IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v238y2025ics0960148124020512.html
   My bibliography  Save this article

Application potential of rooftop photovoltaics (PV) in elevated metro station for a low-carbon future: Characteristic analysis and strategies for supply-demand mismatch

Author

Listed:
  • Yang, Haobo
  • Guan, Bowen
  • Zhang, Ji
  • Zhang, Tao
  • Liu, Xiaohua
  • Wang, Xinke

Abstract

Integrating photovoltaic (PV) system offers a promising solution to mitigate energy demand within the metro system, promoting cleaner electricity and contributing to a low-carbon future. However, due to discrepancies between PV power generation and energy demand profiles, on-site PV utilization remains suboptimal. Currently, there is a research gap concerning mismatch deconstruction based on formative principles. Addressing this gap, the study proposes a novel mismatch deconstruction approach that deconstructs mismatches along three dimensions: quantity, stagger, and shape. The findings reveal that, in the baseline scenario, quantity mismatch dominates, accounting for 62.6 %, and stagger mismatch and shape mismatch contribute 34.3 % and 3.1 %, respectively. Furthermore, the mapping relationship between mismatch deconstruction and mitigation strategies is explored and solutions for scenarios where different deconstruction results are the main contradictions is provided. Results shows that quantity mismatch represents PV capacity requirements, while stagger mismatch and shape mismatch signify energy storage capacity needs. When the quantity mismatch ratio is below 0.5, the investment preference is completely biased towards energy storage. Leveraging the deconstruction, an investment optimization method is introduced to maximize renewable energy supply and maximize economic benefits. It is hoped that the study provides valuable insights into a sustainable and low-carbon future for transport industry.

Suggested Citation

  • Yang, Haobo & Guan, Bowen & Zhang, Ji & Zhang, Tao & Liu, Xiaohua & Wang, Xinke, 2025. "Application potential of rooftop photovoltaics (PV) in elevated metro station for a low-carbon future: Characteristic analysis and strategies for supply-demand mismatch," Renewable Energy, Elsevier, vol. 238(C).
    • Handle: RePEc:eee:renene:v:238:y:2025:i:c:s0960148124020512
    DOI: 10.1016/j.renene.2024.121983
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148124020512
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2024.121983?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. Gul, Eid & Baldinelli, Giorgio & Bartocci, Pietro & Bianchi, Francesco & Domenghini, Piergiovanni & Cotana, Franco & Wang, Jinwen, 2022. "A techno-economic analysis of a solar PV and DC battery storage system for a community energy sharing," Energy, Elsevier, vol. 244(PB).
    2. Niveditha, N. & Rajan Singaravel, M.M., 2022. "Optimal sizing of hybrid PV–Wind–Battery storage system for Net Zero Energy Buildings to reduce grid burden," Applied Energy, Elsevier, vol. 324(C).
    3. Ding, Feng & Yang, Jianping & Zhou, Zan, 2023. "Economic profits and carbon reduction potential of photovoltaic power generation for China's high-speed railway infrastructure," Renewable and Sustainable Energy Reviews, Elsevier, vol. 178(C).
    4. Kaabeche, A. & Belhamel, M. & Ibtiouen, R., 2011. "Sizing optimization of grid-independent hybrid photovoltaic/wind power generation system," Energy, Elsevier, vol. 36(2), pages 1214-1222.
    5. Liu, Jia & Chen, Xi & Yang, Hongxing & Li, Yutong, 2020. "Energy storage and management system design optimization for a photovoltaic integrated low-energy building," Energy, Elsevier, vol. 190(C).
    6. Liu, Aaron & Miller, Wendy & Cholette, Michael E. & Ledwich, Gerard & Crompton, Glenn & Li, Yong, 2021. "A multi-dimension clustering-based method for renewable energy investment planning," Renewable Energy, Elsevier, vol. 172(C), pages 651-666.
    7. Liu, Xinglei & Liu, Jun & Liu, Jiacheng & Yang, Yin, 2024. "Multi-period optimal capacity expansion planning scheme of regional integrated energy systems considering multi-time scale uncertainty and generation low-carbon retrofit," Renewable Energy, Elsevier, vol. 231(C).
    8. Naderipour, Amirreza & Kamyab, Hesam & Klemeš, Jiří Jaromír & Ebrahimi, Reza & Chelliapan, Shreeshivadasan & Nowdeh, Saber Arabi & Abdullah, Aldrin & Hedayati Marzbali, Massoomeh, 2022. "Optimal design of hybrid grid-connected photovoltaic/wind/battery sustainable energy system improving reliability, cost and emission," Energy, Elsevier, vol. 257(C).
    9. Yang, Songpo & Chen, Yanyan & Dong, Zhurong & Wu, Jianjun, 2023. "A collaborative operation mode of energy storage system and train operation system in power supply network," Energy, Elsevier, vol. 276(C).
    10. Liu, Xiaochen & Fu, Zhi & Qiu, Siyuan & Zhang, Tao & Li, Shaojie & Yang, Zhi & Liu, Xiaohua & Jiang, Yi, 2023. "Charging private electric vehicles solely by photovoltaics: A battery-free direct-current microgrid with distributed charging strategy," Applied Energy, Elsevier, vol. 341(C).
    11. Chen, Qi & Kuang, Zhonghong & Liu, Xiaohua & Zhang, Tao, 2022. "Energy storage to solve the diurnal, weekly, and seasonal mismatch and achieve zero-carbon electricity consumption in buildings," Applied Energy, Elsevier, vol. 312(C).
    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. Guan, Bowen & Yang, Haobo & Zhang, Tao & Liu, Xiaohua & Wang, Xinke, 2024. "Technoeconomic analysis of rooftop PV system in elevated metro station for cost-effective operation and clean electrification," Renewable Energy, Elsevier, vol. 226(C).
    2. Rasool, Muhammad Haseeb & Taylan, Onur & Perwez, Usama & Batunlu, Canras, 2023. "Comparative assessment of multi-objective optimization of hybrid energy storage system considering grid balancing," Renewable Energy, Elsevier, vol. 216(C).
    3. Chen, Qi & Kuang, Zhonghong & Liu, Xiaohua & Zhang, Tao, 2024. "Optimal sizing and techno-economic analysis of the hybrid PV-battery-cooling storage system for commercial buildings in China," Applied Energy, Elsevier, vol. 355(C).
    4. Luo, Jianing & Yuan, Yanping & Joybari, Mahmood Mastani & Cao, Xiaoling, 2024. "Development of a prediction-based scheduling control strategy with V2B mode for PV-building-EV integrated systems," Renewable Energy, Elsevier, vol. 224(C).
    5. Jiaxin Lu & Weijun Wang & Yingchao Zhang & Song Cheng, 2017. "Multi-Objective Optimal Design of Stand-Alone Hybrid Energy System Using Entropy Weight Method Based on HOMER," Energies, MDPI, vol. 10(10), pages 1-17, October.
    6. Eid Gul & Giorgio Baldinelli & Pietro Bartocci, 2022. "Energy Transition: Renewable Energy-Based Combined Heat and Power Optimization Model for Distributed Communities," Energies, MDPI, vol. 15(18), pages 1-18, September.
    7. Fitsum Salehu Kebede & Jean-Christophe Olivier & Salvy Bourguet & Mohamed Machmoum, 2021. "Reliability Evaluation of Renewable Power Systems through Distribution Network Power Outage Modelling," Energies, MDPI, vol. 14(11), pages 1-25, May.
    8. Fu, Zhi & Liu, Xiaochen & Zhang, Ji & Zhang, Tao & Liu, Xiaohua & Jiang, Yi, 2025. "Orderly solar charging of electric vehicles and its impact on charging behavior: A year-round field experiment," Applied Energy, Elsevier, vol. 381(C).
    9. Khiareddine, Abla & Ben Salah, Chokri & Rekioua, Djamila & Mimouni, Mohamed Faouzi, 2018. "Sizing methodology for hybrid photovoltaic /wind/ hydrogen/battery integrated to energy management strategy for pumping system," Energy, Elsevier, vol. 153(C), pages 743-762.
    10. Kamjoo, Azadeh & Maheri, Alireza & Putrus, Ghanim A., 2014. "Chance constrained programming using non-Gaussian joint distribution function in design of standalone hybrid renewable energy systems," Energy, Elsevier, vol. 66(C), pages 677-688.
    11. Li, Wanying & Dong, Fugui & Liu, Jiamei & Wang, Peijun & Zhao, Xinru, 2024. "A three-stage decision-making study on capacity configuration of hydropower-wind-photovoltaic-storage complementary systems considering uncertainty," Energy, Elsevier, vol. 313(C).
    12. Jaszczur, Marek & Hassan, Qusay & Palej, Patryk & Abdulateef, Jasim, 2020. "Multi-Objective optimisation of a micro-grid hybrid power system for household application," Energy, Elsevier, vol. 202(C).
    13. Maleki, Akbar & Ameri, Mehran & Keynia, Farshid, 2015. "Scrutiny of multifarious particle swarm optimization for finding the optimal size of a PV/wind/battery hybrid system," Renewable Energy, Elsevier, vol. 80(C), pages 552-563.
    14. Idiano D'Adamo & Alessandro Dell'Aguzzo & Marco Pruckner, 2024. "Residential photovoltaic and energy storage systems for sustainable development: An economic analysis applied to incentive mechanisms," Sustainable Development, John Wiley & Sons, Ltd., vol. 32(1), pages 84-100, February.
    15. Khojaste Effatpanah, Saeed & Rahbari, Hamid Reza & Ahmadi, Mohammad H. & Farzaneh, Ali, 2023. "Green hydrogen production and utilization in a novel SOFC/GT-based zero-carbon cogeneration system: A thermodynamic evaluation," Renewable Energy, Elsevier, vol. 219(P2).
    16. Tan, Bifei & Chen, Simin & Liang, Zipeng & Zheng, Xiaodong & Zhu, Yanjin & Chen, Haoyong, 2024. "An iteration-free hierarchical method for the energy management of multiple-microgrid systems with renewable energy sources and electric vehicles," Applied Energy, Elsevier, vol. 356(C).
    17. Upadhyay, Subho & Sharma, M.P., 2016. "Selection of a suitable energy management strategy for a hybrid energy system in a remote rural area of India," Energy, Elsevier, vol. 94(C), pages 352-366.
    18. 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).
    19. Chen, Jun & Garcia, Humberto E., 2016. "Economic optimization of operations for hybrid energy systems under variable markets," Applied Energy, Elsevier, vol. 177(C), pages 11-24.
    20. Duchaud, Jean-Laurent & Notton, Gilles & Darras, Christophe & Voyant, Cyril, 2019. "Multi-Objective Particle Swarm optimal sizing of a renewable hybrid power plant with storage," Renewable Energy, Elsevier, vol. 131(C), pages 1156-1167.

    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:renene:v:238:y:2025:i:c:s0960148124020512. 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.journals.elsevier.com/renewable-energy .

    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.