How to reduce risk

Presented by:

Matthew Hendrickson, Sr. Director Of Assessment

3TIER is Focused on Understanding the Fuel

» Founded in 1999

» Headquarters in Seattle, WA

» Offices in Panama, India, and

Australia

» Focused on renewable energy

information services

39,000 MW wind energy forecasting

7,400 MW hydropower forecasting

Extensive international wind & solar resource assessment

Pre-construction services

I. Spatial mapping

II. Climate variability analysis

III. Comprehensive net report

A. Spatial

B. Climate

C. Wake

D. Other losses

E. Uncertainty

What is Numerical Weather Prediction?

Understanding of

wind characteristics

Long-term variability

assessments

(up to 50 years)

Spatial wind maps

Global

Weather

Archive

1960-present

High

Resolution

Terrain, Soil,

and Vegetation

Data

OPTIONAL:

Onsite

Observations

INPUTS WRF ANALYSIS OUTPUTS

The Value of Higher Resolution Wind Mapping

8.0

7.0

6.0

5.0

5km resolution 1.5km resolution 500m resolution

Look at the two locations marked on each map…

Sweetwater Nearby Mountain

At 5km resolution = ~7.1m/s ~7.5m/s

At 1.5km resolution = ~6.9m/s ~7.7m/s

At 500m resolution = ~6.8m/s ~8.0m/s

The Value of High Resolution Wind Mapping

8.0

7.0

6.0

5.0

5km resolution 1.5km resolution 500m resolution

90m resolution

~9.0 m/s at mountain

. . . and understand the

spatial variability of the wind

resource, better than with

simple statistical

extrapolations and/or

interpolations of on-site

observations

Avoid Wind Holes!

Options for Understanding Long-term Variability

Using Nearby 3rd Party Station Data

Measure-Correlate-Predict

(MCP)

Traditional MCP

Measure-Correlate-Predict

✪ Reference

Site

Uses a statistical relationship

between on-site obs data and a

longer ‘reference’ site to

understand the variability of the

wind resource and determine a

long-term adjustment

ws=m*wsr+b

» Reference site needs to be a consistent, long-term time

series located within a similar flow regime as the project site

» For robust results, MCP requires high correlation between

reference site and on-site, project data

» What to do if suitable long-term reference data are not

available?

Traditional MCP

Measure-Correlate-Predict

Using Synthetic Reference Data

Numerical Weather Prediction Models

Synthetic Reference Data – Using NWP Models

» Unlike MCP analysis, Numerical Weather Prediction (NWP)

models do not require off-site reference data.

» Over 50 years of historic wind resource data at hourly

resolution can be generated utilizing NWP models

» Synthetic reference data are provided at the project-site

Numerical Weather Prediction Framework

Input Output

Global Weather

Archive

1948-present

High Resolution

Terrain, Soil, and

Vegetation Data

On-Site

Observations

Numerical

Weather

Prediction Model

(NWP)

Understanding

of Wind

Characteristics

Long-Term

Variability

Assessments

Spatial

Wind Maps

NWP wind speed

Long-term mean

NWP Output – Annual-mean Variability

Observed wind speed

Operational wind speed

NWP Output – Monthly-mean Variability

Based on single year of observations, compared to 40 year analysis

Capacity F

acto

r

Validation of 3TIER NWP Time Series

Comparison Against Reanalysis

287 QC’d Tall Towers

Average R=0.53

Median R=0.55

STD R=0.19

Skill of Reanalysis Data

287 QC’d Tall Towers

Average R=0.70

Median R=0.71

STD R=0.08

Skill of 3TIER Data

y = 0,9692x + 2,6531R² = 0,8772

0

20

40

60

80

100

120

140

160

180

200

0 20 40 60 80 100 120 140 160 180 200

3Tie

r 20m

ElZayt NW 24,5m

Wind energy index comaprison

y = 0,5507x + 44,931R² = 0,6706

0

20

40

60

80

100

120

140

160

180

200

0 20 40 60 80 100 120 140 160 180 200

NC

AR

ElZayt NW 24,5m

Wind energy index comaprison

"Our preliminary findings show that 3TIER wind data can

significantly reduce long-term correction error compared to

using NCAR/NCEP data, which is often the only option due to a

lack of reliable long-term ground measurements.

Per Nielsen - EMD Manager

Skill of 3TIER Data - Independent Validation

Incorporating On-site Observational Data

with

Numerical Weather Prediction Models

Model Output Statistics

(MOS)

Incorporating Observational Data

At any particular location the best way to

determine the wind resource is through direct

measurement.

3TIER incorporates observational data into

wind assessments whenever suitable on-site

data are available for

• Validation

• Statistical correction

• MOS (Model Output Statistics) is a statistical technique to

remove bias & adjust the variance of NWP model data to

better match the on-site observed data

• NWP models simulate the full structure and time evolution of

the atmosphere. MOS relates the observed wind speed to

the leading NWP predictors to improve the quality of the

long-term estimate of the wind resource.

• The output of the MOS algorithm is a multi-linear equation

that is applied to all times of the analysis on an hourly basis

(windspeed_97m * 1.25) + (windspeed_200m * 0.51) + (u_200m * 0.07) +

(temperature_0m * -0.06) + 18.93

Incorporating Observational Data - MOS

MOS-Corrected Output – Monthly-mean Variability

Validation of MOS-Corrected Time Series

Influence of observational record length

Skill at Monthly-mean Timescale

Raw Model Data MOS-Corrected Model Data

Analysis performed with Horizon Wind Energy utilizing 299 tall towers

MOS-corrected standard deviation of error for an individual month = 7.8%

Skill at Annual-mean Timescale

MOS-Corrected Model Data Raw Model Data

Analysis performed with Horizon Wind Energy utilizing 299 tall towers

MOS-corrected standard deviation of error for an individual year = 3.4%

MOS skill utilizing short observational records

A single month of observational data helps to remove bias

MOS-corrected errors decrease throughout first year of observed record

MOS skill utilizing short observational records

MOS-corrected errors decrease throughout first year of observed record

Comparing Skill of

3TIER MOS & MCP

Results based on 23 met

towers each with 5 years

of obs data

Obs data and MCP

analysis provided by

Horizon Wind Energy

3TIER MOS

MCP

Wake Modeling

• 3TIER’s super computing

capabilities allow unique

ability to model wakes in

time series across all

climatic conditions.

• Classical engineering

solutions require climatic

conditions to be condensed

into distributions, disguising

important features like

performance in atmospheric

stable conditions

Other losses

» Turbulence

» Shear

» Inflow angle

» Electrical system

» Availability

» Turbine performance

» Environmental

» Blade degradation

» Icing

» Wind sector management

» High speed start/stop hysteresis

Comprehensive Assessment

• 3TIER’s most complete solution, provides finance quality

energy assessment

• Project-wide, net energy assessment based on the last 40+

years of MOS-corrected NWP model data

• Adds a site-visit, quality control of obs data, full uncertainty

analysis, and gross-to-net analysis to a FullView Project

Resource Assessment

• Uses 3TIER’s proprietary time-varying wake modeling

analysis to understand diurnal and seasonal variability of

wakes, wind speed deficits, and turbulence intensity

Comprehensive Assessment

Full, time series simulation at every turbine across historic record

Comprehensive Assessment

Multi-staged observation QC process

Comprehensive Assessment

Comprehensive Assessment

Comprehensive uncertainty analysis highlights risk associated

with measurements, shear, spatial modeling, temporal

modeling, generation, wake modeling, etc…

Other Services

• Power Performance Testing – per IEC 61400-

12-1 standards

• Operational reforecast services – reassess the

long term production of a plant after operational

data is available

• Operational forensic services – root cause

analysis to “deep dive” into SCADA data and

attempt to explain variations on production

against expectations.

• Etc… 3TIER’s Advanced Applications group

positioned to tackle any challenges in need of

scientific solution.