Abstract
Micro-combined heat and power systems ( $\mu $ -CHP) based on proton exchange membrane fuel cell stacks (PEMFC) are capable of supplying electricity and heat for the residential housing sector with a high energy efficiency and a low level of $CO_ {2}$ emissions. For this reason, they are regarded as a promising technology for coping with the current environmental challenges. In these systems, the temperature control of the stack is crucial, since it has a direct impact on its durability and electrical efficiency. In order to design a good temperature control, however, a dynamic model of the $\mu $ -CHP cooling system is required. In this paper, we present a model of the cooling system of a PEMFC-based $\mu $ -CHP system, which is oriented to the design of the temperature control of the stack. The model has been developed from a $\mu $ -CHP system located in the laboratory of our research team, the predictive control and heuristic optimization group (CPOH). It is based on first principles, dynamic, non-linear, and has been validated against the experimental data. The model is implemented in Matlab/Simulink and the adjustment of its parameters was carried out using evolutionary optimization techniques. The methodology followed to obtain it is also described in detail. Both the model and the test data used for its adjustment and validation are accessible to anyone who wants to consult them. The results show that the model is able to faithfully represent the dynamics of the $\mu $ -CHP cooling system, so it is appropriate for the design of the stack temperature control.
Highlights
There are serious environmental problems: global warming, air pollution and depletion of fossil fuel reserves
RESULTS we present, first, the results of the final fine adjustment of the complete model with the data set from the modeling test and, the results of the validation of the model, that is, the testing of the model against the data set from the validation test
OF THE MODEL ADJUSTMENT Fig. 12 shows the results of the adjustment of the complete model with the data set from the modeling test
Summary
There are serious environmental problems: global warming, air pollution and depletion of fossil fuel reserves. The main advantage of these systems over traditional power generation systems is that they take advantage of the heat which is produced during the process of electrical energy generation, which results in a total energy efficiency that can exceed 90%, much higher than that of conventional systems, which is around 40%. Their high efficiency means lower fuel consumption, which leads to a reduction in the operating cost and a reduction in the amount of greenhouse gases emitted into the atmosphere [5]–[7]
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