IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i8p3564-d1128615.html
   My bibliography  Save this article

Techno-Economic Potential of Urban Photovoltaics: Comparison of Net Billing and Net Metering in a Mediterranean Municipality

Author

Listed:
  • Enrique Fuster-Palop

    (Grupo ImpactE Planificación Urbana SL, Carrer Pedro Duque, Camí de Vera s/n, 46022 Valencia, Spain)

  • Carlos Prades-Gil

    (Grupo ImpactE Planificación Urbana SL, Carrer Pedro Duque, Camí de Vera s/n, 46022 Valencia, Spain)

  • Ximo Masip

    (Grupo ImpactE Planificación Urbana SL, Carrer Pedro Duque, Camí de Vera s/n, 46022 Valencia, Spain)

  • J. D. Viana-Fons

    (Grupo ImpactE Planificación Urbana SL, Carrer Pedro Duque, Camí de Vera s/n, 46022 Valencia, Spain)

  • Jorge Payá

    (Instituto Universitario de Investigación en Ingeniería Energética, Universitat Politècnica de València, Camí de Vera s/n, 46022 Valencia, Spain)

Abstract

Solar photovoltaic self-consumption is an attractive approach to increase autarky and reduce emissions in the building sector. However, a successful deployment in urban rooftops requires both accurate and low-computational-cost methods to estimate the self-consumption potential and economic feasibility, which is especially scarce in the literature on net billing schemes. In the first part of this study, a bottom-up GIS-based techno-economic model has helped compare the self-consumption potential with net metering and net billing in a Mediterranean municipality of Spain, with 3734 buildings in total. The capacity was optimized according to load profiles obtained from aggregated real measurements. Multiple load profile scenarios were assessed, revealing that the potential self-sufficiency of the municipality ranges between 21.9% and 42.5%. In the second part of the study, simplified regression-based models were developed to estimate the self-sufficiency, self-consumption, economic payback and internal rate of return at a building scale, providing nRMSE values of 3.9%, 3.1%, 10.0% and 1.5%, respectively. One of the predictors with a high correlation in the regressions is a novel coefficient that measures the alignment between the load and the hours with higher irradiance. The developed correlations can be employed for any other economic or demand scenario.

Suggested Citation

  • Enrique Fuster-Palop & Carlos Prades-Gil & Ximo Masip & J. D. Viana-Fons & Jorge Payá, 2023. "Techno-Economic Potential of Urban Photovoltaics: Comparison of Net Billing and Net Metering in a Mediterranean Municipality," Energies, MDPI, vol. 16(8), pages 1-32, April.
  • Handle: RePEc:gam:jeners:v:16:y:2023:i:8:p:3564-:d:1128615
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/8/3564/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/16/8/3564/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fuster-Palop, Enrique & Prades-Gil, Carlos & Masip, X. & Viana-Fons, Joan D. & Payá, Jorge, 2021. "Innovative regression-based methodology to assess the techno-economic performance of photovoltaic installations in urban areas," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    2. Bruno Domenech & Gema Calleja & Jordi Olivella, 2021. "Residential Photovoltaic Profitability with Storage under the New Spanish Regulation: A Multi-Scenario Analysis," Energies, MDPI, vol. 14(7), pages 1-17, April.
    3. Elham Fakhraian & Marc Alier & Francesc Valls Dalmau & Alireza Nameni & Maria José Casañ Guerrero, 2021. "The Urban Rooftop Photovoltaic Potential Determination," Sustainability, MDPI, vol. 13(13), pages 1-18, July.
    4. Andres Calcabrini & Hesan Ziar & Olindo Isabella & Miro Zeman, 2019. "A simplified skyline-based method for estimating the annual solar energy potential in urban environments," Nature Energy, Nature, vol. 4(3), pages 206-215, March.
    5. 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.
    6. Olivella, Jordi & Domenech, Bruno & Calleja, Gema, 2021. "Potential of implementation of residential photovoltaics at city level: The case of London," Renewable Energy, Elsevier, vol. 180(C), pages 577-585.
    7. Gallego-Castillo, Cristobal & Heleno, Miguel & Victoria, Marta, 2021. "Self-consumption for energy communities in Spain: A regional analysis under the new legal framework," Energy Policy, Elsevier, vol. 150(C).
    8. Sredenšek, Klemen & Štumberger, Bojan & Hadžiselimović, Miralem & Mavsar, Primož & Seme, Sebastijan, 2022. "Physical, geographical, technical, and economic potential for the optimal configuration of photovoltaic systems using a digital surface model and optimization method," Energy, Elsevier, vol. 242(C).
    9. Beck, T. & Kondziella, H. & Huard, G. & Bruckner, T., 2016. "Assessing the influence of the temporal resolution of electrical load and PV generation profiles on self-consumption and sizing of PV-battery systems," Applied Energy, Elsevier, vol. 173(C), pages 331-342.
    10. Thebault, Martin & Desthieux, Gilles & Castello, Roberto & Berrah, Lamia, 2022. "Large-scale evaluation of the suitability of buildings for photovoltaic integration: Case study in Greater Geneva," Applied Energy, Elsevier, vol. 316(C).
    11. Gómez-Navarro, Tomás & Brazzini, Tommaso & Alfonso-Solar, David & Vargas-Salgado, Carlos, 2021. "Analysis of the potential for PV rooftop prosumer production: Technical, economic and environmental assessment for the city of Valencia (Spain)," Renewable Energy, Elsevier, vol. 174(C), pages 372-381.
    12. Memme, Samuele & Fossa, Marco, 2022. "Maximum energy yield of PV surfaces in France and Italy from climate based equations for optimum tilt at different azimuth angles," Renewable Energy, Elsevier, vol. 200(C), pages 845-866.
    13. 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.
    14. 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).
    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. Saez, R. & Boer, D. & Shobo, A.B. & Vallès, M., 2023. "Techno-economic analysis of residential rooftop photovoltaics in Spain," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    2. Evandro Ferreira & Miguel Macias Sequeira & João Pedro Gouveia, 2024. "Sharing Is Caring: Exploring Distributed Solar Photovoltaics and Local Electricity Consumption through a Renewable Energy Community," Sustainability, MDPI, vol. 16(7), pages 1-26, 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. Sun, Tao & Shan, Ming & Rong, Xing & Yang, Xudong, 2022. "Estimating the spatial distribution of solar photovoltaic power generation potential on different types of rural rooftops using a deep learning network applied to satellite images," Applied Energy, Elsevier, vol. 315(C).
    2. Fernando Echevarría Camarero & Ana Ogando-Martínez & Pablo Durán Gómez & Pablo Carrasco Ortega, 2022. "Profitability of Batteries in Photovoltaic Systems for Small Industrial Consumers in Spain under Current Regulatory Framework and Energy Prices," Energies, MDPI, vol. 16(1), pages 1-19, December.
    3. Mao, Hongzhi & Chen, Xie & Luo, Yongqiang & Deng, Jie & Tian, Zhiyong & Yu, Jinghua & Xiao, Yimin & Fan, Jianhua, 2023. "Advances and prospects on estimating solar photovoltaic installation capacity and potential based on satellite and aerial images," Renewable and Sustainable Energy Reviews, Elsevier, vol. 179(C).
    4. Dasí-Crespo, Daniel & Roldán-Blay, Carlos & Escrivá-Escrivá, Guillermo & Roldán-Porta, Carlos, 2023. "Evaluation of the Spanish regulation on self-consumption photovoltaic installations. A case study based on a rural municipality in Spain," Renewable Energy, Elsevier, vol. 204(C), pages 788-802.
    5. Liao, Xuan & Zhu, Rui & Wong, Man Sing & Heo, Joon & Chan, P.W. & Kwok, Coco Yin Tung, 2023. "Fast and accurate estimation of solar irradiation on building rooftops in Hong Kong: A machine learning-based parameterization approach," Renewable Energy, Elsevier, vol. 216(C).
    6. Mattia De Rosa & Vincenzo Bianco & Henrik Barth & Patricia Pereira da Silva & Carlos Vargas Salgado & Fabiano Pallonetto, 2023. "Technologies and Strategies to Support Energy Transition in Urban Building and Transportation Sectors," Energies, MDPI, vol. 16(11), pages 1-16, May.
    7. 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).
    8. Arias-Rosales, Andrés & LeDuc, Philip R., 2023. "Urban solar harvesting: The importance of diffuse shadows in complex environments," Renewable and Sustainable Energy Reviews, Elsevier, vol. 175(C).
    9. 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).
    10. Hui Zhang & Xiaoxi Huang & Zhengwei Wang & Shiyu Jin & Benlin Xiao & Yanyan Huang & Wei Zhong & Aofei Meng, 2024. "An Estimation of the Available Spatial Intensity of Solar Energy in Urban Blocks in Wuhan, China," Energies, MDPI, vol. 17(5), pages 1-26, February.
    11. 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).
    12. 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.
    13. Chen, Qi & Li, Xinyuan & Zhang, Zhengjia & Zhou, Chao & Guo, Zhiling & Liu, Zhengguang & Zhang, Haoran, 2023. "Remote sensing of photovoltaic scenarios: Techniques, applications and future directions," Applied Energy, Elsevier, vol. 333(C).
    14. Ferdowsi, Farzad & Mehraeen, Shahab & Upton, Gregory B., 2020. "Assessing distribution network sensitivity to voltage rise and flicker under high penetration of behind-the-meter solar," Renewable Energy, Elsevier, vol. 152(C), pages 1227-1240.
    15. Pregelj, Boštjan & Micor, Michał & Dolanc, Gregor & Petrovčič, Janko & Jovan, Vladimir, 2016. "Impact of fuel cell and battery size to overall system performance – A diesel fuel-cell APU case study," Applied Energy, Elsevier, vol. 182(C), pages 365-375.
    16. Ramallo-González, Alfonso P. & Loonen, Roel & Tomat, Valentina & Zamora, Miguel Ángel & Surugin, Dmitry & Hensen, Jan, 2020. "Nomograms for de-complexing the dimensioning of off-grid PV systems," Renewable Energy, Elsevier, vol. 161(C), pages 162-172.
    17. 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).
    18. D'Adamo, Idiano & Mammetti, Marco & Ottaviani, Dario & Ozturk, Ilhan, 2023. "Photovoltaic systems and sustainable communities: New social models for ecological transition. The impact of incentive policies in profitability analyses," Renewable Energy, Elsevier, vol. 202(C), pages 1291-1304.
    19. Lu, Qing & Yu, Hao & Zhao, Kangli & Leng, Yajun & Hou, Jianchao & Xie, Pinjie, 2019. "Residential demand response considering distributed PV consumption: A model based on China's PV policy," Energy, Elsevier, vol. 172(C), pages 443-456.
    20. Lange, Christopher & Rueß, Alexandra & Nuß, Andreas & Öchsner, Richard & März, Martin, 2020. "Dimensioning battery energy storage systems for peak shaving based on a real-time control algorithm," Applied Energy, Elsevier, vol. 280(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:8:p:3564-:d:1128615. 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.