Solar Energy Resources

Kevin Bell SLC

Bert Granberg AGRC

Modeling Salt Lake City’s

1

Project Goals

• Quantify the Solar Energy Resources at Relevant Scales– City held properties– City-wide– Residential & business properties

• Make results accessible to all

2

What’s important

• #1 Solar Radiation on Existing Surfaces

– Flush mount ‘active’ solar systems• Heating • PV electrical generation

– Passive heating/cooling analysis• Tree placement• Heat island effect analysis

3

What’s important• #2 Sunlit Hours for Existing Surfaces

– Angled rack mount ‘active’ solar• Heating • PV electrical generation

– Passive uses• H20 planning?

• Gardening?

4

Project Requirements

• Digital model of existing terrain and surfaces– LiDAR digital terrain model of study area

• Mathematical model of the Sun’s path– Nat’l Renewable Energy Labs (NREL)

• Integrating Platform– ESRI ArcGIS

5

LiDAR = Light Detecting And Ranging • Pulsed laser transmission

• Optical sensor

• Like GPS & Radar, uses time as a surrogate for space to measure distance from a known location

6

Using LiDAR to gather terrain data

1. Mount LiDAR sensor on airplane

2. Synchronize LiDAR sensor with high-precision GPS equipment (to get instantaneous geographic position of sensor)

3. Measure vertical distance from plane to surface features (get M for each X,Y)

4. Derive large set of elevation points with 3D geographic coordinates

• Usually 1-2 meters spacing of measurements

7

4212

4220

Raster Terrain Model• Concept: graph paper model of an area• Each cell in the array carries and elevation value

8

Raster Terrain Model• in GIS, colored by height value

9

Raster Terrain Model• in GIS• extruded by height• colored by height value

10

Solar ModelingAnimation

Salt Lake Library

March 21

8:00 AM

11

Solar ModelingAnimation

Salt Lake Library

March 21

9:00 AM

11

Solar ModelingAnimation

Salt Lake Library

March 21

10:00 AM

11

Solar ModelingAnimation

Salt Lake Library

March 21

11:00 AM

11

Solar ModelingAnimation

Salt Lake Library

March 21

12:00 PM

11

Solar ModelingAnimation

Salt Lake Library

March 21

1:00 PM

11

Solar ModelingAnimation

Salt Lake Library

March 21

2:00 PM

11

Solar ModelingAnimation

Salt Lake Library

March 21

3:00 PM

11

Solar ModelingAnimation

Salt Lake Library

March 21

4:00 PM

11

Solar ModelingAnimation

Salt Lake Library

March 21

5:00 PM

11

Solar ModelingAnimation

Salt Lake Library

March 21

6:00 PM

11

Solar ModelingAnimation

Salt Lake Library

March 21

7:00 PM

11

Solar Radiation Calculation

ΣFor given dates/times

- Is Surface Sunlit?

- Factor in relationship between Terrain Slope & Sun Position

optimal instantaneous angle = 90 degrees optimal fixed angle = latitude (~ 40 degrees in SLC)

12

192

4.5

237

7.2

Completed Raster Model, each cell carries monthly averages

• Sunlit hours • Watt hours

400 million cells x 24 data values10 billion data values

+ implied x,y coords

40000

10000

13

Solar Modeling:

• Huge Computational Costs at 1 meter

• Divide and Conquer Approach

• How big a tile to process in isolation?

• How large a buffer to process around the tile

• Look at neighboring tile heights for tall shadow casters

14

Divide and Conquer Tiles•Red larger buffers•Yellow medium buffers•Blue smaller buffers

15

Raster-based Solar Radiation Results Map Web Service (For Mixed Use Neighborhood)

16

Performance Issues

• Raster Datasets are Sequentially Stored data structures– Line scans are fast (rendering)

– Full dataset analysis/summaries are fast (citywide)

– Neighborhood (spatial) queries are slooooow

• And we have 24 of them to deal with– Two measures x 12 months

• Solution….

17

Point-based output sample

July Sunlit Duration,Salt Lake Library Building.

Neighborhood Query Performance Solution:

Store all 24 raster values for a given raster cell in a separate vector based data structure as a simple point feature

18

Solar Radiation Results Spatial Query Web Service (Aggregated to point shapefile)

• Map image service (based on raster output)

• Spatial Query Web services (JSON, based on vector pts)

input: polygon x,y coordinates

production threshold outputs:

monthly sunlit hours (Duration)monthly watt hours (Radiation)area above production threshold

19

Turn Web Services Over to Web Designers

Map Services

Spatial QueryWeb Services

Web App

20

Putting it all Together: Coming Soon…Product

bgranberg@utah.gov