EV-pricing

In this repository we include the code and data used in our experiments for the paper: Why Do Pricing Rules Matter? Electricity Market Design with Electric Vehicle Participants.

This paper has been submitted to the special issue Electric Vehicles Integration in Smart Grids at the World Electric Vehicle Journal.

Python libraries required

• pandas
• numpy
• matplotlib
• ortools

  python -m pip install --upgrade --user ortools

Data set

In the folder data, there are 4 different data files, one per each scenario from the paper:

1.  *Data_EV_Paper_S1.xlsx* for Scenario 1, used as reference (no EVs, no demand response)
2.  *Data_EV_Paper_S2.xlsx* for Scenario 2 (EVs, no demand response)
3.  *Data_EV_Paper_S3.xlsx* for Scenario 3 (EVs and demand response).

Additionally the file Data_Khodayar.xlsx is included. We used this dataset (associated to the paper: Electric Vehicle Mobility in Transmission-Constrained Hourly Power Generation Scheduling, Khodayar et al (2013)) to adapt it for the settings in our experiments, detailed as below:

• The 3-node structure is included here as per Figure 2. in the paper (Section 6).
• Generation and demand resources are described there. They are also explained in Section 6 (see Table 2)
• Transmission lines (how nodes are connected and the respective capacities) are also included there.
• Electric vehicles parameters as per Table 3 (Section 6) are included here.

The notebook contains:

1. Loading the data (and selecting the correct scenario)
2. Allocation model (as described in Section 5 of the paper)
3. Pricing schemes (it also contains IP+ pricing scheme, although we only use IP and ELM pricing for the experiments in the paper)
4. Results and plots