IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v181y2019icp77-90.html
   My bibliography  Save this article

Hardware-in-the-Loop simulation of an optimized energy management incorporating an experimental biocatalytic methanation reactor

Author

Listed:
  • Griese, Martin
  • Hoffarth, Marc Philippe
  • Schneider, Jan
  • Schulte, Thomas

Abstract

Towards renewable energy systems, the coupling of multiple sectors is important and incorporates novel technologies where currently no models exist that correctly represent all transient effects. Therefore, we present a method that incorporates Hardware-in-the-Loop simulations where virtual components as models are coupled to real and experimental facilities in real time. By including experimental components, a higher validity can be obtained and the practical applicability of renewable energy scenario can be discussed more profoundly. In this paper, the considered energy system consists of an experimental biocatalytic methanation reactor, a real photovoltaic park, a regenerative fuel cell and short-term storage units to supply a residential district. A representative control sequence of the methanator is obtained by modeling the scenario as an optimal control problem. A first HIL simulation highlights that modifications of the instrumentation are required for a grid injection of the generated methane. The scientific approach can be applied to any energy system where some of the considered components are available as experimental or real facilities. Non-exisiting components are simply replaced by models. The presented approach helps to determine which parts or process parameters are crucial for the planed operation before the overall energy system is realized on a larger scale.

Suggested Citation

  • Griese, Martin & Hoffarth, Marc Philippe & Schneider, Jan & Schulte, Thomas, 2019. "Hardware-in-the-Loop simulation of an optimized energy management incorporating an experimental biocatalytic methanation reactor," Energy, Elsevier, vol. 181(C), pages 77-90.
    • Handle: RePEc:eee:energy:v:181:y:2019:i:c:p:77-90
    DOI: 10.1016/j.energy.2019.05.092
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544219309697
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2019.05.092?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Alexander Franz & Jürgen Zimmermann, 2018. "A Two-Stage Heuristic Procedure for Solving the Long-Term Unit Commitment Problem with Pumped Storages and Its Application to the German Electricity Market," Operations Research Proceedings, in: Andreas Fink & Armin Fügenschuh & Martin Josef Geiger (ed.), Operations Research Proceedings 2016, pages 149-155, Springer.
    2. Marano, Vincenzo & Rizzo, Gianfranco & Tiano, Francesco Antonio, 2012. "Application of dynamic programming to the optimal management of a hybrid power plant with wind turbines, photovoltaic panels and compressed air energy storage," Applied Energy, Elsevier, vol. 97(C), pages 849-859.
    3. Meng, Lexuan & Sanseverino, Eleonora Riva & Luna, Adriana & Dragicevic, Tomislav & Vasquez, Juan C. & Guerrero, Josep M., 2016. "Microgrid supervisory controllers and energy management systems: A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1263-1273.
    4. Elsido, Cristina & Bischi, Aldo & Silva, Paolo & Martelli, Emanuele, 2017. "Two-stage MINLP algorithm for the optimal synthesis and design of networks of CHP units," Energy, Elsevier, vol. 121(C), pages 403-426.
    5. Buttler, Alexander & Spliethoff, Hartmut, 2018. "Current status of water electrolysis for energy storage, grid balancing and sector coupling via power-to-gas and power-to-liquids: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2440-2454.
    6. Kaboli, S. Hr. Aghay & Selvaraj, J. & Rahim, N.A., 2016. "Long-term electric energy consumption forecasting via artificial cooperative search algorithm," Energy, Elsevier, vol. 115(P1), pages 857-871.
    7. Modiri-Delshad, Mostafa & Aghay Kaboli, S. Hr. & Taslimi-Renani, Ehsan & Rahim, Nasrudin Abd, 2016. "Backtracking search algorithm for solving economic dispatch problems with valve-point effects and multiple fuel options," Energy, Elsevier, vol. 116(P1), pages 637-649.
    8. Rittmann, Simon K.-M.R. & Seifert, Arne H. & Bernacchi, Sébastien, 2018. "Kinetics, multivariate statistical modelling, and physiology of CO2-based biological methane production," Applied Energy, Elsevier, vol. 216(C), pages 751-760.
    9. Brown, T. & Schlachtberger, D. & Kies, A. & Schramm, S. & Greiner, M., 2018. "Synergies of sector coupling and transmission reinforcement in a cost-optimised, highly renewable European energy system," Energy, Elsevier, vol. 160(C), pages 720-739.
    10. Burkhardt, Marko & Jordan, Isabel & Heinrich, Sabrina & Behrens, Johannes & Ziesche, André & Busch, Günter, 2019. "Long term and demand-oriented biocatalytic synthesis of highly concentrated methane in a trickle bed reactor," Applied Energy, Elsevier, vol. 240(C), pages 818-826.
    11. Paul, Biddyut & Andrews, John, 2017. "PEM unitised reversible/regenerative hydrogen fuel cell systems: State of the art and technical challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 79(C), pages 585-599.
    12. Seifert, A.H. & Rittmann, S. & Herwig, C., 2014. "Analysis of process related factors to increase volumetric productivity and quality of biomethane with Methanothermobacter marburgensis," Applied Energy, Elsevier, vol. 132(C), pages 155-162.
    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. Kim, Sunwoo & Choi, Yechan & Park, Joungho & Adams, Derrick & Heo, Seongmin & Lee, Jay H., 2024. "Multi-period, multi-timescale stochastic optimization model for simultaneous capacity investment and energy management decisions for hybrid Micro-Grids with green hydrogen production under uncertainty," Renewable and Sustainable Energy Reviews, Elsevier, vol. 190(PA).
    2. Ahmad, Tanveer & Chen, Huanxin, 2019. "Deep learning for multi-scale smart energy forecasting," Energy, Elsevier, vol. 175(C), pages 98-112.
    3. Stefan Arens & Sunke Schlüters & Benedikt Hanke & Karsten von Maydell & Carsten Agert, 2020. "Sustainable Residential Energy Supply: A Literature Review-Based Morphological Analysis," Energies, MDPI, vol. 13(2), pages 1-28, January.
    4. Ghiasi, Mohammad, 2019. "Detailed study, multi-objective optimization, and design of an AC-DC smart microgrid with hybrid renewable energy resources," Energy, Elsevier, vol. 169(C), pages 496-507.
    5. Martin Thema & Tobias Weidlich & Manuel Hörl & Annett Bellack & Friedemann Mörs & Florian Hackl & Matthias Kohlmayer & Jasmin Gleich & Carsten Stabenau & Thomas Trabold & Michael Neubert & Felix Ortlo, 2019. "Biological CO 2 -Methanation: An Approach to Standardization," Energies, MDPI, vol. 12(9), pages 1-32, May.
    6. Zhu, Jiawei & Lin, Yishuai & Lei, Weidong & Liu, Youquan & Tao, Mengling, 2019. "Optimal household appliances scheduling of multiple smart homes using an improved cooperative algorithm," Energy, Elsevier, vol. 171(C), pages 944-955.
    7. Ahmad Baroutaji & Arun Arjunan & John Robinson & Tabbi Wilberforce & Mohammad Ali Abdelkareem & Abdul Ghani Olabi, 2021. "PEMFC Poly-Generation Systems: Developments, Merits, and Challenges," Sustainability, MDPI, vol. 13(21), pages 1-31, October.
    8. Akbari, Ebrahim & Hooshmand, Rahmat-Allah & Gholipour, Mehdi & Parastegari, Moein, 2019. "Stochastic programming-based optimal bidding of compressed air energy storage with wind and thermal generation units in energy and reserve markets," Energy, Elsevier, vol. 171(C), pages 535-546.
    9. Hu, Yusha & Li, Jigeng & Hong, Mengna & Ren, Jingzheng & Lin, Ruojue & Liu, Yue & Liu, Mengru & Man, Yi, 2019. "Short term electric load forecasting model and its verification for process industrial enterprises based on hybrid GA-PSO-BPNN algorithm—A case study of papermaking process," Energy, Elsevier, vol. 170(C), pages 1215-1227.
    10. Chen, Yue & Wei, Wei & Liu, Feng & Shafie-khah, Miadreza & Mei, Shengwei & Catalão, João P.S., 2018. "Optimal contracts of energy mix in a retail market under asymmetric information," Energy, Elsevier, vol. 165(PB), pages 634-650.
    11. Hu, Maomao & Xiao, Fu & Jørgensen, John Bagterp & Wang, Shengwei, 2019. "Frequency control of air conditioners in response to real-time dynamic electricity prices in smart grids," Applied Energy, Elsevier, vol. 242(C), pages 92-106.
    12. Fiammetta Rita Bianchi & Barbara Bosio, 2021. "Operating Principles, Performance and Technology Readiness Level of Reversible Solid Oxide Cells," Sustainability, MDPI, vol. 13(9), pages 1-23, April.
    13. Strübing, Dietmar & Moeller, Andreas B. & Mößnang, Bettina & Lebuhn, Michael & Drewes, Jörg E. & Koch, Konrad, 2018. "Anaerobic thermophilic trickle bed reactor as a promising technology for flexible and demand-oriented H2/CO2 biomethanation," Applied Energy, Elsevier, vol. 232(C), pages 543-554.
    14. Blanco, Herib & Leaver, Jonathan & Dodds, Paul E. & Dickinson, Robert & García-Gusano, Diego & Iribarren, Diego & Lind, Arne & Wang, Changlong & Danebergs, Janis & Baumann, Martin, 2022. "A taxonomy of models for investigating hydrogen energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    15. Qichen Wang & Zhengmeng Hou & Yilin Guo & Liangchao Huang & Yanli Fang & Wei Sun & Yuhan Ge, 2023. "Enhancing Energy Transition through Sector Coupling: A Review of Technologies and Models," Energies, MDPI, vol. 16(13), pages 1-31, July.
    16. Barman, Mayur & Dev Choudhury, Nalin Behari, 2019. "Season specific approach for short-term load forecasting based on hybrid FA-SVM and similarity concept," Energy, Elsevier, vol. 174(C), pages 886-896.
    17. Wen, Lulu & Zhou, Kaile & Yang, Shanlin & Lu, Xinhui, 2019. "Optimal load dispatch of community microgrid with deep learning based solar power and load forecasting," Energy, Elsevier, vol. 171(C), pages 1053-1065.
    18. Lu, Xinyu & Du, Banghua & Zhu, Wenchao & Yang, Yang & Xie, Changjun & Tu, Zhengkai & Zhao, Bo & Zhang, Leiqi & Wang, Jianqiang & Yang, Zheng, 2024. "Multi-criteria assessment of an auxiliary energy system for desalination plant based on PEMFC-ORC combined heat and power," Energy, Elsevier, vol. 290(C).
    19. Gawlick, Julia & Hamacher, Thomas, 2023. "Impact of coupling the electricity and hydrogen sector in a zero-emission European energy system in 2050," Energy Policy, Elsevier, vol. 180(C).
    20. Xie, Shaobo & Hu, Xiaosong & Liu, Teng & Qi, Shanwei & Lang, Kun & Li, Huiling, 2019. "Predictive vehicle-following power management for plug-in hybrid electric vehicles," Energy, Elsevier, vol. 166(C), pages 701-714.

    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:eee:energy:v:181:y:2019:i:c:p:77-90. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    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.