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Hierarchical Blockchain Energy Trading Platform and Microgrid Management Optimization

Author

Listed:
  • Kristián Košt’ál

    (Institute of Computer Engineering and Applied Informatics, Faculty of Informatics and Information Technologies, Slovak University of Technology, 842 16 Bratislava, Slovakia)

  • Volodymyr Khilenko

    (Institute of Computer Engineering and Applied Informatics, Faculty of Informatics and Information Technologies, Slovak University of Technology, 842 16 Bratislava, Slovakia)

  • Michal Hunák

    (Institute of Computer Engineering and Applied Informatics, Faculty of Informatics and Information Technologies, Slovak University of Technology, 842 16 Bratislava, Slovakia)

Abstract

In this paper, we describe a solution that has been developed to create an intelligent software platform for the optimal management of energy trade (specifically a P2P trade) in microgrids. Furthermore, the choice of a solution based on the architecture of two-level hierarchical systems using the restrictions and recommendations of the control center is substantiated. A general functional design of the platform is proposed using blockchain technology and cyber security solutions. The proposed solution includes the technical specification of the presented platform using the game theory model as a special case without loss of generality. The enhanced learning method was used to simulate customer behavior. Simulation of the platform operation was carried out using the example of optimizing the peak-to-average network load by users making individual decisions using game theory algorithms. The simulation results of the implementation of scenarios with and without recommendations confirmed that the proposed model provides a better peak-to-average ratio (PAR) in the network.

Suggested Citation

  • Kristián Košt’ál & Volodymyr Khilenko & Michal Hunák, 2024. "Hierarchical Blockchain Energy Trading Platform and Microgrid Management Optimization," Energies, MDPI, vol. 17(6), pages 1-18, March.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:6:p:1333-:d:1354741
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