Session 11: AI methodologies in the Operation and Planning of Power Systems

AI methodologies in the Operation and Planning of Power Systems
“电力系统运行与规划中的人工智能技术”

The global energy transition, driven by decarbonization, renewable energy integration, and electrification, has introduced unprecedented complexity and uncertainty into power systems. Traditional methods for operation and planning are increasingly challenged by the variability of renewables, the proliferation of distributed energy resources (DERs), fluctuating demand, and cybersecurity risks. Artificial intelligence (AI) has emerged as a transformative solution, offering advanced tools to address these challenges through data-driven insights, optimization, and adaptive decision-making.
AI methodologies—including machine learning (ML), deep learning (DL), reinforcement learning (RL), and advanced optimization—enable predictive, real-time, and long-term solutions for modern power systems. These techniques enhance forecasting accuracy for renewable generation and load demand, optimize resource allocation for DERs and energy storage, and improve grid resilience through fault detection and self-healing mechanisms. AI also supports dynamic pricing, voltage regulation, and the development of digital twins for grid simulation and testing.
This special session highlights the significance of AI in addressing critical challenges in power system operation and planning. Key topics include AI-driven forecasting, resilience enhancement, optimal resource management, and sustainable infrastructure planning. Additionally, the issue explores the need for interpretable and explainable AI to build trust in data-driven models and hybrid approaches that integrate physics-based principles with AI insights.
Despite its potential, AI implementation faces challenges such as data quality, scalability, and interoperability with legacy systems. Ethical considerations and the need for robust, transparent models are also critical.
This special session aims to showcase cutting-edge research, case studies, and reviews that advance the application of AI in power systems. By fostering collaboration among researchers, engineers, and industry stakeholders, we seek to accelerate the development of smarter, more adaptive, and sustainable energy networks. Contributions are invited to demonstrate innovative AI methodologies, address implementation barriers, and propose scalable solutions for the future of power systems.