Overview on modeling and management of Smart Grids
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Abstract
The concept of Smart Grids refers to a complex ecosystem that can be described as a combination of systems to capture its most structural elements. When studying these complex systems, the traditional tools of the Cartesian methods have shown their limits. There is therefore a need to resort to other methods to model them. These modeling methods are generally classified and grouped into five families: functional modeling, decision modeling, resource modeling, information modeling and mixed modeling. This review provides an overview of the state of the art of an intelligent network. The classification of modeling methods is also presented. Then an application of the bond graph approach will be explained. Finally we describe a general idea on the management of smart grids.
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References
Carvallo, A., & Cooper, J. (2011). The Advanced Smart Grid: Edge Power Driving Sustainability, Artech House, Boston.
Cohen, A. I., & Wang, C. C. (May 1988). An optimization method for load management scheduling, IEEE Trans. Power Syst., 3(2), 612–618.
Darras, F. (2004). Thèse: Proposition d’un cadre de référence pour la conception et l’exploitation d’un progiciel de gestion intégré. Toulouse: Institut national polytechnique de toulouse.
Diaf, S., Diaf, D., Belhamel, M., Haddadi, M., & Louche, A. (2007). A methodology for optimal sizing of autonomous hybrid PV/wind system, Energy Policy, 35, 5708–5718.
Dauphin-Tanguy, G. (2000). «Les Bond Graphs»,: Hermès Science Editor.
Gungor, V. C., et al. (2011). Smart grid technologies: communications, technologies and standards, IEEE Trans. Ind. Inform. 529–539.
Hassan, A. (2010). Thèse: Proposition et développement d’une approche pour la maîtrise conjointe qualité/coût lors de la conception et de l’industrialisation du produit. Metz: École Nationale Supérieure d'Arts et Métiers.
Hsuand, Y. Y., & Su, C. C. (Aug 1991) Dispatchofdirectload control using dynamic programm.ing, IEEE Trans. PowerSyst., 6(3), 1056–1061.
Jabban, A. (2013). Optimisation et analyse des résesaux intelligents et des réseaux hétérogènes. Autre. INSA de Rennes.
Kosanke, K., Vernadat, F. B., & Williams, T. J. (1997). «manufacturing entreprise modeling with PERA and CIMOSA», IFAC manufacturing systems : Modeling Management nd control, vienna, Autria.
Kromm, H., & Deschamps, J. C. Modélisation de processus pour une évaluation par niveaux de détail successifs. Conférence francophone de modélisation et de simulation. Troyes (France)..
Lakhoua, M. N., Naouali, N., & Chakroun, A. (2014). System Analysis of a Hybrid Renewable Energy System, International Journal of Electrical and Computer Engineering (IJECE)., 4(3), 343-350.
Leeand, H., & Wilkins, C. L. (1983). A practical approach to appliance load control analysis: A waterheater case study, IEEETrans.PowerApp.Syst., PAS-102(4), 1007–1013.
Logenthiran, T., Srinivasan, D., & Zong shun, T. (2012). Demand Side Management in smart grid using Heuristic optimization, IEEE.transactions on smart grid., 3(3).
Miceli, R. (2013). Energy Management and smart Grids,Energies, 6, 2262-2290; doi:10.3390/en6042262.
Ourahou, M., Ayrir, W., El Hassouni, B., & Haddi, A. (2018). Review on smart grid control and reliability in presence of renewable energies challanges ns prospects, science direct.
Rahmouni, M., & Lakhoua, M. N. (2010). Using function and decision models for entreprise restructing, STA, Monastir.
Weedall, M. (2000). BPA Smart Grid Overview, Energy and Communications, Washington House Technology.
Rahman, S., & Rinaldy, S. (1993). An efficient load model for analyzing demand side management impacts, IEEE Trans.PowerSyst., 8(3), 1219–1226.
Schweppe, F. C., Daryanian, B., & Tabors, R. D. (1989). Algorithms for a spot price responding residential load controller, IEEE Trans. Power Syst., 4(2), 507–516.