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Zimmerman, N., Kyprianidis, K. & Lindberg, C.-F. (2019). Achieving lower district heating network temperatures using feed-forward MPC. Materials, 12(15), Article ID 2465.
Open this publication in new window or tab >>Achieving lower district heating network temperatures using feed-forward MPC
2019 (English)In: Materials, ISSN 1996-1944, E-ISSN 1996-1944, Vol. 12, no 15, article id 2465Article in journal (Refereed) Published
Abstract [en]

The focus of this work is to present the feasibility of lowering the supply and return temperatures of district heating networks in order to achieve energy savings through the implementation of feed-forward model predictive control. The current level of district heating technology dictates a need for higher supply temperatures, which is not the case when considering the future outlook. In part, this can be attributed to the fact that current networks are being controlled by operator experience and outdoor temperatures. The prospects of reducing network temperatures can be evaluated by developing a dynamic model of the process which can then be used for control purposes. Two scenarios are presented in this work, to not only evaluate a controller's performance in supplying lower network temperatures, but to also assess the boundaries of the return temperature. In Scenario 1, the historical load is used as a feed-forward signal to the controller, and in Scenario 2, a load prediction model is used as the feed-forward signal. The findings for both scenarios suggest that the new control approach can lead to a load reduction of 12.5% and 13.7% respectively for the heat being supplied to the network. With the inclusion of predictions with increased accuracy on end-user demand and feed-back, the return temperature values can be better sustained, and can lead to a decrease in supply temperatures and an increase in energy savings on the production side.

Place, publisher, year, edition, pages
MDPI AG, 2019
National Category
Energy Engineering
Identifiers
urn:nbn:se:mdh:diva-45030 (URN)10.3390/ma12152465 (DOI)000482576900126 ()31382435 (PubMedID)2-s2.0-85070601468 (Scopus ID)
Available from: 2019-08-22 Created: 2019-08-22 Last updated: 2019-10-14Bibliographically approved
Hermansson, K., Kos, C., Starfelt, F., Kyprianidis, K., Lindberg, C.-F. & Zimmerman, N. (2018). An Automated Approach to Building and Simulating Dynamic District Heating Networks. IFAC-PapersOnLine, 51(2), 855-860
Open this publication in new window or tab >>An Automated Approach to Building and Simulating Dynamic District Heating Networks
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2018 (English)In: IFAC-PapersOnLine, ISSN 2405-8963, Vol. 51, no 2, p. 855-860Article in journal (Refereed) Published
Abstract [en]

In Nordic countries, district heating accounts for a large share of the consumers’  heat demand. In Sweden, roughly 50% of the total heat demand is attributed to district heating. Which, over the past few years, is equivalent to around 50 TWh, and imposes a difficult balance between supply and demand for the suppliers of district heating. For large networks the propagation of heat from supplier to end-user can vary several hours. Further complexities of large networks, which can consist of multiple overlapping rings, is that during transient conditions the flow can actually change direction. A dynamic modeling library has been developed in Modelica using OpenModelica for district heating networks. Methods for modeling, handling data, simulating and the visualization of results has been developed using Matlab. The model has been validated using data from Mälarenergi  AB, a local provider of district heating in Västerås, Sweden. The model provides to an acceptable degree in predicting the heat propagation and temperature distribution in a localized case study. Adding a higher level of robustness, the model has the capacity to handle bi-directional and reversing flows in complex ring structures. Through this work, the combination of OpenModelica and Matlab, a framework for automating the building and simulation of district heating networks is obtainable. The implications of automating network modeling from computer-aided design drawings allows for a quick robust overview of how the network is working and how prospective additions to the network could impact the end-users. Furthermore, incorporating visual aspects for heat propagation in a network contributes to a higher understanding of complex network structures. 

Place, publisher, year, edition, pages
Elsevier B.V., 2018
National Category
Energy Engineering
Identifiers
urn:nbn:se:mdh:diva-39303 (URN)10.1016/j.ifacol.2018.04.021 (DOI)000435693000146 ()2-s2.0-85046689930 (Scopus ID)
Available from: 2018-05-24 Created: 2018-05-24 Last updated: 2018-07-12Bibliographically 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)000456908700049 ()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: 2019-02-14Bibliographically approved
Zimmerman, N., Kyprianidis, K. & Lindberg, C.-F. (2018). Waste fuel combustion: Dynamic modeling and control. Processes, 6(11), Article ID 222.
Open this publication in new window or tab >>Waste fuel combustion: Dynamic modeling and control
2018 (English)In: Processes, ISSN 2227-9717, Vol. 6, no 11, article id 222Article in journal (Refereed) Published
Abstract [en]

The focus of this study is to present the adherent transients that accompany the combustion of waste derived fuels. This is accomplished, in large, by developing a dynamic model of the process, which can then be used for control purposes. Traditional control measures typically applied in the heat and power industry, i.e., PI (proportional-integral) controllers, might not be robust enough to handle the the accompanied transients associated with new fuels. Therefore, model predictive control is introduced as a means to achieve better combustion stability under transient conditions. The transient behavior of refuse derived fuel is addressed by developing a dynamic modeling library. Within the library, there are two models. The first is for assessing the performance of the heat exchangers to provide operational assistance for maintenance scheduling. The second model is of a circulating fluidized bed block, which includes combustion and steam (thermal) networks. The library has been validated using data from a 160 MW industrial installation located in Västerås, Sweden. The model can predict, with satisfactory accuracy, the boiler bed and riser temperatures, live steam temperature, and boiler load. This has been achieved by using process sensors for the feed-in streams. Based on this model three different control schemes are presented: a PI control scheme, model predictive control with feedforward, and model predictive control without feedforward. The model predictive control with feedforward has proven to give the best performance as it can maintain stable temperature profiles throughout the process when a measured disturbance is initiated. Furthermore, the implemented control incorporates the introduction of a soft-sensor for measuring the minimum fluidization velocity to maintain a consistent level of fluidization in the boiler for deterring bed material agglomeration.

Place, publisher, year, edition, pages
MDPI AG, 2018
Keywords
Circulating fluidized bed boiler, Dynamic modeling, Process control, Refuse derived fuel, Waste to energy
National Category
Energy Engineering
Identifiers
urn:nbn:se:mdh:diva-41774 (URN)10.3390/pr6110222 (DOI)000451530400018 ()2-s2.0-85057842748 (Scopus ID)
Available from: 2018-12-20 Created: 2018-12-20 Last updated: 2019-10-14Bibliographically approved
Zimmerman, N., Dahlquist, E. & Kyprianidis, K. (2017). Towards On-line Fault Detection and Diagnostics in District Heating Systems. Paper presented at The 8th International Conference on Applied Energy 2016,October 8-11, Beijing, China.. Energy Procedia, 105, 1960-1966
Open this publication in new window or tab >>Towards On-line Fault Detection and Diagnostics in District Heating Systems
2017 (English)In: Energy Procedia, ISSN 1876-6102, E-ISSN 1876-6102, Vol. 105, p. 1960-1966Article in journal (Refereed) Published
Abstract [en]

This paper gives a brief introduction for detecting faults in pressure sensors and diagnostics in a district heating network.  Proper pressure throughout the network is essential in maintaining the requirements for the end-user.  A district heating network library has been constructed in OpenModelica for the purpose of developing a district heating network representation of Skultuna, Sweden.  The use of object-oriented program will give the ease of expanding the network to encompass the entire network distribution from Mälarenergi AB, Västerås, Sweden. The physical model can then be used in conjunction with sensor data to calculate residual values.  These residuals are then used as input into a Bayesian Network to determine the possibility of three different operating outcomes. This approach will allow for operators to evaluate a systems performance, help in decision support mechanisms, and can provide assistance in scheduling maintenance.  

Keywords
District heating, dynamic modeling, object-oriented programming, fault detection, decision support
National Category
Energy Systems
Research subject
Energy- and Environmental Engineering
Identifiers
urn:nbn:se:mdh:diva-33993 (URN)10.1016/j.egypro.2017.03.567 (DOI)000404967902010 ()2-s2.0-85020729621 (Scopus ID)
Conference
The 8th International Conference on Applied Energy 2016,October 8-11, Beijing, China.
Available from: 2016-11-28 Created: 2016-11-28 Last updated: 2018-07-25Bibliographically approved
Campillo, J., Dahlquist, E., Danilov, D. L., Ghaviha, N., Notten, P. H. & Zimmerman, N. (2016). Battery technologies for transportation applications. In: Technologies and Applications for Smart Charging of Electric and Plug-in Hybrid Vehicles: (pp. 151-206). Springer International Publishing
Open this publication in new window or tab >>Battery technologies for transportation applications
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2016 (English)In: Technologies and Applications for Smart Charging of Electric and Plug-in Hybrid Vehicles, Springer International Publishing , 2016, p. 151-206Chapter in book (Other academic)
Abstract [en]

More than a fifth of the greenhouse emissions produced worldwide come from the transport sector. Several initiatives have been developed over the last few decades, aiming at improving vehicles’ energy conversion efficiency and improve mileage per liter of fuel. Most recently, electric vehicles have been brought back into the market as real competitors of conventional vehicles. Electric vehicle technology offers higher conversion efficiencies, reduced greenhouse emissions, low noise, etc. There are, however, several challenges to overcome, for instance: improving batteries’ energy density to increase the driving range, fast recharging, and initial cost. These issues are addressed on this chapter by looking in depth into both conventional and non-conventional storage technologies in different transportation applications. 

Place, publisher, year, edition, pages
Springer International Publishing, 2016
National Category
Energy Engineering
Identifiers
urn:nbn:se:mdh:diva-36207 (URN)10.1007/978-3-319-43651-7_5 (DOI)2-s2.0-85026527662 (Scopus ID)9783319436517 (ISBN)9783319436494 (ISBN)
Available from: 2017-08-10 Created: 2017-08-10 Last updated: 2017-08-10Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-5520-739X

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