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The article shows the proposed solution of the objective function for the seasonal thermal energy storage system. In order to develop this function the technological and economic assumptions were used. In order to select the optimal system configuration mathematical models of the main elements of the system were built. Using these models, and based on the selected design point, the simulation of the entire system for randomly generated outside temperatures was made. The proposed methodology and obtained relationships can be readily used for control purposes, constituting model predicted control (MPC). [ABSTRACT FROM AUTHOR]

This article deals with a thermal energy storage system in the form of a water tank with a thermocline. The well-known thermocline phenomenon is modeled using computational fluid dynamics (CFD). However, the reservoir model proposed in this article is zero-dimensional. This is due to the fact that the aim of this article is to build a mathematical model that will be more useful in mathematical models of complex energy systems in which a hot water tank is one of many elements of the system. In such a zero-dimensional mathematical model, the hot water tank will be modeled using equations describing heat transfer, and the thermocline itself will be treated as a heat transfer surface with known dimensions and heat transfer coefficient. A novelty of this paper is that it addresses heat loss across the thermocline as defined in this manner. A CFD model of a thermal storage tank is created, validated with available experimental data, and used to obtain the heat transfer coefficient U. The resulting value is then analyzed quantitatively and qualitatively and the changes in the thickness of the thermocline are accounted for in the equation. The results from this groundbreaking work can be used to analyze heat storage in the form of thermocline water tanks at the level of system modeling, e.g., for the purpose of configuring the structure of other devices and control systems. [ABSTRACT FROM AUTHOR]

The article provides an overview of knowledge on how to model fuel cells using software which is oriented to system modeling. The overview covers several types of fuel cell such as SOFC, MCFC and PEMFC. Fuel cells were modeled using mainly three types of software, i.e. Aspen Hysys, Aspen Plus and Matlab. Based on our literature review, we decided to use Aspen Hysys to create a proton conducting SOFC model. Model construction is based on a reduced order approach that we published earlier. We used available experimental data to verify the model we created on. The results generated by the model and the experimental data were then subjected to an error analysis. Only two of all the articles found contained a set of information that was fit for the purpose of validating the model. The model maps the work of the proton conducting SOFC with high accuracy, i.e., an error of 0.01 V. • The methodology for model implementation in available software is reported. • The model represents an alternative approach for voltage prediction of a H + SOFC. • A validation process for the models implemented in Aspen Hysys/Excel is presented. [ABSTRACT FROM AUTHOR]