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Peer Reviewed Scientific Journals | 2021

Advanced Optimal Planning for Microgrid Technologies including Hydrogen and Mobility at a real Microgrid Testbed

Mansoor M, Stadler M, Auer H, Zellinger M. Advanced Optimal Planning for Microgrid Technologies including Hydrogen and Mobility at a real Microgrid Testbed. International Journal of Hydrogen Energy.2021.

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This paper investigates the optimal planning of microgrids including the hydrogen energy system through mixed-integer linear programming model. A real case study is analyzed by extending the only microgrid lab facility in Austria. The case study considers the hydrogen production via electrolysis, seasonal storage and fueling station for meeting the hydrogen fuel demand of fuel cell vehicles, busses and trucks. The optimization is performed relative to two different reference cases which satisfy the mobility demand by diesel fuel and utility electricity based hydrogen fuel production respectively. The key results indicate that the low emission hydrogen mobility framework is achieved by high share of renewable energy sources and seasonal hydrogen storage in the microgrid. The investment optimization scenarios provide at least 66% and at most 99% carbon emission savings at increased costs of 30% and 100% respectively relative to the costs of the diesel reference case (current situation).


Peer Reviewed Scientific Journals | 2021

Dekarbonisierung in Salzburgs Skigebieten – Entwicklung von Optimierungsalgorithmen und Energiemanagementsystemen zur Steigerung der Energieeffizienz, Minimierung von Emissionen und Optimierung von Flexibilitäten [Decarbonization of the skiing areas in

Kritzer S, Passegger H, Ayoub T, Liedtke P, Zellinger M, Stadler M, Iglar B, Korner C, Aghaie H. Dekarbonisierung in Salzburgs Skigebieten – Entwicklung von Optimierungsalgorithmen und Energiemanagementsystemen zur Steigerung der Energieeffizienz, Minimierung von Emissionen und Optimierung von Flexibilitäten [Decarbonization of the skiing areas in Salzburg – development of optimization algorithms and energy management systems to increase energy efficiency, minimize emissions and optimize flexibility]. Elektrotechnik und Informationstechnik. 31 May 2021.

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Winter tourism is an energy-intensive branch of industry. The aim of the FFG funding project Clean Energy for Tourism is to support Salzburg’s skiing areas on the way to decarbonization by developing technologies and business models. In this article, the developed ICT infrastructure, the optimization algorithms and the business models are presented.


Peer Reviewed Scientific Journals | 2021

Mixed-integer linear programming based optimization strategies for renewable energy communities

Cosic A, Stadler M, Mansoor M, Zellinger M. Mixed-integer linear programming based optimization strategies for renewable energy communities. Energy. 237.2021

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Local and renewable energy communities show a high potential for the efficient use of distributed energy technologies at regional levels according to the Clean Energy Package of the European Union. However, until now there are only limited possibilities to bring such energy communities into reality because of several limitation factors. Challenges are already encountered during the planning phase since a large number of decision variables have to be considered depending on the number and type of community participants and distributed technologies. This paper overcomes these challenges by establishing a mixed-integer linear programming based optimal planning approach for renewable energy communities. A real case study is analyzed by creating an energy community testbed with a leading energy service provider in Austria. The case study considers nine energy community members of a municipality in Austria, distributed photovoltaic systems, energy storage systems, different electricity tariff scenarios and market signals including feed-in tariffs. The key results indicate that renewable energy communities can significantly reduce the total energy costs by 15% and total carbon dioxide emissions by 34% through an optimal selection and operation of the energy technologies. In all the optimization scenarios considered, each community participant can benefit both economically and ecologically.


Peer Reviewed Scientific Journals | 2021

Optimal planning of thermal energy systems in a microgrid with seasonal storage and piecewise affine cost functions

Mansoor M, Stadler M, Zellinger M, Lichtenegger K, Auer H, Cosic A. Optimal planning of thermal energy systems in a microgrid with seasonal storage and piecewise affine cost functions. Energy. 2021:215;119095.

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The optimal design of microgrids with thermal energy system requires optimization techniques that can provide investment and scheduling of the technology portfolio involved. In the modeling of such systems with seasonal storage capability, the two main challenges include the low temporal resolution of available data and the non-linear cost versus capacity relationship of solar thermal and heat storage technologies. This work overcomes these challenges by developing two different optimization models based on mixed-integer linear programming with objectives to minimize the total energy costs and carbon dioxide emissions. Piecewise affine functions are used to approximate the non-linear cost versus capacity behavior. The developed methods are applied to the optimal planning of a case study in Austria. The results of the models are compared based on the accuracy and real-time performance together with the impact of piecewise affine cost functions versus non-piecewise affine fixed cost functions. The results show that the investment decisions of both models are in good agreement with each other while the computational time for the 8760-h based model is significantly greater than the model having three representative periods. The models with piecewise affine cost functions show larger capacities of technologies than non-piecewise affine fixed cost function based models.


Peer Reviewed Scientific Journals | 2020

Decentralized heating grid operation: A comparison of centralized and agent-based optimization

Lichtenegger K, Leitner A, Märzinger T, Mair C, Moser A, Wöss D, Schmidl C, Pröll T. Decentralized heating grid operation: A comparison of centralized and agent-based optimization. Sustainable Energy, Grids and Networks. 2020;2020(21).

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Moving towards a sustainable heat supply calls for decentralized and smart heating grid solutions. One promising concept is the decentralized feed-in by consumers equipped with their own small production units (prosumers). Prosumers can provide an added value regarding security of supply, emission reduction and economic welfare, but in order to achieve this, in addition to advanced hydraulic control strategies also superordinate control strategies and appropriate market models become crucial.

In this article we study methods to find a global optimum for the local energy community or at least an acceptable approximation to it. In contrast to standard centralized control approaches, based either on expert rules or mixed integer linear optimization, we adopt an agent-based, decentralized approach that allows for incorporation of nonlinear phenomena. While studied here in small-scale systems, this approach is particularly attractive for larger systems, since with an increasing number of interacting units, the optimization problem becomes more complex and the computational effort for centralized approaches increases dramatically.

The agent-based optimization approach is compared to centralized optimization of the same prosumer-based setting as well as to a purely central setup. The comparison is based on the quality of the optimization solution, the computational effort and the scalability. For the comparison of these three approaches, three different scenarios have been set up and analysed for four seasons. In this analysis, no approach has emerged as clearly superior to the others; thus each of them is justified in certain situations.


Conference contributions | 2020

Microgrid Lab 100 % - R&D project for decentralized energy supply with biomass and other Distributed energy Resources

Aigenbauer S. Microgrid Lab 100 % - R&D project for decentralized energy supply with biomass and other Distributed energy Resources. 6th Central European Biomass Conference, 22-24 January 2020, Graz.

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Conference contributions | 2020

Microgrid Lab 100% Testbed for the development of control algorithms for microgrids

Aigenbauer S, Microgrid Lab 100% Testbed for the development of control algorithms for microgrids. 6th Central European Biomass Conference, 22-24 January 2020, Graz.

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Microgrids are local energy grids that (partly) cover their own energy demand. Decentralized renewable energy sources reduce energy costs and CO2 emissions in a microgrid. Various storage systems and strategies like load shift are employed to balance the volatile energy flows. Intelligent controllers improve the energy management of the micro and smart grids. BEST GmbH is the industry leader when it comes to biomass control systems in Austria. Thus, BEST GmbH is already combining this knowledge within the “OptEnGrid” (FFG 858815) and “Grundlagenforschung Smart- und Microgrid“ (K3-F-755/001-2017) research projects, which are based on the leading microgrid optimization tool DER-CAM from Lawrence Berkeley National Laboratory at the University of California. These two BEST GmbH basic research projects form the basis for new innovative microgrid controller concepts which will be implemented and tested in the presented Microgrid Research Lab in Wieselburg (project Microgrid Lab 100%). The Microgrid Research Lab will include the Technology- und Reseach Centre (tfz) Wieselburg-Land and the new firefighting department next to the tfz.


Conference contributions | 2020

Microgrid Lab – R&D project for 100% decentralized energy supply with biomass and other Distributed Energy Resources (DER)

Aigenbauer S, Zellinger M, Stadler M. Microgrid Lab – R&D project for 100% decentralized energy supply with biomass and other Distributed Energy Resources (DER). 6th Central European Biomass Conference (poster). 2020.

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Microgrids, a research topic within the smart grids area, build on close relationships between demand and supply and will create a 170 Mrd. € market potential in 2020[1]. These individual markets are characterized by different technologies in use. For example, biogas will play a key role in microgrids in Asia compared to Photovoltaics, Combined heat and Power (CHP), as well as storage technologies in North America. All these different technologies need to be coordinated and controlled. BIOENERGY2020+ GmbH is the industry leader when it comes to biomass control systems in Austria. Thus, BIOENERGY2020+ GmbH is already combining this knowledge within the OptEnGrid and “Grundlagenforschung Smart- und Microgrid“ (K3-F-755/001-2017) research projects, which are based on the leading microgrid optimization tool DER-CAM from Lawrence Berkeley National Laboratory at the University of California in Berkeley. These two BIOENERGY2020+ GmbH basic research projects constitute the basis for new innovative microgrid controller concepts and these new microgrid controller will be implemented and tested in the suggested Microgrid Research Lab in Wieselburg. The Microgrid Research Lab will include the Technology- und Reseach Centre (tfz) Wieselburg-Land and the new firefighting department next to the tfz.

 

 


Conference contributions | 2020

Optimization based planning of energy systems

Zellinger M, Optimization based planning of energy systems. 6th Central European Biomass Conference, 22-24 January 2020, Graz.

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Peer Reviewed Scientific Journals | 2020

Performance Comparison between Two Established Microgrid Planning MILP Methodologies Tested On 13 Microgrid Projects

Stadler M, Pecenak Z, Mathiesen P, Fahy K, Kleissl J. Performance Comparison between Two Established Microgrid Planning MILP Methodologies Tested On 13 Microgrid Projects. Energies.2020;13:446

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Mixed Integer Linear Programming (MILP) optimization algorithms provide accurate and clear solutions for Microgrid and Distributed Energy Resources projects. Full-scale optimization approaches optimize all time-steps of data sets (e.g., 8760 time-step and higher resolutions), incurring extreme and unpredictable run-times, often prohibiting such approaches for effective Microgrid designs. To reduce run-times down-sampling approaches exist. Given that the literature evaluates the full-scale and down-sampling approaches only for limited numbers of case studies, there is a lack of a more comprehensive study involving multiple Microgrids. This paper closes this gap by comparing results and run-times of a full-scale 8760 h time-series MILP to a peak preserving day-type MILP for 13 real Microgrid projects. The day-type approach reduces the computational time between 85% and almost 100% (from 2 h computational time to less than 1 min). At the same time the day-type approach keeps the objective function (OF) differences below 1.5% for 77% of the Microgrids. The other cases show OF differences between 6% and 13%, which can be reduced to 1.5% or less by applying a two-stage hybrid approach that designs the Microgrid based on down-sampled data and then performs a full-scale dispatch algorithm. This two stage approach results in 20–99% run-time savings.


Peer Reviewed Scientific Journals | 2020

Robust design of microgrids using a hybrid minimum investment optimization

Pecenak ZK, Stadler M, Mathiesen P, Fahy K, Kleissl J. Robust design of microgrids using a hybrid minimum investment optimization. Applied Energy. 2020;276:115400.

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Recently, researchers have begun to study hybrid approaches to Microgrid techno-economic planning, where a reduced model optimizes the DER selection and sizing is combined with a full model that optimizes operation and dispatch. Though providing significant computation time savings, these hybrid models are susceptible to infeasibilities, when the size of the DER is insufficient to meet the energy balance in the full model during macrogrid outages. In this work, a novel hybrid optimization framework is introduced, specifically designed for resilience to macrogrid outages. The framework solves the same optimization problem twice, where the second solution using full data is informed by the first solution using representative data to size and select DER. This framework includes a novel constraint on the state of charge for storage devices, which allows the representation of multiple repeated days of grid outage, despite a single 24-h profile being optimized in the representative model. Multiple approaches to the hybrid optimization are compared in terms of their computation time, optimality, and robustness against infeasibilities. Through a case study on three real Microgrid designs, we show that allowing optimizing the DER sizing in both stages of the hybrid design, dubbed minimum investment optimization (MIO), provides the greatest degree of optimality, guarantees robustness, and provides significant time savings over the benchmark optimization.


Scientific Journals | 2019

Efficient Multi-Year Economic Energy Planning in Microgrids

Pecenak Z, Stadler M, Fahy K, Efficient Multi-Year Economic Energy Planning in Microgrids. Applied Energy 2019;225.

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With energy systems, the problem of economic planning is decisive in the design of a low carbon and resilient future grid. Although several tools to solve the problem already exist in literature and industry, most tools only consider a single “typical year” while providing investment decisions that last around a quarter of a century. In this paper, we introduce why such an approach is limited and derive two approaches to correct this. The first approach, the Forward-Looking model, assumes perfect knowledge and makes investment decisions based on the full planning horizon. The second novel approach, the Adaptive method, solves the optimization problem in single year iterations, making incremental investment decisions that are dependant on previous years, with only knowledge of the current year. Comparing the two approaches on a realistic microgrid, we find little difference in investment decisions (maximum 21% difference in total cost over 20 years), but large differences in optimization time (up to 12000% time difference). We close the paper by discussing implications of forecasting errors on the microgrid planning process, concluding that the Adaptive approach is a suitable choice.


Conference Papers | 2019

Ganzheitliche Planung dezentraler Energiekonzepte durch mathematische Optimierung

Liedtke P, Stadler M, Zellinger M, Hengl F. Ganzheitliche Planung dezentraler Energiekonzepte durch mathematische Optimierung. e-nova Konferenz 2019.

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Kernthema dieses Beitrags ist die ganzheitliche Konzeption von Mikronetze, die sich auf die Reduzierung von Kosten und CO2-Emissionen konzentriert. Mikronetze, oder auch Microgrids, ermöglichen die koordinierte Energieerzeugung von dezentralen Energieressourcen, die Speicherungen der produzierten Energie und ein Lastmanagement zum Ausgleich von Wärme-, Kälte- und Elektrizitätsdienstleistungen. Mikronetze können vom breiteren Versorgungsnetz getrennt werden, können diverse Dienstleistungen erbringen und/oder selbst Energie erzeugen sowie in Überschusszeiten speichern und bei Bedarf wieder Kosten- oder Stabilitäts-orientiert freigeben.
Die mathematische Optimierung dient als unvoreingenommene Alternative für eine gesamtheitliche Planung von dezentralen Energietechnologien. Dieses Kriterium wird bei einer Kosten- oder CO2-Reduktion vor allem dann essentiell, wenn vielfältigen Kombinationen von Technologien und Kapazitäten möglich sind. Modernste Ansätze betrachten jedoch einen quasistatischen Aufbau unter Verwendung linearisierte Modelle und Mixed Integer Linear Optimization (MILP), wobei dynamische Effekte vernachlässigt werden. Unter Berücksichtigung von Lasten, geografischen, ökonomisch-ökologischen und tariflichen Daten sind mathematische Optimierungsalgorithmen in der Lage, verschiedene Anwendungsfälle zu beurteilen, wobei Effekte wie Vorwärmung, Sollwertänderungen oder kurzfristige Sonnenschwankungen unberücksichtigt bleiben. Dies bedeutet, dass die in quasistatischen Ansätzen verwendete Wärme- und Strombilanzen ungenau sein können (eventuell können physikalische Randbedingungen sogar verletzt werden, was zu suboptimalen Ergebnissen bei der Planung führen würde).
Die Notwendigkeit besteht quasistatische Optimierung mit einer weiteren Modellierungsart zu vergleichen und die Auswirkungen auf traditionelle quasistatische Ansätze, wie sie in DER-CAM oder ReOpt eingesetzt werden, aufzudecken. Um Abweichungen - bestehend aus dynamischen oder sogar Rebound Effekten - zu erkennen, werden mit TRNSYS Gebäude- und Anlagensimulationen für eine geplante Siedlungsanlage erstellt und ein Energiekonzept mit dem mathematischen Optimierungsprogramm OptEnGrid berechnet. Der Ansatz wird für vier Doppelhäuser und ein Mehrfamilienhaus getestet. Die Gebäude werden in TRNSYS simuliert und bieten thermische Lastdaten für den Referenzfall. Auch die Stromerzeugung mit PV-Modellen und der elektrische Verbrauch mit synthetischen Lastprofilen sind sowohl in der Optimierung als auch in der Simulation beteiligt. In der elektrischen Stromerzeugung zeigt die mathematische Optimierung bereits eine Abweichung von mehr als 5% auf Jahresbasis zur TRNSYS-Simulation. Ergebnisse im thermischen Energiebereich folgen nach weiterer Auswertung.


Peer Reviewed Scientific Journals | 2019

Input data reduction for microgrid sizing and energy cost modeling: Representative days and demand charges

Fahy K, Stadler M, Pecenak ZK, Kleissl J. Input data reduction for microgrid sizing and energy cost modeling: Representative days and demand charges. Journal of Renewable and Sustainable Energy. 2019.11:065301

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Computational time in optimization models scales with the number of time steps. To save time, solver time resolution can be reduced and input data can be down-sampled into representative periods such as one or a few representative days per month. However, such data reduction can come at the expense of solution accuracy. In this work, the impact of reduction of input data is systematically isolated considering an optimization which solves an energy system using representative days. A new data reduction method aggregates annual hourly demand data into representative days which preserve demand peaks in the original profiles. The proposed data reduction approach is tested on a real energy system and real annual hourly demand data where the system is optimized to minimize total annual costs. Compared to the full-resolution optimization of the energy system, the total annual energy cost error is found to be equal or less than 0.22% when peaks in customer demand are preserved. Errors are significantly larger for reduction methods that do not preserve peak demand. Solar photovoltaic data reduction effects are also analyzed. This paper demonstrates a need for data reduction methods which consider demand peaks explicitly.

 


Other Presentations | 2019

Optimization Based Design and Control of Distributed Energy Resources and Microgrids

Stalder M, Optimization Based Design and Control of Distributed Energy Resources and Microgrids. LetsCluster, Lighthouse Summit in the heart of Europe: Smart Energy Generation - Management - Optimization, Smart Home / Building, Interface to the Smart Grid, Microgrids, Electric Grid of the Future, Sector Linking, Graz, Österreich, 25 - 27 März 2019

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Peer Reviewed Scientific Journals | 2019

Planning and implementation of bankable microgrids

Stadler M, Nasle A. Planning and implementation of bankable microgrids. The Electricity Journal 2019. 32:24-29.

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Currently, many Microgrid projects remain financially uncertain and not bankable for institutional investors due to major challenges in existing planning and design methods that require multiple, complex steps and software tools.

Existing techniques treat every Microgrid project as a unique system, resulting in expensive, non-standardized approaches and implementations which cannot be compared. That is, it is not possible to correlate the results from different planning methods performed by different project developers and/or engineering companies.

This very expensive individual process cannot guarantee financial revenue streams, cannot be reliably audited, impedes pooling of multiple Microgrid projects into a financial asset class, nor does it allow for wide-spread and attractive Microgrid and Distributed Energy Resource projects deployment.

Thus, a reliable, integrated, and streamlined process is needed that guides the Microgrid developer and engineer through conceptual design, engineering, detailed electrical design, implementation, and operation in a standardized and data driven approach, creating reliable results and financial indicators that can be audited and repeated by investors and financers.

This article describes the steps and methods involved in creating bankable Microgrids by relying on an integrated Microgrid planning software approach that unifies proven technologies and tested planning methods, researched and developed by the United States National Laboratory System as well as the US Department of Energy, to reduce design times.


Conference contributions | 2019

Thermal Trouble: Challenges in Optimization and Evaluation of Thermal Energy Systems

Lichtenegger K, Unterberger V, Stadler M, Zellinger M, Carreras F, Moser A. Thermal Trouble: Challenges in Optimization and Evaluation of Thermal Energy Systems. IAPE 2019 : International Conference on Innovative Applied Energy (oral presentation). March 2019.

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Other Publications | 2018

A flexible low cost PV/EV microgrid controller concept based on a Raspberry Pi

Stadler M. A flexible low cost PV/EV microgrid controller concept based on a Raspberry Pi. Working Paper, Center for Energy and innovative Technologies (CET) and Bioenergy 2020+ GmbH, June 2018.

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Technical Reports | 2018

The Green P - Nutzung von städtischen Verkehrsflächen für die Produktion von Biomasse

Lichtenegger K, Meixner K, Riepl R, Schipfer F, Zellinger M. The Green P - Nutzung von städtischen Verkehrsflächen für die Produktion von Biomasse. BMVIT, Schriftenreihe 25/2018.

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Conference contributions | 2018

The Green Parking Area – Utilization of urban parking areas for cultivation of algae

Zellinger M, Riepl R, Lichtenegger K, Meixner K, Drosg B, Enigl M, Theuretzbacher F, Schipfer F. The Green Parking Area – Utilization of urban parking areas for cultivation of algae. presentation at the WSED, Wels, Austria, 01. March 2018.

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The present study examines the possible use of urban and rural traffic areas for producing biomass. Many of those areas (for example, parking lots at cinemas and shopping centers) are only intensively used during certain times. Most of the time those areas remain empty.
At the same time a major problem for large-scale implementation of renewable energy is the massive land use resulting from limited energy density of solar radiation and, in case of biomass production, low efficiency for utilization of solar radiation by plants. Additionally, renewable energies are often criticized for the fact that they require areas, which could also be used for food and feed production.
Therefore, it is an attractive idea to use some of the traffic areas that are lost for the ecosystem anyway for biomass production. This approach is novel that no data have been available yet. The aim of this work was therefore to develop technical solutions, to quantify the technical potential for this type of biomass production and, subsequently, for energy supply, based on data on the area utilization, climatic data and known properties of microalgae.
The work deals with the question of the technical potential for this approach in Austria. This question is
answered by a survey of the area data in Austria, the elaboration of technical systems for a possible implementation, as well as by calculating the biomass potential, based on simulation results. The data have been collected, analyzed and evaluated in a comprehensive literature search. The potential analysis provides an overview of the distribution of traffic areas in Austria and the resulting biomass potential. Thus, a list of possible areas including biomass and energy quantities is available.


Conference contributions | 2018

The Green Parking Area – Utilization of urban parking areas for cultivation of algae

Zellinger M, Riepl R, Lichtenegger K, Meixner K, Drosg B, Enigl M, Theuretzbacher F, Schipfer F. The Green Parking Area – Utilization of urban parking areas for cultivation of algae. presentation at the WSED, Wels, Austria, 01. March 2018.

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The present study examines the possible use of urban and rural traffic areas for producing biomass. Many of those areas (for example, parking lots at cinemas and shopping centers) are only intensively used during certain times. Most of the time those areas remain empty.
At the same time a major problem for large-scale implementation of renewable energy is the massive land use resulting from limited energy density of solar radiation and, in case of biomass production, low efficiency for utilization of solar radiation by plants. Additionally, renewable energies are often criticized for the fact that they require areas, which could also be used for food and feed production.
Therefore, it is an attractive idea to use some of the traffic areas that are lost for the ecosystem anyway for biomass production. This approach is novel that no data have been available yet. The aim of this work was therefore to develop technical solutions, to quantify the technical potential for this type of biomass production and, subsequently, for energy supply, based on data on the area utilization, climatic data and known properties of microalgae.
The work deals with the question of the technical potential for this approach in Austria. This question is
answered by a survey of the area data in Austria, the elaboration of technical systems for a possible implementation, as well as by calculating the biomass potential, based on simulation results. The data have been collected, analyzed and evaluated in a comprehensive literature search. The potential analysis provides an overview of the distribution of traffic areas in Austria and the resulting biomass potential. Thus, a list of possible areas including biomass and energy quantities is available.


Conference contributions | 2017

Microgrids and the Regional Balance of Supply and Demand in the Electricity and Heating Sector

Stadler M, Mair C, Zellinger M, Lichtenegger K, Haslinger W, Temper M, Moser A, Carlon E, Muschick D, Gölles M. Microgrids and the Regional Balance of Supply and Demand in the Electricity and Heating Sector. 20. Österreichischer Biomassetag, Windischgarsten, 14. - 15. November 2017.

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Other publication | 2017

Microgrids und dezentrale Energieerzeugung

Stadler M.,Carlon E., Gölles M., Haslinger W., Lichtenegger K., Mair C., Moser A., Muschick D., Zellinger M. Microgrids und dezentrale Energieerzeugung. Wasser Cluster Lunz/See Österreich, 21. September 2017.

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Other publication | 2017

Mikro-Netze und die regionale Balance von Erzeugung und Verbrauch im Strom- und Wärmebereich

Stadler M, Mair C, Zellinger M, Lichtenegger K, Haslinger W, Temper M, Moser A, Carlon E, Muschick D, Gölles M. Mikro-Netze und die regionale Balance von Erzeugung und Verbrauch im Strom- und Wärmebereich. Impulsreferat 20. Österreichischer Biomassetag. Sektorkopplung & Flexibilisierung. Windischgarsten, Österreich. 14. November 2017.

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Contributions to trade journals | 2017

Startups in Kalifornien – Kollaborationsmodell im Energiebereich

Stadler M., Temper M., Haslinger W. Startups in Kalifornien – Kollaborationsmodell im Energiebereich. Impulsreferat Energy.Inc.Ubator, Start-ups als Katalysator in F&E für marktfähige Energiesystemlösungen. Co-Creation-Workshop. Bundesministerium für Verkehr, Innovation und Technologie. Österreich, 22. September 2017.

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