Design, optimization and validation of start-up sequences of energy production systems.
type: Dataset
description: This thesis focuses on the application of model predictive control approaches to optimize the combined cycle power plants start-ups. Generally, the optimization of start-up is a very problematic issue that poses significant challenges. The development of the proposed approaches is progressive. In the first part a physical model of plant is developed and adapted to optimization purposes, by using a methodology which transforms Modelica model components into optimization-oriented models. By applying this methodology, a library suitable for optimization purposes has been built.In the second part, based on the developed model, an optimization procedure to improve the performances of the start-up phases is suggested. The proposed solution optimizes, in continuous time, the load profile of the turbines, by seeking in specific sets of functions. The optimal profile is derived by considering that this profile can be described by a parameterized function whose parameters are computed by solving a constrained optimal control problem. In the last part, the open-loop optimization procedure has been integrated into a receding horizon control strategy. This strategy represents a robust solution against perturbation and models errors, and enables to improve the trade-off between computation time and optimality of the solution. Nevertheless, the control approach leads to a significant computation time. In order to obtain real-time implementable results, a hierarchical model predictive control structure with two layers, working at different time scales and over different prediction horizons, has been proposed.
landing page: https://theses.hal.science/tel-00765438
identifier: NNT: 2012SUPL0009
keyword: centrales-a-cycles-combines
keyword: combined-cycle-power-plants
keyword: commande-hierarchisee
keyword: commande-predictive
keyword: hierarchical-control
keyword: infoeu-reposemanticsdoctoralthesis
keyword: large-scale-systems
keyword: model-predictive-control
keyword: modelisation-physique
keyword: optimisation
keyword: optimization
keyword: phase-de-demarrage
keyword: physical-modeling
keyword: spiotherengineering-sciences-physicsother
keyword: start-up
keyword: systeme-de-grande-taille
keyword: theses
issued: 2026-05-30T23:28:33.631664
modified: 2026-05-30T23:28:33.631680
language: en
contact point: Organization
  fn: CCSD

test_moissonnage_selune
type: Agent

Design, optimization and validation of start-up sequences of energy production systems.
type: Distribution
format: HTML
access URL: https://theses.hal.science/tel-00765438
issued: 2026-05-30T23:28:33.888532
modified: 2026-05-30T23:28:33.514297