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Online Aging-Aware Energy Optimization for Vehicle-Home-Grid Integration

2025/04/13 by Francesco Popolizio, Torsten Wik, Popolizio, Francesco +5
Engineering · #Electric Vehicles and Infrastructure #Electric and Hybrid Vehicle Technologies #FOS: Electrical engineering #FOS: Mathematics #Optimization and Control (math.OC) #Systems and Control (eess.SY) #Transportation and Mobility Innovations #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2504.09657

openalex publication_date 2025/04/13 · openalex created_date 2025/10/09 · openalex updated_date 2026/07/28

Abstract

This paper investigates the economic impact of vehicle-home-grid integration through an online optimization algorithm that manages energy flows between an electric vehicle, a household, and the electrical grid. The algorithm exploits vehicle-to-home (V2H) for self-consumption and vehicle-to-grid (V2G) for energy trading, adapting in real-time via a hybrid long short-term memory (LSTM) network for household load prediction and a nonlinear battery degradation model including cycle and calendar aging. Simulations show annual economic benefits up to EUR 3046.81 compared to smart unidirectional charging, despite a modest 1.96% increase in battery aging. Even under unfavorable market conditions, with no V2G revenue, V2H alone provides yearly savings of EUR 425.48. Sensitivity analyses on battery capacity, household load, and price ratios confirm the consistent benefits of bidirectional energy exchange, highlighting the role of EVs as active energy nodes for sustainable management.

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