1. Kingston, MA Shadow Flicker Study Elizabeth King Wind Analyst Chester Harvey GIS Specialist 256 Farrell Farm Rd. Norwich, VT 05055 Ph: 802.649.1511

2. Goals 1. Estimate shadow flicker time by location 2. Estimate curtailment time required to meet example shadow flicker thresholds 3. Document areas with line-of-sight to turbine(s)

3. Site Overview 5 Wind Turbines 1083 Receptors within 1.6 km of turbines

4. Methodology 1. Desktop estimate of shadow flicker exposure – Shadow flicker modeled using WindPRO Incorporates GIS terrain model, daily sun paths based on latitude, local weather data and wind data – Receptors identified using aerial images & GIS data – No tree or building obstacles are accounted for 2. Field documentation of line-of-sight – Assessed by car from public streets

5. Flicker Modeling Theoretical Worst Case – Maximum possible shadow hours for a given location – Sun always shining; wind turbines always operating – Is a step in process for deriving realistic case estimates Realistic Case – Incorporates sunshine probability and likely wind turbine operational hours Sunshine data, 61 years – Boston, MA (National Climatic Data Center) Wind data, 1 year (July 05 – July 06) – Kingston, MA (UMass Amherst)

6. Receptors 20 meters wide x 10 meters tall – Intended to simulate the façade of a house Each receptor modeled so that it faces perpendicular to each wind turbine in each iteration of analysis (Greenhouse Mode)

7. Receptors

8. 10 meters tall 20 meters wide Receptor area facing perpendicular to direct line to turbine Receptor point at bottom-center of modeled receptor area Shadow modeled on receptor area 1.5 m figure for scale

9. WindPRO Inputs 9

10. 10

11. WindPRO Inputs 11

12. WindPRO Inputs 12

13. Isolines show shadow flicker estimates derived from a realistic case model using a 10 m grid resolution Hours per Year at 1.5 meters above ground level

14. WindPRO Report

16. Calendar Graphs Receptor A Receptor B

17. WindPRO Report

18. Flicker Results Realistic Case More Than 10 Hours per Year of Flicker More Than 30 Hours per Year of Flicker More Than 50 Hours per Year of Flicker Number of Receptors Affected 1895531 Number of Existing Residential Receptors Affected 1213824

19. Line-of-Sight Survey Assesses line-of-sight to each turbine from public streets within the study area Accounts for trees and buildings that block line-of-sight to turbines Line-of-sight results are not incorporated into modeling results

21. Photo 27

22. Curtailment Analysis Only receptors for existing residential structures are included Accounts for coincident flicker across multiple receptors

23. Curtailment Results Realistic CaseTheoretical Worst Case Estimated Curtailment Required for 10 hrs of Flicker Per Year (h/yr) Estimated Curtailment Required for Maximum 30 hrs of Flicker Per Year (h/yr) NFF West (Gamesa 1) 94286 NFF Southeast (Gamesa 2) 47140 NFF North (Gamesa 3) 107326 KWI (Hyundai) 126366 MBTA (Northern Power) 614