Transcript Methodology and Results from Shadow Flicker Modeling in Kingston, MA

Kingston, MA
Shadow Flicker Study
Elizabeth King
Wind Analyst
Chester Harvey
GIS Specialist
256 Farrell Farm Rd.
Norwich, VT 05055
Ph: 802.649.1511
Goals
1.
2.
3.
Estimate shadow flicker time
by location
Estimate curtailment time required to meet
example shadow flicker thresholds
Document areas with
line-of-sight to turbine(s)
Site Overview
•
5 Wind Turbines
•
1083 Receptors within 1.6 km of turbines
Methodology
1.
Desktop estimate of shadow flicker exposure
–
Shadow flicker modeled using WindPRO
•
2.
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
Field documentation of line-of-sight
–
Assessed by car from public streets
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)
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)
Receptors
Receptors
10
meters
tall
Receptor area facing
perpendicular to
direct line to turbine
Shadow modeled
on receptor area
1.5 m figure for scale
Receptor point at
bottom-center of
modeled receptor area
WindPRO Inputs
9
WindPRO Inputs
10
WindPRO Inputs
11
WindPRO Inputs
12
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
WindPRO Report
WindPRO Report
WindPRO Report
Calendar Graphs
Receptor A
Receptor B
WindPRO Report
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
189
55
31
Number of
Existing
Residential
Receptors
Affected
121
38
24
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
Photo 27
Curtailment Analysis
•
•
Only receptors for existing residential
structures are included
Accounts for coincident flicker across
multiple receptors
Curtailment Results
Realistic Case
Theoretical 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)
94
286
NFF Southeast
(Gamesa 2)
47
140
NFF North
(Gamesa 3)
107
326
KWI
(Hyundai)
126
366
MBTA
(Northern Power)
6
14