Vice Chair 1 : Zongsheng Zheng, Sichuan University, China

Vice Chair 2 : Shilin Gao, Sichuan University, China

Description of the Session:
In the context of the “Dual Carbon” goals and the development of new-type power systems, the widespread integration of large-scale power electronic equipment, a high proportion of renewable energy, and diverse types of loads has endowed the power system with new characteristics, such as strong coupling, weak damping, low inertia, and significant uncertainty. Traditional stability analysis and control methods, which rely on analytical models and hierarchical control frameworks, face challenges including high modeling complexity, time-varying parameters, and significant multi-timescale coupling. This special issue focuses on “AI-Enabled Stability Mechanism Analysis and Adaptive Control Technologies for New-Type Power Systems”, concentrating on the mechanistic reconstruction and control paradigm shift for power system stability under conditions of high power electronics penetration. It explores new theories and methods that integrate data-driven approaches with physical models. The aim is to establish an interdisciplinary platform connecting power system stability analysis, artificial intelligence algorithms, and engineering applications, thereby promoting the development of an intelligent stability control system with real-time sensing, autonomous decision-making, and adaptive control capabilities. This effort seeks to provide technical support for the secure, resilient, and efficient operation of future power grids.

Related Topics:
· Analysis of multi-timescale stability mechanisms and dynamic coupling characteristics in power systems with high power electronic devices penetration
· Unified modeling and criterion construction methods for frequency, voltage, and rotor angle coupling stability issues
· Application of physics-constrained machine learning and mechanism-integrated modeling in stability analysis
· Data-driven methods for small-signal stability assessment and fast transient stability discrimination techniques
· Online inertia estimation and damping characteristic identification methods under high uncertainty scenarios
· Reinforcement learning and adaptive control strategies for coordinated regulation of source-grid-load-storage systems
· Intelligent identification and mitigation techniques for wide-frequency oscillations and sub-synchronous oscillations
· Stability situation awareness, risk prediction, and decision support systems for large-scale power grids
· Multi-agent collaborative control and distributed stability assurance mechanisms
· Application of digital twin and real-time simulation technologies in the validation of stability control strategies