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Publikationen


Peer Reviewed Scientific Journals | 2022

A multi-layer model of stratified thermal storage for MILP-based energy management systems

Muschick D, Zlabinger S, Moser A, Lichtenegger K, Gölles M. A multi-layer model of stratified thermal storage for MILP-based energy management systems. Applied Energy. 2022 May 15;315.118890. https://doi.org/10.1016/j.apenergy.2022.118890

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Both the planning and operation of complex, multi-energy systems increasingly rely on optimization. This optimization requires the use of mathematical models of the system components. The model most often used to describe thermal storage, and especially in the common mixed-integer linear program (MILP) formulation, is a simple integrator model with a linear loss term. This simple model has multiple inherent drawbacks since it cannot be applied to represent the temperature distribution inside of the storage unit. In this article, we present a novel approach based on multiple layers of variable size but fixed temperature. The model is still linear, but can be used to describe the most relevant physical phenomena: heat losses, axial heat transport, and, at least qualitatively, axial heat conduction. As an additional benefit, this model makes it possible to clearly distinguish between heat available at different temperatures and thus suitable for different applications, e.g., space heating or domestic hot water. This comes at the cost of additional binary decision variables used to model the resulting hybrid linear dynamics, requiring the use of state-of-the-art MILP solvers to solve the resulting optimization problems. The advantages of the more detailed model are demonstrated by validating it against a standard model based on partial differential equations and by showing more realistic results for a simple energy optimization problem.


Conference contributions | 2022

Automatic Thermal Model Identification and Distributed Optimisation for Load Shifting in City Quarters

Moser A, Kaisermayer V, Muschick D, Zemann C, Gölles M, Hofer A, Brandl D, Heimrath R, Mach T, Tugores C R, Ramschak, T. Automatic Thermal Model Identification and Distributed Optimisation for Load Shifting in City Quarters. 2nd International Sustainable Energy Conference: ISEC 2022. Graz, 07/04/2022. Oral presentation.

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Modern buildings with floor heating or thermally activated building structures (TABS) offer a significant potential for shifting the thermal load and thus reduce peak demand for heating or cooling. This potential can be realized with the help of model predictive control (MPC) methods, provided that sufficiently descriptive mathematical models describing the thermal characteristics of the individual thermal zones exist. Creating these by hand or from more detailed simulation models is infeasible for large numbers of zones; instead, they must be identified automatically based on measurement data. We present an approach using only open source tools based on the programming language Julia that allows to robustly identify simple thermal models for heating and cooling usable in MPC optimization. The resulting models are used in a distributed optimization scheme that co-ordinates the individual zones and buildings of a city quarter in order to best support an energy hub.


Conference contributions | 2022

FAULT DETECTIVE: FAULT DETECTION FOR SOLAR THERMAL SYSTEMS

Feierl L, Bolognesi T, Unterberger V, Geatani M, Gerardts B. FAULT DETECTIVE: FAULT DETECTION FOR SOLAR THERMAL SYSTEMS. ISEC 2022. 05 - 07. April 2022, Graz. Poster presentation.

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Conference contributions | 2022

IEA SHC Task 68: Efficient Solar District Heating Systems

Unterberger V, Berberich M, Putz S, Byström J, Gölles M. IEA SHC Task 68: Efficient Solar District Heating Systems. ISEC 2022. 5 - 07. April 2022, Graz. Poster presentation.

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Reviewed Conference Papers | 2022

Increased Flexibility of A Fixed-Bed Biomass Gasifier through Advanced Control

Hollenstein C, Zemann C, Martini S, Gölles M, Felsberger W, Horn M. Increased Flexibility of A Fixed-Bed Biomass Gasifier through Advanced Control. Proceedings of the 30th European Biomass Conference and Exhibition. 2022. 704-711.

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Most industrial fixed-bed biomass gasification systems usually operate at steady-state to produce the maximum amount of energy possible although they can principally modulate their loads to compensate for the fluctuations of other volatile renewable energy systems. To unleash their full load modulation capability, their typically traditional control strategies should be improved, their gas residence times affected by typically basic char removal strategies adjusted and any required manual interaction of an operator avoided. In this respect, a new controller for the char handling (accumulation and removal) of the reduction zone in a fixed-bed biomass gasifier of a representative industrial small-scale gasification system is developed and experimentally verified. This new controller consists of a recursive least-squares estimator for the flow resistance of the gasifier representing the amount of char inside and a switching controller for rotating a grate located at its bottom. The experimental verification reveals that only the traditional (pressure-based) controller requires manual adjustment of the thresholds. Moreover, the new controller (flow resistance based) significantly reduces the fluctuation range during partial load and stabilizes the temperature and pressure downstream the gasifier. This provides the basis for enhancing its fuel flexibility too and is an important feature for flexible operation in future.


Peer Reviewed Scientific Journals | 2022

Smart control of interconnected district heating networks on the example of “100% Renewable District Heating Leibnitz”

Kaisermayer V, Binder J, Muschick D, Beck G, Rosegger W, Horn M, Gölles M, Kelz J, Leusbrock I. Smart control of interconnected district heating networks on the example of “100% Renewable District Heating Leibnitz”. Smart Energy. 2022 Apr 7. 100069. https://doi.org/10.1016/j.segy.2022.100069

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District heating (DH) networks have the potential for intelligent integration and combination of renewable energy sources, waste heat, thermal energy storage, heat consumers, and coupling with other sectors. As cities and municipalities grow, so do the corresponding networks. This growth of district heating networks introduces the possibility of interconnecting them with neighbouring networks. Interconnecting formerly separated DH networks can result in many advantages concerning flexibility, overall efficiency, the share of renewable sources, and security of supply. Apart from the problem of hydraulically connecting the networks, the main challenge of interconnected DH systems is the coordination of multiple feed-in points. It can be faced with control concepts for the overall DH system which define optimal operation strategies. This paper presents two control approaches for interconnected DH networks that optimize the supply as well as the demand side to reduce CO2 emissions. On the supply side, an optimization-based energy management system defines operation strategies based on demand forecasts. On the demand side, the operation of consumer substations is influenced in favour of the supply using demand side management. The proposed approaches were tested both in simulation and in a real implementation on the DH network of Leibnitz, Austria. First results show a promising reduction of CO2 emissions by 35% and a fuel cost reduction of 7% due to better utilization of the production capacities of the overall DH system.


Other Presentations | 2022

Solar goes Digital: Wie Solarwärme selbstlernende Algorithmen nutzt (Austria Solar Webinar 26)

Unterberger V. Solar goes Digital: Wie Solarwärme selbstlernende Algorithmen nutzt (Austria Solar Webinar 26). Online am 11.05.2022.

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Conference contributions | 2022

Success Factors and Barriers for Integrated District Heating Networks

Muschick D, Cronbach D, Ianakiev A, Kallert A, Schmidt R-R, Sorknaes P et al. Success Factors and Barriers for Integrated District Heating Networks. 2022. Postersitzung präsentiert bei 2nd International Sustainable Energy Conference , Graz, Österreich.

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Conference Papers | 2022

Technology and Process Improvement of a Demonstration Unit for a Novel Aqueous Phase Reforming Process Via Virtual Commissioning

Nigitz T, Arlt S, Poms U, Weber G, Luisser M, Gölles M. Technology and Process Improvement of a Demonstration Unit for a Novel Aqueous Phase Reforming Process Via Virtual Commissioning. Proceedings of the 30th European Biomass Conference and Exhibition. 2022. 948 - 950.

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A process demonstration unit for a novel aqueous phase reforming (APR) process was built and scaled up by factor 666. The set-up of this demonstration unit was supported by virtual commissioning using a virtual test bed. By using virtual commissioning, it was possible to speed-up the commissioning and to support stable, reliable and continuous plant operation for 100h.


Peer Reviewed Scientific Journals | 2022

Unknown input observer design for linear time-invariant multivariable systems based on a new observer normal form

Niederwieser H, Tranninger M, Seeber R, Reichhartinger M. Unknown input observer design for linear time-invariant multivariable systems based on a new observer normal form. International Journal of Systems Science. 2022 Apr 6. https://doi.org/10.1080/00207721.2022.2046201

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In various applications in the field of control engineering, the estimation of the state variables of dynamic systems in the presence of unknown inputs plays an important role. Existing methods require the so-called observer matching condition to be satisfied, rely on the boundedness e variables or exhibit an increased observer order of at least twice the plant order. In this article, a novel observer normal form for strongly observable linear time-invariant multivariable systems is proposed. In contrast to classical normal forms, the proposed approach also takes the unknown inputs into account. The proposed observer normal form allows for the straightforward construction of a higher-order sliding mode observer, which ensures global convergence of the estimation error within finite time even in the presence of unknown bounded inputs. Its application is not restricted to systems which satisfy the aforementioned limitations of already existing unknown input observers. The proposed approach can be exploited for the reconstruction of unknown inputs with bounded derivative and robust state-feedback control, which is shown by means of a tutorial example. Numerical simulations confirm the effectiveness of the presented work.


Peer Reviewed Scientific Journals | 2021

An adaptive short-term forecasting method for the energy yield of flat-plate solar collector systems

Unterberger V, Lichtenegger K, Kaisermayer V, Gölles M, Horn M. An adaptive short-term forecasting method for the energy yield of flat-plate solar collector systems. Applied Energy. 2021 Apr 16;2021(293). https://doi.org/10.1016/j.apenergy.2021.116891

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The number of large-scale solar thermal installations has increased rapidly in Europe in recent years, with 70 % of these systems operating with flat-plate solar collectors. Since these systems cannot be easily switched on and off but directly depend on the solar radiation, they have to be combined with other technologies or integrated in large energy systems. In order to most efficiently integrate and operate solar systems, it is of great importance to consider their expected energy yield to better schedule heat production, storage and distribution. To do so the availability of accurate forecasting methods for the future solar energy yield are essential. Currently available forecasting methods do not meet three important practical requirements: simple implementation, automatic adaption to seasonal changes and wide applicability. For these reasons, a simple and adaptive forecasting method is presented in this paper, which allows to accurately forecast the solar heat production of flat-plate collector systems considering weather forecasts. The method is based on a modified collector efficiency model where the parameters are continuously redetermined to specifically consider the influence of the time of the day. In order to show the wide applicability the method is extensively tested with measurement data of various flat-plate collector systems covering different applications (below 200 Celsius), sizes and orientations. The results show that the method can forecast the solar yield very accurately with a Mean Absolute Range Normalized Error (MARNE) of about 5 % using real weather forecasts as inputs and outperforms common forecasting methods by being nearly twice as accurate.


Other Presentations | 2021

Betrieb verbundener Nahwärmenetze mit getrennten Eigentümern

Zemann C, Muschick D, Kaisermayer V, Gölles M. Betrieb verbundener Nahwärmenetze mit getrennten Eigentümern. QM Heizwerke Fachtagung, Bad Vöslau, 14. Oktober, 2021. (oral presentation)

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Warum ist es sinnvoll, Wärmenetze zu verbinden?

  • Erläuterung am Beispiel des Projekts Thermaflex
  • Drei Wärmenetze bei Leibnitz in der Steiermark.
  • Sind gewachsen und haben die Grenzen ihrer Nachbar-Wärmenetze erreicht.
  • Die Wärmenetze werden durch zwei getrennte Eigentümer betrieben.

Other Publications | 2021

CO-lambda Optimierung - Betrieb von Biomassefeuerungen mit maximaler Effizienz und minimalen Emissionen

Zemann C. CO-lambda Optimierung - Betrieb von Biomassefeuerungen mit maximaler Effizienz und minimalen Emissionen. CO-lambda Optimierung - Betrieb von Biomassefeuerungen mit maximaler Effizienz und minimalen Emissionen. March 2021.

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Technical Reports | 2021

Control of DHC networks and Reduction of the operating temperatures in DH systems

Task 55 Towards the Integration of Large SHC Systems into DHC Networks

Gölles M, Muschick D, Unterberger V, Leoni P, Schmidt R, Lennermo G. "Control of DHC networks and Reduction of the operating temperatures in DH systems". EA SHC FACTSHEET 55.A-D4.2. Date of Publication: 28.01.2021. https://task55.iea-shc.org/fact-sheets

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Overview on different approaches for the control of the heat distribution networks in case of the integration of large-scale solar thermal systems, and different possibilities for the reduction of the operating temperatures in DH systems.


Technical Reports | 2021

Control of large-scale solar thermal plants

Task 55 Towards the Integration of Large SHC Systems into DHC Networks

Gölles M, Unterberger V. "Control of large-scale solar thermal plants". IEA SHC FACTSHEET 55.B-D3.1. Date of Publication: 28.01.2021. https://task55.iea-shc.org/fact-sheets

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Overview on the control of large-scale thermal plants, limited to plants feeding into DH networks as well as theirkey components, i.e. the actual collector circuit and the heat exchanger between primary and secondary circuit.


Technical Reports | 2021

Endbericht: Heat Pumping system Control (HPC)

Modellbasierte Regelung von Absorptionswärmepump-Anlagen.

Zlabinger S, Wernhart M, Unterberger V, Rieberer R, Gölles M, Rohringer C, Poier H, Halmdienst C, Kemmerzehl C, Otto M. Heat Pumping system Control (HPC). Modellbasierte Regelung von Absorptionswärmepump-Anlagen. FFG, 4. Ausschreibung Energieforschungsprogramm, Projektnummer: 865095. Endbericht. 2021.

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Other publication | 2021

HPC - Workshop

Experimentelle Analyse, Simulation und Regelung von Absorptionswärmepumpen/-kältemaschinen

Zlabinger S, Unterberger V, Gölles M, Wernhart M, Rieberer R, Poier H, Rohinger C, Kemmerzehl C, Halmdienst C. Experimentelle Analyse, Simulation und Regelung von Absorptionswärmepumpen/-kältemaschinen. Online-Workshop im Rahmen des FFG-Projekts HPC ("4. Ausschreibung Energieforschung 2017") am 09.04.2021.

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Durch die vermehrte Einbindung von Absorptionswärmepumpen und -kältemaschinen in bestehende und zukünftige Energiesysteme des Kälte- und Wärmesektors kann der Anteil erneuerbarer Energien deutlich gesteigert werden. Um dies erfolgreich umsetzen zu können, müssen die Betriebsstrategien und Regelungen dieser Systeme jedoch in der Lage sein, auch mit dynamischen und stark variierenden Betriebsbedingungen umgehen zu können. Dieser Herausforderung hat sich das von der FFG geförderte Projekt HPC – heat pumping system control gewidmet. Im Rahmen dieses Workshops sollen die Ergebnisse und deren Nutzen für die Praxis präsentiert und diskutiert werden.


Peer Reviewed Scientific Journals | 2021

Model-Based Estimation of the Flue Gas Mass Flow in Biomass Boilers.

Niederwieser H, Zemann C, Goelles M, Reichhartinger M. Model-Based Estimation of the Flue Gas Mass Flow in Biomass Boilers. IEEE Transactions on Control Systems Technology. 2021 Jul;19(4):1609 - 1622. https://doi.org/10.1109/TCST.2020.3016404

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Three estimators for the estimation of the flue gas mass flow in biomass boilers are presented and compared, namely a sliding-mode observer, a Kalman filter, and a so-called steady-state estimator. The flue gas mass flow is an important process variable in biomass boilers as it contains information about the supplied mass flows of air and decomposed fuel. It is also related to the generated heat flow. Furthermore, its knowledge may be exploited in model-based control strategies which allow one to keep pollutant emissions low, on the one hand, and to achieve high efficiency, on the other hand. However, due to fouling of the equipment over time, measurements and existing estimation methods are not suitable for long-term applications. The estimators proposed in this article are based on a dynamic model for gas tube heat exchangers. They are capable of handling the fouling of the heat exchanger and, additionally, they offer the possibility of monitoring the degree of fouling. By incorporating an additional differential pressure measurement and extending the aforementioned estimators, an improvement regarding the dynamic response and the estimation accuracy is achieved. The application of the estimators to real measurement data from both, a medium-scale and a small-scale biomass boiler, demonstrates their wide applicability.


Other Publications | 2021

Modelling and control of large-scale solar thermal systems

Unterberger V. Modelling and control of large-scale solar thermal systems. 2021. 212 p.

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Heat makes up the largest share of energy end-use, accounting for 50% of global final energy consumption in 2018 and contributing to about 40% of global carbon dioxide (CO2) emissions. Of the total heat produced, about 46% was consumed in buildings for space and water heating. Large-scale solar thermal systems provide a highly valuable possibility to increase the share of renewables in heating systems and to reduce carbon dioxide emissions. In this context, the worldwide number of large-scale solar heating systems has increased rapidly in the last couple of years, especially in China and European countries, e.g. in Denmark. This has led to the installation of about 400 large-scale solar thermal systems ( ≥ 350kWth, 500m²) by the end of 2019.
Unlike other heating systems, their main source of power (solar radiation) cannot be manipulated and is subject to changes on a seasonal as well as on a daily basis. That is why control systems play a very important role for the efficient operation of these systems. This thesis therefore focuses on the application of model-based control strategies, and the necessary preliminary work regarding modelling, in order to achieve an efficient control of large-scale solar thermal systems. Consequently, the thesis addresses three important aspects:
In the first main section, models of components of large-scale solar thermal systems are developed and validated. For the most important components (heat exchanger, solar collector and sensible heat storage), two models of different complexity, one simulation-oriented, one control-oriented, are developed. While the simulation-oriented models aim to model the physical behaviour very accurately in order to be used in simulation studies, control-oriented models aim to model the physical behaviour only as accurately as necessary in order to serve as a basis for model-based control strategies. All models are validated with measurement data from a typical solar system, and it is shown that they are sufficiently accurate for their intended purpose. The sum of the models provides a holistic view on all modelling aspects that have to be considered in large-scale solar thermal plants, and serves as a reasonable basis for model-based control strategies and accurate simulation studies of solar systems.
In the second main section, adaptive forecasting methods for the future solar heat production as well as the heat demand are developed and validated with measurement data and using real weather forecasts. These methods are important to most efficiently integrate and operate solar systems by better scheduling heat production, storage and distribution for the near future. In order to be used in real-world applications, the methods are developed with the goal to meet three important practical requirements: simple implementation, automatic adaption to seasonal changes, and wide applicability. The final long-term evaluation for half a year proves that the developed methods can forecast the solar heat production as well as the heat demand very accurately and outperform common forecasting methods, yielding results that are nearly twice as accurate.
In the third main section, model-based control strategies for the high-level as well as for the low-level control of solar thermal systems are developed and validated. For the high-level control an approach is presented which considers future information by using the developed forecasting methods. It achieves higher profits (plus 3 %) and leads to a more stable operation, compared to the existing commercial solution. For the low-level control, model-based control strategies based on the developed models for the heat generation and distribution are presented. The model-based control strategy for the heat generation considers the dynamic behaviour of the collector and especially considers the variable time-delay. This, compared to conventional control strategies, leads to a significantly better control performance in case of fluctuating solar radiation and changing inlet temperatures. The model-based control strategy for the heat distribution follows a modular approach which can be applied for several hydraulic settings, leading to an accurate and independent control of mass flow and temperature, and outperforms state-of-the-art control strategies. For both control levels, care was taken that the applied strategies can be used in real-world applications regarding their mathematical complexity and computational resources required.
In summary, this thesis presents a holistic approach regarding modelling (simulation-oriented models, control-oriented models and adaptive forecasting methods) and control aspects (high-level as well as low-level control) which can help to improve the efficiency of large-scale solar thermal plants on various levels, making them more competitive, and is furthermore essential for a successful integration of these plants in larger energy systems.


Other Presentations | 2021

Operation of Coupled Multi-Owner District Heating Networks via Distributed Optimization

Muschick D, Gölles M, Kaisermayer V, Horn M. Operation of Coupled Multi-Owner District Heating Networks via Distributed Optimization.17th International Symposium on District Heating and Cooling. Nottingham Trent University, Nottingham, United Kingdom. 7. Sep 2021. Oral Presentation. [online]

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The simultaneous operation of multiple connected heating networks can be handled by optimization techniques. However, a global optimum might not represent a good operating strategy if the networks belong to different owners and thus might habe competing interests. An approach from game theory then needs to be applied, which finds a generalized Nash equilibrium instead.


Peer Reviewed Scientific Journals | 2021

Operation of coupled multi-owner district heating networks via distributed optimization

Kaisermayer V, Muschick D, Horn M, Gölles M. Operation of coupled multi-owner district heating networks via distributed optimization. Energy Reports. 2021 Okt;7(Suppl. 4):273-281. https://doi.org/10.1016/j.egyr.2021.08.145

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The growth of district heating and cooling (DHC) networks introduces the possibility of connecting them with neighbouring networks. Coupling networks can save costs by reducing operating hours of peak load or backup boilers, or free up production capacity for network expansion. Optimization-based energy management systems (EMS) already provide operators of individual DHC networks with solutions to the unit commitment and economic dispatch problem. They are especially useful for complex networks with multiple producers and integrated renewable energy sources, where incorporating forecasts is important. Time-dependent constraints and network capacity limitations can easily be considered. For coupled networks, a centralized optimization would provide a minimum with respect to an objective function which can incorporate fuel costs, operational costs and costs for emissions. However, the individual coupled networks are generally owned by different organizations with competing objectives. The centralized solution might not be accepted, as each company aims to optimize its own objective. Additionally, all data has to be shared with a centralized EMS, and it represents a single point of failure. A decentralized EMS may therefore be a better choice in a multi-owner setting. In this article, a novel decentralized EMS is presented that can handle multi-owner structures with cooperative and non-cooperative coupling. Each local EMS solves its own optimization problem, and an iterative Jacobi-style algorithm ensures consensus among the networks. The distributed EMS is compared to a centralized EMS based on a representative real-world example consisting of three coupled district heating networks operated by two companies.


Other Presentations | 2021

Optimal operation of cross-ownership district heating and cooling networks

Muschick D, Kaisermayer V, Gölles M, Horn M.Optimal operation of cross-ownership district heating and cooling networks. 20th European Roundtable on Sustainable Consumption and Production. 9. Sep 2021. Graz. Oral Presentation.

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Technical Reports | 2021

Supervisory control of large-scale solar thermal systems

Task 55 Towards the Integration of Large SHC Systems into DHC Networks

Gölles M, Unterberger V, Kaisermayer V, Nigitz T, Muschick D. "Supervisory control of large-scale solar thermal systems". IEA SHC FACTSHEET 55.A-D4.1. Date of Publication: 28.01.2021. https://task55.iea-shc.org/fact-sheets

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Overview on different approaches for supervisory control strategies,deciding on operating modes and set points for the controls of the different plants and componentsintegrated in solar thermal systems.


Conference Papers | 2021

The robust exact differentiator toolbox revisited: Filtering and discretization features.

Andritsch B, Horn M, Koch S, Niederwieser H, Wetzlinger M, Reichhartinger M. The robust exact differentiator toolbox revisited: Filtering and discretization features. in 2021 IEEE International Conference on Mechatronics, ICM 2021. Institute of Electrical and Electronics Engineers. 2021. 9385675 https://doi.org/10.1109/ICM46511.2021.9385675

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An extended version of a Simulink ® -block providing on-line differentiation algorithms based on discretized sliding-mode concepts is presented. Based on user-specified settings it computes estimates of the time-derivatives of the input signal up to order ten. Different discrete-time estimation algorithms as well as optional filtering properties can be selected. The paper includes an overview of the implemented algorithms, a detailed explanation of the developed Simulink ® -block and two examples. The first example illustrates the application of the toolbox in a numerical simulation environment whereas the second one shows results obtained via an electrical laboratory setup.


Conference contributions | 2020

"Long-term verification of a new modular method for CO-lambda-optimisation"

Zemann C, Hammer F, Gölles M. Long-term verification of a new modular method for CO-lambda-optimisation. 6th Central European Biomass Conference CEBC 2020 (Oral Presentation). 2020.

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