Abstract
Australia is receiving an average of 58 million PJ of solar radiation per year, which is about 1000 times larger than its total energy generation. Roof-top solar photovoltaic (PV) systems alone can supply a phenomenal fraction of the nation’s total energy. The architectural design and orientation of roofs have considerable impacts on the energy efficiency of roof-top solar PV systems. These aspects, however, have received scant academic attention within the literature. To address this knowledge gap, this research seeks to increase the energy production of roof-top solar PV systems through roof design. The energy generation of roof-top solar PV systems is modelled using Helioscope software, and then validated using real-time monitored data. Based on the verified model, the impact of different tilt angles and shading from surrounding obstructions upon energy generation are analyzed in detail. To ground the research in practical terms, the aesthetic design of five typical roof design patterns (including flat, shed, gable, hip, and butterfly roof) are explored to compare the energy generated from solar PV systems fitted to each design. Findings indicate that: (1) the simulated energy generation from the solar PV system is close to the monitored data, with equal annual generation; (2) the shading of surrounding obstructions can reduce the energy generation of roof-top solar PV systems considerably, where up to 24% energy loss is reported; (3) the optimal tilt angle is about 35°, which is close to the latitude angle of the studied location; and (4) the shed roof design provides the maximum potential for solar energy generation when compared to that of other roof design patterns. The energy generation variation of other aesthetic roof patterns is also presented, providing support for informed decision making on the roof design. This study contributes to the field through improving the energy production of roof-top solar PV systems based on roof design along with considering aesthetic concerns. Novel insights generated will be beneficial for researchers and government policy makers alike; the work also introduces simulation-based methodological approaches for practitioners who seek to improve the energy generation of roof-top solar PV systems.
Similar content being viewed by others
References
Ahmad MJ, Tiwari GN (2009). Optimization of tilt angle for solar collector to receive maximum radiation. The Open Renewable Energy Journal, 2009(2): 19–24.
Ahmed Bhuiyan M, Rashid Khan HU, Zaman K, Hishan SS (2018). Measuring the impact of global tropospheric ozone, carbon dioxide and sulfur dioxide concentrations on biodiversity loss. Environmental Research, 160: 398–411.
Alhusayni S (2017). Cost benefit analysis of PV and storage installation at Murdoch University. Honours Thesis, Murdoch University, Australia. Available at https://researchrepository.murdoch.edu.au/id/eprint/36733/1/ENG470%20Alhusayni%20Honours%20Thesis.pdf
Australian Bureau of Statistics (2012). Household Energy Consumption Survey, Australia: Summary of Results. Available at http://www.abs.gov.au/ausstats/abs@.nsf/Lookup/4670.0main+features100052012.2014.04.029
British Standards Institution (2013). BS 6229:2003 Flat Roofs with Continuously Supported Coverings-Code of Practice, London, UK.
Brito MC, Gomes N, Santos T, Tenedório JA (2012). Photovoltaic potential in a Lisbon suburb using LiDAR data. Solar Energy, 86: 283–288.
Brown G, Kyttä M (2014). Key issues and research priorities for public participation GIS (PPGIS): A synthesis based on empirical research. Applied Geography, 46: 122–136.
Bulliet RW, Hirsch SW, Johnson LL, Crossley PK, Headrick DR, Northrup D (2018). The Earth and Its Peoples: A Global History, 7th edn. London: Cengage Publishing.
Burger B, Rüther R (2006). Inverter sizing of grid-connected photovoltaic systems in the light of local solar resource distribution characteristics and temperature. Solar Energy, 80: 32–45.
Byrne J, Taminiau J, Kurdgelashvili L, Kim KN (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, 41: 830–844.
Cameron PC, Boyson WE, Riley DM (2008). Comparison of PV system performance-model predictions with measured PV system performance. In: Proceedings of the 33rd IEEE Photovoltaic Specialists Conference.
Carneiro C, Morello E, Voegtle T, Golay F (2010). Digital urban morphometrics: automatic extraction and assessment of morphological properties of buildings. Transactions in GIS, 14: 497–531.
Chan HY, Riffat SB, Zhu J (2010). Review of passive solar heating and cooling technologies. Renewable and Sustainable Energy Reviews, 14: 781–789.
Chen J, Hao Q, Yoon C (2018). Measuring the welfare cost of air pollution in Shanghai: evidence from the housing market. Journal of Environmental Planning and Management, 61: 1744–1757.
Clark DR, Klein SA, Beckman WA (1984). A method for estimating the performance of photovoltaic systems. Solar Energy, 33: 551–555.
Cowan H, Smith P (2004). Dictionary of Architectural and Building Technology, 4th edn. London: Routledge.
Crawley DB (1998). Which weather data should you use for energy simulations of commercial buildings? ASHRAE Transactions, 104(2): 498–515.
Crook JA, Jones LA, Forster PM, Crook R (2011). Climate change impacts on future photovoltaic and concentrated solar power energy output. Energy & Environmental Science, 4: 3101–3109.
Curl JS, Wilson S (2006). Oxford Dictionary of Architecture and Landscape Architecture, 2nd edn. Oxford: UK: Oxford University Press.
Dalu MTB, Shackleton CM, Dalu T (2018). Influence of land cover, proximity to streams and household topographical location on flooding impact in informal settlements in the Eastern Cape, South Africa. International Journal of Disaster Risk Reduction, 28: 481–490.
Darhmaoui H, Lahjouji D (2013). Latitude based model for tilt angle optimization for solar collectors in the mediterranean region. Energy Procedia, 42: 426–435.
Davis JP, Eisenhardt KM, Bingham CB (2007). Developing theory through simulation methods. Academy of Management Review, 32: 480–499.
Duffie JA, Beckman WA (2013). Solar Engineering of Thermal Processes, 4th edn. Hoboken, NJ, USA: John Wiley & Sons.
Flynn C, Kennedy T (2018). Australia’s Energy Future—A Shift to Rooftop Solar. Available at https://www.gtlaw.com.au/insights/australias-energy-future-shift-rooftop-solar
Geoscience Australia (2010). Australian Energy Resource Assessment. Available at https://www.ga.gov.au/scientific-topics/energy/resources/other-renewable-energy-resources/solar-energy
Gong X, Kulkarni M (2005). Design optimization of a large scale rooftop photovoltaic system. Solar Energy, 78: 362–374.
Gostein M, Caron JR, Littmann B (2014). Measuring soiling losses at utility-scale PV power plants. In: Proceedings of IEEE 40th Photovoltaic Specialist Conference (PVSC), Denver, CO, USA.
Goswami DY, Kreith F, Kreider JF (2000). Principles of Solar Engineering. Boca Raton, FL, USA: CRC Press.
Green MA, Emery K, Hishikawa Y, Warta W (2010). Solar cell efficiency tables (version 36). Progress in Photovoltaics: Research and Applications, 18: 346–352.
Grineski SE, Collins TW (2018). Geographic and social disparities in exposure to air neurotoxicants at US public schools. Environmental Research, 161: 580–587.
Gui N, Li J, Dong Y, Qiu Z, Jia Q, Gui W, Geert D (2017). BIM-based PV system optimization and deployment. Energy and Buildings, 150: 13–22.
Guittet D, Freeman JM (2018). Validation of photovoltaic modeling tool helioscope against measured data. National Renewable Energy Laboratory. Available at https://www.nrel.gov/docs/fy19osti/72155.pdf
Hossain MF (2018). Photon application in the design of sustainable buildings to console global energy and environment. Applied Thermal Engineering, 141: 579–588.
Kacira M, Simsek M, Babur Y, Demirkol S (2004). Determining optimum tilt angles and orientations of photovoltaic panels in Sanliurfa, Turkey. Renewable Energy, 29: 1265–1275.
Kinesis (2018). Deakin University organisational sustainability reporting platform. Available at https://kinesis.org/case-studies/deakin-university
Li HX, Gül M, Yu H, Awad H, Al-Hussein M (2016). An energy performance monitoring, analysis and modelling framework for NetZero Energy Homes (NZEHs). Energy and Buildings, 126: 353–364.
Li HX, Chen Y, Gül M, Yu H, Al-Hussein M (2018). Energy performance and the discrepancy of multiple NetZero Energy Homes (NZEHs) in cold regions. Journal of Cleaner Production, 172: 106–118.
Lombardo T (2014). Helioscope: An Integrated Photovoltaic Design Tool. Available at https://www.engineering.com/ElectronicsDesign/ ElectronicsDesignArticles/ArticleID/7045/Heli%20oscope-An-Integrated-Photovoltaic-design-Tool.aspx
Loutzenhiser PG, Manz H, Felsmann C, Strachan PA, Frank T, Maxwell GM (2007). Empirical validation of models to compute solar irradiance on inclined surfaces for building energy simulation. Solar Energy, 81: 254–267.
Lukac N, Seme S, Žlaus D, Štumberger G, Žalik B (2014). Buildings roofs photovoltaic potential assessment based on LiDAR (light detection and ranging) data. Energy, 66: 598–609.
Martínez-Moreno F, Muñoz J, Lorenzo E (2010). Experimental model to estimate shading losses on PV arrays. Solar Energy Materials and Solar Cells, 94: 2298–2303.
Meteonorm (2017). Meteonorm data and program. Compared to version 7.1, version 7.2 includes updated meteorological and turbidity data and additional features. Available at http://files.pvsyst.com/help/meteo_source_meteonorm.htm
Mohajeri N, Assouline D, Guiboud B, Scartezzini, JL (2016). Does roof shape matter? Solar photovoltaic (PV) integration on building roofs. In: Proceedings of the International Conference on Sustainable Built Environment (SBE) Regional Conference. Expanding Boundaries: Systems Thinking for the Built Environment, Zurich, Switzerland.
Mohajeri N, Assouline D, Guiboud B, Bill A, Gudmundsson A, Scartezzini JL (2018). A city-scale roof shape classification using machine learning for solar energy applications. Renewable Energy, 121: 81–93.
Norberto C, Gonzalez-Brambila CN, Matsumoto Y (2016). Systematic analysis of factors affecting solar PV deployment. Journal of Energy Storage, 6: 163–172.
Pacca S, Sivaraman D, Keoleian GA (2007). Parameters affecting the life cycle performance of PV technologies and systems. Energy Policy, 35: 3316–3326.
Quaschning V, Hanitsch R (1995). Shade calculations in photovoltaic systems. In: Proceedings of ISES Solar World Conference, Harare, Zimbabwe.
Ramabadran R, Mathur B (2009). Effect of shading on series and parallel connected solar PV modules. Modern Applied Science, 3(10): 32–41.
Sandia National Laboratories, (2018). Extraterrestrial radiation. Available at https://pvpmc.sandia.gov/modeling-steps/1-weather-design-inputs/irradiance-and-insolation-2/extraterrestrial-radiation. Accessed 12 Mar 2019.
Sharma DK, Verma V, Singh AP (2014). Review and Analysis of Solar Photovoltaic Softwares. International Journal of Current Engineering and Technology, 4: 725–731.
Triana MA, Lamberts R, Sassi P (2018). Should we consider climate change for Brazilian social housing? Assessment of energy efficiency adaptation measures. Energy and Buildings, 158: 1379–1392.
Troy P (2000). A History of European Housing in Australia. Cambridge, UK: Cambridge University Press.
Tsoutsos T, Frantzeskaki N, Gekas V (2005). Environmental impacts from the solar energy technologies. Energy Policy, 33: 289–296.
Tyagi VV, Rahim NAA, Rahim NA, Selvaraj JA (2013). Progress in solar PV technology: Research and achievement. Renewable and Sustainable Energy Reviews, 20: 443–461.
Umar N, Bora B, Banerjee C, Panwar BS (2013). Comparison of different PV power simulation softwares: Case study on performance analysis of 1 MW grid-connected PV solar power plant. International Journal of Engineering Science Invention, 7(7): 11–24.
Wiginton LK, Nguyen HT, Pearce JM (2010). Quantifying rooftop solar photovoltaic potential for regional renewable energy policy. Computers, Environment and Urban Systems, 34: 345–357.
Woiceshyn J, Daellenbach U (2018). Evaluating inductive vs deductive research in management studies. Qualitative Research in Organizations and Management: An International Journal, 13: 183–195.
Woro AW, Ecometriks LLC (2009). System and method for identifying the solar potential of rooftops. U.S. Patent 7,500,391.
Zalewski L, Lassue S, Duthoit B, Butez M (2002). Study of solar walls—Validating a simulation model. Building and Environment, 37: 109–121.
Zhao D, McCoy AP, Agee P, Mo Y, Reichard G, Paige F (2018). Time effects of green buildings on energy use for low-income households: A longitudinal study in the United States. Sustainable Cities and Society, 40: 559–568.
Author information
Authors and Affiliations
Corresponding author
Electronic Supplementary Material
Rights and permissions
About this article
Cite this article
Li, H.X., Zhang, Y., Edwards, D. et al. Improving the energy production of roof-top solar PV systems through roof design. Build. Simul. 13, 475–487 (2020). https://doi.org/10.1007/s12273-019-0585-6
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12273-019-0585-6