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Titel:

Optimal Control Combined-Cycle Power Plants: A Data-Enabled Predictive Control Perspective

Dokumenttyp:
Konferenzbeitrag
Art des Konferenzbeitrags:
Textbeitrag / Aufsatz
Autor(en):
Mahdavipour, P.; Wieland, C; , Spliethoff, H.
Seitenangaben Beitrag:
91-96
Abstract:
In this work, we propose an optimal control strategy as the unit control for combined-cycle power generation units. Using the same optimal control, we propose to optimize other internal control structures. Data-Enabled Predictive Control is chosen as the optimal control problem formulation, as it does not require a parametric state-space representation of the system. This bypasses the challenging and expensive-to-solve issue of parametric modeling and linearization for highly nonlinear systems....     »
Stichworte:
Data-Enabled Predictive Control, Power Networks, Flexibility, Power Plant Control, Frequency Control, Load Cycling
Herausgeber:
Elsevier B.V.
Kongress- / Buchtitel:
9th IFAC Conference on Networked Systems NECSYS 2022 / IFAC-PapersOnLine
Band / Teilband / Volume:
55 / 13
Datum der Konferenz:
5–7 July 2022
Publikationsdatum:
05.07.2022
Jahr:
2022
Seiten:
91-96
Nachgewiesen in:
Scopus; Web of Science
E-ISBN:
2405-8963
Reviewed:
ja
Sprache:
en
Volltext / DOI:
doi:https://doi.org/10.1016/j.ifacol.2022.07.241
TUM Einrichtung:
Lehrstuhl für Energiesysteme
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