A Review of Agent-Based Models for Energy Commodity Markets and Their Natural Integration with RL Models
Agent-based models are a flexible and scalable modeling approach employed to study and describe the evolution of complex systems in different fields, such as social sciences, engineering, and economics. In the latter, they have been largely employed to model financial markets with a bottom-up approa...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-06-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/18/12/3171 |
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| author | Silvia Trimarchi Fabio Casamatta Laura Gamba Francesco Grimaccia Marco Lorenzo Alessandro Niccolai |
| author_facet | Silvia Trimarchi Fabio Casamatta Laura Gamba Francesco Grimaccia Marco Lorenzo Alessandro Niccolai |
| author_sort | Silvia Trimarchi |
| collection | DOAJ |
| description | Agent-based models are a flexible and scalable modeling approach employed to study and describe the evolution of complex systems in different fields, such as social sciences, engineering, and economics. In the latter, they have been largely employed to model financial markets with a bottom-up approach, with the aim of understanding the price formation mechanism and to generate market scenarios. In the last few years, they have found application in the analysis of energy markets, which have experienced profound transformations driven by the introduction of energy policies to ease the penetration of renewable energy sources and the integration of electric vehicles and by the current unstable geopolitical situation. This review provides a comprehensive overview of the application of agent-based models in energy commodity markets by defining their characteristics and highlighting the different possible applications and the open-source tools available. In addition, it explores the possible integration of agent-based models with machine learning techniques, which makes them adaptable and flexible to the current market conditions, enabling the development of dynamic simulations without fixed rules and policies. The main findings reveal that while agent-based models significantly enhance the understanding of energy market mechanisms, enabling better profit optimization and technical constraint coherence for traders, scaling these models to highly complex systems with a large number of agents remains a key limitation. |
| format | Article |
| id | doaj-art-cd41cd02a2f546bca45c59c3572f1f30 |
| institution | Matheson Library |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-cd41cd02a2f546bca45c59c3572f1f302025-06-25T13:45:50ZengMDPI AGEnergies1996-10732025-06-011812317110.3390/en18123171A Review of Agent-Based Models for Energy Commodity Markets and Their Natural Integration with RL ModelsSilvia Trimarchi0Fabio Casamatta1Laura Gamba2Francesco Grimaccia3Marco Lorenzo4Alessandro Niccolai5Department of Energy, Politecnico di Milano, Via Lambruschini, 4, 20156 Milan, ItalyBU Trading and Execution, A2A S.p.A., Corso di Porta Vittoria 4, 20122 Milan, ItalyBU Trading and Execution, A2A S.p.A., Corso di Porta Vittoria 4, 20122 Milan, ItalyDepartment of Energy, Politecnico di Milano, Via Lambruschini, 4, 20156 Milan, ItalyBU Trading and Execution, A2A S.p.A., Corso di Porta Vittoria 4, 20122 Milan, ItalyDepartment of Energy, Politecnico di Milano, Via Lambruschini, 4, 20156 Milan, ItalyAgent-based models are a flexible and scalable modeling approach employed to study and describe the evolution of complex systems in different fields, such as social sciences, engineering, and economics. In the latter, they have been largely employed to model financial markets with a bottom-up approach, with the aim of understanding the price formation mechanism and to generate market scenarios. In the last few years, they have found application in the analysis of energy markets, which have experienced profound transformations driven by the introduction of energy policies to ease the penetration of renewable energy sources and the integration of electric vehicles and by the current unstable geopolitical situation. This review provides a comprehensive overview of the application of agent-based models in energy commodity markets by defining their characteristics and highlighting the different possible applications and the open-source tools available. In addition, it explores the possible integration of agent-based models with machine learning techniques, which makes them adaptable and flexible to the current market conditions, enabling the development of dynamic simulations without fixed rules and policies. The main findings reveal that while agent-based models significantly enhance the understanding of energy market mechanisms, enabling better profit optimization and technical constraint coherence for traders, scaling these models to highly complex systems with a large number of agents remains a key limitation.https://www.mdpi.com/1996-1073/18/12/3171agent-based modelingenergy commodity marketsmulti-agent systemsreinforcement learningmarket simulation |
| spellingShingle | Silvia Trimarchi Fabio Casamatta Laura Gamba Francesco Grimaccia Marco Lorenzo Alessandro Niccolai A Review of Agent-Based Models for Energy Commodity Markets and Their Natural Integration with RL Models Energies agent-based modeling energy commodity markets multi-agent systems reinforcement learning market simulation |
| title | A Review of Agent-Based Models for Energy Commodity Markets and Their Natural Integration with RL Models |
| title_full | A Review of Agent-Based Models for Energy Commodity Markets and Their Natural Integration with RL Models |
| title_fullStr | A Review of Agent-Based Models for Energy Commodity Markets and Their Natural Integration with RL Models |
| title_full_unstemmed | A Review of Agent-Based Models for Energy Commodity Markets and Their Natural Integration with RL Models |
| title_short | A Review of Agent-Based Models for Energy Commodity Markets and Their Natural Integration with RL Models |
| title_sort | review of agent based models for energy commodity markets and their natural integration with rl models |
| topic | agent-based modeling energy commodity markets multi-agent systems reinforcement learning market simulation |
| url | https://www.mdpi.com/1996-1073/18/12/3171 |
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