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    Distributed Optimization with Application to Power Systems and Control

    Dissertations (Dissertationen)

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    Author(s)
    Engelmann, Alexander
    Collection
    AG Universitätsverlage
    Language
    English
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    Abstract
    Mathematical optimization techniques are among the most successful tools for controlling technical systems optimally with feasibility guarantees. Yet, they are often centralized—all data has to be collected in one central and computationally powerful entity. Methods from distributed optimization overcome this limitation. Classical approaches, however, are often not applicable due to non-convexities. This work develops one of the first frameworks for distributed non-convex optimization.
    URI
    https://library.oapen.org/handle/20.500.12657/59833
    Keywords
    Verteilte Optimierung; Dezentrale Optimierung; ALADIN; ADMM; Optimal Power Flow; distributed optimization; decentralized optimization; optimal power flow
    DOI
    10.5445/KSP/1000144792
    ISBN
    9783731511809, 9783731511809
    Publisher
    KIT Scientific Publishing
    Publisher website
    https://www.ksp.kit.edu/index.php?link=shop&sort=all
    Publication date and place
    Karlsruhe, 2022
    Imprint
    KIT Scientific Publishing
    Classification
    Maths for computer scientists
    Pages
    226
    Rights
    http://creativecommons.org/licenses/by-sa/4.0
    • Imported or submitted locally

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    License

    • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

    Credits

    • logo EU
    • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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