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A Stackelberg Game-Based Approach for Transactive Energy Management in Smart Distribution Networks

Author

Listed:
  • Sara Haghifam

    (Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz 51368, Iran)

  • Kazem Zare

    (Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz 51368, Iran)

  • Mehdi Abapour

    (Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz 51368, Iran)

  • Gregorio Muñoz-Delgado

    (E.T.S. de Ingeniería Industrial, University of Castilla–La Mancha, 13071 Ciudad Real, Spain)

  • Javier Contreras

    (E.T.S. de Ingeniería Industrial, University of Castilla–La Mancha, 13071 Ciudad Real, Spain)

Abstract

Recently, with the penetration of numerous Distributed Energy Resources (DER) in Smart Distribution Networks (SDN), Local Transactive Markets have emerged. Exchanging energy between all participants of local markets results in the satisfaction of producers and consumers. Based on these issues, this study provides a novel framework for the participation of SDN-independent entities in wholesale and local electricity markets simultaneously. In this regard, the considered system’s players, namely Distribution System Operator (DSO) and DER Aggregator (AG), take part within local as well as wholesale markets in two-day ahead and real-time stages. Moreover, to deal with the inherent conflict between the existing players’ interests, a Stackelberg game-based technique is proposed. In the raised competition, the leader, DSO, attempts to minimize its operating costs, while the follower, DER AG, tends to maximize its profit. Therefore, actors’ actions choices within both markets are made non-cooperatively. On the other hand, to handle the uncertain nature of stochastic parameters in the depicted problem, Monte Carlo Simulation (MCS), together with a fast backward/forward scenario reduction approach, is exploited. Ultimately, to evaluate the efficiency of the proposed scheme, two different case studies, with and without considering the competitive environment, are implemented on a modified IEEE-33 bus SDN.

Suggested Citation

  • Sara Haghifam & Kazem Zare & Mehdi Abapour & Gregorio Muñoz-Delgado & Javier Contreras, 2020. "A Stackelberg Game-Based Approach for Transactive Energy Management in Smart Distribution Networks," Energies, MDPI, vol. 13(14), pages 1-34, July.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:14:p:3621-:d:384336
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    References listed on IDEAS

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    4. Mario Tovar & Miguel Robles & Felipe Rashid, 2020. "PV Power Prediction, Using CNN-LSTM Hybrid Neural Network Model. Case of Study: Temixco-Morelos, México," Energies, MDPI, vol. 13(24), pages 1-15, December.

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