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Two-stage stochastic optimization for cost-minimal charging of electric vehicles at public charging stations with photovoltaics

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  • Seddig, Katrin
  • Jochem, Patrick
  • Fichtner, Wolf

Abstract

Electric vehicles are one promising technology towards an improved sustainable transportation sector, especially when charged with electricity from renewable energy sources. However, the fluctuating generation of renewable energy resources, as well as the changing driving patterns of electric vehicles, have the offset of an uncertain nature. This paper compares three approaches (heuristic, optimization, and stochastic programming) to schedule the charging process of three different electric vehicles fleets (commuters, opportunity, and commercial fleets) at a common charging infrastructure under uncertainty. In the setting of a car park case study, several technical restrictions are taken into consideration when the load shift potential of the electric vehicles fleets are evaluated in order to minimize charging costs or to maximize the utilization of generated electricity by local photovoltaic. The two-stage Stochastic Mixed Integer Optimization Problem is solved by a Latin Hypercube based Sample Average Approximation method. Uncertainties of electricity generation by the photovoltaic system are considered by three different forecasting options and the mobility characteristics of the three electric vehicles fleets are modeled with a non-parametric probability density function (Kernel Density Estimation). The differences in charging costs and utilization of electricity from photovoltaic when applying the three approaches are identified and discussed. The numerical results show the feasibility to charge different electric vehicle fleets in a car park according to different signals and taking thereby technical restrictions as well as uncertainties into consideration. An operator for facilitation of the charging control is needed to enable the load flexibilities of each electric vehicle fleet.

Suggested Citation

  • Seddig, Katrin & Jochem, Patrick & Fichtner, Wolf, 2019. "Two-stage stochastic optimization for cost-minimal charging of electric vehicles at public charging stations with photovoltaics," Applied Energy, Elsevier, vol. 242(C), pages 769-781.
  • Handle: RePEc:eee:appene:v:242:y:2019:i:c:p:769-781
    DOI: 10.1016/j.apenergy.2019.03.036
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    References listed on IDEAS

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    1. Schuller, Alexander & Flath, Christoph M. & Gottwalt, Sebastian, 2015. "Quantifying load flexibility of electric vehicles for renewable energy integration," Applied Energy, Elsevier, vol. 151(C), pages 335-344.
    2. Paterakis, Nikolaos G. & Gibescu, Madeleine, 2016. "A methodology to generate power profiles of electric vehicle parking lots under different operational strategies," Applied Energy, Elsevier, vol. 173(C), pages 111-123.
    3. Weitzel, Timm & Glock, C. H., 2018. "Energy Management for Stationary Electric Energy Storage Systems: A Systematic Literature Review," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 88880, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    4. Long, Yin & Lee, Loo Hay & Chew, Ek Peng, 2012. "The sample average approximation method for empty container repositioning with uncertainties," European Journal of Operational Research, Elsevier, vol. 222(1), pages 65-75.
    5. Lai Wei & Yongpei Guan, 2014. "Optimal Control of Plug-In Hybrid Electric Vehicles with Market Impact and Risk Attitude," Transportation Science, INFORMS, vol. 48(4), pages 467-482, November.
    6. Iversen, Emil B. & Morales, Juan M. & Madsen, Henrik, 2014. "Optimal charging of an electric vehicle using a Markov decision process," Applied Energy, Elsevier, vol. 123(C), pages 1-12.
    7. Seddig, Katrin & Jochem, Patrick & Fichtner, Wolf, 2017. "Integrating renewable energy sources by electric vehicle fleets under uncertainty," Energy, Elsevier, vol. 141(C), pages 2145-2153.
    8. Figueiredo, Raquel & Nunes, Pedro & Brito, Miguel C., 2017. "The feasibility of solar parking lots for electric vehicles," Energy, Elsevier, vol. 140(P1), pages 1182-1197.
    9. Michael Freimer & Jeffrey Linderoth & Douglas Thomas, 2012. "The impact of sampling methods on bias and variance in stochastic linear programs," Computational Optimization and Applications, Springer, vol. 51(1), pages 51-75, January.
    10. Li, Ying & Davis, Chris & Lukszo, Zofia & Weijnen, Margot, 2016. "Electric vehicle charging in China’s power system: Energy, economic and environmental trade-offs and policy implications," Applied Energy, Elsevier, vol. 173(C), pages 535-554.
    11. Rubino, Luigi & Capasso, Clemente & Veneri, Ottorino, 2017. "Review on plug-in electric vehicle charging architectures integrated with distributed energy sources for sustainable mobility," Applied Energy, Elsevier, vol. 207(C), pages 438-464.
    12. Hafez, Omar & Bhattacharya, Kankar, 2017. "Optimal design of electric vehicle charging stations considering various energy resources," Renewable Energy, Elsevier, vol. 107(C), pages 576-589.
    13. Rahbari, Omid & Vafaeipour, Majid & Omar, Noshin & Rosen, Marc A. & Hegazy, Omar & Timmermans, Jean-Marc & Heibati, Seyedmohammadreza & Bossche, Peter Van Den, 2017. "An optimal versatile control approach for plug-in electric vehicles to integrate renewable energy sources and smart grids," Energy, Elsevier, vol. 134(C), pages 1053-1067.
    14. Emelogu, Adindu & Chowdhury, Sudipta & Marufuzzaman, Mohammad & Bian, Linkan & Eksioglu, Burak, 2016. "An enhanced sample average approximation method for stochastic optimization," International Journal of Production Economics, Elsevier, vol. 182(C), pages 230-252.
    15. Weitzel, Timm & Glock, Christoph H., 2018. "Energy management for stationary electric energy storage systems: A systematic literature review," European Journal of Operational Research, Elsevier, vol. 264(2), pages 582-606.
    16. Aghajani, Saemeh & Kalantar, Mohsen, 2017. "A cooperative game theoretic analysis of electric vehicles parking lot in smart grid," Energy, Elsevier, vol. 137(C), pages 129-139.
    17. Wu, Fei & Sioshansi, Ramteen, 2017. "A two-stage stochastic optimization model for scheduling electric vehicle charging loads to relieve distribution-system constraints," Transportation Research Part B: Methodological, Elsevier, vol. 102(C), pages 55-82.
    18. Yang, Zhile & Li, Kang & Foley, Aoife, 2015. "Computational scheduling methods for integrating plug-in electric vehicles with power systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 396-416.
    19. Tulpule, Pinak J. & Marano, Vincenzo & Yurkovich, Stephen & Rizzoni, Giorgio, 2013. "Economic and environmental impacts of a PV powered workplace parking garage charging station," Applied Energy, Elsevier, vol. 108(C), pages 323-332.
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