Full-scale electric vehicles penetration in the Danish Island of Bornholm—Optimal scheduling and battery degradation under driving constraints

Abstract The paper proposes an analysis of a 100% electric vehicle (EV) scenario on the energy system of the island of Bornholm in Denmark. The paper intends to present challenges and opportunities that a realistic system would face when completely shifting to electric transportation. The EVs are subject to different charging strategies in order to assess the impact on the grid, the potential savings on the charging cost and the effects on battery degradation. In contrast to uncontrolled charging, smart charging strategies are designed not only to satisfy the same charging requirements at the EV departure time, but also maximize the savings on the charging cost and avoid interconnection congestions. Smart strategies bring a reduction in annual charging cost around 12%, on top of a reduction in the degradation because of lower average SOC and number of cycles. Moreover, results show a limited benefit in bidirectional charging because of a marginal increase in savings: this more demanding operation, which allows discharges, leads to higher battery degradation, due to the increase in the number of cycles.

[1]  R. Loisel,et al.  Large-scale deployment of electric vehicles in Germany by 2030: An analysis of grid-to-vehicle and vehicle-to-grid concepts , 2014 .

[2]  Mattia Marinelli,et al.  Grid Loading Due to EV Charging Profiles Based on Pseudo-Real Driving Pattern and User Behavior , 2019, IEEE Transactions on Transportation Electrification.

[3]  Egoitz Martinez-Laserna,et al.  Li-Ion Battery Lifetime Model’s Influence on the Economic Assessment of a Hybrid Electric Bus’s Operation , 2018, World Electric Vehicle Journal.

[4]  D. Sauer,et al.  Calendar and cycle life study of Li(NiMnCo)O2-based 18650 lithium-ion batteries , 2014 .

[5]  Donghan Feng,et al.  Decentralized charging control strategy of the electric vehicle aggregator based on augmented Lagrangian method , 2019, International Journal of Electrical Power & Energy Systems.

[6]  Magdy M. A. Salama,et al.  Economical staging plan for implementing electric vehicle charging stations , 2017 .

[7]  J. Apt,et al.  Lithium-ion battery cell degradation resulting from realistic vehicle and vehicle-to-grid utilization , 2010 .

[8]  Marina Gonzalez Vaya,et al.  Optimal Bidding Strategy of a Plug-In Electric Vehicle Aggregator in Day-Ahead Electricity Markets Under Uncertainty , 2015, IEEE Transactions on Power Systems.

[9]  M. Verbrugge,et al.  Degradation of lithium ion batteries employing graphite negatives and nickel-cobalt-manganese oxide + spinel manganese oxide positives: Part 1, aging mechanisms and life estimation , 2014 .

[10]  Heinz Wenzl,et al.  Comparison of different approaches for lifetime prediction of electrochemical systems—Using lead-acid batteries as example , 2008 .

[11]  Samveg Saxena,et al.  Quantifying electric vehicle battery degradation from driving vs. vehicle-to-grid services , 2016 .

[12]  F. Marra,et al.  Electric vehicle charge planning using Economic Model Predictive Control , 2012, 2012 IEEE International Electric Vehicle Conference.

[13]  Le Anh Tuan,et al.  Effects of plug-in electric vehicle charge scheduling on the day-ahead electricity market price , 2012, 2012 3rd IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe).

[14]  Peter Bach Andersen,et al.  Enhancing the Role of Electric Vehicles in the Power Grid: Field Validation of Multiple Ancillary Services , 2017, IEEE Transactions on Transportation Electrification.

[15]  Thomas Bruckner,et al.  Effects of electric vehicle charging strategies on the German power system , 2017 .

[16]  Mehmet Uzunoglu,et al.  A double-layer smart charging strategy of electric vehicles taking routing and charge scheduling into account , 2016 .

[17]  Antonio Zecchino,et al.  A Market Framework for Enabling Electric Vehicles Flexibility Procurement at the Distribution Level Considering Grid Constraints , 2018, 2018 Power Systems Computation Conference (PSCC).

[18]  Mattia Marinelli,et al.  Economic value of electric vehicle reserve provision in the Nordic countries under driving requirements and charger losses , 2019 .

[19]  L. Ochoa,et al.  How Electric Vehicles and the Grid Work Together: Lessons Learned from One of the Largest Electric Vehicle Trials in the World , 2018, IEEE Power and Energy Magazine.

[20]  Peter Bach Andersen,et al.  Added Value of Individual Flexibility Profiles of Electric Vehicle Users For Ancillary Services , 2018, 2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm).

[21]  Zhiwei Xu,et al.  Evaluation of Achievable Vehicle-to-Grid Capacity Using Aggregate PEV Model , 2017, IEEE Transactions on Power Systems.

[22]  Muhammad Babar,et al.  Online scheduling of plug-in vehicles in dynamic pricing schemes , 2016 .

[23]  Michela Robba,et al.  An optimization model for electrical vehicles scheduling in a smart grid , 2018 .

[24]  Simon F. Schuster,et al.  Calendar Aging of Lithium-Ion Batteries I. Impact of the Graphite Anode on Capacity Fade , 2016 .

[25]  John W. Polak,et al.  Electric vehicle charging choices: Modelling and implications for smart charging services , 2017 .