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A Multi-agent Simulation Model Considering the Bounded Rationality of Market Participants: An Example of GENCOs Participation in the Electricity Spot Market

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Multi-Agent-Based Simulation XXIV (MABS 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14558))

Abstract

The concept of bounded rationality has garnered substantial attention and interest from scholars since its inception. It is widely recognized that in complex systems, decision-making by its members is bounded by cognitive limitations. In this context, multi-agent simulation has emerged as a popular tool to model complex systems. One important question is how to incorporate the bounded rationality of market participants in such simulations. This paper introduces a novel multi-agent simulation model that incorporates the bounded rationality of generation companies (GENCOs) in electricity markets. We also propose evaluation metrics to quantify the differences in simulation outcomes between the proposed model and agent-based models that overlook bounded rationality, assessing the performance of market mechanisms when facing the bounded rationality of GENCOs. Using the inability of power generators to accurately predict future load curves as an illustration of bounded rationality, we conduct numerical simulation experiments on various electricity market compensation fee mechanisms. The simulation results demonstrate the effectiveness of the proposed simulation model and evaluation metrics.

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Pan, Z., Jing, Z., Ji, T., Song, Y. (2024). A Multi-agent Simulation Model Considering the Bounded Rationality of Market Participants: An Example of GENCOs Participation in the Electricity Spot Market. In: Nardin, L.G., Mehryar, S. (eds) Multi-Agent-Based Simulation XXIV. MABS 2023. Lecture Notes in Computer Science(), vol 14558. Springer, Cham. https://doi.org/10.1007/978-3-031-61034-9_9

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  • DOI: https://doi.org/10.1007/978-3-031-61034-9_9

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  • Print ISBN: 978-3-031-61033-2

  • Online ISBN: 978-3-031-61034-9

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