IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v242y2019icp769-781.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261919304301
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2019.03.036?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. 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.
    13. 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.
    14. 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.
    15. 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.
    16. 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.
    17. 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).
    18. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Shen, Zuo-Jun Max & Feng, Bo & Mao, Chao & Ran, Lun, 2019. "Optimization models for electric vehicle service operations: A literature review," Transportation Research Part B: Methodological, Elsevier, vol. 128(C), pages 462-477.
    3. Li, Xiaohui & Wang, Zhenpo & Zhang, Lei & Sun, Fengchun & Cui, Dingsong & Hecht, Christopher & Figgener, Jan & Sauer, Dirk Uwe, 2023. "Electric vehicle behavior modeling and applications in vehicle-grid integration: An overview," Energy, Elsevier, vol. 268(C).
    4. Eltoumi, Fouad M. & Becherif, Mohamed & Djerdir, Abdesslem & Ramadan, Haitham.S., 2021. "The key issues of electric vehicle charging via hybrid power sources: Techno-economic viability, analysis, and recommendations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    5. Hoarau, Quentin & Perez, Yannick, 2018. "Interactions between electric mobility and photovoltaic generation: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 510-522.
    6. 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.
    7. Mohammadi Landi, Meysam & Mohammadi, Mohammad & Rastegar, Mohammad, 2018. "Simultaneous determination of optimal capacity and charging profile of plug-in electric vehicle parking lots in distribution systems," Energy, Elsevier, vol. 158(C), pages 504-511.
    8. Zhang, Tianyang & Pota, Himanshu & Chu, Chi-Cheng & Gadh, Rajit, 2018. "Real-time renewable energy incentive system for electric vehicles using prioritization and cryptocurrency," Applied Energy, Elsevier, vol. 226(C), pages 582-594.
    9. Benedikt Finnah, 2022. "Optimal bidding functions for renewable energies in sequential electricity markets," OR Spectrum: Quantitative Approaches in Management, Springer;Gesellschaft für Operations Research e.V., vol. 44(1), pages 1-27, March.
    10. Nie, Qingyun & Zhang, Lihui & Tong, Zihao & Dai, Guyu & Chai, Jianxue, 2022. "Cost compensation method for PEVs participating in dynamic economic dispatch based on carbon trading mechanism," Energy, Elsevier, vol. 239(PA).
    11. Varone, Alberto & Heilmann, Zeno & Porruvecchio, Guido & Romanino, Alessandro, 2024. "Solar parking lot management: An IoT platform for smart charging EV fleets, using real-time data and production forecasts," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    12. Finnah, Benedikt & Gönsch, Jochen & Ziel, Florian, 2022. "Integrated day-ahead and intraday self-schedule bidding for energy storage systems using approximate dynamic programming," European Journal of Operational Research, Elsevier, vol. 301(2), pages 726-746.
    13. Golpîra, Hêriş & Khan, Syed Abdul Rehman, 2019. "A multi-objective risk-based robust optimization approach to energy management in smart residential buildings under combined demand and supply uncertainty," Energy, Elsevier, vol. 170(C), pages 1113-1129.
    14. García-Villalobos, J. & Zamora, I. & Knezović, K. & Marinelli, M., 2016. "Multi-objective optimization control of plug-in electric vehicles in low voltage distribution networks," Applied Energy, Elsevier, vol. 180(C), pages 155-168.
    15. Collath, Nils & Cornejo, Martin & Engwerth, Veronika & Hesse, Holger & Jossen, Andreas, 2023. "Increasing the lifetime profitability of battery energy storage systems through aging aware operation," Applied Energy, Elsevier, vol. 348(C).
    16. Boza, Pal & Evgeniou, Theodoros, 2021. "Artificial intelligence to support the integration of variable renewable energy sources to the power system," Applied Energy, Elsevier, vol. 290(C).
    17. Emilio Ghiani & Alessandro Serpi & Virginia Pilloni & Giuliana Sias & Marco Simone & Gianluca Marcialis & Giuliano Armano & Paolo Attilio Pegoraro, 2018. "A Multidisciplinary Approach for the Development of Smart Distribution Networks," Energies, MDPI, vol. 11(10), pages 1-29, September.
    18. Beatrice Marchi & Simone Zanoni & Marco Pasetti, 2019. "Multi-Period Newsvendor Problem for the Management of Battery Energy Storage Systems in Support of Distributed Generation," Energies, MDPI, vol. 12(23), pages 1-13, December.
    19. Stavros Lazarou & Vasiliki Vita & Lambros Ekonomou, 2018. "Protection Schemes of Meshed Distribution Networks for Smart Grids and Electric Vehicles," Energies, MDPI, vol. 11(11), pages 1-17, November.
    20. Chang, Hsiu-Chuan & Ghaddar, Bissan & Nathwani, Jatin, 2022. "Shared community energy storage allocation and optimization," Applied Energy, Elsevier, vol. 318(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:242:y:2019:i:c:p:769-781. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.