Evolutionary Game Theory as a Catalyst in Smart Grids: From Theoretical Insights to Practical Strategies
The increase in the installation of distributed energy resources (DERs) globally has led to a remarkable transformation in the structure of smart grids due to the growing number of energy participants. Recently, electricity markets (EM) have received substantial attention as a viable solution for th...
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IEEE
2024-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/10620210/ |
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| author | Anas Karaki Luluwah Al-Fagih |
| author_facet | Anas Karaki Luluwah Al-Fagih |
| author_sort | Anas Karaki |
| collection | DOAJ |
| description | The increase in the installation of distributed energy resources (DERs) globally has led to a remarkable transformation in the structure of smart grids due to the growing number of energy participants. Recently, electricity markets (EM) have received substantial attention as a viable solution for the complex issue of managing DERs. Modeling the power grid as a complex system of interacting components facilitates investigating the interaction among electricity producers and consumers to maintain the total generation and demand at a balance. In this work, we present a review of the recent advances in adopting evolutionary game theory (EGT), to mitigate challenges in the emerging smart grid, as a decision-making framework for trading dynamics and considering large populations. It includes a taxonomy of various EGT applications in energy trading dynamics, DER management, and policy and infrastructure development. Finally, the linkage between multi-agent reinforcement learning (MARL) and EGT is provided, highlighting their mathematical parallels in the context of smart grid applications. |
| format | Article |
| id | doaj-art-a3dde23f1d094920a59a632cd457f0cf |
| institution | DOAJ |
| issn | 2169-3536 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-a3dde23f1d094920a59a632cd457f0cf2025-08-20T02:49:09ZengIEEEIEEE Access2169-35362024-01-011218692618694010.1109/ACCESS.2024.343693510620210Evolutionary Game Theory as a Catalyst in Smart Grids: From Theoretical Insights to Practical StrategiesAnas Karaki0https://orcid.org/0000-0003-4302-9367Luluwah Al-Fagih1https://orcid.org/0000-0002-0449-1324Division of Sustainable Development, College of Science and Engineering, Hamad Bin Khalifa University, Doha, QatarDivision of Sustainable Development, College of Science and Engineering, Hamad Bin Khalifa University, Doha, QatarThe increase in the installation of distributed energy resources (DERs) globally has led to a remarkable transformation in the structure of smart grids due to the growing number of energy participants. Recently, electricity markets (EM) have received substantial attention as a viable solution for the complex issue of managing DERs. Modeling the power grid as a complex system of interacting components facilitates investigating the interaction among electricity producers and consumers to maintain the total generation and demand at a balance. In this work, we present a review of the recent advances in adopting evolutionary game theory (EGT), to mitigate challenges in the emerging smart grid, as a decision-making framework for trading dynamics and considering large populations. It includes a taxonomy of various EGT applications in energy trading dynamics, DER management, and policy and infrastructure development. Finally, the linkage between multi-agent reinforcement learning (MARL) and EGT is provided, highlighting their mathematical parallels in the context of smart grid applications.https://ieeexplore.ieee.org/document/10620210/Game theoryevolutionary gameselectricity marketsreinforcement learningmulti-agent systemdynamic populations |
| spellingShingle | Anas Karaki Luluwah Al-Fagih Evolutionary Game Theory as a Catalyst in Smart Grids: From Theoretical Insights to Practical Strategies IEEE Access Game theory evolutionary games electricity markets reinforcement learning multi-agent system dynamic populations |
| title | Evolutionary Game Theory as a Catalyst in Smart Grids: From Theoretical Insights to Practical Strategies |
| title_full | Evolutionary Game Theory as a Catalyst in Smart Grids: From Theoretical Insights to Practical Strategies |
| title_fullStr | Evolutionary Game Theory as a Catalyst in Smart Grids: From Theoretical Insights to Practical Strategies |
| title_full_unstemmed | Evolutionary Game Theory as a Catalyst in Smart Grids: From Theoretical Insights to Practical Strategies |
| title_short | Evolutionary Game Theory as a Catalyst in Smart Grids: From Theoretical Insights to Practical Strategies |
| title_sort | evolutionary game theory as a catalyst in smart grids from theoretical insights to practical strategies |
| topic | Game theory evolutionary games electricity markets reinforcement learning multi-agent system dynamic populations |
| url | https://ieeexplore.ieee.org/document/10620210/ |
| work_keys_str_mv | AT anaskaraki evolutionarygametheoryasacatalystinsmartgridsfromtheoreticalinsightstopracticalstrategies AT luluwahalfagih evolutionarygametheoryasacatalystinsmartgridsfromtheoreticalinsightstopracticalstrategies |