IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i14p10798-d1190513.html
   My bibliography  Save this article

Deep Learning Method for Evaluating Photovoltaic Potential of Rural Land Use Types

Author

Listed:
  • Zhixin Li

    (School of Architecture, Tsinghua University, Beijing 100084, China)

  • Chen Zhang

    (Wuhan Natural Resources Conservation and Utilization Center, Wuhan 430014, China)

  • Zejun Yu

    (School of Architecture, Tianjin University, Tianjin 300072, China)

  • Hong Zhang

    (School of Architecture, Tsinghua University, Beijing 100084, China)

  • Haihua Jiang

    (Beijing Institute of Architectural Design Co., Ltd., Beijing 100045, China)

Abstract

Rooftop photovoltaic (PV) power generation uses building roofs to generate electricity by laying PV panels. Rural rooftops are less shaded and have a regular shape, which is favorable for laying PV panels. However, because of the relative lack of information on buildings in rural areas, there are fewer methods to assess the utilization potential of PV on rural buildings, and most studies focus on urban buildings. In addition, in rural areas, concentrated ground-mounted PV plants can be built on wastelands, hillsides, and farmlands. To facilitate the overall planning and synergistic layout of rural PV utilization, we propose a new workflow to identify different types of surfaces (including building roofs, wastelands, water surfaces, etc.) by applying a deep learning approach to count the PV potential of different surfaces in rural areas. This method can be used to estimate the spatial distribution of rural PV development potential from publicly available satellite images. In this paper, 10 km 2 of land in Wuhan is used as an example. The results show that the total PV potential in the study area could reach 198.02 GWh/year, including 4.69 GWh/year for BIPV, 159.91 GWh/year for FSPV, and 33.43 GWh/year for LSPV. Considering the development cost of different land types, several timespans (such as short-, medium-, and long-term) of PV development plans for rural areas can be considered. The method and results provide tools and data for the assessment of PV potential in rural areas and can be used as a reference for the development of village master plans and PV development plans.

Suggested Citation

  • Zhixin Li & Chen Zhang & Zejun Yu & Hong Zhang & Haihua Jiang, 2023. "Deep Learning Method for Evaluating Photovoltaic Potential of Rural Land Use Types," Sustainability, MDPI, vol. 15(14), pages 1-17, July.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:14:p:10798-:d:1190513
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/14/10798/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/14/10798/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhang, Yuhu & Ren, Jing & Pu, Yanru & Wang, Peng, 2020. "Solar energy potential assessment: A framework to integrate geographic, technological, and economic indices for a potential analysis," Renewable Energy, Elsevier, vol. 149(C), pages 577-586.
    2. Amaducci, Stefano & Yin, Xinyou & Colauzzi, Michele, 2018. "Agrivoltaic systems to optimise land use for electric energy production," Applied Energy, Elsevier, vol. 220(C), pages 545-561.
    3. Zhang, Ji & Xu, Le & Shabunko, Veronika & Tay, Stephen En Rong & Sun, Huixuan & Lau, Stephen Siu Yu & Reindl, Thomas, 2019. "Impact of urban block typology on building solar potential and energy use efficiency in tropical high-density city," Applied Energy, Elsevier, vol. 240(C), pages 513-533.
    4. Martinez Alvarez, V. & González-Real, M.M. & Baille, A. & Maestre Valero, J.F. & Gallego Elvira, B., 2008. "Regional assessment of evaporation from agricultural irrigation reservoirs in a semiarid climate," Agricultural Water Management, Elsevier, vol. 95(9), pages 1056-1066, September.
    5. Ferrer-Gisbert, Carlos & Ferrán-Gozálvez, José J. & Redón-Santafé, Miguel & Ferrer-Gisbert, Pablo & Sánchez-Romero, Francisco J. & Torregrosa-Soler, Juan Bautista, 2013. "A new photovoltaic floating cover system for water reservoirs," Renewable Energy, Elsevier, vol. 60(C), pages 63-70.
    6. Hong, Taehoon & Lee, Minhyun & Koo, Choongwan & Jeong, Kwangbok & Kim, Jimin, 2017. "Development of a method for estimating the rooftop solar photovoltaic (PV) potential by analyzing the available rooftop area using Hillshade analysis," Applied Energy, Elsevier, vol. 194(C), pages 320-332.
    7. Huang, Zhaojian & Mendis, Thushini & Xu, Shen, 2019. "Urban solar utilization potential mapping via deep learning technology: A case study of Wuhan, China," Applied Energy, Elsevier, vol. 250(C), pages 283-291.
    8. Coruhlu, Yakup Emre & Solgun, Necmettin & Baser, Volkan & Terzi, Fatih, 2022. "Revealing the solar energy potential by integration of GIS and AHP in order to compare decisions of the land use on the environmental plans," Land Use Policy, Elsevier, vol. 113(C).
    9. Jacques, David A. & Gooding, James & Giesekam, Jannik J. & Tomlin, Alison S. & Crook, Rolf, 2014. "Methodology for the assessment of PV capacity over a city region using low-resolution LiDAR data and application to the City of Leeds (UK)," Applied Energy, Elsevier, vol. 124(C), pages 28-34.
    10. Yu, Shiwei & Han, Ruilian & Zhang, Junjie, 2023. "Reassessment of the potential for centralized and distributed photovoltaic power generation in China: On a prefecture-level city scale," Energy, Elsevier, vol. 262(PA).
    11. Mahtta, Richa & Joshi, P.K. & Jindal, Alok Kumar, 2014. "Solar power potential mapping in India using remote sensing inputs and environmental parameters," Renewable Energy, Elsevier, vol. 71(C), pages 255-262.
    12. Doljak, Dejan & Stanojević, Gorica, 2017. "Evaluation of natural conditions for site selection of ground-mounted photovoltaic power plants in Serbia," Energy, Elsevier, vol. 127(C), pages 291-300.
    13. Mondal, Md. Alam Hossain & Denich, Manfred, 2010. "Assessment of renewable energy resources potential for electricity generation in Bangladesh," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(8), pages 2401-2413, October.
    14. Sarralde, Juan José & Quinn, David James & Wiesmann, Daniel & Steemers, Koen, 2015. "Solar energy and urban morphology: Scenarios for increasing the renewable energy potential of neighbourhoods in London," Renewable Energy, Elsevier, vol. 73(C), pages 10-17.
    15. Trapani, Kim & Millar, Dean L. & Smith, Helen C.M., 2013. "Novel offshore application of photovoltaics in comparison to conventional marine renewable energy technologies," Renewable Energy, Elsevier, vol. 50(C), pages 879-888.
    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. 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).
    2. 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).
    3. Zhang, Chen & Li, Zhixin & Jiang, Haihua & Luo, Yongqiang & Xu, Shen, 2021. "Deep learning method for evaluating photovoltaic potential of urban land-use: A case study of Wuhan, China," Applied Energy, Elsevier, vol. 283(C).
    4. Jiang, Mingkun & Qi, Lingfei & Yu, Ziyi & Wu, Dadi & Si, Pengfei & Li, Peiran & Wei, Wendong & Yu, Xinhai & Yan, Jinyue, 2021. "National level assessment of using existing airport infrastructures for photovoltaic deployment," Applied Energy, Elsevier, vol. 298(C).
    5. Zhong, Teng & Zhang, Zhixin & Chen, Min & Zhang, Kai & Zhou, Zixuan & Zhu, Rui & Wang, Yijie & Lü, Guonian & Yan, Jinyue, 2021. "A city-scale estimation of rooftop solar photovoltaic potential based on deep learning," Applied Energy, Elsevier, vol. 298(C).
    6. Redón Santafé, Miguel & Torregrosa Soler, Juan Bautista & Sánchez Romero, Francisco Javier & Ferrer Gisbert, Pablo S. & Ferrán Gozálvez, José Javier & Ferrer Gisbert, Carlos M., 2014. "Theoretical and experimental analysis of a floating photovoltaic cover for water irrigation reservoirs," Energy, Elsevier, vol. 67(C), pages 246-255.
    7. Yu, Shiwei & Han, Ruilian & Zhang, Junjie, 2023. "Reassessment of the potential for centralized and distributed photovoltaic power generation in China: On a prefecture-level city scale," Energy, Elsevier, vol. 262(PA).
    8. Teresa Santos & Raquel Deus & Jorge Rocha & José António Tenedório, 2021. "Assessing Sustainable Urban Development Trends in a Dynamic Tourist Coastal Area Using 3D Spatial Indicators," Energies, MDPI, vol. 14(16), pages 1-22, August.
    9. Daniel Matulić & Željko Andabaka & Sanja Radman & Goran Fruk & Josip Leto & Jakša Rošin & Mirta Rastija & Ivana Varga & Tea Tomljanović & Hrvoje Čeprnja & Marko Karoglan, 2023. "Agrivoltaics and Aquavoltaics: Potential of Solar Energy Use in Agriculture and Freshwater Aquaculture in Croatia," Agriculture, MDPI, vol. 13(7), pages 1-26, July.
    10. Hou, Yali & Wang, Qunwei & Tan, Tao, 2023. "An ensemble learning framework for rooftop photovoltaic project site selection," Energy, Elsevier, vol. 285(C).
    11. Mendis, Thushini & Huang, Zhaojian & Xu, Shen & Zhang, Weirong, 2020. "Economic potential analysis of photovoltaic integrated shading strategies on commercial building facades in urban blocks: A case study of Colombo, Sri Lanka," Energy, Elsevier, vol. 194(C).
    12. Lobaccaro, G. & Croce, S. & Lindkvist, C. & Munari Probst, M.C. & Scognamiglio, A. & Dahlberg, J. & Lundgren, M. & Wall, M., 2019. "A cross-country perspective on solar energy in urban planning: Lessons learned from international case studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 108(C), pages 209-237.
    13. Zhang, Yuhu & Ren, Jing & Pu, Yanru & Wang, Peng, 2020. "Solar energy potential assessment: A framework to integrate geographic, technological, and economic indices for a potential analysis," Renewable Energy, Elsevier, vol. 149(C), pages 577-586.
    14. Ranjbaran, Parisa & Yousefi, Hossein & Gharehpetian, G.B. & Astaraei, Fatemeh Razi, 2019. "A review on floating photovoltaic (FPV) power generation units," Renewable and Sustainable Energy Reviews, Elsevier, vol. 110(C), pages 332-347.
    15. Jae Woo Ko & Hae Lim Cha & David Kwang-Soon Kim & Jong Rok Lim & Gyu Gwang Kim & Byeong Gwan Bhang & Chang Sub Won & Han Sang Jung & Dong Hyung Kang & Hyung Keun Ahn, 2017. "Safety Analysis of Grounding Resistance with Depth of Water for Floating PVs," Energies, MDPI, vol. 10(9), pages 1-12, September.
    16. Alexander E. Cagle & Alona Armstrong & Giles Exley & Steven M. Grodsky & Jordan Macknick & John Sherwin & Rebecca R. Hernandez, 2020. "The Land Sparing, Water Surface Use Efficiency, and Water Surface Transformation of Floating Photovoltaic Solar Energy Installations," Sustainability, MDPI, vol. 12(19), pages 1-22, October.
    17. Vladan Durković & Željko Đurišić, 2017. "Analysis of the Potential for Use of Floating PV Power Plant on the Skadar Lake for Electricity Supply of Aluminium Plant in Montenegro," Energies, MDPI, vol. 10(10), pages 1-23, September.
    18. Sánchez-Aparicio, M. & Martín-Jiménez, J. & Del Pozo, S. & González-González, E. & Lagüela, S., 2021. "Ener3DMap-SolarWeb roofs: A geospatial web-based platform to compute photovoltaic potential," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    19. Wang, Tiantian & Wang, Yanhua & Wang, Ke & Fu, Sha & Ding, Li, 2024. "Five-dimensional assessment of China's centralized and distributed photovoltaic potential: From solar irradiation to CO2 mitigation," Applied Energy, Elsevier, vol. 356(C).
    20. Job Taminiau & John Byrne & Jongkyu Kim & Min‐Hwi Kim & Jeongseok Seo, 2022. "Inferential‐ and measurement‐based methods to estimate rooftop “solar city” potential in megacity Seoul, South Korea," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 11(5), September.

    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:14:p:10798-:d:1190513. 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.