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.

Interest in PV for Seattle

• Black & Veatch Renewable Energy group

• Personal interest in sustainability

• Considering PV for my roof

Image courtesy of

Presentation Outline

• Project Objectives & Timeline

• PV feasibility in Seattle

• Workflow for GIS-based Estimate of Capacity

• Questions

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

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

How Photovoltaic Systems Work

Image: Clean Energy Associates

• 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.

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

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

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 SalmonSource: Washington Economic Steering Committee and the Climate Leadership Initiative Institute for a Sustainable Environment

Estimating PV Production Capacity

Estimating PV Production Capacity

Airborne LiDAR Basics

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

Available LiDAR Data

Puget Sound LiDAR Consortium• Flown in 2000 & 2002• Nominal 1 pulse per m2

• Bare Earth and Top Surface DEMs: 6ft res• All-Returns ASCII files

Source: Puget Sound LiDAR Consortium.

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.

Hillshade derived from KC DSM nodes

Estimating PV Production Capacity

Extraction of Buildings from LiDAR Data

Lots of research over the past 10 years1) 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…

Building Extraction Algorithms

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

Some LiDAR Software with Feature Extraction Capabilities

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

Estimating PV Production Capacity

Goals for 3D Urban Model

• Successful segmentation of features

• Realistic modeling of rooftop geometry

• Accurate representation of tree canopy height

• Accurate representation of terrain

Estimating PV Production Capacity

Anlaysis of 3D Urban Model

Easier, static

• Rooftop Size

• Rooftop Aspect

• Rooftop Slope

Anlaysis of 3D Urban Model

• More Difficult, temporal in nature

–Rooftop Shading

–Rooftop Insolation

Estimating PV Production Capacity

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

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

Questions