Panel Sessions

1. 报告论坛名称：Cyber-physical power system interdependency and security

2. 主持人：王宇教授, 重庆大学 / Prof. Yu Wang, Chongqing University

3. 时间：12月19日下午2点-3点半 / 2:00pm-3:30pm, Dec.19, 2025

Name/Affiliation
姓名+单位

Position
职位

Presentation Title
报告题目

Presentation Abstract
报告摘要

刘健哲, 上海交通大学
Jianzhe Liu, Shanghai Jiao Tong University

副教授 Associate Professor

Steady-state and Dynamic Stability Analysis and Control for Cyber-Physical Microgrids

This seminar reports the stability and control of cyber-physical microgrids under denial-of-service (DoS) attacks that disrupt communication among distributed controllers. As microgrids increasingly depend on real-time data exchange for coordination, such communication failures can threaten both steady-state power balance and dynamic stability. Drawing on our related studies, we present analytical frameworks for steady-state feasibility and dynamic resilience, showing how DoS events alter system models, affect operating points, and introduce switching dynamics. The seminar concludes with insights into resilient control design that enables microgrids to maintain stable and reliable operation amid cyber disturbances.

章谦之, 浙江大学
Qianzhi Zhang, Zhejiang University

教授
Professor

Cybersecurity of the Future Grid: From Coordinated Substations Attacks to Resilient Microgrid Control

The rapid advancement of smart grid technology has equipped power systems with highly automated communication networks, significantly enhancing grid monitoring and response capabilities. However, this growing connectivity also expands the attack surface, making the grid a prime target for cyberattacks. This presentation will explore the critical intersection of cyber threats and defense strategies through two concrete examples: smart substations and networked microgrids (NMGs). First, we will unveil a novel coordinated cyberattack targeting smart substations. This attack exploits vulnerabilities in the IEC 61850 process layer by employing a covert communication protocol to embed malicious commands within Sampled Value (SV) and GOOSE messages. Second, we will introduce an improved Asynchronous Distributed Leader-Follower Control (ADLFC) method for voltage/var control in NMGs. This method is enhanced with a built-in cybersecurity strategy, specifically designed to mitigate the impacts of Denial-of-Service (DoS) attacks and Continuous Communication Failures (CCFs), thereby ensuring robust voltage control and guaranteed algorithm convergence.

夏侯凯顺, 华南理工大学
Kaishun Xiahou, South China University of Technology

副教授 Associate Professor

Cyber-Physical Security Assessment and Defense for Power Systems with Renewable Energy

The integration of computation, communication, and control technology has given rise to the emergence and rapid advancement of cyber-physical power systems (CPPSs), which improves the operational efficiency of power systems while also introducing new security risks. Additionally, the high penetration of renewable energy resources increases the uncertainty of power system operation, reduces system inertia, and further elevates the security challenges faced by CPPSs. Therefore, it is crucial to develop comprehensive security risk assessment methods, investigate effective defense strategies against cyber attacks, and propose new mitigation measures for cascading failure to ensure the secure operation of CPPSs. This presentation highlights the recent research in cyber-physical security assessment and defense for power systems with renewable energy, in order to enhance the security, reliability and resilience of power systems with renewable energy.

姚巍涛，西交利物浦大学
Weitao Yao, Xi'an Jiaotong-Liverpool University

助理教授 Assistant Professor

Advanced Distributed Control and Stability Analysis for Cyber-Physical Microgrid Systems

The microgrid (MG) and the networked microgrid (NMG) system formed by interconnecting multiple MGs are cyber-physical systems with coupled electrical and communication networks. Such systems, along with their corresponding hierarchical control frameworks, can introduce new stability issues due to intrinsic characteristics and non-ideal communication networks, such as low-inertia properties, time delays, and cyber-attacks. This report will investigate and analyze the aforementioned issues by designing a cyber-attack detector, appropriate controllers or control frameworks, and performing corresponding stability analysis simultaneously. The focus is mainly on the following aspects: distributed control to enhance the time-delay margin for cyber-physical MG systems; attack detection & location and cyber-resilient control against cyber-attacks for cyber-physical MG systems; distributed layered control for low-inertia cyber-physical NMG systems; stability analysis and time-delay compensation control for cyber-physical NMG systems.

崔秋实, 重庆大学
Qiushi Cui, Chongqing University

副教授 Associate Professor

Research on Simulation Technology and Software Development of Electric Power Physical Information System

In an era where digitalization and intelligence are advancing by leaps and bounds, power systems are becoming increasingly complex. Traditional analysis methods can no longer satisfy the stringent demands for high accuracy and real-time performance. Against this backdrop, the simulation technology of cyber-physical power systems has emerged. By integrating the physical characteristics of power grids with modern information processing, it builds virtual models that can mirror and analyze the operating state of real-world systems in real time, providing robust decision support for planning, design, operation and maintenance. This talk will take an in-depth look at recent research progress in cyber-physical power-system simulation, covering its theoretical foundations, key enabling technologies and real-world engineering case studies. Particular emphasis will be placed on introducing power-system simulation software developed on this technology, demonstrating its remarkable advantages in enhancing reliability, optimizing resource allocation and reducing operating costs, thereby offering strong technical underpinning for the digital transformation and sustainable development of the power industry.

1. 报告论坛名称：AI-Enabled Construction of New Power Systems

2. 主持人：林伟副教授, 重庆大学 / Assoc. Prof. Wei Lin, Chongqing University

3. 时间：12月19日下午2点-3点半 / 2:00pm-3:30pm, Dec. 19, 2025

Name/Affiliation
姓名+单位

Position
职位

Presentation Title
报告题目

Presentation Abstract
报告摘要

俞耀文，华中科技大学
Yaowen Yu, Huazhong University of Science and Technology

副教授 Associate Professor

Strategic bidding in electricity markets with price-quantity pairs based on deep reinforcement learning considering competitors’ behaviors and job-shop scheduling

In a deregulated electricity market, self-interested market participants have incentives to bid strategically to maximize their own profits. However, existing studies on strategic bidding often ignore competitors’ bidding behaviors and only consider strategic actions on prices without quantities. Furthermore, it is important for a smart factory with substantial demand to jointly study its electricity strategic bidding and job-shop scheduling. On the supply side, this talk presents a novel deep reinforcement learning-based framework to model and solve the strategic bidding problem of a producer. To capture competitors’ historical bidding behaviors in the market environment, their demand-bid mappings are established based on a data-driven method combining K-medoids clustering and a deep neural network. To make full use of the bidding action space and increase the profit of the strategic producer, a bilevel optimization model considering bids in price-quantity pairs is formulated. To efficiently solve the problem with competitors’ bidding behaviors, an imitation learning-enhanced deep reinforcement learning algorithm is developed to improve training stability and convergence in complex action spaces. On the demand side, the electricity strategic bidding and job-shop scheduling of a smart factory are innovatively integrated and formulated as a bilevel optimization model. Numerical results demonstrate the profitability and robustness of our approach for a producer under market dynamics, as well as the benefits of comprehensive participation in industrial demand response for a smart factory.

陆帅, 东南大学Shuai Lu, Southeast University

副教授 Associate Professor

PowerBiMIP: An Open-Source, Efficient Bilevel Mixed-Integer Programming Solver for Power & Energy Systems

Bilevel Mixed-Integer Programming (BiMIP) is a critical modeling tool for power system planning and operation, yet its application is severely limited by high computational complexity and a lack of versatile, user-friendly toolkits. To address these challenges, we have developed PowerBiMIP, an open-source MATLAB-based solver designed to make advanced optimization accessible to researchers in the power and energy domain. PowerBiMIP integrates a “disciplined bilevel programming framework” (DBP) for automated model reformulation, a suite of high-performance algorithms for rapid large-scale problem solving, and a thriving open-source community with extensive documentation and application cases. By bridging the gap between operations research theory and practical engineering applications, PowerBiMIP provides a powerful and easy-to-use platform that supports scientific research and education in the power and energy domain.

邱伟, 湖南大学
Wei Qiu, Hunan University

助理教授 Assistant Professor

Research on Deep Model–Data-Driven Fault Perception and Traceability in Power Grids

In modern power systems, fault categories and locations are highly complex, making it challenging to accurately detect fault types and pinpoint their origins. To address this challenge, we propose a deep model–data-driven framework for fault perception and traceability in power grids. The framework comprises: (i) high-precision synchrophasor measurement techniques; (ii) anti-interference triggering and targeted feature extraction for disturbance and fault signals; and (iii) a deep model–data-driven multi-task graph network for integrated fault perception and traceability.

吴江华, 深圳市大数据研究院
Jianghua Wu, Shenzhen Institute of Big Data Research

副研究员/Associate Researcher

Multiple Decomposition Algorithms for Large Scale Security-Constrained Unit Commitment

The secure and economic operation of large-scale power systems relies on Security-Constrained Unit Commitment (SCUC), which is normally formulated as a large scale mixed-integer linear programming (MILP) problem. The high-dimensional decision space and tightly coupled constraints induce rapidly escalating combinatorial complexity of SCUC, posing intractable computational challenges. This talk presents a suite of efficient decomposition-based optimization frameworks, centered on surrogate Lagrangian relaxation, temporal decomposition, and succesive fixing. These frameworks successfully enhance solution efficiency and scalability in ultra large instances, offering practically implementable and innovative schemes for power system operations.

1. 报告论坛名称：Interaction Between Multi-type Flexible Resources and the Power Grid

2. 主持人：
张儒峰教授, 东北电力大学 / Prof. Rufeng Zhang, Northeast Electric Power University
吴昊助理研究员, 天津大学 / Assistant Researcher, Hao Wu, Tianjin University

3. 时间：12月19日下午4点到6点 / 4:00pm-6:00pm, Dec.19, 2025

Name/Affiliation
姓名+单位

Position
职位

Presentation Title
报告题目

Presentation Abstract
报告摘要

章锐, 东北电力大学
Rui Zhang, Northeast Electric Power University

副教授 Associate Professor

Assessing the Multi-Dimensional Responsive Capability of Central Air Conditioning Systems Considering Carbon Emissions and Apparent Temperature

As the proportion of new energy integrated into the power grid gradually increases, its power characteristics, which were previously implicit in the power system dominated by thermal power units, will become increasingly prominent—such as faster, more persistent, and continuous power fluctuations. Tapping into the regulatory capacity of central air-conditioning (CAC) on the load side is one of the effective measures to address the aforementioned power fluctuations. However, the traditional CAC assessment method based on a 15-minute cycle struggles to respond effectively. Against the backdrop of demands for low-carbon operation and high comfort, this paper proposes a multi-dimensional regulatory capacity assessment model for CAC that accounts for carbon emissions and perceived temperature, aiming to effectively tackle the aforementioned power fluctuations.
Firstly, an operation model based on perceived temperature is constructed to correct the operating characteristics of CAC, enabling the acquisition of more accurate operation plans. Secondly, a CAC operation model considering carbon emissions is established to provide insights into the adjustable capacity of CAC under low-carbon operation scenarios. On this basis, assessment models for the rapid regulatory capacity, continuous regulatory capacity, and residual regulatory capacity of CAC loads are developed, which can effectively respond to the increasingly prominent fast, persistent, and continuous power fluctuations in the new-type power system. Finally, the effectiveness of the proposed method is verified using the CAC load data from an actual building.

吴昊, 天津大学
Hao Wu, Tianjin University

助理研究员 Assistant Researcher

Optimal Collaborative Scheduling Method of Emergency Resources for Enhancing Distribution System Resilience under Extreme Disasters

In recent years, with the growing frequency of extreme disasters induced by global climate change, severe challenges have been posed to the safe and stable operation of power distribution systems. The resulting power outages have caused enormous economic losses and significant social impacts. In response, this report elaborates on the research on the optimal coordinated scheduling of emergency resources aimed at enhancing the resilience of power distribution systems.
The research comprehensively considers the spatial allocation and dynamic scheduling of various types of emergency resources, including emergency repair teams, mobile power sources and other emergency vehicles. Meanwhile, it incorporates responsive loads into post-disaster recovery to provide support for improving system resilience. In addition, a coordinated restoration mechanism between the power distribution system and multiple other infrastructures such as communication networks and transmission networks has been established. This mechanism offers technical support and decision-making basis for the rapid cross-system restoration and resilience enhancement of power distribution systems under extreme disaster conditions.

陈思远, 武汉大学
Siyuan Chen, Wuhan University

助理研究员 Assistant Researcher

Key Technologies for Flexible Complementarity and Intelligent Dispatch of Hydro-Solar-Wind Integrated Systems

In accordance with China’s 14th Five-Year Plan for Renewable Energy Development, Yunnan has become the country’s first integrated hydro-solar-wind energy base facing scenarios where the installed capacity of new energy exceeds 40% and its power generation accounts for over 20%. Yunnan Province has vigorously developed new energy dominated by wind and photovoltaic power, which has effectively alleviated the provincial power shortage amid the context of simultaneous deficits in both power capacity and electricity supply. However, the power grid operation of the integrated hydro-solar-wind energy base needs to address uncertainties from broader sources and across more time scales: the short-term randomness and volatility of new energy are superimposed with the long-term randomness and volatility of hydropower. This study starts from the generation side and grid side of the hydro-solar-wind system, focuses on the complementary characteristics of multiple resources on the generation side to support the day-ahead dispatching of the power grid, investigates the system-level proactive dispatching issue on the grid side to formulate the intraday re-dispatching strategy of the power grid, and achieves the coordination of generation, grid, load, and energy storage through the connection between the day-ahead and intraday two-stage dispatching. 关键术语说明

付麟博，东北电力大学
Linbo Fu, Northeast Electric Power University

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Research on energy management and transaction strategy for microgrid participating in distribution market

With the continuous increase in the number and scale of distributed energy resources(DERs), the safe and stable operation of distribution networks is facing severe challenges. As an aggregated carrier for diversified DERs, microgrids have become a key technology to address this challenge. However, relying solely on technical means to operate and manage microgrids makes it difficult to proactively improve the absorption capacity of DERs and achieve collaborative interaction between microgrids and distribution networks. Utilizing market mechanisms to guide the energy management of microgrids is one of the important ways to solve this problem. Therefore, this presentation takes microgrids as the research object, under the background of participating in the distribution market, and follows the idea of "transaction pricing → energy management → risk preference decision-making", respectively proposing the transaction pricing methods for active and reactive power of microgrids, the energy management methods of microgrids , and the transaction strategies and energy management methods of microgrids participating in the distribution market under uncertainty. The purpose is to improve the economic benefits of microgrids, stimulate the potential of DERs within microgrids, explore the complementary and mutual support capabilities between microgrids and distribution networks, and thereby enhance the operational flexibility of distribution networks.

1. 报告论坛名称：Face-to-Face with Young Faculties

2. 主持人：杨知方教授，重庆大学 / Prof. Zhifang Yang, Chongqing University

3. 时间：12月19日下午4-6点 / 4:00pm-6:00pm, Dec. 19, 2025

Name 姓名

Position 职位

Affiliation 单位

周念成 Niancheng Zhou

教授 Professor

重庆大学 Chongqing University

刘玉乾 Yuqian Liu

副教授 Associate Professor

西安交通大学 Xi'an Jiaotong University

孙晓荣 Xiaorong Sun

副教授 Associate Professor

河海大学 Hohai University

邱伟 Wei Qiu

助理教授 Assistant Professor

湖南大学 Hunan University

王怡 Yi Wang

助理研究员 Assistant Researcher