Abstract
Photovoltaic (PV) production from the sun significantly contributes to the sustainable generation of energy from renewable resources. With the availability of detailed 3D city models across many cities in the world, accurate calculation of PV energy production can be performed. The goal of this paper is to introduce and describe PLANTING, a numerical model to estimate the solar irradiance and PV potential at the resolution of individual building surfaces and hourly time steps, using 3D city models. It considers the shading of neighboring buildings and terrains to perform techno-economic PV potential assessment with indicators such as installed power, produced electrical energy, levelized cost of electricity on the horizontal, vertical and tilted surfaces of buildings in a city or district. It is developed within an open-source architecture using mostly non-proprietary data formats, software and tools. The model has been tested on many cities in Europe and as a case study, the results obtained on the city of Lyon in France are explained in this paper. PLANTING is flexible enough to allow the users to choose PV installation settings, based on which solar irradiance and energy production calculations are performed. The results can also be aggregated at coarser spatial (building, district) and temporal (daily, monthly, annual) resolutions or visualized in 3D maps. Therefore, it can be used as a planning tool for decision makers or utility companies to optimally design the energy supply infrastructure in a district or city.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
- 2.
- 3.
- 4.
- 5.
- 6.
- 7.
- 8.
PANDA 60 CELL SERIES 2, 260-280 Wc, Yingli Solar, available at www.yinglisolar.com.
- 9.
JKM270P-60-V, 255-270 W, Jinko Solar, available at www.jinkosolar.com.
- 10.
First Solar Series 4™ PV Module, available at www.firstsolar.com.
- 11.
The economic assumptions can be improved with more recent data on affordable PV panels.
- 12.
References
Ademe (2015) Filière Photovoltaïque Française: Bilan, perspectives et Stratégie. Agence De l’Environnement et de la Maitrise de l’Energie, Angers
Alam N, Coors V, Zlatanova S, Van Oosterom P. Shadow effect on photovoltaic potentiality analysis using 3D city models. In: XXII congress of the international society for photogrammetry and remote sensing, 25 August–1 September 2012, Melbourne. ISPRS
Bahu J-M, Koch A, Kremers E, Murshed, SM (2014). Towards a 3D spatial urban energy modelling approach. Int J 3-D Informat Model 3:1–16
Biljecki F, Stoter J, Ledoux H, Zlatanova S, Çöltekin A (2015) Applications of 3D city models: state of the art review. ISPRS Int J Geo-Informat 4:2842–2889
Buffat R (2016) Feature-aware surface interpolation of rooftops using low-density lidar data for photovoltaic applications. In: Sarjakoski T, Santos M, Sarjakoski L (eds.) Geospatial data in a changing world. Lecture notes in geoinformation and cartography geospatial data in a changing world. Cham, Springer
Catita C, Redweik P, Pereira J, Brito MC (2014) Extending solar potential analysis in buildings to vertical facades. Comput Geosci 66:1–12
Chaturvedi K, Willenborg B, Sindram M, Kolbe TH (2017) Solar potential analysis and integration of the time-dependent simulation results for semantic 3D city models using dynamizers. ISPRS Ann Photogramm Remote Sens Spatial Inf Sci IV-4/W5:25–32
Cole IR, Palmer D, Betts TR, Gottschalg, R (2016) A fast and effective approach to modelling solar energy potential in complex environments. In: 32nd European photovoltaic solar energy conference and exhibition, 20–24 June 2017. Munich
Duffie JA, Beckman WA (2006) Solar engineering of thermal processes. Wiley, New York
El Hajje G, Boyere E (2017) Comparison and cross validation of PV production models used by EIFER and EDF R&D/TREE. EDF R&D, Moret Sur Loing Cedex
European Commission E (2011) Review of the energy performance of buildings directive 2010/31/EU. EC Directorate-General of Energy, Brussels
European Commission E (2017) Climate strategies and targets [Online]. http://ec.europa.eu/clima/policies/strategies/2020. Accessed 2017
Freitas S, Catita C, Redweik P, Brito M (2015) Modelling solar potential in the urban environment: State-of-the-art review. Renew Sustain Energy Rev 41:915–931
Gueymard CA (2012) Clear-sky irradiance predictions for solar resource mapping and large-scale applications: Improved validation methodology and detailed performance analysis of 18 broadband radiative models. Sol Energy 86:2145–2169
Hofierka J, Zlocha M (2012) A new 3-D solar radiation model for 3-D city models. Trans GIS 16:681–690
Huld T (2017) PVMAPS: software tools and data for the estimation of solar radiation and photovoltaic module performance over large geographical areas. Sol Energy 142:171–181
Jaillot V, Pedrinis F, Servigne S, Gesquière G (2017) A generic approach for sunlight and shadow impact computation on large city models. In: 25th international conference on computer graphics, visualization and computer vision, May 29–June 2, 2017. Pilsen, Czech Republic
Jourdier B, Hoang T-T-H, Chiodetti M (2016) Reconstitution de la production photovoltaïque horaire en Grande-Bretagne et Turquie sur 58 ans et validation d’un nouveau modèle physique de production PV. EDF R&D, Chatou cedex
Lee J, Zlatanova S (2009) Solar radiation over the urban texture: LIDAR data and image processing techniques for environmental analysis at city scale. In: Lee J, Zlatanova S (eds) 3D Geo-information sciences. Lecture notes in geoinformation and cartography. Springer, Berlin, Heidelberg
Li Y, Liu C (2017) Estimating solar energy potentials on pitched roofs. Energy Build 139:101–107
Luque A, Hegedus S (2011) Handbook of photovoltaic science and engineering Wiley
Mainzer K, Fath K, Mckenna R, Stengel J, Fichtner W, Schultmann F (2014) A high-resolution determination of the technical potential for residential-roof-mounted photovoltaic systems in Germany. Sol Energy 105:715–731
Martin N, Ruiz J (2001) Calculation of the PV modules angular losses under field conditions by means of an analytical model. Sol Energy Mater Sol Cells 70:25–38
Murshed SM, Picard S, Koch A (2017) CityBEM: an open source implementation and validation of monthly heating and cooling energy needs for 3D buildings in cities. ISPRS Ann. Photogramm Remote Sens Spatial Inf Sci. IV-4/W5 83–90
Murshed SM, Simons A, Lindsay A, Picard S, De Pin C (2018) Evaluation of two solar radiation algorithms on 3D city models for calculating photovoltaic potential. In: 4th international conference on geographical information systems theory, applications and management, 17–19 March 2018. Funchal, Madeira, Portugal
Ogc 2012. OGC City Geography Markup Language (CityGML) Encoding Standard 2.0.0. Open Geospatial Consortium
Palmer D, Cole IR, Goss B, Betts TR, Gottschalg R (2015) Detection of roof shading for PV based on LiDAR data using a multi-modal approach, 14–18 September 2015. In: 31st European photovoltaic solar energy conference and exhibition. Hamburg
Quaschning V (2011) Regenerative energiesysteme. München, Carl Hanser Verlag, Technologie-Berechnung-Simulation
Redweik P, Catita C, Brito M (2013) Solar energy potential on roofs and facades in an urban landscape. Sol Energy 97:332–341
Santos T, Gomes N, Freire S, Brito M, Santos L, Tenedório J (2014) Applications of solar mapping in the urban environment. Appl Geogr 51:48–57
Sarralde JJ, Quinn DJ, Wiesmann D, Steemers K (2015) Solar energy and urban morphology: scenarios for increasing the renewable energy potential of neighbourhoods in London. Renew Energy 73:10–17
Strzalka A, Alam N, Duminil E, Coors V, Eicker U (2012) Large scale integration of photovoltaics in cities. Appl Energy 93:413–421
Šúri M, Hofierka J (2004) A new GIS-based solar radiation model and its application to photovoltaic assessments. Trans GIS 8:175–190
Test F, Lessmann R, Johary A (1981) Heat transfer during wind flow over rectangular bodies in the natural environment. J Heat Transf 103:262–267
Vdma (2016) International technology roadmap for photovoltaic (ITRPV) 2015 results., 7th edn. VDMA, Frankfurt am Main
Wate P, Coors V (2015) 3D data models for urban energy simulation. Energy Procedia 78:3372–3377
Wieland M, Nichersu A, Murshed SM, Wendel J (2015) Computing solar radiation on CityGML building data. In: 18th AGILE international conference on geographic information science, June 9–12. Lisbon
Wilcox S, Marion W (2008) Users manual for TMY3 data sets. Colorado, National Renewable Energy Laboratory (NREL)
Acknowledgements
We are grateful to EDF R&D and Métropole de Lyon for funding this research within the projects “Smart and Low Carbon Cities” and “Modélisation Urbaine Gerland (MUG)”, respectively. Our heartiest gratitude to the city of Lyon and Laboratoire LIRIS for providing the 3D city model of Lyon. We would like to thank City of Karlsruhe for the permission of using the CityGML data for evaluating the model. We are very grateful to Gilbert El Hajje and Emmanuel Boyere of EDF R&D for comparison and cross validation of the model. We also acknowledge Fabrice Casciani, Monika Heyder, Pierre Imbert, Omar Benhamid, Alexandru Nichersu, Céline De Pin, Alice Duval, Manfred Wieland and other colleagues for their input. Finally, our sincere gratitude extends to the editors and two anonymous referees for their insightful comments, which helped us to improve the manuscript.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
1 Electronic Supplementary Material
Below is the link to the electronic supplementary material.
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this paper
Cite this paper
Murshed, S.M., Lindsay, A., Picard, S., Simons, A. (2018). PLANTING: Computing High Spatio-temporal Resolutions of Photovoltaic Potential of 3D City Models. In: Mansourian, A., Pilesjö, P., Harrie, L., van Lammeren, R. (eds) Geospatial Technologies for All. AGILE 2018. Lecture Notes in Geoinformation and Cartography. Springer, Cham. https://doi.org/10.1007/978-3-319-78208-9_2
Download citation
DOI: https://doi.org/10.1007/978-3-319-78208-9_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-78207-2
Online ISBN: 978-3-319-78208-9
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)