The thesis deals with the principle functions of low-temperature fuel cells with proton exchange membrane (PEMFC), photovoltaic sources (PVPP) and wind energy sources (WPP), along with solving their detailed mathematical expressions. In this work, the individual sources and their simulated models are analyzed in depth. The actual simulation is preceded by familiarization with important historical milestones in the development of fuel cells. Furthermore there is a basic classification of fuel cells and the characteristics of the cells used in the energy sectors. The text also provides information on projects that address the implementation of PEMFC as a primary or supplementary source of energy. Along with outlining the options for PEMFC as a perspective hydrogen technologies in the near future, the basic methods of hydrogen production and storage options are presented for the complexity. The work is exclusively focused on improving PEMFC mathematical models that under the hybrid system cooperate with renewable energy sources (RES). Part of the theses contains a short review of run or modeled concepts of hybrid systems in the energy sector. Using these models the main deficiencies of the models or of the whole PEMFC system can be identify. Specifications of the deficiencies lead to the creation of a new advanced dynamic PEMFC model that allows an analysis of the development of electrical and non-electrical quantities using long term tests. Furthermore, the thesis presents results of the experiments of thermal and dynamic behavior PEMFC, which were obtained from the additionally extended model with a reformer and the DC/DC converter. In this text there is a model of a photovoltaic module created, which is based on the nominal values parameterization. The model is subjected to basic experiments in which measured hydrometeorological data are used. If the hybrid system utilizes renewable energy sources, it is good to know the evolution of atmospheric conditions in the installation of these resources. Specifically for PVPP, publicly available databases containing information about solar radiation levels can be used for the selected location. Public databases are often used for initial design and manufacturing options for PVPP. An evaluation of the relevancy of public databases is performed based on a long-term observation of real measured data. Furthermore, these data are used for experiments on the photovoltaic module. Partially the text addresses the issue of the wind energy sources, however, it is simulated only on a simplified model of WPP. Created models of subsystems can be generally implemented as partial inputs hybrid systems in the future work. The thesis was developed at Centre for Research and Utilization of Renewable Energy (CVVOZE) with the financial support of the National Programme for Sustainability and the Ministry of Education, Youth and Sports of the Czech Republic under the project no. LO1210 - Energy for Sustainable Development and the project no. FEKT-S-14-2520 - New Technologies for Sustainable Development of Electrical Power Systems. The thesis was also generated under the project no. TA03020523 - Dynamic model of distribution network with the financial support of Technology Agency of the Czech Republic.

This thesis explores what Karlstad Airport needs to go 100% green. Photovoltaics are assumed to be installed at the facility and a Hydrogen Energy Storage System and Battery Energy Storage System will be evaluated to reduce peaks during charging of the planes. Different power peak limits are explored as well as different sized Energy Storage Systems and later evaluated economically. A method to find the cheapest possible system is created with some assumptions and is then used to evaluate throughout the whole dataset. In the end any of the different sized Energy Storage Systems reduces the profitability when considering each systems expected lifecycle.

Improving the efficiency and performance of vehicle propulsion systems has always been desirable, and with increasing environmental awareness this has become increasingly topical. A particularly strong focus today is at fossil-free alternatives, and there is a strong trend for electrification. Hybrid powertrains of different types can bring benefits in certain aspects, and there is a lot of research and development involved in the making of a new powertrain. In this thesis, a complete powertrain for a fuel cell hybrid electric vehicle is modeled, with the intention of contributing to this trend. The model can be used to investigate design choices and their impact on energy consumption. A component-based library is developed, with the purpose of being easy to implement for different configurations. The results show that it is possible to assemble and simulate a complete hybrid drivetrain, using the modeled components, while not being very computationally heavy. The developed models correspond well with reality while being modular and easy to implement.

In this research, a proton exchange membrane fuel cell (PEMFC) sensor was investigated for specific detection of volatile organic compounds (VOCs) for point-of-care (POC) diagnosis of the physiological conditions of humans. A PEMFC is an electrochemical transducer that converts chemical energy into electrical energy. A Redox reaction takes place at its electrodes whereas the volatile biomolecules (e.g. ethanol) are oxidized at the anode and ambient oxygen is reduced at the cathode. The compounds which were the focus of this investigation were ethanol (C2H5OH) and isoflurane (C3H2ClF5O), but theoretically, the sensor is not limited to only those VOCs given proper calibration. Detection in biosensing, which needs to be carried out in a controlled system, becomes complex in a multivariate environment. Major limitations of all types of biosensors would include poor selectivity, drifting, overlapping, and degradation of signals. Specific detection of VOCs in multi-dimensional environments is also a challenge in fuel cell sensing. Humidity, temperature, and the presence of other analytes interfere with the functionality of the fuel cell and provide false readings. Hence, accurate and precise quantification of VOC(s) and calibration are the major challenges when using PEMFC biosensor. To resolve this problem, a statistical model was derived for the calibration of PEMFC employing multivariate analysis, such as the “Principal Component Regression (PCR)” method for the sensing of VOC(s). PCR can correlate larger data sets and provides an accurate fitting between a known and an unknown data set. PCR improves calibration for multivariate conditions as compared to the overlapping signals obtained when using linear (univariate) regression models. Results show that this biosensor investigated has a 75% accuracy improvement over the commercial alcohol breathalyzer used in this study when detecting ethanol. When detecting isoflurane, this sensor has an average deviation in the steady-state response of ~14.29% from the gold-standard infrared spectroscopy system used in hospital operating theaters. The significance of this research lies in its versatility in dealing with the existing challenge of the accuracy and precision of the calibration of the PEMFC sensor. Also, this research may improve the diagnosis of several diseases through the detection of concerned biomarkers.

In recent years, Polymer Electrolyte Membrane Fuel Cells (PEMFC) have attracted much attention due to their potential as a clean power source for many applications, including automotive, portable and stationary devices. This resulted in a tremendous technological progress, such as the development of new membranes and electro-catalysts or the improvement of electrode structures. However, in order to compete within the most attractive markets, the PEMFC technologies did not reach all the required characteristics yet, in particular in terms of cost and durability.Because of the strong coupling between different physicochemical phenomena, the interpretation of experimental observations is difficult, and analysis through modeling becomes crucial to elucidate the degradation and failure mechanisms, andto help improving both PEMFC electrochemical performance and durability.The development of a theoretical tool is essential for industrials and the scientific community to evaluate the PEMFC degradation and to predict itsperformance and durability in function of the materials properties and in a diversity of operating conditions. This manuscript summarizes my scientific research efforts in this exciting topic during the last 9 years in France, including my invention of the MEMEPhys multiscale simulation package,developed on the basis of my childhood passion for the New Technologies for Energyin Argentina. My perspectives of adapting this approach to other electrochemical systems such as water electrolyzers and batteries are also discussed.