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Rossi, I., Zaccaria, V. & Traverso, A. (2018). Advanced Control for Clusters of SOFC/Gas Turbine Hybrid Systems. Journal of engineering for gas turbines and power, 140(5), Article ID 051703.
Open this publication in new window or tab >>Advanced Control for Clusters of SOFC/Gas Turbine Hybrid Systems
2018 (English)In: Journal of engineering for gas turbines and power, ISSN 0742-4795, E-ISSN 1528-8919, Vol. 140, no 5, article id 051703Article in journal (Refereed) Published
Abstract [en]

The use of model predictive control (MPC) in advanced power systems can be advantageous in controlling highly coupled variables and optimizing system operations. Solid oxide fuel cell/gas turbine (SOFC/GT) hybrids are an example where advanced control techniques can be effectively applied. For example, to manage load distribution among several identical generation units characterized by different temperature distributions due to different degradation paths of the fuel cell stacks. When implementing an MPC, a critical aspect is the trade-off between model accuracy and simplicity, the latter related to a fast computational time. In this work, a hybrid physical and numerical approach was used to reduce the number of states necessary to describe such complex target system. The reduced number of states in the model and the simple framework allow real-time performance and potential extension to a wide range of power plants for industrial application, at the expense of accuracy losses, discussed in the paper. 

Place, publisher, year, edition, pages
American Society of Mechanical Engineers (ASME), 2018
Keywords
Economic and social effects; Fuel cells; Hybrid systems; Industrial plants; Model predictive control; Predictive control systems; Turbines, Advanced control; Computational time; Generation units; Load distributions; Number of state; Numerical approaches; Real time performance; System operation, Solid oxide fuel cells (SOFC)
National Category
Energy Engineering
Identifiers
urn:nbn:se:mdh:diva-38576 (URN)10.1115/1.4038321 (DOI)000428871900012 ()2-s2.0-85040680634 (Scopus ID)
Available from: 2018-02-08 Created: 2018-02-08 Last updated: 2018-04-26Bibliographically approved
Zaccaria, V., Stenfelt, M., Aslanidou, I. & Kyprianidis, K. (2018). Fleet monitoring and diagnostics framework based on digital twin of aero-engines. In: Proceedings of the ASME Turbo Expo: . Paper presented at ASME Turbo Expo 2018: Turbomachinery Technical Conference and Exposition, GT 2018, 11 June 2018 through 15 June 2018. American Society of Mechanical Engineers (ASME), 6
Open this publication in new window or tab >>Fleet monitoring and diagnostics framework based on digital twin of aero-engines
2018 (English)In: Proceedings of the ASME Turbo Expo, American Society of Mechanical Engineers (ASME) , 2018, Vol. 6Conference paper, Published paper (Refereed)
Abstract [en]

Monitoring aircraft performance in a fleet is fundamental to ensure optimal operation and promptly detect anomalies that can increase fuel consumption or compromise flight safety. Accurate failure detection and life prediction methods also result in reduced maintenance costs. The major challenges in fleet monitoring are the great amount of collected data that need to be processed and the variability between engines of the fleet, which requires adaptive models. In this paper, a framework for monitoring, diagnostics, and health management of a fleet of aircrafts is proposed. The framework consists of a multi-level approach: starting from thresholds exceedance monitoring, problematic engines are isolated, on which a fault detection system is then applied. Different methods for fault isolation, identification, and quantification are presented and compared, and the related challenges and opportunities are discussed. This conceptual strategy is tested on fleet data generated through a performance model of a turbofan engine, considering engine-to-engine and flight-to-flight variations and uncertainties in sensor measurements. Limitations of physics-based methods and machine learning techniques are investigated and the needs for fleet diagnostics are highlighted. 

Place, publisher, year, edition, pages
American Society of Mechanical Engineers (ASME), 2018
Keywords
Aircraft engines, Engines, Fault detection, Learning systems, Turbofan engines, Turbomachinery, Uncertainty analysis, Aircraft performance, Fault detection systems, Life prediction methods, Machine learning techniques, Monitoring and diagnostics, Physics-based methods, Reduced maintenance costs, Sensor measurements, Fleet operations
National Category
Aerospace Engineering
Identifiers
urn:nbn:se:mdh:diva-41129 (URN)10.1115/GT2018-76414 (DOI)2-s2.0-85053863979 (Scopus ID)9780791851128 (ISBN)
Conference
ASME Turbo Expo 2018: Turbomachinery Technical Conference and Exposition, GT 2018, 11 June 2018 through 15 June 2018
Available from: 2018-10-08 Created: 2018-10-08 Last updated: 2018-10-08Bibliographically approved
Cuneo, A., Zaccaria, V., Tucker, D. & Sorce, A. (2018). Gas turbine size optimization in a hybrid system considering SOFC degradation. Applied Energy, 230, 855-864
Open this publication in new window or tab >>Gas turbine size optimization in a hybrid system considering SOFC degradation
2018 (English)In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 230, p. 855-864Article in journal (Refereed) Published
Abstract [en]

The coupling of a pressurized solid oxide fuel cell (SOFC) and a gas turbine has been proven to result in extremely high efficiency and reduced emissions. The presence of the gas turbine can improve system durability compared to a standalone SOFC, because the turbomachinery can supply additional power as the fuel cell degrades to meet the power request. Since performance degradation is an obstacles to SOFC systems commercialization, the optimization of the hybrid system to mitigate SOFC degradation effects is of great interest. In this work, an optimization approach was used to innovatively study the effect of gas turbine size on system durability for a 400 kW fuel cell stack. A larger turbine allowed a bigger reduction in SOFC power before replacing the stack, but increased the initial capital investment and decreased the initial turbine efficiency. Thus, the power ratio between SOFC and gas turbine significantly influenced system economic results.

Place, publisher, year, edition, pages
Elsevier Ltd, 2018
Keywords
Design optimization, Economic analysis, Hybrid systems, SOFC degradation
National Category
Energy Engineering
Identifiers
urn:nbn:se:mdh:diva-40967 (URN)10.1016/j.apenergy.2018.09.027 (DOI)000448226600064 ()2-s2.0-85053071574 (Scopus ID)
Available from: 2018-09-20 Created: 2018-09-20 Last updated: 2018-11-08Bibliographically approved
Aslanidou, I., Zaccaria, V., Pontika, E., Zimmerman, N., Kalfas, A. I. & Kyprianidis, K. (2018). Teaching gas turbine technology to undergraduate students in Sweden. In: Proceedings of the ASME Turbo Expo: . Paper presented at ASME Turbo Expo 2018: Turbomachinery Technical Conference and Exposition, GT 2018, 11 June 2018 through 15 June 2018; Code 138886. American Society of Mechanical Engineers (ASME), 6
Open this publication in new window or tab >>Teaching gas turbine technology to undergraduate students in Sweden
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2018 (English)In: Proceedings of the ASME Turbo Expo, American Society of Mechanical Engineers (ASME) , 2018, Vol. 6Conference paper, Published paper (Refereed)
Abstract [en]

This paper addresses the teaching of gas turbine technology in a third-year undergraduate course in Sweden and the challenges encountered. The improvements noted in the reaction of the students and the achievement of the learning outcomes is discussed. The course, aimed at students with a broad academic education on energy, is focused on gas turbines, covering topics from cycle studies and performance calculations to detailed design of turbomachinery components. It also includes economic aspects during the operation of heat and power generation systems and addresses combined cycles as well as hybrid energy systems with fuel cells. The course structure comprises lectures from academics and industrial experts, study visits, and a comprehensive assignment. With the inclusion of all of these aspects in the course, the students find it rewarding despite the significant challenges encountered. An important contribution to the education of the students is giving them the chance, stimulation, and support to complete an assignment on gas turbine design. Particular attention is given on striking a balance between helping them find the solution to the design problem and encouraging them to think on their own. Feedback received from the students highlighted some of the challenges and has given directions for improvements in the structure of the course, particularly with regards to the course assignment. This year, an application developed for a mobile phone in the Aristotle University of Thessaloniki for the calculation of engine performance will be introduced in the course. The app will have a supporting role during discussions and presentations in the classroom and help the students better understand gas turbine operation. This is also expected to reduce the workload of the students for the assignment and spike their interest.

Place, publisher, year, edition, pages
American Society of Mechanical Engineers (ASME), 2018
Keywords
Curricula, E-learning, Fuel cells, Gas turbines, Gases, Machine design, Structural design, Teaching, Engine performance, Gas turbine design, Gas Turbine Technologies, Hybrid energy system, Performance calculation, Turbomachinery components, Undergraduate Courses, Undergraduate students, Students
National Category
Energy Engineering
Identifiers
urn:nbn:se:mdh:diva-41126 (URN)10.1115/GT2018-77074 (DOI)2-s2.0-85053912750 (Scopus ID)9780791851128 (ISBN)
Conference
ASME Turbo Expo 2018: Turbomachinery Technical Conference and Exposition, GT 2018, 11 June 2018 through 15 June 2018; Code 138886
Available from: 2018-10-08 Created: 2018-10-08 Last updated: 2018-10-08Bibliographically approved
Zaccaria, V., Dik, A., Bitén, N., Aslanidou, I. & Kyprianidis, K. (2017). Conceptual Design of a 3-Shaft Turbofan Engine with Reduced Fuel Consumption for 2025. In: Elsevier (Ed.), Energy Procedia: . Paper presented at 9th International Conference on Applied Energy, ICAE2017, 21-24 August 2017, Cardiff, UK.
Open this publication in new window or tab >>Conceptual Design of a 3-Shaft Turbofan Engine with Reduced Fuel Consumption for 2025
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2017 (English)In: Energy Procedia / [ed] Elsevier, 2017Conference paper, Published paper (Refereed)
Abstract [en]

In the past decade, aircraft fuel burn has been continually decreased, mainly by improving thermal and propulsion efficiencies with consequent decrement in specific fuel consumption. In view of future emission specifications, the requirements for SFC in the forthcoming years are expected to become more stringent. In this paper, a preliminary design of a turbofan engine for entry in service in 2025 was performed. The design of a baseline 2010 EIS engine was improved according to 2025 specifications. A thermodynamic analysis was carried out to select optimal jet velocity ratio, pressure ratio, and temperatures with the goal of minimizing specific fuel consumption. A gas path layout was generated and an aerodynamic analysis was performed to optimize the engine stage by stage design. The optimization resulted in a 3-shaft turbofan jet engine with a 21% increase in fan diameter, a 2.2% increment in engine length, and a fuel burn improvement of 11% compared to the baseline engine, mainly due to an increment in propulsive efficiency. A sensitivity analysis was also conducted to highlight what the focus of technology development should be.

National Category
Energy Engineering
Identifiers
urn:nbn:se:mdh:diva-37465 (URN)
Conference
9th International Conference on Applied Energy, ICAE2017, 21-24 August 2017, Cardiff, UK
Available from: 2017-12-15 Created: 2017-12-15 Last updated: 2018-03-05Bibliographically approved
Zaccaria, V., Branum, Z. & Tucker, D. (2017). Fuel Cell Temperature Control with a Pre-Combustor in SOFC Gas Turbine Hybrids during Load Changes. Journal of electrochemical energy conversion and storage, 14, 031006-031014
Open this publication in new window or tab >>Fuel Cell Temperature Control with a Pre-Combustor in SOFC Gas Turbine Hybrids during Load Changes
2017 (English)In: Journal of electrochemical energy conversion and storage, ISSN 2381-6872, Vol. 14, p. 031006-031014Article in journal (Refereed) Published
Abstract [en]

The use of high temperature fuel cells, such as Solid Oxide Fuel Cells (SOFCs), for power generation is considered a very efficient and clean solution to conservation of energy resources. When the SOFC is coupled with a gas turbine, the global system efficiency can go beyond 70% on natural gas LHV. However, durability of the ceramic material and system operability can be significantly penalized by thermal stresses due to temperature fluctuations and non-even temperature distributions. Thermal management of the cell during load following is therefore essential.The purpose of this work was to develop and test a pre-combustor model for real-time applications in hardware-based simulations, and to implement a control strategy to keep constant cathode inlet temperature during different operative conditions. The real-time model of the pre-combustor was incorporated into the existing SOFC model and tested in a hybrid system facility, where a physical gas turbine and hardware components were coupled with a cyber-physical fuel cell for flexible, accurate, and cost-reduced simulations.The control of the fuel flow to the pre-combustor was proven to be effective in maintaining a constant cathode inlet temperature during a step change in fuel cell load. With a 20 A load variation, the maximum temperature deviation from the nominal value was below 0.3% (3K). Temperature gradients along the cell were maintained below 10 K/cm. An efficiency analysis was performed in order to evaluate the impact of the pre-combustor on the overall system efficiency.

Keywords
SOFC, hybrid system, control, dynamics
National Category
Energy Engineering
Research subject
Energy- and Environmental Engineering
Identifiers
urn:nbn:se:mdh:diva-37169 (URN)10.1115/1.4036809 (DOI)
Available from: 2017-11-01 Created: 2017-11-01 Last updated: 2018-01-26Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-6101-2863

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