This paper provides computer analysis and experiential investigation of the permanent magnet machines with neodymium and ferrite permanent magnets to discuss the feasibility of utilizing induction machines-oriented equipment for PM machine production. For this purpose, the machines are obtained by replacing the squirrel-cage rotor of the induction motor with the flux-focusing (tangential) and surface-mounted (radial) permanent magnet rotors. Electromechanical parameters of the machines as electromagnetic torque and output power are discussed and compared. The temperatures of the neodymium and ferrite magnets are also calculated at rated current, and short circuit scenarios and the performance of two different cooling systems in minimizing the temperature effect on the machines are investigated. Furthermore, the demagnetization of permanent magnets at various load conditions is also studied. Finally, the results of the computer modeling are validated by the physical prototypes of the ma... [more]

The aim of the article is to present a new idea of limiting the bearing voltage in electric machines with permanent magnets through the use of a shielding winding placed in stator slot wedges. The first part of the article is dedicated to the mechanisms of generating bearing voltages when the machine is supplied from the mains and from a power electronic converter. Additionally, some methods of counteracting these phenomena were described. Next, multivariant simulation tests were carried out based on the two-dimensional field model of a synchronous machine with permanent magnets. The tests were run in order to determine the internal capacitances of the machine, on which the level of bearing voltages depends. Based on these results, the optimal variant of the design solution ensuring the limitation of the bearing voltage to a safe level was selected. Using the model of a two-level converter and based on the equivalent diagram of the internal capacitances of the machine, the influence of... [more]

The internal heat transfer performance and flow structures of a sweeping jet and film composite cooling on a flat plate were numerically studied. Sweeping jet and film composite cooling consists of a fluidic oscillator and 20 cylindrical film holes; the direct jet is formed by removing the feedback from the fluidic oscillator, which is different from the traditional cylindrical nozzle. Four different mass flow rates of coolant were considered, and the inclination angle of the film hole was 30°. The Conjugate Heat Transfer method (CHT) and Unsteady Reynolds Averaged Navier Stokes equation (URANS) were employed. The results indicated that the flow resistance coefficients of the sweeping jet were larger than those of the direct jet, and the Nusselt number monotonously increased with the increase in the mass flow rate. Compared to the direct jet, the sweeping jet had a more spatially uniform heat removal rate, and the area-averaged Nusselt number was slightly lower. Therefore, the sweeping... [more]

This study examines the heat and mass transfer coefficient, thermal effusivity, and other thermal properties of solar-dried cocoyam chips, as well as the drying kinetics. The research also assessed the economics of the solar dryer. For these reasons, a solar dryer with a partitioned collector was developed that creates a double airflow travel distance to delay the airflow inside the collector. The partitioning of the collector delays the airflow and helps to create more turbulence for the airflow with increased energy. The solar dryer was locally developed at the Michael Okpara University of Agriculture and tested during the humid crop harvesting period of September for the worst-case scenario. The obtained drying curves and kinetics for cocoyam drying are subjected to the vagaries of weather conditions. The drying rate showed declining sinusoidal characteristics and took about 25 h to attain equilibrium. Analysis of the airflow velocity showed gravitation between laminar and turbulent... [more]

A constant worldwide growing load stress over a power system compelled the practice of a reactive power injection to ensure an efficient power network. For this purpose, multiple technologies exist in the knowledge market out of which this paper emphasizes the usage of the flexible alternating current transmission system (FACTS) and presents a comparative study of the static var compensator (SVC) with the static synchronous compensator (STATCOM), inducted in a real electric substation. The aim is to improve the power factor (PF) and power quality and to encounter reliably extreme conditions. A 220 kV electric substation was opted for the analysis, and both the static and dynamic conditions were observed with the help of a power system analysis tool termed PowerFactory-DIgSILENT. Multiple aspects were investigated via software simulations to assess the performance of the aforementioned FACTS devices, such as the voltage profile evaluation via the load flow analysis method (LFA), the har... [more]

Hyper compressors are key facilities for producing the low-density polyethylene with discharge pressure up to 350 MPa. Such high pressure brings great challenges to the design of the hyper compressor in many aspects. In this paper, a 3D transient computational fluid dynamics (CFD) model with inlet and outlet pipelines is built to investigate the thermodynamic performance of a hyper compressor. To realize the interaction between the thermodynamic processes and the pressure pulsation through valve dynamics, the pressures across the valve surfaces were monitored to the dynamic equation of the poppet valve. Then, structured grids were generated for the flow domain inside the valve, and the entire numerical model was solved by a commercial code: ANSYS Fluent. Consequently, the p-V diagram, the valve motion and pressure pulsation could be acquired simultaneously. The results of the numerical model showed that the exponents of the expansion and compression processes were 5.12 and 13.22, which... [more]

Since the DC-link of the dual-inverter two-stage matrix converter (TSMC) has no energy storage element, its grid-side current waveform is closely related to the load-side condition. The conventional modulation strategy of the dual-inverter TSMC is only the stack of the double inverters, without considering the cooperation between both modulation strategies. Thus, the fluctuations in the grid-side currents synthesized by both load-side currents will be obvious. To solve this problem, this paper analyzes the effect of the current pulse position on the grid-side current waveform quality, and relevant relationship between the pulse position and current harmonics is obtained according to Fourier transform. On this basis, the harmonic attenuation strategy for the dual-inverter TSMC is proposed. In the proposed strategy, the grid-side current harmonic is reduced based on the optimal duty-cycle combination, obtained from the harmonic optimization problem. The simulation and experimental result... [more]

Graphene oxide, as a new two-dimensional material, has a large specific surface area, high thermal stability, excellent mechanical stability and exhibits hydrophilic properties. By combining the carboxyl groups on the surface of graphene oxide with hydrophilic groups, surfactant-like polymers can be obtained. In this paper, based on the molecular dynamics method combined with the first nature principle, we first determine the magnitude of the binding energy of three different coupling agents—alkylamines, silane coupling agents, and haloalkanes—and analytically obtain the characteristics of the soft reaction. The high stability of alkylamines and graphene oxide modified by cetylamine, oil, and water models was also established. Then, three different chain lengths of simulated oil, modified graphene oxide−water solution, and oil-modified graphene oxide−water systems were established, and finally, the self-aggregation phenomenon and molecular morphology changes in modified graphene oxide... [more]

This paper proposes a modelling technique for Synchronous Reluctance Motors (SynRMs) based on a generalized Magnetic Equivalent Circuit (MEC). The proposed model can be used in the design of any number of stator teeth, rotor poles, and rotor barrier combinations. This technique allows elimination of infeasible machine solutions during the initial machine sizing stage, resulting in a lower cohort of feasible machine solutions that can be further optimized using finite element methods. Therefore, saturation effects, however, are not considered in the modelling. This paper focuses on modelling a generic structure of the SynRM in modular form and is then extended to a full SynRM model. The proposed model can be iteratively used for any symmetrical rotor pole and stator teeth combination. The developed technique is applied to model a 4-pole, 36 slot SynRM as an example, and the implemented model is executed following a time stepping strategy. The motor characteristics such as flux distribut... [more]

In recent years, machine learning, especially deep learning, has developed rapidly and has shown remarkable performance in many tasks of the smart grid field. The representation ability of machine learning algorithms is greatly improved, but with the increase of model complexity, the interpretability of machine learning algorithms is worse. The smart grid is a critical infrastructure area, so machine learning models involving it must be interpretable in order to increase user trust and improve system reliability. Unfortunately, the black-box nature of most machine learning models remains unresolved, and many decisions of intelligent systems still lack explanation. In this paper, we elaborate on the definition, motivations, properties, and classification of interpretability. In addition, we review the relevant literature addressing interpretability for smart grid applications. Finally, we discuss the future research directions of interpretable machine learning in the smart grid.

The present work mainly developed a mathematical model based on the plug flow model and coarse fly ash particles’ fragmentation model to describe the behavior and evolution of ash formation and the influence of the biomass feeding rate and flue gas cooling rate on ash properties, which is validated by literature data. The model considers homogeneous nucleation of alkali vapors, heterogeneous condensation of vapors on newly formed particles and fly ash particles, and collision-coagulation between aerosol particles, which is also applied to numerically study and analyze the ash formation characteristics in the cases of practical boiler pulverized fuel combustion and SO2 sulfation. The results show that the mathematical model can reasonably describe the ash formation and the influence of the biomass feeding rate and the flue gas cooling rate on the mass PSDs of PM10 and its elements. The initial nucleation temperature and initial nucleation particle size increase with the biomass feeding... [more]

The combustion of waste biomass is becoming a key challenge for the energy sector, especially in times of growing energy demand and increasing environmental awareness of society. Processing such fuels is usually demanding. Mathematical modeling makes it possible to adapt the course of the process. The best option is to use appropriate fuel mixtures. The aim of this work was to develop a simple model that would allow the pre-selection of the mixture of two types of digestate. Residues from methane fermentation of maize and apple pomace were used in the study. The paper presents both a mathematical model and laboratory tests. The practical part was to check the validity of the model estimates. The model works on the basic data from physicochemical analysis. Laboratory tests included combustion of the samples of different mixtures. We used image analysis of thermograms to determine changes during combustion, which allowed us to determine when and where the main combustion occurs. Results... [more]

Electricity demand has surged over the last several years and will persist in the future. Increased transmission loads cause transmission lines to operate much closer to their security limits, leading to thermal and mechanical stress and thus affecting the transmission reliability and thermal aging. Accordingly, monitoring the conductor temperature over time is critical to identifying power transmission networks that may need extra attention and perhaps maintenance. This paper presents a fuzzy thermal aging model for transmission lines equipped with a fuzzy dynamic thermal rating system based on the IEEE 738 standard. In this framework, the ampacity of the transmission line was calculated. The conductor temperature was computed with the back-calculation method by considering the fully loaded transmission line. The estimated conductor temperature was employed to determine the corresponding conductor fuzzy loss of tensile strength, i.e., the fuzzy annealing degree of the conductor based... [more]

This study aims to analyze the aerodynamic interaction between moving vehicles platooning with the change in the platooning conditions on a freeway. The effect of the vortex generated by the forward vehicle reduces the value of the stagnation pressure generated at the front of the rear vehicle, which effectively reduces drag on the driving vehicle. To elucidate this, a total of four vehicles were applied to platooning at a speed of 100 km/h by altering the gap distance of heavy-duty vehicles (HDVs) such as 0.5 Length (L), 1 L, 1.5 L, 2.0 L, and 2.5 L under the conditions of 1 L equal to 13.16 m. The stagnation pressure at the front of the following vehicle (FV) was reduced, and quantitative analysis of drag force generated at each leading vehicle (LV) and following vehicle that is platooning exhibited a reduction of about 51%, 56%, and 52%, respectively, when compared to the single moving HDV. This is considered as a reduction in engine power for the driving vehicle. Taken together, th... [more]

In a competitive electricity market, generation capacities can exactly cover their full costs. However, the real market deviates from this ideal in some aspects. One is the concern of non-existent or insufficient scarcity prices. We present an iterative method in a linear optimization model to investigate the profitability of assets in the absence of scarcity prices and how the system changes when this risk is incorporated into investors’ expectations. Therefore, we use a two-step optimization of capacity planning and unit commitment. Iteratively, mark-ups at the height of uncovered costs are added to investment costs. This typically leads to a system with better investment profitability while keeping the system cost increase low. The methodology is applied to a simplified brownfield generation system, targeting CO2-free power generation within 25 years. In a model with annual foresight of actors, iterations result in a generation system with significantly lower (or even no) uncovered... [more]

Best estimate system thermal-hydraulic codes in the nuclear engineering community, e.g., TRACE, RELAP3D, CATHARE-3, etc., were extended with 3D coarse-mesh components to better describe the 3D Thermal-Hydraulic (TH) phenomena taking place within the Reactor Pressure Vessel (RPV) and the core. The RPV is usually shaped like a cylinder while the core is mostly a cube. Hence, the TRACE code is equipped with a Cylindrical VESSEL and a Cartesian VESSEL. The former one is to represent the RPV (including core), pressurizer, and steam generator. The latter one is more appropriate to represent the core. The two components are connected by two Vessel-Junctions (VJ) at the core inlet and outlet. Due to the different nodalization between the two VESSELs, the analyst needs to do repetitive and error-prone work defining the cell-to-cell junctions and their TH parameters. To facilitate this process, the Karlsruhe Institute of Technology (KIT) has developed an automatic approach based on a mesh-constr... [more]

District heating and cooling (DHC) networks, and in particular, the fifth generation of DHC networks, offer great potential in increasing the overall system efficiency and reducing CO2 emissions in the heating and cooling of urban districts. Due to the growing complexity of these energy systems, the use of new planning methods, such as the use of dynamic simulation models based on Modelica, becomes more important. However, especially with large, complex thermal networks, there is a high effort for manual model construction and parameterization. For this reason, we present a framework for automated model generation of DHC networks based on simulation models in Modelica written in Python. The core function of the Python framework is to transform a graph representation of a district heating network into a dynamic simulation model. The authors briefly describe the workflow and demonstrate its applicability with three different use cases. We investigate the impact of different design decisi... [more]

In recent years, demand for electric energy has steadily increased; therefore, the integration of renewable energy sources (RES) at a large scale into power systems is a major concern. Wind and solar energy are among the most widely used alternative sources of energy. However, there is intense variability both in solar irradiation and even more in windspeed, which causes solar and wind power generation to fluctuate highly. As a result, the penetration of RES technologies into electricity networks is a difficult task. Therefore, more accurate solar irradiation and windspeed one-day-ahead forecasting is crucial for safe and reliable operation of electrical systems, the management of RES power plants, and the supply of high-quality electric power at the lowest possible cost. Clouds’ influence on solar irradiation forecasting, data categorization per month for successive years due to the similarity of patterns of solar irradiation per month during the year, and relative seasonal similarity... [more]

The geological sequestration of CO2 in deep saline aquifers is one of the most effective strategies to reduce greenhouse emissions from the stationary point sources of CO2. However, it is a complex task to quantify the storage capacity of an aquifer as it is a function of various geological characteristics and operational decisions. This study applies physics-based proxy modeling by using multiple machine learning (ML) models to predict the CO2 trapping scenarios in a deep saline aquifer. A compositional reservoir simulator was used to develop a base case proxy model to simulate the CO2 trapping mechanisms (i.e., residual, solubility, and mineral trapping) for 275 years following a 25-year CO2 injection period in a deep saline aquifer. An expansive dataset comprising 19,800 data points was generated by varying several key geological and decision parameters to simulate multiple iterations of the base case model. The dataset was used to develop, train, and validate four robust ML models—... [more]

Floor heaving is a phenomenon that occurs in almost all mining roadways and tunnels. It can restrain the advance of the heading face or cause serious problems during roadway use. The highest levels of floor uplifting are observed in coal mines, which can reduce the output or even stop it altogether. The floor heaving intensity depends on the rock type, the stress in the rock mass, and rocks’ mechanical properties. Floor deformation develops when the secondary state of stress is formed around the working, and it is much higher and more dynamic in the case of waterlogged rocks. The presence of water increases the floor’s propensity to heave, especially clay rocks, such as claystones or mudstones, if they include water-absorbed minerals. In this paper, we present a new modeling methodology for roadway floor heave. The modeling covers a dry floor condition in which the parameters of the Hoek-Brown failure criterion are gradually lowered over time, and a waterlogged floor condition, in whic... [more]

Atmospheric air is a commonly used working fluid in turbomachinery. The air typically contains a certain amount of suspended solid particles, as well as water in the form of vapor or droplets. In the current paper, we focus on the numerical modeling of humid air transonic flow in turbomachinery. In this paper we demonstrate a rarely considered, but as presented herein important influence of air humidity, pollution and liquid water content on the performance of the first stage of the gas turbine compressor and turbofan engine fan (NASA rotors 37 and 67). We also discuss the impact of the interfacial heat transfer associated with steam condensation or water evaporation on the distribution of stagnation parameters at the rotor outlet, the rotor performance, and flow conditions, as well as losses. Results demonstrate the impact of the number of pollution particles and water droplets on the compression process in the analyzed rotors, especially on the Mach number distribution in the blade-t... [more]

Maintaining proper operation of adaptive protection schemes is one of the main challenges that must be considered for smart grid deployment. The use of reliable cyber detection and protection systems boosts the preparedness potential of the network as required by National Infrastructure Protection Plans (NIPPS). In an effort to enhance grid cyber-physical resilience, this paper proposes a tool to enable attack detection in protective relays to tackle the problem of compromising their online settings by cyber attackers. Implementing the tool first involves an offline phase in which Monte Carlo simulation is used to generate a training dataset. Using rough set classification, a set of If-Then rules is obtained for each relay and loaded to the relays at the initialization stage. The second phase occurs during online operation, with each updated setting checked by the corresponding relay’s built-in tool to determine whether the settings received are genuine or compromised. A test dataset w... [more]

The electrical power infrastructure of the modern world is advanced, efficient, and robust, yet power outages still occur. In addition to affecting millions of people around the world, these outage events cost billions of dollars to the global economy. In this paper, the revenue loss borne by electricity-supplying companies in the United States due to power outage events is estimated and predicted. Various factors responsible for power outages are considered in order to present an exploratory data analysis at the U.S. level, followed by the top ten affected states, which bear over 85% of the total revenue loss. The loss is computed using historic observational data of electricity usage patterns and the tariff offered by the energy suppliers. The study is supplemented with reliable and publicly available records, including electricity usage patterns, the consumer category distribution, climatological annotations, population density, socio-economic indicators and land area. Machine learn... [more]

The aim of the article is to present and analyze the processes occurring as a result of installing a long flashover arrester (LFA) and a multi-chamber arrester (MCA) as overvoltage protection of power networks. The numerical models of LFA and MCA will be made in order to carry out simulations in the scope of selected structural elements of the considered overvoltage protection device. The above research is a significant supplement to the information on the selection of an effective solution for overvoltage protection.

Oil drilling is the core process of oil and natural gas resources exploitation. Well overflow is one of the biggest threats to safety drilling. Prediction of the overflow in advance can effectively avoid the occurrence of this kind of accident. However, the drilling history has unbalanced distribution, and labeling data is a time-consuming and laborious job. To address this issue, an overflow-prediction algorithm based on semi-supervised learning is designed in this paper, which can accurately predict overflow 10 min in advance when the labeled data are limited. Firstly, a three-step feature-selection algorithm is conducted to extract 22 features, and the time series samples are constructed through a 500-width sliding window with step size 1. Then, the Mean Teacher model with Jitter noise is employed to train the labeled and unlabeled data at the same time, in which a fused CNN-LSTM network is built for time-series prediction. Compared with supervised learning and other semi-supervised... [more]