PSM3 Data VS TMY3

[syangsunpinsolar.us]

Hi everyone,

I have a question about the meteo data I should use for estimating production in US. I'm currently using the build-in NREL API and I believe that pulls PSM3 data from NREL/NSRDB. I'm just wondering what is the difference between the PSM3 data and the TMY3 data collected from actual ground stations and which one is more acurate/reliable?

Thanks,

[dtarin]

NSRDB ground station data is a bit old, and varies in uncertainty (Class I-III, with III having highest uncertainty). Class II-III are generally not used due to the uncertainty and quality of data. However the other issue with this source is the proximity of these stations to your site and how representative it might or might not be.

PSMv3 compared to some commercially available satellite data providers (for TMY data) has been quite high in GHI in my experience (3-6%). You are able to select your location however, which is a benefit compared to NSRDB. Perhaps look at both and consider the result might be somewhere in between the two (NSRDB is often lower GHI compared to PSMv3 and other sources).

[SunOne]

I would caution PVsyst users modeling in the Northeast or Northwest United States from using the newer NSRDB weather dataset PSMv3 (Physical Solar Model version 3, 1998-2016, 4 km resolution). The PSM data is higher resolution and is derived from the most current weather satellite observations. However, it has been shown to have a large positive bias for locations with above average cloud cover, snowfall, or changing ground albedo.

 

“The NSRDB (1998–2015) data appear to have some challenges in quantifying the GHI accurately for areas susceptible to high occurrences of clouds, snow, and bright surfaces.”

Evaluation of the National Solar Radiation Database (NSRDB Version 2): 1998–2015, Aron Habte 2017

 

A comparison of weather data from Rochester, NY shows the effect of this bias.

Weather Data .................................................Global H.....Diffuse H

..................................................................kWh/M2......kWh/M2

PVGIS api TMY, TMY.............................................1343.5........563.8

Meteonorm 7.2 TMY (1991-2005).............................1349.2........626.8

NREL NSRD : TMY3 (1990-2010, 10 km)......................1349.9........653.5

NREL NSRDB PSMv3 TMY (1998 to 2016, 4 km)..............1390.5........577.4

PSMv3 variance to Meteonorm 7.2............................3.1%.........-7.9%

This bias generally leads to a 3.5% higher predicted output in PVsyst compared modeling the same physical PV plant (array tilt angle 25 degrees) using Meteonorm or older NSRDB 10 km data.

Until a newer version of the PSM satellite data corrects for these biases and can be confirmed to give reasonable production estimates (when compared to measured plant data), I recommend PVsyst users stick with Meteonorm weather data (with the Hay/Davies transposition model) for modeling plants in the Northern United States.

[LauraH]

NSRDB ground station data is a bit old, and varies in uncertainty (Class I-III, with III having highest uncertainty). Class II-III are generally not used due to the uncertainty and quality of data. However the other issue with this source is the proximity of these stations to your site and how representative it might or might not be.

 

It is a misconception that the pre-PSM NSRDB data came from ground stations. The 1961-1990 version contained only 7% observations; the rest of the data came from an empirical model (METSTAT) that used meteorological data as inputs. The 1991-2005 version contained only 1% observations; the rest of the data came from the METSTAT model or the "SUNY Albany" satellite model (a precurser to CPR's SolarAnywhere product). Thus only a miniscule portion of the data in the TMY2 or TMY3 products consists of observations.

The situation with Meteonorm is similar. Although some people say that Meteornorm has ~8,000 ground station, in fact only meteorological variables were measured at most of those stations. There are about 1,600 stations with measurements. The rest of the data comes from a satellite model; it is used to fill gaps in the ground site spatial coverage (which tend to be large outside of Europe).

You can learn all these things by reading the NSRDB users' manuals or the Meteonorm software and theory documents.

But I agree that the values from PSM tend to be high.