The effect of heavy tars (toluene and naphthalene) on the electrochemical performance of an anode-supported SOFC running on bio-syngas

The effect of heavy tar compounds on the performance of a Ni-YSZ anode supported solid oxide fuel cell was investigated. Both toluene and naphthalene were chosen as model compounds and tested separately with a simulated bio-syngas. Notably, the effect of naphthalene is almost negligible with pure H2 feed to the SOFC, whereas a severe degradation is observed when using a bio-syngas with an H2:CO = 1. The tar compound showed to have a remarkable effect on the inhibition of the WGS shift-reaction, possibly also on the CO direct electro-oxidation at the three-phase-boundary. An interaction through adsorption of naphthalene on nickel catalytic and electrocatalytic active sites is a plausible explanation for observed degradation and strong performance loss. Different sites seem to be involved for H2 and CO electro-oxidation and also with regard to catalytic water gas shift reaction. Finally, heavy tars (C>=10) must be regarded as a poison more than a fuel for SOFC applications, contrarily to lighter compounds such benzene or toluene that can directly reformed within the anode electrode. The presence of naphthalene strongly increases the risk of anode re-oxidation in a syngas stream as CO conversion to H2 is inhibited and also CH4 conversion is blocked

CFD Performance Analysis of a Dish-Stirling System for Microgeneration

The sustainable transition towards renewable energy sources has become increasingly important nowadays. In this work, a microgeneration energy system was investigated. The system is composed of a solar concentrator system coupled with an alpha-type Stirling engine. The aim was to maximize the production of electrical energy. By imposing a mean value of the direct irradiance on the system, the model developed can obtain the temperature of the fluid contained inside the Stirling engine. The heat exchanger of the microgenerator system was analyzed, focusing on the solar coupling with the engine, with a multiphysical approach (COMSOL v5.3). A real Stirling cycle was implemented using two methods for comparison: the first-order empirical Beale equation and the Schmidt isothermal method. Results demonstrated that a concentrator of 2.4 m in diameter can generate, starting from 800 W/m2 of mean irradiance, a value of electrical energy equal to 0.99 kWe

Biogas Cleaning: Activated Carbon Regeneration for H2S Removal

The coupling of fuel cell technology with wastewater treatment plants (WWTPs) is within the sustainable development imperative for the integration of energy production purposes and recovery of materials, even if research is still under development in this field. The anaerobic digestion process can be used for fuel cell feeding, only if trace contaminants are removed continuously. The most harmful and frequent contaminant is H2S. This article shows the results of H2S adsorption on activated carbon fixed-beds (dry process), since it is one of the best solutions from both the complexity and costs perspectives. Inside the wide range of commercial activated carbons, a specific commercial carbon has been used in test campaigns, since it is also used in the Società Metropolitana Acque Torino (SMAT) real plant. Thermal regeneration of spent carbons was exploited, using different conditions of temperature, treatment time and atmosphere, since it is a better cost-effective and environmentally sound option than immediate carbon disposal after adsorption. Regeneration with CO2 showed the best regeneration ratio values. In particular, the best conditions achieved were 300 ◦C and 75 min of thermal treatment time, with a regeneration ratio of 30%

A Prediction Model for Energy Production in a Solar Concentrator Using Artificial Neural Networks

Solar energy is widely adopted today and produced by photovoltaic or concentrator solar power (CSP). Photovoltaic technology is the most prevalent, thanks to its well-established technology and low costs. CSP technology, on the other hand, has received less attention and interest, as it requires larger investments and a considerable surface. A relevant difficulty connected to the CSP is decoupling solar randomness and energy production. This paper proposes an artificial neural network (ANN) which foresees energy production using a solar parabolic dish installed at Politecnico di Torino (Energy Center Lab). The investigation was performed using a backpropagation ANN. Different learning algorithms were used: Levenberg-Marquardt, Bayesian regularization, resilient backpropagation, and scaled conjugate gradient. Seven atmospheric condition parameters were adopted (humidity, temperature, pressure, wind velocity and direction, solar radiation, and rain), to calculate the receiver temperature as an output. Bayesian regularization was found to be the optimal model for CSP energy production. The results of this investigation suggest that the ANNs are a strong, reliable, and useful tool for predicting temperature in a CSP receiver that can be of great value in the forecasting of energy production. The outcome of this investigation can simplify energy production forecasting using readily available meteorological data

Thermal gradients - evaluations for the receiver of a disc solar concentrator

The receiver of a disc solar concentrator is not only stressed by the high solar radiation concentrated in a limited volume; it must also cope with thermal fluctuations. The resulting thermal gradient has a catastrophic effect on the mechanical characteristics of the receiver. As the thermal gradient increases, the thermal stress on the selected materials increases. If the creep limit is exceeded, the material begins to deform plastically to the point of fracture. The outputs of the problem are the spatial trend of the temperature at the end of the transient and the temporal trend of the most stressed section, which turns out to be the output section. In addition, the thermal stress induced by the temperature gradient was evaluated at the end of the transient, which turns out to be the most extreme working condition. The following materials were studied: Alloy 625, Alloy 800H, Haynes 230, Inconel 740H, Alloy 316H. The best material is Inconel 740H, which has a high yield strength and the lowest ΔT of all the materials analyzed. It is also the only one that could withstand the induced thermal shock even under extreme working conditions

Physical activation of waste-derived materials for biogas cleaning

Biogas produced from biomass is carbon neutral. In fact, the carbon feedstock of biomass is converted into gas phase. Biogas use in high efficient energy systems, such as Solid Oxide Fuel Cells is a viable choice. One of the most important drawbacks for such systems is related to the interaction between trace compounds and anode section. Gas cleaning through physical removal mechanisms is the simplest and cheapest method adopted in the literature. Coupled with this solution, the recovery of waste materials is an efficient application of the circular economy approach. In this work, a physical activation process was investigated experimentally for waste-derived materials at a temperature of 700 °C. The removal of H2S was considered as the most abundant trace compound. Activated biochar showed an adsorption capacity comparable to commercial sorbents, while the performance of ashes are still too poor. An important parameter to be considered is the biogas humidity content that enters in competition with trace compounds that must be removed

Synthetic-Gas Production through Chemical Looping Process with Concentrating Solar Dish: Temperature-Distribution Evaluation

The energy crisis and the adaptation of the global energy structure promote the development of renewable energies, in particular solar energy, also for syngas production. In this work, attention was focused on solar devices, necessary to provide high-temperature heat for the reduction reaction of metal oxides involved in the chemical looping driven by solar energy. Thermochemical processes for synthetic-gas production and CO2 sequestration were investigated using a concentrating solar thermal system. This paper proposes a useful forecasting model of the receiver temperature to make a realistic estimate of the system’s producibility for the different periods of the year. The model proposed was validated in the winter season, and the predicted temperature varied below 5% considering the real experimental data (442–472 ◦C). The validated model was used to evaluate the temperature receiver in spring and in summer, when the thermal level is reliable for thermochemical processes. From the spring season until the completion of the summer season, optimum conditions inside the receiver were reached (above 1000 ◦C). These preliminary findings could be used for the development of large-scale production systems

Thévenin's Battery Model Parameter Estimation Based on Simulink

Lithium-ion batteries (LIB) proved over time to be one of the best choices among rechargeable batteries. Their small size, high energy density, long life, and low maintenance need make them a prominent candidate for the role of the most widespread energy storage system. They have the potential to monopolize the green technology sector. An accurate definition of the parameters defining the behaviour of the battery in different operating conditions is thus essential, as their knowledge proves crucial in certain fields such as those that involve electric vehicles. This paper proposes the estimation of the values of the parameters of the Thevenin equivalent circuit of a LIB commercial cell. Experimental data obtained through constant current charge/discharge cycles are analysed through a Simulink model, and results are obtained as a function of the state of charge (SOC) for a fixed and controlled temperature value. The results achieved with the proposed model can monitor the salient parameters of the equivalent circuit with an error between 7 and 10%