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@INPROCEEDINGS{Riebesel:1020541,
      author       = {Riebesel, Lea and Xhonneux, André and Müller, Dirk},
      title        = {{D}egradation-cost-aware scheduling of electric vehicle
                      charging and discharging},
      reportid     = {FZJ-2024-00254},
      year         = {2023},
      abstract     = {Degradation-cost-aware scheduling of electric vehicle
                      charging and discharging Lithium-ion battery degradation is
                      strongly dependent on operating conditions. Battery
                      degradation imposes costs on electric vehicle owners. To
                      ensure economically viable participation in vehicle-to-grid
                      schemes, the cost of battery degradation due to battery
                      cycling for this purpose has to be taken into account. Cycle
                      depth is one crucial stress factor for battery operation
                      according to tests. Therefore, an optimization model for a
                      vehicle-to-grid-enabled electric vehicle is presented that
                      schedules charging and discharging while modeling calendar
                      degradation as a function of state of charge. To keep the
                      model computationally tractable, a mixed-integer linear
                      program is formulated. Battery degradation in terms of
                      capacity loss is defined as a piecewise-linear function
                      based on an empirical model. In the model, capacity loss due
                      to calendar aging is dependent on state of charge and
                      capacity loss due to cycle aging is dependent on number of
                      full equivalent cycles. In a case study, we optimize the
                      charging and discharging schedule of a
                      vehicle-to-grid-enabled electric vehicle in a household for
                      the prediction horizon of one day. Energy costs consist of
                      an energy costs and a power costs. The energy cost is based
                      on electricity cost per unit. The power price is based on
                      grid fee costs per unit of the daily peak power use. The
                      schedules aim to minimize both energy costs and battery
                      degradation costs. The study compares state of charge levels
                      for the described degradation-cost-aware model to a
                      reference model without degradation cost model. By
                      comparison to the reference model, the study shows that
                      degradation-cost-aware scheduling is able to reduce the
                      degradation.},
      month         = {Apr},
      date          = {2023-04-09},
      organization  = {Advanced Battery Power 2023, Aachen
                       (Germany), 9 Apr 2023 - 11 Apr 2023},
      subtyp        = {After Call},
      cin          = {IEK-10},
      cid          = {I:(DE-Juel1)IEK-10-20170217},
      pnm          = {1122 - Design, Operation and Digitalization of the Future
                      Energy Grids (POF4-112) / LLEC::VxG - Integration von
                      "Vehicle-to-grid" (BMBF-03SF0628)},
      pid          = {G:(DE-HGF)POF4-1122 / G:(DE-Juel1)BMBF-03SF0628},
      typ          = {PUB:(DE-HGF)24},
      doi          = {10.34734/FZJ-2024-00254},
      url          = {https://juser.fz-juelich.de/record/1020541},
}