Solar radiation data Planned maintenance scheduled April 17/18, 2019 at 00:00UTC (8:00pm US/Eastern) Announcing the arrival of Valued Associate #679: Cesar Manara Unicorn Meta Zoo #1: Why another podcast?Analytically finding critical values in a hysteresis curve made with ListPlotWolframAlpha Selective SubPod ContentColumn specific data inputsHow to perform a multi-peak fitting?unevenly spaced dataCan A Plot Be Overlayed With A Map?Orderless storage of tabulated function valuesHelp with data manipulationTwo-Point correlation function of Ising data is not giving expected resultsHow to calculate and plot a function with continous(input data) and constant variables
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Solar radiation data
Planned maintenance scheduled April 17/18, 2019 at 00:00UTC (8:00pm US/Eastern)
Announcing the arrival of Valued Associate #679: Cesar Manara
Unicorn Meta Zoo #1: Why another podcast?Analytically finding critical values in a hysteresis curve made with ListPlotWolframAlpha Selective SubPod ContentColumn specific data inputsHow to perform a multi-peak fitting?unevenly spaced dataCan A Plot Be Overlayed With A Map?Orderless storage of tabulated function valuesHelp with data manipulationTwo-Point correlation function of Ising data is not giving expected resultsHow to calculate and plot a function with continous(input data) and constant variables
$begingroup$
Is there somewhere in Mathematica I can find direct and diffuse solar radiation for a specific position on Earth ?
If not, is there a way to import those data from a website within a Mathematica code ? The best would be a code in which I give specifics date, latitude and longitude, and I get in return GHI and BHI for this place at this specific date.
Thanks !
data
asked Apr 10 at 12:52
AdrienAdrien
312
$endgroup$
add a comment |
$begingroup$
Is there somewhere in Mathematica I can find direct and diffuse solar radiation for a specific position on Earth ?
If not, is there a way to import those data from a website within a Mathematica code ? The best would be a code in which I give specifics date, latitude and longitude, and I get in return GHI and BHI for this place at this specific date.
Thanks !
data
asked Apr 10 at 12:52
AdrienAdrien
312
$endgroup$
$begingroup$
Does globalsolaratlas.info help you at all? It contains maps for GHI, DHI, and so on (check the top right of the page). You can download data here: globalsolaratlas.info/downloads/world
$endgroup$
– Carl Lange
Apr 10 at 13:03
$begingroup$
This is not exactly what I'm looking for... I would like to get GHI and BHI for different places, that's why I'd rather import directly those datas within a code, if it is possible.
$endgroup$
– Adrien
Apr 10 at 13:23
$begingroup$
If necessary, you could download that data for much of the world as GeoTIFF from that web page, and then index into it locally.
$endgroup$
– Carl Lange
Apr 10 at 13:26
$begingroup$
Your best bet would probably to get long term monthly irradiance values (e.g. from re.jrc.ec.europa.eu/pvgis or Meteonorm), create synthetic hourly values with dedicated software (PVSOL, PVSYST, INSEL or possibly Python PVlib) and import them into Mathematica. One algorithm to create hourly values from monthly values has been published by Gordon-Reddy : sciencedirect.com/science/article/pii/0038092X88900163
$endgroup$
– Eric Duminil
Apr 10 at 17:27
add a comment |
$begingroup$
Is there somewhere in Mathematica I can find direct and diffuse solar radiation for a specific position on Earth ?
If not, is there a way to import those data from a website within a Mathematica code ? The best would be a code in which I give specifics date, latitude and longitude, and I get in return GHI and BHI for this place at this specific date.
Thanks !
data
asked Apr 10 at 12:52
AdrienAdrien
312
$endgroup$
Is there somewhere in Mathematica I can find direct and diffuse solar radiation for a specific position on Earth ?
If not, is there a way to import those data from a website within a Mathematica code ? The best would be a code in which I give specifics date, latitude and longitude, and I get in return GHI and BHI for this place at this specific date.
Thanks !
data
data
asked Apr 10 at 12:52
AdrienAdrien
312
asked Apr 10 at 12:52
AdrienAdrien
312
edited Apr 10 at 13:20
Adrien
asked Apr 10 at 12:52
AdrienAdrien
312
asked Apr 10 at 12:52
AdrienAdrien
312
asked Apr 10 at 12:52
AdrienAdrien
312
312
$begingroup$
Does globalsolaratlas.info help you at all? It contains maps for GHI, DHI, and so on (check the top right of the page). You can download data here: globalsolaratlas.info/downloads/world
$endgroup$
– Carl Lange
Apr 10 at 13:03
$begingroup$
This is not exactly what I'm looking for... I would like to get GHI and BHI for different places, that's why I'd rather import directly those datas within a code, if it is possible.
$endgroup$
– Adrien
Apr 10 at 13:23
$begingroup$
If necessary, you could download that data for much of the world as GeoTIFF from that web page, and then index into it locally.
$endgroup$
– Carl Lange
Apr 10 at 13:26
$begingroup$
Your best bet would probably to get long term monthly irradiance values (e.g. from re.jrc.ec.europa.eu/pvgis or Meteonorm), create synthetic hourly values with dedicated software (PVSOL, PVSYST, INSEL or possibly Python PVlib) and import them into Mathematica. One algorithm to create hourly values from monthly values has been published by Gordon-Reddy : sciencedirect.com/science/article/pii/0038092X88900163
$endgroup$
– Eric Duminil
Apr 10 at 17:27
add a comment |
$begingroup$
Does globalsolaratlas.info help you at all? It contains maps for GHI, DHI, and so on (check the top right of the page). You can download data here: globalsolaratlas.info/downloads/world
$endgroup$
– Carl Lange
Apr 10 at 13:03
$begingroup$
This is not exactly what I'm looking for... I would like to get GHI and BHI for different places, that's why I'd rather import directly those datas within a code, if it is possible.
$endgroup$
– Adrien
Apr 10 at 13:23
$begingroup$
If necessary, you could download that data for much of the world as GeoTIFF from that web page, and then index into it locally.
$endgroup$
– Carl Lange
Apr 10 at 13:26
$begingroup$
Your best bet would probably to get long term monthly irradiance values (e.g. from re.jrc.ec.europa.eu/pvgis or Meteonorm), create synthetic hourly values with dedicated software (PVSOL, PVSYST, INSEL or possibly Python PVlib) and import them into Mathematica. One algorithm to create hourly values from monthly values has been published by Gordon-Reddy : sciencedirect.com/science/article/pii/0038092X88900163
$endgroup$
– Eric Duminil
Apr 10 at 17:27
$begingroup$
Does globalsolaratlas.info help you at all? It contains maps for GHI, DHI, and so on (check the top right of the page). You can download data here: globalsolaratlas.info/downloads/world
$endgroup$
– Carl Lange
Apr 10 at 13:03
$begingroup$
Does globalsolaratlas.info help you at all? It contains maps for GHI, DHI, and so on (check the top right of the page). You can download data here: globalsolaratlas.info/downloads/world
$endgroup$
– Carl Lange
Apr 10 at 13:03
$begingroup$
This is not exactly what I'm looking for... I would like to get GHI and BHI for different places, that's why I'd rather import directly those datas within a code, if it is possible.
$endgroup$
– Adrien
Apr 10 at 13:23
$begingroup$
This is not exactly what I'm looking for... I would like to get GHI and BHI for different places, that's why I'd rather import directly those datas within a code, if it is possible.
$endgroup$
– Adrien
Apr 10 at 13:23
$begingroup$
If necessary, you could download that data for much of the world as GeoTIFF from that web page, and then index into it locally.
$endgroup$
– Carl Lange
Apr 10 at 13:26
$begingroup$
If necessary, you could download that data for much of the world as GeoTIFF from that web page, and then index into it locally.
$endgroup$
– Carl Lange
Apr 10 at 13:26
$begingroup$
Your best bet would probably to get long term monthly irradiance values (e.g. from re.jrc.ec.europa.eu/pvgis or Meteonorm), create synthetic hourly values with dedicated software (PVSOL, PVSYST, INSEL or possibly Python PVlib) and import them into Mathematica. One algorithm to create hourly values from monthly values has been published by Gordon-Reddy : sciencedirect.com/science/article/pii/0038092X88900163
$endgroup$
– Eric Duminil
Apr 10 at 17:27
$begingroup$
Your best bet would probably to get long term monthly irradiance values (e.g. from re.jrc.ec.europa.eu/pvgis or Meteonorm), create synthetic hourly values with dedicated software (PVSOL, PVSYST, INSEL or possibly Python PVlib) and import them into Mathematica. One algorithm to create hourly values from monthly values has been published by Gordon-Reddy : sciencedirect.com/science/article/pii/0038092X88900163
$endgroup$
– Eric Duminil
Apr 10 at 17:27
add a comment |
1 Answer
1
active
oldest
votes
$begingroup$
It appears the US NREL has made an API available for this data. However, it is monthly averages, rather than live data by date. I think for this data, that's just how it is. It's also not clear to me what exactly the spatial extent is.
Let's write a WL function to query the data. You should replace DEMO_KEY with your own key after signing up, or you will very quickly hit rate limits. Signing up is free: https://developer.nrel.gov/signup/
solarData[place_] :=
Import[URLBuild[
"https://developer.nrel.gov/api/solar/solar_resource/v1.json", <|
"api_key" -> "DEMO_KEY",
"lat" -> QuantityMagnitude@Latitude@place,
"lon" -> QuantityMagnitude@Longitude@place|>], "RawJSON"][
"outputs"]
Which we can then use with:
solarData[Entity["AdministrativeDivision", "Kansas", "UnitedStates"]]
<|"avg_dni" -> <|"annual" -> 5.32,
"monthly" -> <|"jan" -> 4.48, "feb" -> 4.72, "mar" -> 4.87,
"apr" -> 5.47, "may" -> 5.86, "jun" -> 6.23, "jul" -> 6.67,
"aug" -> 6.14, "sep" -> 5.78, "oct" -> 4.91, "nov" -> 4.58,
"dec" -> 4.03|>|>,
"avg_ghi" -> <|"annual" -> 4.62,
"monthly" -> <|"jan" -> 2.47, "feb" -> 3.26, "mar" -> 4.27,
"apr" -> 5.49, "may" -> 6.42, "jun" -> 6.79, "jul" -> 6.86,
"aug" -> 6.13, "sep" -> 5.04, "oct" -> 3.67, "nov" -> 2.73,
"dec" -> 2.16|>|>,
"avg_lat_tilt" -> <|"annual" -> 5.44,
"monthly" -> <|"jan" -> 4.46, "feb" -> 4.91, "mar" -> 5.31,
"apr" -> 5.84, "may" -> 6.05, "jun" -> 6.08, "jul" -> 6.31,
"aug" -> 6.28, "sep" -> 6.01, "oct" -> 5.22, "nov" -> 4.69,
"dec" -> 4.07|>|>|>
Another option would be to download data from https://globalsolaratlas.info/downloads/world or some other source (there are a few) and index into it locally, but this is a bit more hassle. In fact, if I was to use the Global Solar Atlas data, I would probably load it into a local Postgis database (using raster2pgsql) and query it that way, since Wolfram Language's ability to query into large spatial datasets is not as good as Postgis' is. Maybe someday :)
answered Apr 10 at 13:40
Carl LangeCarl Lange
5,39911242
$endgroup$
add a comment |
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1 Answer
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1 Answer
1
active
oldest
votes
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votes
$begingroup$
It appears the US NREL has made an API available for this data. However, it is monthly averages, rather than live data by date. I think for this data, that's just how it is. It's also not clear to me what exactly the spatial extent is.
Let's write a WL function to query the data. You should replace DEMO_KEY with your own key after signing up, or you will very quickly hit rate limits. Signing up is free: https://developer.nrel.gov/signup/
solarData[place_] :=
Import[URLBuild[
"https://developer.nrel.gov/api/solar/solar_resource/v1.json", <|
"api_key" -> "DEMO_KEY",
"lat" -> QuantityMagnitude@Latitude@place,
"lon" -> QuantityMagnitude@Longitude@place|>], "RawJSON"][
"outputs"]
Which we can then use with:
solarData[Entity["AdministrativeDivision", "Kansas", "UnitedStates"]]
<|"avg_dni" -> <|"annual" -> 5.32,
"monthly" -> <|"jan" -> 4.48, "feb" -> 4.72, "mar" -> 4.87,
"apr" -> 5.47, "may" -> 5.86, "jun" -> 6.23, "jul" -> 6.67,
"aug" -> 6.14, "sep" -> 5.78, "oct" -> 4.91, "nov" -> 4.58,
"dec" -> 4.03|>|>,
"avg_ghi" -> <|"annual" -> 4.62,
"monthly" -> <|"jan" -> 2.47, "feb" -> 3.26, "mar" -> 4.27,
"apr" -> 5.49, "may" -> 6.42, "jun" -> 6.79, "jul" -> 6.86,
"aug" -> 6.13, "sep" -> 5.04, "oct" -> 3.67, "nov" -> 2.73,
"dec" -> 2.16|>|>,
"avg_lat_tilt" -> <|"annual" -> 5.44,
"monthly" -> <|"jan" -> 4.46, "feb" -> 4.91, "mar" -> 5.31,
"apr" -> 5.84, "may" -> 6.05, "jun" -> 6.08, "jul" -> 6.31,
"aug" -> 6.28, "sep" -> 6.01, "oct" -> 5.22, "nov" -> 4.69,
"dec" -> 4.07|>|>|>
Another option would be to download data from https://globalsolaratlas.info/downloads/world or some other source (there are a few) and index into it locally, but this is a bit more hassle. In fact, if I was to use the Global Solar Atlas data, I would probably load it into a local Postgis database (using raster2pgsql) and query it that way, since Wolfram Language's ability to query into large spatial datasets is not as good as Postgis' is. Maybe someday :)
answered Apr 10 at 13:40
Carl LangeCarl Lange
5,39911242
$endgroup$
add a comment |
$begingroup$
It appears the US NREL has made an API available for this data. However, it is monthly averages, rather than live data by date. I think for this data, that's just how it is. It's also not clear to me what exactly the spatial extent is.
Let's write a WL function to query the data. You should replace DEMO_KEY with your own key after signing up, or you will very quickly hit rate limits. Signing up is free: https://developer.nrel.gov/signup/
solarData[place_] :=
Import[URLBuild[
"https://developer.nrel.gov/api/solar/solar_resource/v1.json", <|
"api_key" -> "DEMO_KEY",
"lat" -> QuantityMagnitude@Latitude@place,
"lon" -> QuantityMagnitude@Longitude@place|>], "RawJSON"][
"outputs"]
Which we can then use with:
solarData[Entity["AdministrativeDivision", "Kansas", "UnitedStates"]]
<|"avg_dni" -> <|"annual" -> 5.32,
"monthly" -> <|"jan" -> 4.48, "feb" -> 4.72, "mar" -> 4.87,
"apr" -> 5.47, "may" -> 5.86, "jun" -> 6.23, "jul" -> 6.67,
"aug" -> 6.14, "sep" -> 5.78, "oct" -> 4.91, "nov" -> 4.58,
"dec" -> 4.03|>|>,
"avg_ghi" -> <|"annual" -> 4.62,
"monthly" -> <|"jan" -> 2.47, "feb" -> 3.26, "mar" -> 4.27,
"apr" -> 5.49, "may" -> 6.42, "jun" -> 6.79, "jul" -> 6.86,
"aug" -> 6.13, "sep" -> 5.04, "oct" -> 3.67, "nov" -> 2.73,
"dec" -> 2.16|>|>,
"avg_lat_tilt" -> <|"annual" -> 5.44,
"monthly" -> <|"jan" -> 4.46, "feb" -> 4.91, "mar" -> 5.31,
"apr" -> 5.84, "may" -> 6.05, "jun" -> 6.08, "jul" -> 6.31,
"aug" -> 6.28, "sep" -> 6.01, "oct" -> 5.22, "nov" -> 4.69,
"dec" -> 4.07|>|>|>
Another option would be to download data from https://globalsolaratlas.info/downloads/world or some other source (there are a few) and index into it locally, but this is a bit more hassle. In fact, if I was to use the Global Solar Atlas data, I would probably load it into a local Postgis database (using raster2pgsql) and query it that way, since Wolfram Language's ability to query into large spatial datasets is not as good as Postgis' is. Maybe someday :)
answered Apr 10 at 13:40
Carl LangeCarl Lange
5,39911242
$endgroup$
add a comment |
$begingroup$
It appears the US NREL has made an API available for this data. However, it is monthly averages, rather than live data by date. I think for this data, that's just how it is. It's also not clear to me what exactly the spatial extent is.
Let's write a WL function to query the data. You should replace DEMO_KEY with your own key after signing up, or you will very quickly hit rate limits. Signing up is free: https://developer.nrel.gov/signup/
solarData[place_] :=
Import[URLBuild[
"https://developer.nrel.gov/api/solar/solar_resource/v1.json", <|
"api_key" -> "DEMO_KEY",
"lat" -> QuantityMagnitude@Latitude@place,
"lon" -> QuantityMagnitude@Longitude@place|>], "RawJSON"][
"outputs"]
Which we can then use with:
solarData[Entity["AdministrativeDivision", "Kansas", "UnitedStates"]]
<|"avg_dni" -> <|"annual" -> 5.32,
"monthly" -> <|"jan" -> 4.48, "feb" -> 4.72, "mar" -> 4.87,
"apr" -> 5.47, "may" -> 5.86, "jun" -> 6.23, "jul" -> 6.67,
"aug" -> 6.14, "sep" -> 5.78, "oct" -> 4.91, "nov" -> 4.58,
"dec" -> 4.03|>|>,
"avg_ghi" -> <|"annual" -> 4.62,
"monthly" -> <|"jan" -> 2.47, "feb" -> 3.26, "mar" -> 4.27,
"apr" -> 5.49, "may" -> 6.42, "jun" -> 6.79, "jul" -> 6.86,
"aug" -> 6.13, "sep" -> 5.04, "oct" -> 3.67, "nov" -> 2.73,
"dec" -> 2.16|>|>,
"avg_lat_tilt" -> <|"annual" -> 5.44,
"monthly" -> <|"jan" -> 4.46, "feb" -> 4.91, "mar" -> 5.31,
"apr" -> 5.84, "may" -> 6.05, "jun" -> 6.08, "jul" -> 6.31,
"aug" -> 6.28, "sep" -> 6.01, "oct" -> 5.22, "nov" -> 4.69,
"dec" -> 4.07|>|>|>
Another option would be to download data from https://globalsolaratlas.info/downloads/world or some other source (there are a few) and index into it locally, but this is a bit more hassle. In fact, if I was to use the Global Solar Atlas data, I would probably load it into a local Postgis database (using raster2pgsql) and query it that way, since Wolfram Language's ability to query into large spatial datasets is not as good as Postgis' is. Maybe someday :)
answered Apr 10 at 13:40
Carl LangeCarl Lange
5,39911242
$endgroup$
It appears the US NREL has made an API available for this data. However, it is monthly averages, rather than live data by date. I think for this data, that's just how it is. It's also not clear to me what exactly the spatial extent is.
Let's write a WL function to query the data. You should replace DEMO_KEY with your own key after signing up, or you will very quickly hit rate limits. Signing up is free: https://developer.nrel.gov/signup/
solarData[place_] :=
Import[URLBuild[
"https://developer.nrel.gov/api/solar/solar_resource/v1.json", <|
"api_key" -> "DEMO_KEY",
"lat" -> QuantityMagnitude@Latitude@place,
"lon" -> QuantityMagnitude@Longitude@place|>], "RawJSON"][
"outputs"]
Which we can then use with:
solarData[Entity["AdministrativeDivision", "Kansas", "UnitedStates"]]
<|"avg_dni" -> <|"annual" -> 5.32,
"monthly" -> <|"jan" -> 4.48, "feb" -> 4.72, "mar" -> 4.87,
"apr" -> 5.47, "may" -> 5.86, "jun" -> 6.23, "jul" -> 6.67,
"aug" -> 6.14, "sep" -> 5.78, "oct" -> 4.91, "nov" -> 4.58,
"dec" -> 4.03|>|>,
"avg_ghi" -> <|"annual" -> 4.62,
"monthly" -> <|"jan" -> 2.47, "feb" -> 3.26, "mar" -> 4.27,
"apr" -> 5.49, "may" -> 6.42, "jun" -> 6.79, "jul" -> 6.86,
"aug" -> 6.13, "sep" -> 5.04, "oct" -> 3.67, "nov" -> 2.73,
"dec" -> 2.16|>|>,
"avg_lat_tilt" -> <|"annual" -> 5.44,
"monthly" -> <|"jan" -> 4.46, "feb" -> 4.91, "mar" -> 5.31,
"apr" -> 5.84, "may" -> 6.05, "jun" -> 6.08, "jul" -> 6.31,
"aug" -> 6.28, "sep" -> 6.01, "oct" -> 5.22, "nov" -> 4.69,
"dec" -> 4.07|>|>|>
Another option would be to download data from https://globalsolaratlas.info/downloads/world or some other source (there are a few) and index into it locally, but this is a bit more hassle. In fact, if I was to use the Global Solar Atlas data, I would probably load it into a local Postgis database (using raster2pgsql) and query it that way, since Wolfram Language's ability to query into large spatial datasets is not as good as Postgis' is. Maybe someday :)
answered Apr 10 at 13:40
Carl LangeCarl Lange
5,39911242
edited Apr 10 at 13:55
answered Apr 10 at 13:40
Carl LangeCarl Lange
5,39911242
answered Apr 10 at 13:40
Carl LangeCarl Lange
5,39911242
answered Apr 10 at 13:40
Carl LangeCarl Lange
5,39911242
5,39911242
add a comment |
add a comment |
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Does globalsolaratlas.info help you at all? It contains maps for GHI, DHI, and so on (check the top right of the page). You can download data here: globalsolaratlas.info/downloads/world
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– Carl Lange
Apr 10 at 13:03
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This is not exactly what I'm looking for... I would like to get GHI and BHI for different places, that's why I'd rather import directly those datas within a code, if it is possible.
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– Adrien
Apr 10 at 13:23
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If necessary, you could download that data for much of the world as GeoTIFF from that web page, and then index into it locally.
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– Carl Lange
Apr 10 at 13:26
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Your best bet would probably to get long term monthly irradiance values (e.g. from re.jrc.ec.europa.eu/pvgis or Meteonorm), create synthetic hourly values with dedicated software (PVSOL, PVSYST, INSEL or possibly Python PVlib) and import them into Mathematica. One algorithm to create hourly values from monthly values has been published by Gordon-Reddy : sciencedirect.com/science/article/pii/0038092X88900163
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– Eric Duminil
Apr 10 at 17:27