CAISO wind data file examples

Sample Command 1:

The following command will take the data from wind_total_forecast_actual_070113_063015.csv, and launch the simulations with n=3 and s=1234 from forecasts to actuals using an iid Base Process. It will compute the distribution from 2014-7-1 00:00:00 to 2014-8-1 00:00:00 and simulate from 2014-7-2 00:00:00 to 2014-7-31 00:00:00. Finally, it will return a plot of simulations, and create an output dir called “wind_actuals_iid” in your current working directory.

python -m mape_maker -xf "mape_maker/samples/wind_total_forecast_actual_070113_063015.csv" -f "actuals" -n 3 -bp "iid" -o "wind_actuals_iid" -is "2014-7-1 00:00:00" -ie "2014-8-1 00:00:00" -ss "2014-7-2 00:00:00" -se "2014-7-31 00:00:00" -s 1234
  • -xf “mape_maker/samples/wind_total_forecast_actual_070113_063015.csv”:
The csv file containing forecasts and actuals for specified datetimes.
  • -f “actuals”:
Set up the the target of the simulation as “actuals”. So the MapeMaker will simulate the “actuals” data according to the “forecasts” data in the input file.
  • -n 3:
The number of simulations that we want to create is “3”. This will create three simulation columns in the output file.
  • -bp “iid”:
Use “iid” as the base process. The default base process is set as “ARMA”.
  • -is “2014-7-1 00:00:00”:
The start date for the computation of the distributions is “2014-7-1 00:00:00”
  • -ie “2014-8-1 00:00:00”:
The end date for the computation of the distributions is “2014-8-1 00:00:00”
  • -ss “2014-7-2 00:00:00”:
The start date of the simulation is “2014-7-2 00:00:00”
  • -se “2014-7-31 00:00:00”:
The end date of the simulation is “2014-7-31 00:00:00”
  • -s 1234:
Set the seed as “1234”, so it won’t randomly choose a number as the seed.
  • -o “wind_actuals_iid”:
Create an output directory called “wind_actuals_iid”, in which will store the simulation output file.

After running the command line, you should see a similar plot like this:

../_images/wind_actuals_iid_with_dates.png


Sample Command 2:

The following command will take the data from wind_total_forecast_actual_070113_063015.csv , and launch the simulations with n=3 and seed=1234 from forecasts to actuals using an ARMA Base Process. It will simulate all the dates in the input files. Finally, it will return a plot of simulations, and create an output dir called “wind_actuals_ARMA”.

python -m mape_maker -xf "mape_maker/samples/wind_total_forecast_actual_070113_063015.csv" -f "actuals" -n 3 -bp "ARMA" -o "wind_actuals_ARMA" -s 1234
  • -xf “mape_maker/samples/wind_total_forecast_actual_070113_063015.csv”:
The csv file containing forecasts and actuals for specified datetimes.
  • -f “actuals”:
Set up the the target of the simulation as “actuals”. So the MapeMaker will simulate the “actuals” data according to the “forecasts” data in the input file.
  • -n 3:
The number of simulations that we want to create is “3”. This will create three simulation columns in the output file.
  • -bp “ARMA”:
Use “ARMA” as the base process.
  • -o “wind_actuals_ARMA”:
Create an output directory called “wind_actuals_ARMA”, in which will store the simulation output file.
  • -s 1234:
Set the seed as “1234”, so it won’t randomly choose a number as the seed.

After running the command line, you should see a similar plot like this:

../_images/wind_actuals_ARMA_without_dates.png