Dynamic modeling and simulations of solid oxide fuel cells for grid-tied applications

As energy consumption rises, one must find suitable alternative means of generation to supplement conventional existing generation facilities. In this regard, distributed generation (DG) will continue to play a critical role in the energy supply-demand realm. The common technologies available as DG are micro-turbines, solar photovoltaic systems, fuel cells stack and wind energy systems. In this thesis, a dynamic model of solid oxide fuel cell (SOFC) is presented. Fuel cells operate at low voltages and hence need to be boosted and inverted in order to be connected to the utility grid. The interconnection of the SOFC with a DC-DC converter and a DC-AC inverter for interfacing with the grid is presented in this thesis --Abstract, page iii

SOFC-Based Fuel Cells for Load Following Stationary Applications

This paper presents a dynamic model of SOFC and the response of the fuel cell for sudden load changes. Slow response of the fuel cell prevents it from following the load, Hence connection with the DC/DC buck-boost converter is required. The models are developed in PSCAD with and without a feedback control system. Power characteristics obtained in order to validate the need of the DC/DC converter which allows the SOFC system to be used for load following application

Reversible and irreversible potentials and an inaccuracy in popularmodels in the fuel cell literature

Modeling is an integral part of fuel cell design and development. This paper identifies a long-standing inaccuracy in the fuel cell modeling literature. Specifically, it discusses an inexact insertion, in popular models, of cell/stack current into Nernst\u27s equation in the derivation of output (load) voltage. The origin of the inaccuracy is traced to the nature of reversible and irreversible potentials (equilibrium and non-equilibrium states) in the cell. The significance of the inaccuracy is explained in the context of the electrochemistry and thermodynamics of the fuel cell

A New Inverter for Improved Fuel Cell Performance in Grid-Tied Application

The interconnection of a solid oxide fuel cell (SOFC) with the power conditioning units vis-à-vis a DC/DC converter and a DC/AC inverter for interfacing with the utility grid is presented. Fuel cells operate at low voltages and hence need to be boosted and inverted in order to be connected to the grid. The fuel cell and the DC/DC converter modeling are briefly explained. The methodology and the controller design for the control of power flow from the fuel cell to the utility grid are discussed. Power characteristics of the DC/AC inverter are compared with the characteristics of the DC/DC converter and the fuel cell. Fuel cells have slow response time which prevents it from grid-tie applications. Simulations validate the improvement in the response when the power conditioning unit is connected

Modeling of Phosphorous Acid Fuel Cell in PSCAD

The renewable energy sources, such as wind, fuel cells, etc. are gaining more attention due to the increase in energy demand as well as being environmental kindly. A dynamic model of Phosphorous Acid Fuel Cell is modeled and simulated using PSCAD/EMTDC. The system consists of a fuel cell stack along with 3-phase Pulse-Width Modulator (PWM) inverter, LCL filter and step-up transformer connected to the main grid. A Real-Reactive power controller is implemented into the 3-phase PWM inverter to control and stabilize the active and reactive power flow onto the main grid. A LCL filter is connected to the inverter side, which eliminates the ultra-harmonic distortions of the frequency. The effect of the Line-Ground, Line-Line, etc. faults on the performance of the main grid’s output voltage is analyzed and studied. The fuel cell is connected to the main grid and the simulation results contain the analysis at different stages of the simulation

A new model for constant fuel utilization and constant fuel flow in fuel cells

This paper presents a new model of fuel cells for two different modes of operation: constant fuel utilization control (constant stoichiometry condition) and constant fuel flow control (constant flow rate condition). The model solves the long-standing problem of mixing reversible and irreversible potentials (equilibrium and non-equilibrium states) in the Nernst voltage expression. Specifically, a Nernstian gain term is introduced for the constant fuel utilization condition, and it is shown that the Nernstian gain is an irreversibility in the computation of the output voltage of the fuel cell. A Nernstian loss term accounts for an irreversibility for the constant fuel flow operation. Simulation results are presented. The model has been validated against experimental data from the literature

Modeling Of A Planar Sofc Performance Using Artificial Nueral Network

The Planar Solid Oxide Fuel Cell (PSOFC) is one of the renewable energy technologies that is important as the main source for distributed generation and can play a significant role in the conventional electrical power generation. PSOFC stack modeling is performed in order to provide a platform for the optimal design of fuel cell systems. It is explained by the structure and operating principle of the PSOFC for the modeling purposes. PSOFC model can be developed using Artificial Neural Network approach. The data required to train the neural net-work model is generated by simulating the existing PSOFC model in the MATLAB/ Simulink software. The Radial Basis Function (RBF) and Multilayer Perceptron (MLP) neural networks are the most useful techniques in many applications and will be applied in developing the PSOFC model. A detailed analysis is presented on the best ANN network that gives the greatest results on the performances of the PSOFC. The simulation results show that Multilayer Perceptron (MLP) gives the best outcomes of the PSOFC performance based on the smallest errors and good regression analysis

Avaliação do uso de célula a combustível como fonte secundária de energia em sistema híbrido com arranjo fotovoltaico

A dissertação propõe a modelagem de um sistema híbrido isolado composto por arranjo fotovoltaico e conjunto de células a combustível do tipo membrana trocadora de prótons utilizando o software PSCAD. O texto traz a revisão dos principais conceitos relativos à energia fotovoltaica e à célula a combustível, além de apresentar trabalhos relacionados ao tema que motivaram a realização desse estudo. O módulo fotovoltaico é modelado a partir de folha de dados fornecida pelo fabricante, enquanto que a célula a combustível tem seu modelo baseado em estudo realizado anteriormente. Para garantir a potência do sistema, são feitas associações série-paralelo dos módulos fotovoltaicos e das células a combustível. A modelagem do sistema híbrido, que inclui inversores, conversor buck e filtros LCL, assim como o controle utilizado são apresentados de forma detalhada. As fontes atuam em conjunto para suprir as cargas no sistema isolado. Entretanto, o conjunto de células a combustível somente produz potência ativa quando o arranjo fotovoltaico é incapaz de suprir a demanda total, com exceção da partida do sistema. Por se tratar de sistema isolado e pela fonte solar fotovoltaica ter a característica de fonte intermitente, a referência dos sistemas de controle advém do conjunto de PEMFCs. O objetivo das simulações é verificar a dinâmica de funcionamento do sistema isolado mediante variações de radiação solar e de carga. Palavras-chave: Célula a combustível. Arranjo fotovoltaico. PEMFC. PSCAD. Sistema híbrido

STUDY OF STRATEGIES FOR AN OPTIMAL ENERGY MANAGEMENT ON ELECTRIC AND HYBRID VEHICLES

Questa tesi di dottorato è focalizzata sull’identificazione di strategie di gestione dell’energia a bordo di veicoli elettrici e ibridi, con l’obiettivo di ottimizzare la gestione dell’energia e, quindi, consentire un risparmio di risorse. Infatti, l’ottimizzazione della fase d’uso del veicolo, attraverso una più efficiente gestione dell’energia, consente di dimensionare in modo ridotto i principali componenti, come il pacco batterie. Innanzitutto, viene presentato un tool di simulazione denominato TEST (Target-speed EV Simulation Tool). Questo strumento consente di effettuare simulazioni di dinamica longitudinale per veicoli completamente elettrici o ibridi e, quindi, di monitorare tutti i dati rilevanti necessari per effettuare un corretto dimensionamento del gruppo propulsore, inclusi il/i motore/i elettrico/i ed il pacco batterie. Inoltre, è possibile testare anche diversi layout di propulsori, compresi quelli che utilizzano celle a combustibile, le cosiddette “fuel cell”. Viene poi presentata una strategia di frenata rigenerativa, adatta per veicoli FWD, RWD e AWD. L’obiettivo principale è quello di recuperare la massima energia frenante possibile, mantenendo il veicolo stabile, con buone prestazioni in frenata. La strategia è stata testata sia attraverso un consolidato software di simulazione della dinamica del veicolo (VI-CarRealTime), sia attraverso simulazioni “driver-in-the-loop” utilizzando un simulatore di guida. Inoltre, la strategia proposta è stata integrata nel tool TEST per valutarne l’influenza sull’autonomia e sui consumi del veicolo. Gli strumenti sopra menzionati sono stati utilizzati per studiare uno scenario di casi reali, per valutare la fattibilità dell’utilizzo di una flotta alimentata a fuel cell a metano per svolgere attività di raccolta rifiuti porta a porta. I risultati mostrano un’elevata fattibilità in termini di autonomia del veicolo rispetto alle missioni standard di raccolta dei rifiuti, a condizione che i componenti siano adeguatamente dimensionati. Il dimensionamento dei componenti è stato effettuato attraverso iterazioni, utilizzando diversi componenti nelle stesse missioni. Infine, è stata riportata un’analisi approfondita degli studi LCA (Life Cycle Assessment) relativi ai veicoli elettrici, con particolare attenzione al pacco batterie, evidenziando alcune criticità ambientali. Questo studio sull’LCA sottolinea quindi l’importanza di una corretta gestione dell’energia per ridurre al minimo l’impatto ambientale associato al consumo stesso di energia.This PhD thesis is focused on identifying energy management strategies on board electric and hybrid vehicles, to optimize energy management and thus allow for resource savings. In fact, vehicle’s operational phase optimisation through a more efficient energy management allows main components downsizing, such as battery pack. First of all, a simulation tool called TEST (Target-speed EV Simulation Tool), is presented. This tool allows to carry out longitudinal dynamics simulations on pure electric or hybrid-electric vehicles, and therefore monitoring all the relevant data needed to carry out a proper powertrain sizing, including the electric motor(s) and the battery pack. Furthermore, several powertrain layouts can be also tested, including those using fuel cells. Then a regenerative braking strategy, suitable for FWD, RWD and AWD vehicles, is presented. Its main target is to recover the maximum possible braking energy, while keeping the vehicle stable with good braking performance. The strategy has been tested both through a state-of-art vehicle dynamics simulation software (VI-CarRealTime) and through driver-in-the-loop simulations using a driving simulator. Furthermore, the proposed strategy has been integrated into TEST to evaluate its influence on vehicle range and consumptions. The above-mentioned tools have been used to evaluate a real-world case scenario to assess the feasibility of using a methane fuel cell powered fleet to carry out door to door waste collection activities. Results show high feasibility in terms of vehicle range compared to standard waste collection missions, provided that components are properly sized. Components sizing has been done through iterations using different components on the same missions. Finally, an in-depth analysis of the LCA (Life Cycle Assessment) studies related to electric vehicles has been reported, with particular focus to the battery pack, highlighting some environmental critical issues. This LCA study therefore emphasizes the importance of a correct energy management to minimize the environmental impact associated with energy consumption