ICPEA 2026 | Hefei, China
English: With the massive integration of heterogeneous resources such as distributed renewable energy, electric vehicles, energy storage systems, and flexible loads, distribution systems exhibit characteristics of high dimensionality, strong coupling, and high randomness. Traditional methods based on precise modeling and rule-driven control face significant challenges in complex scenarios. The rapid development of AI provides new perspectives for the operation and control of distribution systems. By leveraging big data and AI technologies, we can fully exploit the latent patterns in vast operational data to achieve key functions, including state perception, power forecasting, optimal dispatch, and autonomous decision-making. This forum aims to enhance the adaptive, self-learning, and self-optimizing capabilities of distribution systems, supporting their efficient, safe, and economic operation.
中文: 随着分布式新能源、电动汽车、储能系统、柔性负荷等海量异构资源接入，配电系统运行呈现出高维、强耦合、强随机性等特点，传统基于精确模型和规则驱动的控制方法在复杂场景下的适应能力面临挑战。人工智能技术的快速发展为配电系统运行控制提供了新思路。依托大数据、人工智能等技术，可充分挖掘海量运行数据中的潜在规律，实现配电系统运行状态感知、功率预测、运行优化和自主决策等关键功能，提升配电系统的自适应、自学习和自优化能力，支撑复杂配电系统的高效、安全、经济运行。