Integrated Energy System Systems and Game Theory A Review
Keywords:Integrated Energy, System, Game Theory, Energy Management, Demand Respone
As mankind expands quickly, there is a shortage of energy worldwide. Instead of focusing on the production, transmission, and provision of a particular power source, China has proposed an To address the energy crisis, an integrated energy system is being developed. This system links energy resources and utilizes their complementary benefits. With the development of integrated energy systems, involvement and Engagement is getting increasingly difficult. Game theory, which can successfully address issues arising from multi-agent commerce, is a natural application of the System of integrated energy. This publication gives in-depth information analysis of how the integrated power system has undergone game theory analysis. Initial game situations in integrated power systems are provided, followed by a brief introduction to the evolution of integrated energy, The design and deployment of interconnected power systems issues are outlined, along with game scenarios that take into account the energy production side, supply chain, demand side, and all of these factors. Second, a summary of the fundamental for the integrated energy system, use game theory models is provided. The last topic is examined along with the challenges involved in game theory's potential application to integrated power systems. When applying the newly created game models to the integrated power system, a mixed game is recommended to solve these issues. This study should prove to be an invaluable resource for upcoming scholars in the subject.
Z. Liu et al., “Artificial intelligence powered large-scale renewable integrations in multi-energy systems for carbon neutrality transition: challenges and future perspectives,” Energy AI, p. 100195, 2022.
A. A. Alola, F. V. Bekun, and S. A. Sarkodie, “Dynamic impact of trade policy, economic growth, fertility rate, renewable and non-renewable energy consumption on ecological footprint in Europe,” Sci. Total Environ., vol. 685, pp. 702–709, 2019.
J. Li et al., “Optimization configuration of regional integrated energy system based on standard module,” Energy Build., vol. 229, p. 110485, 2020.
C. Smith, J. Mouli-Castillo, D. Van Der Horst, S. Haszeldine, and M. Lane, “Towards a 100% hydrogen domestic gas network: Regulatory and commercial barriers to the first demonstrator project in the United Kingdom,” Int. J. Hydrogen Energy, vol. 47, no. 55, pp. 23071–23083, 2022.
Y. Huang, Q. Sun, N. Zhang, and R. Wang, “A multi-slack bus model for bi-directional energy flow analysis of integrated power-gas systems,” CSEE J. Power Energy Syst., 2021.
T. Klatzer, U. Bachhiesl, and S. Wogrin, “State-of-the-art expansion planning of integrated power, natural gas, and hydrogen systems,” Int. J. Hydrogen Energy, 2022.
A. Angelopoulos et al., “Tackling faults in the industry 4.0 era—a survey of machine-learning solutions and key aspects,” Sensors, vol. 20, no. 1, p. 109, 2019.
Ş. Kılkış, G. Krajačić, N. Duić, L. Montorsi, Q. Wang, and M. A. Rosen, “Research frontiers in sustainable development of energy, water and environment systems in a time of climate crisis,” Energy conversion and management, vol. 199. Elsevier, p. 111938, 2019.
Y. Wang et al., “Capacity planning and optimization of business park-level integrated energy system based on investment constraints,” Energy, vol. 189, p. 116345, 2019.
J. Jia, G. Zang, and M. C. Paul, “Energy, exergy, and economic (3E) evaluation of a CCHP system with biomass gasifier, solid oxide fuel cells, micro‐gas turbine, and absorption chiller,” Int. J. Energy Res., vol. 45, no. 10, pp. 15182–15199, 2021.
E. Gholamian, P. Ahmadi, P. Hanafizadeh, and M. Ashjaee, “Dynamic feasibility assessment and 3E analysis of a smart building energy system integrated with hybrid photovoltaic-thermal panels and energy storage,” Sustain. Energy Technol. Assessments, vol. 42, p. 100835, 2020.
A. Bartolini, S. Mazzoni, G. Comodi, and A. Romagnoli, “Impact of carbon pricing on distributed energy systems planning,” Appl. Energy, vol. 301, p. 117324, 2021.
C. Mu, T. Ding, M. Qu, Q. Zhou, F. Li, and M. Shahidehpour, “Decentralized optimization operation for the multiple integrated energy systems with energy cascade utilization,” Appl. Energy, vol. 280, p. 115989, 2020.
J. Ramsebner et al., “From single to multi-energy and hybrid grids: Historic growth and future vision,” Renew. Sustain. Energy Rev., vol. 151, p. 111520, 2021.
J. Wang et al., “Cooperative and Competitive Multi-Agent Systems: From Optimization to Games,” IEEE/CAA J. Autom. Sin., vol. 9, no. 5, pp. 763–783, 2022.
S. Nazari, A. Ahmadi, S. K. Rad, and B. Ebrahimi, “Application of non-cooperative dynamic game theory for groundwater conflict resolution,” J. Environ. Manage., vol. 270, p. 110889, 2020.
X. Cai, F. Xiao, and B. Wei, “Distributed generalized Nash equilibrium seeking for noncooperative games with unknown cost functions,” Int. J. Robust Nonlinear Control, 2022.
Z. Ni and S. Paul, “A multistage game in smart grid security: A reinforcement learning solution,” IEEE Trans. neural networks Learn. Syst., vol. 30, no. 9, pp. 2684–2695, 2019.
P. De Giovanni, “Digital supply chain through dynamic inventory and smart contracts,” Mathematics, vol. 7, no. 12, p. 1235, 2019.
M. Mahmoud, M. Ramadan, A.-G. Olabi, K. Pullen, and S. Naher, “A review of mechanical energy storage systems combined with wind and solar applications,” Energy Convers. Manag., vol. 210, p. 112670, 2020.
R. Yang and D. Li, “Adaptive wavelet transform based on artificial fish swarm optimization and fuzzy C-means method for noisy image segmentation,” Comput. Sci. Inf. Syst., no. 00, p. 39, 2022.
D. Wang et al., “Review of key problems related to integrated energy distribution systems,” CSEE J. Power Energy Syst., vol. 4, no. 2, pp. 130–145, 2018.
H. Sun, B. K. Edziah, C. Sun, and A. K. Kporsu, “Institutional quality and its spatial spillover effects on energy efficiency,” Socioecon. Plann. Sci., vol. 83, p. 101023, 2022.
J. Pacheco, S. Garbatov, and M. Goulão, “Improving Collaboration Efficiency Between UX/UI Designers and Developers in a Low-Code Platform,” in 2021 ACM/IEEE International Conference on Model Driven Engineering Languages and Systems Companion (MODELS-C), 2021, pp. 138–147.
M. J. Kim, T. S. Kim, R. J. Flores, and J. Brouwer, “Neural-network-based optimization for economic dispatch of combined heat and power systems,” Appl. Energy, vol. 265, p. 114785, 2020.
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