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Görtler, Gregor
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Official Name
Görtler, Gregor
Main Affiliation
Akademische Titel
DI Dr.
Email
gregor.goertler@fh-burgenland.at
Scopus Author ID
8340337300
Status
staff
Research Outputs
Now showing 1 - 10 of 10
- PublicationSimulation einer prädiktiven Raumtemperaturregelung unter Verwendung einer idealen WettervorhersageDurch die Anwendung von prädiktiven Regelalgorithmen (Model Predictive Control MPC) für die Raumheizung versprechen sich Errichter und Betreiber eine nennenswerte Energieeinsparung. Mittels einer Simulation soll für einen ausgewählten Fall das Energieeinsparpotential eines prädiktiven Regelalgorithmus zur Raumtemperaturregelung unter Verwendung einer idealen Wettervorhersage im Vergleich zu gängigen Algorithmen wie z. B. PI‐Regler oder Zweipunktregler abgeschätzt werden. Als Regelstrecke mit der Regelgröße Raumtemperatur dient ein Raum mit Fußbodenheizung, der in TRNSYS modelliert wurde. Mittels geeigneter Identifikationsmethoden wurde ein lineares Zustandsraummodell der Regelstrecke entworfen, welches vom prädiktiven Regelalgorithmus, der in MATLAB programmiert wurde, verwendet wird. Durch Einbindung eines Referenzwetterdatensatzes aus der TRNSYS‐Bibliothek, welcher dem Regelalgorithmus zur Verfügung gestellt wird, sind alle relevanten Wetterdaten bereits im Voraus bekannt (ideale Wettervorhersage). Für die in diesem Beitrag betrachtete Konfiguration ergab sich ein Energieeinsparpotential von ca. 10 % pro Jahr bei der Verwendung eines MPCReglers, verglichen mit einem PI‐Regler.
432 1 - PublicationCarbon monoxide emission models for small-scale biomass combustion of wooden pelletsTighter legal emission limits require means to prevent releasing harmful substances into the atmosphere during the combustion of biomass. Economic considerations suggest to meet these restrictions by improving the ability to predict and therefore prevent emissions, which can be done by improved control algorithms. This work presents different methods to obtain models for the prediction of carbon monoxide emissions in a small-scale biomass combustion furnace for wooden pellets. The presented models are intended for an application in model based control, either as part of the underlying model or for carbon monoxide soft sensing and fault detection. The main focus is on simple structures which can be handled by the already existing hardware of the furnaces. Different black-box models and a kinetic process model are introduced and compared. The black-box models are based on the measured flue gas oxygen concentration and the combustion temperature, since these measurements are typically available even for smaller plants. The obtained models are validated with measured data in order to find the most suitable structures, of which combined fuzzy black-box models show the most promising results. The presented methodology can be readily applied to the investigated furnace. However, the model parameters have to be adapted for other plants.
468 1Scopus© Citations 17 - Publication
117 1Scopus© Citations 23 - Publication
550 2 - PublicationEmission limited model predictive control of a small-scale biomass furnace(Elsevier, 2021-03-01)
; ; ; Kozek, MartinThis paper presents the application of an emission limiting model-based predictive controller for a small-scale biomass grate furnace. The furnace has a nominal power of 100 kW with wood pellets as fuel, but it can be operated with different fuels as well. The model predictive approach extends the existing static feedforward controller of the investigated furnace with a dynamic feedback controller that is able to improve the combustion performance. Simultaneously, the formation of carbon monoxide emissions is minimized within the prediction horizon based on an available emission estimation model for pellets. The results obtained from closed-loop measurements show that the control concept is able to reduce carbon monoxide emissions in partial load operation up to four times while the control error of the supply water temperature for heating is nearly halved during transient operation. This is achieved by incorporating the emission estimation model into the constrained optimization of the predictive controller. Additional results obtained from closed-loop experiments for different fuel types with varying water contents demonstrate the advantages of the proposed model-based approach and its robustness with respect to typical uncertainties of the combustion process.207 36536Scopus© Citations 8 - PublicationSmart home management system with extensive disturbance predictions(Leykam, 2018-11)
106 543 - PublicationTest buildings with TABS for MPC-performance evaluation — Comparability and system identificationThe research project (MPC-Boxes) deals with the design and construction of two test buildings (Test-Boxes), built for the purpose of performance evaluation of a model predictive controller (MPC) in comparison to a standard controller - for heating and cooling via thermally activated building systems (TABS). The paper introduces the experimental environment, investigates the thermo-physical similarity of the two Test-Boxes, and deals with system identification related aspects. A simple third order state space model (SSM) is derived from first principles. This SSM served as a basis for the derivation of a structured SSM which is facilitated for parameter estimation by means of real measurement data. The performance of the structured SSM is validated with different identification data. The cross-validation performance decreases especially for longer validation intervals, however, within the MPC relevant prediction horizon the performance is still acceptable.
73 1Scopus© Citations 2 - PublicationModel Predictive Control of Biomass Combustion with CO Sensor Fault Detection(2022)
; ; Martin Kozek14 1 - PublicationA novel linear predictive control approach for auxiliary energy supply to a solar thermal combistorage(Elsevier, 2014)
; 68 1Scopus© Citations 17