MilicaKov
commented
5 months ago Description of repository
Python code is designed to minimize the electricity cost associated with charging an electric vehicle (EV) battery over 24 hours. The function takes as input the prices of electricity throughout the day, the arrival time of the EV, the state of charge (SOC) of the EV battery upon arrival, and the hours needed to fully charge the battery (H). It utilizes the PuLP library for linear programming to optimize the charging schedule, aiming to minimize the total cost while ensuring that the battery is fully charged by the specified time.
The code begins by defining the problem as a linear programming minimization task. Decision variables are created to represent whether the EV is charging during each time slot. The objective function is formulated to minimize the total electricity cost based on the charging schedule and electricity prices. Constraints are imposed to ensure that the battery is fully charged by the required time and that the charging operation occurs only when needed, taking into account the current SOC.
Once the optimization problem is defined, it is solved using the PuLP solver. The optimal charging schedule and total cost are then extracted from the solution. Finally, the code generates a visual representation of the electricity prices and the optimal charging schedule using Matplotlib, with the prices plotted on one y-axis and the charging schedule on another, providing a clear visualization of the optimized charging strategy.
Tests
- [x] License exists
- [x] Create a fork and start a pull-request
- [x] Pytests passed as expected
- [x] Ruff linter passed as expected
Please review, @MilicaKov