IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v313y2022ics030626192200201x.html
   My bibliography  Save this article

Sizing battery energy storage and PV system in an extreme fast charging station considering uncertainties and battery degradation

Author

Listed:
  • Rehman, Waqas ur
  • Bo, Rui
  • Mehdipourpicha, Hossein
  • Kimball, Jonathan W.

Abstract

This paper presents mixed integer linear programming (MILP) formulations to obtain optimal sizing for a battery energy storage system (BESS) and solar generation system in an extreme fast charging station (XFCS) to reduce the annualized total cost. The proposed model characterizes a typical year with eight representative scenarios and obtains the optimal energy management for the station and BESS operation to exploit the energy arbitrage for each scenario. Contrasting extant literature, this paper proposes a constant power constant voltage (CPCV) based improved probabilistic approach to model the XFCS charging demand for weekdays and weekends. This paper also accounts for the monthly and annual demand charges based on realistic utility tariffs. Furthermore, BESS life degradation is considered in the model to ensure no replacement is needed during the considered planning horizon. Different from the literature, this paper offers pragmatic MILP formulations to tally BESS charge/discharge cycles using the cumulative charge/discharge energy concept. McCormick relaxations and the Big-M method are utilized to relax the bi-linear terms in the BESS operational constraints. Finally, a robust optimization-based MILP model is proposed and leveraged to account for uncertainties in electricity price, solar generation, and XFCS demand. Case studies were performed to signify the efficacy of the proposed formulations.

Suggested Citation

  • Rehman, Waqas ur & Bo, Rui & Mehdipourpicha, Hossein & Kimball, Jonathan W., 2022. "Sizing battery energy storage and PV system in an extreme fast charging station considering uncertainties and battery degradation," Applied Energy, Elsevier, vol. 313(C).
    • Handle: RePEc:eee:appene:v:313:y:2022:i:c:s030626192200201x
    DOI: 10.1016/j.apenergy.2022.118745
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S030626192200201X
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2022.118745?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. Ding, Huajie & Hu, Zechun & Song, Yonghua, 2015. "Value of the energy storage system in an electric bus fast charging station," Applied Energy, Elsevier, vol. 157(C), pages 630-639.
    2. Akhtar Hussain & Van-Hai Bui & Ju-Won Baek & Hak-Man Kim, 2019. "Stationary Energy Storage System for Fast EV Charging Stations: Simultaneous Sizing of Battery and Converter," Energies, MDPI, vol. 12(23), pages 1-17, November.
    3. Ghimar Merhy & Ahmed Nait-Sidi-Moh & Nazih Moubayed, 2021. "A multi-objective optimization of electric vehicles energy flows: the charging process," Annals of Operations Research, Springer, vol. 296(1), pages 315-333, January.
    4. Sadeghi-Barzani, Payam & Rajabi-Ghahnavieh, Abbas & Kazemi-Karegar, Hosein, 2014. "Optimal fast charging station placing and sizing," Applied Energy, Elsevier, vol. 125(C), pages 289-299.
    5. Kevin R. Mallon & Francis Assadian & Bo Fu, 2017. "Analysis of On-Board Photovoltaics for a Battery Electric Bus and Their Impact on Battery Lifespan," Energies, MDPI, vol. 10(7), pages 1-31, July.
    6. Liu, Jingkun & Zhang, Ning & Kang, Chongqing & Kirschen, Daniel & Xia, Qing, 2017. "Cloud energy storage for residential and small commercial consumers: A business case study," Applied Energy, Elsevier, vol. 188(C), pages 226-236.
    7. Ahmad Almaghrebi & Fares Aljuheshi & Mostafa Rafaie & Kevin James & Mahmoud Alahmad, 2020. "Data-Driven Charging Demand Prediction at Public Charging Stations Using Supervised Machine Learning Regression Methods," Energies, MDPI, vol. 13(16), pages 1-21, August.
    8. Lisa Feeney & George H. Haines & Allan L. Riding, 1999. "Private investors' investment criteria: Insights from qualitative data," Venture Capital, Taylor & Francis Journals, vol. 1(2), pages 121-145, April.
    9. Dimitris Bertsimas & Melvyn Sim, 2004. "The Price of Robustness," Operations Research, INFORMS, vol. 52(1), pages 35-53, February.
    10. Ibrahim Alsaidan & Abdulaziz Alanazi & Wenzhong Gao & Hongyu Wu & Amin Khodaei, 2017. "State-Of-The-Art in Microgrid-Integrated Distributed Energy Storage Sizing," Energies, MDPI, vol. 10(9), pages 1-14, September.
    11. Germana Trentadue & Alexandre Lucas & Marcos Otura & Konstantinos Pliakostathis & Marco Zanni & Harald Scholz, 2018. "Evaluation of Fast Charging Efficiency under Extreme Temperatures," Energies, MDPI, vol. 11(8), pages 1-13, July.
    12. Zhihong Jin & Xin Lin & Linlin Zang & Weiwei Liu & Xisheng Xiao, 2021. "Lane Allocation Optimization in Container Seaport Gate System Considering Carbon Emissions," Sustainability, MDPI, vol. 13(7), pages 1-16, March.
    13. Mu, Yunfei & Wu, Jianzhong & Jenkins, Nick & Jia, Hongjie & Wang, Chengshan, 2014. "A Spatial–Temporal model for grid impact analysis of plug-in electric vehicles," Applied Energy, Elsevier, vol. 114(C), pages 456-465.
    14. Deepak Ronanki & Apoorva Kelkar & Sheldon S. Williamson, 2019. "Extreme Fast Charging Technology—Prospects to Enhance Sustainable Electric Transportation," Energies, MDPI, vol. 12(19), pages 1-17, September.
    15. Zafirakis, Dimitrios & Chalvatzis, Konstantinos J. & Baiocchi, Giovanni & Daskalakis, Georgios, 2016. "The value of arbitrage for energy storage: Evidence from European electricity markets," Applied Energy, Elsevier, vol. 184(C), pages 971-986.
    16. Bi, Zicheng & Keoleian, Gregory A. & Ersal, Tulga, 2018. "Wireless charger deployment for an electric bus network: A multi-objective life cycle optimization," Applied Energy, Elsevier, vol. 225(C), pages 1090-1101.
    17. 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.
    18. Grimm, Veronika & Orlinskaya, Galina & Schewe, Lars & Schmidt, Martin & Zöttl, Gregor, 2021. "Optimal design of retailer-prosumer electricity tariffs using bilevel optimization," Omega, Elsevier, vol. 102(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Paudel, Diwas & Das, Tapas K., 2023. "A deep reinforcement learning approach for power management of battery-assisted fast-charging EV hubs participating in day-ahead and real-time electricity markets," Energy, Elsevier, vol. 283(C).
    2. Juan A. Tejero-Gómez & Ángel A. Bayod-Rújula, 2024. "Sizing of Battery Energy Storage Systems for Firming PV Power including Aging Analysis," Energies, MDPI, vol. 17(6), pages 1-30, March.
    3. Anna Manowska & Andrzej Nowrot, 2022. "Solar Farms as the Only Power Source for the Entire Country," Energies, MDPI, vol. 15(14), pages 1-15, July.
    4. Zhouquan Wu & Pradeep Krishna Bhat & Bo Chen, 2023. "Optimal Configuration of Extreme Fast Charging Stations Integrated with Energy Storage System and Photovoltaic Panels in Distribution Networks," Energies, MDPI, vol. 16(5), pages 1-20, March.
    5. Asrin Seyedzahedi & Salah Bahramara, 2023. "Facilitating Investment in Photovoltaic Systems in Iran Considering Time-of-Use Feed-in-Tariff and Carbon Market," Energies, MDPI, vol. 16(3), pages 1-20, January.
    6. Tostado-Véliz, Marcos & Rezaee Jordehi, Ahmad & Zhou, Yuekuan & Mansouri, Seyed Amir & Jurado, Francisco, 2024. "Best-case-aware planning of photovoltaic-battery systems for multi-mode charging stations," Renewable Energy, Elsevier, vol. 225(C).
    7. Sohani, Ali & Cornaro, Cristina & Shahverdian, Mohammad Hassan & Moser, David & Pierro, Marco & Olabi, Abdul Ghani & Karimi, Nader & Nižetić, Sandro & Li, Larry K.B. & Doranehgard, Mohammad Hossein, 2023. "Techno-economic evaluation of a hybrid photovoltaic system with hot/cold water storage for poly-generation in a residential building," Applied Energy, Elsevier, vol. 331(C).
    8. Houssem R. E. H. Bouchekara & Yusuf A. Sha’aban & Mohammad S. Shahriar & Saad M. Abdullah & Makbul A. Ramli, 2023. "Sizing of Hybrid PV/Battery/Wind/Diesel Microgrid System Using an Improved Decomposition Multi-Objective Evolutionary Algorithm Considering Uncertainties and Battery Degradation," Sustainability, MDPI, vol. 15(14), pages 1-38, July.
    9. Grzegorz Hołdyński & Zbigniew Skibko & Andrzej Borusiewicz & Andrzej Marczuk & Adam Koniuszy, 2024. "Effect of Reactive Power Generation in Photovoltaic Installations on the Voltage Value at the Inverter Connection Point," Energies, MDPI, vol. 17(19), pages 1-12, September.
    10. Àlex Alonso-Travesset & Diederik Coppitters & Helena Martín & Jordi de la Hoz, 2023. "Economic and Regulatory Uncertainty in Renewable Energy System Design: A Review," Energies, MDPI, vol. 16(2), pages 1-30, January.
    11. Zhou, Siyu & Han, Yang & Mahmoud, Karar & Darwish, Mohamed M.F. & Lehtonen, Matti & Yang, Ping & Zalhaf, Amr S., 2023. "A novel unified planning model for distributed generation and electric vehicle charging station considering multi-uncertainties and battery degradation," Applied Energy, Elsevier, vol. 348(C).
    12. Irina Picioroaga & Madalina Luca & Andrei Tudose & Dorian Sidea & Mircea Eremia & Constantin Bulac, 2023. "Resilience-Driven Optimal Sizing of Energy Storage Systems in Remote Microgrids," Sustainability, MDPI, vol. 15(22), pages 1-16, November.

    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. Ahmed Abdalrahman & Weihua Zhuang, 2017. "A Survey on PEV Charging Infrastructure: Impact Assessment and Planning," Energies, MDPI, vol. 10(10), pages 1-25, October.
    2. Boud Verbrugge & Mohammed Mahedi Hasan & Haaris Rasool & Thomas Geury & Mohamed El Baghdadi & Omar Hegazy, 2021. "Smart Integration of Electric Buses in Cities: A Technological Review," Sustainability, MDPI, vol. 13(21), pages 1-23, November.
    3. Natascia Andrenacci & Roberto Ragona & Antonino Genovese, 2020. "Evaluation of the Instantaneous Power Demand of an Electric Charging Station in an Urban Scenario," Energies, MDPI, vol. 13(11), pages 1-19, May.
    4. Morro-Mello, Igoor & Padilha-Feltrin, Antonio & Melo, Joel D. & Heymann, Fabian, 2021. "Spatial connection cost minimization of EV fast charging stations in electric distribution networks using local search and graph theory," Energy, Elsevier, vol. 235(C).
    5. Rafał Kopacz & Michał Harasimczuk & Bartosz Lasek & Rafał Miśkiewicz & Jacek Rąbkowski, 2021. "All-SiC ANPC Submodule for an Advanced 1.5 kV EV Charging System under Various Modulation Methods," Energies, MDPI, vol. 14(17), pages 1-16, September.
    6. Shariatio, O. & Coker, P.J. & Smith, S.T. & Potter, B. & Holderbaum, W., 2024. "An integrated techno-economic approach for design and energy management of heavy goods electric vehicle charging station with energy storage systems," Applied Energy, Elsevier, vol. 369(C).
    7. Buzna, Luboš & De Falco, Pasquale & Ferruzzi, Gabriella & Khormali, Shahab & Proto, Daniela & Refa, Nazir & Straka, Milan & van der Poel, Gijs, 2021. "An ensemble methodology for hierarchical probabilistic electric vehicle load forecasting at regular charging stations," Applied Energy, Elsevier, vol. 283(C).
    8. Xiang, Yue & Liu, Junyong & Li, Ran & Li, Furong & Gu, Chenghong & Tang, Shuoya, 2016. "Economic planning of electric vehicle charging stations considering traffic constraints and load profile templates," Applied Energy, Elsevier, vol. 178(C), pages 647-659.
    9. Zeng, Ziling & Wang, Tingsong & Qu, Xiaobo, 2024. "En-route charge scheduling for an electric bus network: Stochasticity and real-world practice," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 185(C).
    10. Guo, Sen & Zhao, Huiru, 2015. "Optimal site selection of electric vehicle charging station by using fuzzy TOPSIS based on sustainability perspective," Applied Energy, Elsevier, vol. 158(C), pages 390-402.
    11. Gang Chen & Dawei Hu & Steven Chien & Lei Guo & Mingzheng Liu, 2020. "Optimizing Wireless Charging Locations for Battery Electric Bus Transit with a Genetic Algorithm," Sustainability, MDPI, vol. 12(21), pages 1-20, October.
    12. Zhang, Li & Shaffer, Brendan & Brown, Tim & Scott Samuelsen, G., 2015. "The optimization of DC fast charging deployment in California," Applied Energy, Elsevier, vol. 157(C), pages 111-122.
    13. Jefferson Morán & Esteban Inga, 2022. "Characterization of Load Centers for Electric Vehicles Based on Simulation of Urban Vehicular Traffic Using Geo-Referenced Environments," Sustainability, MDPI, vol. 14(6), pages 1-20, March.
    14. Erdogan, Nuh & Pamucar, Dragan & Kucuksari, Sadik & Deveci, Muhammet, 2021. "An integrated multi-objective optimization and multi-criteria decision-making model for optimal planning of workplace charging stations," Applied Energy, Elsevier, vol. 304(C).
    15. Yan, Jie & Zhang, Jing & Liu, Yongqian & Lv, Guoliang & Han, Shuang & Alfonzo, Ian Emmanuel Gonzalez, 2020. "EV charging load simulation and forecasting considering traffic jam and weather to support the integration of renewables and EVs," Renewable Energy, Elsevier, vol. 159(C), pages 623-641.
    16. Phiraphat Antarasee & Suttichai Premrudeepreechacharn & Apirat Siritaratiwat & Sirote Khunkitti, 2022. "Optimal Design of Electric Vehicle Fast-Charging Station’s Structure Using Metaheuristic Algorithms," Sustainability, MDPI, vol. 15(1), pages 1-22, December.
    17. Liu, Zhaocai & Wang, Qichao & Sigler, Devon & Kotz, Andrew & Kelly, Kenneth J. & Lunacek, Monte & Phillips, Caleb & Garikapati, Venu, 2023. "Data-driven simulation-based planning for electric airport shuttle systems: A real-world case study," Applied Energy, Elsevier, vol. 332(C).
    18. Zhang, Jing & Yan, Jie & Liu, Yongqian & Zhang, Haoran & Lv, Guoliang, 2020. "Daily electric vehicle charging load profiles considering demographics of vehicle users," Applied Energy, Elsevier, vol. 274(C).
    19. Yuping Lin & Kai Zhang & Zuo-Jun Max Shen & Lixin Miao, 2019. "Charging Network Planning for Electric Bus Cities: A Case Study of Shenzhen, China," Sustainability, MDPI, vol. 11(17), pages 1-27, August.
    20. Foda, Ahmed & Mohamed, Moataz, 2024. "The impacts of optimization approaches on BEB system configuration in transit," Transport Policy, Elsevier, vol. 151(C), pages 12-23.

    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:313:y:2022:i:c:s030626192200201x. 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.