10.1007/s40095-018-0289-1

Evaluating solar energy technical and economic potential on rooftops in an urban setting: the city of Lethbridge, Canada

  1. University of Lethbridge, Lethbridge, AB, T1K 6T5, CA
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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

  1. van der Hoeven, M.: Energy and climate change—world energy outlook special report. Int. Energy Agency (2015)
  2. Mueller et al. (2016) International Energy Agency
  3. 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)
  4. IRENA: Renewable Energy in Cities. In. International Renewable Energy Agency (IRENA), Abu Dhabi.
  5. www.irena.org
  6. (2016)
  7. 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
  8. 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
  9. Kammen and Sunter (2016) City-integrated renewable energy for urban sustainability 352(6288) (pp. 922-928) https://doi.org/10.1126/science.aad9302
  10. 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)
  11. 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
  12. 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
  13. 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
  14. 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
  15. 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
  16. International Energy Agency (IEA): Energy Technology Perspectives, Annex H- Rooftop Solar PV Potential in Cities. International Energy Agency.
  17. www.iea.org
  18. (2016)
  19. Denholm, P., Margolis, R.: Supply Curves for Rooftop Solar PV-Generated Electricity for the United States. National Renewable Energy Lab (NREL) (2008)
  20. 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
  21. (IEEE)
  22. 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
  23. 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
  24. 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
  25. 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
  26. 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
  27. 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
  28. 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
  29. 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
  30. 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
  31. 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
  32. 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
  33. Canadian Solar Industries Association (CanSIA): Roadmap 2020 - Powering Canada’s Future with Solar Electricity. ​Canadian Solar Industries Association (CanSIA).
  34. www.cansia.ca
  35. People Power Planet Partnership: Alberta Renewable Energy and Community Energy Overview. People Power Planet.
  36. www.peoplepowerplanet.ca
  37. (2018)
  38. Natural Resources Canada: Photovoltaic and solar resource maps -​ photovoltaic potential and insolation dataset. Natural Resources Canada.
  39. www.nrcan.gc.ca
  40. (2017)
  41. City of Lethbridge: About Lethbridge. City of Lethbridge. http://
  42. www.lethbridge.ca/Things-To-Do/About-Lethbridge/Pages/default.aspx
  43. . Accessed Jan 2017
  44. City of Lethbridge OpenData CATALOGUE: building footprints.
  45. http://opendata.lethbridge.ca/datasets/7d32446fb333488598268bd4bc0c830d_0
  46. . Accessed Jan 2017
  47. City of Lethbridge: census results 2016. City of Lethbridge.
  48. http://www.lethbridge.ca/City-Government/Census/Pages/Census-Results-2015.aspx
  49. . Accessed Jan 2017
  50. Esri Canada Ed: Canada Boundary. ArcGIS.
  51. https://www.arcgis.com/home/item.html?id=dcbcdf86939548af81efbd2d732336db
  52. (2013). Accessed Feb 2017
  53. City of Lethbridge OpenData CATALOGUE: City Boundary.
  54. http://opendata.lethbridge.ca/datasets/3d37b1a4840d4eac88bb89a49672c2e7_1
  55. . Accessed Jan 2017
  56. Esri: LAS dataset considerations. ArcGIS Help 10.1.
  57. http://resources.arcgis.com/en/help/main/10.1/index.html#/LAS_dataset_considerations/015w00000069000000/ESRI_SECTION1_104F85DA2EBC405E9EEBBFF61208759E/
  58. (2013). Accessed Feb 2017
  59. Esri: Creating raster DEMs and DSMs from large lidar point collections. ArcGIS for Desktop.
  60. 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
  61. . Accessed Jan 2017
  62. Chaves and Bahill (2010) Locating sites for photovoltaic solar panels 13(4) (pp. 24-27)
  63. Esri: How Slope works. ArcGIS Resources.
  64. http://resources.arcgis.com/en/help/main/10.2/index.html#/How_Slope_works/009z000000vz000000/
  65. (2014). Accessed Feb 2017
  66. 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
  67. Esri: Hillshade. ArcGIS Desktop.
  68. http://pro.arcgis.com/en/pro-app/tool-reference/3d-analyst/hillshade.htm
  69. . Accessed Feb 2017
  70. Solar Choice: 1.5 kW solar PV systems, Pricing, outputs and payback. Solar Choice,
  71. https://www.solarchoice.net.au/blog/1-5kw-solar-pv-systems-price-output-payback
  72. (2016). Accessed Feb 2017
  73. 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
  74. Esri: How raster calculator works. ArcGIS for Desktop.
  75. http://desktop.arcgis.com/en/arcmap/10.3/tools/spatial-analyst-toolbox/how-raster-calculator-works.htm
  76. . Accessed Feb 2017
  77. Esri: Area Solar Radiation. ArcGIS for Desktop.
  78. http://desktop.arcgis.com/en/arcmap/10.3/tools/spatial-analyst-toolbox/area-solar-radiation.htm
  79. . Accessed Mar 2017
  80. 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
  81. Duffie, J.A., Beckman, W.A.: Solar Engineering of Thermal Processes. Wiley (2013)
  82. 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
  83. 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
  84. 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
  85. Wirth, H.: Recent Facts about Photovoltaics in Germany. Fraunhofer Institute for Solar Energy (ISE), Freiburg (2016)
  86. Philipps, S., Warmuth, W.: Photovoltaics Report. Fraunhofer Institute for Solar Energy Systems (ISE), Freiburg (2017)
  87. Schmalensee (2015) Massachusetts Institute of Technology
  88. 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
  89. (IEEE)
  90. Vignola, F., Mavromatakis, F., Krumsick, J.: Performance of PV inverters. In: Proc. of the 37th ASES Annual Conference, San Diego, CA (2008)
  91. 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)
  92. Reich et al. (2012) Performance ratio revisited: is PR > 90% realistic? 20(6) (pp. 717-726) https://doi.org/10.1002/pip.1219
  93. Pelland, S., Poissant, Y.: An evaluation of the potential of building integrated photovoltaics in Canada. In: Proceedings of the SESCI 2006 Conference (2006)
  94. MacKinnon, J., Mintz, J.: Putting the Alberta budget on a new trajectory. University of Calgary, the School of Public Policy Publications (2017)
  95. Statistics Canada: Consumer Price Index, by province (Alberta). Statistics Canada.
  96. https://www.statcan.gc.ca/tables-tableaux/sum-som/l01/cst01/econ09j-eng.htm
  97. (2018). Accessed Mar 2018
  98. Government of Alberta: Electricity price protection. Alberta.
  99. https://www.alberta.ca/electricity-price-protection.aspx
  100. . Accessed Mar 2018
  101. Alberta Electric System Operator (aeso): Transmission costs. ​Alberta Electric System Operator.
  102. https://www.aeso.ca/grid/transmission-costs/
  103. (2016). Accessed Mar 2018
  104. Kuby Renewable Energy Ltd: The cost of solar panels. ​Kuby Renewable Energy Ltd.​
  105. https://kubyenergy.ca/blog/the-cost-of-solar-panels
  106. . Accessed Mar 2018
  107. Alberta Government: Rebates to help Albertans tap solar resources. Alberta.
  108. https://www.alberta.ca/release.cfm?xID=463610A3269CE-0D2C-C140-6E391B3112A56664
  109. (2017). Accessed Mar 2018
  110. 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)
  111. 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
  112. Environment Lethbridge: Lethbridge State of the Environment 2017. Environment Lethbridge Council.
  113. www.environmentlethbridge.ca
  114. (2017)
  115. Alberta Government: Climate Leadership Plan Progress Report 2016-17. Alberta Government (2017)