Wencong Su
Biographic Data
| ID | 6564050 |
|---|---|
| NAME | Wencong Su |
| GIVEN NAMES | Wencong |
| FAMILY NAME | Su |
| SIGNATURE | SU W |
| AFFILIATIONS | University of Michigan–Dearborn |
| ORCID | 0000-0003-1482-3078 |
| VERIFIED | Yes |
| TOTAL WORKS | 2 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 2 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2026 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
FairMarket-RL
Peer-to-peer (P2P) trading is increasingly recognized as a key mechanism for decentralized market regulation, yet existing approaches often lack robust frameworks to ensure fairness. This paper presents FairMarket-RL, a novel hybrid framework that combines Large Language Models (LLMs) with Reinforcement Learning (RL) to enable fairness-aware trading agents. In a simulated P2P microgrid with multiple sellers and buyers, the LLM acts as a real-time…
Scalable fairness shaping with LLM-guided multi-agent reinforcement learning for peer-to-peer electricity markets
Peer-to-peer (P2P) energy trading is becoming central to modern distribution systems as rooftop PV and home energy management systems become pervasive, yet most existing market and reinforcement learning(RL) designs emphasize efficiency or private profit and offer little real-time guidance to ensure equitable outcomes under uncertainty. To address this gap, we propose FairMarket-RL, a fairness-aware multiagent RL framework in which a large langua…
No prominent works on this page.
FairMarket-RL
Peer-to-peer (P2P) trading is increasingly recognized as a key mechanism for decentralized market regulation, yet existing approaches often lack robust frameworks to ensure fairness. This paper presents FairMarket-RL, a novel hybrid framework that combines Large Language Models (LLMs) with Reinforcement Learning (RL) to enable fairness-aware trading agents. In a simulated P2P microgrid with multiple sellers and buyers, the LLM acts as a real-time…
Scalable fairness shaping with LLM-guided multi-agent reinforcement learning for peer-to-peer electricity markets
Peer-to-peer (P2P) energy trading is becoming central to modern distribution systems as rooftop PV and home energy management systems become pervasive, yet most existing market and reinforcement learning(RL) designs emphasize efficiency or private profit and offer little real-time guidance to ensure equitable outcomes under uncertainty. To address this gap, we propose FairMarket-RL, a fairness-aware multiagent RL framework in which a large langua…
Smart Grid Energy Management (2 works) · Auction Theory and Applications (1 work) · Bidding (1 work) · Blockchain Technology Applications and Security (1 work) · Common value auction (1 work) · Demand response (1 work) · Distributed generation (1 work) · Electric Power System Optimization (1 work) · Electricity (1 work) · Mechanism Design (1 work)