D. Qiu

PowerMarketJax: A JAX Benchmark Suite for Multi-Agent Reinforcement Learning in Power Markets

This work introduces PowerMarketJax, a benchmark suite for MARL across five power markets: day-ahead wholesale, real-time balancing, ancillary services, peer-to-peer double auctions, and local flexibility, which implements its own clearing, pricing, and settlement rules while providing a common framework for learning a...

PowerZooJax: A JAX-based Power System Benchmark for Reinforcement Learning

Power system operation is a safety-critical sequential decision-making problem, making it a natural testbed for reinforcement learning (RL). However, existing RL environments for power systems are often narrow in scope and computationally limited by CPU-based simulation workflows, making large-scale evaluation difficul...

Risk-Aware Economic Scheduling for Hydrogen-Enabled Building Energy Systems Considering Extreme Weather Events

Uncertainty-aware reinforcement learning for joint optimization of data center operations and electricity market bidding