Browsing by Author "Lopes, Vitor V."
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- Assessing cell polarity reversal degradation phenomena in PEM fuel cells by electrochemical impedance sectroscopyPublication . Travassos, Maria Antónia; Lopes, Vitor V.; Silva, R. A.; Novais, Augusto Q.; Rangel, C. M.Electrochemical impedance spectroscopy (EIS) is identified as one of the most promising in-situ diagnostics tools available for assessing fuel cell ageing and degradation. In this work, the degradation phenomena caused by cell polarity reversal due to fuel starvation of an open cathode 16 membrane electrode assembly (MEA) – low power (PEM) fuel cell (15 W nominal power) – is reported using EIS as a base technique. Measuring the potential of individual cells, while the fuel cell is on load, was found instrumental in assessing the “state of health” of cells at fixed current. Location of affected cells, those farthest away from hydrogen entry in the stack, was revealed by very low or even negative potential values. EIS spectra were taken at selected break-in periods during fuel cell functioning. The analysis of impedance data was made using an a priori equivalent circuit describing the transfer function of the system in question –equivalent circuit elements were evaluated by a complex non-linear least square (CNLS) fitting algorithm, and by calculating and analyzing the corresponding distribution of relaxation times (DRT). Results and interpretation of cell polarity reversal due to hydrogen starvation were complemented with ex-situ MEA cross section analysis, using scanning electron microscopy. Electrode thickness reduction and delamination of catalyst layers were observed as a result of reactions taking place during hydrogen starvation. Carbon corrosion and membrane degradation by fluoride depletion are discussed.
- Assessing cell polarity reversal degradation phenomena in PEM Fuel Cells by electrochemical impedance spectroscopyPublication . Travassos, Maria Antónia; Lopes, Vitor V.; Novais, Augusto Q.; Rangel, C. M.The mechanisms of fuel cell degradation are multiple and not well understood. Irreversible changes in the kinetic and/or transport properties of the cell are fostered by thermal, chemical and mechanical issues which constrain stability, power and fuel cell lifetime. Within the in-situ diagnostics methods and tools available, in-situ electrochemical impedance spectroscopy (EIS) is within the most promising to better understand and categorize changes during fuel cell ageing. In this work, the degradation phenomena caused by cell polarity reversal due to fuel starvation of an open cathode 16 MEA (membrane-electrode assembly) –low power PEM fuel cell (15 W nominal power) is reported using EIS as a base technique. A frequency response analyzer from Solartron Model 1250 was used connected to an electrochemical interface also from Solartron, Model 1286. The range of covered frequencies spans from 37000 Hz to 0.01Hz. Hydrogen is supplied from a metallic hydride small reactor with a capacity of 50 NL H2 at a pressure of 0.2 bar. Measuring the potential of individual cells, while the fuel cell is on load, was found instrumental in assessing the “state of health” of cells at fixed current. Location of affected cells, those farthest away from hydrogen entry in the stack, was revealed by the very low or even negative potential values. EIS spectra were taken at selected break-in periods during fuel cell functioning. The analysis of impedance data is made using two different approaches: using an a priori equivalent circuit describing the transfer function of the system in question -equivalent circuit elements were evaluated by a complex non-linear least square (CNLS) fitting algorithm, and by calculating and analyzing the corresponding distribution of relaxation times (DRT) -avoiding the ambiguity of the a priori equivalent circuit and the need for provision of the initial fitting parameters. A resistance and two RQ elements connected in series are identified as describing the impedance response of the cell during normal functioning. A constant phase element (CPE) was chosen to describe the impedance observed behavior. The quality of the fit was evaluated by analysis of the residuals between the fit result and the measured data at every single point. Consistency and quality of the impedance data were established by Kramers-Kronning validation. With continuous operation, using a reduced hydrogen flow, an inversion of polarity was observed in the 16th cell of the stack, evident in the potential measurement of individual cells as a result of insufficient hydrogen to reach the last cells. EIS data analyses suggest that water electrolysis happens at the anode judging by the appearance of an intermediate semicircle associated to a marked change in resistance and capacitance values. The presence of an inductive loop at low frequencies is now evident, which cannot be explained by the relaxation of reaction intermediates involved in the oxygen reduction reaction [1]. It is to be noticed that when the incursion into the negative potential values is not too marked the phenomenon is partially reversible, so it is suggested that the relaxation is due to intermediates in the water electrolysis process. The anode potential rose to levels compatible with the oxidation of water. Once the phenomenon is made irreversible and when water is no longer available, oxidation of the carbon support is favored accelerating catalyst sintering. Ex-situ MEA cross section analysis, under a scanning electron microscope, confirmed it. Electrode thickness reduction and delamination of catalyst layers were observed as a result of reactions taking place during hydrogen starvation. Carbon corrosion and membrane degradation are analyzed, according to evidence by SEM.
- Comparison of GA and PSO performance in parameter estimation of microbial growth models: a case-study using experimental dataPublication . Calçada, Dulce; Rosa, Agostinho; Duarte, Luís C.; Lopes, Vitor V.In this work we examined the performance of two evolutionary algorithms, a genetic algorithm (GA) and particle swarm optimization (PSO), in the estimation of the parameters of a model for the growth kinetics of the yeast Debaryomyces hansenii. Fitting the model’s predictions simultaneously to three replicates of the same experiment, we used the variability among replicates as a criterion to evaluate the optimization result. The performance of the two algorithms was tested using 12 distinct settings for their operating parameters and running each of them 20 times. For the GA, the crossover fraction, crossover function and magnitude of mutation throughout the run of the algorithm were tested; for the PSO, we tested swarms with 3 different types of convergence behavior - convergent with and without oscillations and divergent - and also varied the relative weights of the local and global acceleration constants. The best objective function values were obtained when the PSO fell in the zone of convergence with oscillations or zigzagging, and had a local acceleration larger than the global acceleration. immunization.
- A cyclic time-dependent Markov process to model daily patterns in wind turbine power productionPublication . Scholz, Teresa; Lopes, Vitor V.; Estanqueiro, AnaWind energy is becoming a top contributor to the renewable energy mix, which raises potential reliability issues for the grid due to the fluctuating nature of its source. To achieve an adequate reserve commitment which mitigates wind integration costs as well as to promote market participation, it is necessary to provide models that can capture daily patterns in wind power production. This paper presents a cyclic inhomogeneous Markov process, which is based on a three-dimensional state-space partition of the wind power, speed and direction variables. Each transition probability is a time-dependent function, expressed as a Bernstein polynomial. The model parameters are estimated by solving a constrained optimization problem: The objective function combines two maximum likelihood estimators, one to ensure that the Markov process long-term behavior reproduces the data accurately and, another to capture daily fluctuations. The paper presents a convex formulation for the overall optimization problem and demonstrates its applicability through the analysis of a case-study. The proposed model is capable of reproducing the diurnal patterns of a three-year dataset collected from a wind turbine located in a mountainous region in Portugal. In addition, it is shown how to compute persistence statistics directly from the Markov process transition matrices. Based on the case-study, the power production persistence through the daily cycle is analysed and discussed.
- Dynamic testing of systems – use of TRNSYS as an approach for parameter identificationPublication . Almeida, Patrícia; Carvalho, Maria João; Amorim, Ricardo; Mendes, J. Farinha; Lopes, Vitor V.Dynamic testing of solar thermal systems is presently defined by ISO 9459-5:2007. The testing methodology is clearly defined in the standard. Presently, laboratories that use Dynamic System Testing methodology only have available for identification of parameters, a closed source program, which is based on a model described by Spirkl and Muschawek (1992). The present paper describes the work done following a different approach for the identification of parameters – use of TRNSYS to simulate the system and use of GENOPT for optimization. Results are presented, both for thermosyphon and forced circulation systems, and show, in most cases, good agreement (differences lower then ±5%) when compared with the results using ISS, v2.7 (from In Situ Scientific Software). Comparison of system energy yield, calculated using TRNSYS for periods higher than one month, with measured energy yield for these periods, was also done for a thermosyphon system showing very good agreement (differences lower than ±3%).
- Electrochemical impedance spectroscopy modeling using the dis-tribution of relaxation times and error analysis for fuel cellsPublication . Lopes, Vitor V.; Rangel, C. M.; Novais, Augusto Q.This paper proposes a new approach to determine the distribution of relaxation times (DRT) directly from the electro-chemical impedance spectroscopy (EIS) data, i.e. without the use of an equivalent electrical circuit model. The method uses a generalized fractional-order Laguerre basis to represent EIS where both the parameters of the basis and their co-efficients are estimated by solving a nonconvex minimization problem. Furthermore, the DRT confidence region is de-termined to assess the accuracy and precision of the DRT estimate. The approach is applied to analyze the dominant dynamic properties of an open-cathode hydrogen fuel-cell under different current and air-flow conditions. Results showed that the estimated DRT closely reconstructs EIS data even when there is a higher variance at smaller relaxation times.
- Heuristic algorithm for the piecewise linear segmentation of multiple time-series for solar thermal systems inverse modellingPublication . Lopes, Vitor V.; Ferro, Filipa; Carvalho, Maria João; Novais, Augusto Q.This paper presents a novel algorithm for the piecewise linear segmentation of multivariate time-series and proposes its application to the analysis of hot water thermal solar systems (TSS). The ISO 9459-5:2007 norm describes a non-intrusive dynamic test for the performance assessment of TSS. This allows to characterize the system heat losses and the thermal stratification properties, as well as to predict its long-term performance. The application of this norm requires an inverse modeling approach where the parameters of a simplified plug flow storage model, based on simulation runs, are determined through an optimization procedure aiming at the adjustment of the predicted results to those obtained by a predefined experimental test sequence (3-5 days). This paper proposes a new method to decrease the computation time required for the model simulation, which is based on the segmentation of the multivariate time-series into a piecewise linear approximation, where the number of segments is critically selected. An illustrative example is presented consisting in the simulation of a real 3-day experimental dataset with 26873 points and a 15 s sampling rate.
- Hydrogen PEMFC stack performance analysis : a data-driven approachPublication . Lopes, Vitor V.; Novais, Augusto Q.; Rangel, C. M.For low power fuel cells, it is paramount that management of reactants, water and heat, be realized in a passive fashion in order to minimize parasitic losses. Effective fuel, oxygen supply and water management for reliable performance are also greatly affected by cell geometry and materials. Fuel cells are complex systems to optimize on a mere experimental basis. As an aid to this goal, data-driven analysis techniques, requiring no mathematical model to be fixed a priori, are gaining a reputation in other fields of work, where a phenomenological modeling approach might be intractable. This work presents a characterization study of a 12W PEMFC series stack by means of a new data-driven technique, M-NMF. The stack was developed for low temperature operation, uses own designed flow field plates, integrated in a series configuration, and is operated for 12 combinations of hydrogen/air flowrate ratios, generating as many polarization curves. M-NMF is applied, in combination with an alternating least squares algorithm, to the analysis of the overvoltage data matrix derived from the original experimental polarization data. From this analysis, it is possible to group and differentiate data according to similar overvoltage patterns and gain insight into their relative contribution to fuel cell performance immunization.
- Impact of weather regimes on the wind power ramp forecastPublication . Couto, António; Costa, Paula Silva; Rodrigues, L.; Lopes, Vitor V.; Estanqueiro, AnaThe stochastic nature of wind and the continuous need to balance electric generation with demand poses serious challenges to the power system operators. The impact of large wind integration into the power system is mitigated by decreasing the uncertainty associated with wind forecasts. In particular, the forecast of severe wind power ramps is important due to its impact on the energy market and grid operation and planning. This study proposes to classify the weather regimes over continental Portugal associated with the severe wind power production ramps. Thus, an automated classification system is developed by combining principal components analysis and kmeans clustering to find the most representative atmospheric flow patterns near the surface. This system can tackle with the synoptic spatial variability allowing the decrease of phase and timing mismatches present in single time forecasts. Then, the patterns are linked to the wind power production. Results show that it is possible to associate weather regimes with different levels of wind power production and identify certain atmospheric circulations with a higher chance to trigger severe wind power ramps.
- Impact of weather regimes on the wind power ramp forecast in PortugalPublication . Couto, António; Costa, Paula Silva; Rodrigues, L.; Lopes, Vitor V.; Estanqueiro, AnaShort-term forecasting and diagnostic tools for severe changes of wind power production (power ramps) may provide reliable information for a secure power system operation at a small cost. Understanding the underlying role of the synoptic weather regimes (WRs) in triggering the wind power ramp events can be an added value to improve and complement the current forecast techniques. This work identifies and classifies the WRs over mainland Portugal associated with the occurrence of severe wind power ramps. The most representative WRs are identified on compressed surface level atmospheric data using principal component analysis by applying K-means clustering. The results show a strong association between some synoptic circulation patterns and step variations of the wind power production indicating the possibility to identify certain WRs that are prone to trigger severe wind power ramps, thus opening the possibility for future development of diagnostic warning systems for system operators’ use.