Abstract
Game theory is a theoretical framework to analyze the interaction of rational decision-makers in a system. Game theory is an effective tool to investigate real-world scenarios with multiple stakeholders interacting with each other. For that reason, game theory has become an essential tool to analyze modern energy systems. Unlike traditional energy systems with centralized decision-making authorities, modern energy systems include markets, decentralized technologies, and multiple stakeholders who act independently in the system. Game theory has been used as a tool that enables the researchers to investigate the independent decision-making of stakeholders in energy systems. Game theory is an effective tool for developing models that provide a better understanding of real-world scenarios compared to centralized models developed in the past.
Game theory has been used in different areas of energy system analysis including the optimum design and control of smart energy systems and microgrids. Additionally, game theory modeling has been used to address new challenges faced by energy system operators, and decision-makers such as electric vehicle charging, hybrid energy system planning, generation expansion planning, and energy policy issues.
A game theory framework, however, has certain limits when it is used for modeling real-world problems. The primary limits of game theory modeling are solution complexity and assumptions needed to develop a game model. Both these limits may require simplification of a game model, which limits the researchers’ ability to capture all aspects of a complex real-world energy system with multiple stakeholders.
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References
S. Abapour, M. Nazari-Heris, B. Mohammadi-Ivatloo, M.T. Hagh, Game theory approaches for the solution of power system problems: A comprehensive review. Arch. Comput. Methods Eng. 27(1), 81–103 (2020a)
S. Abapour, B. Mohammadi-Ivatloo, M.T. Hagh, Robust bidding strategy for demand response aggregators in electricity market based on game theory. J. Clean. Prod. 243, 118393 (2020b)
J. Axelsson, Game theory applications in systems-of-systems engineering: A literature review and synthesis. Proc. Comp. Sci. 153, 154–165 (2019)
R.F.S. Budi, S.P. Hadi, Game theory for multi-objective and multi-period framework generation expansion planning in deregulated markets. Energy 174, 323–330 (2019)
Z. Chen, Y. Zhang, T. Ji, Z. Cai, L. Li, Z. Xu, Coordinated optimal dispatch and market equilibrium of integrated electric power and natural gas networks with P2G embedded. J. Modern Power Syst. Clean Energy 6(3), 495–508 (2018)
Y. Fang, W. Wei, F. Liu, S. Mei, L. Chen, J. Li, Improving solar power usage with electric vehicles: Analyzing a public-private partnership cooperation scheme based on evolutionary game theory. J. Clean. Prod. 233, 1284–1297 (2019)
E. Haghi, H. Shamsi, S. Dimitrov, M. Fowler, K. Raahemifar, Assessing the potential of fuel cell-powered and battery-powered forklifts for reducing GHG emissions using clean surplus power; a game theory approach. Int. J. Hydrog. Energy 45(59), 34532–34544 (2020)
Y. Huang, W. Zhang, K. Yang, W. Hou, Y. Huang, An optimal scheduling method for multi-energy hub systems using game theory. Energies 12(12), 2270 (2019)
R. Jing, M. Wang, H. Liang, X. Wang, N. Li, N. Shah, Y. Zhao, Multi-objective optimization of a neighborhood-level urban energy network: Considering game-theory inspired multi-benefit allocation constraints. Appl. Energy 231, 534–548 (2018)
C.S. Karavas, K. Arvanitis, G. Papadakis, A game theory approach to multi-agent decentralized energy management of autonomous polygeneration microgrids. Energies 10(11), 1756 (2017)
A. Laha, B. Yin, Y. Cheng, L.X. Cai, Y. Wang, Game theory based charging solution for networked electric vehicles: A location-aware approach. IEEE Trans. Veh. Technol. 68(7), 6352–6364 (2019)
R.H. Lasseter, Microgrids, in 2002 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (cat. No. 02CH37309), vol. 1, (IEEE, 2002), pp. 305–308
H. Lund, P.A. Østergaard, D. Connolly, B.V. Mathiesen, Smart energy and smart energy systems. Energy 137, 556–565 (2017)
J. Michalski, Investment decisions in imperfect power markets with hydrogen storage and large share of intermittent electricity. Int. J. Hydrog. Energy 42(19), 13368–13381 (2017)
A. Navon, G. Ben Yosef, R. Machlev, S. Shapira, N. Roy Chowdhury, J. Belikov, A. Orda, Y. Levron, Applications of game theory to design and operation of modern power systems: A comprehensive review. Energies 13(15), 3982 (2020a)
A. Navon, G. Ben Yosef, R. Machlev, S. Shapira, N. Roy Chowdhury, J. Belikov, A. Orda, Y. Levron, Applications of game theory to design and operation of modern power systems: A comprehensive review. Energies 13(15), 3982 (2020b)
A. Paudel, K. Chaudhari, C. Long, H.B. Gooi, Peer-to-peer energy trading in a prosumer-based community microgrid: A game-theoretic model. IEEE Trans. Ind. Electron. 66(8), 6087–6097 (2018)
A. Sarker, Z. Li, W. Kolodzey, H. Shen, Opportunistic energy sharing between power grid and electric vehicles: A game theory-based pricing policy, in 2017 IEEE 37th International Conference on Distributed Computing Systems (ICDCS), (IEEE, 2017), pp. 1197–1207
Y. Wang, X. Ai, Z. Tan, L. Yan, S. Liu, Interactive dispatch modes and bidding strategy of multiple virtual power plants based on demand response and game theory. IEEE Trans. Smart Grid 7(1), 510–519 (2015)
H. Wang, C. Zhang, K. Li, X. Ma, Game theory-based multi-agent capacity optimization for integrated energy systems with compressed air energy storage. Energy 221, 119777 (2021)
H. Yin, C. Zhao, M. Li, C. Ma, M.Y. Chow, A game theory approach to energy management of an engine–generator/battery/ultracapacitor hybrid energy system. Iieee Trans. Ind. Elect. 63(7), 4266–4277 (2016)
H. Zhang, Z. Xu, D. Zhou, J. Cao, Waste cooking oil-to-energy under incomplete information: Identifying policy options through an evolutionary game. Appl. Energy 185, 547–555 (2017)
Z. Zhu, S. Lambotharan, W.H. Chin, Z. Fan, A mean field game theoretic approach to electric vehicles charging. IEEE Access 4, 3501–3510 (2016)
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Haghi, E. (2022). Game Theory Modeling of Energy Systems. In: Fathi, M., Zio, E., Pardalos, P.M. (eds) Handbook of Smart Energy Systems. Springer, Cham. https://doi.org/10.1007/978-3-030-72322-4_117-1
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DOI: https://doi.org/10.1007/978-3-030-72322-4_117-1
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