Evolutionary Game Theory as a Catalyst in Smart Grids: From Theoretical Insights to Practical Strategies
<p dir="ltr">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 attentio...
محفوظ في:
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| منشور في: |
2024
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| الملخص: | <p dir="ltr">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.</p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Access<br>License: <a href="https://creativecommons.org/licenses/by/4.0/deed.en" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2024.3436935" target="_blank">https://dx.doi.org/10.1109/access.2024.3436935</a></p> |
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