The article is devoted to the study of steady-state conditions of a distribution network containing a thyristor voltage regulator. The thyristor voltage regulator (TVR) is a new controlled semiconductor device developed at Nizhny Novgorod State Technical University n.a. R.E. Alekseev (NNSTU). The TVR allows the optimization of the parameters of 6−20 kV distribution networks (currents and voltages) by voltage regulation. An analytical calculation of electromagnetic processes of a distribution network with the TVR has been carried out. The verification of the obtained results has been made using a computer simulation. The dependences of the current and power on additional voltage introduced by the TVR under different voltage regulation modes have been obtained. It has been shown that the use of the TVR enables optimal flow distribution to be ensured over the power transmission lines in proportion to their transfer capability when changing load power and its power factor.

This paper introduces an enhancement of the protection and operation of the Future Renewable Electric Energy Delivery and Management (FREEDM) system. It uses the solid-state transformers to connect the residential A.C. and D.C. microgrids to the distribution system and fault isolation devices for faulty line isolation. In this paper, a current differential protection scheme has been proposed to detect faults in the FREEDM-based microgrid network. This method is based on the current measurement at the two-line terminals using phasor measurement units to ensure data synchronization and minimize the measuring error. Also, a communication scheme that is based on the Internet of things technology and Wi-Fi is constructed for data monitoring and interlinking between the relays, transducers, and the fault isolation devices in the two-terminals lines. A hypothetical FREEDM system has been used for the verification and testing of the proposed method. Different fault types at different locations... [more]

It is very important to effectively describe the sweep characteristics of CO2 miscible flooding based on physical models for actual reservoir development. In this study, based on the geological characteristics of the Jilin ultra-low permeability reservoir, which has significant vertical heterogeneity, a two-dimensional double-layer heterogeneous visualization model with a permeability contrast of 10 and thickness contrast of 2 was designed to perform experimental research on the sweep law of CO2 miscible flooding with an injection-production mode of “united injection and single production”. With the goal of determining the obvious differences in the gas absorption capacity and displacement power of the two layers, the CO2 dynamic miscible flooding characteristics were comprehensively analyzed, and the sweep law of CO2 miscible flooding, including the oil and gas flow trend, migration direction of the oil−gas interface, and distribution characteristics of the miscible zone, was further... [more]

In addition to the different technologies of silicon solar cells in crystalline form, TOPCon solar cells have an exceptionally great efficiency of 26%, accomplished by the manufacturing scale technique for industrialization, and have inordinate cell values of 732.3 mV open-circuit voltage (Voc) and a fill factor (FF) of 84.3%. The thickness of tunnel oxide, which is less than 2 nm in the TOPCon cell, primarily affects the electrical properties and efficiency of the cell. In this review, various techniques of deposition were utilized for the layer of SiOx tunnel oxide, such as thermal oxidation, ozone oxidation, chemical oxidation, and plasma-enhanced chemical vapor deposition (PECVD). To monitor the morphology of the surface, configuration of annealing, and rate of acceleration, a tunnel junction structure of oxide through a passivation quality of better Voc on a wafer of n-type cell might be accomplished. The passivation condition of experiments exposed to rapid thermal processing (RT... [more]

The 55th International Universities Power Engineering Conference (UPEC 2020) has been held on 1−4 September 2020 in the Virtual Conference mode because of the limitations due to the pandemics, hosted by Politecnico di Torino, Torino, Italy [...]

During well drilling in offshore conditions beyond the North of the Arctic Circle, there are often problems associated with deviations in the rheological parameters of the drilling mud as the temperature changes. Mud temperature in the upper part of the well in most cases is in the range up to 20 °C, whereas in the productive formation it is up to 80 °C and more. For such conditions, it is necessary to estimate the influence of temperature on the rheological parameters of drilling fluids, which is done in this paper. Compositions of water-based and hydrocarbon-based muds that may be used in the conditions of the offshore hydrocarbon fields were considered. The paper presents the authors’ formula for a drilling mud that possesses more stable rheological parameters in the temperature conditions of the offshore oil field and is more environmentally friendly. The physical properties of the newly designed drilling mud were measured with laboratory equipment. Rheological investigations were... [more]

In the progressive development of Electric Vehicles (EVs) and the transformation of transport towards electromobility and decarbonization of cities, many different problems are being faced related to energy management in transport in smart cities [...]

Analysis of the sedimentary environment during the clastic formation process is of great significance for reservoir evaluation and desert prediction. This paper focused on the Paleocene in the West Lishui Sag, East China Sea Basin. XRF fluorescence diffraction and carbon and oxygen isotope tests were carried out on core samples from four wells. Based on the geochemical characteristics of the samples and the changes in the elemental ratios, combined with the lithologic characteristics and sedimentary structure of the samples, the paleoclimate, paleosalinity, paleobathymetric, paleoredox, paleotemperature, and other paleoenvironmental characteristics were analyzed. The results show that the characteristics of major and trace elements were similar in the lower Mingyuefeng Formation (E1m2), Upper Lingfeng Formation (E1l1), Lower Lingfing Formation (E1l2), and Yueguifeng Formation (E1y). The Paleocene in the West Lishui Sag was mainly in the reducing environment of brackish-salt water with... [more]

Reactive and biased human decision-making during well construction operations can result in problems ranging from minor inefficiencies to events that can have far-reaching negative consequences for safety, environmental compliance and cost. A system that can automatically generate an optimal action sequence from any given state to meet an operation’s objectives is therefore highly desirable. Moreover, an intelligent agent capable of self-learning can offset the computation and memory costs associated with evaluating the action space, which is often vast. This paper details the development of such action planning systems by utilizing reinforcement learning techniques. The concept of self-play used by game AI engines (such as AlphaGo and AlphaZero in Google’s DeepMind group) is adapted here for well construction tasks, wherein a drilling agent learns and improves from scenario simulations performed using digital twins. The first step in building such a system necessitates formulating the... [more]

The conventional denoising method in Rayleigh imaging in a general sense requires an additional hardware investment and the use of the underlying physics. This work demonstrates an alternative image denoising reconstruction model based on unsupervised learning that aims to remove Mie scattering and shot noise interference from two-dimensional (2D) Rayleigh images. The model has two generators and two discriminators whose parameters can be trained with either feature-paired or feature-unpaired data independently. The proposed network was extensively evaluated with a qualitative examination and quantitative metrics, such as PSNR, ER, and SSIM. The results demonstrate that the feature-paired training network exhibits a better performance compared with several other networks reported in the literature. Moreover, when the flame features are not paired, the feature-unpaired training network still yields a good agreement with ground truth data. Specific indicators of the quantitative evaluati... [more]

This study develops robust numerical algorithms for the simulation of three-phase (solid-liquid-gas) boiling and bubble formation problems in rectangular channels. The numerical algorithms are based on the Finite Volume Methods (FVM) and implement both the volume-of-fluid (VOF) methods for liquid-gas interface tracking as well as the volume-fraction methods to account for the concentration of embedded solid nano-particles in the liquid phase. Water is used as the base-liquid and the solid phase is modelled via metallic nano-particles (both aluminium oxide and titanium oxide nano-particles are considered) that are homogeneously mixed within the liquid phase. The gas phase is considered as a vapour arising from the bolling processes of the liquid-phase. The finite volume methodology is implemented on the OpenFOAM software platform, specifically by careful modification and manipulation of existing OpenFOAM solvers. The governing fluid dynamical equations, for the three-phase boiling probl... [more]

Realizing the dynamic redundancy of sensors is of great significance to ensure the energy saving and normal operation of the heating, ventilation, and air-conditioning (HVAC) system. Building a virtual sensor model is an effective method of redundancy and fault tolerance for hardware sensors. In this paper, a virtual sensor modeling method combining the maximum information coefficient (MIC) and the spatial−temporal attention long short-term memory (STA-LSTM) is proposed, which is named MIC-STALSTM, to achieve the dynamic and nonlinear modeling of the supply and return water temperature at both ends of the chiller. First, MIC can extract the influencing factors highly related to the target variables. Then, the extracted impact factors via MIC are used as the input variables of the STA-LSTM algorithm in order to construct an accurate virtual sensor model. The STA-LSTM algorithm not only makes full use of the LSTM algorithm’s advantages in handling historical data series information, but... [more]

This paper proposes a quasi-resonant step-up DC-DC converter to provide the DC-link voltage for piezoelectric transmitters (PZETs). The resonance not only provides a soft-switching condition for the converter switches, but also helps to decrease the converter element sizes for marine applications. Operation modes of the proposed converter are discussed. The current and voltage of the converter components are derived analytically, and hence the converter gain is obtained. The performance of the proposed high-step-up, high-power density converter is examined through a comprehensive simulation study. The simulation results demonstrate the soft-switching operation and short transient time required for the converter to reach the reference output voltage. The converter output voltage remains unchanged when an inverter with a passive filter is placed at its output while supplying the PZET. The proposed DC-DC converter is prototyped to validate the converter gain and soft-switching operation e... [more]

This paper uses two competing machine learning models, namely the Support Vector Regression (SVR) and the eXtreme Gradient Boosting (XGBoost) against the Autoregressive Integrated Moving Average ARIMAX (p,d,q) model to identify their predictive performance of the crude oil volatility index before and during COVID-19. In terms of accuracy, forecasting results reveal that the SVR model dominates the XGBoost and ARIMAX models in predicting the crude oil volatility index before COVID-19. However, the XGBoost model provides more accurate predictions of the crude oil volatility index than the SVR and ARIMAX models during the pandemic. The inverse cumulative distribution of residuals suggests that both ML models produce good results in terms of convergence. Findings also indicate that there is a fast convergence to the optimal solution when using the XGBoost model. When analyzing the feature importance, the Shapley Additive Explanation Method reveals that the SVR performs significantly better... [more]

Data-driven electrical energy efficiency management is the emerging trend in electrical energy forecasting and management. This fusion of data science, artificial intelligence, and electrical energy management has turned out to be the most precise and robust energy management solution. The Smart Energy Informatics Lab (SEIL) of the Indian Institute of Technology (IIT) conducted an experimental study in 2019 to collect massive data on university campus energy consumption. The comprehensive comparative study preparatory to the recommendation of the best candidate out of 24 machine learning algorithms on the SEIL dataset is presented in this work. In this research work, an exhaustive parametric and empirical comparative study is conducted on the SEIL dataset for the recommendation of the optimal machine learning algorithm. The simulation results established the findings that Bagged Trees, Fine Trees, and Medium Trees are, respectively, the best-, second-best-, and third-best-performing al... [more]

A semi-empirical method is proposed for determining the rate of gas production in a flow-through gas generator (GG) with the allocation of a part of the gas flow produced by gasification of a low-melting solid material (LSM) in the total gas flow rate through the GG. The method is verified by test fires with polypropylene sample gasification by hot air under conditions of incoming supersonic flow with Mach number 2.43, 2.94, and 3.81 and stagnation temperature 600−700 K. The mean flow rates of gasification products obtained in test fires were 0.08 kg/s at Mach 2.43, 0.10 kg/s at Mach 2.94, and 0.05−0.02 kg/s at Mach 3.81. For obtaining 1 kg of gasification products in the test fires there was a need of 1.61 to 2.86 kg of gasifying agent.

The article presents a study of the flow through a tunable check valve used as a hydraulic lock in a system with an actuator. Special attention is given to energy losses of the liquid stream in the poppet gap. In the first stage of the research, CFD methods were used to determine the speed and pressure distributions for the fixed values of the input flow rate and the poppet position. The values of the jet angle and pressures determined based on the CFD results were used to build a simulation model of the entire hydraulic system in Matlab/Simulink environment. The influence of the spring parameters pressing the poppet against the valve seat on the pressure drop and thus on the amount of energy lost was investigated. In particular, the spring stiffness and initial tension were studied. The obtained results were used to develop guidelines for constructing a valve prototype. Finally, the results of simulation tests were verified based on the actual valve characteristic obtained on a test b... [more]

In a doubly-fed induction generator (DFIG)-based wind energy conversion system (WECS), when the grid voltage sags severely, the rotor side converter (RSC) suffers from overvoltage and overcurrent owing to the large electromotive force (EMF). To ensure that the converter operates within a safe range when grid faults occur, this paper proposes a double impedance-substitution control (DISC) strategy to improve the system’s low-voltage ride through (LVRT) capability. When the grid voltage sag is detected, the grid side converter (GSC) and RSC are connected in parallel to the rotor circuit by changing the topology of the system. In the new topology, GSC and RSC are equivalent to inductive impedance by controlling, which can not only suppress the overvoltage and overcurrent at the rotor side, but also effectively reduce the torque ripple. Additionally, the DISC strategy can provide reactive power support to the grid during LVRT. Finally, the simulation results show that the DISC strategy can... [more]

Digitization is a driving force for social development and corporate innovation. Digital projects have become an indispensable part of the sustainable development of enterprises. However, due to the imperfect decision-making system of digital projects and the lack of experience of traditional enterprises’ digital projects, the decision-making of digital projects is an unavoidable challenge in the digital transformation of enterprises. For the digital project decision of the STATE GRID Corporation of China, this paper conducts a sensitivity analysis of digital project evaluation index weights based on cloud model theory, on top of historical successful project experience to support digital project decision-making. Firstly, this paper establishes a comprehensive evaluation index system for digitalization projects from five aspects: economic efficiency, interconnection, intelligent management, value release, and development innovation. The coefficient of variation method is used for index... [more]

Ordered interdigitated heterojunction as a promising nanostructure has attracted considerable attention due to its potential application in solar cells. However, a suitable construction to achieve effective free carrier transport in these nanostructures remains a challenge. In this study, interdigitated nanostructure was fabricated by combining vertically orientated TiO2 nanotube array with discotic liquid crystal Copper (II) 2,9,16,23-tetra-tert-butyl-29H,31H-phthalocyanine (tbCuPc). These discotic molecules were assembled as homeotropic alignment in the interdigitated nanostructure, which enhanced the carrier mobility of active layer considerably. The performance of photovoltaic cells with this interdigitated heterojunction was improved. Molecule orientation leading to charge carrier mobility enhancement was found to play a key role in improving the power conversion efficiency of the devices substantially.

Many researchers spent much effort on the online power management strategies for plug-in hybrid vehicles (PHEVs) and hybrid electric vehicles (HEVs). Nowadays, artificial neural networks (ANNs), one of the machine learning techniques, have also been applied to this problem due to their good performance in learning non-linear and complicated multi-inputs multi-outputs (MIMO) dynamic systems. In this paper, an ANN is applied to the online power management for a plug-in hybrid electric vehicle (PHEV) by predicting the torque split between an internal combustion engine (ICE) and an electric motor (e-Motor) to optimize the greenhouse gas (GHG) emissions by using dynamic programming (DP) results as training data. Dynamic programming can achieve a global minimum solution while it is computationally intensive and requires prior knowledge of the entire drive cycle. As such, this method cannot be implemented in real-time. The DP-based ANN controller can get the benefit of using an ANN to fit the... [more]

The helium-cooled pebble bed (HCPB) breeding blanket (BB) is one of the two driver-blanket candidates for the European DEMO fusion reactor. Recent design activities were focused, among other objectives, on the achievement of an efficient shielding system to adequately protect the vacuum vessel (VV) and toroidal field coils (TFCs). Several shielding options have been studied in terms of architecture (e.g., in-BB shield and ex-BB shield) and materials (e.g., B4C, WC, WB, YHx, and ZrHx). In this study, the B4C material was selected as the most attractive option considering not only shielding performance but also availability, industrialization, experience, and cost factors. Subsequently, we performed a parametric study by implementing different thicknesses of a B4C external shield and reporting information of its effect on shielding performance, structural behavior, swelling and tritium breeding. Furthermore, a detailed structure for the VV was developed considering an internal layered co... [more]

This study presents a variable incremental controller for flux-weakening control in the high-speed operation area of a permanent-magnetic synchronous motor (PMSM). In general, voltage-based flux-weakening control utilizes a reference voltage and a PI controller to generate a flux component current. In this paper, the voltage-based flux-weakening control is performed using the variable incremental controller instead of the PI controller. The variable incremental controller can control the flux component current using only the maximum speed and maximum current of the motor. A method for properly setting an appropriate variable incremental controller using acceleration is additionally presented. A variable incremental controller is applied and, accordingly, the overshoot of the motor speed can be reduced and the speed error of the motor can be minimized by reducing the difference between the actual motor and targeted accelerations. This method can simplify the design of a controller that... [more]

Exhaust emissions from vehicles are the subject of numerous studies and legal acts. In the European Union, exhaust emissions are regulated by “Euro” emission standards, which limit emissions of gaseous pollutants such as CO, CO2, HC, and NOx, as well as the particulate matter (PM) and particle number (PN). Solid particles consist of a number of micro-contaminants, inter alia polycyclic aromatic hydrocarbons (PAHs) and their nitrated and oxygenated derivatives. Despite their highly mutagenic and carcinogenic character, these micro-contaminants are not regulated in Euro emissions standards. This paper presents both a general discussion of the phenomenon of particulate formation in and emission from direct injection gasoline engines, as well as a wide range of results on the subject. The subject of the micro-contaminants in solid particles from modern gasoline vehicles is explored. The samples of solid particles were collected from 11 groups of vehicles according to the WLTP test methodol... [more]

In view of the main problems of the condensing heat discharge modes of the existing underground air-conditioning system, the technical scheme of using phase change heat storage modules to improve the heat storage capacity of the reservoir is proposed. By establishing a 3D flow and transient heat transfer model of the phase change reservoir, the effects of thermal property parameters, package size and arrangement of the phase change heat storage modules on the heat storage performance of the phase change reservoir were quantitatively analyzed based on three indexes: heat storage capacity per volume Δq, guaranteed efficiency coefficient η and slope of temperature rise per unit load ε. The results show that when the phase change temperature is 29 °C (23 °C increased to 33 °C) and the latent heat value is 250 kJ/kg (100 kJ/kg increased to 250 kJ/kg), Δq (110.92 MJ/m3, 112.83 MJ/m3) and η (1.22, 1.24) under both conditions are at their most, respectively, indicating that the phase change te... [more]