lynx   »   [go: up one dir, main page]

IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v18y2025i15p3977-d1709885.html
   My bibliography  Save this article

Energy Management of Industrial Energy Systems via Rolling Horizon and Hybrid Optimization: A Real-Plant Application in Germany

Author

Listed:
  • Loukas Kyriakidis

    (German Aerospace Center, Institute of Low-Carbon Industrial Processes, Simulation and Virtual Design Department, Walther-Pauer-Straße 5, 03046 Cottbus, Germany)

  • Rushit Kansara

    (German Aerospace Center, Institute of Low-Carbon Industrial Processes, Simulation and Virtual Design Department, Walther-Pauer-Straße 5, 03046 Cottbus, Germany)

  • Maria Isabel Roldán Serrano

    (German Aerospace Center, Institute of Low-Carbon Industrial Processes, Simulation and Virtual Design Department, Walther-Pauer-Straße 5, 03046 Cottbus, Germany)

Abstract
Industrial energy systems are increasingly required to reduce operating costs and CO 2 emissions while integrating variable renewable energy sources. Managing these objectives under uncertainty requires advanced optimization strategies capable of delivering reliable and real-time decisions. To address these challenges, this study focuses on the short-term operational planning of an industrial energy supply system using the rolling horizon approach (RHA). The RHA offers an effective framework to handle uncertainties by repeatedly updating forecasts and re-optimizing over a moving time window, thereby enabling adaptive and responsive energy management. To solve the resulting nonlinear and constrained optimization problem at each RHA iteration, we propose a novel hybrid algorithm that combines Bayesian optimization (BO) with the Interior Point OPTimizer (IPOPT). While global deterministic and stochastic optimization methods are frequently used in practice, they often suffer from high computational costs and slow convergence, particularly when applied to large-scale, nonlinear problems with complex constraints. To overcome these limitations, we employ the BO–IPOPT, integrating the global search capabilities of BO with the efficient local convergence and constraint fulfillment of the IPOPT. Applied to a large-scale real-world case study of a food and cosmetic industry in Germany, the proposed BO–IPOPT method outperformed state-of-the-art solvers in both solution quality and robustness, achieving up to 97.25%-better objective function values at the same CPU time. Additionally, the influence of key parameters, such as forecast uncertainty, optimization horizon length, and computational effort per RHA iteration, was analyzed to assess their impact on system performance and decision quality.

Suggested Citation

  • Loukas Kyriakidis & Rushit Kansara & Maria Isabel Roldán Serrano, 2025. "Energy Management of Industrial Energy Systems via Rolling Horizon and Hybrid Optimization: A Real-Plant Application in Germany," Energies, MDPI, vol. 18(15), pages 1-29, July.
  • Handle: RePEc:gam:jeners:v:18:y:2025:i:15:p:3977-:d:1709885
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/18/15/3977/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/18/15/3977/
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:18:y:2025:i:15:p:3977-:d:1709885. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.
    Лучший частный хостинг