Solar radiation data The 2019 Stack Overflow Developer Survey Results Are InAnalytically 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
The 2019 Stack Overflow Developer Survey Results Are InAnalytically 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
New contributor
$endgroup$
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
New contributor
$endgroup$
$begingroup$
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
14 hours ago
$begingroup$
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
14 hours ago
$begingroup$
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
14 hours ago
$begingroup$
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
10 hours ago
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
New contributor
$endgroup$
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
New contributor
New contributor
edited 14 hours ago
Adrien
New contributor
asked 15 hours ago
AdrienAdrien
312
312
New contributor
New contributor
$begingroup$
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
14 hours ago
$begingroup$
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
14 hours ago
$begingroup$
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
14 hours ago
$begingroup$
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
10 hours ago
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
14 hours ago
$begingroup$
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
14 hours ago
$begingroup$
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
14 hours ago
$begingroup$
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
10 hours ago
$begingroup$
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
14 hours ago
$begingroup$
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
14 hours ago
$begingroup$
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
14 hours ago
$begingroup$
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
14 hours ago
$begingroup$
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
14 hours ago
$begingroup$
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
14 hours ago
$begingroup$
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
10 hours ago
$begingroup$
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
10 hours ago
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 :)
$endgroup$
add a comment |
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1 Answer
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$begingroup$
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 :)
$endgroup$
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 :)
$endgroup$
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 :)
$endgroup$
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 :)
edited 14 hours ago
answered 14 hours ago
Carl LangeCarl Lange
5,27411141
5,27411141
add a comment |
add a comment |
Adrien is a new contributor. Be nice, and check out our Code of Conduct.
Adrien is a new contributor. Be nice, and check out our Code of Conduct.
Adrien is a new contributor. Be nice, and check out our Code of Conduct.
Adrien is a new contributor. Be nice, and check out our Code of Conduct.
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$begingroup$
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
14 hours ago
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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
14 hours ago
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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
14 hours ago
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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
10 hours ago