Geomatics and Environmental Engineering, vol. 16, no. 4

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Vol. 16 No. 4 (2022): Geomatics and Environmental Engineering

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Submitted
Feb 13, 2022
Accepted
Jul 5, 2022
Published
Oct 12, 2022
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This work is licensed under a Creative Commons Attribution 4.0 International License.

Using GIS and SDSS Tools in the Design of a Photovoltaic System for a Built-up Roof

https://doi.org/10.7494/geom.2022.16.4.31
Lidiia Davybida
Ivano-Frankivsk National Technical University of Oil and Gas, Department of Geotechnical Safety and Geoinformatics, Ukraine
https://orcid.org/0000-0002-9796-7124
Ireneusz Wyczałek
Poznan University of Technology, Institute of Civil Engineering, Poland
http://orcid.org/0000-0003-3963-8186
Artur Plichta
Poznan University of Technology, Institute of Civil Engineering, Poland
https://orcid.org/0000-0001-6134-290X

Corresponding Author(s) : Lidiia Davybida

lidiia.davybida@nung.edu.ua

Geomatics and Environmental Engineering, Vol. 16 No. 4 (2022): Geomatics and Environmental Engineering

Abstract

The design and installation of solar panels on the roofs of urban buildings often require consideration of the specific spatial conditions that affect their efficiency. The primary purpose of this work is to develop a procedure for designing and optimizing photovoltaic installations using geomatics methods and specific tools of GIS and CAD systems. The roof of the historic building A2, which is a part of the Poznań University of Technology campus, was selected as the tested object. Solar radiation modelling and determination of suitability zones were performed using SEBE (Solar Energy on Building Envelopes) in QGIS. Possible options for the placement of photovoltaic modules on the roof were simulated with CAD technique in the web-based HelioScope software. The results of the simulation show that the current roof area can generate electrical power of 99.9 MWh/year. The proposed methodology is universal for photovoltaic installations on built-up roofs and can be applied to other buildings and, consequently, the results obtained can be used to improve the content of the solar data urban geoportal.

Keywords

solar irradiance historic building shadow effect obstructions geospatial assessment roof-top photovoltaic system
Davybida, L., Wyczałek, I. ., & Plichta, A. . (2022). Using GIS and SDSS Tools in the Design of a Photovoltaic System for a Built-up Roof. Geomatics and Environmental Engineering, 16(4), 31–58. https://doi.org/10.7494/geom.2022.16.4.31
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References
  1. Green M.A.: Silicon Photovoltaic Modules: A Brief History of the First 50 Years. Progress in Photovoltaics: Research and Applications, vol. 13, 2005, pp. 447–455. https://doi.org/10.1002/pip.612.
  2. Jastrzębska G.: Ogniwa słoneczne: budowa, technologia i zastosowanie. Wydawnictwa Komunikacji i Łączności, Warszawa 2013.
  3. Soumya C., Deepanraj B., Ranjitha J.: A review on solar photovoltaic systems and its application in electricity generation. [in:] AIP Conference Proceedings, 2396, 020011, 2021. https://doi.org/10.1063/5.0066291.
  4. Mirowski T., Sornek K.: Potencjał energetyki prosumenckiej w Polsce na przykładzie mikroinstalacji fotowoltaicznych w budownictwie indywidualnym [Potential of prosumer power engineering in Poland by example of micro PV installation in private construction]. Polityka Energetyczna, t. 18, z. 2, 2015, pp. 73–84.
  5. Mughal Sh., Sood Yog R., Jarial R.K.: A Review on Solar Photovoltaic Technology and Future Trends. National Conference on Recent Advances in Computer Science and IT (NCRACIT). International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 4, no. 1, 2018, pp. 227–235.
  6. Dondariya C., Porwal D., Awasthi A., Shukla A.K., Bhimte A.: Performance simulation of grid-connected rooftop solar PV system for small households: A case study of Ujjain, India. Energy Reports, vol. 4, 2018, pp. 546–553. https://doi.org/10.1016/j.egyr.2018.08.002.
  7. Bonomolo M., Di Lisi S., Leone G.: Building Information Modelling and Energy Simulation for Architecture Design. Applied Sciences, vol. 11, 2021, 2252. https://doi.org/10.3390/app11052252.
  8. Yankiv-Vitkovska L., Peresunko B., Wyczałek I., Papis J.: Site selection for solar power plant in Zaporizhia city (Ukraine). Geodesy and Cartography, vol. 69, no. 1, 2020, pp. 97–116. https://doi.org/10.24425/gac.2020.131076.
  9. Yushchenko A., de Bono A., Chatenoux B., Kumar Patel M., Ray N.: GIS-based assessment of photovoltaic (PV) and concentrated solar power (CSP) generation potential in West Africa. Renewable & Sustainable Energy Reviews, vol. 81, 2018, pp. 2088–2103. https://doi.org/10.1016/j.rser.2017.06.021.
  10. Romero Rodríguez L., Duminil E., Sánchez Ramos J., Eicker U.: Assessment of the photovoltaic potential at urban level based on 3D City models: A case study and new methodological approach. Solar Energy, vol. 146, 2017, pp. 264–275. https://doi.org/10.1016/j.solener.2017.02.043.
  11. Khan J., Arsalan M.H.: Estimation of rooftop solar photovoltaic potential using geo-spatial techniques: A perspective from planned neighborhood of Karachi – Pakistan. Renewable Energy, vol. 90, 2016, pp. 188–203. https://doi.org/10.1016/j.renene.2015.12.058.
  12. Fuentes J.E., Francisco D.M., Oscar D.M.: Method for Estimating Solar Energy Potential Based on Photogrammetry from Unmanned Aerial Vehicles. Electronics, vol. 9, no. 12, 2020, 2144. https://doi.org/10.3390/electronics9122144.
  13. Zambrano-Asanza S., Quiros-Tortos J., Franco J.: Optimal site selection for photovoltaic power plants using a GIS-based multi-criteria decision making and spatial overlay with electric load. Renewable and Sustainable Energy Reviews, vol. 143, 2021, 110853. https://doi.org/10.1016/j.rser.2021.110853.
  14. Bujarkiewicz A., Sztubecka M., Sztubecki J.: The Study of Using GIS Tools in Sustainable Management of Solar Energy. Civil and Environmental Engineering Reports, vol. 28, 2018, pp. 26–39. https://doi.org/10.2478/ceer-2018-0003.
  15. Chow A., Alan S.F., Songnian L.: GIS Modeling of Solar Neighborhood Potential at a Fine Spatiotemporal Resolution. Buildings, vol. 4, no. 2, 2014, pp. 195–206. https://doi.org/10.3390/buildings4020195.
  16. Iñaki P., Izkara J.L., Usobiaga E.: The Application of LiDAR Data for the Solar Potential Analysis Based on Urban 3D Model. Remote Sensing, vol. 11, no. 20, 2019, 2348. https://doi.org/10.3390/rs11202348.
  17. Redweik P., Catita C., Brito M.: Solar energy potential on roofs and facades in an urban landscape. Solar Energy, vol. 97, 2013, pp. 332–341. https://doi.org/10.1016/j.solener.2013.08.036.
  18. Thebault M., Clivillé V., Berrah L., Desthieux G.: Multicriteria roof sorting for the integration of photovoltaic systems in urban environments. Sustainable Cities and Society, vol. 60, 2020, 102259. http://doi.org/10.1016/j.scs.2020.102259.
  19. Stachura T., Krzyś M.: GIS-based assessment of the feasibility of solar energy applications, in the case of Łazy village. Geomatics, Landmanagement and Landscape, no. 1, 2017, pp. 65–79. http://doi.org/10.15576/GLL/2017.1.65.
  20. Beseničar J., Trstenjak B., Setnika D.: Application of geomatics in photovoltaics. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. 37(B4), 2008, pp. 53–56.
  21. Guaita-Pradas I., Marques-Perez I., Gallego A., Segura B.: Analyzing territory for the sustainable development of solar photovoltaic power using GIS databases. Environmental Monitoring and Assessment, vol. 191, 2019, 764. https://doi.org/10.1007/s10661-019-7871-8.
  22. Ostapenko O., Koval V., Olczak P., Нren L., Matuszewska D., Postupna О.: Application of Geoinformation Systems for Assessment of Effective Integration of Renewable Energy Technologies in the Energy Sector of Ukraine. Applied Sciences, vol. 12, 2022, 592. https://doi.org/10.3390/app12020592.
  23. Bukowski M., Majewski J., Sobolewska A.: Macroeconomic Electric Energy Production Efficiency of Photovoltaic Panels in Single-Family Homes in Poland. Energies, vol. 14(1), no. 126, 2021. https://doi.org/10.3390/en14010126.
  24. Gassar A.A.A., Cha S.H.: Review of geographic information systems-based rooftop solar photovoltaic potential estimation approaches at urban scales. Applied Energy, vol. 291, 2021, 116817. https://doi.org/10.1016/j.apenergy.2021.116817.
  25. Pawłowska M., Pawłowski L. (eds.): Advances in Environmental Engineering Research in Poland. 1st ed. Routledge, London 2021. https://doi.org/10.1201/9781003171669.
  26. Bremer M., Mayr A., Wichmann V., Schmidtner K., Rutzinger M.: A new multi-scale 3D-GIS-approach for the assessment and dissemination of solar income of digital city models. Computers, Environment and Urban Systems, vol. 57, 2016, pp. 144–154. https://doi.org/10.1016/j.compenvurbsys.2016.02.007.
  27. Saretta E., Bonomo P., Frontini F.: A calculation method for the BIPV potential of Swiss façades at LOD2.5 in urban areas: A case from Ticino region. Solar Energy, vol. 195, 2020, pp. 150–165. http://doi.org/10.1016/j.solener.2019.11.062.
  28. Brito M., Redweik P., Catita C., Freitas S., Santos M.: 3D Solar Potential in the Urban Environment: A Case Study in Lisbon, Energies, vol. 12, no. 18, 2019, 3457. https://doi.org/10.3390/en12183457.
  29. Sánchez-Aparicio M., Jimenez Jose A., Del Pozo S., González E., Lagüela S.: Ener3DMap-SolarWeb roofs: A geospatial web-based platform to compute photovoltaic potential. Renewable and Sustainable Energy Reviews, vol. 135, 2021, 110203. https://doi.org/10.1016/j.rser.2020.110203.
  30. Desthieux G., Carneiro C., Camponovo R., Ineichen P., Morello E., Boulmier A., Abdennadher N. et al.: Solar energy potential assessment on rooftops and facades in large built environments based on LIDAR data, image processing, and cloud computing. Methodological background, application, and validation in Geneva (solar cadaster ). Frontiers Built Environment, vol. 4, 2018, 14. https://doi.org/10.3389/fbuil.2018.00014.
  31. Stendardo N., Desthieux G., Abdennadher N., Gallinelli P.: GPU-Enabled Shadow Casting for Solar Potential Estimation in Large Urban Areas. Application to the Solar Cadaster of Greater Geneva. Applied Sciences, vol. 10, 2020, 5361. https://doi.org/10.3390/app10155361.
  32. Bieda A., Cienciała A.: Towards a Renewable Energy Source Cadastre – A Review of Examples from around the World. Energies, vol. 14, no. 23, 2021, 8095. https://doi.org/10.3390/en14238095.
  33. SIP Poznan. http://sip.poznan.pl/model3d/#/legend [access: 1.12.2021].
  34. Solar cadaster of Grand Genève. https://apps.sitg-lab.ch/solaire/ [access: 9.04.2022].
  35. Map of solar potential in Munich. https://geoportal.muenchen.de/portal/solarpotenzial/ [access: 9.04.2022].
  36. The London Solar Opportunities Map. https://maps.london.gov.uk/lsom/?_gl=1%2a13sqp4w%2a_ga%2aMTY4OTIzNzMzOC4xNjQ5NTEzODc4 [access: 9.04.2022].
  37. Solar atlas of Amsterdam. https://www.zonatlas.nl/amsterdam/ontdek-de-zonatlas/ [access: 9.04.2022].
  38. Map of solar potential in Wrocław. https://gis.um.wroc.pl/en/maps/solarna/ [access: 9.04.2022].
  39. Mapping solar energy resources in San Francisco. http://app.dumpark.com/sunlight/sf [access: 9.04.2022].
  40. Energy Efficiency and Historic Buildings: Solar Electric (Photovoltaics). Historic England, Swindon 2018.
  41. Kandt A., Hotchkiss E., Walker A., Buddenborg J., Lindberg J.: Implementing Solar PV Projects on Historic Buildings and in Historic Districts. National Renewable Energy Laboratory, Colorado 2011.
  42. Global Solar Atlas. https://globalsolaratlas.info/download/poland [access: 8.12.2021].
  43. Geoportal Poland. https://www.geoportal.gov.pl/ [access: 8.12.2021].
  44. Google Earth Engine. A planetary-scale platform for Earth science data and analysis. https://earthengine.google.com/ [access: 8.12.2021].
  45. Solar Energy – Introduction to SEBE. https://umep-docs.readthedocs.io/projects/tutorial/en/latest/Tutorials/SEBE.html [access: 9.04.2022].
  46. Garcia R., Polo J.: Evaluating the Solar Potential of Rooftops on Campus San Joaquín, Santiago – Chile using Opensource GIS. [in:] EuroSun2020 – ISES Conference Proceedings, International Solar Energy Society, 2020. https://doi.org/10.18086/eurosun.2020.01.12.
  47. SunPower. https://sunpower.maxeon.com/uk/solar-panel-products/maxeon-solar-panels [access: 8.12.2021].
  48. PVGIS – Photovoltaic Geographical Information System. https://ec.europa.eu/jrc/en/pvgis [access: 8.12.2021].
  49. University of Oregon. Solar Radiation Monitoring Laboratory. http://solardat.uoregon.edu/SunChartProgram.html [access: 8.12.2021].
  50. Fialho L., Melicio R., Mendes V.M.F., Figueiredo J., Collares-Pereira M.: Effect of Shading on Series Solar Modules: Simulation and Experimental Results. Procedia Technology, vol. 17, 2014, pp. 295–302. https://doi.org/10.1016/j.protcy.2014.10.240.
  51. HelioScope. Advanced Solar Design Software. https://www.helioscope.com/ [access: 8.12.2021].
  52. Green M., Ho-Baillie A., Snaith H.: The emergence of perovskite solar cells. Nature Photon, vol. 8, 2014, pp. 506–514. https://doi.org/10.1038/nphoton.2014.134.
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