Weather File Upload Guide
The selection of a weather file is one of the first steps in running a prediction. PlantPredict can handle weather files of almost any granularity, from 60 minutes down to single minute granularity. PlantPredict can also handle many different weather file formats:
- Solar Prospector
- NREL TMY3
In addition to the file formats above, any reasonable excel workbook or CSV file can be uploaded and formatted during the upload process.
The user can start uploading their own weather file either from 1) the weather component library, or 2) from within a prediction. In either case, the use will be taken to the following screen:
From here, the following steps describe how to upload the desired weather file:
- Click on “upload your own weather file” and select the desired file
2. Define Locality
3. Set Parameters– These values are not required. However, it is highly encouraged to fill in these values for informational purposes
4. Format Data – The “meat and potatoes” of the weather file upload. Some items to note:
a) The table on the right shows all the data from the uploaded file. This step aims to trim out unwanted information not needed for the final PlantPredict weather file
b) The section on the left with “Variables” and “Timestamp” tabs contains 1) all potential variables that can be included in a PlantPredict weather file, and 2) inputs required to define the timestamps associated with the data
i) Using the “Variables” tab in the column on the left, the user first selects which variables are to be included in the PlantPredict weather file by using the check boxes. After the checkbox is selected, the user then selects in which column that variable exists in the imported file by using the drop down menu.
ii) “Header Rows to Skip” indicates how many header rows in included in the excel file. These are not to be included in the final PlantPredict weather file and are thus to be skipped
iii) Timestamps are not currently able to be read from columns in an imported file. Instead, when defining the parameters on the “Timestamp” tab, the user indicates 1) the Start Date and 2) the Interval Duration. The application then automatically extrapolates the end date of the file. Additionally, the user can toggle on whether to include a leap day(s) in the timestamp definition or not.
c) As a note – the minimum required data series for a PlantPredict weather file is irradience (GHI or POAI) and Temperature.
5) Quality Check – Here the user can review all the data uploaded before the PlantPredict whether file is created. Users can also visualize how the weather data compares to the clear sky model which is especially useful for detecting timeshifts in the data. A handy data shifting feature is available for cases where a timeshift does exist to avoid having to start the process over.
FAQ’s, Tips and Tricks, and Troubleshooting
- Imported files may contain neither blanks nor NULLS. If the weather file contains blanks or NULLS, fill in “0” for that entry prior to importing (the excel function “=COUNTBLANK()” can be very useful here)
- It’s extremely easy for measured excel files to unintentionally have duplicate or missing data entries. These situations are especially tricky because an error won’t be thrown upon upload. A good way to identify this problem is to compare the projected End Date in the “Format Data” step of the upload process to the final timestamp in the excel file. If they do not match, that means there are either missing entries or extra entries in the original excel file, and the user should investigate further
- If variables that affect spectral correction (relative humidity, dewpoint temperature, precipitable water) are not included, then spectral calculations will not be included in predictions where this weather file is used
- If the upload is erroring out on the first step, the application is having an issue parsing the file. Check to make sure all headers are correct and contain the correct type of information. Additionally, simplifying the imported file can many times allow for the upload to continue – one easy way of simplifying is to remove all or all-but-one header rows