AI-Enhanced Strategies for Power Grid Operation and Resilience: Integration of Emerging Resources and Technologies

Dear Colleagues,

This Special Issue focuses on the role of artificial intelligence (AI) in enhancing the operation and resilience of next-generation power systems. As modern grids undergo rapid transformation due to the deep integration of renewable energy, electric vehicles (EVs), and distributed storage, both the structure and dynamics of power system operation are evolving. In particular, this publication will target the development of AI-driven strategies to address these complexities and to enable intelligent, flexible, and robust grid operation under conditions of growing uncertainty and volatility.

We invite original research articles and review papers addressing AI-enabled modeling, analysis, and control methods that align with the new operational paradigms of power systems. Topics of interest include, but are not limited to, the following areas:

• Artificial intelligence in next-generation power systems;
• Power system resilience enhancement;
• Vehicle to grid (V2G) technologies and grid interaction modeling;
• Coordination and control of distributed energy storage systems;
• AI-driven forecasting of load and renewable generation;
• Real-time optimization and intelligent control of power systems;
• Data-driven decision-making under grid uncertainty;
• Modeling of new resources and load behaviors in modern grids;
• Resilience-oriented grid planning and real-time reconfiguration;
• Reinforcement learning for distributed and coordinated control.

With the development of next-generation power systems, resources such as EVs and distributed storage are inevitably influencing grid operation, both proactively (e.g., demand-side participation, V2G) and passively (e.g., stochastic behavior, reverse power flow). As a result, the operational objectives of power systems are transitioning from traditional cost-effectiveness and reliability toward enhanced resilience, flexibility, and intelligence. This Special Issue aims to provide a dedicated platform for academic exchange on this topic, grounded in real-world engineering challenges. We seek to attract cutting-edge research from the power systems community and encourage interdisciplinary collaboration between academia and industry. We are particularly keen to publish contributions that combine advanced AI methods with practically relevant modelling approaches, with the goal of jointly addressing the emerging operational challenges of future grids.

While previous studies have explored AI applications in power systems or investigated the integration of emerging resources separately, there is a growing need for systematic research that addresses both dimensions in a unified framework. This Special Issue contributes to the existing literature by positioning AI, not just as a computational tool, but as a transformative enabler for managing the complexity and uncertainty introduced by new energy technologies. By bridging data-driven intelligence and domain-specific modeling, this Issue aims to enrich current knowledge and accelerate the transition toward resilient, adaptive, and intelligent power system operations.

Dr. Song Ke
Dr. Siyuan Chen
Dr. Hao Wu
Guest Editors

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