Example model_inputs.xlsx file?

[williamhobbs]

Is an example version of model_inputs.xlsx with generic inputs available? I think that would help new users get familiar with the package.

[Edit] Understanding that the example file would leave NREL API email and key fields blank and users would need to populate those values.

Thanks.

[grgmiller]

Hi William - thanks for this excellent suggestion. We'll look into this and see if we can get something added to the repo soon.

[ktehranchi]

Hi Greg... I'm finding that the example input file has an error. Seems like solar runs with SAM but we get an error on wind.

ValueError                                Traceback (most recent call last)
[/Users/kamrantehranchi/Local_Documents/MATCH-model/match_model/notebooks/run_scenarios.ipynb](https://file+.vscode-resource.vscode-cdn.net/Users/kamrantehranchi/Local_Documents/MATCH-model/match_model/notebooks/run_scenarios.ipynb) Cell 6 line 3
     33             generate_input_files.generate_inputs(model_workspace)
     34     else:
...
--> 131         raise ValueError(field_name.lower() + " required for wind data")
    132     data_dict['fields'].append(field_names.index(field_name.lower()) + 1)
    134 data_dict['data'] = []

ValueError: 2012 required for wind data

Any tips?

[ktehranchi]

Full Traceback

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
[/Users/kamrantehranchi/Local_Documents/MATCH-model/match_model/notebooks/run_scenarios.ipynb](https://file+.vscode-resource.vscode-cdn.net/Users/kamrantehranchi/Local_Documents/MATCH-model/match_model/notebooks/run_scenarios.ipynb) Cell 6 line 3
     33             generate_input_files.generate_inputs(model_workspace)
     34     else:
---> 35         generate_input_files.generate_inputs(model_workspace)
     36 # if the directory does not exist, generate the input files
     37 else:
     38     print("Generating inputs now...")

File [~/Local_Documents/MATCH-model/match_model/generate_input_files.py:863](https://file+.vscode-resource.vscode-cdn.net/Users/kamrantehranchi/Local_Documents/MATCH-model/match_model/notebooks/~/Local_Documents/MATCH-model/match_model/generate_input_files.py:863), in generate_inputs(model_workspace)
    860 elif sam_function == "windpower":
    861     # run PySAM to simulate the solar outputs
    862     import pdb; pdb.set_trace()
--> 863     wind_vcf = simulate_wind_generation(
    864         nrel_api_key,
    865         nrel_api_email,
    866         resource_dict,
    867         config_dict,
    868         resource_years,
    869         pysam_dir,
    870         tz_offset,
    871     )
    873     # add the data to the dataframe
    874     df_vcf = df_vcf.merge(
    875         wind_vcf, how="left", left_index=True, right_index=True
    876     )

File [~/Local_Documents/MATCH-model/match_model/generate_input_files.py:1643](https://file+.vscode-resource.vscode-cdn.net/Users/kamrantehranchi/Local_Documents/MATCH-model/match_model/notebooks/~/Local_Documents/MATCH-model/match_model/generate_input_files.py:1643), in simulate_wind_generation(nrel_api_key, nrel_api_email, resource_dict, config_dict, resource_years, input_dir, tz_offset)
   1640 wtk_path_dict = wtkfetcher.resource_file_paths_dict
   1642 for filename in wtk_path_dict:
-> 1643     windResource = tools.SRW_to_wind_data(wtk_path_dict[filename])
   1645     # assign the wind resource input data to the model
   1646     system_model_wind.Resource.wind_resource_data = windResource

File [~/mambaforge/envs/match_model/lib/python3.10/site-packages/PySAM/ResourceTools.py:131](https://file+.vscode-resource.vscode-cdn.net/Users/kamrantehranchi/Local_Documents/MATCH-model/match_model/notebooks/~/mambaforge/envs/match_model/lib/python3.10/site-packages/PySAM/ResourceTools.py:131), in SRW_to_wind_data(filename)
    129 for field_name in fields:
    130     if field_name.lower() not in field_names:
--> 131         raise ValueError(field_name.lower() + " required for wind data")
    132     data_dict['fields'].append(field_names.index(field_name.lower()) + 1)
    134 data_dict['data'] = []