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Dynamic modeling and investigation of residential fuel cell cogeneration systems

: Vetter, M.; Wittwer, C.

Fulltext urn:nbn:de:0011-n-345228 (383 KByte PDF)
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Created on: 9.7.2008

16. Internationales Kolloquium über Anwendungen der Informatik und der Mathematik in Architektur und Bauwesen 2003. CD-ROM : 10. - 12.06.2003 in Weimar
Weimar, 2003
10 pp.
Internationales Kolloquium über Anwendungen der Informatik und der Mathematik in Architektur und Bauwesen (IKM) <16, 2003, Weimar>
Conference Paper, Electronic Publication
Fraunhofer ISE ()

This paper describes the development of control strategies for residential fuel cell cogeneration plants, using the simulation environment ColSim [COLSIM-1]. The investigated facility is illustrated, including a fuel cell system fueled with natural gas and a stratified storage with an internal gas burner. The components of this facility are modeled in the simulation environment ColSim as so called "plug-flow-types" [COLSIM-02]. Demonstrative of this, the object of a polymer electrolyte fuel cell stack is described. The model of the entire system is shown with the used vector graphic tool [XFIG]. The dynamic behavior of the main components of the fuel cell cogeneration system, the fuel cell stack and the fuel processor, is shown and compared to measurement data. Two criteria are defined optimizing the running costs or the primary energy consumption. Based on these definitions control strategies are shown. The efficiencies of the system are taken into account in several operating points. In addition the user behavior (electric and thermal energy demands) is detected by the control algorithm. Measured data of a "low energy consumption house", monitored by the German utility EnBW [EnBW-1], are used. In these investigations the user of the facility is premised as the owner. Dynamic tariff structures for natural gas and electricity offer the possibility to influence the operational point of the fuel cell system by the energy supply company. The differences of the two presented control strategies are shown for a typical day in winter and in summer. Finally the simulation results for the time period of one year are illustrated with and without a solar thermal system, differing also in the chosen control strategy.