AI Speeds Up Energy Storage Scheduling for Underground Pumped Hydro

This research explores the application of decision-focused learning to optimize the scheduling of underground pumped hydro energy storage. The study's focus on accelerating this process suggests a significant potential impact on grid efficiency and renewable energy integration.

• •Applies decision-focused learning to optimize energy storage scheduling.
• •Focuses on underground pumped hydro systems.
• •Potentially improves grid efficiency and renewable integration.