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Battery Thermal Management System (BTSM) is essential for maintaining optimal operation conditions for hybrid electric vehicles (HEVs) and electric vehicles (EVs). This study aimed to propose an innovative impinging jet cooling BTMS for HEVs using mist cooling. The dilute mist completely evaporated to avoid the risk of external circuit failure or corrosion that could result from surface wetting. Impinging experiments were performed under the conditions where inflow air temperature, T a,in, was 21.2 °C ≤ T a,in ≤ 31.0 °C and initial humidity, φ , was 50.9 %RH ≤ φ ≤ 96.0 %RH. It was found that the target plate was cooled down by up to 0.8 K without surface wetting by adding 5.5 mg/s water mist to the air. Numerical analyses were performed under conditions ranging from 21.2 °C ≤ T a,in ≤ 31.0 °C and 0.0 %RH ≤ φ ≤ 100.0 %RH. The results and discussion highlight the importance of the critical initial humidity, φ critical : the complete evaporative threshold. Deviation between the experimental and numerical results at a fixed inflow air temperature, Δ φ , was −1.9 %RH ≤ Δ φ ≤ 3.0 %RH. Δ φ was within the range of measurement uncertainty U (φ) = 4.0 %RH. Thus, the experimental and numerical results were consistent within the experimental measurement uncertainty. As a result, φ critical tends to be high in the case of high inflow temperature. The mist cooling is a viable way of BTMS for HEVs without surface wetting due to its large cooling capacity that results in a 7.4 K cooling effect in a hot environment. [Display omitted] • Mist jet impinging battery thermal management system for HEVs was investigated. • Guaranteed safe operation through complete evaporation of the water mist. • Numerical simulations and experiments confirmed efficient mist evaporation. • Achieved a mist cooling effect of up to 7.4 K. • Simple structure enables high cooling efficiency with air and water supply. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the flow and flame dynamics within a combustion chamber supplied with nitrogen-diluted hydrogen fuel and air as oxidiser. The chamber is equipped with a bluff body that serves as a flame stabiliser. We focus primarily on the influence of the bluff body shape on the formation of large and small-scale vortical structures generated at the bluff body edge. We analyse how the geometry of the bluff body alters these structures and examine the impact of resulting modifications on flame characteristics, including key features such as flame length and radial extent, temperature and species field, and completeness of the combustion process. We consider four bluff body geometries, namely a typical cylindrical shape, a star-shaped wall, and a small triangular sharp and smooth wavy structure. The research employs the Large Eddy Simulation (LES) method, providing deep insight into the complex physics of unsteady flow. In the cylindrical bluff body configuration, the key mechanism driving the fuel-oxidiser mixing process is the periodic occurrence of large toroidal vortices shed at an exit of the oxidiser duct and on the bluff body edge. They exert the flow towards and away from a recirculation zone formed above the bluff body. When its geometry is irregular, the appearance of the large vortices is suppressed, however, the wall irregularities induce small-scale flow phenomena that enhance mixing in the shear layer formed between the recirculation zone and the oxidiser stream. The mixing efficiency is largely dependent on the shape of the bluff body wall, and it turns out that seemingly small changes (sharp vs. smooth small triangular parts), which in non-reactive regimes have only a minor effect on the flow dynamics, significantly change the flame length and fuel consumption rate. Compared to the cylindrical bluff body configuration, the small triangular parts cause an axial shift of the maximum temperature downstream and slow down fuel consumption. Contrary, large triangular elements in the star-shape bluff body clearly influence the flow both in non-reactive and reactive regimes. They cause the formation of local oxidiser streams directed towards the fuel-rich mixture. Consequently, the injected fuel burns at a rate similar to that observed in the case of the cylindrical bluff body, but the combustion process occurs at an average temperature approximately 200 K lower and its fluctuations are reduced. These factors may influence the thermal reduction of NOx. On the other hand, a negative aspect is the highest level of hydrogen in the closest vicinity of the bluff body, which in practical applications may accelerate the embrittlement of its surface. • A star-shaped bluff body suppresses the formation of large toroidal vortices generated at edges of typical cylindrical bluff bodies. • An oscillatory nature of large-scale mixing is supplanted by vigorous small-scale mixing, resulting in a more uniform combustion process. • The flame temperature is significantly reduced while the fuel consumption rate remains unchanged. [ABSTRACT FROM AUTHOR]

The low-temperature cold start has become one of the leading technical bottlenecks limiting the large-scale commercial application of proton exchange membrane(PEM) fuel cells. This paper establishes the 1-D numerical model of the fuel cell stack to study the reactant gas, charge transfer, heat transfer, and water phase transition process. Then the critical parameters in the numerical model of the fuel cell stack are identified based on the cold start experiment data. The identification results show that the cold start model is consistent with the experimental results, and the model's output voltage and average temperature errors are under the acceptable range. Based on the numerical model, with the cold start time as the optimization objective and load current and initial membrane water content as the optimization variable, the cold start strategy is optimized under different ambient temperatures. The results show that the optimized current loading strategy can reduce the cold start time of the fuel cell stack and achieve a fast, successful cold start for −20 °C and − 25 °C conditions. The cold start time of the optimized cold start strategy is reduced by 42.2% compared with the strategy of step stair current under −20 °C. For the lower ambient temperature,-30 °C or below, to realize the successful cold start of fuel cell stacks, two aspects are needed: the redesign of the bipolar plate and endplate structure and the optimization of the cold start strategy. • The supercooled water phase change process is established based on JMAK theory. • Parameters identification and error analysis for the numerical model are conducted. • Initial membrane and segmented currents are optimized for the cold start strategy. [ABSTRACT FROM AUTHOR]

As the integration of renewable energy sources (RES) progresses and energy technologies advance, integrated energy systems (IES) have emerged as a practical solution for leveraging RES and balancing local demand–supply dynamics. This paper investigates the planning and optimization of operations for an electricity-hydrogen integrated energy system (EH-IES), considering degradation and multi-timescale operations of storage devices to minimize the life cycle costs. To mitigate computational challenges, the planning model adopts a Representative Time Period (RTP) framework, and a novel intertemporal operation model is developed to coordinate the operations of battery and hydrogen storage. Furthermore, we propose a two-stage approach to derive representative weeks and hours from meteorological and load data using fewer data points, ensuring chronological coherence and preserving long-term patterns to validate storage device constraints and improve planning accuracy. Case studies in southeastern China's IES verify the effectiveness of our planning approach, which lowers equivalent annual costs by 4.5% and reduces battery capacity needs by 12.8%, thereby highlighting its significant economic benefits. Additionally, numerical analyses reveal that our two-stage method surpasses conventional RTP selection techniques, delivering at least 10% less average error with an equal number of operating points. • A novel planning and intertemporal model of EH-IES based on representative time periods is established. • The multi-timescale operations of the battery and hydrogen storage system is considered. • An efficient and accurate representative time-period selection method is developed. [ABSTRACT FROM AUTHOR]

In this study, a novel cathode flow field plate with additional tapered oblique fin (OF) channels is proposed for air-cooled proton exchange membrane fuel cells (PEMFCs) to promote their heat dissipation and output power. Air-cooled PEMFC stacks with conventional (parallel configuration) and novel flow fields are respectively manufactured and experimentally tested under various load currents. The performance and temperature distributions of the stacks are comparatively studied in detail. Besides, a three-dimensional and two-phase numerical model is established and validated by the experiment data to further comparative investigate the heat and mass transport mechanism of the two studied flow field designs. The results show that the stack with the novel flow field has higher output power, which is 4.87% higher than that with a conventional design at a load current density of 0.55 A cm−2. Due to the forced convection and secondary vortex phenomena in the OF channels, the local overheating in the porous electrode is relieved. Moreover, the entropy generations due to heat transfer of the cathode CL and cooling channels are significantly increased. The oxygen transport under cathode ribs is also noteworthily enhanced when the OF channels are adopted. • An air-cooled PEMFC stack with tapered oblique fin channels is designed and fabricated. • Tapered oblique fin channel design enhances stack performance and heat dissipation. • Local multi-physics fields inside the PEMFC are studied by numerical methods. • Mass transport and thermal behaviors inside the air-cooled PEMFC are optimized. • Entropy generation due to mass transport and heat transfer is studied for the PEMFC. [ABSTRACT FROM AUTHOR]

Due to heat losses of preferential areas of packed-bed energy storage systems, transverse temperature variations may occur during the charging, discharging and standby processes. Furthermore, the heat losses of preferential areas of the storage tank cause a lower pressure drop in these areas resulting in an increased mass flow rate and further cooling, and thereby an enhanced transverse temperature variation, in a positive feedback loop – a phenomenon called instability. The transverse temperature variations may deteriorate the performance and thereby the economic feasibility of packed-bed energy storage systems. In this paper, numerical and experimental investigations of an air-based packed-bed rock thermal energy storage system for large-scale high temperature applications are presented. The objective of the study is to predict the instability and to analyze the effect of different standby durations and storage size on the instability of the air-based packed-bed system. Transient axisymmetric computational fluid dynamics models were developed for the standby and discharging processes of the packed-bed thermal energy storage systems. In addition, experimental investigations were carried out at a test facility located at Stiesdal Storage, Denmark, using magnetite rocks as heat storage material and air as heat transfer fluid. The results suggest that the numerical predictions are in good agreement with the test data. The instability phenomenon is found to increase with the standby duration, resulting in a maximum difference of 161 K between the maximum rock temperature and the outlet air temperature for a standby period of 10 h followed by a discharging process. Moreover, the results indicate that the maximum difference between the rock temperature and outlet temperature is 73 K and 56 K for a reduced-scale and a full-scale system (no standby period), respectively. • Experiments were conducted on an air-based packed-bed thermal energy storage system. • CFD models were developed and validated for both static and dynamic operation. • Instability in packed-bed systems is predicted during the discharging process. • Increase in instability is observed with the increase in standby duration. • Comparison of reduced-scale and full-scale packed-bed systems is presented. [ABSTRACT FROM AUTHOR]

Ensuring the reliable operation of industrial boilers with high production efficiency and low pollutant emissions remains a significant challenge due to the complex chemical and physical reactions that occur within the boiler system. To address this issue, the present research introduces a novel air proportioning methodology for optimized combustion in gas-fired boilers, incorporating real-world data, numerical-computational technologies, and a normalization method. Initially, an average discrepancy of 11.32% is observed between the airflow recorded by the sensors and the actual airflow in the gas-fired boiler. The optimum oxygen levels in the flue gas are determined by striking a trade-off between heat release and pollutant emissions. At loads of 35%, 55%, 75%, and 95%, the recommended oxygen levels under equal-weighted conditions are 3.62%, 3.75%, 3.82%, and 3.91%, respectively. Furthermore, this research also considers the oxygen levels when there are non-equal weightings between heat release and nitrogen oxide (NO x) emissions. At 55% load, the weighting between heat release and pollutant emissions shifts from 1:1 to 1:2, necessitating an increase in the oxygen concentration from 3.75% to 4.30%. The air proportioning methodology proposed in this study offers an efficient framework for optimizing combustion in gas-fired boilers. • Introducing an innovative air proportioning methodology for gas-fired boilers. • Offering the optimal oxygen levels of flue gas for multiple operating conditions. • Employing real-world data, numerical analysis, and a normalization method. • Identifying an average discrepancy in airflow of 11.32% under multiple conditions. • Recommending an oxygen content in flue gas of 3.82% at 75% load. [ABSTRACT FROM AUTHOR]

• Four cooling regimes were employed to form CH 4 -hydrate bearing sediments. • All four multi-stage cooling regimes result in heterogeneous distribution of S H. • Heat inflow on the spatial distribution of S H (hydrate saturation) is significant. • Perfect insulation improves the uniformity of all phases in hydrate-bearing cores. Laboratory-created samples of methane hydrate (MH)-bearing media are a necessity because of the rarity and difficulty of obtaining naturally-occurring samples. The hypothesis that the inevitable heterogeneity in the phase saturations of the laboratory samples may lead to unreliable and non-repeatable results provided the impetus for this study, which aimed to determine the conditions under which maximum uniformity can be achieved. To that end, we designed four experiments involving different multi-stage cooling regimes (in terms of their duration and number of stages) to induce MH formation under excess-water conditions. In the absence of direct visualization capabilities, we analysed the experimental results by means of numerical simulation, which provided high-resolution predictions of the spatial distributions of the phase saturations in the cores and enabled the estimation of the parameters controlling the kinetic MH-formation behaviour through history-matching. Analysis of the numerical results indicated that, under the conditions of the experiments and with the design of the reactor, significant heterogeneities in phase saturation distributions were observed in all cases, leading to the conclusion that it is not possible to obtain cores with uniform phase saturation. Additionally, contrary to expectations, heterogeneities increased with the number of cooling stages and the duration of cooling, and this was attributed to imperfect insulation of the upper part of the reactor. A set of simulations involving perfect insulation of the reactor top confirmed the validity of this assumption: (a) predicting the formation of high-uniformity MH-bearing cores that became more homogeneous as the number of cooling stages and the length of the cooling period increased; and (b) providing important information for the improvement of the standard design of the experimental apparatus for the laboratory creation of MH-bearing cores using the excess water method. [ABSTRACT FROM AUTHOR]

• Model with particle radius and porosity changes for metal hydride tank is proposed. • Hydrogen absorption rates at different particle radii and porosities are studied. • Effect of volume expansion is coupled in mass, heat transfer and kinetics completely. • Simulation results of the models with and without volume expansion are compared. • Hydrogen absorption time is optimized from 1394.12 to 474.83 s without components. Slow hydrogen absorption rate and low capacity of a metal hydride tank are the main bottlenecks restricting the practical applications of hydrogen energy. It is crucial to avoid of reducing system gravimetric/volumetric capacity by the additional components for enhancing the hydrogen absorption rate. In this work, we present a new method to increase the hydrogen absorption rate on the basis of the influence of particle radius and porosity to the performance of a LaNi 5 tank. A model considering the effects of volume expansion on mass, heat transfer and kinetics is proposed and solved by the finite element method, which constructs the relationship of the hydrogen absorption rate of a metal hydride tank with particle radius and porosity. The results indicate that larger particle radius and higher porosity is of benefit to the hydrogen absorption reaction. Compared with the model without volume expansion, a slightly slower hydrogen absorption rate is given by the model with volume expansion, which is attributed to the decreased thermal diffusivity. The simulation results obtained by the model with volume expansion agree well with the experimental data. The LaNi 5 tank is further optimized based on the model with volume expansion, from which the hydrogen absorption time at 90% of maximum hydrogen capacity can be reduced from 1394.12 to 474.83 s when the particle radius is 100 μm and porosity is 0.63. [ABSTRACT FROM AUTHOR]

• TEG power output was relatively small due to small temperature difference. • The PV/TEG/PCM system achieved 9.5% power output more than other systems. • 50 mm thick PCM layer achieved the best performance for the PV/TEG/PCM system. Solar photovoltaic (PV) cells especially crystal silicon cells have witnessed a soaring installed capacity during past years. Research efforts have been made to increase the PV conversion efficiency and one direction is towards the cooling of PV systems since a higher PV temperature impairs its conversion efficiency. Phase change materials (PCM) capable of storing large amounts of latent heat are found to be effective on cooling PV cells while thermoelectric generators (TEG) which are solid waste heat converters can be used for converting the heat from PV into electricity. Therefore, this research investigates the concept of an integrated thermoelectric PCM system to enhance the PV efficiency. Theoretical investigations found that the TEGs had small power output due to small temperature difference under natural convection conditions. However, PCM was effective on hampering PV temperature increase during heat storage process. This research developed a numerical model for thermal simulations of the integrated system and has been validated by experimental results. The effect of various PCM thicknesses, conductivities and phase change temperatures were evaluated. The simulation results stressed the importance of high PCM conductivity for a thick PCM layer to reduce its insulation effect on the TEG and PV layers. Finally, the best thermal performance for the PV/TEG/PCM system was achieved with a 50 mm thick PCM layer with thermal conductivity of 5 W/m K and a phase change temperature of 40–45 °C. Further optimisation and experimental evaluation are however being recommended towards the establishment of the full technical and scientific boundaries. [ABSTRACT FROM AUTHOR]

• Modelling and experimental results of reciprocating expander were presented. • Variable valve timing was employed to control the expansion ratio of the expander. • The expander provide 2.5 kW power output and 70% isentropic efficiency. • Dynamic model predicts torque and pressure traces with reasonable accuracy. • Model predicts power and isentropic efficiency within ±10% and ±30% accuracy. This paper presents a reciprocating expander concept for organic Rankine cycle applications using a novel rotating variable timing admission valve system, enabling the adjustment of the expansion ratio in real time while the expander is running. An organic Rankine cycle experimental test rig with n-pentane as the working fluid and a single-cylinder reciprocating piston expander was developed. Experiments were conducted for evaporation temperatures ranging from 125 °C to 150 °C and condensation temperatures ranging from 20 °C to 40 °C. The performance of the reciprocating piston expander was investigated in terms of the torque of the expander, pressure inside the cylinder, isentropic efficiency of the expander, and net power produced by the expander. Based on the experimental data, a dynamic model of the system was formulated in the object-oriented language, Modelica. The model was validated using the experimental results and then used to predict the performance of the expander. Special attention was paid to the robust modelling of the valve actuation to avoid computational inefficiencies caused by singularities of state variables or their derivatives. The results indicate that the expander produces up to 2.5 kW of electricity from a low-temperature heat source while operating at pressure ratios ranging from 10 to 16.5 with an isentropic efficiency of approximately 70%. The relative differences between the model and the measurements of the isentropic efficiency and power output of the expander per revolution were ±10% and ±30%, respectively. [ABSTRACT FROM AUTHOR]

Highlights • A novel TEM structure is proposed to recover the waste heat contained in the fluid. • A numerical model is developed to evaluate the TEM performance. • The effect of different parameters on the TEM performance is investigated. • A maximum power occurs when load resistance is slightly larger than internal resistance. • The validation of the numerical model is performed through the comparison with experiment. Abstract Thermoelectric module (TEM) has been widely used to recover the waste heat contained in the fluid. However, its performance will be limited since all the thermoelements are connected in serial and the generated current each of them is not the same. To work out this deficiency, a novel TEM structure is disclosed, where the cross-sectional area of thermoelements is increasing gradually along with the hot fluid downward flow. Besides, this work develops a steady-state, three-dimensional and fluid-thermal-electric multi-physical model to evaluate the TEM performance. Based on the numerical results, the influences of different TEM structures, hot air temperature and mass flow rate on the TEM output performance are investigated. The results show that (i) Compared to conventional TEM, the novel TEM structure with the same quantity of thermoelectric material can reach a better performance when Δ W = 0.01 mm or 0.02 mm , and the higher temperature and mass flow rate, the more gains of the novel TEM; (ii) Compared with temperature, mass flow rate has a much higher effect on the output performance of the novel TEM structure; (iii) The maximum output power occurs when the load resistance is slightly greater than internal resistance. Apart from that, the verification experiments are conducted and the results indicate a good agreement of the proposed numerical model. The findings of this work may provide a new idea to optimize the TEM structure and improve its performance. [ABSTRACT FROM AUTHOR]

Highlights • PV parameters extraction using a system of non-linear equations. • New concept of shift-factors introduced. • Estimating each PV parameter as a function of both irradiance and temperature. • Variation of each parameter in accordance with PV device theory. • Model validated against PV panel's datasheet as well as field experiments. Abstract The batteries used with standalone PV systems are very sensitive to the current-voltage charging. Thus, for choosing the right battery, a PV system designer needs to make an accurate estimate of the current and voltage outputs of the PV module under consideration. However, this task is challenging due to randomness in the field operating conditions. To achieve this goal, the PV module in this work has been represented by a well-known equivalent one-diode electrical circuit with five unknown PV parameters. Using multiple current-voltage curves at different operating conditions, the proposed methodology extracts the five unknown PV parameters against each current-voltage curve. Each PV parameter is then plotted independently, first against the varying sunlight and then against the varying temperature. Then introducing a novel concept of shift-factors, the proposed methodology couples the two independent plots of each PV parameter and helps predict the value of that PV parameter at any operating condition. Unlike other works from the literature, the variations of these five PV parameters by the proposed methodology have been shown to be in accordance with the PV device theory and the physical behavior of the PV devices. The proposed model has been validated against both the PV panel's datasheet information and the experimental in-field data. With realistic values captured for each PV parameter by the proposed methodology, the validations show a significant increase in the prediction accuracy of the current-voltage output of the PV panel. It has also been shown how this methodology can be used to better understand the behavior of the PV system and aid in its preventive/corrective maintenance. [ABSTRACT FROM AUTHOR]

Highlights • A detailed piezoelectric-based energy harvesting pavement system is proposed. • A thin piezoelectric layer with piezo balls produces up to 85 V electricity. • A thick piezoelectric layer with piezo cylinders produces up to 50 V electricity. • Selections of insulative fillers in a piezoelectric layer are discussed. • Design strategies are proposed to lead this system closer to the field application. Abstract This study focuses on numerical investigation and optimization of one piezoelectric-based energy harvesting pavement system (PZ-EHPS), which consists of a piezoelectric layer sandwiched between two conductive asphalt layers. Novel piezoelectric element designs inside the piezoelectric layer, such as piezo ball and piezo roof, were proposed to explore the energy harvesting potential of the system. Considering the large scale of the system, finite element models were built not only to analyze the performance of PZ-EHPS specimens fabricated in the laboratory, but also to simulate the PZ-EHPS operation under real traffic conditions. Results from the laboratory-based finite element models, which were verified by experimental study, determined that a thin piezoelectric layer with piezo ball elements and a low stiffness insulative filler had the significant advantage of producing up to 85 V electricity. Compared to piezo ball elements, piezo cylinder elements may fit a thick and stiff piezoelectric layer better and lead to a high voltage output up to 50 V. As a result of the field-based finite element models, the PZ-EHPS with a rigid piezoelectric layer produces more electricity than that with a flexible piezoelectric layer. For a single-vehicle scenario, if each PZ-EHPS segment length equals the vehicle wheelbase length, consecutive PZ-EHPS segments may constantly supply high electricity as the vehicle moves at a high speed over the segments. For a multiple-vehicle scenario, however, the voltage output generated by a second vehicle will be reduced if the first vehicle is still on the same PZ-EHPS segment. This study provides optimal design features of the PZ-EHPS to lead this energy harvesting system significantly closer to the field application. [ABSTRACT FROM AUTHOR]

Highlights • Adsorption separation of CO 2 from dry and humid CO 2 /N 2 mixture is carried out under ambient conditions. • Experimentally validated model is applied by a user-defined-function in ANSYS Fluent. • 13X and Mg-MOF-74 are tested for breakthrough and cyclic CO 2 separations. • Dehydration process before CO 2 adsorption processes is strongly recommended. • Cycling separation is recommended to be used instead of breakthrough tests. Abstract Carbon dioxide and storage is an efficient method to reduce the emitted CO 2 from the burning of fossil fuels. Zeolite-based materials are conventional adsorbents used to adsorb some gasses involving carbon dioxide. Mg-MOF-74 is an eminent reticular material among adsorbents due to its good CO 2 capacity at low pressures (10–20 kPa). In this study, an experimentally validated model is used to report the H 2 O effect on CO 2 separation using 13X and Mg-MOF-74 under ambient conditions. A computational model has been developed using ANSYS Fluent program linked by user-define-function (written in C). The adsorption breakthrough results show that a humid CO 2 /N 2 mixture, under 300 K, 86% RH, 101.3 kPa, could slightly reduce the CO 2 adsorption capacity by about 0.05% and 6% for 13X and Mg-MOF-74, respectively (at CO 2 adsorption breakthrough saturation). Regardless of these reductions, Mg-MOF-74 has better adsorption capacity, even under humid ambient conditions, by about 5.77 mmol/g in a comparison to 2.27 mmol/g for 13X, respectively. Cycling stability over more than 90 cycles is also simulated; and shows that, a dehydration process is recommended to be carried out before the CO 2 separation process for efficient energy consumption and sustainable adsorbents. The total recyclable amounts of adsorbed CO 2 are about 0.94 and 3.07 mmol/g for 13X and Mg-MOF-74, respectively, under 101.3 kPa adsorption, 2 kPa desorption, 86% relative humidity, and 298 K. The cyclic CO 2 separation is found to be a robust method more than the breakthrough separation to evaluate the real adsorption capacities. [ABSTRACT FROM AUTHOR]

Highlights • Anode supported solid oxide fuel cell was experimentally studies. • Different rates of direct internal reforming (DIR) were considered. • Cell was exposed to presence of 1.2 ppm(v) of H 2 S. • Literature data were used for determination of the change of resistance of SOFC. • Effects of DIR and sulfur on the resistance of cell was correlated with voltage. Abstract Experimental analysis of a planar 100 mm × 100 mm SOFC cell was conducted during operation at 1173 K in direct internal reforming (DIR) mode. In the first phase the rate of direct internal reforming was varied from 0 to 100% what corresponds to complete external reforming and complete DIR, respectively. In the second phase 1.2 ppm(v) of H 2 S was introduced to the feeding gas and the variation of the rate of direct internal reforming was repeated. Following the experimental analysis the numerical model was proposed to determine the correlation between the presence of the poisoning agent and the electrochemical performance. The effect on the resistance of the cell was studied. The lumped volume model was applied to predict the cell voltage. With the use of the experimental data it was possible to determine the relative change of the model parameters which describe the ionic and electronic conductivity of the SOFC. Model was adopted for predictive modeling of the solid oxide fuel cell, operated in DIR-SOFC mode with and without the presence of hydrogen sulfide. Additionally, literature data measured for a cell operated in complete internal reforming mode with variation of the sulfur content in the feeding gas were analyzed to define the effect of H 2 S content on the performance drop. Relative change of the resistance of a cell was correlated with the rate of internal reforming and the content of sulfur. Results of the analysis show that the degradation of the performance of SOFC due to sulfur poisoning during operation in DIR mode can be modelled with high fidelity. Change of the ionic and electronic resistance of a cell accounted for the maximum of 34 and 53%, respectively when the rate of DIR was altered between 0 and 100%. The contribution of the sulfur poisoning accounts for 69 and 79% when the H 2 S content varies in the range of 0.001–5 ppm(v). With average relative prediction error below 3%, the proposed approach finds good application in simulating the performance of a cell exposed to different gas mixtures with different levels of sulfur in the fuel stream. [ABSTRACT FROM AUTHOR]

Highlights • A combined model is proposed for multi-step ahead wind speed forecasting. • Data preprocessing technology is introduced to improve the forecasting performance. • Quasi-Newton algorithm is used to increase the particle diversity of water cycle algorithm. • The accuracy and stability of wind speed forecasting are improved simultaneously. • The simulation results are validated well in China. Abstract Owing to the complexity and uncertainty of wind speed, accurate wind speed prediction has become a highly anticipated and challenging problem in recent years. Researchers have conducted numerous studies on wind speed prediction theory and practice; however, research on multi-step wind speed prediction remains scarce, which hinders further development in this area. To improve upon the accuracy and stability of multi-step wind speed prediction, this paper proposes a combination model based on a data preprocessing strategy, an improved optimization model, a no negative constraint theory, and several single prediction models. To improve upon forecasting performance, an improved water cycle algorithm based on a quasi-Newton algorithm is proposed to optimize the weight coefficients of the single models. In the empirical research, 10-min and 30-min wind speed data from Shandong Province in China, collected for case studies, were used to assess the comprehensive performance of the proposed combination model. Finally, we used 10-fold cross-validation and multiple error criteria to evaluate the comprehensive performance of the proposed combination model. The simulation results indicate that (a) the quasi-Newton algorithm can effectively increase the diversity of the water cycle algorithm particles, resulting in improved water cycle algorithm optimization performance; (b) the combination model exhibits superior predictive performance to a single model by taking advantage of each single model; and (c) the proposed combination model can effectively improve multi-step wind speed prediction results. [ABSTRACT FROM AUTHOR]

Highlights • The performance of an oil-free scroll expander is presented. • A total of 75 steady-state points with R245fa have been collected. • The friction losses were quantified to be up to 20% of total power output. • Semi-empirical and Artificial Neural Network models have been compared in a systematic way. • Experimental data and simulation model source-codes have been provided. Abstract Organic Rankine cycles (ORCs) are thermodynamic power cycles designed to generate work from a wide range of heat source conditions. In particular, low-grade waste heat recovery (WHR) (<150 ° C) can be effectively exploited with such systems. The efficiency of an ORC is highly dependent on its expander performance. In the low power output range (<10 kW), scroll expanders are cost-effective. Although a number of researchers have investigated the use of scroll compressors as expanders, very little work has been carried out in modeling and investigating the performance of oil-free expanders. In this work, an experimental evaluation of a newly designed open-drive oil-free scroll expander was performed. The expander had a nominal capacity of 5 kW, built-in volume ratio of 3.5, and was integrated into an ORC test-rig with R245fa as working fluid. The experimental data consisted of 75 data points that were used to map the oil-free operation of the scroll expander over five expander rotational speeds (from 800 rpm to 3000 rpm). Two heat sources inlet temperature, i.e. 85 ° C and 110 ° C, were investigated. The scroll expander achieved a maximum overall isentropic efficiency of 0.58 for the temperature source of 110 ° C, for the imposed specific volume ratio of 6.12 at rotational speed of 1600 rpm. For the same heat source, the maximum expander power output was 3.75 kW for an imposed specific volume ratio of 6.55 and rotational speed of 2500 rpm. Besides the experimental work, the performance of the expander was characterized by means of a semi-empirical model to break-down the different loss terms. A well known model available in the literature was extended to account for the major frictional losses in a scroll machine, i.e. bearings, tip-seals and other sources of friction. Additionally, an Artificial Neural Network (ANN) modeling approach was also proposed to achieve higher accuracy in mapping expander performance for use in system simulation. The experimental data and model source codes are provided as supplementary materials. [ABSTRACT FROM AUTHOR]

Highlights • Thermodynamic analysis of the ITM system. • Development of a two dimensional numerical ITM model. • Parametric analysis for the ITM. • Performance comparison of the proposed system with two other ITM systems. Abstract Ion transport membranes (ITM) have been studied as a promising air separation unit (ASU) technology for oxy–fuel combustion owing to their high oxygen permeability. Even though the power consumption of the ITM is lower than that of cryogenic ASU, it still consumes a high proportion of the overall system power. In this study, a numerical analysis of the ITM system has been conducted using Aspen Plus® to determine the optimal system design for minimizing the power consumption to separate oxygen from air. Since the oxygen permeation through the ITM is driven by the oxygen partial pressure gradient between feed and permeation side, three ITM systems that have different pressure gradients across the membrane have been presented and their performances compared. The effects of the contributing parameters, such as thickness, pressure, temperature, and air flow rate on the oxygen permeation rate have been investigated. ITM performances of the counter and parallel flow configurations have been compared. The system that operates under atmospheric pressure at the feed channel and under vacuum pressure at the permeate channel yields the lowest power consumption for obtaining the same oxygen permeation rate among other pressure conditions. [ABSTRACT FROM AUTHOR]

Highlights • Spatial and temporal correlation of wind power and uncertainty considered. • Sparse correlation matrix efficiently models the spatial-temporal correlation. • Distributionally robust chance constrained OPF model considers economics and security. • Considering spatial-temporal correlation leads to lower system operating cost. • Comparison with scenario-based stochastic model shows efficiency of proposed model. Abstract The significantly increasing deployment of wind power necessitates that system operation considers the spatial-temporal correlation of power forecast from different wind power plants. How to model this spatial-temporal correlation in the actual system dispatch is challenging. In this paper, a sparse correlation matrix is utilized to efficiently model the spatial-temporal correlation of wind power forecast in the generation dispatch model. A novel, adjustable, and distributionally-robust chance-constrained multi-interval optimal power flow (ADRCC-MIOPF) model is proposed to obtain reliable economic dispatch (ED) solutions. The spatial-temporal correlation of wind power plants power forecasts is represented by the sparse correlation covariance matrix obtained from historical, time series wind power forecast error data. The chance constraints in the ADRCC-MIOPF model are transformed into a set of second-order-cone (SOC) constraints in which an adjustable coefficient in the chance constraints controls the robustness of the ADRCC-MIOPF model to the wind power forecast errors distribution. Case studies performed on the PJM 5-bus system and IEEE 118-bus system verify the proposed method to improve the system security and reduce the cost especially under the high wind penetration levels. All the cases can be solved within several minutes for both the small and large cases which validates the efficiency of the proposed sparse matrix model. In addition, considering the spatial-temporal correlation of wind power forecast and the distributional robustness of wind power forecast error leads to a more reliable economic dispatch with lower system violations. [ABSTRACT FROM AUTHOR]

Highlights • Numerical analysis of MH dissociation and fluids production by depressurization. • A function describing the change in MH surface area is incorporated in the T+H code. • Flow, thermal, kinetic parameters are optimized using a history-matching technique. • Simulation validated by experiment elucidates the issue of spatial heterogeneity. Abstract Methane Hydrates (MHs) are a promising energy source abundantly available in nature. Understanding the complex processes of MH formation and dissociation is critical for the development of safe and efficient technologies for energy recovery. Many laboratory and numerical studies have investigated these processes using synthesized MH-bearing sediments. A near-universal issue encountered in these studies is the spatial heterogeneous hydrate distribution in the testing apparatus. In the absence of direct observations (e.g. using X-ray computed tomography) coupled with real time production data, the common assumption made in almost all numerical studies is a homogeneous distribution of the various phases. In an earlier study (Yin et al., 2018) that involved the numerical description of a set of experiments on MH-formation in sandy medium using the excess water method, we showed that spatially heterogeneous phase distribution is inevitable and significant. In the present study, we use as a starting point the results and observations at the end of the MH formation and seek to numerically reproduce the laboratory experiments of depressurization-induced dissociation of the spatially-heterogeneous MH distribution. This numerical study faithfully reproduces the geometry of the laboratory apparatus, the initial and boundary conditions of the system, and the parameters of the dissociation stimulus, capturing accurately all stages of the experimental process. Using inverse modelling (history-matching) that minimized deviations between the experimental observations and numerical predictions, we determined the values of all the important flow, thermal, and kinetic parameters that control the system behaviour, which yielded simulation results that were in excellent agreement with the measurements of key monitored variables, i.e. pressure, temperature, cumulative production of gas and water over time. We determined that at the onset of depressurization (when the pressure drop – the driving force of dissociation – is at its maximum), the rate of MH dissociation approaches that of an equilibrium reaction and is limited by the heat transfer from the system surroundings. As the effect of depressurization declines over time, the dissociation reaction becomes kinetically limited despite significant heat inflows from the boundaries, which lead to localized temperature increases in the reactor. [ABSTRACT FROM AUTHOR]

Highlights • Joint energy and reserve market increases energy storage profits. • Revenue collected by energy storage in reserve market is lower than in energy market. • Storage siting and sizing and its profitability depend on transmission line limits. Abstract Grid-scale energy storage units are regarded as an enabler of the renewable-dominant power systems. Currently available energy storage technologies are ubiquitous, but not equally suitable for providing different grid support services. As part of their investment process, merchant energy storage investors need to ensure that their energy storage investments are well aligned with unique grid support needs of each power system and that the storage characteristics are suitable for the simultaneous provision of multiple services. This paper presents a model to optimize merchant investments in energy storage units that can compete in the joint energy and reserve market. The proposed model uses the bilevel programming framework to maximize the expected lifetime profit and to ensure a desirable rate-of-return for the merchant energy storage investor, while endogenously considering market clearing decisions over a set of characteristic days. The bilevel model is first converted into a single-level equivalent using the Karush-Kuhn-Tucker-based approach and then linearized to obtain a mixed-integer linear program. The resulting program is solved using the Benders' decomposition approach and tested on the 8-zone Independent System Operator New England test system. The case study provides numerical insights that are discussed from viewpoints of the merchant energy storage owner, the system operator, and the regulator. [ABSTRACT FROM AUTHOR]

Highlights • An asynchronous production line modeling based on finite state machine is formulated. • The problem of maximizing production rates under power constraints is considered. • Provide a novel framework to manage production lines during demand response intervals. • A constrained local search heuristic is developed to find near-optimal schedules. • Simulation results show considerable improvement in production rates. Abstract Energy efficiency in factories is a new paradigm arising with Demand Response (DR) programs that enables energy providers to ask their clients to reduce their power consumption for a given time. In this paper, we consider demand side management of an industrial customer who owns asynchronous production line systems. Our aim is to help the customer achieve a good trade-off between production rates and power consumption during DR events. To attain this objective, we develop a framework named DR-Mgmt to schedule activities of machines on production lines so that the number of simultaneously working machines is maximized while satisfying DR constraints. Our framework first models activities of a production line using a new approach based on temporal deterministic finite station machine concept, where each state represents machine status (working/idle) and transitions capture temporal changes. Then, the problem of finding an optimal schedule from all feasible schedules is handled by selecting the optimal set of state transitions. We adapt the well-known local search heuristic to find near-optimal transitions. Numerical results show a significant benefit of our approach on production rates during DR intervals. Compared to other approaches, the proposed framework performs best and improves production rates up to 70% in some cases with higher total power consumption. We also validate our work by a real case study. [ABSTRACT FROM AUTHOR]

Highlights • Simulations of large scale automotive thermoelectric generators have been performed. • The methodology of the numerical model has been validated experimentally. • Thermal and electrical combinations of thermoelectric modules have been analyzed. • There is an optimum number of thermoelectric modules beyond which power decreases. • An approach for the mixed configuration that improves recovery energy is proposed. Abstract The need to reduce both energy consumption and greenhouse gas emissions has boosted the interest in using thermoelectric generators (TEGs) as waste heat energy harvesters. High-power TEGs are usually formed by an array of commercial thermoelectric modules (TEMs). Recent studies have analyzed the effects of using different types of electrical connections between TEMs in TEGs to produce electric power, but the effects of using different thermal configurations between TEMs have not been fully examined. Here, both electrical and thermal effects have been investigated using a numerical model developed with GT-SUITE software, which has been validated with laboratory data. TEGs with a number of TEMs between 1 and 100 distributed in different patterns along the exhaust pipe have been simulated under three engine regimes. For a given TEM geometrical pattern and engine regime, results prove the existence of an optimum number of TEMs, beyond which the total extracted power decreases. A mixed spatial distribution of TEMs generates more power than either the pure series or the pure parallel topologies. Finally, a methodology is proposed to choose an appropriate pattern of TEMs for a TEG installed in a system with variable regimes. This method is applied to a mid-size automotive diesel engine. [ABSTRACT FROM AUTHOR]

Highlights • A solid mechanics model combined with fully coupled flow-heat-mass-current transport. • Simulations based on and validated by the newest experimental data. • Effects of Ni content and oxidation state on stress and failure probability revealed. • Importance of reducing temperature gradient for the increased lifetime illustrated. Abstract Damage by mismatch of thermal expansion coefficients and temperature gradient is a major factor limiting the long-term stability of solid oxide fuel cell (SOFC). Numerical simulations are performed to provide in-depth information about the mechanical stress, mechanical failure probability and creep strain rate of planar SOFC. The dependences of the mechanical performance of SOFC on the Ni content and its oxidation state as well as the temperature (T) are revealed. Based on a realistic T -profile obtained by multi-physics simulation of a SOFC stack model, it is shown that the maximum creep strain rate of the operating stack is 40% higher than that of an isothermal stack with the same average T. A T -distribution deduced from a multi-physics fully coupled model is essential for a reliable prediction of the creep rate and the corresponding lifetime of an operating stack. [ABSTRACT FROM AUTHOR]

Hybrid design combinations of sensible and latent heat thermal energy storage (TES) leverage the advantages and reduce the disadvantages of both types. Thus, the range of application of said individual storage types is extended and crucial retrofit opportunities are enabled. Such hybrid TES concept consisting of a Ruths steam storage (RSS) and a surrounding layer of storage containers filled with an eutectic mixture of sodium nitrate (NaNO 3) and lithium nitrate (LiNO 3) as phase change material (PCM) was for the first time realized and investigated during operation in a steel production plant. In this work, the hybrid TES prototype is characterized with the help of detailed modelling and real measurement results. Uncertain model parameters are identified via parameter optimization and the numerical models show satisfactory validation results. Additional 30% of thermal energy could be stored in the PCM containers retrofitted to the lab-scale RSS. Charging/discharging times and specific thermal power of the PCM containers were roughly measured as 8 h and 12 h and 560 kW m − 3 / − 802 kW m − 3 , respectively, in the typical operation region. A sensitivity analysis of the performance indicators reveals potential but also engineering challenges for following generations of the hybrid TES concept. Compared to the achieved experimental results, charging/discharging power could be increased by up to 10 and 5 times, respectively, in the future by adequate measures to increase heat transfer between both storage types. [Display omitted] • First-of-a-kind hybrid steam/latent thermal energy storage prototype for retrofit. • Storage capacity is increased by 60 MJ (30%) without interfering with infrastructure. • Latent heat storage charging/discharging power was measured at 560/802 kWm-3. • Sensitivity analysis reveals potential to improve LHTES power by up to 10 times. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • The real-time simulation framework for active distribution networks was built. • A multirate simulation method was proposed with high-accuracy and stability. • The detailed hardware design of the real-time simulator was presented. Abstract Real-time simulation of large-scale active distribution networks exhibiting a wide range of time-scales puts forward higher requirements for simulation accuracy and efficiency. This paper presents an extendable method and design for the real-time simulation of active distribution networks utilising high-performance hardware field programmable gate arrays. In the aspect of numerical algorithm, a high-accuracy and stable multirate simulation algorithm is proposed. The entire active distribution network is decoupled into different subsystems by their inherent time-scales and distinct time steps are used to solve the subsystems. Then root-matching method is adopted to form the exponential difference equations that represent the behaviours of the electric distribution network being modelled, which eliminates the truncation errors and thus provides a highly accurate time-domain solution. To handle the interface between the subsystems, a multirate interfacing method is proposed. The hardware design of the multirate interfaces is presented as well. With the multirate algorithm, a fully functional extendable real-time simulator based on field programmable gate arrays is designed and implemented. Two modified IEEE 33-node systems with photovoltaics and energy storage are simulated on the 4-field-programmable-gate-arrays-based real-time simulator. Simulation results are compared with the commercial simulation tool PSCAD/EMTDC to validate the correctness and effectiveness of the proposed method and design. [ABSTRACT FROM AUTHOR]

Highlights • Performance and efficiency of all-vanadium redox flow batteries were studied. • Relationship between ion concentration and parameters in the system was analyzed. • Steady state and transient responses established an optimal operating strategy. • An empirical equation is suggested to maximize the energy efficiency of the systems. Abstract The parametric study for an all-vanadium redox flow battery system was examined to determine the optimal operating strategy. As dimensionless parameters, the stoichiometric number and state of charge were used to apply the strategy to all scales of the flow battery system. In this study, we developed a transient model for this system, which is supported by experimental data, to analyze effect of parameters on the ion concentration and determine its optimal operating conditions. First, the performance of the flow battery system was analyzed in steady-state conditions to examine the changes of the ion concentration depending on different flow rates, current densities, and sizes of active area. As flow rate increases, the energy efficiency slightly increases, because faster flow rates can deliver more vanadium ions from the reservoir. The energy efficiency decreases according to current density, because large current results in large amount of ohmic loss of membrane. When the size of active area increases, the energy efficiencies remain constant, however, the cycle time decreases. Next, the transient response for the system was analyzed by changing the stoichiometric number and current density during the charge and discharge processes. Variation of the system’s energy efficiency was studied with changes in the stoichiometric number and state of charge as the current density was varied from 20 to 100 mA/cm2. Increasing the flow rate at the beginning of the charge–discharge process is more efficient in the low current density region. At a current density of 100 mA/cm2, however, it is better to increase the flow rate after the state of charge reaches 50%. Lastly, an operating strategy is suggested that involves controlling the mass flow rate of the electrolyte during the charge–discharge process. The operating strategy is presented as an empirical equation defined by the stoichiometric number and state of charge. Notably, this equation can contribute to improving the performance of all scales of the flow battery system by simply changing the electrolyte flow rate at right time. [ABSTRACT FROM AUTHOR]

Highlights • A numerical model has been developed to simulate Oxy-Methane combustion. • Experiments have been conducted to validate the developed numerical model. • Different combustion mechanisms and radiation models have been tested. • The increase of CO 2 contents in the oxidizer increases the CO emission. • Combustion at an equivalence ratio of 0.98 was found to give least CO emission. Abstract There is a renewed interest in oxy-fuel combustion of natural gas for reduction of greenhouse gas emissions. This has necessitated various experimental and numerical studies of oxy-fuel combustion. In the numerical combustion study, the radiation model and combustion chemistry are critical for accurate numerical predictions of oxy-fuel combustion characteristics. In this study, three global reaction mechanisms: Westbrook-Dryer (3 equations), Jones-Lindstedt (5 equations) and Jones-Lindstedt (7 equations) for oxy-methane combustion were combined with different weighted sum of gray gas radiation models (WSGGM) available in the literature to determine the most accurate combination for oxy-methane combustion modeling and simulation. Experiments were conducted in a non-premixed swirl stabilized model gas turbine combustor at a firing rate of 4 MW/m3-bar while varying the percentage of CO 2 in the oxidizer (O 2 /CO 2) mixture. Numerical model developed using ANSYS FLUENT 17 code was validated against the experimental results. The combinations of Jones-Lindstedt (5 equations) reaction mechanism and WSGGM model proposed by Bordbar gave the closest approximation of the flame temperature with an average deviation of 5.52%. The model combination also predicted the flame attachment to the fuel nozzle and flame lift-off at a high CO 2 percentage in the oxidizer mixture. The results of the parametric study on the effect of CO 2 percentage in the oxidizer mixture, combustor energy level and equivalence ratio on the combustion characteristics and CO emissions were also reported. The CO emissions monotonically increases with increasing percentage of CO 2 in the oxidizer due to decreased residence time and the reduction in the flame temperature. While the CO emission increases with the energy level in the combustor up to 3.5 MW/m3 and decreases thereafter. The optimum equivalence ratio for minimum CO emission is 0.98 with approximately 2 PPM at 40% CO 2 in the oxidizer. [ABSTRACT FROM AUTHOR]

Highlights • A scalable distributed formal analysis (DFA) is devised for stability analysis of networked microgrids under disturbances. • A distributed quasi-diagonalized Geršgorin (DQG) theory is developed to identify systems’ stability margins. • A microgrid-oriented decomposition approach is established to decouple networked microgrids. • A novel framework is designed to effectively implement DQG-based DFA in networked microgrids. Abstract A scalable distributed formal analysis (DFA) via reachable set computation is presented to efficiently evaluate the stability of networked microgrids under disturbances induced by distributed energy resources (DERs). With mathematical rigor, DFA can efficiently compute the boundaries of all possible dynamics in a distributed way, which are unattainable via traditional time-domain simulations or direct methods. A distributed quasi-diagonalized Geršgorin (DQG) theory is then combined with DFA to identify systems’ stability margins. A microgrid-oriented decomposition approach is established to decouple a networked microgrid system and enable calculations of DFA and DQG while also preserving the privacy of each subsystem. Numerical tests on a networked microgrid system validate that DFA and DQG facilitate the efficient calculation and analysis of networked microgrids’ stability. [ABSTRACT FROM AUTHOR]

This paper studies the energy trading among flexible demand response aggregators (DRAs) and a distribution company (Disco) with self-owned generators. Instead of the conventional non-cooperative game based approach, the trading problem is formulated as a bargaining based cooperative model, where Disco and DRAs collaboratively decide the amounts of energy trade and the associated payments. This cooperative interaction can be beneficial to both Disco and DRAs, by reducing the aggregated peak demand and increasing the potential cost savings. The increased benefits from cooperation are fairly allocated among these participants, based on the Nash bargaining theory. Compared with the non-cooperative game based approach, the proposed bargaining cooperative model can further improve the benefits of Disco and DRAs. Moreover, the bargaining outcome can maximize the social welfare of the system. Considering the privacy and autonomy issues of participants, we utilize a decentralized solution to solve the bargaining problem, with minimum information exchange. Numerical studies demonstrate the effectiveness of the bargaining -based cooperative framework, and also show the improvement of benefits of the system. [ABSTRACT FROM AUTHOR]

This paper presents a novel computing method of optical efficiency fitting formulas and its applications for parabolic trough solar collectors, by combining the Monte Carlo ray-tracing methodology with the population-based particle swarm optimization algorithm. The expressions of the optical efficiency fitting formulas are deduced by means of analyzing the Monte Carlo ray-tracing data samples with a variable reduction technique, while the fitting formula coefficients are obtained using the particle swarm optimization algorithm. The computing time of the annual optical efficiency reduces to less than 10 −7  s, from about a day as previously calculated by a once powerful Monte Carlo ray-tracing model. Thus, it makes the once time-consuming long-time average optical efficiency calculations or corresponding population-based optimizations much more feasible and efficient. A dynamic particle swarm size factor is also proposed to improve the particle swarm optimization performance, which reduces nearly 90% of the particle swarm optimization computing time. Numerical results calculated by the Monte Carlo ray-tracing model and the obtained optical efficiency fitting formulas were compared with the corresponding reference data. Good agreements were obtained, proving that the computing method and model are reliable. The obtained optical efficiency fitting formula of parabolic trough solar collectors is then applied successfully to efficiently study the characteristics of long-time average optical efficiencies under different geometrical configurations, geographical locations, tracking models and corresponding optical or geometrical optimizations. This proposed novel method offers a useful option of high potential for further applications on efficient optical efficiency related analyses and corresponding population-based optimizations for parabolic trough solar collectors. [ABSTRACT FROM AUTHOR]

The scale-down trend increases the chips’ density and the high power handling capability generates unnecessary heat which can disrupt the reliability of the electronic devices. Therefore, various types of cooling solution have been proposed to enhance heat dissipation from the electronic devices. One of the solution is using inexpensive straight-channel heat sink. However, the presence of large temperature gradient between the upstream and downstream in the straight-channel can shorten the life span of the device and subsequently reduce the reliability. In this study, a novel segmented micro-channel is introduced to improve the thermal performance of the straight-channel heat sink. Computational fluid dynamic analysis are performed to investigate the performance of the micro-channel heat sink. The bottom of the heat sink is subjected to a constant heat flux condition and water is used as a coolant. Following that, Taguchi-grey method is applied to optimize the design of the segmented micro-channel. The effect of fin width, fin length, fin transverse distance, number of segments, channel width and mass flow rate on the specific performance, variation of temperature and pressure drop are investigated. The results indicate that a three segments of segmented micro-channel, fin width-1 mm, fin length-2 mm, fin transverse distance-5 mm and channel width-1 mm have successfully enhance the heat transfer performance with minimum pressure drop. It is also found that the optimized micro-channel heat sink is able to cool the chip with heat flux of 800 W to 56.6 °C and pumping power of 0.13 W using 15 gs −1 of water. [ABSTRACT FROM AUTHOR]

Self-sustained thermoacoustic oscillations resulting from a dynamic coupling between unsteady heat release and flow perturbations are detrimental to engine systems such as boilers, land-based gas turbines and furnaces. In this work, mitigating premixed flame-sustained thermoacoustic oscillations in a combustor is studied by actively passive control of a Helmholtz resonator with an oscillating volume. For this, a numerical model of a thermoacoustic combustor with a Helmholtz resonator attached is developed. As a feedback control technique is implemented on the combustion system to optimize the resonator’s damping effect, combustion-driven oscillations are successfully mitigated by approximately 30 dB. In addition, the dynamic response of the flame to oncoming acoustic disturbances is studied. This is achieved by numerically solving a nonlinear G -equation tracking flame front, as the disturbances with multiple frequencies are imposed. Flame transfer function is then derived via linearizing the flame model to obtain analytical results. Comparison is then made between the analytical and numerical results. It is shown from the transfer function analysis that the unsteady heat release linearly depends on the oncoming flow disturbance. However, the numerical results reveal that the flame response is nonlinear. Furthermore, the flame responds strongly to acoustic disturbances at a lower frequency and it behaves like a ‘low-pass’ filter. The flame speed is also found to play an important role in determining the unsteady heat release. Finally, to validate the effectiveness and performance of the feedback control, a Helmholtz resonator with a controllable oscillating diaphragm is implemented on a Y-shaped Rijke-type thermoacoustic system. Sound pressure level is shown to be reduced by more than 60 dB via tuning the gain and phase of the vibration of the loudspeaker diaphragm. The present investigation opens up an alternative applicable means to stabilize engine systems via minimizing thermoacoustic oscillations. [ABSTRACT FROM AUTHOR]

The proton exchange membrane (PEM) fuel cell is regarded as the best choice in the next power generation source in recent years due to its high fuel conversion efficiency, low noise, no emissions, and so on. The performance of the PEM fuel cell is dominated by the flow field design. The authors first numerically explore how the changed flow field design by the arrangement pattern of the protrusive gas diffusion layer (GDL) affects the cell performance for a full-scale serpentine channel. The best arrangement pattern of the protrusive GDL is then used to find the optimal combined factors by Taguchi design of experiments. The optimal energy conversion and conservation for this arrangement can upgrade the PEM fuel cell performance about 12% while decreasing pressure drop is approximately 35%. In addition, employing experimental data validates the calculation results of the flow channel design. Both the numerical and the experimental results can contribute to a better comprehension of the flow phenomenon that occurs in the energy process device. [ABSTRACT FROM AUTHOR]

In this study, we conducted a numerical investigation on the effect of injection timing of boot injection rate shape on the combustion and emission characteristics in a direct injection compression ignition (DICI) engine fueled with kerosene/diesel blending. Considering the complex surrogate in kerosene chemical mechanisms and the huge computational workload in multi-dimensional engine simulations, we employed a clustered dynamic adaptive chemistry method (CDAC) to accelerate the chemistry integration process. This study firstly specified the user-defined parameters in this CDAC method by sensitivity analysis in a HCCI and DICI engine with different user-defined parameter combinations. With these specified parameters, CDAC is then validated by comparing its predicted in-cylinder pressure with the full chemistry ones. It is found that the current CDAC method could reduce the computational time by more than 60% compared with the full chemistry CPU time. CDAC, subsequently, is used to conduct the numerical investigation on the injection timing of boot injection rate shapes. Four different boot injection rate shapes are simulated and compared with the normal rectangular injection. The effect injection timing of the boot injection rate on the engine performance and combustion/emission characteristic is then analyzed in detail. It is found that the change of start of injection (SOI) in boot injection has little influence of the ignition delay in the DICI engine fuelled with diesel and kerosene blending due to the high cetane number of diesel and better volatility of kerosene. In addition, with kerosene addition into the diesel combustion, it is observed that the CO emission could be reduced at all the varied SOI. [ABSTRACT FROM AUTHOR]

We analyse numerically an earlier experimental study that involved the formation of methane hydrates by the excess water method in a small reactor filled with a sandy porous medium, and seek to address questions about the type of the hydration reaction and the phase heterogeneity in the resulting hydrate-bearing sand. Using a fine discretization describing the reactor assembly, the experimental process is faithfully replicated numerically. The multi-stage process of hydrate formation is subdivided in 7 steps. The experimental data from the continuously-monitored pressure and temperature during each step are used for comparison against the numerical predictions, the identification of the dominant processes and the determination of the associated parameters through a history-matching process that minimizes deviations between observations and simulation results. The results of this first-ever study on this subject demonstrate unequivocally that the hydration reaction is a kinetic (as opposed to an equilibrium) process, and that the spatial distributions of the various phases (aqueous, gas and hydrate) at the end of the formation process are strongly heterogeneous. This has serious implications in simulation studies of hydrate dissociation that assume uniform initial phase saturation distributions. The history-matching process indicates that (a) the system behaviour is sensitive to some flow parameters (porosity and irreducible water saturation) only during the first water injection, (b) it is insensitive to the sand intrinsic permeability during all steps of the study, and (c) thermal processes dominate after the first water injection, yielding estimates of the thermal properties of the sand and of time-variable key parameters of the kinetic reaction. [ABSTRACT FROM AUTHOR]

Electrode compression is an effective approach to enhance the performance of vanadium redox flow battery (VRFB). Electrode compression can decrease the contact resistance between the electrode and the current collector. Porous electrode compression and deformation are not uniform because of the rib-channel patterns and part of the fibers pressed into the channel. The effects of the non-uniform deformation of a compressed electrode on the performance of a VRFB with flow field are not fully analyzed. In this study, a non-uniform model is proposed to consider the electrode shape deformation and non-uniformity of physical properties inside a compressed electrode. Morphological features of a deformed electrode including the intrusion ratio and local porosities under compression are investigated. Non-uniformly compressed electrodes with different local porosity and permeability are obtained. The predicted cell performance is initially validated using experiment data. The performance of VRFB with non-uniformly compressed electrode and serpentine flow field are investigated under different compression ratios (CRs). The non-uniform model can reasonably predict the charge/discharge and flow behavior. The velocity profile, local current density, and overpotential fluctuation along the rib and channel regions are obtained. The bulk velocity associated with species transport is improved because of the decreased cross-section areas of the flow channel inside the compressed electrode. An appropriate compression can improve the VRFB performance because of the enhanced species transport and increased reaction area when the intrusion part is considered. An optimized electrode CR of 55.7% is found to exhibit the maximum concentration uniformity as well as the minimum current density and overpotential. The present model can guide the VRFB design when the compressed electrode is considered. [ABSTRACT FROM AUTHOR]

This paper reports on the numerical simulation and experimental studies of carbonized woody briquettes gasification employing an updraft fixed bed gasifier. There is a strong industrial stake when it comes to the optimization of this gasification process, in terms of the flexibility of the type of biomass and its conversion efficiency. The influences of the gasification temperature and the equivalence ratio (ER) on the gaseous production and the tar yield were examined. In order to optimize the operating conditions of the biomass gasification process, a numerical model was developed using the COMMENT code (Combustion Mathematics and Energy Transport). This model is a two-dimensional computer model describing the biomass gasification process in an updraft gasifier using carbonized woody briquettes as fuel. The present study proved that ER significantly influenced the composition of gaseous species and its optimization is important to obtain a higher gasification rate. The particle size presented considerable effects on the temperature distribution within the gasifier and the syngas compositions produced during the gasification process as well. The numerical model presented was validated by the experimental results and it provided a promising way to simulate the gasification of solid fuel, which is considered to be a versatile and useful computational tool to optimize the biomass gasification process and to design fixed bed gasifiers. [ABSTRACT FROM AUTHOR]

Crude oil plays an important role in various production processes throughout the world. Changes in oil prices affect economic development, social stability and the residents in a country. Based on a full consideration of the fluctuations in oil prices and discovering the future dynamic trend of oil prices from historical trend features, a vector trend forecasting method that defines the vector trend over a specified length of time and predicts future price trends of crude oil based on the vector trend series of historical crude oil prices is proposed. The core idea behind vector trend forecasting method is to construct the vector trend by using the parameters of a fitting function within a specified interval. Based on the previous linear regression, a variety of non-linear morphological features were selected for numerical fitting, avoiding unity in the price trend and stochastic factors that are difficult to solve in forecast price trends. Combined with an econometric model composed of simultaneous equations, making full use of the characteristic information of the historical vector trend makes the definition of the trend more reasonable and the prediction more accurate. The empirical results show that the percentage error of the fitted real oil price in the vector trend is less than 4%. At the same time, it is found that the numerical fitting result using exponential and quadratic functions are better than that with general linear regression. The forecasting error of the trend is no more than 5%, which is lower than the traditional forecasting accuracy of econometrics and statistical learning models. This study can provide suggestions for oil market investors to understand trends in oil prices and for their investment decision-making, and provide reference for policy makers to stabilize economic markets and people’s life. [ABSTRACT FROM AUTHOR]

Ground-Source Heat Pump (GSHP) systems represent one of the most efficient renewable energy technologies. Their efficiency is highly influenced by the thermal properties of the ground, which are often measured in-situ using the Thermal Response Tests (TRTs). While three-dimensional mechanistic models offer significant advantages over analytical solutions for the numerical interpretation of TRTs, their computational cost represents a limiting factor. Moreover, most of the existing models do not include a comprehensive description of hydrological processes, which have proven to strongly influence the behavior of GSHP. Thus, in this study, we propose a computationally efficient pseudo-3D model for the numerical analysis and interpretation of TRTs. The numerical approach combines a one-dimensional description of the heat transport in the buried tubes of the exchanger with a two-dimensional description of the heat transfer and water flow in the surrounding subsurface soil, thus reducing the dimensionality of the problem and the computational cost. The modeling framework includes the widely used hydrological model, HYDRUS, which can simulate the movement of water, heat, and multiple solutes in variably-saturated porous media. First, the proposed model is validated against experimental data collected at two different experimental sites in Japan, with satisfactory results. Then, it is combined with the Morris method to carry out a sensitivity analysis of thermal properties. Finally, the model is exploited to investigate the influence of groundwater and lithologic heterogeneities on the thermal behavior of the GSHP. [ABSTRACT FROM AUTHOR]

In this paper, the desalination performance of a plant variant with the same size as the Manzanares pilot model was numerically investigated. A three-dimensional compressible flow and heat transfer model has been developed, describing the air cooling process along the chimney and the associated condensation. In this plant variant, instead of installing the turbine, water droplets were sprayed for evaporation at the bottom of the chimney, and thus airflow was subjected to humidification. Results show that with increased mass fraction of water in the air, the influence of the microclimate on the local environment will also increase. The evaporation of the droplets improves the relative humidity of the air within the chimney, and the condensation level can thus be greatly reduced. Moreover, the freshwater output increases with increasing amount of water sprayed, which is beneficial for the improvement of the desalination efficiency of the system. [ABSTRACT FROM AUTHOR]

• Numerical model of a cascade solid oxide fuel cell system is developed. • Effect of fuel regeneration rate on cascade system electrical efficiency is captured. • Numerical analysis of cascade system by varying operating parameters is conducted. • System electrical efficiency increases with increasing fuel regeneration rate. • Cascade system has not the highest efficiency at fuel regeneration rate of 100%. One of the most effective ways to improve the electrical efficiency of a solid oxide fuel cell system is to maximize the fuel utilization of the system. As a method to increase fuel utilization, the anode off-gas from the first stack is supplied to the second stack. Because low fuel concentrations in the first stack could highly reduce the performance of the second stack, a fuel regenerator is installed after the first stack to remove the water and increase the fuel concentration. In this study, a numerical model of a cascade solid oxide fuel cell system was developed using Aspen Plus®. To capture the effects of the fuel regeneration rate on the electrical efficiency of the cascade solid oxide fuel cell system, the models were simulated at various operating parameters such as the fuel utilization, steam-to-carbon ratio, external reforming ratio, and current density. As a result, the electrical efficiency of the system increased with increasing fuel regeneration rate. However, when the fuel regeneration rate becomes 100%, the electrical efficiency of the cascade system is not the highest efficiency because of the power consumption of the electric heat pump. [ABSTRACT FROM AUTHOR]

Due to its advantages of small size, wide adaptability and high reliability, thermoelectric power generation (TEG) technology is attracting more and more attention in the application prospects of distributed energy, waste heat recovering and clean electricity supply. However, the promotion of the TEG is hindered by its low energy conversion efficiency which has become the most urgent problem in the TEG system. In order to achieve higher efficiency, a novel cascaded thermoelectric generator system (CTEG) with three-stage thermoelectric generators and its dynamic models based on the energy conservation equation, unsteady heat conduction theory and fluid dynamics were proposed and built. Through experimental data and numerical results, the system dynamic performance and the key parameters which affect the characteristics of the TEG system were analyzed. The results show that the efficiency of the new cascaded TEG system is greatly improved by 21.56% compared with the system with single-stage TEG. Furthermore, this study puts forward guidance for system improvement, and it is encouraging that a more appropriate system configuration could be an important means to further increase the system efficiency. Moreover, this dynamic simulation model can be used in the system design and operating improvement. [ABSTRACT FROM AUTHOR]

This paper presents a numerical model used for analyzing heat propagation as a safety feature in a custom-made battery pack. The pack uses a novel technology consisting of an internal short circuit device implanted in a cell to trigger thermal runaway. The goal of the study is to investigate the importance of wrapping cylindrical battery cells (18650 type) in a thermally and electrically insulating mica sleeve, to fix the cells in a thermally conductive aluminum heat sink. By modeling the full-scale pack using a 2D model and coupling the thermal model with an electrochemical model, good agreement with a 3D model and experimental data was found (less than 6%). The 2D modeling approach also reduces the computation time considerably (from 11 h to 25 min) compared to using a 3D model. The results showed that the air trapped between the cell and the boreholes of the heat sink provides a good insulation which reduces the temperature of the adjacent cells during thermal runaway. At the same time, a highly conductive matrix dissipates the heat throughout its thermal mass, reducing the temperature even further. It was found that for designing a safe battery pack which mitigates thermal runaway propagation, a combination of small insulating layers wrapped around the cells, and a conductive heat sink is beneficial. [ABSTRACT FROM AUTHOR]

The penetration of renewable energy sources (RES) in power system is increasing around the world. However, the severe intermittency and variability characteristics of RES make the operating reserve become more and more important for the electric power system to maintain balance between supply and demand. Moreover, the flexible loads, especially for air conditioners (AC), are growing so rapidly that they account for an increasingly large share in power consumption. With the development of information and communication technologies (ICT), ACs can be monitored and controlled remotely to provide operating reserve and respond actively when needed by the electric power system operation. In this paper, a novel control strategy for the aggregation model of ACs based on the thermal model of the room is proposed. By resetting the temperature of each AC, the operation state is adjusted temporarily without affecting customers’ satisfaction. The operation characteristics of both individual AC and the aggregation model of ACs are analysed. Furthermore, several indexes are put forward to evaluate the operating reserve performance, including reserve capacity, response time, duration time and ramp rate. The effectiveness of the proposed control strategy is illustrated in the numerical studies. [ABSTRACT FROM AUTHOR]

It has been well recognized that both the performance and operation stability of proton exchange membrane fuel cells (PEMFCs) are closely associated with water transport and accumulation behaviors in the membrane electrode assembly. Therefore, an optimal water management is highly desired. Conventional serpentine flow field (CSFF) can effectively facilitate water removal and prevent water flooding. However, CSFF would cause a high pressure drop from the inlet to outlet, thus resulting in large parasitic power loss. In this study, a novel three-dimensional flow field (WSFF), patterned with waved serpentine flow channels, is designed and analyzed by combing the simulating method with experimental method. A three-dimensional, multi-phase, steady, isothermal, laminar simulation model is firstly established based on FLUENT PEM fuel cell module, and this model reveals that WSFF is overall better than CSFF in promoting oxygen transport though the diffusion layer and removing liquid water accumulated in microstructure. Its periodic waved structure introduces cyclical variation of local flow direction, local flow velocity and local pressure, thus leading to enhanced forced-convection. The superior performance of WSFF has also been experimentally verified, proving that WSFF not only enables a lower pressure drop over the entire current density range, but also improves the cell performance in comparison to CSFF at high current density region. Specifically, there is a 17.8% increment in the peak power density due to the use of WSFF. [ABSTRACT FROM AUTHOR]

Molten-salt packed-bed thermocline thermal energy storage (TES) is identified to be a cost-competitive TES type for concentrating solar power (CSP). The present study reveals the system-level cyclic thermal characteristics of the molten-salt packed-bed TES with typical configurations on two levels of investigation, based on a one-dimensional enthalpy-method dispersed-concentric (D-C) model. Firstly, a three-stage operation scheme is proposed to evaluate the thermal performance of the introduced partial charge cycles and the subsequent full charge cycles, under ideal operating conditions. The ‘partial charge effect’ of the packed-bed TES is identified by evaluating the variations in thermocline development and energy storage/release capacity. The results show that the introduced partial charge cycles can generally lead to a thermocline degradation, and then impact the energy store/release capacity in the subsequent full charge cycles. The configurations containing encapsulated PCMs are of greater resistance and stronger recoverability to the variation in energy storage/release capacity. Then the study is extended to investigate the thermal performance of a 100 MWe CSP plant integrated with a well-sized packed-bed TES system, over a 14-day practical operation based on variable energy collections. Deviations between the designed and practical energy store/release capacity of the systems are evaluated. The results indicate that of the sensible-heat and the single-layered latent-heat packed-bed TES present significant shortages in energy storage capacity during the operation, which can lead to energy collection discards. Overall, the obtained results present a new perspective to evaluate the availability of the packed-bed TES system for CSP plants. [ABSTRACT FROM AUTHOR]

This paper presents a time-spatial electric vehicle (EV) charging-power demand forecast model at fast-charging stations located in urban areas. Most previous studies have considered private charging locations and a fixed charging-start time to predict the EV charging-power demand. Few studies have considered predicting the EV charging-power demand in urban areas with time-spatial model analyses. The approaches used in previous studies also may not be applicable to predicting the EV charging-power demand in urban areas because of the complicated urban road network. To possibly forecast the actual EV charging-power demand in an urban area, real-time closed-circuit television (CCTV) data from an actual urban road network are considered. In this study, a road network inside the metropolitan area of Seoul, South Korea was used to formulate the EV charging-power demand model using two steps. First, the arrival rate of EVs at the charging stations located near road segments of the urban road network is determined by a Markov-chain traffic model and a teleportation approach. Then, the EV charging-power demand at the public fast-charging stations is determined using the information from the first step. Numerical examples for the EV charging-power demand during three time ranges (i.e., morning, afternoon, and evening) are presented to predict the charging-power demand profiles at the public fast-charging stations in urban areas. The proposed time-spatial model can also contribute to investment and operation plans for adaptive EV charging infrastructures with renewable resources and energy storage depending on the EV charging-power demand in urban areas. [ABSTRACT FROM AUTHOR]

This paper presents an integrated numerical framework to co-optimize EOR and CO 2 storage performance under uncertainty in the Farnsworth Unit (FWU) oil field in Ochiltree County, Texas. The framework includes a field-scale compositional reservoir multiphase flow model, an uncertainty quantification model and a neural network optimization process. The reservoir flow model has been constructed based on the field geophysical, geological, and engineering data. Equation of state parameters were tuned to achieve field measured fluid properties and subsequently used to predict the minimum miscible pressure (MMP). A history match of primary and secondary recovery processes was conducted to estimate the reservoir and multiphase flow parameters as the base case for analyzing the effect of recycling produced gas, infill drilling and water alternating gas (WAG) cycles on oil recovery and CO 2 storage. A multi-objective optimization model was defined for maximizing both oil recovery and CO 2 storage. The uncertainty quantification model comprising the Latin Hypercube sampling, Monte Carlo simulation, and sensitivity analysis, was used to study the effects of uncertain variables on the defined objective functions. Uncertain variables include bottom hole injection pressure, WAG cycle, injection and production group rates, and gas-oil ratio. The most significant variables were chosen as control variables to be used for the optimization process. A neural network optimization algorithm was utilized to optimize the objective function both with and without geological uncertainty. The vertical permeability anisotropy (Kv/Kh) was selected as one of the uncertain parameters in the optimization process. The simulation results were compared to a scenario baseline case that predicted CO 2 storage of 74%. The results showed an improved approach for optimizing oil recovery and CO 2 storage in the FWU. The optimization model predicted that about 94% of CO 2 would be stored and most importantly, that this increased storage could result in about 25% of incremental oil recovery. The sensitivity analysis reduced the number of control variables to decrease computational time. A risk aversion factor was used to represent results at various confidence levels to assist management in the decision-making process. The defined objective functions were shown to be a robust approach to co-optimize oil recovery and CO 2 storage. [ABSTRACT FROM AUTHOR]