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Comparison of Component-Oriented and System-Oriented Modeling in the Context of Operational Energy System Analysis

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  • Jan-Philip Beck

    (Institute of Automation Technology, Helmut Schmidt University/University of the Federal Armed Forces Hamburg, Holstenhofweg 85, 22043 Hamburg, Germany)

  • Parantapa Sawant

    (Institute of Sustainable Energy Systems, Offenburg University of Applied Sciences, Badstrasse 24, 77652 Offenburg, Germany)

  • Simon Ruben Drauz

    (Fraunhofer Institute for Energy Economics and Energy System Technology, Königstor 59, 34119 Kassel, Germany)

  • Jan Sören Schwarz

    (OFFIS—Institute for Information Technology, Escherweg 2, 26121 Oldenburg, Germany)

  • Annika Heyer

    (Gas- und Wärme-Institut Essen e.V., Hafenstraße 101, 45356 Essen, Germany)

  • Philipp Huismann

    (Gas- und Wärme-Institut Essen e.V., Hafenstraße 101, 45356 Essen, Germany)

Abstract

Simulation based studies for operational energy system analysis play a significant role in evaluation of various new age technologies and concepts in the energy grid. Various modelling approaches already exist and in this original paper, four models representing these approaches are compared in two real-world hybrid energy system scenarios. The models, namely TransiEnt, µGRiDS, and OpSim (including pandaprosumer and mosaic) are classified into component-oriented or system-oriented approaches as deduced from the literature research. The methodology section describes their differences under standard conditions and the necessary parameterization for the purpose of creating a framework facilitating a closest possible comparison. A novel methodology for scenario generation is also explained. The results help to quantify primary differences in these approaches that are also identified in literature and qualify the influence of the accuracy of the models for application in a system-wide analysis. It is shown that a simplified model may be sufficient for the system-oriented approach especially when the objective is an optimization-based control or planning. However, from a field level operational point of view, the differences in the time series signify the importance of the component-oriented approaches.

Suggested Citation

  • Jan-Philip Beck & Parantapa Sawant & Simon Ruben Drauz & Jan Sören Schwarz & Annika Heyer & Philipp Huismann, 2022. "Comparison of Component-Oriented and System-Oriented Modeling in the Context of Operational Energy System Analysis," Energies, MDPI, vol. 15(13), pages 1-22, June.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:13:p:4712-:d:849136
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    References listed on IDEAS

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    1. Jasmine Ramsebner & Reinhard Haas & Amela Ajanovic & Martin Wietschel, 2021. "The sector coupling concept: A critical review," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 10(4), July.
    2. Menon, Ramanunni P. & Maréchal, François & Paolone, Mario, 2016. "Intra-day electro-thermal model predictive control for polygeneration systems in microgrids," Energy, Elsevier, vol. 104(C), pages 308-319.
    3. Lund, Henrik & Duić, Neven & Krajac˘ić, Goran & Graça Carvalho, Maria da, 2007. "Two energy system analysis models: A comparison of methodologies and results," Energy, Elsevier, vol. 32(6), pages 948-954.
    4. Priesmann, Jan & Nolting, Lars & Praktiknjo, Aaron, 2019. "Are complex energy system models more accurate? An intra-model comparison of power system optimization models," Applied Energy, Elsevier, vol. 255(C).
    5. Bracco, Stefano & Delfino, Federico & Pampararo, Fabio & Robba, Michela & Rossi, Mansueto, 2014. "A mathematical model for the optimal operation of the University of Genoa Smart Polygeneration Microgrid: Evaluation of technical, economic and environmental performance indicators," Energy, Elsevier, vol. 64(C), pages 912-922.
    6. Facci, Andrea Luigi & Andreassi, Luca & Ubertini, Stefano, 2014. "Optimization of CHCP (combined heat power and cooling) systems operation strategy using dynamic programming," Energy, Elsevier, vol. 66(C), pages 387-400.
    7. Afroz, Zakia & Shafiullah, GM & Urmee, Tania & Higgins, Gary, 2018. "Modeling techniques used in building HVAC control systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 83(C), pages 64-84.
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