6 papers
Learning in Stackelberg Markov Games
Jun He, Andrew L. Liu, Yihsu Chen
Designing socially optimal policies in multi-agent environments is a fundamental challenge in both economics and artificial intelligence. This paper studies a general framework for…
A Hybrid Mean Field Framework for Aggregators Participating in Wholesale Electricity Markets
Jun He, Andrew L. Liu
The rapid growth of distributed energy resources (DERs), including rooftop solar and energy storage, is transforming the grid edge, where distributed technologies and customer-side…
Carbon-Aware Data Center Workload Allocation: Emission Disclosure, Capacity Leasing, and Contract Reshuffling
Yihsu Chen, Abel Souza, Fargol Nematkhah +1
The rapid adoption of AI has driven rapid growth in computational demand, with large language models (LLMs) at the forefront since ChatGPT's debut in 2022. Meanwhile, large amounts…
Evaluating the Impact of Multiple DER Aggregators on Wholesale Energy Markets: A Hybrid Mean Field Approach
Jun He, Andrew L. Liu
The integration of distributed energy resources (DERs) into wholesale energy markets can greatly enhance grid flexibility, improve market efficiency, and contribute to a more susta…
Decentralized Integration of Grid Edge Resources into Wholesale Electricity Markets via Mean-field Games
Chen Feng, Andrew L. Liu
Grid edge resources refer to distributed energy resources (DERs) located on the consumer side of the electrical grid, controlled by consumers rather than utility companies. Integra…
Peer-to-Peer Energy Trading of Solar and Energy Storage: A Networked Multiagent Reinforcement Learning Approach
Chen Feng, Andrew L. Liu
Utilizing distributed renewable and energy storage resources in local distribution networks via peer-to-peer (P2P) energy trading has long been touted as a solution to improve ener…