Based on mathematical modelling and numerical simulations, a control strategy for a Molten Carbonate Fuel Cell Hybrid System (MCFC-HS) is presented. Adequate maps of performances with three independent parameters are shown. The independent parameters are as follows: stack current, fuel mass flow and compressor outlet pressure. Those parameters can be controlled by external load, fuel valve and turbine-compressor shaft speed, respectively. The control system is purposed to meet many constraints: e.g. stack temperature, steam-to-carbon ratio, compressor surge limitation, etc. The aim is to achieve maximum efficiency of power generated within these constraints. Governing equations of MCFC-HS modelling are given. An operational line of the MCFC-GT system is presented which fulfils several constraints (temperature difference, cell temperature, etc.) The system is able to achieve efficiency of more than 62% even in part-load operation.
High-temperature solid oxide fuel cells (SOFCs) are considered as suitable components of future large-scale clean and efficient power generation systems. However, at its current stage of development some technical barriers exists which limit SOFC’s potential for rapid large-scale deployment. The present article aims at providing solutions to key technical barriers in SOFC technology. The focus is on the solutions addressing thermal resistance, fuel reforming, energy conversion efficiency, materials, design, and fuel utilisation issues.
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).
Based on mathematical modeling and numerical simulations, applicativity of various biofuels on high temperature fuel cell performance are presented. Governing equations of high temperature fuel cell modeling are given. Adequate simulators of both solid oxide fuel cell (SOFC) and molten carbonate fuel cell (MCFC) have been done and described. Performance of these fuel cells with different biofuels is shown. Some characteristics are given and described. Advantages and disadvantages of various biofuels from the system performance point of view are pointed out. An analysis of various biofuels as potential fuels for SOFC and MCFC is presented. The results are compared with both methane and hydrogen as the reference fuels. The biofuels are characterized by both lower efficiency and lower fuel utilization factors compared with methane. The presented results are based on a 0D mathematical model in the design point calculation. The governing equations of the model are also presented. Technical and financial analysis of high temperature fuel cells (SOFC and MCFC) are shown. High temperature fuel cells can be fed by biofuels like: biogas, bioethanol, and biomethanol. Operational costs and possible incomes of those installation types were estimated and analyzed. A comparison against classic power generation units is shown. A basic indicator net present value (NPV) for projects was estimated and commented.
The paper presents dynamic model of hot water storage tank. The literature review has been made. Analysis of effects of nodalization on the prediction error of generalized finite element method (GFEM) is provided. The model takes into account eleven various parameters, such as: flue gases volumetric flow rate to the spiral, inlet water temperature, outlet water flow rate, etc. Boiler is also described by sizing parameters, nozzle parameters and heat loss including ambient temperature. The model has been validated on existing data. Adequate laboratory experiments were provided. The comparison between 1-, 5-, 10- and 50-zone boiler is presented. Comparison between experiment and simulations for different zone numbers of the boiler model is presented on the plots. The reason of differences between experiment and simulation is explained.