This repository has the code and related material that I am using in my PyPSA project related to a 100% renewable, reliable energy system for Oahu
Link to Zenodo archive of repo:
The following is a description of the contents of each folder:
Data Processing: Code that performed the necessary functions to turn weather data into capacity factors
- Finished, processed weather capacity factors and electricity demand input files are in the Input Data folder.
- Each subfolder contains detailed instructions on how to run the data processing scripts
Input Data: The energy demand or weather capacity files used as inputs for PyPSA
Output Data: The output files for each analysis
- First workbook tab in the output data .xlsx is an exact copy of the model input parameters xlsx fed into PyPSA
Plotting Code: The code used to make each graph. Broken down by figure.
HPCC: Code, information, and inputs needed to run PyPSA on Caltech's high performance computing cluster
- Optional, PyPSA runs fine on desktop
To run an optimization via PyPSA:
- Download clab_pypsa on your system as described in the submodule (will create a folder)
- Put weather capacity factors and electricity demand input files from the above "Input Data" GitHub folder (as .csv) into the clab_pypsa folder
- Put Gurobi license file and model input parameters .xlsx file from the above "Output Data" Github folder in the folder that contains the clab_pypsa folder (not in the clab_pypsa folder)
- In command terminal, type "conda activate pypsa_table"
- Then "python clab_pypsa/run_pypsa.py -f filename.xlsx" <-- filename is the name of the .xlsx model input parameters file.
- Enjoy