Business-oriented optimization of EV-to-building energy flows: Predictive modeling and scenario evaluation

Jie Dai, Qiong Yuan, Helen Huifen Cai, Vince Zhang, Md. Hasanuzaman and J. Selvaraj

Energy, 2025, vol. 333, issue C

Abstract: This study presents a hybrid electric vehicle-to-building (EV-t-B) energy management system that integrates high-resolution demand forecasting with real-world scheduling constraints to reduce peak electricity loads in institutional buildings. The framework comprises two components: (1) a machine learning module that forecasts next-day electricity demand at 15-min intervals using historical sub-metering and environmental data, and (2) a mixed-integer linear programming (MILP) optimization model that generates feasible charging/discharging schedules for EVs under multiple operational constraints.

Keywords: EV-To-building; Machine learning; Stakeholder constraints; Demand forecasting; Peak shaving; MILP optimization; Smart building; Energy management systems (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:333:y:2025:i:c:s0360544225030981

DOI: 10.1016/j.energy.2025.137456

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