Solar air heating devices have been employed in a wide range of industrial and home applications for solar energy conversion and recovery. It is a useful technique for increasing the rate of heat transfer by artificially creating repetitive roughness on the absorbing surface in the form of semicircular ribs. A thermo-hydraulic performance analysis for a fully developed turbulent flow through rib-roughened solar air heater (SAH) is presented in this article by employing computational fluid dynamics. Both 2-dimensional geometrical modeling and numerical solutions were performed in the finite volume package ANSYS FLUENT. The renormalization-group (RNG) k-ε turbulence model was used, as it is suitable for low Reynolds number (Re) turbulent flows. A thermo-hydraulic performance analysis of an SAH was carried out for a ranging Re, 3800−18,000 (6 sets); relative roughness pitch (RRP), 5−25 (12 sets); relative roughness height (RRH), 0.03−0.06 (3 sets); and heat flux, 1000 W/m2. The numerical... [more]

The Francis hydro-turbine is a typical nonlinear system with coupled hydraulic, mechanical, and electrical subsystems. It is difficult to understand the reasons for its operational failures, since the main cause of failures is due to the complex interaction of the three subsystems. This paper presents an improved dynamic model of the Francis hydro-turbine. This study involves the development of a nonlinear dynamic model of a hydraulic unit, given start-up and emergency processes, and the consideration of the effect of water hammer during transients. To accomplish the objectives set, existing models used to model hydroelectric units are analyzed and a mathematical model is proposed, which takes into account the dynamics during abrupt changes in the conditions. Based on these mathematical models, a computer model was developed, and numerical simulation was carried out with an assessment of the results obtained. The mathematical model built was verified on an experimental model. As a resu... [more]

By operating over a large bandwidth, the terahertz (THz) frequency band (0.3−3 THz) promises to deliver extremely high data rates. While the use of this band in cellular communications systems is not expected to happen within the next decade, various other use-cases such as wireless backhauling and point-to-point wireless access are on the immediate horizon. In this study, we develop an analytical propagation model for the case of ground-to-aircraft communications by explicitly accounting for THz-specific propagation phenomena including path loss, attenuation by different types of clouds, and atmospheric absorption at different altitudes. To this aim, we first exhaustively characterize the geometric, molecular, and structural properties of clouds for different weather conditions and Earth regions. Then, by applying the tools of stochastic geometry, we present the closed-form expression for received power at the aircraft. Our numerical results show that the type of weather forming diffe... [more]

Enhancing the accuracy of the battery state of charge (SOC) estimation is essential in developing more effective, dependable, and convenient electric vehicles. In this paper, a hybrid CNN and gated recurrent unit-long short-term memory (CNN-GRU-LSTM) approach, which is a recurrent neural network (RNN) based model with an explainable artificial intelligence (EAI) was used for the battery SOC estimation, where the cell parameters were explicitly synchronized to the SOC. The complexed link between the monitoring signals related to current, voltage, and temperature, and the battery SOC, was established using the deep learning (DL) technique. A LG 18650HG2 li-ion battery dataset was used for training the model so that the battery was subjected to a dynamic process. Moreover, the data recorded at ambient temperatures of −10 °C, 0 °C, 10 °C, and 25 °C are fed into the method during training. The trained model was subsequently used to estimate the SOC instantaneously on the testing datasets. A... [more]

This article presents selected methods of limiting the bearing voltages of synchronous machines with permanent magnets supplied from power electronic converters. The authors analyzed methods based on the use of various shielding windings placed in slot wedges and mounted in the stator end-winding region. The values of the parasitic capacitances of the machine, on which the levels of bearing voltages depend, were determined using the finite element method. Three-dimensional simulation models were used for the calculations. The analysis of the influence of the shielding windings on the bearing voltage waveforms was conducted on the basis of circuit models with two- and three-level converters. The obtained calculation results indicate a high potential in limiting bearing voltages.

The need for a verification method for aggregation techniques for passive electrical systems is necessary as power systems increase in complexity. Model reduction is crucial to increase the number of simulations necessary to ensure a stable and reliable design of power systems. This paper presents a novel modal domain-based technique to identify the best aggregation technique for a given system and to indicate the validity of the aggregation. This is done by benchmarking different aggregation techniques and using the dominant contribution factor ratio as a validity parameter. The different aggregation techniques are compared via time-domain simulations against the full detailed model. It is found that (1) the power loss aggregation technique is the most precise when it weighs the equivalent impedances of the parallel feeders, (2) unequal current generation does not impact the aggregation accuracy, (3) individual string aggregation provides the best results for dynamic simulations, and... [more]

With the coming of the 2022 Beijing Winter Olympic Games, China’s artificial ice rink construction will be in rapid development. A parametric evaluation of the cooling pipe in a direct evaporation rink was performed by numerical simulation. The results showed that the influence of the temperature of the antifreeze pipe on the ice surface temperature can be ignored. The evaporation temperature of the working medium in the cooling pipe is between −32 °C and −22.4 °C to ensure the ice surface temperature is between −5 °C and −3 °C. With the increase in the cooling pipe spacing, the required evaporation temperature of the working medium in the cooling pipe and the uniformity of the ice surface temperature decreased. The required evaporation temperature of the working medium in the cooling pipe decreases by 1.2−1.5 °C for every 10 mm increment of spacing. With the increase in the cooling pipe diameter, the required evaporation temperature of the working medium in the cooling pipe and the un... [more]

Scarcity has made fresh water too economically and socially too valuable to be used by the processing industry without restriction. Wet evaporative cooling cycles offer competitive advantages in terms of CoP compared to other cooling cycles with relatively low cost but requiring extensive quantities of water. Dry cooling, on the other hand, requires large heat-transfer areas, in addition to high power requirements. In this study, a hybrid cycle is proposed for high-end cooling loads of 215 MW. The proposed cycle combines the benefits of phase change to make dry cycles competitive. Furthermore, the proposed cycle also diminishes the extensive use of various chemicals used in wet cooling cycles. The applicable dry bulb temperature range is 25−50 °C. Variations in cooling fluid cold temperature due to ambient conditions are curtailed to a maximum of 2 °C by the proposed cycle. A technoeconomic comparison of the proposed solution to wet evaporative cooling is presented, and the effects are... [more]

Hydroelectric power plants (HEPPs) are renewable energy power plants with the highest installed power in the world. The control systems are responsible for stopping the relevant unit safely in case of any malfunction while ensuring the desired operating point. Conventional control systems detect anomalies at certain limits or predefined threshold values by evaluating analog signals regardless of differences caused by operating conditions. In this study, using real data from a large hydro unit (>150 MW), a normal behavior model of a hydraulic governor’s oil circulation in an operational HEPP is created using several machine learning methods and historical data obtained from the HEPP’s SCADA system. Model outputs resulted in up to 96.45% success of prediction with less than 1% absolute deviation from actual measurements and an R2 score of 0.985 with the random forest regression method. This novel approach makes the model outputs far more appropriate to use as an active threshold value ch... [more]

Online monitoring of Partial Discharges (PDs) in rotating electrical machines is an useful tool for machine prognosis, as it presents reduced costs compared to intrusive inspections and is associated with relevant problems. Although this monitoring method has been developed for almost 50 years, the recent advancements in processes automation and signal processing techniques allow improvements that are still being studied by academic and industrial researchers. To analyze the current context of PDs monitoring, this article presents a literature review based on concepts of PDs in rotating machines, data acquisition techniques, state-of-the art commercial equipment, and recent methodologies for detection and pattern recognition of PDs. The challenges identified in the literature that motivate the development of more reliable and robust PD monitoring systems are presented and discussed.

A low-performance fuel cell significantly hinders the application and commercialization of fuel cell technology. Computational fluid dynamics modeling could predict and evaluate the performance of a proton exchange membrane fuel cell (PEMFC) with less time consumption and cost-effectiveness. PEMFC performance is influenced by the distribution of reactants, water, heat, and current density. An uneven distribution of reactants leads to the localization of current density that produces heat and water, which are the by-products of the reaction to be concentrated at the location. The simplification of model geometry can affect performance prediction. Numerical investigations are commonly validated with experimental results to validate the method’s accuracy. Poor prediction of PEMFC results has not been discussed. Thus, this study aims to predict the effect of geometry modeling on fuel cell performance. Two contrasting 3D model dimensions, particularly single-channel and small-scale seven-ch... [more]

In this paper, a new carrier phase-shift (CPS) modulation method based on switching the displacement angle (SDA) is proposed to compromise the harmonic content of the output voltage and the circulating current. It can be used in medium- and low-voltage applications where the AC-side voltage and DC-side current of the modular multilevel converter (MMC) are required to have low harmonic content simultaneously. In this proposed SDA-based CPS modulation, the carrier displacement angle of the MMC with N submodules in each arm is periodically switched between the values of 0 and π/N degrees, so that the harmonic content of the output voltage and the harmonic content of the circulating current will not be in extreme conditions, which occurs when the displacement angle is set to 0 or π/N degrees. The effectiveness of this method has been verified by simulation and experimental results.

Magnetic properties of hard magnets are currently attracting a great deal of attention. In the paper, the modified Harrison model was used to describe the saturating hysteresis loops of three praseodymium−dysprosium ribbons that differed in their chemical composition and processing conditions. Microstructural studies (TEM and diffraction patterns) were performed for the ribbons under consideration. The Harrison model incorporates a number of physically tangible concepts such as the anhysteretic curve, bifurcations, and bi-stability. The modification of the original approach consisted of adding an additional degree of freedom in the modeling by freeing the restraints present in the original version, in which both coercivity and remanence are functions of temperature only.

The solar cavity heat absorber is the core component of a solar thermal power generation system; its structure and installation position directly affect the efficiency of the heat absorber. To study the influence of these factors on the performance of the heat absorber, in this paper, a numerical simulation of dish solar collector optics is constructed based on the Monte Carlo method, and the distribution characteristics of heat flux density under different heat absorber structures and installation positions are analyzed. The results show that the heat flux density on the inner wall surface of the absorber has a linear relationship with the solar radiation intensity; under the same cavity depth, the energy received by the cylindrical, dome, and inverted cone absorbers is easier to deposit on the top. The heat flux density on the top surface of the inner cavity presents an annular distribution law. As the position of the heat absorber moves away from the dish solar collector surface, th... [more]

Based on the existing research results, a theoretical fracture model of strata under the compound impact of static and harmonic dynamic load is improved, and the fracture characteristic parameters (stress intensity factor, T-stress, and fracture initiation angle) under the two far-field stress are determined according to the crack dip angle. Additionally, the effects of harmonic dynamic load on the distribution of the stress field and the fracture characteristic (the crack initiation angle, the fracture degree, the number of fracture units, and the fracture area) are further calculated and discussed by theoretical model solution, extended finite element simulation, and the secondary development of the simulation module, respectively. The research results show that the far-field stress, stress intensity factor, and T-stress vary in harmonic form with time under the compound impact of static and harmonic dynamic loads. The frequency of dynamic load affects the number of reciprocal fluctu... [more]

Deep-water gas well testing is a key technology for obtaining reservoir production and physical property parameters. However, gas hydrates could easily form and cause blockage in the low-temperature and high-pressure environment on the seafloor. Therefore, it is extremely important to inhibit hydrate growth in deep-water operations. Ionic liquid is a type of hydrate inhibitor with both thermodynamic and kinetic effects. However, its intrinsic inhibiting mechanism is still unclear. By using molecular dynamics simulation, the growth process of methane hydrate in the 1-ethyl-3-methylimidazole chloride (EMIM-Cl)-containing system at the pressure of 15 MPa and temperature of 273.15 K was studied. The system energy and angular order parameters (AOP) were extracted as the evaluation indicators. It was found that the time for the complete growth of methane hydrate in the EMIM-Cl-containing system was about 10 ns, longer than that in the pure water, indicating that EMIM-Cl showed an obvious inh... [more]

Microstructured optical fibres (MOFs) are fibres that contain an array of air holes that runs through the whole fibre length. The hole pattern of these fibres can be customized to manufacture optical devices for different applications ranging from high-power energy transmission equipment to telecommunications and optical sensors. During the drawing process, the size of the preform is greatly scaled down and the original hole pattern result might be modified, potentially leading to unwanted optical effects. Because only a few parameters can be controlled during the fabrication process, mathematical models that can accurately describe the fibre drawing process are highly desirable, being powerful predictive tools that are significantly cheaper than costly experiments. In this manuscript, we derive a new asymptotic energy equation for the drawing process of a single annular capillary and couple it with existing asymptotic mass, momentum, and evolution equations. The whole asymptotic model... [more]

This paper proposes a novel T-type 7-level single-phase DC-AC inverter having a single input power source, self-balancing, and voltage gain of 3 along with low total harmonic distortion (THD). Since the structure of the proposed 7-level DC-AC inverter is symmetrical, the interchangeability of mass production can be easily achieved. In addition, because only one switch works for all time, the switch has quite low switching loss and voltage stress as well as the control being very easy. Furthermore, not only the proposed 7-level DC-AC inverter is analyzed in detail by the operating principle, but also the mathematical model for the adopted level-shift sinusoidal pulse width modulation (LS-SPWM) for this multilevel DC-AC inverter is successfully developed by using the well-known state averaging technique widely employed in the DC-DC converter. As a result, the required proportional-integral (PI) controller, used in the closed loop, can be designed systematically and easily. Eventually, th... [more]

The large-scale numerical simulation of complex flows has been an important research area in scientific and engineering computing. The lattice Boltzmann method (LBM) as a mesoscopic method for solving flow field problems has become a relatively new research direction in computational fluid dynamics. The multi-layer grid-refinement strategy deals with different-level of computing complexity through multi-scale grids, which can be used to solve the complex flow field of the non-uniform grid LBM without destroying the parallelism of the standard LBM. It also avoids the inefficiencies and waste of computational resources associated with standard LBMs using uniform and homogeneous Cartesian grids. This paper proposed a multi-layer grid-refinement strategy for LBM and implemented the corresponding parallel algorithm with load balancing. Taking a parallel scheme for two-dimensional non-uniform meshes as an example, this method presented the implementation details of the proposed parallel algo... [more]

Distribution network planners are facing a strong shift in the way they plan and analyze the network. With their intermittent nature, the introduction of distributed energy resources (DER) calls for yearly or at least seasonal analysis, which is in contrast to the current practice of analyzing only the highest demand point of the year. It requires not only a large number of simulations but long-term simulations as well. These simulations require significant computational and human resources that not all utilities have available. This article proposes a nonlinear clustering methodology to find a handful of representative medium voltage (MV) distribution feeders for DER penetration studies. It is shown that the proposed methodology is capable of uncovering nonlinear relations between features, resulting in more consistent clusters. Obtained results are compared to the most common linear clustering algorithms.

In this paper, we present an approach for multi-level parallel-in-time (PinT) electromagnetic transient (EMT) simulation. We evaluate the approach in the context of power electronics system-level simulation. While PinT approaches to power electronics simulations based on two-level algorithms have been thoroughly explored in the past, multi-level PinT approaches have not yet been investigated. We use the multigrid-reduction-in-time (MGRIT) method to parallelize a dedicated EMT simulation tool which is capable of switching between different converter models as it operates. The presented approach yields a time-parallel speed-up of up to 10 times compared to the sequential-in-time implementation. We also show that special care has to be taken to synchronize the time grids with the electronic components’ switching periods, indicating that further research into the usage of different models from adequate model hierarchies is necessary.

The accurate prediction of building heat demand plays the critical role in refined management of heating, which is the basis for on-demand heating operation. This paper proposed a prediction model framework for building heat demand based on reinforcement learning. The environment, reward function and agent of the model were established, and experiments were carried out to verify the effectiveness and advancement of the model. Through the building heat demand prediction, the model proposed in this study can dynamically control the indoor temperature within the acceptable interval (19−23 °C). Moreover, the experimental results showed that after the model reached the primary, intermediate and advanced targets in training, the proportion of time that the indoor temperature can be controlled within the target interval (20.5−21.5 °C) was over 35%, 55% and 70%, respectively. In addition to maintaining indoor temperature, the model proposed in this study also achieved on-demand heating operati... [more]

For the various climatic zones of India, machine learning (ML) models are created in the current work to forecast monthly-average diffuse solar radiation (DSR). The long-term solar radiation data are taken from Indian Meteorological Department (IMD), Pune, provided for 21 cities that span all of India’s climatic zones. The diffusion coefficient and diffuse fraction are the two groups of ML models with dual input parameters (sunshine ratio and clearness index) that are built and compared (each category has seven models). To create ML models, two well-known ML techniques, random forest (RF) and k-nearest neighbours (KNN), are used. The proposed ML models are compared with well-known models that are found in the literature. The ML models are ranked according to their overall and within predictive power using the Global Performance Indicator (GPI). It is discovered that KNN models generally outperform RF models. The results reveal that in diffusion coefficient models perform well than diff... [more]

This paper presents the theoretical analysis, experimental results and generalized structure for N modules of an isolated dc−dc SEPIC converter. The structure comes from the integration of N conventional SEPIC converters based on the input-series and output-parallel connection. The main advantages provided by the proposed structure are reduced voltage stress across the semiconductors and division of the current stress in the output diodes. The proposed converter is presented in a generalized approach, varying the voltage stress across the semiconductors according to the number of modules used. As the converter uses more than one switch, the commands can be either equal or phase-shifted by 360∘/N degrees. When operating with phase-shift modulation, a multilevel converter is obtained, which brings another advantage of the structure, since there is a reduction in the volume of the input inductors (Li1 and Li2) and the output capacitor (Co). In this paper, the steady-state analysis, a dyna... [more]

The optimized concentration of SF6 gas is the key to maintaining a good insulation performance by GIS equipment. The precise measurements of the SF6 concentration and decomposition byproducts could be used to indicate the remaining GIS insulation level during long-term operations. In this paper, a finite-element simulation model was created to investigate the SF6 gas decomposition and diffusion dynamics. A theoretical analysis and simulation of the overheating fault, i.e., the contact between the GIS disconnect switches, were carried out, followed by an estimation of the SF6 decomposition and diffusion characteristics caused by the local heating faults, based on the calculated flow velocity field and temperature field.