This paper presents a Mix Integer Linear Programming (MILP) optimization approach to reduce peak demand and maximize revenue in a grid-connected building with a PV-equipped charging station for Shared EVs. The study investigates the impact of EV availability on the effectiveness
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This paper presents a Mix Integer Linear Programming (MILP) optimization approach to reduce peak demand and maximize revenue in a grid-connected building with a PV-equipped charging station for Shared EVs. The study investigates the impact of EV availability on the effectiveness of the system by comparing the results for different connection times of a fleet of Shared EVs, a private EV used for commuting, and a stationary battery. Results from the case study conducted in The Netherlands demonstrate that not only the duration but also the timing of EV connection significantly influence system effectiveness, emphasizing the need for accurate availability estimation. The trade-off between peak reduction and Peak-to-Average Ratio (PAR) reduction is also highlighted, underscoring the importance of considering both factors for optimizing charging station usage. These findings provide valuable insights for optimizing energy management, reducing peak loads, and increasing the utilization of renewable energy sources in the context of Shared EVs and V2G technology. @en