Published in Issue 2018-11-09
How to Cite
Mansouri Kouhestani, F., Byrne, J., Johnson, D., Spencer, L., Hazendonk, P., & Brown, B. (2018). Evaluating solar energy technical and economic potential on rooftops in an urban setting: the city of Lethbridge, Canada. International Journal of Energy and Environmental Engineering, 10(1 (March 2019). https://doi.org/10.1007/s40095-018-0289-1
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Abstract
Abstract Solar energy deployment is gaining greater attention as a sustainable source of energy that could alleviate aspects of the current climate crisis. Knowledge of the characteristics and economics of the solar electricity sector is required to integrate it in the energy generation and utilization mix. Unlike energy generation from fossil fuels, renewable energy sources have relatively low geographic density and are spread unevenly over large areas. Therefore, especially in cities, where space has greater value and opportunity costs, finding suitable spaces for implementing solar systems are essential to promote the use of solar technologies. Using remote-sensing data, the intricate topography of cities can be modelled, and insolation incident at each location can be estimated. A multi-criteria approach based on geographic information systems (GIS) and light detection and ranging (LiDAR) is used in this research to estimate rooftop photovoltaic electricity potential of buildings in an urban environment, the city of Lethbridge. An economic assessment is conducted utilizing present market prices to determine economically attractive rooftop PV systems. The total rooftop photovoltaic (PV) electricity potential is evaluated and compared with the local electricity demand. Effective expansion of solar power systems in the city is achieved by determining the geographic distribution of the best locations for exploiting the systems. This study estimates that the rooftop PV electricity generation potential of the city of Lethbridge is approximately 301 ± 29 (SD) GWh annually (almost 38% of its annual electricity consumption in 2016), and about 96% of the recognized potential rooftop PV systems are economically feasible. The results can assist in making informed policy decisions about investment in deployment of renewable energy generation.Keywords
- GIS,
- LiDAR,
- NPV,
- Rooftop photovoltaic potential,
- Suitable rooftop areas,
- Economic assessment
References
- van der Hoeven, M.: Energy and climate change—world energy outlook special report. Int. Energy Agency (2015)
- Mueller et al. (2016) International Energy Agency
- Appavou, F., Brown, A., Epp, B., Leidreiter, A., Lins, C., Murdock, H.E., Musolino, E., Petrichenko, K., Farrell, T.C., Krader, T.T.: Renewables 2017 global status report. In. Tech. Rep., Renewable Energy Policy Network for the 21st Century (REN21) (2017)
- IRENA: Renewable Energy in Cities. In. International Renewable Energy Agency (IRENA), Abu Dhabi.
- www.irena.org
- (2016)
- Castellanos et al. (2017) Rooftop solar photovoltaic potential in cities: how scalable are assessment approaches? 12(12) https://doi.org/10.1088/1748-9326/aa7857
- Gooding et al. (2013) Solar City indicator: a methodology to predict city level PV installed capacity by combining physical capacity and socio-economic factors (pp. 325-335) https://doi.org/10.1016/j.solener.2013.06.027
- Kammen and Sunter (2016) City-integrated renewable energy for urban sustainability 352(6288) (pp. 922-928) https://doi.org/10.1126/science.aad9302
- Gagnon, P., Margolis, R., Melius, J., Phillips, C., Elmore, R.: Rooftop Solar Photovoltaic Technical Potential in the United States. A Detailed Assessment. National Renewable Energy Lab. (NREL), Golden, CO, USA (2016)
- Strupeit and Palm (2016) Overcoming barriers to renewable energy diffusion: business models for customer-sited solar photovoltaics in Japan, Germany and the United States (pp. 124-136) https://doi.org/10.1016/j.jclepro.2015.06.120
- Izquierdo et al. (2008) A method for estimating the geographical distribution of the available roof surface area for large-scale photovoltaic energy-potential evaluations 82(10) (pp. 929-939) https://doi.org/10.1016/j.solener.2008.03.007
- Mirmasoudi et al. (2018) A novel time-effective model for daily distributed solar radiation estimates across variable terrain 9(4) (pp. 383-398) https://doi.org/10.1007/s40095-018-0279-3
- Kanters and Davidsson (2014) Mutual shading of PV modules on flat roofs: a parametric study (pp. 1706-1715) https://doi.org/10.1016/j.egypro.2014.10.160
- Ordóñez et al. (2010) Analysis of the photovoltaic solar energy capacity of residential rooftops in Andalusia (Spain) 14(7) (pp. 2122-2130) https://doi.org/10.1016/j.rser.2010.01.001
- International Energy Agency (IEA): Energy Technology Perspectives, Annex H- Rooftop Solar PV Potential in Cities. International Energy Agency.
- www.iea.org
- (2016)
- Denholm, P., Margolis, R.: Supply Curves for Rooftop Solar PV-Generated Electricity for the United States. National Renewable Energy Lab (NREL) (2008)
- Anderson, K.H., Coddington, M.H., Kroposki, B.D.: Assessing technical potential for city PV deployment using NREL’s in my backyard tool. In: Photovoltaic Specialists Conference (PVSC), 2010 35th IEEE 2010, pp. 001085–001090
- (IEEE)
- Verso et al. (2015) GIS-based method to evaluate the photovoltaic potential in the urban environments: the particular case of Miraflores de la Sierra (pp. 236-245) https://doi.org/10.1016/j.solener.2015.04.018
- Martín et al. (2015) Applying LIDAR datasets and GIS based model to evaluate solar potential over roofs: a review 3(3) (pp. 326-343) https://doi.org/10.3934/energy.2015.3.326
- Singh and Banerjee (2015) Estimation of rooftop solar photovoltaic potential of a city (pp. 589-602) https://doi.org/10.1016/j.solener.2015.03.016
- Jakubiec and Reinhart (2013) A method for predicting city-wide electricity gains from photovoltaic panels based on LiDAR and GIS data combined with hourly Daysim simulations (pp. 127-143) https://doi.org/10.1016/j.solener.2013.03.022
- Huang et al. (2015) Estimating roof solar energy potential in the downtown area using a gpu-accelerated solar radiation model and airborne lidar data 7(12) (pp. 17212-17233) https://doi.org/10.3390/rs71215877
- Jochem et al. (2009) Automatic roof plane detection and analysis in airborne lidar point clouds for solar potential assessment 9(7) (pp. 5241-5262) https://doi.org/10.3390/s90705241
- Boz et al. (2015) An automated model for rooftop PV systems assessment in ArcGIS using LIDAR 3(3) (pp. 401-420) https://doi.org/10.3934/energy.2015.3.401
- Fath et al. (2015) A method for predicting the economic potential of (building-integrated) photovoltaics in urban areas based on hourly Radiance simulations (pp. 357-370) https://doi.org/10.1016/j.solener.2015.03.023
- Santosa et al. (2014) Applications of solar mapping in the urban environment [J] (pp. 48-57) https://doi.org/10.1016/j.apgeog.2014.03.008
- Redweik et al. (2013) Solar energy potential on roofs and facades in an urban landscape (pp. 332-341) https://doi.org/10.1016/j.solener.2013.08.036
- Tooke et al. (2012) Integrated irradiance modelling in the urban environment based on remotely sensed data 86(10) (pp. 2923-2934) https://doi.org/10.1016/j.solener.2012.06.026
- Canadian Solar Industries Association (CanSIA): Roadmap 2020 - Powering Canada’s Future with Solar Electricity. Canadian Solar Industries Association (CanSIA).
- www.cansia.ca
- People Power Planet Partnership: Alberta Renewable Energy and Community Energy Overview. People Power Planet.
- www.peoplepowerplanet.ca
- (2018)
- Natural Resources Canada: Photovoltaic and solar resource maps - photovoltaic potential and insolation dataset. Natural Resources Canada.
- www.nrcan.gc.ca
- (2017)
- City of Lethbridge: About Lethbridge. City of Lethbridge. http://
- www.lethbridge.ca/Things-To-Do/About-Lethbridge/Pages/default.aspx
- . Accessed Jan 2017
- City of Lethbridge OpenData CATALOGUE: building footprints.
- http://opendata.lethbridge.ca/datasets/7d32446fb333488598268bd4bc0c830d_0
- . Accessed Jan 2017
- City of Lethbridge: census results 2016. City of Lethbridge.
- http://www.lethbridge.ca/City-Government/Census/Pages/Census-Results-2015.aspx
- . Accessed Jan 2017
- Esri Canada Ed: Canada Boundary. ArcGIS.
- https://www.arcgis.com/home/item.html?id=dcbcdf86939548af81efbd2d732336db
- (2013). Accessed Feb 2017
- City of Lethbridge OpenData CATALOGUE: City Boundary.
- http://opendata.lethbridge.ca/datasets/3d37b1a4840d4eac88bb89a49672c2e7_1
- . Accessed Jan 2017
- Esri: LAS dataset considerations. ArcGIS Help 10.1.
- http://resources.arcgis.com/en/help/main/10.1/index.html#/LAS_dataset_considerations/015w00000069000000/ESRI_SECTION1_104F85DA2EBC405E9EEBBFF61208759E/
- (2013). Accessed Feb 2017
- Esri: Creating raster DEMs and DSMs from large lidar point collections. ArcGIS for Desktop.
- http://desktop.arcgis.com/en/arcmap/10.3/manage-data/las-dataset/lidar-solutions-creating-raster-dems-and-dsms-from-large-lidar-point-collections.htm
- . Accessed Jan 2017
- Chaves and Bahill (2010) Locating sites for photovoltaic solar panels 13(4) (pp. 24-27)
- Esri: How Slope works. ArcGIS Resources.
- http://resources.arcgis.com/en/help/main/10.2/index.html#/How_Slope_works/009z000000vz000000/
- (2014). Accessed Feb 2017
- McKenney et al. (2008) Spatial insolation models for photovoltaic energy in Canada 82(11) (pp. 1049-1061) https://doi.org/10.1016/j.solener.2008.04.008
- Esri: Hillshade. ArcGIS Desktop.
- http://pro.arcgis.com/en/pro-app/tool-reference/3d-analyst/hillshade.htm
- . Accessed Feb 2017
- Solar Choice: 1.5 kW solar PV systems, Pricing, outputs and payback. Solar Choice,
- https://www.solarchoice.net.au/blog/1-5kw-solar-pv-systems-price-output-payback
- (2016). Accessed Feb 2017
- Camargo et al. (2015) Spatio-temporal modeling of roof-top photovoltaic panels for improved technical potential assessment and electricity peak load offsetting at the municipal scale (pp. 58-69) https://doi.org/10.1016/j.compenvurbsys.2015.03.002
- Esri: How raster calculator works. ArcGIS for Desktop.
- http://desktop.arcgis.com/en/arcmap/10.3/tools/spatial-analyst-toolbox/how-raster-calculator-works.htm
- . Accessed Feb 2017
- Esri: Area Solar Radiation. ArcGIS for Desktop.
- http://desktop.arcgis.com/en/arcmap/10.3/tools/spatial-analyst-toolbox/area-solar-radiation.htm
- . Accessed Mar 2017
- Ruiz-Arias et al. (2009) A comparative analysis of DEM-based models to estimate the solar radiation in mountainous terrain 23(8) (pp. 1049-1076) https://doi.org/10.1080/13658810802022806
- Duffie, J.A., Beckman, W.A.: Solar Engineering of Thermal Processes. Wiley (2013)
- Fu and Rich (2002) A geometric solar radiation model with applications in agriculture and forestry 37(1) (pp. 25-35) https://doi.org/10.1016/S0168-1699(02)00115-1
- Besharat et al. (2013) Empirical models for estimating global solar radiation: a review and case study (pp. 798-821) https://doi.org/10.1016/j.rser.2012.12.043
- Despotovic et al. (2015) Review and statistical analysis of different global solar radiation sunshine models (pp. 1869-1880) https://doi.org/10.1016/j.rser.2015.08.035
- Wirth, H.: Recent Facts about Photovoltaics in Germany. Fraunhofer Institute for Solar Energy (ISE), Freiburg (2016)
- Philipps, S., Warmuth, W.: Photovoltaics Report. Fraunhofer Institute for Solar Energy Systems (ISE), Freiburg (2017)
- Schmalensee (2015) Massachusetts Institute of Technology
- Ropp, M., Begovic, M., Rohatgi, A.: Determination of the curvature derating factor for the Georgia Tech Aquatic Center photovoltaic array. In: Photovoltaic Specialists Conference, 1997, Conference Record of the Twenty-Sixth IEEE 1997, pp. 1297–1300
- (IEEE)
- Vignola, F., Mavromatakis, F., Krumsick, J.: Performance of PV inverters. In: Proc. of the 37th ASES Annual Conference, San Diego, CA (2008)
- Pelland, S., McKenney, D.W., Poissant, Y., Morris, R., Lawrence, K., Campbell, K., Papadopol, P.: The development of photovoltaic resource maps for Canada. In: Proc. 31st Annual Conference of the Solar Energy Society of Canada (SESCI) (2006)
- Reich et al. (2012) Performance ratio revisited: is PR > 90% realistic? 20(6) (pp. 717-726) https://doi.org/10.1002/pip.1219
- Pelland, S., Poissant, Y.: An evaluation of the potential of building integrated photovoltaics in Canada. In: Proceedings of the SESCI 2006 Conference (2006)
- MacKinnon, J., Mintz, J.: Putting the Alberta budget on a new trajectory. University of Calgary, the School of Public Policy Publications (2017)
- Statistics Canada: Consumer Price Index, by province (Alberta). Statistics Canada.
- https://www.statcan.gc.ca/tables-tableaux/sum-som/l01/cst01/econ09j-eng.htm
- (2018). Accessed Mar 2018
- Government of Alberta: Electricity price protection. Alberta.
- https://www.alberta.ca/electricity-price-protection.aspx
- . Accessed Mar 2018
- Alberta Electric System Operator (aeso): Transmission costs. Alberta Electric System Operator.
- https://www.aeso.ca/grid/transmission-costs/
- (2016). Accessed Mar 2018
- Kuby Renewable Energy Ltd: The cost of solar panels. Kuby Renewable Energy Ltd.
- https://kubyenergy.ca/blog/the-cost-of-solar-panels
- . Accessed Mar 2018
- Alberta Government: Rebates to help Albertans tap solar resources. Alberta.
- https://www.alberta.ca/release.cfm?xID=463610A3269CE-0D2C-C140-6E391B3112A56664
- (2017). Accessed Mar 2018
- Poissant, Y., Baldus-Jeursen, C., CanmetENERGY, Natural Resources Canada, Bateman, P., Canadian Solar Industries Association: National Survey Report of PV Power Applications in Canada—2016. International Energy Agency (2017)
- Thevenard and Pelland (2013) Estimating the uncertainty in long-term photovoltaic yield predictions (pp. 432-445) https://doi.org/10.1016/j.solener.2011.05.006
- Environment Lethbridge: Lethbridge State of the Environment 2017. Environment Lethbridge Council.
- www.environmentlethbridge.ca
- (2017)
- Alberta Government: Climate Leadership Plan Progress Report 2016-17. Alberta Government (2017)
10.1007/s40095-018-0289-1