The scarcity of inertial resources in the new AC−DC hybrid grids makes the grid frequency prone to fluctuation. In this paper, the relationship between the grid-side and load-side characteristics of the power router is constructed. By adjusting the port load parameters, the load power can respond quickly to the fluctuation of the grid frequency, thereby realizing rapid support of the grid frequency. Firstly, two kinds of mathematical models for sensitivity identification of load characteristics, variable voltage and variable frequency, are established to calculate the characteristic parameters of a multi-port load. The allocation rules of port power and allocation coefficients are designed according to the parameters. A frequency modulation control method that matches the load response capability of the multi-port router is proposed. Then, taking into consideration the uncertainty of load group characteristics and power, a variable coefficient frequency modulation control strategy for... [more]

The failure of wellbore sealing will cause leakage of greenhouse gases, such as carbon dioxide and methane, which will harm oil and gas recovery and environmental safety. Cementing is an important part of wellbore sealing. Only good cementing can keep the wellbore seal for a long time and improve the well life. In this study, we considered the construction of a horizontal shale oil well in eastern China as the background and analysed the rheological properties of the annulus fluid. We developed a displacement motion model and a calculation model for the annulus dynamic equivalent circulation density, and numerical simulations were used to study the impact of the dosage and injection sequence of the pad fluid on the displacement efficiency and annulus dynamic equivalent circulation density. The results show that when the pad fluid is composed completely of flushing fluid, the displacement performance is better than that of the spacer. By increasing the dosage of the flushing fluid from... [more]

Recently, renewable energy resources (RESs) have been utilized to supply electricity to remote areas, instead of the conventional methods of electrical energy production. In this paper, the optimal design of a standalone hybrid RES comprising photovoltaic (PV), wind turbine (WT), and biomass sources as well as an energy storage system, such as a hydro-pumped storage system, is studied. The problem of the optimal sizing of the generating units in the proposed energy system is formulated as an optimization problem and the algorithms heap-based optimizer (HBO), grey wolf optimizer (GWO), and particle swarm optimization (PSO) are applied to achieve the optimal sizing of each component of the proposed grid-independent hybrid system. The optimization problem is formulated depending on the real-time meteorological data of the Ataka region on the Red Sea in Egypt. The main goal of the optimization process is to minimize the cost of energy (COE) and the loss of power supply probability (LPSP),... [more]

The eddy current brake (ECB) is an electromechanical energy conversion device that can be used as a load emulator to load a motor according to the intended load scenario. However, conducting an analysis in the time domain is difficult due to its complex behavior involving mechanical, electrical, and magnetic phenomena. The challenges with the time domain analysis of the ECB require new modeling approaches that provide reliability, robustness, and controllability over a wide speed interval. If the ECB can be modeled with high accuracy, it can be controlled like a load emulator that can simulate nonlinear industrial loads. This paper describes a neuromodeling approach taken to develop an ECB. The nonlinear characteristic of the brake system was modeled with a high performance by using an artificial neural network (ANN), which is a potent nonlinear system identification tool. Several characteristics of a designed and optimized brake system undergoing various excitation currents in whole s... [more]

This manuscript provides an overview of the most commonly-produced bitumen roofing sheets, focusing on the types of reinforcements used for their production and the reinforcements’ effects on the durability of tensile mechanical properties of roofing sheets under thermal loads. The paper includes the analysis of working conditions of roof coverings in the mid-European transitional climate, i.e., exposed to temperatures passing through 0 °C for three seasons in a year, periodic exposure to negative temperatures reaching −15 °C and positive temperatures up to +70 °C, justifying the above-mentioned emphasis on thermal load. It draws attention to technical problems related to the cooperation of roofing sheets with roofing substrates, with particular emphasis on concrete substrates. For the purposes of the work, the analyses were carried out with regard to the assessment of the service life of roof coverings made of various reinforcements working in conditions of variable temperatures and t... [more]

The challenge of achieving net-zero carbon emissions in the shipping sector is a pressing issue that is yet to be fully overcome. While new fuels and technologies hold promise for the future, they are not currently viable solutions on a large scale in the short-term. One strategy that is being considered as a way to reduce CO2 and CO emissions in the immediate future is carbon capture technology. Additionally, the possibility of a carbon tax being implemented in the future further strengthens the case for the adoption of this technology, which is already quite mature and in use in industries, although it has yet to be developed in the maritime sector. In this paper, the authors start from the definition of carbon capture technology to provide a technical overview of the solutions that are currently available to the maritime sector. Given the absolute innovation of such systems for application on board ships, the authors studied their installation and developed appropriate schemes to il... [more]

In this paper, we propose a concise but general two-dimensional model based on the penetration model in order to simulate the heat and mass transfer and drying kinetics of sludge in the paddle dryer. The sludge control equations were developed to simulate the heat and mass transfer of sludge and the penetration model was introduced to describe the mixing of sludge. Compared to the experimental results in the existing literature, the drying kinetics simulated simulated by the present model were in good agreement with the experimental data under various operation conditions. The effects of four key parameters on drying kinetics in the paddle dryer were studied. The results showed that the water content increased with the increase of sludge flowrate and the decrease of wall temperature and sludge density. Furthermore, the stirring velocity had little effect on the drying kinetics of the sludge. The present study contributes to the better understanding of the sludge drying kinetics and pro... [more]

In high voltage insulation systems, dielectric materials may be exposed to partial discharges (PD), which can lead to equipment failures and safety hazards. Therefore, it is crucial to detect and characterize PD activity on the surface of insulation systems. Techniques such as radio frequency signal analysis and ultraviolet radiation emission detection are commonly used for this purpose. In this research study, an analysis was conducted on the signals emitted by surface PD in the radio frequency and ultraviolet radiation emission ranges. The goal was to indicate possible directions for further basic research aimed at building a knowledge base and improving measurement methods. The analysis confirmed that radio frequency and ultraviolet signal analysis can provide important information about the activity and location of PD on the surface, including the intensity and nature of PD. The experimental investigation presented in this paper provides valuable insights into the potential for usi... [more]

The installed wind power capacity is growing worldwide. Remote condition monitoring of wind turbines is employed to achieve higher up-times and lower maintenance costs. Machine learning approaches can be used for detecting developing faults in wind turbines in their earlier occurrence. However, training fault detection models may require large amounts of past and present data. These data are often not available or not representative of the current operation behaviour. These data can be acquired with supervisory control and data acquisition systems. Note also that newly commissioned wind farms lack data from previous operation, whilst older installations may also lack representative working condition data as a result of control software updates or component replacements. After such events, a turbine’s operation behaviour can change significantly so its data are no longer representative of its current behaviour. Therefore, this paper shows that cross−turbine transfer learning can improve... [more]

Perovskite Solar Cells (PSCs) have attracted attention due to their low cost, easy solution processability, high efficiency, and scalability. However, the benchmark expensive hole transport material (HTM) 2,2′,7,7′-tetrakis[N, N-di(4-methoxyphenyl)amino]-9,9′-spirobifluorene (Spiro-MeOTAD), which is traditionally solution-processed with toxic solvents such as chlorobenzene (CB), dichlorobenzene (DCB), or toluene, is a bottleneck. To address this issue, this work investigates the implementation of Zn(II), Cu(II), or Co(II) tetra-tert-butylphthalocyanines (TBU4-Cu, TBU4-Zn, TBU4-Co), established macrocyclic derivatives whose synthesis and processing inside the devices have been redesigned to be more environmentally sustainable and cost-effective by substituting conventional solvents with greener alternatives such as anisole, propane-1,2-diol, and their mixture, as dopant-free HTMs in planar n-i-p PSCs. The anisole-processed HTMs provided power conversion efficiencies (PCE) up to 12.27% f... [more]

As a result of the dissemination of the sustainability concept, social disclosures have become an important area of non-financial reporting, and the energy sector is no exception. The purpose of our article is a multi-faceted evaluation of sustainability reports published by companies operating in the Polish energy sector, from the perspective of social disclosures. The study involved the Polish listed companies that made up the WIG-Energia index. The time scope of the study covers the 2017−2021 period. In total, 54 non-financial reports were analyzed. In the first place, a comparative analysis was carried out to assess the social disclosures made by the WIG-Energia companies against the background of the biggest and the most liquid (blue chip) WIG20 companies. All the applied tools: ESG rating, NFR_S index, and multidimensional data visualization, have confirmed that the energy companies year by year have been presenting larger and larger extents of social disclosures. At the same tim... [more]

Penetration of wind power plants (WPPs) in the electric power system will complicate the system load flow analysis. Consequently, the traditional load flow algorithm can no longer be used to find the solution to the load flow problem of such a system. This paper proposes a doubly fed induction generator (DFIG)-based WPP model for a load flow analysis of the electric power system. The proposed model is derived based on the power formulations of the WPP—namely, DFIG power, DFIG power loss, and WPP power output formulas. The model can be applied to various DFIG power factor operating modes. In the present paper, applications of the proposed methods in two representative electric power systems (i.e., IEEE 14-bus and 30-bus systems) have been investigated. The investigation results verify the proposed method’s capability to solve the load flow problem of the system embedded with DFIG-based variable-speed WPPs.

The expansion of end-to-end Industry 4.0 technologies in various industries has caused a technological shock in the mineral resource sector, wherein itsdigital maturity is lower than in the manufacturing sector. As a result of the shock, the productivity and profitability of raw materials extraction has begun to lag behind the industries of its deep processing, which, in the conditions of volatile raw materials markets, can provoke sectoral crises. The diffusion of Industry 4.0 technologies in the mining sector (Mining 4.0) can prevent a technological shock if they are implemented in all segments, including quarrying (Surface Mining 4.0). The Surface Mining 4.0 technological platform would connect the advanced achievements of the Fourth Industrial Revolution (end-to-end digital artificial intelligence technologies, cyber-physical systems and unmanned production with traditional geotechnology) without canceling them, but instead bringing them to a new level of productivity, resource con... [more]

In recent years, renewable energy (RE) has shown promise as a sustainable solution to the rising energy demand worldwide. Photovoltaic (PV) technology has emerged as a highly viable RE alternative. The majority of PV schemes use specific PV models with specified parameters. This study proposes a PV model with generic specifications, a PV array, a DC/DC converter, a DC/AC inverter, maximum power point tracking (MPPT), and grid synchronization using a feedback control system under the MATLAB/Simulink environment. Various MPPT techniques have been adapted to track the PV’s maximum power point (MPP); however, there are various uncertainties. To address these challenges, this paper presented a perturb and observe (P&O) strategy to track the MPP of PV systems reliably. The MPP of a PV system varies according to meteorological order, such as solar radiation and cell temperature. The MPPT primarily gathers the maximum current and voltage of the PV array and provides them to the load using a bo... [more]

The in-vessel Loss-of-Coolant Accident (LOCA) is one of the design basis accidents in the design of the EU DEMO tokamak fusion reactor. System-level codes are typically employed to analyse the evolution of these transients. However, being based on a lumped approach, they are unable to quantify localised quantities of interest, such as local pressure peaks on the vacuum vessel walls, to which the failure criteria are linked. To calculate local quantities, the 3D nature of the phenomenon needs to be considered. In this work, a 3D transient model of the in-vessel LOCA from a water-cooled blanket is developed. The model is implemented in the commercial CFD software STAR-CCM+. It simulates the propagation of the water jet in the vessel from the beginning of the accident, thus accounting for the phase change of the water, i.e., from the pressurised liquid phase to the vapour phase inside the vessel, being the latter at a much lower pressure than in the blanket coolant pipes. Due to the large... [more]

In order to accurately calculate the geometric characteristics of the twin-screw compressor and obtain the optimal profile parameters, a calculation method for the geometric characteristics of twin-screw compressors was proposed to simplify the profile parameter design in this paper. In this method, the database of geometric characteristics is established by back-propagation (BP) neural network, and the genetic algorithm is used to find the optimal profile design parameters. The effects of training methods and hidden layers on the calculation accuracy of neural network are discussed. The effects of profile parameters, including inner radius of the male rotor, protection angle, radius of the elliptic arc, outer radius of the female rotor on the comprehensive evaluation value composed of length of the contact line, blow hole area and area utilization rate, are analyzed. The results show that the time consumed for the database established by BP neural network is 92.8% shorter than that of... [more]

Recent research has shown an increasing interest in wireless power transfer (WPT) technology for drone batteries. The inconvenience of wired charging, especially for drones, is a huge obstacle. In this research project, a WPT platform was proposed by applying four transmitting coils and a single receiving coil. To meet the industrial standards required for transmitter Tx and receiver Rx, a calculation of the parameters was implemented. An H-bridge MOSFET was used as a DC−AC inverter, a bridge diode was used as an AC−DC rectifier, and a Pi low pass filter was added to the receiver circuit design to filter the high-frequency noise. Experimental investigations were conducted to study the maximum power and power efficiency of the coil’s alignment. The focus of this article was to design and fabricate workable multiple-transmitter coils and a single-receiver coil for a wireless power transfer system, in order to charge a 3S LiPo drone’s battery. It not only covers an overview of wireless po... [more]

This study explored underground biomethanation as a means to achieve carbon neutrality and promote carbon circular utilization by methanating CO2 and hydrogen-rich industrial waste gas in depleted natural gas reservoirs (MECHIG). This approach not only aids the development of carbon capture, utilization, and storage (CCUS) technologies, but also effectively processes industrial waste gas, thereby reducing pollutant emissions. In order to verify the feasibility of the MECHIG concept, this study builds upon the analysis of the MECHIG process overview and employs the net present value (NPV) analysis method to investigate its economic viability. Additionally, the study conducts a sensitivity analysis on six factors, namely methanation efficiency, facility site investment, hydrogen content in waste gas, natural gas prices, operation and maintenance (O&M) investment, and CO2 capture and injection prices. The results indicate the following: (1) Under the baseline scenario, the NPV of the MECH... [more]

The need for and interest in very-short-term load forecasting (VSTLF) is increasing and important for goals such as energy pricing markets. There is greater challenge in predicting load consumption for residential-load-type data, which is highly variable in nature and does not form visible patterns present in aggregated nodal-type load data. Previous works have used methods such as LSTM and CNN for VSTLF; however, the use of DNN has yet to be investigated. Furthermore, DNNs have been effectively used in STLF but have not been applied to very-short-term time frames. In this work, a deep network architecture is proposed and applied to very-short-term forecasting of residential load patterns that exhibit high variability and abrupt changes. The method extends previous work by including delayed load demand as an input, as well as working for 1 min data resolution. The deep model is trained on the load demand data of selected days—one, two, and a week—prior to the targeted day. Test results... [more]

In this paper, an asymmetric rotor interior permanent magnet (ARIPM) motor with high demagnetization prevention capability and robust torque performance is proposed. The key contribution of this paper lies in two aspects. On the one hand, a novel asymmetric rotor with a shifted magnet axis is proposed to improve the demagnetization prevention capability and torque density. In order to obtain a proper asymmetric rotor topology of the ARIPM motor, the multi-physical performances, especially the PM demagnetization characteristics of five types of PM arrangements, are analyzed. Furthermore, an asymmetric rotor with V- and VV-type PM arrangement is preliminarily designed, considering the multi-physical performance balance and the potentially high anti-demagnetization ability. On the other hand, it is found that the asymmetric rotor structure can not only improve the nominal value of motor performance but also can enhance the resistance to the influence of manufacturing uncertainties. Theref... [more]

The energy stored in fossil fuels is released through combustion and is a fundamental process in the production of cement. The negative aspect of this combustion is the emission of greenhouse gases and dust. This paper presents the results of a study conducted within a cement plant in Ożarów (south-eastern Poland). The chemical properties (selected elements) in the needles of Scots pine (Pinus sylvestris L.) were determined. The needle surface was scanned using a scanning electron microscope (SEM) and was characterised in terms of chemical composition through energy dispersive spectroscopy (EDS). The concentrations of selected analytes in the biennial needles formed the following descending sequence: Fe > Al > Mn > Zn > Cu > Pb > Cr > Ni. SEM/EDS microphotographs showed the presence of particles of varying shape, size and chemical composition indicative of anthropogenic origin.

This paper proposes correlation equations of heat transfer and pressure drop for the design and operation of tunnel kilns loaded with lattice brick settings of different geometrical parameters in the form of Nusselt number and friction factor. The developed correlation equations considered parameters that were not investigated in previous studies, such as the relative roughness of the bricks and the stack channels, and they also extended the Reynolds numbers to a practical range that was not covered before in a simple, practical form. The correlation equations are valid for Reynolds number between 125 and 10,200, Prandtl number between 0.68 and 0.73, brick’s relative roughness between 0.23 and 0.93, voidage fraction between 0.48 and 0.653, and the geometrical parameters of the tested lattice brick settings. The achieved correlations of the Nusselt number and the friction factor are well compared with the available correlations in the literature in their valid range of parameters. It is... [more]

In this research sustainable refrigerants are tested as filler gases in Transparent Thermal Insulation (TTI) for the first time. These are compared with pig fat, a readily available material with good thermal inertia that is proposed as an organic phase change material (PCM). The aim of this paper is to compare the thermal behaviour of a Hybrid Air Conditioning System (HACS) with TTI filled with R134a, R1233zd and a pig-fat-based PCM. Numerical simulations using the OPAQUE 3 program and two online platforms are used to evaluate the possible application of TTI and PCM as passive systems. Additionally, three TTI models are used to simulate the heat transfer processes of TTI, PCM and R134a. The velocity of the flow in the air gap is also analysed numerically in both laminar and turbulent states. For the assessment, infrared thermographic imagery is used to measure the temperatures in the HACS, giving values of 46.17 °C by day and 38.05 °C at night. The results show that the heat loss and... [more]

The solid oxide fuel cell (SOFC) system is complicated because the characteristics of gas, heat, and electricity are intricately coupled. During the operation of the system, problems such as frequent failures and a decrease in the stack’s performance have caused the SOFC system to work less well and greatly shortened the SOFC’s practical life. As such, it is essential to accurately forecast its remaining useful life (RUL) to make the system last longer and cut down on economic losses. In this study, both model-based and data-driven prediction methods are used to make predictions about the RUL of SOFC. First, the linear degradation model of the SOFC system is established by introducing degradation resistance as the index of health status. Using the Kalman filtering (KF) method, the health status of SOFC is evaluated online. The results of the health state estimation indicated that the KF algorithm is accurate enough to provide a good basis for the model-based RUL prediction. Then, a lon... [more]

The main objective of this paper is to propose two innovative monitoring methods for electrical disturbances in low-voltage networks. The two approaches present a focus on the classification of voltage signals in the frequency domain using machine learning techniques. The first technique proposed here uses the Fourier transform (FT) of the voltage waveform and classifies the corresponding complex coefficients through a multilayered neural network with multivalued neurons (MLMVN). In this case, the classifier structure has three layers and a small number of neurons in the hidden layer. This allows complex-valued inputs to be processed without the need for pre-coding, thus reducing computational cost and keeping training time short. The second technique involves the use of the short-time Fourier transform (STFT) and a convolutional neural network (CNN) with 2D convolutions in each layer for feature extraction and dimensionality reduction. The voltage waveform perturbations taken into con... [more]