IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i12p2945-d1415234.html
   My bibliography  Save this article

Feasible Actuator Range Modifier (FARM), a Tool Aiding the Solution of Unit Dispatch Problems for Advanced Energy Systems

Author

Listed:
  • Haoyu Wang

    (Argonne National Laboratory, Lemont, IL 60439, USA)

  • Roberto Ponciroli

    (Argonne National Laboratory, Lemont, IL 60439, USA)

  • Andrea Alfonsi

    (Nucube Energy, Inc., Pasadena, CA 91103, USA)

  • Paul W. Talbot

    (Idaho National Laboratory, Idaho Falls, ID 83415, USA)

  • Thomas W. Elmer

    (Argonne National Laboratory, Lemont, IL 60439, USA)

  • Aaron S. Epiney

    (Idaho National Laboratory, Idaho Falls, ID 83415, USA)

  • Richard B. Vilim

    (Argonne National Laboratory, Lemont, IL 60439, USA)

Abstract

Integrated energy systems (IESs) seek to minimize power generating costs in future power grids through the coupling of different energy technologies. To accommodate fluctuations in load demand due to the penetration of renewable energy sources, flexible operation capabilities must be fully exploited, and even power plants that are traditionally considered as base-load units need to be operated according to unconventional paradigms. Thermomechanical loads induced by frequent power adjustments can accelerate the wear and tear. If a unit is flexibly operated without respecting limits on materials, the risk of failures of expensive components will eventually increase, nullifying the additional profits ensured by flexible operation. In addition to the bounds on power variations (explicit constraints),the solution of the unit dispatch problem needs to meet the limits on the variation of key process variables, including temperature, pressure and flow rate (implicit constraints).The FARM (Feasible Actuator Range Modifier) module was developed to enable existing optimization algorithms to identify solutions to the unit dispatch problem that are both economically favorable and technologically sustainable. Thanks to the iterative dispatcher–validator scheme, FARM permits addressing all the imposed constraints without excessively increasing the computational costs. In this work, the algorithms constituting the module are described, and the performance was assessed by solving the unit dispatch problem for an IES composed of three units, i.e., balance of plant, gas turbine, and high-temperature steam electrolysis. Finally, the FARM module provides dedicated tools for visualizing the response of the constrained variables of interest during operational transients and a tool aiding the operator at making decisions. These techniques might represent the first step towards the deployment of an ecological interface design (EID) for IES units.

Suggested Citation

  • Haoyu Wang & Roberto Ponciroli & Andrea Alfonsi & Paul W. Talbot & Thomas W. Elmer & Aaron S. Epiney & Richard B. Vilim, 2024. "Feasible Actuator Range Modifier (FARM), a Tool Aiding the Solution of Unit Dispatch Problems for Advanced Energy Systems," Energies, MDPI, vol. 17(12), pages 1-36, June.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:12:p:2945-:d:1415234
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/12/2945/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/17/12/2945/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Kim, Jong Suk & Boardman, Richard D. & Bragg-Sitton, Shannon M., 2018. "Dynamic performance analysis of a high-temperature steam electrolysis plant integrated within nuclear-renewable hybrid energy systems," Applied Energy, Elsevier, vol. 228(C), pages 2090-2110.
    2. Epiney, A. & Rabiti, C. & Talbot, P. & Alfonsi, A., 2020. "Economic analysis of a nuclear hybrid energy system in a stochastic environment including wind turbines in an electricity grid," Applied Energy, Elsevier, vol. 260(C).
    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. Yi, Zonggen & Luo, Yusheng & Westover, Tyler & Katikaneni, Sravya & Ponkiya, Binaka & Sah, Suba & Mahmud, Sadab & Raker, David & Javaid, Ahmad & Heben, Michael J. & Khanna, Raghav, 2022. "Deep reinforcement learning based optimization for a tightly coupled nuclear renewable integrated energy system," Applied Energy, Elsevier, vol. 328(C).
    2. Stančin, H. & Mikulčić, H. & Wang, X. & Duić, N., 2020. "A review on alternative fuels in future energy system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 128(C).
    3. Athanasios Ioannis Arvanitidis & Vivek Agarwal & Miltiadis Alamaniotis, 2023. "Nuclear-Driven Integrated Energy Systems: A State-of-the-Art Review," Energies, MDPI, vol. 16(11), pages 1-23, May.
    4. Zhong, Like & Yao, Erren & Zou, Hansen & Xi, Guang, 2022. "Thermodynamic and economic analysis of a directly solar-driven power-to-methane system by detailed distributed parameter method," Applied Energy, Elsevier, vol. 312(C).
    5. Epiney, A. & Rabiti, C. & Talbot, P. & Alfonsi, A., 2020. "Economic analysis of a nuclear hybrid energy system in a stochastic environment including wind turbines in an electricity grid," Applied Energy, Elsevier, vol. 260(C).
    6. Wang, L.X. & Zheng, J.H. & Li, M.S. & Lin, X. & Jing, Z.X. & Wu, P.Z. & Wu, Q.H. & Zhou, X.X., 2019. "Multi-time scale dynamic analysis of integrated energy systems: An individual-based model," Applied Energy, Elsevier, vol. 237(C), pages 848-861.
    7. Jia Zhou & Hany Abdel-Khalik & Paul Talbot & Cristian Rabiti, 2021. "A Hybrid Energy System Workflow for Energy Portfolio Optimization," Energies, MDPI, vol. 14(15), pages 1-28, July.
    8. El-Emam, Rami S. & Constantin, Alina & Bhattacharyya, Rupsha & Ishaq, Haris & Ricotti, Marco E., 2024. "Nuclear and renewables in multipurpose integrated energy systems: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
    9. Athanasios Ioannis Arvanitidis & Miltiadis Alamaniotis, 2024. "Integrating an Ensemble Reward System into an Off-Policy Reinforcement Learning Algorithm for the Economic Dispatch of Small Modular Reactor-Based Energy Systems," Energies, MDPI, vol. 17(9), pages 1-21, April.
    10. Gong, Yu & Liu, Pan & Liu, Yini & Huang, Kangdi, 2021. "Robust operation interval of a large-scale hydro-photovoltaic power system to cope with emergencies," Applied Energy, Elsevier, vol. 290(C).
    11. Zhang, Ru & Qiu, Leilei & Sun, Peiwei & Wei, Xinyu, 2024. "Research on nuclear reactor power control system of VVER-1000 with thermal energy supply system," Energy, Elsevier, vol. 294(C).
    12. Ramirez-Corredores, M.M. & Diaz, Luis A. & Gaffney, Anne M. & Zarzana, Christopher A., 2021. "Identification of opportunities for integrating chemical processes for carbon (dioxide) utilization to nuclear power plants," Renewable and Sustainable Energy Reviews, Elsevier, vol. 150(C).
    13. Johan Augusto Bocanegra Cifuentes & Davide Borelli & Antonio Cammi & Guglielmo Lomonaco & Mario Misale, 2020. "Lattice Boltzmann Method Applied to Nuclear Reactors—A Systematic Literature Review," Sustainability, MDPI, vol. 12(18), pages 1-37, September.
    14. Kang, Seong Woo & Yim, Man-Sung, 2023. "Coupled system model analysis for a small modular reactor cogeneration (combined heat and power) application," Energy, Elsevier, vol. 262(PA).
    15. Takasu, Hiroki & Hoshino, Hitoshi & Tamura, Yoshiro & Kato, Yukitaka, 2019. "Performance evaluation of thermochemical energy storage system based on lithium orthosilicate and zeolite," Applied Energy, Elsevier, vol. 240(C), pages 1-5.
    16. Xu, Changrui & Xu, Xiaosheng & Li, Mengshi & Wu, Qinghua & Zheng, Jiehui & Xiao, Wenting, 2024. "A multi-rate dynamic analysis method of individual-based district heating system," Energy, Elsevier, vol. 295(C).

    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:17:y:2024:i:12:p:2945-:d:1415234. 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.