Performance degradation data obtained from single Solid oxide fuel cells, tested at 850 degrees C with air and humidified H-2 and using Ni-YSZ anode supported cells, are presented here. Microscopic investigation is carried out on both anode and cathode to quantify variations in the morphology at different operation times. The comparison between the measurements On the cells and the SEM Image analysis, allows to conclude that there is no relationship between the initial cell activation and microstructural modifications of the electrodes. On the other hand, it was found that cell degradation is Strictly related to the coarsening of Ni particles occurring in the anode. A theoretical analysis based. on an electrode micro-model has been performed in order to compare the variation in performance, expected from particle size change, with the observed data. The model confirmed the conclusions of the experimental results
Composite electrodes are of great interest in the field of solid oxide fuel cells because their use can improve the performance of these cells. However, an important correlation exists between composition, microstructure, and thickness of an electrode and its performance. This correlation has been investigated in this work using a theoretical model. The model, in order to consider all the losses occurring in an electrode, includes Ohm’s law for ionic and electronic charge transport, and the Butler-Volmer equation to evaluate the activation polarizations, and mass transport equations, taking into account diffusion through porous media, to evaluate the concentration losses. The model shows that the best electrode performance is a trade-off between activation and concentration losses. This is because a decrease in the dimensions of the particles or an increase in its thickness result, on the one hand, in a reduction of the activation polarizations, because of a larger active area for the electrochemical reaction, and, on the other hand, in an increase in the concentration losses due to a more difficult gas diffusion. In particular, in order to understand the impact of concentration losses on the performance of composite electrodes, the simulations have been run with two models, one including and the other one neglecting the mass transport equations. The results show that concentration losses play a role only with thick electrodes composed of small particles, operating at high fuel utilization.
The anodes used in SOFCs are composites, formed by a mixture of nickel and YSZ particles. This paper presents a model for this type of electrode, taking mass transport effects into account. The effect of the operating conditions, such as temperature and pressure, is discussed. Also, the effect of the choice of the geometrical parameters, such as electrode thickness and particle radius, on the electrode performance is analysed in detail. In particular, the electrode losses display a minimum for a well-defined radius of the electrode particles, which is related to a trade-off between activation and concentration losses
Abstract:Intermediate temperature-solid oxide fuel cell (IT-SOFC) Ni-(ZrO 2 ) x (Y 2 O 3 ) 1−x (Ni-YSZ) anodes formed by two layers, with different thicknesses and morphologies, offer the possibility of obtaining adequate electrochemical performance coupled to satisfactory mechanical properties. We investigate bi-layered Ni-YSZ anodes from a modeling point of view. The model includes reaction kinetics (Butler-Volmer equation), mass transport (Dusty-Gas model), and charge transport (Ohm's law), and allows to gain an insight into the distribution of the electrochemical reaction within the electrode. Additionally, the model allows to evaluate a reciprocal overall electrode resistance 1/R p ≈ 6 S· cm −2 for a bi-layer electrode formed by a 10 µm thick active layer (AL) composed of 0.25 µm radius Ni and YSZ particles (34% vol. Ni), coupled to a 700 µm thick support layer (SL) formed by 0.5 µm radius Ni and YSZ particles (50% vol. Ni), and operated at a temperature of 1023 K. Simulation results compare satisfactorily to literature experimental data. The model allows to investigate, in detail, the effect of morphological and geometric parameters on the various sources of losses, which is the first step for an optimized electrode design.
Wind power is one of the fastest-growing renewable energy sectors and is considered instrumental in the ongoing decarbonization process. However, wind turbines (WTs) present high operation and maintenance costs caused by inefficiencies and failures, leading to ever-increasing attention to effective Condition Monitoring (CM) strategies. Nowadays, modern WTs are integrated with sensor networks as part of the Supervisory Control and Data Acquisition (SCADA) system for supervision purposes. CM of wind farms through predictive models based on routinely collected SCADA data is envisaged as a viable mean of improving producibility by spotting operational inefficiencies. However, given the large number of variables monitored by SCADA systems, selecting those that contribute the most to the modelling of wind turbine health conditions is an open challenge. In this paper, we propose an unsupervised feature selection algorithm based on a novel multivariate Predictive Power Score (PPS). Unlike other approaches in literature that only consider relationships between pairs of variables, here we propose a Combined PPS (CPPS), where the information content of combinations of variables is considered for the prediction of one or more key parameters. The algorithm has been tested on 9 turbines belonging to the same wind farm located in the Italian territory. The results show that the proposed approach is more flexible and outperforms standard PPS.
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