Proposed a mathematical model for optimizing the profits and emissions while setting dynamic prices of electricity. A bilevel & multi-objective model is proposed for maximizing profits of retailer, minimizing the emissions produced, & minimizing the total cost of customers. Our models use Time-of-Use(TOU) price structure of Demand Response Management. We use following as the input data parameters.
demand_profile.csv
contains the hourly demand for electricity in kWh. The Rows represent customers & each column corresponds hours beginning from 00:00 to 23:00.fuel_properties.csv
contains the attributes of fuels used in the thermal power plants. The attributes are unit costs, unit electricity produced, unit emissions prodcued.
Model Building.ipynb
contains the Python script for data storing and optimization building. Here I have built several user defined function to solve the models. Please note here to execute this file you first need to install the mathematical solver Gurobi. For installation please visit Gurobi
Use Data Visualization.ipynb
for the visualzation & summary of the results obtained from the models. For any further queries please contact me.