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Modeling and Comparative Analysis of Multi-Agent Cost Allocation Strategies Using Cooperative Game Theory for the Modern Electricity Market

Author

Listed:
  • Smita Shandilya

    (Department of Electrical and Electronics, Sagar Institute of Research and Technology, Bhopal 462041, India)

  • Zdzislaw Szymanski

    (Department of Management, University of Social Sciences, 03-815 Lodz, Poland)

  • Shishir Kumar Shandilya

    (School of Computing Science and Engineering, VIT Bhopal University, Bhopal 466114, India)

  • Ivan Izonin

    (Department of Artificial Intelligence, Lviv Polytechnic National University, 79013 Lviv, Ukraine)

  • Krishna Kant Singh

    (Faculty of Engineering & Technology, Jain (Deemed-to-be University), Bengaluru 560069, India)

Abstract

The electrical market scenario has changed drastically in the last decade. In the presence of increased competition and less tolerant players, more sophisticated methods are required to balance the diversity and differential pricing while promoting cooperation among the agents. In the monopolistic environment, the central utility incurred the total cost of the transmission expansion. But as the current scenario demands, there are several public and private market players. The growth will benefit all the players, so the total cost in transmission expansion can be divided among players as per the benefit received by each player. In this paper, a transmission system expansion planning problem in the cooperative environment using cooperative game theory (CGT) is framed for the power sector, in which various players can cooperate in a coordinated manner to maximize their benefit but ultimately strengthen the power grid. In this paper, we have modeled, analyzed and compared various cost allocation methods of cooperative game theory specifically for the cost allocation in a transmission expansion planning problem. The present work focuses on forming coalitions to calculate the costs using the forward search and frog leap optimization approach. We have compared the SCRB, BSV, ENSC, and ACA methods for transmission expansion planning while attempting to satisfy the axioms. We have also observed that bilateral Shapely value efficiently allocated the costs due to its decentralized approach and the sequencing of coalition formations to achieve the best possible cost allocations.

Suggested Citation

  • Smita Shandilya & Zdzislaw Szymanski & Shishir Kumar Shandilya & Ivan Izonin & Krishna Kant Singh, 2022. "Modeling and Comparative Analysis of Multi-Agent Cost Allocation Strategies Using Cooperative Game Theory for the Modern Electricity Market," Energies, MDPI, vol. 15(7), pages 1-14, March.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:7:p:2352-:d:778002
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    References listed on IDEAS

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    1. Churkin, Andrey & Bialek, Janusz & Pozo, David & Sauma, Enzo & Korgin, Nikolay, 2021. "Review of Cooperative Game Theory applications in power system expansion planning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    2. Pablo David Necoechea-Porras & Asunción López & Juan Carlos Salazar-Elena, 2021. "Deregulation in the Energy Sector and Its Economic Effects on the Power Sector: A Literature Review," Sustainability, MDPI, vol. 13(6), pages 1-23, March.
    3. Otten, G.J.M., 1993. "Characterizations of a Game Theoretical Cost Allocation Method," Other publications TiSEM 18a0262e-a6d3-4bd9-bdb0-6, Tilburg University, School of Economics and Management.
    4. Otten, G.J.M., 1993. "Characterizations of a Game Theoretical Cost Allocation Method," Discussion Paper 1993-37, Tilburg University, Center for Economic Research.
    5. Otten, G.J., 1993. "Characterizations of a Game Theoretical Cost Allocation Methods," Papers 9337, Tilburg - Center for Economic Research.
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    2. Alrobaian, Abdulrahman A. & Alsagri, Ali Sulaiman, 2023. "Multi-agent-based energy management for a fully electrified residential consumption," Energy, Elsevier, vol. 282(C).
    3. Robert P. Gilles & Lina Mallozzi, 2023. "Game Theoretic Foundations of the Gately Power Measure for Directed Networks," Games, MDPI, vol. 14(5), pages 1-19, September.

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