IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v279y2020ics0306261920312708.html
   My bibliography  Save this article

Potential analysis of roof-mounted solar photovoltaics in Sweden

Author

Listed:
  • Yang, Ying
  • Campana, Pietro Elia
  • Stridh, Bengt
  • Yan, Jinyue

Abstract

Solar photovoltaic energy, driven mostly by the residential and commercial market segments, has been growing a lot in recent years in Sweden. In response to the commitment towards sustainability goals, this paper explores the potential of roof-mounted solar photovoltaic projects. This paper focuses on: roof area estimation, potential installed capacity, and potential electricity generation, at the single municipal scale and at the national scale. The following categories of different building types have been investigated: residential buildings, industrial buildings, buildings of social function, buildings of business function, buildings of economic/agricultural function, buildings of complementary function, and buildings of other unknown functions. The analysis starts from Västerås, a typical Swedish municipality and ranking seventh among the largest cities in Sweden. An estimate of 5.74 km2 available roof area potential is calculated, by considering factors such as building purposes, roof orientations, shadows and obstacles. The total potential installed capacity is calculated, assuming the installation of commercial photovoltaic modules, and design parameters for flat roofs such as inter-row distances and tilt angles. With the inputs of meteorological parameters and geographical information, the potential yearly electricity generation is calculated. The results reveal 727, 848, and 956 MWp potential installed capacity and 626, 720, and 801 GWh annual electricity production for Västerås on pitched roofs and flat roofs with three scenarios, respectively. The extrapolation of the methodology to the entire of Sweden yields a total of 504 km2 usable roof area and 65, 75, and 84 GWp installed capacity. Finally, we reveal a new understanding of usable roof area distribution and of potential installed capacity of roof-mounted solar photovoltaic systems, which can largely help evaluate subsidy scale and solar energy policy formulation in Sweden.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:appene:v:279:y:2020:i:c:s0306261920312708
    DOI: 10.1016/j.apenergy.2020.115786
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261920312708
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2020.115786?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. Sumita Ghosh & Robert Vale & Brenda Vale, 2006. "Domestic energy sustainability of different urban residential patterns: a New Zealand approach," International Journal of Sustainable Development, Inderscience Enterprises Ltd, vol. 9(1), pages 16-37.
    2. Jinyue Yan & Ying Yang & Pietro Elia Campana & Jijiang He, 2019. "City-level analysis of subsidy-free solar photovoltaic electricity price, profits and grid parity in China," Nature Energy, Nature, vol. 4(8), pages 709-717, August.
    3. J. Richard Snape, 2016. "Spatial and Temporal Characteristics of PV Adoption in the UK and Their Implications for the Smart Grid," Energies, MDPI, vol. 9(3), pages 1-18, March.
    4. He, Gang & Kammen, Daniel M., 2016. "Where, when and how much solar is available? A provincial-scale solar resource assessment for China," Renewable Energy, Elsevier, vol. 85(C), pages 74-82.
    5. Freitas, S. & Catita, C. & Redweik, P. & Brito, M.C., 2015. "Modelling solar potential in the urban environment: State-of-the-art review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 915-931.
    6. Strzalka, Aneta & Alam, Nazmul & Duminil, Eric & Coors, Volker & Eicker, Ursula, 2012. "Large scale integration of photovoltaics in cities," Applied Energy, Elsevier, vol. 93(C), pages 413-421.
    7. Buffat, René & Grassi, Stefano & Raubal, Martin, 2018. "A scalable method for estimating rooftop solar irradiation potential over large regions," Applied Energy, Elsevier, vol. 216(C), pages 389-401.
    8. Alam Hossain Mondal, Md. & Sadrul Islam, A.K.M., 2011. "Potential and viability of grid-connected solar PV system in Bangladesh," Renewable Energy, Elsevier, vol. 36(6), pages 1869-1874.
    9. Theodoridou, Ifigeneia & Karteris, Marinos & Mallinis, Georgios & Papadopoulos, Agis M. & Hegger, Manfred, 2012. "Assessment of retrofitting measures and solar systems' potential in urban areas using Geographical Information Systems: Application to a Mediterranean city," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(8), pages 6239-6261.
    10. Yue, Cheng-Dar & Huang, Guo-Rong, 2011. "An evaluation of domestic solar energy potential in Taiwan incorporating land use analysis," Energy Policy, Elsevier, vol. 39(12), pages 7988-8002.
    11. Fan, Jing-Li & Wang, Jia-Xing & Hu, Jia-Wei & Wang, Yu & Zhang, Xian, 2019. "Optimization of China’s provincial renewable energy installation plan for the 13th five-year plan based on renewable portfolio standards," Applied Energy, Elsevier, vol. 254(C).
    12. Byrne, John & Taminiau, Job & Kurdgelashvili, Lado & Kim, Kyung Nam, 2015. "A review of the solar city concept and methods to assess rooftop solar electric potential, with an illustrative application to the city of Seoul," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 830-844.
    13. Vardimon, Ran, 2011. "Assessment of the potential for distributed photovoltaic electricity production in Israel," Renewable Energy, Elsevier, vol. 36(2), pages 591-594.
    14. Haegermark, Maria & Kovacs, Peter & Dalenbäck, Jan-Olof, 2017. "Economic feasibility of solar photovoltaic rooftop systems in a complex setting: A Swedish case study," Energy, Elsevier, vol. 127(C), pages 18-29.
    15. Pawluk, Robert E. & Chen, Yuxiang & She, Yuntong, 2019. "Photovoltaic electricity generation loss due to snow – A literature review on influence factors, estimation, and mitigation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 107(C), pages 171-182.
    16. Kucuksari, Sadik & Khaleghi, Amirreza M. & Hamidi, Maryam & Zhang, Ye & Szidarovszky, Ferenc & Bayraksan, Guzin & Son, Young-Jun, 2014. "An Integrated GIS, optimization and simulation framework for optimal PV size and location in campus area environments," Applied Energy, Elsevier, vol. 113(C), pages 1601-1613.
    17. Hofierka, Jaroslav & Kaňuk, Ján, 2009. "Assessment of photovoltaic potential in urban areas using open-source solar radiation tools," Renewable Energy, Elsevier, vol. 34(10), pages 2206-2214.
    18. Hartner, Michael & Ortner, André & Hiesl, Albert & Haas, Reinhard, 2015. "East to west – The optimal tilt angle and orientation of photovoltaic panels from an electricity system perspective," Applied Energy, Elsevier, vol. 160(C), pages 94-107.
    19. Ordóñez, J. & Jadraque, E. & Alegre, J. & Martínez, G., 2010. "Analysis of the photovoltaic solar energy capacity of residential rooftops in Andalusia (Spain)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(7), pages 2122-2130, September.
    20. Sun, Yan-wei & Hof, Angela & Wang, Run & Liu, Jian & Lin, Yan-jie & Yang, De-wei, 2013. "GIS-based approach for potential analysis of solar PV generation at the regional scale: A case study of Fujian Province," Energy Policy, Elsevier, vol. 58(C), pages 248-259.
    21. del Río, Pablo & Mir-Artigues, Pere, 2012. "Support for solar PV deployment in Spain: Some policy lessons," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(8), pages 5557-5566.
    22. Sommerfeldt, Nelson & Madani, Hatef, 2017. "Revisiting the techno-economic analysis process for building-mounted, grid-connected solar photovoltaic systems: Part two - Application," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 1394-1404.
    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. Claudio Moscoloni & Fernando Zarra & Riccardo Novo & Enrico Giglio & Alberto Vargiu & Guglielmina Mutani & Giovanni Bracco & Giuliana Mattiazzo, 2022. "Wind Turbines and Rooftop Photovoltaic Technical Potential Assessment: Application to Sicilian Minor Islands," Energies, MDPI, vol. 15(15), pages 1-35, July.
    2. Guglielmina Mutani & Valeria Todeschi, 2021. "Optimization of Costs and Self-Sufficiency for Roof Integrated Photovoltaic Technologies on Residential Buildings," Energies, MDPI, vol. 14(13), pages 1-25, July.
    3. Shali Wang & Jiaxi Wu & Yunan Peng & Jane Xu & Lisa Leinonen & Yuyu Wang & Zheng Meng, 2022. "Influence of Residential Photovoltaic Promotion Policy on Installation Intention in Typical Regions of China," Sustainability, MDPI, vol. 14(14), pages 1-30, July.
    4. 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).
    5. Johanna Fink, 2023. "Can the creation of separate bidding zones within countries create imbalances in PV uptake? Evidence from Sweden," Papers 2312.16161, arXiv.org.
    6. Zhong, Teng & Zhang, Kai & Chen, Min & Wang, Yijie & Zhu, Rui & Zhang, Zhixin & Zhou, Zixuan & Qian, Zhen & Lv, Guonian & Yan, Jinyue, 2021. "Assessment of solar photovoltaic potentials on urban noise barriers using street-view imagery," Renewable Energy, Elsevier, vol. 168(C), pages 181-194.
    7. Barbón, A. & Bayón-Cueli, C. & Bayón, L. & Carreira-Fontao, V., 2022. "A methodology for an optimal design of ground-mounted photovoltaic power plants," Applied Energy, Elsevier, vol. 314(C).
    8. Barbón, A. & Bayón-Cueli, C. & Bayón, L. & Rodríguez-Suanzes, C., 2022. "Analysis of the tilt and azimuth angles of photovoltaic systems in non-ideal positions for urban applications," Applied Energy, Elsevier, vol. 305(C).
    9. Tingting Zhu & Yiren Guo & Zhenye Li & Cong Wang, 2021. "Solar Radiation Prediction Based on Convolution Neural Network and Long Short-Term Memory," Energies, MDPI, vol. 14(24), pages 1-16, December.
    10. 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).
    11. 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).
    12. 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).
    13. Ren, Haoshan & Ma, Zhenjun & Chan, Antoni B. & Sun, Yongjun, 2023. "Optimal planning of municipal-scale distributed rooftop photovoltaic systems with maximized solar energy generation under constraints in high-density cities," Energy, Elsevier, vol. 263(PA).
    14. Liu, Zhengguang & Guo, Zhiling & Chen, Qi & Song, Chenchen & Shang, Wenlong & Yuan, Meng & Zhang, Haoran, 2023. "A review of data-driven smart building-integrated photovoltaic systems: Challenges and objectives," Energy, Elsevier, vol. 263(PE).
    15. 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).
    16. 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).
    17. Walch, Alina & Rüdisüli, Martin, 2023. "Strategic PV expansion and its impact on regional electricity self-sufficiency: Case study of Switzerland," Applied Energy, Elsevier, vol. 346(C).
    18. Smolenski, Robert & Szczesniak, Pawel & Drozdz, Wojciech & Kasperski, Lukasz, 2022. "Advanced metering infrastructure and energy storage for location and mitigation of power quality disturbances in the utility grid with high penetration of renewables," Renewable and Sustainable Energy Reviews, Elsevier, vol. 157(C).
    19. Ren, Haoshan & Ma, Zhenjun & Ming Lun Fong, Alan & Sun, Yongjun, 2022. "Optimal deployment of distributed rooftop photovoltaic systems and batteries for achieving net-zero energy of electric bus transportation in high-density cities," Applied Energy, Elsevier, vol. 319(C).
    20. 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).
    21. 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.

    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. 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.
    3. Thai, Clinton & Brouwer, Jack, 2021. "Challenges estimating distributed solar potential with utilization factors: California universities case study," Applied Energy, Elsevier, vol. 282(PB).
    4. Lee, Minhyun & Hong, Taehoon & Jeong, Kwangbok & Kim, Jimin, 2018. "A bottom-up approach for estimating the economic potential of the rooftop solar photovoltaic system considering the spatial and temporal diversity," Applied Energy, Elsevier, vol. 232(C), pages 640-656.
    5. Liu, Zhengguang & Guo, Zhiling & Chen, Qi & Song, Chenchen & Shang, Wenlong & Yuan, Meng & Zhang, Haoran, 2023. "A review of data-driven smart building-integrated photovoltaic systems: Challenges and objectives," Energy, Elsevier, vol. 263(PE).
    6. Zhixin Zhang & Min Chen & Teng Zhong & Rui Zhu & Zhen Qian & Fan Zhang & Yue Yang & Kai Zhang & Paolo Santi & Kaicun Wang & Yingxia Pu & Lixin Tian & Guonian Lü & Jinyue Yan, 2023. "Carbon mitigation potential afforded by rooftop photovoltaic in China," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    7. Assouline, Dan & Mohajeri, Nahid & Scartezzini, Jean-Louis, 2018. "Large-scale rooftop solar photovoltaic technical potential estimation using Random Forests," Applied Energy, Elsevier, vol. 217(C), pages 189-211.
    8. Orioli, Aldo & Di Gangi, Alessandra, 2014. "Review of the energy and economic parameters involved in the effectiveness of grid-connected PV systems installed in multi-storey buildings," Applied Energy, Elsevier, vol. 113(C), pages 955-969.
    9. 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).
    10. Byrne, John & Taminiau, Job & Kurdgelashvili, Lado & Kim, Kyung Nam, 2015. "A review of the solar city concept and methods to assess rooftop solar electric potential, with an illustrative application to the city of Seoul," Renewable and Sustainable Energy Reviews, Elsevier, vol. 41(C), pages 830-844.
    11. Ruhang, Xu, 2016. "The restriction research for urban area building integrated grid-connected PV power generation potential," Energy, Elsevier, vol. 113(C), pages 124-143.
    12. Meskiana Boulahia & Kahina Amal Djiar & Miguel Amado, 2021. "Combined Engineering—Statistical Method for Assessing Solar Photovoltaic Potential on Residential Rooftops: Case of Laghouat in Central Southern Algeria," Energies, MDPI, vol. 14(6), pages 1-16, March.
    13. Zhong, Qing & Tong, Daoqin, 2020. "Spatial layout optimization for solar photovoltaic (PV) panel installation," Renewable Energy, Elsevier, vol. 150(C), pages 1-11.
    14. Finn, Thomas & McKenzie, Paul, 2020. "A high-resolution suitability index for solar farm location in complex landscapes," Renewable Energy, Elsevier, vol. 158(C), pages 520-533.
    15. 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).
    16. Bódis, Katalin & Kougias, Ioannis & Jäger-Waldau, Arnulf & Taylor, Nigel & Szabó, Sándor, 2019. "A high-resolution geospatial assessment of the rooftop solar photovoltaic potential in the European Union," Renewable and Sustainable Energy Reviews, Elsevier, vol. 114(C), pages 1-1.
    17. Ali, Ihsan & Shafiullah, GM & Urmee, Tania, 2018. "A preliminary feasibility of roof-mounted solar PV systems in the Maldives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 83(C), pages 18-32.
    18. Wang, Peng & Zhang, Shuainan & Pu, Yanru & Cao, Shuchao & Zhang, Yuhu, 2021. "Estimation of photovoltaic power generation potential in 2020 and 2030 using land resource changes: An empirical study from China," Energy, Elsevier, vol. 219(C).
    19. Phuong Minh Khuong & Russell McKenna & Wolf Fichtner, 2020. "A Cost-Effective and Transferable Methodology for Rooftop PV Potential Assessment in Developing Countries," Energies, MDPI, vol. 13(10), pages 1-46, May.
    20. Sebastian Krapf & Nils Kemmerzell & Syed Khawaja Haseeb Uddin & Manuel Hack Vázquez & Fabian Netzler & Markus Lienkamp, 2021. "Towards Scalable Economic Photovoltaic Potential Analysis Using Aerial Images and Deep Learning," Energies, MDPI, vol. 14(13), pages 1-22, June.

    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:279:y:2020:i:c:s0306261920312708. 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.