Tracks 专题分论坛

Track 2

AI-Driven Forecasting and Optimization for Smart Microgrids | 面向智能微电网的人工智能预测与优化

Organizers / 组织者

  • Jiangjiao Xu, Lecturer, Shanghai University of Electric Power, China | 许江蛟,上海电力大学,讲师
  • Haiwen Chen, Lecturer, Hebei University of Technology, China | 陈海文,河北工业大学,讲师

Abstract / 论坛简介

With the large-scale integration of renewable energy and the rapid development of distributed power systems, smart microgrids play a vital role in enhancing energy efficiency, improving system flexibility, and supporting the transition toward low-carbon energy. However, the inherent uncertainty and complexity of microgrids pose significant challenges to forecasting and optimization. Advances in artificial intelligence provide powerful tools to address these issues, enabling breakthroughs in load and renewable energy forecasting, energy management optimization, storage scheduling, and multi-energy coordination. This forum aims to bring together leading experts and scholars worldwide to share the latest research progress, explore frontier challenges, and discuss future trends in AI-driven forecasting and optimization for smart microgrids, fostering synergy between academic research and engineering practice.

微电网在提升能源利用效率、增强系统灵活性和推动绿色低碳转型方面发挥着重要作用。然而,其高度不确定性和复杂性对预测与优化提出了新的挑战。人工智能技术为应对这些问题提供了强有力的工具,能够在负荷与可再生能源预测、能量管理策略优化以及多能协同方面展现出巨大潜力。本分论坛旨在汇聚国内外专家学者,交流预测与优化的最新研究进展,探讨人工智能在实际应用中的前沿问题与未来趋势,推动学术研究与工程实践的深度融合。

Topics / 主题范围

  • AI-based Renewable Energy and Load Forecasting Methods | 基于人工智能的可再生能源与负荷预测方法
  • Optimization Scheduling and Energy Management Strategies for Smart Microgrids | 智能微电网的优化调度与能量管理策略
  • Modeling, Optimization, and Coordinated Control of Energy Storage Systems | 储能系统建模、优化与协同控制
  • Uncertainty Modeling and Robust Optimization in Microgrids | 不确定性建模与鲁棒优化方法在微电网中的应用
  • Engineering Applications and Case Studies of AI in Microgrid Operation and Control | 人工智能在微电网运行控制中的工程应用与案例研究