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On the Modeling of Energy-Multisource Networks by the Thermostatted Kinetic Theory Approach: A Review with Research Perspectives

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  • Carlo Bianca

    (Laboratoire Quartz EA 7393, École Supérieure d’Ingénieurs en Génie Électrique, Productique et Management Industriel, 13 Boulevard de l’Hautil, 95092 Cergy-Pontoise, France
    Laboratoire de Recherche en Eco-Innovation Industrielle et Energétique, École Supérieure d’Ingénieurs en Génie Électrique, Productique et Management Industriel, 13 Boulevard de l’Hautil, 95092 Cergy-Pontoise, France)

Abstract

Recently, different mathematical frameworks of the thermostatted kinetic theory approach have been proposed for the modeling of complex systems. In particular, thermostatted kinetic frameworks have been employed for the modeling and time evolution of a hybrid energy-multisource network composed of renewable and nonrenewable energy sources, for the construction of the energy storage and for open networks. In the frameworks of the thermostatted kinetic theory approach, the evolution of an energy source and the interactions with other energy sources are modeled by introducing a distribution function and interaction rates. This paper is a survey of the recent proposed frameworks of the thermostatted kinetic theory for the modeling of a hybrid energy-multisource network and reviews the recent proposed models. The paper is not limited to review the existing frameworks, but it also generalizes the mathematical structures proposed in the pertinent literature and outlines future research perspectives and applications of this new approach proposed in 2012.

Suggested Citation

  • Carlo Bianca, 2022. "On the Modeling of Energy-Multisource Networks by the Thermostatted Kinetic Theory Approach: A Review with Research Perspectives," Energies, MDPI, vol. 15(21), pages 1-22, October.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:21:p:7825-:d:950229
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    1. Gonçalves, J.F. & Mendes, J.J.M. & Resende, M.G.C., 2008. "A genetic algorithm for the resource constrained multi-project scheduling problem," European Journal of Operational Research, Elsevier, vol. 189(3), pages 1171-1190, September.
    2. Diaf, S. & Notton, G. & Belhamel, M. & Haddadi, M. & Louche, A., 2008. "Design and techno-economical optimization for hybrid PV/wind system under various meteorological conditions," Applied Energy, Elsevier, vol. 85(10), pages 968-987, October.
    3. Wang, B.C. & Sechilariu, M. & Locment, F., 2013. "Power flow Petri Net modelling for building integrated multi-source power system with smart grid interaction," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 91(C), pages 119-133.
    4. Bruno Carbonaro & Marco Menale, 2019. "Dependence on the Initial Data for the Continuous Thermostatted Framework," Mathematics, MDPI, vol. 7(7), pages 1-11, July.
    5. Chassin, David P. & Posse, Christian, 2005. "Evaluating North American electric grid reliability using the Barabási–Albert network model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(2), pages 667-677.
    6. Jebaraj, S. & Iniyan, S., 2006. "A review of energy models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 10(4), pages 281-311, August.
    7. Tsao, Yu-Chung & Thanh, Vo-Van & Lu, Jye-Chyi, 2019. "Multiobjective robust fuzzy stochastic approach for sustainable smart grid design," Energy, Elsevier, vol. 176(C), pages 929-939.
    8. Carlo Bianca, 2013. "Modeling Complex Systems with Particles Refuge by Thermostatted Kinetic Theory Methods," Abstract and Applied Analysis, Hindawi, vol. 2013, pages 1-13, November.
    9. Zaibi, Malek & Champenois, Gérard & Roboam, Xavier & Belhadj, Jamel & Sareni, Bruno, 2018. "Smart power management of a hybrid photovoltaic/wind stand-alone system coupling battery storage and hydraulic network," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 146(C), pages 210-228.
    10. Cabello, Javier M. & Roboam, Xavier & Junco, Sergio & Turpin, Christophe, 2019. "Direct sizing and characterization of Energy Storage Systems in the Energy-Power plane," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 158(C), pages 2-17.
    11. Crucitti, Paolo & Latora, Vito & Marchiori, Massimo, 2004. "A topological analysis of the Italian electric power grid," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 338(1), pages 92-97.
    12. G. Filatrella & A. H. Nielsen & N. F. Pedersen, 2008. "Analysis of a power grid using a Kuramoto-like model," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 61(4), pages 485-491, February.
    13. Coester, Andreas & Hofkes, Marjan W. & Papyrakis, Elissaios, 2018. "An optimal mix of conventional power systems in the presence of renewable energy: A new design for the German electricity market," Energy Policy, Elsevier, vol. 116(C), pages 312-322.
    14. Meade, Nigel, 2010. "Oil prices -- Brownian motion or mean reversion? A study using a one year ahead density forecast criterion," Energy Economics, Elsevier, vol. 32(6), pages 1485-1498, November.
    15. Pagani, Giuliano Andrea & Aiello, Marco, 2013. "The Power Grid as a complex network: A survey," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(11), pages 2688-2700.
    16. Mirkhani, Sh. & Saboohi, Y., 2012. "Stochastic modeling of the energy supply system with uncertain fuel price – A case of emerging technologies for distributed power generation," Applied Energy, Elsevier, vol. 93(C), pages 668-674.
    17. Kusiak, Andrew & Zheng, Haiyang & Song, Zhe, 2009. "On-line monitoring of power curves," Renewable Energy, Elsevier, vol. 34(6), pages 1487-1493.
    18. Broeer, Torsten & Fuller, Jason & Tuffner, Francis & Chassin, David & Djilali, Ned, 2014. "Modeling framework and validation of a smart grid and demand response system for wind power integration," Applied Energy, Elsevier, vol. 113(C), pages 199-207.
    19. Tan, Chee Wei & Green, Tim C. & Hernandez-Aramburo, Carlos A., 2010. "A stochastic method for battery sizing with uninterruptible-power and demand shift capabilities in PV (photovoltaic) systems," Energy, Elsevier, vol. 35(12), pages 5082-5092.
    20. Dai, YuanYu & Chen, Guo & Dong, ZhaoYang & Xue, YuSheng & Hill, David J. & Zhao, Yuan, 2014. "An improved framework for power grid vulnerability analysis considering critical system features," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 395(C), pages 405-415.
    21. Tina, Giuseppe Marco & Gagliano, Salvina, 2011. "Probabilistic modelling of hybrid solar/wind power system with solar tracking system," Renewable Energy, Elsevier, vol. 36(6), pages 1719-1727.
    22. Jiang, Haibo & Li, Yanru & Cheng, Zhongqing, 2015. "Performances of ideal wind turbine," Renewable Energy, Elsevier, vol. 83(C), pages 658-662.
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