Building a Better TMYGwendalyn Bender - PresentingAndrew Etringer, Steve Ihnen, Pascal StorckCo-authors

February 14, 2013

Setting the stage…

NREL TMY Methodology

TMY2: Ground data derived 1961-1990 (mixed irradiance and

meteorological observations)

With irradiance obs: Monthly cumulative distribution of daily

means for 5 variables using different weights (GHI (25%), DNI (25%),

temperature (20%), dew point (20%), and wind speed(10%))

With met data obs only: Irradiance is derived. Then monthly cumulative

distribution of daily means for 5 variables using different weights (GHI

(25%), DNI (25%), temperature (20%), dew point (20%), and wind

speed(10%))

TMY3: TMY2 database + Satellite data derived irradiance data 1991-

2005

Monthly cumulative distribution of daily means for 5 variables using different weights (GHI (25%), DNI

(25%), temperature (20%), dew point (20%), and wind speed(10%))

3TIER TMY Methodology

Satellite Derived Data (1997 –Current) for irradiance.

Choose irradiance value as main input (GHI, DNI or DIF).

4-day samples, within 0.5% deviation, for monthly means,

the monthly cumulative distribution of daily means, monthly diurnal cycles and

the annual mean.

NWP run (1997 – Current) for weather variables.

Temperature, wind speed, wind direction, surface

pressure, and relative humidity for matching time period

4-day samples for irradiance must also preserve temporal

correlation for weather, within 1.0% deviation, for the same

statistics.

TMY Dataset Differences

• Direct irradiance & weather observations for the TMY2 database vs derived irradiance & weather observations from 3TIER and the TMY3 database.

• The time periods covered vary. – NREL dataset is static vs the 3TIER updated dataset

• NREL’s monthly sampling period vs 3TIER’s 4-day sampling period– Weighting for the different parameters also varies

• Coverage of the United States and India with NREL vsglobal coverage with 3TIER

……so how do they compare?

Comparison Results

Comparison Results

January

July

Case Study – Southern California

• Private observations with 2+ years of GHI observations

• 3TIER TMY pulled at the site

• Nearest 7 NREL sites were TMY3 locations

– Nearest TMY2 location ~130km away

Case Study – Southern California

17km

103km

105km

Case Study – Southern CaliforniaMean (W/m2) Private Site 3TIER NREL Site 1 NREL Site 2 NREL Site 3

Annual 251.27 241.77 240.36 224.8 225.67

Jan 146.5 143.36 148.58 146.13 144.78

Feb 189.39 177.64 172.86 179.86 177.08

Mar 256.41 247.41 239.89 207.06 189.7

Apr 303.45 299.56 300.18 287.36 277.55

May 338.6 330.97 327.19 291.53 324.74

Jun 341.12 345.68 340.27 292.08 300.2

Jul 315.86 315.12 316.14 294.94 298.1

Aug 288.34 288.03 296.96 263.87 273.7

Sept 266.12 258.11 254.19 254.31 250.93

Oct 205.99 206.2 191 208.39 209.66

Nov 162.28 155.43 155.53 164.17 153.5

Dec 124.26 130.21 137.58 106.48 105.68

Case Study – Southern CaliforniaPrivate ObservationsNREL Site 1 TMY3TIER TMYNREL Site 2 TMYNREL Site 3 TMY

Monthly Means Comparison

W/m

2

Months

Case Study – Southern California

20

10

20

11

GHI DNI DIF

Case Study – Southern California

Annual Yield [GWh]

Ann Avg DNI [Wh/m2-day]

Ann Avg GHI [Wh/m2-day]

3TIER 14-year data set

33.778 6,441 5,784

3TIER TMY methodology

33.816 6,405 5,803

NREL TMY methodology

35.751 7,230 5,767

Case Study – Southern California

Long-term Variability is Important

“The TMY should not be used to predict weather for a particular

period of time, nor is it an appropriate basis for evaluating real-

time energy production or efficiencies for building design

applications or solar conversion systems.”NREL Technical Report 2008

Conclusions

• 3T TMY = pretty good, available any where for better site accuracy

• BUT TMY’s suck

• Get a long-term timeseries

Questions?

Gwendalyn Bendergbender@3tier.com