Introducing energy-py-linear
A Python library for optimizing energy systems using mixed integer linear programming.
This post introduces energy-py-linear - a Python library for optimizing energy assets using mixed integer linear programming (MILP).
Why Linear Programming?
Linear programming is a popular choice for solving many energy industry problems - many energy systems can be modelled as linear, and suitable for optimization using linear solvers.
Linear models have the quality that if a feasible solution exists, it exists on the boundary of a constraint. This makes solving linear programs fast in practice. The optimization itself is also deterministic - it doesn’t rely on randomness like gradient descent.
What can energypylinear do?
- optimize the dispatch of electric batteries, electric vehicle charging and gas fired CHP generators,
- optimize for either price or carbon,
- calculate the variance between two simulations.
You can find the source code for energypylinear at ADGEfficiency/energy-py-linear.