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auction-vs-continuous

Code for operating auction-based and continuous local flexibility markets considering block bids and network constraints. The code is associated with the paper Auction-Based vs Continuous Clearing in Local Flexibility Markets with Block Bids by A. Alarcón Cobacho et al.

Case Study files

  • network33bus.xlsx: Network data.
  • Bids_energy_33.xlsx: Flexibility bids submitted (offers and requests).
  • Setpoint.xlsx: Initial setpoint of the grid.

Market clearing

The script Scenarios_generation.py calls the rest of the algorithms. It operates the auction-based and continuous clearing models for several scenarios with and without considering block bids and network constraints. Its ouputs (total social welfare, energy volume traded and computational time) are stored in the dataframe results.

  • arrival_creation.py creates random arrival sequences for the bids in Bids_energy_33.xlsx.
  • Continuous_Energy_BB.py is the continuous clearing model, that uses PTDF_check.py to check network constraints and BB_match.py and BB_match_WithoutNC.py to match block bids.
  • Auction_Energy_BB.py and Auction_Energy_WithoutNC.py are the auction-based clearing models that trade block bids with and without network constraints.

Suboptimality gap

In the folder Worst and best sequences, the script Worst_Best_Sequence.py can be run to determine the worst and best social welfare that can be obtained with the continuous market clearing. A parameter allows to choose between worst and best. The other files are the data files for the 5-bus test case run in the paper.

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