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Simulation tools for electricity markets considering power flow analysis

Author

Listed:
  • Veiga, Bruno
  • Santos, Gabriel
  • Pinto, Tiago
  • Faia, Ricardo
  • Ramos, Carlos
  • Vale, Zita

Abstract

The share of renewable generation is growing worldwide, increasing the complexity of the grids operation to maintain its stability and balance. This leads to an increased need for designing new electricity markets (EMs) suited to this new reality. Simulation tools are widely used to experiment and analyze the potential impacts of new solutions, such as novel EM designs and power flow analysis and validation. This work introduces two web services for EMs’ simulation and study, in addition to power flow evaluation and validation, namely the Electricity Market Service (EMS) and Power Flow Service (PFS). EMS enables the simulation of two auction-based algorithms and the execution of three wholesale EMs. PFS creates and evaluates electrical grids from the transmission to distribution grids. Being published as web services facilitates their integration with other services, systems, or software agents. Combining them allows for the simulation of EMs from wholesale to local markets and testing if the results are compatible with a specific grid. This article presents a detailed description of each service and a case study of an electricity trading community participating in the MIBEL day-ahead market through an aggregator to reduce their energy bills. The results demonstrate the accuracy and usefulness of the proposed services.

Suggested Citation

  • Veiga, Bruno & Santos, Gabriel & Pinto, Tiago & Faia, Ricardo & Ramos, Carlos & Vale, Zita, 2023. "Simulation tools for electricity markets considering power flow analysis," Energy, Elsevier, vol. 275(C).
    • Handle: RePEc:eee:energy:v:275:y:2023:i:c:s0360544223008885
    DOI: 10.1016/j.energy.2023.127494
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    References listed on IDEAS

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    1. Park, Haryn & Kim, Jin-Kuk & Yi, Sung Chul, 2023. "Optimization of site utility systems for renewable energy integration," Energy, Elsevier, vol. 269(C).
    2. Santos, Gabriel & Pinto, Tiago & Praça, Isabel & Vale, Zita, 2016. "MASCEM: Optimizing the performance of a multi-agent system," Energy, Elsevier, vol. 111(C), pages 513-524.
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