NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, operated by the Alliance for Sustainable Energy, LLC.

Distributed Wind Diffusion 

Model Overview

SOLAR 2014 Conference

Robert Preus, Easan Drury, Ben 

Sigrin, and Michael Gleason 

San Francisco, California

July 8, 2014

NREL/PR-5000-62341
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Data Presented Are Samples Only

• This presentation includes sample graphs and 

tables and all data included are for purposes 

of illustrating input or output data type. 

• The Distributed Wind Market Diffusion 

Model has not been confirmed to produce 

reliable data and not all examples are from 

the same model input set. 
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Purpose/Background 

• Simulate distributed wind (DW) generator 

demand through 2050; simulates customer 

purchase decision 

• Explore market impacts of: 

o DW installed cost changes 

o DW generator performance changes

o DW energy policy and incentive changes

o Changes to electricity rates and rate structure 

o Changes in financing options

o Other factors.
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Modeling Distributed Wind Diffusion

(1) Simulate the DW energy generation profiles for a range of 

turbine sizes and heights (12 sizes from 2.5 to 3,000 kW)

(2) Characterize the electricity load and on-site wind power 

potential for multiple market segments (residential, 

commercial, and industrial) 

(3) Represent siting exclusions and limitations by location for 

each market segment 

(4) Calculate the distributed wind economics for each market 

segment and location 

(5) Calculate DW power diffusion based on wind economics and 

historical DW deployment. 

Basic model representation approach is to: 
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Modeling Distributed Wind Diffusion

Distributed wind turbine size and hub height matrix

Turbine Rated 

Power (kW) h1 (m) h2 (m) h3 (m) h4 (m)

2.5 30

5 30 40

10 30 40 50

20 30 40 50

50 30 40 50

100 40 50

250 50

500 50 80

750 50 80

1000 80

1500 80

3000 80

• We will add a 20-m hub height option for 2.5-kW turbines

• Other height options will be considered and balanced against the added computation required.
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Wind Resource Data

• NREL recently received a data set from AWS 

Truepower with 80-, 50-, and 30-meter data for the 

United States including Alaska and Hawaii. 

• The model will be modified to calculate shear values 

from the 50- and 30-meter data to produce wind 

speed estimates at 40 and 20 meters. 
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Performance

• Turbine performance (kWh/kWrating /year) is modeled 

on a unit basis using generic power curves derived 

from a variety of current turbines. 

• The family of generic curves was created assuming 

an array of values for turbine efficiency and specific 

swept area (m2/kWrating).

• Improvements in wind turbine performance are 

modeled by using a combination of increased area 

and efficiency.
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Performance

Large improvements are expected
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Performance – Capacity Factor Supply Curve

This graph represents the total load that could be supplied by distributed wind if built 

out to include all on-site load that has a capacity factor (CF) above the labeled value 

(i.e., at CF > 15% 100 GW). A similar graph with future power curves would show more 

available capacity. 

This graph generated by the 

model, illustrates the customer 

load available and only 

represents the continental 

United States. At this point, the 

primary purpose is looking for 

model output anomalies. 
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Optimum Turbine Size/Hub-Height Combination

Likely need 

to add 

height

restraints to 

get more 

realistic 

results for 

small wind
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Diffusion – Past Work

Maximum market share as a 

function of payback time from 

referenced studies. NREL is 

currently adding new 

relationships based on a survey 

of 790 photovoltaic owners. 

Typical annual and cumulative 

adoption rates simulated using 

the Bass Diffusion model 
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Development Before Simulating Market Trends

Next steps include:

• Importing improved wind data set from AWS Truepower

o Covers Alaska and Hawaii

o 30-m wind speed data set and 20-m calculation

• Improving representation of end-use electricity demand, 

rates, and rate structure 

• Analyzing potential performance and cost improvements 

for small wind 

• Reviewing if the model is over-predicting the tall tower 

selection 

• Reviewing the exclusions parameter settings 

• Adding leasing to financing options.
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What Questions the Model Can Address

• What is the potential market size for distributed 

wind with current economic conditions? 

• How large can the DW market grow with a range 

of performance and cost improvements?

• How much can reducing soft costs and other 

barriers improve the market? 

• How much impact will incentives have and 

which ones are most effective? 

• What is the impact of more attractive financing 

options? 
Robert Preus

Robert.preus@nrel.gov