h1

% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@PHDTHESIS{Popp:1025017,
      author       = {Popp, Rudolf},
      othercontributors = {Abel, Dirk and Pitz-Paal, Robert},
      title        = {{M}odellprädiktive {R}egelung von
                      {S}olarturm-{K}raftwerken},
      school       = {Rheinisch-Westfälische Technische Hochschule Aachen},
      type         = {Dissertation},
      address      = {Aachen},
      publisher    = {RWTH Aachen University},
      reportid     = {RWTH-2026-00473},
      pages        = {1 Online-Ressource : Illustrationen},
      year         = {2025},
      note         = {Veröffentlicht auf dem Publikationsserver der RWTH Aachen
                      University 2026; Dissertation, Rheinisch-Westfälische
                      Technische Hochschule Aachen, 2025},
      abstract     = {The safe and efficient operation of solar thermal tower
                      power plants poses a demanding automation challenge due to
                      complex system dynamics and extreme thermal conditions.
                      While higher temperatures improve efficiency, material
                      constraints impose strict thermal limits. Conventional
                      control strategies, such as feedforward PID controllers with
                      heuristic safety mechanisms, reach their limits under
                      dynamic disturbances like passing clouds. They react only
                      after deviations occur, operate conservatively and do not
                      fully exploit the available solar power potential. This work
                      investigates the application of Model Predictive Control
                      (MPC) as an active strategy to balance efficiency and
                      safety. By leveraging a physics-based system model, the MPC
                      enables predictive optimization over a finite planning
                      horizon while explicitly considering thermal limits and
                      dynamic system responses. The first application focuses on
                      the control of a molten-salt receiver for power generation.
                      Compared to a conventional PID controller, the MPC reduces
                      the root mean square temperature deviation by $45\%,$
                      maintains a thermal efficiency of approximately $86\%,$ and
                      avoids all critical limit violations. Across 34 simulated
                      scenarios, including dynamic cloud-induced irradiance
                      fluctuations, MPC demonstrates significantly higher
                      robustness. The second application addresses a multi-reactor
                      receiver for direct hydrogen production, where solar
                      radiation must be dynamically allocated among several
                      reactors. A detailed parameter study identified an efficient
                      reduction regime, which MPC is able to target specifically.
                      In hybrid field trials with four inactive reactor dummies,
                      the precise control of absorber temperature and reduction
                      degree proves fundamentally feasible. However, this is
                      contingent on accurate realization of the commanded
                      irradiance. Deviations of up to $60\%$ between target and
                      actual irradiance are successfully mitigated using an
                      integrated disturbance observer. In summary, this work
                      demonstrates that MPC holds strong potential for operating
                      solar thermal systems closer to their physical performance
                      limits without compromising safety. MPC thus represents a
                      promising approach to enhance efficiency and economic
                      viability of next-generation solar tower power plants.},
      cin          = {416610},
      ddc          = {620},
      cid          = {$I:(DE-82)416610_20140620$},
      pnm          = {BMWE 0324202D - Verbundvorhaben: DynaSalt-2 -
                      Unterstützung des dynamischen Betriebs von
                      Salzschmelzereceivern; Teilvorhaben: Regelung des
                      transienten einphasigen Betriebs von Salzschmelzereceivern
                      (0324202D) / BMWE 03EE5042B - Verbundvorhaben: SolarFuelNow
                      - Effiziente Regelung solarer Kraftstoffproduktion mit DNI
                      Nowcasts; Teilvorhaben: Modellbasierte Mehrgrößenregelung
                      solarer Multikammerreaktoren unter Einbeziehung eines
                      DNI­Nowcasts (03EE5042B)},
      pid          = {G:(BMWE)0324202D / G:(BMWE)03EE5042B},
      typ          = {PUB:(DE-HGF)11},
      doi          = {10.18154/RWTH-2026-00473},
      url          = {https://publications.rwth-aachen.de/record/1025017},
}