Data base for the Expansion Planning of a Price-Maker Virtual Power Plant in Energy and Reserve Markets

This database contains essential data for developing the problem addressed in the thesis titled "Stochastic Bilevel Models for Strategic Expansion Planning of Virtual Power Plants." The loaded data includes the file "representative_days.csv," which contains representative days from the year 2020, selected through a clustering method based on k-medoids. The file "Capacity_Factors_of_Renewable_Energy_Generation.csv" provides the energy production data for both solar PV and wind energy during the representative days of 2020.

The files "Power_Bids_Offered_to_the_DA_Market_by_Demands.csv" and "Power_Bids_Offered_to_the_DA_Market_by_Producers.csv" contain 24-hour block data for the 10 representative days of the day-ahead electricity market clearing. The files "Power_Bids_Offered_to_the_Reserve_Market_by_Agents.csv" and "Reserve_Capacity_Required_in_the_Reserve_Market.csv" include 24-hour block data for the 10 representative days of the reserve market clearing.

Additionally, the file "Flexible_Demand_Consumption_Levels.csv" contains the consumption limits for flexible demand in the VPP, while the file "Reserve_deployment_request_parameter.csv" includes a set of scenarios for the reserve deployment request used in Chapter 2. Finally, the file "Generated_scenarios_for_variable_costs_of_conventional_power_plants.csv" contains the scenarios generated for the variable costs of conventional power plants, used in Chapter 3.