Open Access Open Access  Restricted Access Subscription or Fee Access

Application of GIS tools to the improvement of energy supply in PV rooftop installations

Carlos Armenta-Déu, Félix Jesús Segura-Muñoz, Francisco José Domínguez-Bravo


Present work studies the energy supply from photovoltaic (PV) installations in industrial conglomerates using the rooftops as a surface to install the PV panels. The study is based on a modelling procedure that takes into account the specific characteristics of the rooftop, shape, size, azimuth and inclination, using GIS tools to identify these parameters for every single rooftop. Modelling has been developed modifying the tilt angle of the PV panel for vertical and horizontal PV panel layout and analyzing which one of the two configurations generates more energy. The study has been extended for tilt angles from the horizontal plane to the latitude of the location. The methodology uses a previous study in determining the optimum number of PV panels that can be placed on the rooftop. Shading effects have been taken into account for energy supply calculation, resulting in a variation with the tilt angle of the PV panel that depends on the range of the tilt angle; three ranges have been identified, low (0≤β/ϕ≤0.3), medium (0.3≤β/ϕ≤0.8)and high (0.8≤β/ϕ≤1). Maximum variation, 1.6%, has been observed in the low range, while for the high range energy supply does not seem there is no blocking to depend on the tilt angle. The results show that the modelling matches theoretical predictions within accuracy higher than 99.4%. Modelling has also been developed for two different configurations of the PV panel positioning, vertical and horizontal. Tests have been applied to the largest and smallest rooftop; the similar trend in the evolution and the close values of the energy supply with tilt angle proves that the methodology can be applied to any of the industrial building rooftops. The results of the modelling show that there is no much difference between the two configurations; however, horizontal configuration works better for larger areas while vertical one is more suitable for smaller areas. Additional row has been added to the layout provided the shadow is out of rooftop bounds. The increase of the energy is not very relevant, barely 1% for the vertical configuration and 0.2% for the horizontal one.

Full Text:



International Energy Agency (IEA) (Statistics of IEA © OCDE/AIE, ); Energy Statistics of OCDE and non-OCDE country balance, 2019. [Online]. Available:

Christian Breyer, Otto Koskinen and Philipp Blechinger (2015) Profitable climate change mitigation: The case of greenhouse gas emission reduction benefits enabled by solar photovoltaic systems, Renewable and sustainable Energy Reviews, Vol.49, pp.610-628

Global Market Outlook for Solar Power 2016-2020, Solar Power Europe (SPE), January 2017

Global Market Outlook for Solar Power 2015-2019, Solar Power Europe (SPE), June 2015

Global Market Outlook for Photovoltaics 2014-2018, European Photovoltaic Industry Association (EPIA), June 2014

Snapshot on Global PV 1992-2014, International Energy Agency (IEA), Photovoltaic Power System Programme, March 2015

Snapshot on Global PV 1992-2015, International Energy Agency (IEA), Photovoltaic Power System Programme, 2015

Snapshot on Global PV Markets 2016, International Energy Agency (IEA), Photovoltaic Power System Programme, October 2017

Electricity in the USA. US Energy Information Administration (EIA), March 2020

Electricity mix in the European Union, EIA, Q1, April 2020

Mohammad Javanbakht, Ali Darvishi Boloorani, Majid Kiavarz, Najmeh Neisany Samany, Lobat Zebardast and Mahdieh Zangiabadi (2021) Spatial-temporal analysis of urban environmental quality of Tehran, Iran, Ecological Indicators, Vol.120, 106901

Jinqing Peng and Lin Lu (2013) Investigation on the development potential of rooftop PV system in Hong Kong and its environmental benefits, Renewable and Sustainable Energy Reviews, Vol.27, pp.149-162

Christopher Jones and Paul Gilbert (2018) Determining the consequential life cycle greenhouse gas emissions of increased rooftop photovoltaic deployment, Journal of Cleaner Production, Vol.184, pp-211-219

The impact of increasing home size on energy demand, Residential Energy Consumption Survey (RECS), EIA, US. Energy Information Administration, 2009

Qing Zhong and Daoqin Tong (2020) Spatial layout optimization for solar photovoltaic (PV) panel installation, Renewable Energy, Vol.150, pp.1-11

Adam Hinge, Paolo Bertoldi and Paul Waide (2004) Comparing Commercial Building Energy Use Around the World, IEA, EU Commission DG JRC, Proceedings, pp.4-136 to 4-147

Yibo Chen, Hongwei Tan, Simeng Li and Xiaodong Song (2017) GIS-based Dimensionless Assessment of Distributed Rooftop PV in Chinese Residential Communities, Procedia Engineering, Vol.205, pp.205-212

Osama Bany Mousa, Robert A. Taylor and Ali Shirazi (2019) Multi-objective optimization of solar photovoltaic and solar thermal collectors for industrial rooftop applications, Energy Conversion and Management, Vol.195, pp.392-408

Sagar G. Randive and T.Z. Quazi (2017) Review Paper On Energy Consumption in Industrial Sector, International Journal of Scientific & Engineering Research, Volume 8, Issue 3, pp.254-258

Jannik Heusinger, Ashley M. Broadbent, E. Scott Krayenhoff and Stephan Weber (2021) Adaptation of photovoltaic energy balance model for rooftop applications, Building and Environment, Vol.192, 107628

WaqasAhmed, Jamil Ahmed Sheikh, Salman Ahmad, Shahjadi Hisan Farjana and M.A. Parvez Mahmud (2021) Impact of PV system orientation angle accuracy on greenhouse gases mitigation, Case Studies in Thermal Engineering, Vol.23, 100815

Taehoon Hong, Choongwan Koo, Joonho Park and Hyo Seon Park (2014) A GIS (geographic information system)-based optimization model for estimating the electricity generation of the rooftop PV (photovoltaic) system, Energy, Vol.65, pp.190-199

Segura-Muñoz, F.J., Armenta-Déu, C. and Domínguez-Bravo, F.J. (2021) Rooftop layout optimization for PV installation using GIS, Journal of Remote Sensing and GIS (under review)

“WGS 84 / UTM zone 14N - EPSG:32614.” [Online]. Available: [Accessed: 17-Feb-2021]

“ArcGIS,” 2017. [Online]. Available: [Accessed: 10-May-2017]

G. I. Northern et al., “NASA Surface meteorology and Solar Energy ­ Available Tables Parameters for Solar Cooking :,” pp. 1–21, 2015

P. D. Paul W. Stackhouse, Jr., “NASA Surface meteorology and Solar Energy,” 2016, p. 1, 2016

Q. Hernández-Escobedo, A. Fernández-García, and F. Manzano-Agugliaro, “Solar resource assessment for rural electrification and industrial development in the Yucatan Peninsula (Mexico),” Renewable and Sustainable Energy Reviews, vol. 76. pp. 1550–1561, 2017

E. Lorenzo, Electricidad Solar Fotovoltaica: Ingeniería fotovoltaica, vol. III. Ed. Progensa, Sevilla, 2014

Germán Santamaría-Herranz and Agustín Castejón-Oliva, “Instalaciones Solares Fotovoltaicas,” p. 32, Ed. Editex. Madrid. 2012

O. Perpiñán Lamigueiro, Energía Solar Fotovoltaica, Diseño de Sistemas Fotovoltaicos, Ed. Progensa, Sevilla. 2014. Licence by Creative Commons

“The Python Language Reference — Python 3.9.2 documentation.” [Online]. Available: [Accessed: 23-Feb-2021]



  • There are currently no refbacks.

eISSN: 2230-7990