AI RESEARCH
Towards Affordable Energy: A Gymnasium Environment for Electric Utility Demand-Response Programs
arXiv CS.AI
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ArXi:2605.12462v1 Announce Type: new Extreme weather and volatile wholesale electricity markets expose residential consumers to catastrophic financial risks, yet demand response at the distribution level remains an underutilized tool for grid flexibility and energy affordability. While a demand-response program can shield consumers by issuing financial credits during high-price periods, optimizing this sequential decision-making process presents a unique challenge for reinforcement learning despite the plentiful offline historical smart meter and wholesale pricing data available publicly.