Anti-misoperation Control and Risk Prevention for New Power Systems

Submission Deadline: 28 February 2027 View: 49 Submit to Special Issue

Guest Editor(s)

Prof. Kaifeng Zhang

Email: kaifengzhang@seu.edu.cn

Affiliation: School of Automation, Southeast University, Nanjing, China

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Research Interests: power system dispatch and control, data analysis

Assist. Prof. Zhengmao Li

Email: zhengmao.li@aalto.fi

Affiliation: Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland

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Research Interests: multi energy system, uncertainty handling

Dr. Hao Wang

Email: hao.wang2@monash.edu

Affiliation: Department of Data Science & AI, Monash University, Melbourne, Australia

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Research Interests: power systems, energy management

Assist. Prof. Shunbo Lei

Email: leishunbo@cuhk.edu.cn

Affiliation: School of Science and Engineering, The Chinese University of Hong Kong, Shenzhen, China

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Research Interests: power and energy systems

Assoc. Prof. Chunyu Chen

Email: chunyuchen@cumt.edu.cn

Affiliation: Department of Electric Power Engineering, China University of Mining and Technology, Xuzhou, China

Homepage:

Research Interests: power systems

Summary

The new power systems are evolving rapidly due to high renewable energy penetration and digital transformation. This evolution, along with the diversification of market participants such as distributed generation operators, virtual power plants, and prosumers, has led to increased complexity in dispatch and control. Moreover, the rising frequency and intensity of extreme weather events threaten grid reliability.Given these challenges, it is crucial to explore advanced anti - misoperation control frameworks and multi - layered risk prevention strategies to ensure the stability and security of power systems.

The aim is to address the challenges posed by the complexity of new power systems and extreme weather events.This special issue focuses on integrating modern solutions like AI - driven predictive analytics, cyber - physical system protections, and adaptive market mechanisms. It also emphasizes compliance with standards for distributed resource integration.

Hybrid risk assessment models combining physical grid parameters with market behavior simulations, especially for compound disaster scenarios.Cross - disciplinary collaboration among power engineers, climate scientists, and market designers to ensure system security.Development of methodologies for real - time decision - making under uncertainty, human - machine interface optimization, and resilience quantification.

Topics of interest include, but are not limited to:
· Analysis on weak links and mis-operation of SCADA, AGC, AVC and other systems.
· Mechanism-driven and data-driven anomaly identification for power systems.
· Blocking methods and fault-tolerant strategy design for various abnormalities.
· Risk analysis and prevention for new power systems.
· Attack analysis and defense strategies for power Cyber-Physical Systems (CPS).
· Attack analysis and defense strategies for energy storage, renewable energy, power markets and other fields.

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