1. Estimating Rooftop Solar Electricity Potential in Seattle from LiDAR Data Ryan M. Liddell Faculty advisor: Dr. Joe Bishop Photo Copyright H Brothers Inc; used by permission.

3. Interest in PV for Seattle Black & Veatch Renewable Energy group Personal interest in sustainability Considering PV for my roof Image courtesy of

4. Presentation Outline Project Objectives & Timeline PV feasibility in Seattle Workflow for GIS-based Estimate of Capacity Questions

5. Project Objectives Examine feasibility of photovoltaic (PV) systems in Seattle Generate urban 3D model of Seattle Identify rooftops suitable for PV installations Estimate total solar electricity production capacity for the City of Seattle

6. Project Timeline Examine feasibility of PV in Seattle: Complete Generate urban 3D model: July-August Identify suitable rooftops: August Estimate total PV production capacity for the City of Seattle: September

7. How Photovoltaic Systems Work Image: Clean Energy Associates

8. Solar insolation –Latitude: Short winter days Long summer days –Local weather, especially cloud cover Temperature – cooler is more efficient Germany produced 6,200 GWh in 2009* Technical Feasibility of PV in Seattle *Source: "Development of Renewable Energy Sources in Germany 2009". Federal Ministry for Environment, Nature Conservation and Nuclear Safety. http://www.erneuerbare- energien.de/files/pdfs/allgemein/application/pdf/ee_in_deutschland_graf_tab_2009_en.pdf.

10. Economic Feasibility in Seattle Nearly 90% of electricity from hydropower –$$$ is 30% less than the national average –Winter High demand, lower supply City Light buys cheap electricity on market –Summer Low demand, high supply City light sells at high price on market Sources: Seattle City Light; U.S. Energy Information Administration Independent Statistics and Analysis

11. Economic Incentives –30% federal tax credit for PV system cost –No Washington sales tax –Washington State 6170 program: Purchases solar generated electricity Starts at 15¢ per kWh Up to 54¢ per kWh Max: $5000 per year –Net Metering through Seattle City Light

13. Potential Effects of Climate Change –Reduced snowpack –Peak stream flows earlier in year –Winter Decreased demand for electricity (heating) Increased supply of hydro power –Summer Increased demand (Air Conditioning) Decreased supply of hydro power –Changes in Water Management for Salmon Source: Washington Economic Steering Committee and the Climate Leadership Initiative Institute for a Sustainable Environment

14. Estimating PV Production Capacity

16. Airborne LiDAR Basics From: http://www.dot.state.oh.us/Divisions/ProdMgt/Aerial/Pages/LiDARBasicS.aspx

17. Available LiDAR Data Puget Sound LiDAR Consortium Flown in 2000 & 2002 Nominal 1 pulse per m 2 Bare Earth and Top Surface DEMs: 6ft res All-Returns ASCII files Source: Puget Sound LiDAR Consortium.

18. Available LiDAR Data King County GIS Digital Ground Model (DGM) TIN Digital Surface Model (DSM) TIN For both, nodes provide same level of control as ASCII point files. Intensity data Source: King County GIS Center.

19. Hillshade derived from KC DSM nodes

20. Estimating PV Production Capacity

21. Extraction of Buildings from LiDAR Data Lots of research over the past 10 years 1)Priestnall, et al. 2000. Extracting Urban Features from LiDAR Digital Surface Models. 2)Haithcoat, et al. 2001. Building Footprint Extraction and 3-D Reconstruction from LiDAR Data. 3)Elaksher and Bethel. 2002. Reconstructing 3D Buildings from LiDAR Data. 4)Rottensteiner. 2003. Automatic Generation of High-quality Building Models from LiDAR Data. 5)Vosselman, et al. 2005. The Utilization of Airborne Laser Scanning for Mapping. 6)Verma, et al. 2006. 3D Building Detection and Modeling from Aerial LiDAR Data. 7)Sampath and Shan. 2007. Building Boundary Tracing and Regularization from Airborne Lidar Point Clouds. 8)Q.-Y. Zhou and U. Neumann. 2008. Fast and Extensible Building Modeling from Airborne LiDAR Data. 9)Vu, et al. 2009. Multi-scale Solution for Building Extraction from LiDAR and Image Data. and many more…

22. Building Extraction Algorithms From: Q.-Y. Zhou and U. Neumann. Fast and Extensible Building Modeling from Airborne LiDAR Data. 2008.

23. Some LiDAR Software with Feature Extraction Capabilities

24. From: G. Zhou, et al. Urban 3D GIS From LiDAR and digital aerial images. 2003.

25. Estimating PV Production Capacity

26. Goals for 3D Urban Model Successful segmentation of features Realistic modeling of rooftop geometry Accurate representation of tree canopy height Accurate representation of terrain

27. Estimating PV Production Capacity

28. Anlaysis of 3D Urban Model Easier, static Rooftop Size Rooftop Aspect Rooftop Slope

29. Anlaysis of 3D Urban Model More Difficult, temporal in nature – Rooftop Shading – Rooftop Insolation

30. Estimating PV Production Capacity

31. Estimating PV Production Quantities of Suitable Rooftop Areas PV Module Performance Data Input from local PV contractors Advice from renewable energy experts at Black & Veatch

32. References 1)“2000-2005 Lower Puget Sound Projects”. Puget Sound LiDAR Consortium. Retrieved May 3, 2010. From http://pugetsoundlidar.ess.washington.edu/lidardata/restricted/projects/2000- 05lowerpugetsound.html 2)"Development of Renewable Energy Sources in Germany 2009". Federal Ministry for Environment, Nature Conservation and Nuclear Safety. http://www.erneuerbare- energien.de/files/pdfs/allgemein/application/pdf/ee_in_deutschland_graf_tab_2009_en.pdf. 3)“Fuel Mix: How Seattle City Light electricity is generated”. Seattle City Light. Retrieved May 3, 2010. From http://www.cityofseattle.net/light/FuelMix/ 4)“Impacts of Climate Change on Washington’s Economy: A Preliminary Assessment of Risks and Opportunities”. 2006. Washington Economic Steering Committee and the Climate Leadership Initiative Institute for a Sustainable Environment. Written for State of Washington Department of Ecology and Department of Community, Trade, and Economic Development. Retrieved June 5, 2010. From http://www.ecy.wa.gov/pubs/0701010.pdf 5)“LiDAR Basics”. Ohio Department of Transportation. Retrieved Juen 14, 2010. From http://www.dot.state.oh.us/Divisions/ProdMgt/Aerial/Pages/LiDARBasicS.aspx 6)“State Electricity Profiles” U.S. Energy Information Administration Independent Statistics and Analysis. Retrieved May 3, 2010. From http://www.eia.doe.gov/electricity/st_profiles/e_profiles_sum.html 7)Vu, et al. 2009. Multi-scale Solution for Building Extraction from LiDAR and Image Data. 8)G. Zhou, et al. 2003. Urban 3D GIS from LiDAR and Digital Aerial Images. Computers & Geosciences 30 (2004) 345-353. 9)Q.-Y. Zhou and U. Neumann. 2008. Fast and Extensible Building Modeling from Airborne LiDAR Data. Retrieved May 3, 2010. From http://graphics.usc.edu/~qianyizh/papers/modeling_gis.pdf

33. Questions