The study on the adsorption and micropore filling of water vapor in coal is significant for predicting coalbed methane content in coal seams. The primary purpose of this study is to explain the effects of coal pore structure and its surface chemistry on water vapor monolayer adsorption, micropore filling, and diffusion coefficient. First, X-ray diffraction (XRD) and mercury intrusion porosimetry (MIP) analyzed inorganic mineral components of two kinds of coal samples and pore fissures structures. Then, we divide pores and fissures according to the theory of fractal dimensions. Furthermore, we carried out the water vapor adsorption and desorption experiments on two kinds of coal; in particular, we set 14 points of relative pressure between 0 and 0.2. Guggenheim−Anderson−de Boer (GAB), Frenkel−Halsey−Hill (FHH), and Freundlich models were used to analyze the data of water vapor adsorption to obtain the boundary pressure points of the monolayer, multilayer adsorption, and capillary conden... [more]

This paper introduces a new single-phase AC-AC converter based on an impedance source circuit. Like the existing single-phase impedance source AC-AC converters, it has the buck-boost ability and direct ac conversion. The input and output voltage possesses the same ground, and the phase angle is maintained and reversed smoothly. The presented converter utilizes a coupled transformer which allows the designer to exploit the transformer’s turns ratio as a variable to attain the desired output voltage. Additionally, the used transformer provides an option to obtain higher voltage gain by decreasing the turns ratio. Hence, smaller size of the coupled inductors is required for the higher voltage cases. To eliminate the switching voltage and current spikes on the power switches, a safe commutation strategy is used instead of utilizing snubber circuits. Furthermore, the input current is continuous and sinusoidal with low harmonics thanks to embedding the input inductor in series with the input... [more]

This article analyzed the cost of capital under risk conditions for thermoelectric plants in Brazil, applying the Capital Asset Pricing Model—CAPM and the Weighted Average Capital Cost—WACC. To estimate the local CAPM, we used information from the Electric Energy Index—IEE of publicly traded companies in the electricity sector in Brazil and for the global CAPM, we observed the companies associated with the Edison Electric Institute—EEI, listed on the New York Stock Exchange—NYSE and at the National Association of Securities Dealers Automated Quotations—NASDAQ—USA. The risk conditions for capital costs were represented by Monte Carlo simulation using, as a basis, the WACC of a fuel oil thermoelectric plant and the local and global CAPM. The main results show that the IEE and EEI companies obtained a positive average daily return. Due to the Brazil risk, under deterministic conditions, the local WACC (11.13% p.a.) was more attractive to investors when compared to the global WACC (10.32%... [more]

Wind resource assessment is a key factor for the development and implementation of wind farms with the purpose of generating green, eco-friendly and clean electricity. The Bolivian Andes, as a large dry region, represents an important source of renewable energy. However, the altitude and high wind energy resources of the Bolivian Andes require further knowledge and understanding of the wind energy resources. In this study, the GWA have been used to determine the total area available to install wind farms considering the protected areas, roads, cities and transmission lines. In addition, the Weather Research and Forecasting (WRF v3.8.1) model is employed to complement the results of the GWA based on the validation of WRF simulations with measurements from Qollpana wind farm. The main purpose is to estimate the wind power potential along the Bolivian Andes and its variability in time. The wind power simulations have been compared with the power generated by the Qollpana wind farm to veri... [more]

To acquire a satisfying cutting effect during medium-length hole blasting driving of rock tunnels, an improved wedge cutting blasting method with supplementary blasting of the center holes was proposed. Initially, the cavity forming mechanism of the improved cutting method was analyzed theoretically. The results suggested that cutting hole blasting could realize the ejection of rock within the range from free face to critical cutting depth, and hence reduce the restraining force of the center hole blasting, and the supplementary blasting of the center holes could further accomplish the expulsion of the residuary rock. Subsequently, simulation of the improved cutting method was implemented to exhibit the stress wave evolution and reveal the stress field distribution. The simulation results indicated that cutting hole blasting could cause the preliminary failure of the residuary rock, and center hole blasting could strengthen the stress field intensity in 1.8−2.5 m in order to aggravate... [more]

The incineration process in waste-to-energy plants is characterized by high levels of inertia, large delays, strong coupling, and nonlinearity, which makes accurate modeling difficult. Therefore, an intelligent modeling method for the incineration process in waste-to-energy plants based on deep learning is proposed. First, the output variables were selected from the three aspects of safety, stability and economy. The initial variables related to the output variables were determined by mechanism analysis and the input variables were finally determined by removing invalid and redundant variables through the Lasso algorithm. Secondly, each delay time was calculated, and a multi-input and multi-output model was established on the basis of deep learning. Finally, the deep learning model was compared and verified with traditional models, including LSSVM, CNN, and LSTM. The simulation results show that the intelligent model of the incineration process in the waste-to-energy plant based on dee... [more]

The paper presents in an applicative manner a parameter-based methodology about design, modeling and optimization of a spur gear pump, currently under production in a Romanian company. Wanting to expand their product range, the company asked for a parameter-based design of this type of pump, FEM simulations and optimization of its conception to cover a wider range of flow rates, as required by current beneficiaries. The purpose of this research was to find improved alternative solutions via parametric design, mathematical validation and finite element simulation of the manufacturing solutions. The pump model is well known and has been manufactured for decades in many countries, under various licenses and constructive variants. The research process analyzed the functional role of the gear pump, its structure, its 3D model, which was reconstructed from the last manufactured solution, while identifying certain dimensions to be optimized and used in parametric design relations. The author... [more]

This paper developed a 3D physical model of the hydraulic end of a high-pressure liquid hydrogen reciprocating pump to research the dynamic characteristics of the pump valve system. Based on dynamic mesh technology, we analyzed the coupling characteristics of pump valve and plunger motion and spool force considering the leakage model, closure model of valve gap, and compressibility of liquid hydrogen. Further, we analyzed the effect of the spring stiffness and preload force on the laws of motion of the pump valve. Finally, a liquid hydrogen pressurization test was conducted to revise the simulation model and verify the accuracy of the simulation. The results of the simulation and test show that the simulation method in this paper can simulate the liquid hydrogen pressurization process more accurately and obtain the motion law of the suction and discharge valves. Both the suction and discharge valves have an opening hysteresis angle of about 40°, and there is a strong coupling relations... [more]

Previous micro-scale studies of the effect of pore structure on spontaneous imbibition are mainly limited to invariable-diameter capillaries. However, in real oil and gas reservoir formations, the capillary diameters are changing and interconnected. Applying the lattice Boltzmann color gradient two-phase flow model and the parallel computation of CPUs, we simulated the spontaneous imbibition in variable-diameter capillaries. We explored the reasons for the nonwetting phase snap-off and systematically studied the critical conditions for the snap-off in spontaneous imbibition. The effects of pore-throat aspect ratio, throat diameter, and the pore-throat tortuosity of the capillary on spontaneous imbibition were studied. Through analyzing the simulated results, we found that the variation in the capillary diameter produces an additional resistance, which increases with the increase in the pore-throat ratio and the pore-throat tortuosity of a capillary. Under the action of this additional... [more]

Accurately detecting oil leakage from a power transformer is important to maintain its normal operation. Deep learning (DL) methods have achieved satisfactory performance in automatic oil detection, but challenges remain due to the small amount of training data and oil targets with large variations in position, shape, and scale. To manage these issues, we propose a dual attention residual U-net (DAttRes-Unet) within a U-net architecture that extensively uses a residual network as well as spatial and channel-wise attention modules. To overcome the vanishing gradient problem due to deeper layers and a small amount of training data, a residual module from ResNet18 is used to construct the encoder path in the U-net framework. Meanwhile, to overcome the issue of training difficulty for the network, inspired by the advantage of transfer learning, initial network parameters in the encoder are obtained from the pre-trained ResNet18 on the ImageNet dataset. Further, in the decoder path, spatial... [more]

Flue gas produced by biomass fuel combustion contains various chlorine-containing substances and is an important factor causing biomass boiler corrosion. The corrosion processes of chlorine, hydrogen chloride and water on iron covered with an intact/damaged oxide film were investigated under the high temperature of 1300 K through reactive molecular dynamics simulation. The results show that the diffusion processes of oxygen and chlorine are similar and can be divided into three stages: rapid diffusion, continuous diffusion, and no oxide film (stable). Oxygen diffusion in Fe2O3 into a pure iron layer is the main cause of gas corrosion in iron/iron oxide systems. A complete oxide film can hinder iron corrosion by chlorine and hydrogen chloride. Damage in an oxide film significantly affects oxygen and chlorine diffusion and iron corrosion. However, such influence is gradually reduced. The integrity of a protective film is the key to alleviating corrosion. Water facilitates the dissociatio... [more]

The air leakage in sintering machines affects the technological and economic indexes of the sintering process. It is of great significance to monitor and estimate the key areas. Mathematical models of sintering air leakage through holes in the steady-state process are given based on the fluid mechanics to predict the flow rate and effect on the key area. It was found that the hole model is the application of constant orifice outflow in the computation of sintering air leakage. The counter-flow bed model is suitable for predicting the flow rate through a complete break in sintering wind boxes. Furthermore, This paper proposes a new hole−bed generalized model to cover all the possible hole diameters for further high-precision application. The model connects the leakage hole diameter with the sintering process for the first time and establishes their coupling relationship. The pressure state in the sintering system depends on the ratio of the leakage hole area to the sintering bed area. T... [more]

The power system is undergoing significant changes so as to accommodate an increasing amount of renewably generated electricity. In order to facilitate these changes, a shift from the currently employed zonal pricing to nodal pricing is a topic that is receiving increasing interest. To explore alternative pricing mechanisms for the European electricity market, one needs to solve large-scale nodal optimization problems. These are computationally intensive to solve, and a parallelization or sequencing of the models can become necessary. The seasonality of hydro inflows and the issue of myopic foresight that does not display the value in storing water today and utilizing it in the future is a known problem in power system modeling. This work proposes a heuristic step-wise methodology to obtain state of charge profiles for hydro storage units for large-scale nodal and zonal models. Profiles obtained from solving an aggregated model serve as guidance for a nodal model with high spatial and... [more]

For the first time, the Weather Research and Forecast (WRF) model with the Wind Farm Parameterization (WFP) modeling method is utilized for a short-range wind power forecast simulation of 48 h of an offshore wind farm with 100 turbines located on the east coast of the China Yellow Sea. The effects of the horizontal multi-grid downsize method were deployed and investigated on this simulation computation. The simulation was validated with the field data from the Supervisory Control and Data Acquisition (SCADA) system, and the results showed that the horizontal mesh downsize method improved the accuracy of wind speed and then wind power forecast. Meanwhile, the wind power plant aerodynamics with turbine wake and sea−land shore effects were investigated, where the wake effects from the wind farm prolonged several miles downstream, evaluated at two wind speeds of 7 m/s and 10 m/s instances captured from the 48 h of simulation. At the same time, it was interesting to find some sea−land atmos... [more]

Motivated by the growing demand for distributed energy resources (DERs), peer-to-peer (P2P) electricity markets have been explored worldwide. However, such P2P markets must be balanced in much smaller regions with a lot fewer participants than centralized wholesale electricity markets; hence, the market has inherent problems of low liquidity and price instability. In this study, we propose applying a market maker system to the P2P electricity market and developing an efficient market strategy to increase liquidity and mitigate extreme price fluctuations. To this end, we construct an artificial market simulator for P2P electricity trading and design a market agent and general agents (photovoltaic (PV) generators, consumers, and prosumers) to perform power bidding and contract processing. Moreover, we introduce market-maker agents in this study who follow the regulations set by a market administrator and simultaneously place both sell and buy orders in the same market. We implement two t... [more]

Smart buildings that utilize innovative technologies such as artificial intelligence (AI), the internet of things (IoT), and cloud computing to improve comfort and reduce energy waste are gaining popularity. Smart buildings comprise a range of sensors to measure real-time indoor environment variables essential for the heating, ventilation, and air conditioning (HVAC) system control strategies. For accuracy and smooth operation, current HVAC system control strategies require multiple sensors to capture the indoor environment variables. However, using too many sensors creates an extensive network that is costly and complex to maintain. Our proposed research solves the mentioned problem by implementing a machine-learning algorithm to estimate unmeasured variables utilizing a limited number of sensors. Using a six-month data set collected from a three-story smart building in Japan, several extreme gradient boosting (XGBoost) models were designed and trained to estimate unmeasured room temp... [more]

Energy management and utilization for commercial users is becoming increasingly intelligent and refined, fostering a closer and growing connection with the electricity market. In this paper, a novel energy management optimization theoretical framework for commercial users is proposed based on the hybrid simulation of electricity market bidding. The hybrid simulation model based on Multi-Agent Simulation (MAS) with reinforcement learning and System Dynamic Simulation (SDS) is established to solve the problem using a single simulation method: it cannot adjust the clearing price when considering the whole market; considering the uncertainty of Electric Vehicles (EVs) travel and Lighting Loads (LLs), the multi-objective optimization model of energy management for commercial users is constructed to minimize the total energy cost of commercial users, as well as maximize the lighting comfort of indoor office staff, which compensates for the lack of the single-objective optimization of the pow... [more]

In the present work, uncertainty quantification of a venturi tube simulation with the cavitating flow is conducted based on Bayesian inference and point-collocation nonintrusive polynomial chaos (PC-NIPC). A Zwart−Gerber−Belamri (ZGB) cavitation model and RNG k-ε turbulence model are adopted to simulate the cavitating flow in the venturi tube using ANSYS Fluent, and the simulation results, with void fractions and velocity profiles, are validated with experimental data. A grid convergence index (GCI) based on the SLS-GCI method is investigated for the cavitation area, and the uncertainty error (UG) is estimated as 1.12 × 10−5. First, for uncertainty quantification of the venturi flow simulation, the ZGB cavitation model coefficients are calibrated with an experimental void fraction as observation data, and posterior distributions of the four model coefficients are obtained using MCMC. Second, based on the calibrated model coefficients, the forward problem with two random inputs, an inle... [more]

Accurate and rapid forecasting of short-term loads facilitates demand-side management by electricity retailers. The complexity of customer demand makes traditional forecasting methods incapable of meeting the accuracy requirements, so a self-attention based short-term load forecasting (STLF) considering demand-side management is proposed. In the data preprocessing stage, non-parametric kernel density estimation is used to construct customer electricity consumption feature curves, and then historical load data are used to delineate the feasible domain range for outlier detection. In the feature selection stage, the feature data are selected using variational modal decomposition and a maximum information coefficient to enhance the model prediction accuracy. In the model prediction stage, the decomposed intrinsic mode function components are independently predicted and reconstructed using an Informer based on improved self-attention. Additionally, the novel AdaBlief optimizer is used to o... [more]

This paper proposes the full simulation model for the electrical analysis of all-electric ship (AES) based on a medium voltage DC power system. The AES has become popular both in the commercial and the military areas due to a low emission, a high fuel consumption efficiency, and a wide applicability. In spite of many advantages, it is complex and difficult to construct the whole system with many mechanical and electrical components onboard. Full electrical analysis is essentially required to simplify the design of the AES, a control and optimization of a ship electric system. The proposed full simulation model of the AES includes the mechanical and the electrical elements by using the MATLAB/Simulink. The mechanical elements are comprised of a steam turbine and a hydrodynamic model of a ship which is adopted by an average value model that is based on the characteristic equation of the mechanical system. The electrical elements are developed by full detailed models which consist of gene... [more]

The conversion of biomass to olefin by employing gasification has recently gained the attention of the petrochemical sector, and syngas composition is a keystone during the evaluation of process design. Process simulation software is a preferred evaluation tool that employs stoichiometric and kinetic approaches. Despite the available literature, the estimation errors of these simulation methods have scarcely been contrasted. This study compares the errors of stoichiometric and kinetic models by simulating a downdraft steam gasifier in PRO/II. The quantitative examination identifies the model that best predicts the composition of products for the gasification of Japanese wood waste. The simulation adopts reaction mechanisms, flowsheet topology, reactions parameters, and component properties reported in the literature. The results of previous studies are used to validate the models in a comparison of the syngas composition and yield of products. The models are used to reproduce gasificat... [more]

In the course of the switch to renewable energy sources, there is a shift from a few large energy sources (power plants) to a large number of small, distributed energy sources (e.g., photovoltaic systems) and energy storage devices (e.g., electric vehicles). This results in the need to know and identify these energy sources and sinks as soon as new devices are installed, in order to ensure grid stability. This paper presents an approach to identify energy sources and energy storage in smart meter data, using photovoltaic systems and electric vehicles as examples. For this purpose, the Pecan Street dataset is used, which has been extended by charging processes from the ACN dataset. The presented approach comprises a combination of a Convolutional Neural Network and a Multilayer Perceptron, which decides separately, on the basis of the smart meter data of a household, whether an electric vehicle and a photovoltaic system are present. It is shown that the combination of both classifiers a... [more]

In this paper, heat transfer and airflow in the gap between the panes of a central part of a double-glazed window were investigated using mathematical modeling. It has been shown that the cyclical airflow regime, in the form of ascending and descending boundary layers, loses stability and changes to a vortex regime under certain conditions depending on the gap width, transverse temperature gradient, inclination angle and window height, as in Rayleigh−Bernard convection cells. The study made it possible to determine the critical values of the Rayleigh number (Ra) at which the air flow regime in the gap between the panes of a window changes (in the range of values 6.07 × 103 < Ra < 6.7 × 103). As a result of the modeling, the values of the thermal resistance of a central part of double-glazed window were determined as a function of the width of the gap between the panes, the angle of inclination and the transverse temperature gradient.

Given the spatial structures and functional requirements, there are a number of different types of obstacles in long and narrow confined spaces that will cause a premixed gas explosion to produce greater overpressure and influence the flame behavior for different obstacles. Because the volume fraction of unburned gas changes with the changing height of the U-type obstacles, we can further study the influence on the volume fraction of the unburned premixed gas for the characteristics of the overpressure and the flame behaviors in the closed tube with the obstacles. The results show that after the premixed gas is successfully ignited in the pipe, the overpressure in the pipe greatly increases as the unburned premixed gas burns between the adjacent plates. Moreover, the increase of the overpressure in the closed duct becomes faster when the decrease of unburned gas becomes faster. The high-pressure areas between the plates move inversely compared with the direction of flame propagation wh... [more]

With the development of power modules for high voltage, high temperature, and high power density, their size is becoming smaller, and the packaging insulation experiences higher electrical, thermal, and mechanical stress. Packaging insulation needs to meet the requirement that internal electric field, temperature, and mechanical stress should be as low as possible. Focusing on the coupling principles and optimization design among electrical, thermal, and mechanical stresses in the power module packaging insulation, a multi-objective optimization design method based on Spice circuit, finite element field numerical calculation, and multi-objective gray wolf optimizer (MOGWO) is proposed. The packaging insulation optimal design of a 1.2 kV SiC MOSFET half-bridge power module is presented. First, the high field conductivity characteristics of the substrate ceramic and encapsulation silicone of the packaging insulation material were tested at different temperatures and external field streng... [more]