Abstract
The article describes the combinatorial modelling approach to the research of energy sector development. The idea of the approach is to model a system development in the form of a directed graph which nodes correspond to the possible states of a system at certain moments of time and arcs characterize the possibility of transitions from one state to another. The combinatorial modelling is a visual representation of dynamic discrete alternatives and permits to simulate the long-term process of system development at various possible external and internal conditions, to determine an optimal development strategy of the system under study. The formation and analysis procedures of energy development options are implemented in the Corrective software package. The heterogeneous distributed computing environment is needed to compute an energy sector development graph. In 2015 Institute of Energy Science of Vietnamese Academy of Science and Technology performed the study of Vietnam sustainable energy development from 2015 to 2030. Based on data of this study the combinatorial modelling methods are applied to the formation and analysis of Vietnam energy development options taking into account energy security requirements. The created Vietnam energy sector development graph consists of 531442 nodes. It is computed on the cluster located at Institute for System Dynamics and Control Theory of Siberian Branch of Russian Academy of Science (Irkutsk) under control of the Orlando Tools software package. The found optimal path of Vietnam sustainable energy development provides the minimum costs of energy sector development and operation.
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The research was partially supported by Russian Foundation of Basic Research, project no. 15-07-07412a.
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Edelev, A., Zorkaltsev, V., Gorsky, S., Van Binh, D., Nam, N.H. (2017). The Combinatorial Modelling Approach to Study Sustainable Energy Development of Vietnam. In: Voevodin, V., Sobolev, S. (eds) Supercomputing. RuSCDays 2017. Communications in Computer and Information Science, vol 793. Springer, Cham. https://doi.org/10.1007/978-3-319-71255-0_16
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