ISBN 978-3-8439-5756-4

978-3-8439-5756-4, Reihe Energietechnik

Pouya Mahdavipour Vahdati
Operational Flexibility in Combined-Cycle Power Plants through Predictive Control

184 Seiten, Dissertation Technische Universität München (2026), Softcover, A5

Zusammenfassung / Abstract

The rapid integration of intermittent renewable energy sources into modern power grids imposes increasingly stringent flexibility requirements on conventional thermal generation units. Natural-Gas Combined-Cycle Power Plants (CCPPs) constitute a critical asset class within this evolving energy landscape; however, the inherently slow thermodynamic dynamics of the Heat-Recovery Steam Generator (HRSG) impose fundamental constraints on load-cycling capability that established classical control architectures are unable to fully overcome.

This dissertation advances the operational flexibility through the development and application of two novel control methodologies: a frequency-domain system identification tool for the systematic optimization of individual control loops, and a nonlinear, multi-point Data-Enabled Predictive Control (DeePC) framework for coordinated unit-level MIMO control. Grounded in behavioral systems theory, the proposed approach yields a significant enhancement in operational flexibility during load-cycling regimes, while simultaneously maintaining highly stable and optimized thermodynamic process properties, establishing data-driven predictive control as a compelling and practically viable paradigm for the next generation of flexible thermal power generation.