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Multilevel modeling and optimization of large-scale pipeline systems operation

Author

Listed:
  • Novitsky, N.N.
  • Alekseev, A.V.
  • Grebneva, O.A.
  • Lutsenko, A.V.
  • Tokarev, V.V.
  • Shalaginova, Z.I.

Abstract

The paper is devoted to the main results of the development and application of a multilevel approach to mathematical and computer modeling of large-scale pipeline systems. The approach is intended to overcome the problems of dimension of such systems, as well as fragmentation of information and methodological support of modeling tasks that are dealt with at different departmental, regional, organizational and temporal levels of decision-making on the control of pipeline system expansion and operation. The principles and experience of the implementation of a computer platform for the automation of customization and use of multilevel information and computational models of pipeline systems of various purposes are characterized. Heating systems are used as an example to set forth the mechanisms for implementing the multilevel approach to calculate and analyze operating conditions in the design, operation and dispatch control. The formalization of the hydraulic planning task is presented as a discrete-continuous optimization problem of large dimension with multiple criteria. A new procedure for hierarchical optimization of hydraulic conditions and new methods to solve the problems of optimization of different hierarchical levels and coordination of solutions are presented. This approach could be useful in calculation of energy systems (heat, gas, water, electricity, etc.).

Suggested Citation

  • Novitsky, N.N. & Alekseev, A.V. & Grebneva, O.A. & Lutsenko, A.V. & Tokarev, V.V. & Shalaginova, Z.I., 2019. "Multilevel modeling and optimization of large-scale pipeline systems operation," Energy, Elsevier, vol. 184(C), pages 151-164.
  • Handle: RePEc:eee:energy:v:184:y:2019:i:c:p:151-164
    DOI: 10.1016/j.energy.2018.02.070
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    References listed on IDEAS

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    1. Vesterlund, Mattias & Toffolo, Andrea & Dahl, Jan, 2017. "Optimization of multi-source complex district heating network, a case study," Energy, Elsevier, vol. 126(C), pages 53-63.
    2. Schweiger, Gerald & Larsson, Per-Ola & Magnusson, Fredrik & Lauenburg, Patrick & Velut, Stéphane, 2017. "District heating and cooling systems – Framework for Modelica-based simulation and dynamic optimization," Energy, Elsevier, vol. 137(C), pages 566-578.
    3. Guelpa, Elisa & Toro, Claudia & Sciacovelli, Adriano & Melli, Roberto & Sciubba, Enrico & Verda, Vittorio, 2016. "Optimal operation of large district heating networks through fast fluid-dynamic simulation," Energy, Elsevier, vol. 102(C), pages 586-595.
    4. Lazzaretto, Andrea & Toffolo, Andrea & Morandin, Matteo & von Spakovsky, Michael R., 2010. "Criteria for the decomposition of energy systems in local/global optimizations," Energy, Elsevier, vol. 35(2), pages 1157-1163.
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    Cited by:

    1. Guelpa, Elisa & Bischi, Aldo & Verda, Vittorio & Chertkov, Michael & Lund, Henrik, 2019. "Towards future infrastructures for sustainable multi-energy systems: A review," Energy, Elsevier, vol. 184(C), pages 2-21.
    2. Nikolay Novitsky & Egor Mikhailovsky, 2021. "Generalization of Methods for Calculating Steady-State Flow Distribution in Pipeline Networks for Non-Conventional Flow Models," Mathematics, MDPI, vol. 9(8), pages 1-16, April.

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