Uses data from the data driven battery scheduling competition; introduces battery scheduling using MILP; compares to the find optimisation method I developed for the competition
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Optimizing_battery_schedule_using_pyomo.ipynb
README.md
Running_all_sites_and_forecasts_DD_comp.ipynb
battery.py
metadata.csv
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README.md

MILP_vs_Find_batt_scheduler

Uses data from the data driven battery scheduling competition; introduces battery scheduling using MILP.

Firstly, unzip the submit.csv file and put the contained csv files in the submit folder.
Secondly, run the Optimizing_battery_schedule_using_pyomo.ipynb file.

Hopefully the code is pretty well documented in the notebook. This post (http://energystoragesense.com/uncategorized/scheduling_batt_optimisation/) accompanies the code.