IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i6p5480-d1102535.html
   My bibliography  Save this article

Capacity Allocation Method Based on Historical Data-Driven Search Algorithm for Integrated PV and Energy Storage Charging Station

Author

Listed:
  • Xiaogang Pan

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China)

  • Kangli Liu

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China
    TUM School of Engineering and Design, Technical University of Munich, 80333 Munich, Germany)

  • Jianhua Wang

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China)

  • Yutao Hu

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China)

  • Jianfeng Zhao

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China
    College of Information Science and Technology, Nanjing Forestry University, Nanjing 210037, China)

Abstract

The promotion of electric vehicles (EVs) is an important measure for dealing with climate change and reducing carbon emissions, which are widely agreed goals worldwide. Being an important operating mode for electric vehicle charging stations in the future, the integrated photovoltaic and energy storage charging station (PES-CS) is receiving a fair amount of attention and discussion. However, how to optimally configure photovoltaic and energy storage capacity to achieve the best economy is essential and a huge challenge to overcome. In this paper, based on the historical data-driven search algorithm, the photovoltaic and energy storage capacity allocation method for PES-CS is proposed, which determines the capacity ratio of photovoltaic and energy storage by analyzing the actual operation data, which is performed while considering the target of maximizing economic benefits. In order to achieve the proposed capacity allocation, the method is as follows: First, the economic benefit model of the charging stations is established, taking the net present value and investment payback period as evaluation indicators; then, by analyzing the operation data of the existing charging station with the target of maximizing economic benefits, the initial configuration capacity is obtained; finally, the capacity configuration is verified through a comprehensive case analysis for the actual operation data. The results show that the capacity configuration obtained through the data analysis features an optimized economic efficiency and photovoltaic utilization. The proposed method can provide a theoretical and practical basis for newly planned or improved large-scale charging stations.

Suggested Citation

  • Xiaogang Pan & Kangli Liu & Jianhua Wang & Yutao Hu & Jianfeng Zhao, 2023. "Capacity Allocation Method Based on Historical Data-Driven Search Algorithm for Integrated PV and Energy Storage Charging Station," Sustainability, MDPI, vol. 15(6), pages 1-16, March.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:6:p:5480-:d:1102535
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/6/5480/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/6/5480/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wei Chen & Lei Zheng & Hengjie Li & Xiping Pei, 2022. "An Assessment Method for the Impact of Electric Vehicle Participation in V2G on the Voltage Quality of the Distribution Network," Energies, MDPI, vol. 15(11), pages 1-14, June.
    2. Gong, Lili & Cao, Wu & Liu, Kangli & Yu, Yue & Zhao, Jianfeng, 2020. "Demand responsive charging strategy of electric vehicles to mitigate the volatility of renewable energy sources," Renewable Energy, Elsevier, vol. 156(C), pages 665-676.
    3. PraveenKumar, Seepana & Agyekum, Ephraim Bonah & Kumar, Abhinav & Velkin, Vladimir Ivanovich, 2023. "Performance evaluation with low-cost aluminum reflectors and phase change material integrated to solar PV modules using natural air convection: An experimental investigation," Energy, Elsevier, vol. 266(C).
    4. Pramod R. Sonawane & Sheetal Bhandari & Rajkumar Bhimgonda Patil & Sameer Al-Dahidi, 2023. "Reliability and Criticality Analysis of a Large-Scale Solar Photovoltaic System Using Fault Tree Analysis Approach," Sustainability, MDPI, vol. 15(5), pages 1-24, March.
    5. Iliana Ilieva & Bernt Bremdal, 2021. "Utilizing Local Flexibility Resources to Mitigate Grid Challenges at Electric Vehicle Charging Stations," Energies, MDPI, vol. 14(12), pages 1-15, June.
    6. 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.
    7. Jicheng Liu & Qiongjie Dai, 2020. "Portfolio Optimization of Photovoltaic/Battery Energy Storage/Electric Vehicle Charging Stations with Sustainability Perspective Based on Cumulative Prospect Theory and MOPSO," Sustainability, MDPI, vol. 12(3), pages 1-20, January.
    8. Sen Zhang & Jianfeng Zhao & Zhihong Zhao & Kangli Liu & Pengyu Wang & Bin Yang, 2019. "Decoupled Current Controller Based on Reduced Order Generalized Integrator for Three-Phase Grid-Connected VSCs in Distributed System," Energies, MDPI, vol. 12(12), pages 1-15, June.
    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. Ibrahim Alsaidan & Mohd Bilal & Muhannad Alaraj & Mohammad Rizwan & Fahad M. Almasoudi, 2023. "A Novel EA-Based Techno–Economic Analysis of Charging System for Electric Vehicles: A Case Study of Qassim Region, Saudi Arabia," Mathematics, MDPI, vol. 11(9), pages 1-31, April.
    2. Jieun Ihm & Bilal Amghar & Sejin Chun & Herie Park, 2023. "Optimum Design of an Electric Vehicle Charging Station Using a Renewable Power Generation System in South Korea," Sustainability, MDPI, vol. 15(13), pages 1-16, June.
    3. Zhou, Yuekuan & Cao, Sunliang & Hensen, Jan L.M., 2021. "An energy paradigm transition framework from negative towards positive district energy sharing networks—Battery cycling aging, advanced battery management strategies, flexible vehicles-to-buildings in," Applied Energy, Elsevier, vol. 288(C).
    4. Shahriyar Nasirov & Paula Gonzalez & Jose Opazo & Carlos Silva, 2023. "Development of Rooftop Solar under Netbilling in Chile: Analysis of Main Barriers from Project Developers’ Perspectives," Sustainability, MDPI, vol. 15(3), pages 1-18, January.
    5. Haiyan Meng & Yakai Lu & Zhe Tian & Xiangbei Jiang & Zhongqing Han & Jide Niu, 2023. "Performance Evaluation Method of Day-Ahead Load Prediction Models in a District Heating and Cooling System: A Case Study," Energies, MDPI, vol. 16(14), pages 1-19, July.
    6. Alya AlHammadi & Nasser Al-Saif & Ameena Saad Al-Sumaiti & Mousa Marzband & Tareefa Alsumaiti & Ehsan Heydarian-Forushani, 2022. "Techno-Economic Analysis of Hybrid Renewable Energy Systems Designed for Electric Vehicle Charging: A Case Study from the United Arab Emirates," Energies, MDPI, vol. 15(18), pages 1-20, September.
    7. Abraham Alem Kebede & Maitane Berecibar & Thierry Coosemans & Maarten Messagie & Towfik Jemal & Henok Ayele Behabtu & Joeri Van Mierlo, 2020. "A Techno-Economic Optimization and Performance Assessment of a 10 kW P Photovoltaic Grid-Connected System," Sustainability, MDPI, vol. 12(18), pages 1-29, September.
    8. Józef Ober & Janusz Karwot, 2022. "Pro-Ecological Behavior: Empirical Analysis on the Example of Polish Consumers," Energies, MDPI, vol. 15(5), pages 1-27, February.
    9. Zou, Wenke & Sun, Yongjun & Gao, Dian-ce & Zhang, Xu & Liu, Junyao, 2023. "A review on integration of surging plug-in electric vehicles charging in energy-flexible buildings: Impacts analysis, collaborative management technologies, and future perspective," Applied Energy, Elsevier, vol. 331(C).
    10. Junchao Cheng & Yongyi Huang & Hongjing He & Abdul Matin Ibrahimi & Tomonobu Senjyu, 2023. "Optimal Operation of CCHP System Combined Electric Vehicles Considering Seasons," Energies, MDPI, vol. 16(10), pages 1-21, May.
    11. KM Puja Bharti & Haroon Ashfaq & Rajeev Kumar & Rajveer Singh, 2024. "Designing a Bidirectional Power Flow Control Mechanism for Integrated EVs in PV-Based Grid Systems Supporting Onboard AC Charging," Sustainability, MDPI, vol. 16(20), pages 1-27, October.
    12. Abdulla, Hind & Sleptchenko, Andrei & Nayfeh, Ammar, 2024. "Photovoltaic systems operation and maintenance: A review and future directions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 195(C).
    13. Li, Zening & Su, Su & Jin, Xiaolong & Chen, Houhe, 2021. "Distributed energy management for active distribution network considering aggregated office buildings," Renewable Energy, Elsevier, vol. 180(C), pages 1073-1087.
    14. Haiqing Gan & Wenjun Ruan & Mingshen Wang & Yi Pan & Huiyu Miu & Xiaodong Yuan, 2024. "Bi-Level Planning of Electric Vehicle Charging Stations Considering Spatial–Temporal Distribution Characteristics of Charging Loads in Uncertain Environments," Energies, MDPI, vol. 17(12), pages 1-30, June.
    15. MD Shouquat Hossain & Laveet Kumar & Adeel Arshad & Jeyraj Selvaraj & A. K. Pandey & Nasrudin Abd Rahim, 2023. "A Comparative Investigation on Solar PVT- and PVT-PCM-Based Collector Constancy Performance," Energies, MDPI, vol. 16(5), pages 1-26, February.
    16. Khan, Sheher Yar & Waqas, Adeel & Kumar, Mahesh & Liu, Shuli & Shen, Yongliang & Chen, Tingsen & Shoaib, Muhammad & Khan, Muhammad Omair, 2024. "Experimental, numerical, and 4E assessment of photovoltaic module using macro-encapsulation of pure and nano phase change material: A comparative analysis," Energy, Elsevier, vol. 290(C).
    17. Abdulla Al Wahedi & Yusuf Bicer, 2020. "A Case Study in Qatar for Optimal Energy Management of an Autonomous Electric Vehicle Fast Charging Station with Multiple Renewable Energy and Storage Systems," Energies, MDPI, vol. 13(19), pages 1-26, September.
    18. Zhou, Yuekuan & Liu, Xiaohua & Zhao, Qianchuan, 2024. "A stochastic vehicle schedule model for demand response and grid flexibility in a renewable-building-e-transportation-microgrid," Renewable Energy, Elsevier, vol. 221(C).
    19. Motahareh Sagharidooz & Hamzeh Soltanali & José Torres Farinha & Hugo D. N. Raposo & José Edmundo de-Almeida-e-Pais, 2024. "Reliability, Availability, and Maintainability Assessment-Based Sustainability-Informed Maintenance Optimization in Power Transmission Networks," Sustainability, MDPI, vol. 16(15), pages 1-22, July.
    20. Ana Carolina Kulik & Édwin Augusto Tonolo & Alberto Kisner Scortegagna & Jardel Eugênio da Silva & Jair Urbanetz Junior, 2021. "Analysis of Scenarios for the Insertion of Electric Vehicles in Conjunction with a Solar Carport in the City of Curitiba, Paraná—Brazil," Energies, MDPI, vol. 14(16), pages 1-15, August.

    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:gam:jsusta:v:15:y:2023:i:6:p:5480-:d:1102535. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.