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Multi-agent Electricity Markets and Smart Grids Simulation with Connection to Real Physical Resources

  • Tiago Pinto
  • Zita Vale
  • Isabel Praça
  • Luis Gomes
  • Pedro Faria
Chapter
Part of the Studies in Systems, Decision and Control book series (SSDC, volume 144)

Abstract

The increasing penetration of distributed energy sources, mainly based on renewable generation, calls for an urgent emergence of novel advanced methods to deal with the associated problems. The consensus behind smart grids (SGs) as one of the most promising solutions for the massive integration of renewable energy sources in power systems has led to the development of several prototypes that aim at testing and validating SG methodologies. The urgent need to accommodate such resources require alternative solutions. This chapter presents a multi-agent based SG simulation platform connected to physical resources, so that realistic scenarios can be simulated. The SG simulator is also connected to the Multi-Agent Simulator of Competitive Electricity Markets, which provides a solid framework for the simulation of electricity markets. The cooperation between the two simulation platforms provides huge studying opportunities under different perspectives, resulting in an important contribution to the fields of transactive energy, electricity markets, and SGs. A case study is presented, showing the potentialities for interaction between players of the two ecosystems: a SG operator, which manages the internal resources of a SG, is able to participate in electricity market negotiations to trade the necessary amounts of power to fulfill the needs of SG consumers.

Notes

Acknowledgements

This work has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement N. 641794 (project DREAM-GO). It has also received FEDER Funds through the COMPETE program and National Funds through FCT under the project UID/EEA/00760/2013. The authors gratefully acknowledge the valuable contribution of Bruno Canizes, Daniel Paiva, Gabriel Santos and Marco Silva to the work presented in the chapter.

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Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Tiago Pinto
    • 1
  • Zita Vale
    • 1
  • Isabel Praça
    • 1
  • Luis Gomes
    • 1
  • Pedro Faria
    • 1
  1. 1.GECAD-Research Group on Intelligent Engineering and Computing for Advanced Innovation and DevelopmentInstitute of Engineering, Polytechnic of PortoPortoPortugal

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