passive loads into active flexible resources, providing support for peak shaving, congestion relief, emergency response, and safe and low-carbon grid operation. Solid-state transformer-based power supply equipment is also an important supporting technology for future data centers. With flexible voltage transformation capabilities, fast controllability, DC distribution compatibility, and multi-port energy integration capabilities, solid-state transformers can enhance the flexibility, efficiency, and grid-friendly interaction capabilities of next-generation data center energy systems.

专题会议（五）：人工智能在新型电力系统中的应用

Track 5: Applications of Artificial Intelligence in Modern Power Systems

杨楠

Nan Yang

三峡大学

Three Gorges University

本专题会议聚焦人工智能在新型电力系统中的前沿理论、关键技术及工程应用，围绕新型电力系统建设与运行过程中的核心挑战与难题展开，涵盖可再生能源智能预测、电网状态智能感知与评估、电力设备智能运行与维护、发电、电网、负荷与储能的协同智能控制、电网故障智能诊断与安全防护、大规模电力AI模型在行业的应用、数字与模拟融合下的智能决策，以及电力系统的低碳智能运行等主要研究方向。本次会议旨在汇聚国内外高校、科研院所、电力企业和科技组织的最新研究成果与工程技术实践，探索人工智能技术与电力系统深度融合的创新路径，突破传统技术瓶颈，推动电力系统从经验驱动和模型驱动向智能感知、分析、决策与控制全面升级。会议致力于搭建高水平的学术交流与产学研合作平台，促进电力人工智能领域的技术创新、科研成果商业化以及学术交流，为新型电力系统的安全稳定运行、高效低碳发展以及数字化智能化转型提供坚实的理论支撑和技术参考。

This track focuses on cutting-edge theories, key technologies, and engineering applications of artificial intelligence in modern power systems, addressing core challenges and problems in the construction and operation of modern power systems. It covers major research directions such as intelligent prediction of renewable energy, intelligent sensing and evaluation of power grid states, intelligent operation and maintenance of power equipment, collaborative intelligent control of generation, grid, load, and energy storage, intelligent fault diagnosis and security protection of power grids, application of large-scale power AI models in the industry, intelligent decision-making with digital-analog fusion, and low-carbon intelligent operation of power systems. This conference aims to bring together the latest research results and engineering practices from universities, research institutions, power enterprises, and technology organizations worldwide, explore innovative paths for deep integration of artificial intelligence technology and power systems, break through traditional technological bottlenecks, and drive power systems to fully upgrade from experience-driven and model-driven to intelligent sensing, analysis, decision-making, and control. The conference is committed to building a high-level academic exchange and industry-university-research cooperation platform, promoting technological innovation, commercialization of research results, and academic exchanges in the field of power artificial intelligence, providing solid theoretical support and technical reference for the safe and stable operation, efficient low-carbon development, and digital intelligent transformation of modern power systems.

专题会议（六）：含大规模可再生能源的微能网集群高效运行与稳定控制

Track 6: Efficient Operation and Stability Control of Micro-energy Grid Clusters with High Penetration Renewable Energy

尚磊

Lei Shang

武汉大学

Wuhan University

冀浩然

Haoran Ji

天津大学

Tianjin University

舒杰

Jie Shu

中国科学院广州能源学院

Guangzhou Institute of Energy, Chinese Academy of Sciences

周乐明

Leming Zhou

湖南大学

Hunan University

刘通

Tong Liu

南方电网科学研究院有限公司

China Southern Power Grid Research Institute

何梨梨

Lili He

湖南大学

Hunan University

郭祺

Qi Guo

湖南大学

Hunan University

崔雪

Xue Cui

武汉大学

Wuhan University

陈磊

Lei Chen

武汉大学

Wuhan University

随着"双碳"战略深入推进和乡村振兴战略全面实施，乡村能源清洁高效利用已成为构建现代能源体系的重要组成部分。然而，我国乡村能源基础设施薄弱、能源利用效率低、分布式能源系统运行方式单一等问题制约了乡村能源转型进程。本分会场聚焦乡村分布式智慧能源系统的核心科学问题与关键技术挑战，围绕"乡村分布式智慧能源系统形态演化特征与动态交互机制"这一核心科学命题，重点探讨以下四项关键技术：（1）多分区弱连接高渗透分布式能源系统协同规划技术；（2）数智赋能乡村多元异质能源综合利用提质增效技术；（3）复杂能流多尺度交互下分布式能源系统灵活运行控制技术；（4）多能耦合群发故障的安全保护与自主保障技术。本分会场旨在汇聚国内外乡村能源领域的研究成果与工程实践，推动乡村分布式智慧能源系统理论创新与技术突破，助力美丽乡村建设与绿色低碳发展。

With the in-depth advancement of the "dual carbon" strategy and the comprehensive implementation of the rural revitalization strategy, clean and efficient utilization of rural energy has become an important part of building a modern energy system. However, issues such as weak rural energy infrastructure, low energy utilization efficiency, and single operation mode of distributed energy systems restrict the rural energy transition process. This track focuses on the core scientific issues and key technical challenges of rural distributed smart energy systems, centering on the core scientific proposition of "morphological evolution characteristics and dynamic interaction mechanisms of rural distributed smart energy systems". It focuses on discussing the following four key technologies: (1) Collaborative planning technology for multi-zone weakly connected high-penetration distributed energy systems; (2) Digital intelligence-enabled quality and efficiency improvement technology for comprehensive utilization of rural multi-source heterogeneous energy; (3) Flexible operation control technology for distributed energy systems under complex energy flow multi-scale interaction; (4) Safety protection and autonomous guarantee technology for multi-energy coupling group faults. This track aims to bring together research results and engineering practices in the field of rural energy worldwide, promote theoretical innovation and technological breakthroughs in rural distributed smart energy systems, and contribute to beautiful rural construction and green low-carbon development.

专题会议（七）：源网荷储多元主体协同互动与市场化调度机制

Track 7: Collaborative Interaction and Market-oriented Dispatch Mechanisms for Multi-source-grid-load-storage Entities

吴赋章

Fuzhang Wu

武汉大学

Wuhan University

李高俊杰

Junjie Ligao

香港理工大学

Hong Kong Polytechnic University

在双碳目标引领与电力市场化改革加速推进背景下，新型电力系统迈入高比例新能源、高电力电子化发展新阶段，光伏风电新能源、配电网、柔性负荷、储能等主体规模持续增长。多元主体权属差异化、利益诉求多元化、出力负荷随机波动化，叠加现有市场交易规则适配性不足、跨层级协同调度壁垒突出，制约新能源高效消纳、电网安全运行与多方收益均衡，给全域调度运营带来全新挑战。

本专题立足新型能源体系建设需求，聚焦源网荷储多主体利益耦合、协同调控、市场竞价核心问题，探究适配多级电力市场的协同调度模式，破解多主体博弈、资源统筹调配、市场机制落地等重难点问题，打通物理调度与市场交易联动壁垒。

本专题旨在为相关领域研究人员提供高水平学术交流平台，聚焦机制优化、协同调控、工程落地多维方向，助力完善源网荷储多元主体电力市场化调度体系，赋能电力系统低碳高效安全运行。

Against the backdrop of the dual carbon goals and accelerating power market reform, modern power systems have entered a new stage of high-proportion renewable energy and high-power electronics development. The scale of entities such as photovoltaic and wind power renewable energy, distribution networks, flexible loads, and energy storage continues to grow. The diverse ownership, diversified interest demands, and random fluctuations of output and load of multiple entities, coupled with inadequate adaptability of existing market transaction rules and prominent barriers to cross-level collaborative dispatch, restrict the efficient consumption of renewable energy, safe operation of power grids, and balanced benefits of multiple parties, bringing new challenges to global dispatch and operation.

This track is based on the construction needs of the new energy system, focusing on the core issues of multi-agent interest coupling, collaborative regulation, and market bidding for source-grid-load-storage. It explores collaborative dispatch models adapted to multi-level power markets, addresses key and difficult issues such as multi-agent game, resource overall planning and allocation, and market mechanism implementation, and breaks through the linkage barriers between physical dispatch and market transactions.

This track aims to provide a high-level academic exchange platform for researchers in related fields, focusing on mechanism optimization, collaborative regulation, and engineering implementation, helping to improve the market-oriented dispatch system for multi-source-grid-load-storage entities and enabling low-carbon, efficient, and safe operation of power systems.

专题会议（八）：主动支撑型虚拟电厂及其源-荷-储资源自主协同控制技术

Track 8: Active Support Virtual Power Plants and Autonomous Collaborative Control Technology for Source-Load-Storage Resources

王逸

Yi Wang

武汉大学

Wuhan University

彭勇刚

Yonggang Peng

浙江大学

Zhejiang University

孙铭阳

Mingyang Sun

北京大学

Peking University

随着现代电力系统中可再生能源渗透率的不断提高，虚拟电厂正成为聚合、协调与控制分布式能源、柔性负荷和储能系统的重要平台。不同于传统意义上的被动式市场聚合主体，新一代虚拟电厂需要通过源-荷-储资源的自主协同控制，主动支撑电力系统安全、稳定与高效运行。本专题聚焦主动支撑型虚拟电厂的建模、控制、协调与优化方法，重点关注虚拟电厂在功率平衡、频率调节、电压稳定、韧性提升和市场参与等方面的自主支撑能力。专题将探讨在可再生能源波动、负荷不确定性、通信时延、网络物理安全风险以及电网扰动等不确定因素影响下，虚拟电厂内部异构资源的聚合建模与协同控制问题。征文主题包括但不限于：虚拟电厂分布式与分层控制架构、模型预测控制、鲁棒与随机优化、需求响应协同、储能能量管理、点对点能量交易，以及面向虚拟电厂运行的数据驱动决策方法。同时，本专题也欢迎围绕虚拟电厂内部构网型与跟网型逆变器协同控制、主动支撑能力评估、虚拟电厂参与输配协同运行，以及虚拟电厂控制平台工程示范等方面的研究。本专题旨在汇聚电力系统运行、控制理论、人工智能与能源市场等领域的研究成果，推动主动支撑型虚拟电厂发展成为未来低碳电力系统中灵活、可靠、智能的电网友好型运行主体。

With the continuous increase in the penetration rate of renewable energy in modern power systems, virtual power plants are becoming an important platform for aggregating, coordinating, and controlling distributed energy, flexible loads, and energy storage systems. Different from traditional passive market aggregation entities, the new generation of virtual power plants needs to actively support the safe, stable, and efficient operation of power systems through autonomous collaborative control of source-load-storage resources. This track focuses on modeling, control, coordination, and optimization methods for active support virtual power plants, with emphasis on the autonomous support capabilities of virtual power plants in terms of power balance, frequency regulation, voltage stability, resilience enhancement, and market participation. The track will discuss the aggregation modeling and collaborative control issues of heterogeneous resources within virtual power plants under the influence of uncertain factors such as renewable energy fluctuations, load uncertainty, communication delays, cyber-physical security risks, and grid disturbances. Topics include but are not limited to: distributed and hierarchical control architectures for virtual power plants, model predictive control, robust and stochastic optimization, demand response coordination, energy storage energy management, peer-to-peer energy trading, and data-driven decision-making methods for virtual power plant operation. At the same time, this track also welcomes research on collaborative control of grid-forming and grid-following inverters within virtual power plants, active support capability evaluation, virtual power plant participation in transmission and distribution coordinated operation, and engineering demonstrations of virtual power plant control platforms. This track aims to bring together research results from the fields of power system operation, control theory, artificial intelligence, and energy markets, and promote the development of active support virtual power plants into flexible, reliable, and intelligent grid-friendly operating entities in future low-carbon power systems.

专题会议（九）：大语言模型、边缘智能与优化在分布式柔性资源中的应用

Track 9: Applications of Large Language Models, Edge Intelligence and Optimization in Distributed Flexible Resources

何松

Song He

香港理工大学

Hong Kong Polytechnic University

侯慧

Hui Hou

武汉理工大学

Wuhan University of Technology

陈思远

Siyuan Chen

武汉大学

Wuhan University

随着现代电力系统向高比例新能源与分布式能源形态加速演进，分布式柔性资源的高效管理与协同调控正面临新的范式变革需求。电动汽车、分布式储能等多元柔性资源由于具有时空不确定性、多物理耦合特性以及复杂人因行为交互，其高效聚合与协同控制仍面临诸多挑战。

本专题聚焦大语言模型（LLMs）、边缘智能与先进优化技术在新一代智能能源系统中的交叉融合，重点探讨语义推理、自主AI智能体与分布式智能如何推动传统柔性负荷向具备自主感知、主动支撑与人机协同能力的边缘能源智能体演化。

本专题旨在为相关领域研究人员提供高水平学术交流平台，涵盖AI增强建模、分布式优化与控制、边缘智能以及人因能源交互等前沿方向。特别关注大语言模型与电力系统运行机理的深度融合，包括面向需求侧的语义感知、人机智能交互、自主决策以及分布式柔性资源的规模化协同调控等关键问题。

As modern power systems accelerate their evolution towards high-proportion renewable energy and distributed energy, the efficient management and coordinated control of distributed flexible resources are facing new paradigm transformation requirements. Due to their spatio-temporal uncertainty, multi-physical coupling characteristics, and complex human-factor behavior interactions, multiple flexible resources such as electric vehicles and distributed energy storage still face many challenges in efficient aggregation and collaborative control.

This track focuses on the cross-fusion of large language models (LLMs), edge intelligence, and advanced optimization technologies in the new generation of intelligent energy systems, with emphasis on how semantic reasoning, autonomous AI agents, and distributed intelligence can drive the evolution of traditional flexible loads into edge energy agents with autonomous perception, active support, and human-machine collaboration capabilities.

This track aims to provide a high-level academic exchange platform for researchers in related fields, covering cutting-edge directions such as AI-enhanced modeling, distributed optimization and control, edge intelligence, and human-factor energy interaction. Special attention is paid to the deep integration of large language models and power system operation mechanisms, including key issues such as semantic perception for demand side, human-machine intelligent interaction, autonomous decision-making, and large-scale coordinated control of distributed flexible resources.

专题会议（十）：分布式电源集群边缘聚合与协同控制技术

Track 10: Edge Aggregation and Collaborative Control Technology for Distributed Generation Clusters

刘友波

Youbo Liu

四川大学

Sichuan University

唐志远

Zhiyuan Tang

四川大学

Sichuan University

高比例分布式电源接入使配电网呈现源荷强不确定性与多主体自治特征，集中式调控模式在实时性、隐私性与扩展性方面面临瓶颈。本专题聚焦分布式电源集群的边缘聚合与协同控制技术，探讨边缘智能、边云协同、集群划分、多时间尺度优化调度、去中心化协同控制与可信交互等前沿议题。内容涵盖分布式资源动态聚合建模、轻量化边缘计算架构、数据驱动与物理模型融合的控制策略、以及面向电碳耦合和电力市场环境的分布式资源灵活调控。本专题旨在为新型配电系统的智能化运行提供理论基础与技术路径，促进边缘计算与电力系统深度交叉融合，支撑大规模分布式电源的安全、高效消纳与协同自治。

High-proportion distributed generation integration has made distribution networks exhibit characteristics of strong source-load uncertainty and multi-agent autonomy. Centralized control modes face bottlenecks in real-time performance, privacy, and scalability. This track focuses on edge aggregation and collaborative control technologies for distributed generation clusters, exploring cutting-edge topics such as edge intelligence, edge-cloud collaboration, cluster partitioning, multi-time-scale optimal scheduling, decentralized collaborative control, and trusted interaction. Content covers dynamic aggregation modeling of distributed resources, lightweight edge computing architectures, data-driven and physical model integrated control strategies, and flexible regulation of distributed resources in the context of electricity-carbon coupling and electricity market environments. This track aims to provide theoretical foundations and technical paths for the intelligent operation of modern distribution systems, promote deep cross-fusion of edge computing and power systems, and support safe, efficient consumption and collaborative autonomy of large-scale distributed generation.

专题会议（十一）：跨省域协同规划与市场机制

Track 11: Inter-provincial Collaborative Planning and Market Mechanisms

艾小猛

Xiaomeng Ai

华中科技大学

Huazhong University of Science and Technology

谭振飞

Zhenfei Tan

上海交通大学

Shanghai Jiao Tong University

魏翔

Xiang Wei

湖北工业大学

Hubei University of Technology

随着大型新能源基地开发和超远距离电力外送需求持续增长，跨省域电力系统正面临源荷时序耦合特性不清、优化决策维度增加、多主体博弈关系复杂等挑战。在此背景下，面向送端、接续端和受端三端电网，需要构建跨省域接续平衡的源网荷储规划与市场设计协同的新型技术体系，实现跨省域资源优化配置、新能源高效消纳和多主体利益合理分配。

本专题聚焦"跨省域协同规划与市场机制"，旨在汇聚源网荷储协同规划、电力市场及智能决策等领域的研究成果，探讨跨省域电力电量平衡、协同规划与市场机制设计的关键理论、方法和工程实践。征稿范围包括但不限于：新能源与负荷时空关联特征分析，源荷出力模拟与预测，电力电量平衡时序生产模拟，源网荷储协同规划和求解，源网荷储多主体成本收益测算，电力市场设计与交易机制，电力系统的数据融合、数字孪生、智能决策等规划平台应用技术。

With the continuous growth of large-scale renewable energy base development and ultra-long-distance power transmission requirements, inter-provincial power systems are facing challenges such as unclear spatio-temporal coupling characteristics between supply and demand, increased optimization decision dimensions, and complex multi-agent game relationships. Against this background, for the sending-end, transit-end, and receiving-end power grids, it is necessary to build a new technical system for inter-provincial transit-balanced source-grid-load-storage planning and market design collaboration, to achieve optimal allocation of inter-provincial resources, efficient consumption of renewable energy, and reasonable distribution of multi-agent interests.

This track focuses on "inter-provincial collaborative planning and market mechanisms", aiming to bring together research results in the fields of source-grid-load-storage collaborative planning, power market, and intelligent decision-making. It discusses the key theories, methods, and engineering practices of inter-provincial power balance, collaborative planning, and market mechanism design. The scope of submissions includes but is not limited to: spatio-temporal correlation characteristic analysis of renewable energy and load, source-load output simulation and prediction, power balance time-series production simulation, source-grid-load-storage collaborative planning and solution, multi-agent cost-benefit calculation for source-grid-load-storage, power market design and transaction mechanism, and planning platform application technologies such as data fusion, digital twin, and intelligent decision-making for power systems.

专题会议（十二）：面向日前-日内-实时多元市场的虚拟电厂聚合商优化运行

Track 12: Optimal Operation of Virtual Power Plant Aggregators for Day-Ahead, Intra-Day and Real-Time Multi-Market

刘运鑫

Yunxin Liu

武汉大学

Wuhan University

陈宋宋

Songsong Chen

中国电力科学研究院

China Electric Power Research Institute

当前虚拟电厂交易方法多针对省级需求响应、调峰调频辅助服务市场下的资源调度与经济性优化，然而多元市场交易与多级电网支撑耦合下的虚拟电厂交易决策与优化运行存在分布式聚合资源经济性难以刻画、主动支撑功能价值难以评估、日前-日内-实时耦合决策困难以及内部异构多主体利益难以分配等问题。需要深入探讨融合市场需求预测、智能组合报价、虚拟电厂优化运行和多视角价值评估方法体系构建方法，实现虚拟电厂在多元多级市场中跨时域联动智能报价与高效优化运行。

Current virtual power plant trading methods mostly focus on resource scheduling and economic optimization under provincial-level demand response and peak-shaving/frequency-regulation auxiliary service markets. However, virtual power plant trading decisions and optimal operation under the coupling of multi-market transactions and multi-level grid support face challenges such as difficulty in characterizing the economics of distributed aggregated resources, difficulty in evaluating the value of active support functions, difficulty in day-ahead/intra-day/real-time coupled decision-making, and difficulty in distributing benefits among internal heterogeneous multi-agents. There is a need to deeply explore methods for integrating market demand prediction, intelligent portfolio bidding, virtual power plant optimal operation, and multi-perspective value assessment methodologies to achieve cross-time-domain coordinated intelligent bidding and efficient optimal operation of virtual power plants in multi-market and multi-level markets.

专题会议（十三）：面向新型电力系统负荷管理的大模型与智能体技术

Track 13: Large Models and Agent Technologies for Load Management in Modern Power Systems

张俊

Zhang Jun

武汉大学

Wuhan University

蒋怀光

Huaiguang Jiang

华南理工大学

South China University of Technology

戴小然

Xiaoran Dai

武汉大学

Wuhan University

随着新能源渗透率提升、需求侧资源多元化以及运行数据在时序量测、文本规程、视觉巡检等多模态上的指数级增长，现代电力系统负荷管理面临前所未有的挑战。传统单模态方法难以捕捉跨模态语义，无法满足全局负荷管理决策需求。

本专题探讨大模型与智能体AI如何为电力系统负荷管理构建新型认知基础设施。征稿方向包括：通过时序-文本-图像统一编码与任务感知解码策略构建领域适配的多模态大模型；设计基于形式化通信协议与混合记忆机制的自主智能体工具协同系统；通过向量-符号融合与领域知识图谱约束下的反事实校验保障推理可信性；借助扩散模型场景合成与模块化评估框架实现模型对电网运行态势的持续自适应；以及面向多智能体协作的分层任务分解与能力感知动态调度。

本专题欢迎将AI基础研究与电力工程实践相结合的论文，涵盖新型模型架构、训练方法论到已部署系统在需求响应、负荷预测、虚拟电厂运行及配用电侧智能化中取得实际成效的研究成果。理论分析与应用导向研究均受欢迎。

With the increase in renewable energy penetration, diversification of demand-side resources, and exponential growth of operational data across multiple modalities such as time-series measurements, textual procedures, and visual inspections, load management in modern power systems faces unprecedented challenges. Traditional single-modal methods struggle to capture cross-modal semantics and cannot meet the requirements of global load management decision-making.

This track explores how large models and agent AI can build a new cognitive infrastructure for power system load management. Submission directions include: building domain-adapted multi-modal large models through time-series-text-image unified encoding and task-aware decoding strategies; designing autonomous agent tool collaboration systems based on formalized communication protocols and hybrid memory mechanisms; ensuring reasoning credibility through vector-symbol fusion and counterfactual verification under domain knowledge graph constraints; achieving continuous model adaptation to grid operation situations through diffusion model scenario synthesis and modular evaluation frameworks; and implementing hierarchical task decomposition and capability-aware dynamic scheduling for multi-agent collaboration.

This track welcomes papers that combine AI fundamental research with power engineering practice, covering research results from new model architectures and training methodologies to deployed systems that have achieved practical results in demand response, load forecasting, virtual power plant operation, and distribution-side intelligence. Both theoretical analysis and application-oriented research are welcome.

专题会议（十四）：面向现代电力系统的先进潮流求解算法及应用

Track 14: Advanced Power Flow Solving Algorithms and Applications for Modern Power Systems

张逸

Yi Zhang

福州大学

Fuzhou University

刘承锡

Chengxi Liu

武汉大学

Wuhan University

郑宗华

Zonghua Zheng

福州大学

Fuzhou University

高比例新能源接入、电力电子化、配电网分布式资源渗透，以及低碳运行需求的提出，使现代电力系统的运行点呈现强不确定性，网络结构日益不平衡和交直流混合；同时，电–碳市场、风险感知运行等下游应用对潮流计算提出了新的需求——不仅要求精确的稳态解，更要求灵敏度信息、概率分布以及可复用的离线–在线结构。在这一背景下，"求解潮流"已从单一算法演化为一类面向精度、可扩展性、鲁棒性与复用性的先进算法体系，并衍生出日益丰富的工程应用。

本session 聚焦面向现代电力系统的先进潮流求解算法及其应用，征集主题包括但不限于：全纯嵌入潮流方法及其多维拓展；连续潮流与电压稳定裕度评估；新能源不确定性下的概率潮流与区间潮流；三相不平衡潮流；含HVDC 和换流器接口的交直流混合潮流；数据驱动与学习型潮流代理模型；潮流与碳排放流等其它物理层的耦合计算；以及上述方法在调度、规划、稳定分析与电–碳市场等场景中的应用。

本session 旨在为研究者与工程师提供交流平台，围绕方法的收敛性保证、面向省级电网的可扩展性、跨工况复用性等开放问题展开讨论；欢迎围绕算法进展及其在实际配电或输电系统中的应用的理论与案例研究投稿。

High-proportion renewable energy integration, power electronics, distributed resource penetration in distribution networks, and low-carbon operation requirements have made the operating points of modern power systems exhibit strong uncertainty, and the network structure is increasingly unbalanced and AC-DC hybrid. At the same time, downstream applications such as electricity-carbon markets and risk-aware operation have put forward new requirements for power flow calculation - not only requiring accurate steady-state solutions, but also sensitivity information, probability distributions, and reusable offline-online structures. Against this background, "solving power flow" has evolved from a single algorithm to an advanced algorithm system oriented towards accuracy, scalability, robustness, and reusability, and has derived increasingly rich engineering applications.

This session focuses on advanced power flow solving algorithms and their applications for modern power systems. Topics include but are not limited to: holomorphic embedding power flow methods and their multi-dimensional extensions; continuation power flow and voltage stability margin assessment; probabilistic and interval power flow under renewable energy uncertainty; three-phase unbalanced power flow; AC-DC hybrid power flow with HVDC and converter interfaces; data-driven and learning-based power flow surrogate models; coupled calculation of power flow with other physical layers such as carbon emission flow; and applications of the above methods in scenarios such as dispatch, planning, stability analysis, and electricity-carbon markets.

This session aims to provide a platform for researchers and engineers to exchange ideas, focusing on open issues such as convergence guarantees of methods, scalability for provincial-level power grids, and cross-condition reusability. Theoretical and case studies on algorithm advances and their applications in actual distribution or transmission systems are welcome.