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battery operation optimization

Project description

Code style: black

batteryopt is a battery operation optimization tool developed by Jakub Szcześniak and implemented by Samuel Letellier-Duchesne. The objective is to minimize the annual electricity costs of a battery-integrated PV system using a Mixed-Integer Linear Program (MILP). The algorithm is implemented using the pyomo library opening up the model to a large array of solvers (e.g.: Gurobi, GLPK, etc.).

Installation

conda create --name batteryopt python=3.7  # tested with 3.7, 3.8 and 3.9
conda activate batteryopt
git clone https://github.com/MITSustainableDesignLab/batteryopt.git
cd batteryopt
python setup.py install

Usage

Type batteryopt --help to access the command line options

Output

batteryopt outputs an Excel file with the model Variables for each time step of the year:

t tf M P_dmd P_elec P_pv Buying Charging Discharging E_s P_charge P_discharge P_dmd_unmet P_grid P_pv_excess P_pv_export
0 1 nan nan 60536.5 0.0002624 0 1 0 0 20000 -0 -0 60536.5 60536.5 0 0
1 1 1 nan 60536.5 0.0002624 0 1 0 0 20000 -0 0 60536.5 60536.5 0 0
2 1 1 nan 60536.5 0.0002624 0 1 0 0 20000 -0 0 60536.5 60536.5 0 0
3 1 1 nan 60536.5 0.0002624 0 1 0 0 20000 -0 0 60536.5 60536.5 0 0
4 1 1 nan 60536.5 0.0002624 0 1 0 0 20000 -0 0 60536.5 60536.5 0 0

The column names are:

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