IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i7p3123-d1111151.html
   My bibliography  Save this article

Techno-Economic Analysis of Rooftop Photovoltaic System under Different Scenarios in China University Campuses

Author

Listed:
  • Xingyu Zhu

    (School of Mechanical Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China
    Shandong Institute of Mechanical Design and Research, Jinan 250031, China)

  • Yuexia Lv

    (School of Mechanical Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China
    Shandong Institute of Mechanical Design and Research, Jinan 250031, China)

  • Jinpeng Bi

    (School of Mechanical Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China
    Shandong Institute of Mechanical Design and Research, Jinan 250031, China)

  • Mingkun Jiang

    (SPIC Qinghai Photovoltaic Industry Innovation Center Co., Ltd., Xi’an 710000, China)

  • Yancai Su

    (School of Mechanical Engineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan 250353, China
    Shandong Institute of Mechanical Design and Research, Jinan 250031, China)

  • Tingting Du

    (School of Energy and Power Engineering, Shandong University, Jinan 250061, China)

Abstract

The expansively unutilized rooftop spaces in the university campuses can provide an excellent opportunity for the installation of solar photovoltaic systems to achieve renewable electricity generation and carbon dioxide reduction. Based on available rooftop areas and local solar radiation situations, technical potential and economic benefits of rooftop photovoltaic system under seven scenarios were carried out for three university campuses located in different solar zones in China. The potential capacity of photovoltaic installations on building’s flat rooftops in Tibet University, Qinghai University, and Qilu University of Technology reaches 11,291 kW, 9102 kW, and 3821 kW, corresponding to the maximum annual power generation of 28.19 GWh, 18.03 GWh, and 5.36 GWh, respectively. From the perspective of economic analysis, PV systems installed in “full self-consumption” mode are superior to those installed in “full-feed-into-grid” mode for all three study cases. The highest return on investment of PV systems installed on flat and pitched rooftops can be achieved at 208% and 204%, respectively, in Tibet University. The payback period for PV systems installed on flat rooftops is 1 year in Tibet University, and less than 8 years for both Qinghai University and Qilu University of Technology, respectively. Results reveal that rooftop photovoltaic systems can significantly help the universities to move towards sustainability.

Suggested Citation

  • Xingyu Zhu & Yuexia Lv & Jinpeng Bi & Mingkun Jiang & Yancai Su & Tingting Du, 2023. "Techno-Economic Analysis of Rooftop Photovoltaic System under Different Scenarios in China University Campuses," Energies, MDPI, vol. 16(7), pages 1-18, March.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:7:p:3123-:d:1111151
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/7/3123/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/16/7/3123/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ghaleb, Belal & Asif, Muhammad, 2022. "Assessment of solar PV potential in commercial buildings," Renewable Energy, Elsevier, vol. 187(C), pages 618-630.
    2. Yang, Ying & Campana, Pietro Elia & Stridh, Bengt & Yan, Jinyue, 2020. "Potential analysis of roof-mounted solar photovoltaics in Sweden," Applied Energy, Elsevier, vol. 279(C).
    3. Lee, Jongsung & Chang, Byungik & Aktas, Can & Gorthala, Ravi, 2016. "Economic feasibility of campus-wide photovoltaic systems in New England," Renewable Energy, Elsevier, vol. 99(C), pages 452-464.
    4. Josué F. Rosales-Pérez & Andrés Villarruel-Jaramillo & José A. Romero-Ramos & Manuel Pérez-García & José M. Cardemil & Rodrigo Escobar, 2023. "Hybrid System of Photovoltaic and Solar Thermal Technologies for Industrial Process Heat," Energies, MDPI, vol. 16(5), pages 1-45, February.
    5. Wang, Kai & Herrando, María & Pantaleo, Antonio M. & Markides, Christos N., 2019. "Technoeconomic assessments of hybrid photovoltaic-thermal vs. conventional solar-energy systems: Case studies in heat and power provision to sports centres," Applied Energy, Elsevier, vol. 254(C).
    6. Liu, Wen & Lund, Henrik & Mathiesen, Brian Vad & Zhang, Xiliang, 2011. "Potential of renewable energy systems in China," Applied Energy, Elsevier, vol. 88(2), pages 518-525, February.
    7. Thai, Clinton & Brouwer, Jack, 2021. "Challenges estimating distributed solar potential with utilization factors: California universities case study," Applied Energy, Elsevier, vol. 282(PB).
    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. Hurtado-Pérez, Elías & Bastida-Molina, Paula & Aparisi-Cerdá, Isabel & Alfonso-Solar, David & Fernández, Ana Rodríguez, 2024. "Multicriteria solar photovoltaic potential evaluation for high educational buildings. Case study of Polytechnic University of Valencia, Spain," Renewable Energy, Elsevier, vol. 227(C).
    2. Kyoik Choi & Jangwon Suh, 2023. "Fault Detection and Power Loss Assessment for Rooftop Photovoltaics Installed in a University Campus, by Use of UAV-Based Infrared Thermography," Energies, MDPI, vol. 16(11), pages 1-16, June.

    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. Liu, Jiang & Wu, Qifeng & Lin, Zhipeng & Shi, Huijie & Wen, Shaoyang & Wu, Qiaoyu & Zhang, Junxue & Peng, Changhai, 2023. "A novel approach for assessing rooftop-and-facade solar photovoltaic potential in rural areas using three-dimensional (3D) building models constructed with GIS," Energy, Elsevier, vol. 282(C).
    2. Gassar, Abdo Abdullah Ahmed & Cha, Seung Hyun, 2021. "Review of geographic information systems-based rooftop solar photovoltaic potential estimation approaches at urban scales," Applied Energy, Elsevier, vol. 291(C).
    3. Aslani, Mohammad & Seipel, Stefan, 2022. "Automatic identification of utilizable rooftop areas in digital surface models for photovoltaics potential assessment," Applied Energy, Elsevier, vol. 306(PA).
    4. Ren, Haoshan & Xu, Chengliang & Ma, Zhenjun & Sun, Yongjun, 2022. "A novel 3D-geographic information system and deep learning integrated approach for high-accuracy building rooftop solar energy potential characterization of high-density cities," Applied Energy, Elsevier, vol. 306(PA).
    5. Vivar, M. & H, Sharon & Fuentes, M., 2024. "Photovoltaic system adoption in water related technologies – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    6. Ahmed, Saeed & Mahmood, Anzar & Hasan, Ahmad & Sidhu, Guftaar Ahmad Sardar & Butt, Muhammad Fasih Uddin, 2016. "A comparative review of China, India and Pakistan renewable energy sectors and sharing opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 216-225.
    7. Formolli, M. & Kleiven, T. & Lobaccaro, G., 2023. "Assessing solar energy accessibility at high latitudes: A systematic review of urban spatial domains, metrics, and parameters," Renewable and Sustainable Energy Reviews, Elsevier, vol. 177(C).
    8. Liu, Wen & Hu, Weihao & Lund, Henrik & Chen, Zhe, 2013. "Electric vehicles and large-scale integration of wind power – The case of Inner Mongolia in China," Applied Energy, Elsevier, vol. 104(C), pages 445-456.
    9. Shangfeng Han & Baosheng Zhang & Xiaoyang Sun & Song Han & Mikael Höök, 2017. "China’s Energy Transition in the Power and Transport Sectors from a Substitution Perspective," Energies, MDPI, vol. 10(5), pages 1-25, April.
    10. Frank, Alejandro Germán & Gerstlberger, Wolfgang & Paslauski, Carolline Amaral & Lerman, Laura Visintainer & Ayala, Néstor Fabián, 2018. "The contribution of innovation policy criteria to the development of local renewable energy systems," Energy Policy, Elsevier, vol. 115(C), pages 353-365.
    11. Rômulo de Oliveira Azevêdo & Paulo Rotela Junior & Luiz Célio Souza Rocha & Gianfranco Chicco & Giancarlo Aquila & Rogério Santana Peruchi, 2020. "Identification and Analysis of Impact Factors on the Economic Feasibility of Photovoltaic Energy Investments," Sustainability, MDPI, vol. 12(17), pages 1-40, September.
    12. Zhai, Yijie & Ma, Xiaotian & Gao, Feng & Zhang, Tianzuo & Hong, Jinglan & Zhang, Xu & Yuan, Xueliang & Li, Xiangzhi, 2020. "Is energy the key to pursuing clean air and water at the city level? A case study of Jinan City, China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    13. Delivand, Mitra Kami & Barz, Mirko & Gheewala, Shabbir H. & Sajjakulnukit, Boonrod, 2011. "Economic feasibility assessment of rice straw utilization for electricity generating through combustion in Thailand," Applied Energy, Elsevier, vol. 88(11), pages 3651-3658.
    14. Valentine, Scott Victor, 2014. "The socio-political economy of electricity generation in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 32(C), pages 416-429.
    15. Lindner, Soeren & Liu, Zhu & Guan, Dabo & Geng, Yong & Li, Xin, 2013. "CO2 emissions from China’s power sector at the provincial level: Consumption versus production perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 19(C), pages 164-172.
    16. Yunpeng Sun & Ruoya Jia & Asif Razzaq & Qun Bao, 2023. "RETRACTED ARTICLE: Drivers of China’s geographical renewable energy development: evidence from spatial association network structure approaches," Economic Change and Restructuring, Springer, vol. 56(6), pages 4115-4163, December.
    17. Fang, Yiping & Wei, Yanqiang, 2013. "Climate change adaptation on the Qinghai–Tibetan Plateau: The importance of solar energy utilization for rural household," Renewable and Sustainable Energy Reviews, Elsevier, vol. 18(C), pages 508-518.
    18. Guo, Zhiling & Zhuang, Zhan & Tan, Hongjun & Liu, Zhengguang & Li, Peiran & Lin, Zhengyuan & Shang, Wen-Long & Zhang, Haoran & Yan, Jinyue, 2023. "Accurate and generalizable photovoltaic panel segmentation using deep learning for imbalanced datasets," Renewable Energy, Elsevier, vol. 219(P1).
    19. Li, X. & Hubacek, K. & Siu, Y.L., 2012. "Wind power in China – Dream or reality?," Energy, Elsevier, vol. 37(1), pages 51-60.
    20. Ma, Ziming & Zhong, Haiwang & Xia, Qing & Kang, Chongqing & Jin, Liming, 2020. "Constraint relaxation-based day-ahead market mechanism design to promote the renewable energy accommodation," Energy, Elsevier, vol. 198(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:gam:jeners:v:16:y:2023:i:7:p:3123-:d:1111151. 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.