Recently, a study co-authored by Wenqing Ai, a lecturer in the Department of Management Science at USTB's School of Economics and Management, was published in Manufacturing & Service Operations Management, a top UTD24-listed journal.
The paper, titled *Crowdsourcing Electric Vehicles for Omni-Sharing Distributed Energy Storage*, proposes a new model that combines fixed and mobile energy storage for communities.
Ai is the first author. Co-authors include Professor Tianhu Deng of Soochow University, Associate Professor Wei Qi of Tsinghua University, and Professor Wei Gu of the Department of Management Science at SEM.
Traditional peer-to-peer energy sharing relies heavily on fixed storage. The proposed omni-sharing model first uses a community's fixed storage to meet demand, then crowdsources electricity from nearby electric vehicles, and finally turns to the grid.
The authors designed a crowdsourcing payment scheme that accounts for EV charging costs, battery degradation, spatial matching, and EV owners' opportunity costs, and derived optimal prices and quantities to minimize community operating costs. They also modeled storage sharing among residents as a cooperative game and extended the classic newsvendor model to determine optimal storage investment.
Using residential electricity data and ride-hailing market data, the authors found that omni-sharing improves supply-demand matching, reduces community storage investment, and remains resilient under changing technology and prices.
Manufacturing & Service Operations Management is published by INFORMS and is one of the most influential journals in operations management.
