Optimal V2G Scheduling of an EV With Calendar and Cycle Aging of Battery: An MILP Approach | IEEE Journals & Magazine | IEEE Xplore

Optimal V2G Scheduling of an EV With Calendar and Cycle Aging of Battery: An MILP Approach


Abstract:

Since battery cost represents a substantial part of an electric vehicle’s (EV) total cost, the degradation of EV battery and how it is affected by vehicle-to-grid (V2G) i...Show More

Abstract:

Since battery cost represents a substantial part of an electric vehicle’s (EV) total cost, the degradation of EV battery and how it is affected by vehicle-to-grid (V2G) is a concern. Battery degradation is too complex in terms of nonlinearity for practical optimization of V2G scheduling. This article develops a mixed-integer linear programming (MILP) model to optimize the V2G scheduling of an EV, considering a detailed degradation model for calendar aging and cycle aging. In the developed model, calendar aging is affected by the state of charge (SOC), battery age, and temperature. The cycle aging is affected by temperature, C-rate, and energy throughput. A case study is performed to minimize the annual operational cost for two different years of electricity cost and ambient temperature data. The results of the developed model are compared with four different cases: immediate charging, smart charging algorithms without V2G, V2G without degradation cost, and V2G with degradation cost as the objective function. It is shown that the developed V2G model achieves a slightly increased cycle aging due to usage in V2G. However, it reduces the overall scheduling cost of the EV by 48%–88% compared with the immediate charging and by 10%–73% compared with the smart charging.
Published in: IEEE Transactions on Transportation Electrification ( Volume: 10, Issue: 4, December 2024)
Page(s): 10497 - 10507
Date of Publication: 02 April 2024

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I. Introduction

Electrification of the transportation system using renewable energy would gradually decrease the emissions of greenhouse gases by relieving the energy dependency on fossil fuels. For this aim, EVs are accounted as one of the new technologies to reduce the economic and environmental concerns in the smart grid era. With the emergence of bidirectional power transfer capability for EVs, i.e., vehicle-to-grid (V2G), there has been a possibility to increase the grid utilization and reduce the cost for the EV owner [1]. A reoccurring concern and argument against V2G regards how the EV battery is affected by V2G usage. The concern is that the EV battery will age prematurely. Since the battery cost represents a substantial part of the EV’s total cost, this can reduce the value of the EV that in the worst case requires a premature battery replacement. The optimal scheduling of EVs thus requires to include EV battery degradation. The optimization problem then becomes more complex as it requires determining the optimized charge/discharge behavior of EVs to achieve the minimum cost, composed of charging cost, net discharge revenue, and cost of battery degradation [2].

References

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