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 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

Dynamic Behavior and Management Strategy of Hybrid Wind/Fuel Cell System

Abstract: hybrid generation system is considered as a solution for the uncontrolled energy production from such dispersed sources as wind generation. In this paper, modeling and control of wind/FC system is proposed. Dynamics models for the main system components, namely, wind energy conversion system (WECS), fuel cell, electrolyses, power electronic interfacing circuits, hydrogen storage tank and ultra-capacitor are developed. Also, a variable speed wind generation maximum power point tracking (MPPT) based on Adaptative Neuro-Fuzzy Inference system (ANFIS) is presented. Based on the dynamic component model, a simulation model for the proposed hybrid energy system has been developed using Matlab/Simulink and the power flows management strategy are proposed. The result shows that this system can tolerate the rapid changes in wind speed and/or power demand. This results shows also that, the overall power management strategy is effective and the power flows among the different energy sources and the load demand is balanced successfully

Energy Management Strategy Using ANFIS Approach for Hybrid Power System

Renewable Energy Sources are the promising hopes of upcoming years as they are abundant in nature and available free of cost. In addition to this, these sources are pollution-free which makes them a perfect substitute for fossil fuels. A Hybrid Power System (HPS) is one that has multiple power generating sources like Photo Voltaic (PV) system, Wind turbine, Fuel cell, etc. interconnected to supply electric power for varying demand requirements with / without energy storage backup. This paper concentrates on the automation for control and integration of Renewable energy systems Viz. PV system, Solid Oxide Fuel Cell (SOFC) with Nickel-Metal-Hydride (Ni-MH) battery together with a variable load. The Proposed HPS mainly focuses on the use of PV which is 100% clean in nature with no toxic emissions on power generation. Here, the solar photovoltaic system with power extracting maximum by algorithm used as the major supply contributor in the HPS to meet with variable load demands. If there is a deficit of power supply from PV, the power from the Ni-MH battery / SOFC is utilized to meet the varying load demands. On the other hand, if there is excess supply from PV system, the excess energy will be stored in the Ni-MH battery. For efficient supply-demand balance, the HPS makes use of various control strategies namely Proportional Integral (PI) and Adaptive Neuro Fuzzy Inference System (ANFIS)

Urban and extra-urban hybrid vehicles: a technological review

Pollution derived from transportation systems is a worldwide, timelier issue than ever. The abatement actions of harmful substances in the air are on the agenda and they are necessary today to safeguard our welfare and that of the planet. Environmental pollution in large cities is approximately 20% due to the transportation system. In addition, private traffic contributes greatly to city pollution. Further, “vehicle operating life” is most often exceeded and vehicle emissions do not comply with European antipollution standards. It becomes mandatory to find a solution that respects the environment and, realize an appropriate transportation service to the customers. New technologies related to hybrid –electric engines are making great strides in reducing emissions, and the funds allocated by public authorities should be addressed. In addition, the use (implementation) of new technologies is also convenient from an economic point of view. In fact, by implementing the use of hybrid vehicles, fuel consumption can be reduced. The different hybrid configurations presented refer to such a series architecture, developed by the researchers and Research and Development groups. Regarding energy flows, different strategy logic or vehicle management units have been illustrated. Various configurations and vehicles were studied by simulating different driving cycles, both European approval and homologation and customer ones (typically municipal and university). The simulations have provided guidance on the optimal proposed configuration and information on the component to be used

Comprehensive summary of solid oxide fuel cell control : a state-of-the-art review

Hydrogen energy is a promising renewable resource for the sustainable development of society. As a key member of the fuel cell (FC) family, the solid oxide fuel cell (SOFC) has attracted a lot of attention because of characteristics such as having various sources as fuel and high energy conversion efficiency, and being pollution-free. SOFC is a highly coupled, nonlinear, and multivariable complex system, and thus it is very important to design an appropriate control strategy for an SOFC system to ensure its safe, reliable, and efficient operation. This paper undertakes a comprehensive review and detailed summary of the state-of-the-art control approaches of SOFC. These approaches are divided into eight categories of control: proportional integral differential (PID), adaptive (APC), robust, model predictive (MPC), fuzzy logic (FLC), fault-tolerant (FTC), intelligent and observer-based. The SOFC control approaches are carefully evaluated in terms of objective, design, application/scenario, robustness, complexity, and accuracy. Finally, five perspectives are proposed for future research directions

Adaptive Neural Network-Based Control of a Hybrid AC/DC Microgrid

In this paper, the behavior of a grid-connected hybrid ac/dc microgrid has been investigated. Different renewable energy sources - photovoltaics modules and a wind turbine generator - have been considered together with a solid oxide fuel cell and a battery energy storage system. The main contribution of this paper is the design and the validation of an innovative online-trained artificial neural network-based control system for a hybrid microgrid. Adaptive neural networks are used to track the maximum power point of renewable energy generators and to control the power exchanged between the front-end converter and the electrical grid. Moreover, a fuzzy logic-based power management system is proposed in order to minimize the energy purchased from the electrical grid. The operation of the hybrid microgrid has been tested in the MATLAB/Simulink environment under different operating conditions. The obtained results demonstrate the effectiveness, the high robustness and the self-adaptation ability of the proposed control system

A review of microgrid energy systems

Microgrid combined cooling, heating and power energy systems are under intensive investigation owing to expansion of renewable energy generation and development of advanced technologies in distributed energy generation. Multi-generation systems serve as one of the core parts in any microgrid energy systems. This review paper presents the summary of state-of-the-art technologies in these multi-generation systems. The first part introduces the energy structure based on energy sources and the latest renewable energy harvesting technologies for solar, biomass and geothermal energy. In the second part, prime movers, including small-scale ones used in a microgrid energy system, are summarized. The third part shows the expanded microgrid system configurations mainly for desalination. The fourth part describes the control and operation strategies for complex multi-generation systems. In the first three parts, insufficient investigation or research gaps are also pointed out. Overall, this paper systematically summaries recent progress in microgrid multigeneration system, and suggest future researches for designing and optimizing a microgrid energy system