Now showing 1 - 10 of 10
- PublicationA novel linear predictive control approach for auxiliary energy supply to a solar thermal combistorage(Elsevier, 2014)
;Pichler, Martin Felix ;Lerch, Werner ;Heinz, Andreas ; ;Schranzhofer, HermannRieberer, RenéThis paper presents and investigates a novel, hybrid model predictive approach to control the auxiliary heating for a combistorage. Faulty design, as well as suitable design schemes cause situations in which solar energy supply has to “compete against” the auxiliary energy supply. This research demonstrates a feasible method to remedy such situations with the utilization of weather forecast data. The developed approach is modular and expandable to be used with additional heat sources. A suitable disturbance-prediction, which approximates the expected solar energy flux into the storage, in connection with a linear model predictive control (MPC), can prevent the auxiliary system to switch on at an early stage and thus reduce the auxiliary energy demand and keep storage capacity for solar thermal energy supply. Results obtained through simulations for selected months show a reduction of auxiliary energy demand up to 40%, when facilitating this approach for a solar thermal combisystem for a single family house. Monthly solar fractions (Fs) increase by approximately 4% points or 5% with respect to the base case. 68Scopus© Citations 16
- PublicationFuzzy model predictive control for small-scale biomass combustion furnaces
117Scopus© Citations 15
- PublicationModel Predictive Control of Biomass Combustion with CO Sensor Fault Detection
- PublicationEmission limited model predictive control of a small-scale biomass furnaceThis 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 174Scopus© Citations 5
- PublicationSmart home management system with extensive disturbance predictions(Leykam, 2018-11)
;Zauner, Michael ;Killian, M. ;Böhler, Lukas ;Kozek, Martin ;Leitner, A. ;Goldgruber, R. 106 132
- PublicationTest buildings with TABS for MPC-performance evaluation — Comparability and system identification(IEEE, 2016)
;Pichler, Martin Felix ;Schranzhofer, HermannThe 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. 73Scopus© Citations 2
- PublicationSimulation einer prädiktiven Raumtemperaturregelung unter Verwendung einer idealen Wettervorhersage(Wiley, 2010-12)
;Beigelböck, BarbaraDurch 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
- 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.
468Scopus© Citations 14