Agent-based modeling: Insights into consumer behavior, urban dynamics, grid management, and market interactions
A future sustainable energy system is expected to be digital, de-central, de-carbonized, and democratized. As the transition unfolds, new and diverse actors of various sizes will emerge in different segments. Thereby, the future energy system could shift its attention to the actors’ behavior than fi...
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| Format: | Article |
| Language: | English |
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Elsevier
2025-01-01
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| Series: | Energy Strategy Reviews |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2211467X24003225 |
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| author | Sambeet Mishra Thiago Lima Silva Lars Hellemo Stefan Jaehnert Lars Even Egner Sobah Abbas Petersen Tim Signer Florian Zimmermann Chiara Bordin |
| author_facet | Sambeet Mishra Thiago Lima Silva Lars Hellemo Stefan Jaehnert Lars Even Egner Sobah Abbas Petersen Tim Signer Florian Zimmermann Chiara Bordin |
| author_sort | Sambeet Mishra |
| collection | DOAJ |
| description | A future sustainable energy system is expected to be digital, de-central, de-carbonized, and democratized. As the transition unfolds, new and diverse actors of various sizes will emerge in different segments. Thereby, the future energy system could shift its attention to the actors’ behavior than finding an optimum based on the physical system. Agent based modeling tools can reflect decisions from several actors in a decentralized and digital market setting. Then, such tools can enable a sustainable energy transition.This work sets out to investigate how agent-based models could tackle various challenges in energy transition. This investigation covers four segments of the energy system — consumer, city, microgrid, and market. It starts with the consumer where consumer behavior is modeled. From there, expands to a city level where the dynamic characteristics of a city are simulated. The next step is distributed microgrids, particularly how to optimally plan the grid expansions. The final step in the investigation is simulating an energy market with national and international stakeholders. The selection of models presents how agent-based models can be applied to decision-making processes in the aforementioned segments. Then a novel framework with metrics for characterization is proposed and validated that addresses the challenge — which are the characteristics that make an agent-based model a better fit to tackle a modeling objective? Additionally, the framework identifies the existing knowledge gaps and the scope for further developments.In summary, this work outlines how far agent-based models have come to tackle energy system challenges to sustain the energy transition. This work specifically highlights the scope, advantages, challenges, and trends of the agent-based models in energy sector applications. Moreover, this study finds that agent-based models reflect what a solution could be more than the traditional modeling practice that focuses on what a solution should be. |
| format | Article |
| id | doaj-art-aefa99c267514c68b56317920a856a3a |
| institution | Kabale University |
| issn | 2211-467X |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Energy Strategy Reviews |
| spelling | doaj-art-aefa99c267514c68b56317920a856a3a2025-01-05T04:27:56ZengElsevierEnergy Strategy Reviews2211-467X2025-01-0157101613Agent-based modeling: Insights into consumer behavior, urban dynamics, grid management, and market interactionsSambeet Mishra0Thiago Lima Silva1Lars Hellemo2Stefan Jaehnert3Lars Even Egner4Sobah Abbas Petersen5Tim Signer6Florian Zimmermann7Chiara Bordin8SINTEF Energy Research, Norway; University of South-Eastern Norway (USN), Norway; Corresponding author at: SINTEF Energy Research, Norway.SINTEF Industry, NorwayNorwegian University of Science and Technology (NTNU), NorwaySINTEF Energy Research, NorwayNorwegian University of Science and Technology (NTNU), NorwayNorwegian University of Science and Technology (NTNU), NorwayKarlsruhe Institute of Technology (KIT), GermanyKarlsruhe Institute of Technology (KIT), GermanyUiT: The Arctic University of Norway, NorwayA future sustainable energy system is expected to be digital, de-central, de-carbonized, and democratized. As the transition unfolds, new and diverse actors of various sizes will emerge in different segments. Thereby, the future energy system could shift its attention to the actors’ behavior than finding an optimum based on the physical system. Agent based modeling tools can reflect decisions from several actors in a decentralized and digital market setting. Then, such tools can enable a sustainable energy transition.This work sets out to investigate how agent-based models could tackle various challenges in energy transition. This investigation covers four segments of the energy system — consumer, city, microgrid, and market. It starts with the consumer where consumer behavior is modeled. From there, expands to a city level where the dynamic characteristics of a city are simulated. The next step is distributed microgrids, particularly how to optimally plan the grid expansions. The final step in the investigation is simulating an energy market with national and international stakeholders. The selection of models presents how agent-based models can be applied to decision-making processes in the aforementioned segments. Then a novel framework with metrics for characterization is proposed and validated that addresses the challenge — which are the characteristics that make an agent-based model a better fit to tackle a modeling objective? Additionally, the framework identifies the existing knowledge gaps and the scope for further developments.In summary, this work outlines how far agent-based models have come to tackle energy system challenges to sustain the energy transition. This work specifically highlights the scope, advantages, challenges, and trends of the agent-based models in energy sector applications. Moreover, this study finds that agent-based models reflect what a solution could be more than the traditional modeling practice that focuses on what a solution should be.http://www.sciencedirect.com/science/article/pii/S2211467X24003225Agent based modelingEnergy system modelingEnergy transitionEnergy strategyDecision support system |
| spellingShingle | Sambeet Mishra Thiago Lima Silva Lars Hellemo Stefan Jaehnert Lars Even Egner Sobah Abbas Petersen Tim Signer Florian Zimmermann Chiara Bordin Agent-based modeling: Insights into consumer behavior, urban dynamics, grid management, and market interactions Energy Strategy Reviews Agent based modeling Energy system modeling Energy transition Energy strategy Decision support system |
| title | Agent-based modeling: Insights into consumer behavior, urban dynamics, grid management, and market interactions |
| title_full | Agent-based modeling: Insights into consumer behavior, urban dynamics, grid management, and market interactions |
| title_fullStr | Agent-based modeling: Insights into consumer behavior, urban dynamics, grid management, and market interactions |
| title_full_unstemmed | Agent-based modeling: Insights into consumer behavior, urban dynamics, grid management, and market interactions |
| title_short | Agent-based modeling: Insights into consumer behavior, urban dynamics, grid management, and market interactions |
| title_sort | agent based modeling insights into consumer behavior urban dynamics grid management and market interactions |
| topic | Agent based modeling Energy system modeling Energy transition Energy strategy Decision support system |
| url | http://www.sciencedirect.com/science/article/pii/S2211467X24003225 |
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