Market Clearing

Market clearing in electricity grids aims to efficiently allocate energy resources while ensuring grid stability and economic fairness, a task complicated by the increasing integration of volatile renewable energy sources. Current research focuses on improving the speed and accuracy of market clearing algorithms, employing techniques like physics-informed machine learning, deep learning with embedded optimization layers, and model-based reinforcement learning to approximate computationally expensive optimal power flow calculations. These advancements are crucial for enabling real-time grid management and facilitating a reliable transition to cleaner energy systems, improving both operational efficiency and market design.