Solar RadiationMeasurement, Modeling,

and Performance PredictionPrepared for Solar

Minnesota by Darryl Thayer

Solar Performance• Simply put, solar PV performance is predicted by

using the data from TMY 2 or TMY 3. • All approaches use the principals of the PV

photo response and apply in either an empirical method (PVWatts, Retscreen, Pathfinder) or simulation routine (SAM, Homer, PVsys, PVsol, Polysun).

• But all are based on TMY Data Files (Typical Meteorological Year)

What is TMY?• The term TMY is from Typical Meteorological

Year.• It is a data file consisting of a full year of data

constructed from twelve months chosen as most typical months from all the years that made up the data file.

• Example March maybe from 1973, April from 1989 etc.

• Because March 1973 is the most typical March of all Marchs in the data file.

TMY files• Where do the TMY’s Data Files come from?• TMY(1) 239 stations some with measured data

shown here using stars.• TMY 2-3 are 1,456 locations, of differing quality.

There are 40 stations with actual solar radiation measurements indicated by circles

TMY File data points

TMY Files• What was considered in selecting the most typical

months? • The original TMY(1) data files were created by Sandia

National Laboratory using a method in which a typical month was selected based on nine daily indices.

• (such as max, min, temp, humidity, mean wind velocity; and the total global horizontal irradiance.)

• The data set used measured and calculated solar data for 239 cities, compiled from the period 1952 to 1975.

• The original TMY data files were created from measured GHI SOLMET data and modeled ERSATZ data.

Why was TMY1 created?• The reason the TMY(1) was created was for

building science, to predict building performance where outdoor temp, humidity, wind speed and solar radiation play the major roles.

Why was TMY2 created?• TMY 2 files were created to better serve the solar thermal

industry. • TMY2 data files were created from the 1961 to 1990

NSRDB where 93% of the values were modeled data.• However the weighting of daily indices were changed and

DNI (Direct Normal Irradiation) was added to reflect the greater importance of solar radiation.

• The months May 1982 through December 1984 were excluded because of the eruption of El Chichón, Mexico.

• Climatologist require a 30 year data set for significance.• The direct normal irradiance (DNI) was added to the

weighting indices.

Why was TMY3 created?• TMY 3 files use the same daily indices as TMY 2

but are from 1991 to 2005 data set. • The months of June 1991 to December 1994

were excluded because of the eruption of Mount Pinatubo, Philippines.

• As a result of the exclusion, the TMY3 files were derived using 11.5 years of data.

TMY 3.1 data • TMY 3.1 files soon to be released (July 1) add to

the TMY 3 files the years of 2006-(2008-10?) • This data is resulting in recalculation of TMY in

some cases the selected month will change.• This expands the record, and includes more

recent data. • The 3.1 data will be accessible on the NREL

web site • (A recent report indicates Minnesota has

warmed 2.5 degrees in the last 40 years.)

Table of Daily Indices for determining “Typical”:Indices TMY (1) % TMY (2-3) %

Max Temp DB 7% 5%

Min Temp DB 7% 5%

Mean Temp DB 15% 10%

Min Dew Pt 7% 5%

Max Dew Pt 7% 5%

Mean Dew Pt 14% 10%

Max Wind Spd 14% 5%

Mean Wind Spd 14% 5%

GHI (global horiz) 14% 25%

DNI (direct normal) 0% 25%

Summary of above table

Indices TMY(1) TMY 2-3

DB Temp 28% 20%

Dew Pt 28% 20%

Wind 28% 10%

Solar 14% 50%

Limitations of the TMY2 and TMY3 Files

• The TMY files were created to represent typical meteorological years and not typical solar years.

• Due to the limited number of years in TMY3 data files, there is no guarantee that the TMY3 file will be an accurate representation of the average GHI or DNI for the entire historical data set.

• Examples where the GHI and DNI TMY annual average are different from the average are shown in Figs. 1-2.

An Example:• At Groton-New London, CT, the annual TMY GHI

is below the yearly average GHI for every single year in the NSRDB.

• A moving average was used and no 12-month period has an annual GHI as low as the TMY3 file.

TMY 3 over predicts

Eppley Black & White Pyranometer

Licor Silicon Radiometer

Comparison testing

Eppley NIP

Rotating Shadowband Radiometer

Rotating Shadowband Radiometer

Licor

Satellite Data• Starting 1998 the Data from the GOES Weather Satellite

was available. • The Satellite data is measured once per hour, on a 0.1

degree grid. • This is about 100,000 data points, across the US and is

available at NREL and SUNY and NCDC• Satellite data is best near ground based stations. • Modeling selects the same TMY 3 months as the ground

based stations.

Solar Radiation Modeling• So far all we have done is build a TMY set of GHI and

DNI• Data that reflects the solar radiation on a horizontal

surface. • Of course we want the solar radiation on a tilted surface• Richard Perez developed the standard technique and is

accepted world wide, for the calculation of radiation on other surfaces.

Emperical based programs

• Programs like RetScreen, Pathfinder, Suneye Companion, take TMY 3 GHI and DNI and complied a set of numbers for each month for each location.

• A set of 5 numbers for each month for 1000 locations is only 60,000 data points

• This set of numbers allows reconstruction of monthly radiation and application of the Pérez model for change of orientation to selected orentation

Simulation Based Programs

• Programs like PV designer, Homer, SAM, Polysun etc. go back to the TMY 3 data set and recover the hourly data

• These programs take the Hourly GHI and DNI and apply the Perez model to determine the radiation on a tilted surface.

• The value of returning to the TMY-3 hourly is not for total annual performance, but for timing critical performanceo Shading analysiso Time of Day pricingo Time critical LOL calculationso Demand reductiono Utility interconnect considerations

How to test for module and array performance

• Because TMY-3 data is meant to be Typical Year data and is complied over 11.5 years….

• A one month set of averages is not representative of the record. (energy collected over one month, is just that and not indicative of a long term average

• Even a One year record is not indicative of a long term record.

• So is there a way to test for Solar performance to compare with expected performance?

Testing to determine system performance

• Since most of the radiation is DNI most of the comparison should be on DNI

• Suggested Methods: o Measure on clear dayso Compare with a standard sourceo Such as radiometer at the same angle as your collectorso Compare with DC value .

• Caveats • The sun is not 1000 Watts / M^2• The sun varies over time differently a different locations• Correct for Cos Angle factor if arrays are at different

angles.

Example of measured Performance

Minneapolis, MN