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The aim of Solargis API is to provide programmatic access to Solargis database and procedures (e.g. PV or GTI calculator) services for computers over the web. API is a "user interface" for developers. Developers can automate getting Solargis products by using standard web protocols (FTP, HTTP) and integrate data values into their processing chain (for evaluation. monitoring, forecasting, validation, calibration etc.).
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Solargis API | Available data (PV, solar, meteorological) | Technical features | ||||||
| historical | operational | real-time / & nowcast | NWP forecast | long-term average | web protocol | communication | content type | |
|---|---|---|---|---|---|---|---|---|
| FTP API |  | | | |  | FTP | asynchronous | CSV |
| WS API Time Series | | | | | | HTTP | synchronous | XML |
| WS API Long-term Averages | | | | | | HTTP | synchronous | XML |
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| satellite region | data availability sinceoperational | historical data update | historical operational data update | real-time and& nowcasting | satellite scan frequency | |
| GOES-EAST | 1999-01-01 | in the beginning of every month, whole previous month is re-calculated and archived | every day at 10:00 UTC (USA), 13:00 UTC (whole region) | in the beginning of every month, whole previous month is re-calculated to become archived | no | 30 minutes |
| MSG | 2005-01-01 | every day at 03:45 UTC | Europe, Kenya | 15 minutes | ||
| MTSAT / HIMAWARI | 2006-07-01 | every day at 22:40 UTC | East China, Japan | 30 min. (10 min. since Feb 2016 onward) |
Operational data daily update affects re-calculates two days - DAY-1 and DAY-2. Monthly update affects re-calculates the whole previous month as soon as completed. The purpose of those updates is described in this article. We gradually expands spatial coverage of satellite data accessible via API. To access operational and historical data in the gray areas on the map, please use Solargis climData online shop.
Note: the data from orange zones in the map is also available by using interactive application pvSpot (daily operational data) and is accessible within minutes when purchased via climData online shop (historical archived data).
Meteorological data from re-analysed Numerical Weather Model
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Parameters "fromDate" and "toDate" are required in this case. Such request is processed only once. Note, only radiation and temperature is requested herein this case, so no PV system settings are needed.
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Forecast data request example
Note the usage of "forecastFromDay" and "forecastToDay" parameters. Typically data will processed each 12 hours with forecasting from period since today (forecastFromDay=0) up to 7 days ahead (forecastToDay=7).
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There is no regularly processed request in case of this standard synchronous web service. Instead, the client will post the request and wait for the response. For technicalities visit this link. Developer can test various requests directly from web browser by using e.g. REST Client for Firefox. From within REST Client set HTTP Method to "POST", endpoint URL to: https://solargis.info/ws/rest/datadelivery/request?key=demo and also set header "Content-Type: application/xml". Then post the examples below in the body of the request and explore responses. Note, there is a limit of max. 31 days within requested date period. Typically, developer will create client code to schedule post requests and handle responses. This client code can be created based on XSD schema documents by multiple libraries (JAXB for Java, PyXB for Python etc.)
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There is no difference between historical an forecast data request. Note, there are no "forecastFromDay" and "forecastToDay" parameters as with FTP API. Instead, user have has to explicitly set the date period needed to be forecast-ed (max. 7 days ahead). Following request will give 8 days forecast-ed in total. The request below also shows minimalist settings needed for getting PV production (note that "inverter" and "losses" elements must be present are mandatory even if they are empty) .
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Responses from this service are standard Solargis CSV format files with header, metadata and data sections. They Files are suitable for automated processing. Examples of CSV response files:
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