IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i13p4712-d849136.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/13/4712/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/13/4712/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Prina, Matteo Giacomo & Nastasi, Benedetto & Groppi, Daniele & Misconel, Steffi & Garcia, Davide Astiaso & Sparber, Wolfram, 2022. "Comparison methods of energy system frameworks, models and scenario results," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    2. Fodstad, Marte & Crespo del Granado, Pedro & Hellemo, Lars & Knudsen, Brage Rugstad & Pisciella, Paolo & Silvast, Antti & Bordin, Chiara & Schmidt, Sarah & Straus, Julian, 2022. "Next frontiers in energy system modelling: A review on challenges and the state of the art," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    3. Jana, Kuntal & Ray, Avishek & Majoumerd, Mohammad Mansouri & Assadi, Mohsen & De, Sudipta, 2017. "Polygeneration as a future sustainable energy solution – A comprehensive review," Applied Energy, Elsevier, vol. 202(C), pages 88-111.
    4. Rubio Rodríguez, M.A. & Ruyck, J. De & Díaz, P. Roque & Verma, V.K. & Bram, S., 2011. "An LCA based indicator for evaluation of alternative energy routes," Applied Energy, Elsevier, vol. 88(3), pages 630-635, March.
    5. Lukas Kriechbaum & Philipp Gradl & Romeo Reichenhauser & Thomas Kienberger, 2020. "Modelling Grid Constraints in a Multi-Energy Municipal Energy System Using Cumulative Exergy Consumption Minimisation," Energies, MDPI, vol. 13(15), pages 1-23, July.
    6. Gabriele Loreti & Andrea Luigi Facci & Stefano Ubertini, 2021. "High-Efficiency Combined Heat and Power through a High-Temperature Polymer Electrolyte Membrane Fuel Cell and Gas Turbine Hybrid System," Sustainability, MDPI, vol. 13(22), pages 1-24, November.
    7. Gils, Hans Christian & Gardian, Hedda & Kittel, Martin & Schill, Wolf-Peter & Zerrahn, Alexander & Murmann, Alexander & Launer, Jann & Fehler, Alexander & Gaumnitz, Felix & van Ouwerkerk, Jonas & Bußa, 2022. "Modeling flexibility in energy systems — comparison of power sector models based on simplified test cases," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    8. Leonard Goke & Jens Weibezahn & Christian von Hirschhausen, 2021. "A collective blueprint, not a crystal ball: How expectations and participation shape long-term energy scenarios," Papers 2112.04821, arXiv.org, revised Dec 2022.
    9. Yanfeng Liu & Yaxing Wang & Xi Luo, 2020. "Design and Operation Optimization of Distributed Solar Energy System Based on Dynamic Operation Strategy," Energies, MDPI, vol. 14(1), pages 1-26, December.
    10. Cui, Can & Zhang, Xin & Cai, Wenjian, 2020. "An energy-saving oriented air balancing method for demand controlled ventilation systems with branch and black-box model," Applied Energy, Elsevier, vol. 264(C).
    11. Gholami, M. & Barbaresi, A. & Torreggiani, D. & Tassinari, P., 2020. "Upscaling of spatial energy planning, phases, methods, and techniques: A systematic review through meta-analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 132(C).
    12. De Rosa, Luca & Castro, Rui, 2020. "Forecasting and assessment of the 2030 australian electricity mix paths towards energy transition," Energy, Elsevier, vol. 205(C).
    13. Krajacic, Goran & Duic, Neven & Carvalho, Maria da Graça, 2011. "How to achieve a 100% RES electricity supply for Portugal?," Applied Energy, Elsevier, vol. 88(2), pages 508-517, February.
    14. Wang, Yingli & Duan, Jialong & Zhao, Yuanyuan & He, Benlin & Tang, Qunwei, 2018. "Harvest rain energy by polyaniline-graphene composite films," Renewable Energy, Elsevier, vol. 125(C), pages 995-1002.
    15. Li, Yanxue & Wang, Zixuan & Xu, Wenya & Gao, Weijun & Xu, Yang & Xiao, Fu, 2023. "Modeling and energy dynamic control for a ZEH via hybrid model-based deep reinforcement learning," Energy, Elsevier, vol. 277(C).
    16. Mariia Kozlova & Alena Lohrmann, 2021. "Steering Renewable Energy Investments in Favor of Energy System Reliability: A Call for a Hybrid Model," Sustainability, MDPI, vol. 13(24), pages 1-18, December.
    17. Park, Sung-Won & Son, Sung-Yong, 2023. "Techno-economic analysis for the electric vehicle battery aging management of charge point operator," Energy, Elsevier, vol. 280(C).
    18. Mazzola, Simone & Astolfi, Marco & Macchi, Ennio, 2015. "A detailed model for the optimal management of a multigood microgrid," Applied Energy, Elsevier, vol. 154(C), pages 862-873.
    19. Yoon, Y. & Jung, S. & Im, P. & Salonvaara, M. & Bhandari, M. & Kunwar, N., 2023. "Empirical validation of building energy simulation model input parameter for multizone commercial building during the cooling season," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    20. Facci, Andrea L. & Sánchez, David & Jannelli, Elio & Ubertini, Stefano, 2015. "Trigenerative micro compressed air energy storage: Concept and thermodynamic assessment," Applied Energy, Elsevier, vol. 158(C), pages 243-254.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:15:y:2022:i:13:p:4712-:d:849136. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.