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

Pouya Mahdavipour, Christoph Wieland, Hartmut Spliethoff

Research output: Contribution to journalConference articlepeer-review

5 Scopus citations

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. The performance of the controller is investigated in several critical operational scenarios, such as load-following for frequency control and disturbance rejection. Simulation results in Apros®, which is an environment dedicated to advanced process simulation, are presented.

Original languageEnglish
Pages (from-to)91-96
Number of pages6
JournalIFAC Proceedings Volumes (IFAC-PapersOnline)
Volume55
Issue number13
DOIs
StatePublished - 2022
Event9th IFAC Conference on Networked Systems, NECSYS 2022 - Zurich, Switzerland
Duration: 5 Jul 20227 Jul 2022

Keywords

  • Data-Enabled Predictive Control
  • Flexibility
  • Frequency Control
  • Load Cycling
  • Power Networks
  • Power Plant Control

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