The battery scheduling problem is about deciding when to charge and discharge a behind-the-meter battery to maximize profit (or minimize cost) given predictions of time-dependent electricity prices (tariffs). In this notebook, we also consider photovoltaic (PV) generation and the technical constraints of the battery.
This notebook provides a beginner-friendly introduction to battery scheduling using mathematical optimization and Gurobi. Basic knowledge about mathematical optimization and Python programming are required as taught in Optimization 101 for Data Scientists as well as the basics in battery energy management.
Click on the button below to access the example in Google Colab, which is a free, online Jupyter Notebook environment that allows you to write and execute Python code through your browser.Â
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