This paper describes experimental activities for the characterization of Lithium-ion Capacitors (LiC), with particular focus on their application in road hybrid thermal-electric vehicles. These activities represent a valid methodology to perfor\m experimental characterization of storage systems based on lithium technology. With this aim, electrical and thermal characterizations of LiC storage cells and modules, carried out through experimental tests on advanced laboratory facilities, are described in this paper.
The obtained results represent a useful knowledge base to evaluate optimal design and energy management strategies of the on board storage systems for their real application on the vehicle.
With the access of large-scale clean energy and in face of a lot of reconstruction strategies, the problems of complexity and poor convergence exist in the traditional investment planning optimization model which includes optimal power flow (OPF) and network safety constraint (NSC), as well as the iteration calculation of performance index. Thus, an optimal investment decision model of distribution network (DN) is proposed based on correlation mining between reconstruction strategies and reliability index. Based on the correlation constraint, the multi-year rolling investment model is established respectively aiming at maximizing the index and minimizing the total investment cost to obtain the optimal investment plans. Finally, an example is given to verify the rapidity, feasibility and effectiveness of the investment model.
Natural gas hydrate has been regarded as an alternative energy resource and has attracted much attention in recent years. According to laboratory investigations and field test researches, pore-scale distribution habit of gas hydrate in the hydrate bearing sediments plays a critical role in gas hydrate exploration and exploitation. In this work, the micro X-ray computed tomography was applied to investigate the pore-scale hydrate distribution habit during hydrate formation and dissociation. The gas hydrate was formed and dissociated in-situ and a nondestructive detection was performed to observe the internal characteristics of the hydrate sediment. The experimental results indicate that the hydrate distribution habit evolves from grain-coating to pore-filling during hydrate formation. During hydrate dissociation, thermal stimulation can promote homogeneous hydrate redistribution, and uniform distribution of glass beads is promoted by the depressurization.
Woodchip as an alternative fuel is widely fired to generate electricity and steam. However, fouling is a major issue for woodchip fired boilers. It is important to develop mathematical models and predictive tools to understand and predict ash deposition behavior. A mechanistic fouling model considering build‐up and removal mechanisms during ash deposition is developed in this work. In the models, the effect of surface roughness on ash deposition was also considered. Meanwhile, the fouling model was implemented into the ANSYS FLUENT and was combined with the discrete particle model (DPM), heat transfer model, and dynamic mesh model to predict ash deposition behavior on a deposition probe. The simulation result was validated against the experimental data obtained from a lab‐scale experimental setup. The simulated trend of the deposit thickness as a function of time shows good agreement with the experimental results. Based on the developed model, the effects of the removal model and flue gas velocity were investigated. The results show that it is necessary to consider the removal mechanism even when the flue gas is low. The deposition mass presented a significant decrease with the increase of flue gas velocity. An asymptotic trend for the deposition mass was observed for the cases considering the removal model. The research shows that the mechanistic fouling model coupled with CFD is a promising tool to predict the ash deposition behavior in low‐temperature conditions for the woodchip fired grate boilers.
There are implicit assumptions that should be considered for the commonly used production-decline models (Exponential, Harmonic and Hyperbolic decline models), such as relative stable well control conditions, leads to the difficulty on quantitative forecasting during some complicated situation happens. A new decline prediction model was proposed through theoretical derivation, and the decline rate was interpreted from three different parts (water cut rising, liquid productivity index changing , and pressure drop changing ) for the first time. Furthermore, three calculation cases under different conditions (under constant liquid production rate, constant pressure drop and arbitrary conditions) were analyzed, and the different changing rules of deline rate were analyzed. Comparing to the actual dynamic data, the proposed model shows high accuracy, even if some complicated situation happens, however theprediction error of the common decline models could be large. So it makes great sense in improving the dynamic performance forecasting.
This paper presents thermodynamic analyses of a two-stage organic Rankine cycle (ORC) for solar thermal power generation. The effects of the operational parameters (i.e. high-pressure stage evaporating temperature, low-pressure stage evaporating temperature, solar collector outlet temperature and solar irradiation) on the SORC system performance (net power generation, overall system thermal efficiency, exergy efficiency and total thermal conductance) were investigated. The results indicated that there exist optimal high-pressure stage evaporating temperature and solar collector outlet temperature for maximizing the power generation, energy efficiency and exergy efficiency of the SORC system. As the solar irradiation and low-pressure stage evaporating temperature increase, the net power generation, overall system thermal efficiency and exergy efficiency increase.
Aviation industry has a substantial carbon footprint, which is likely to increase due to a continuous rise in air travel demand. Use of bio-fuels present a prospective carbon mitigation measure. Success of any technological innovation depends on public’s awareness and perception of that technology. Little is known about the social acceptance of aviation bio-fuels. Public’s awareness and opinion can contribute to social acceptance resulting in higher uptake of this type of fuel by the aviation sector. In this study, we examine public acceptance by designing a multiple-choice questionnaire based upon public’s knowledge, perception and attitude. Convenience randomly sampling is used to select the respondents. Along with demographic questions, 4 questions are related to knowledge; 3 questions explore the social trust; 10 questions try to judge respondents’ perception while 5 relate to attitude. For recording the responses, five point Likert Scale is used. A model questionnaire is presented for discussion. Preliminary results of pilot study are also presented.
The thermal inertia of the district heating system (DHS), which are natural and great heat storages, have been considered in the combined heat and power (CHP) system operation to reduce wind curtailments. In this paper, according to the different thermal characteristics of public and residential buildings, a CHP system optimal operation model considering the thermal inertia of DHS and adopting a centralized control with flow varied by steps mode in DHS operation is proposed. Case study shows that the proposed model has much better performance in economic benefits and wind power integration.
A well‐parameterized battery model is prerequisite of the model‐based estimation and control methods. This paper focuses on the unbiased model parameter identification when noises corrupt the measurements. The parameter identification problem within the noise corruption scenario is reformulated as a nonlinear least squares (NLS) problem. A novel offline two‐step method combining least squares (LS) regression and variable projection algorithm (VPA) is then proposed to coestimate the noise variances and unbiased model parameters. The proposed LSVPA is further extended to the online recursive version by using the Gauss‐Newton (GN) method. Simulation and experimental results show that the proposed method can well compensate for the noise effect and improve the accuracy of model parameterization.
In order to solve the problems of high heat loss, low fermentation temperature and low gas production in biogas engineering in winter. In this paper, the annual thermal energy loss of biogas project is systematically analyzed, and a regenerative mass recovery device with solid-liquid separation is developed. Finally, the heating effect of the device at different temperatures is tested through experiments. The results showed that under the condition of good heat preservation measures, the heat loss of the fermentation tank accounted for 89.3% 93.2% of the total heat loss of the anaerobicfermentation system. Under the ambient temperatureof 18 ℃, the feed at 16.2 ℃can be heated to 26.6 ℃by regeneration and mass recovery. The waste heat ofthe biogas slurry recovered accounted for 51.9% of theheat required for constant temperature fermentation.At ambient temperature of 0 ℃, the feed at 2.5 ℃can be heated to 18.9 ℃ by regeneration and massrecovery. The waste heat of the biogas slurry recoveredaccounted for 47.2% of the heat required for constanttemperature fermentation. The remaining heat issupplied by a collector array consisting of 14 groups ofsolar collectors, which can ensure the constanttemperature fermentation of biogas engineering at37 ℃ in winter. And the system has good economicand environmental benefits.