The farmers’ welfare and its interlinkages to energy efficiency and farm sustainability has attracted global scientific interest within the last few decades. This study examines the contribution of Agriculture 5.0 to the prosperity of the farmers in the post-pandemic era and the gradual transition to an energy-smart farm. To obtain an insight into the attributes of Agriculture 5.0 and the emerging technologies in the field, Bibliometrix analysis with the use of an R package was conducted based on 2000 data consisting of peer-reviewed articles. The data were retrieved from the Scopus database. A bibliometric approach was employed to analyze the data for a comprehensive overview of the trend, thematic focus, and scientific production in the field of Agriculture 5.0 and energy-smart farming. Emerging technologies that are part of Agriculture 5.0 in combination with alternative energy sources can provide cost-effective access to finance, weather updates, remotely monitoring, and future ene... [more]

Electrohydraulic drives consist of several nonlinear elements, and the use and design of their control system is difficult. One of the most important parameters of the industrial drive is its settling time, which characterizes their dynamics. An interesting control method, which can be used for the improvement of electrohydraulic drive properties, is the model-following control (MFC). This technique enables to ensure the good control parameters of nonlinear systems in quite an easy way. In this paper, a modification consisting of changing the oil flow factor in the reference model is proposed. This improves both the dynamics of the electrohydraulic servo drive and the adaptation to the load forces, and thus energy consumption. The article describes the application of the MFC method to control an electrohydraulic servo drive in which a special proportional valve, with an permanent magnet synchronous motor (PMSM), is used. To verify the effectiveness of this method, a theoretical descrip... [more]

To address the safety displacement-constrained control problem of maglev trains during operation, this study applied the radial-based neural network control displacement-constrained method to maglev trains based on the multi-mass-point model, and strictly limited the output of maglev train displacement and speed values to keep the overshoot within a given range. Firstly, the dynamics and kinematics of the maglev train were modeled from the perspective of multi-mass modeling. Secondly, the basic structure of the radial-based neural network was determined according to the displacement-limited constraints of the maglev train during operation, and the stability was proven by applying the control rate and output-limited priming according to the limitations. Finally, based on the displacement-limited operation control of maglev trains, the system of the radial-based neural network was simulated. The simulation results show that this method can make the displacement and velocity signals of th... [more]

Thin-walled tubes are widely used as energy-absorbing components in traffic vehicles, which can absorb part of the energy in time by using the plastic deformation of the components during collision so as to reduce the damage of the vehicle body and improve the overall safety and reliability of traffic vehicles. The prefolded design of thin-walled tube components can guide it to achieve the ideal energy dissipation performance according to the preset damage path, so the related research based on origami tubes has attracted a lot of attention. Since the geometry of the origami tubes is controlled by many parameters and stress and deformation is a complex nonlinear damage process, most of the previous studies adopted the method of case analysis to carry out numerical simulation and experimental verification of the relevant influence parameters. This paper makes a new exploration of this kind of problem and focuses on solving the related technical problems in three aspects: 1. The automati... [more]

The parabolic trough solar collector as a popular technique is widely used in solar concentrating technologies (SCTs). The solar absorber tube is the key position of the trough solar thermal power system. The internal modification of the absorber tube is one of the most interesting techniques for increasing the collector’s performance. At present, most of the methods to enhance heat transfer efficiency focus on designing alternative parabolic trough collectors (PTC) absorbers and improving the internal structure of absorption tubes. Due to the limitation of temperature range, most absorption tubes use oil as heat absorbing liquid, and very few heat absorbing tubes directly use water as working fluid. This is because water is limited by critical heat flux in high temperature environment, resulting in low heat transfer performance. In this work, we designed a new porous absorber tube with the function of allowing liquid resupply and vapor overflow from different paths, which can effectiv... [more]

The paper presents the results of laboratory tests regarding the impact of accelerated thermal ageing of cellulose−aramid insulation samples saturated with electrical-insulating synthetic ester on the polarization and depolarization current characteristics being analyzed in the time domain. In the tests, electro-technical paper from DuPontTM was used, commercially designated as NOMEX®910. Laboratory-accelerated ageing consisted of heating with air a supply of samples of not-impregnated cellulose−aramid insulation for a specified time at specified temperatures. The temperatures and the warming time were selected so as to faithfully represent the degree of the thermal degradation of the cellulose fibers that takes place during normal operation of the material in power transformers. To determine the described impact of the ageing process in the insulation samples on the dielectric properties, the Polarization and Depolarization Method was applied. In the measurements, the MIC-15k1 high re... [more]

Thermodynamic, exergetic and thermoeconomic analyses were performed on two types of double-effect LiBr−water absorption refrigeration systems (ARS) for use with a 5-kW high-temperature proton exchange membrane fuel cell (HT-PEMFC) as a heat source. Proper temperatures of the high-pressure generator, combined generator and condenser, condenser, absorber and evaporator were determined to meet the requirements of constant cooling demands for data center operations. The heat balance of the combined unit of generator and condenser in the industrial double-effect LiBr-water ARS is important for determining the flow rate of the primary vapor refrigerant from the high-pressure generator. The industrial double-effect ARS system, whose analysis has not been studied analytically, outperformed the series double-effect system and provided 6.5 kW of cooling capacity with a coefficient of performance of 0.99. The unit cost of chilled water estimated by the modified productive structure analysis (MOPS... [more]

In grid-connected photovoltaic (PV) systems, a transformer is needed to achieve the galvanic isolation and voltage ratio transformations. Nevertheless, these traditional configurations of transformers increase the weight, size, and cost of the inverter while decreasing the efficiency and power density. The transformerless topologies have become a good solution. However, the problem is that commode-mode voltage and leakage current can occur via the stray capacitors between the PV array and the ground of the inverter. Various transformerless inverters have been introduced with different techniques, such as reducing the common-mode voltage or eliminating the leakage current. Furthermore, to introduce the development of transformerless PV inverters, especially in three-phase two-level inverter systems, this paper provides a comprehensive review of various common-mode voltage reduction three-phase two-level inverters.

This article involves forecasting daily electricity consumption in Thailand. Electricity consumption data are provided by the Electricity Generating Authority of Thailand, the leading power utility state enterprise under the Ministry of Energy. Five forecasting techniques, including multiple linear regression, artificial neural network (ANN), support vector machine, hybrid models, and ensemble models, are implemented. The article proposes a hyperparameter tuning technique, called sequential grid search, which is based on the widely used grid search, for ANN and hybrid models. Auxiliary variables and indicator variables that can improve the models’ forecasting performance are included. From the computational experiment, the hybrid model of a multiple regression model to forecast the expected daily consumption and ANNs from the sequential grid search to forecast the error term, along with additional indicator variables for some national holidays, provides the best mean absolution percent... [more]

The condition of the oil and gas sector is characterized by the complication of geological settings, and there is more competition in energy markets due to the current trend towards decarbonization. These circumstances require oil and gas companies to become more flexible and improve their project economic feasibility studies. The purpose of the research was to develop a methodological approach for the economic evaluation of oil and gas projects that includes choosing and substantiating the choice of engineering solutions that can be used to make decisions on subsequent investing. A comparative analysis of various economic evaluation methods applied to oil and gas projects included the DCF model, DPNV model with modifications, binary discounting, and reverse discounting. Taking into account the specific features of oil and gas projects, the authors provide a rationale for using a risk-free rate to calculate project outflows and a combination of reverse rates to calculate inflows. In ad... [more]

A solid oxide fuel cell (SOFC) system is a kind of green chemical-energy−electric-energy conversion equipment with broad application prospects. In order to ensure the long-term stable operation of the SOFC power-generation system, prediction and evaluation of the system’s operating state are required. The mechanism of the SOFC system has not been fully revealed, and data-driven single-step prediction is of little value for practical applications. The state-prediction problem can be regarded as a time series prediction problem. Therefore, an innovative deep learning model for SOFC system state prediction is proposed in this study. The model uses a two-layer LSTM network structure that supports multiple sequence feature inputs and flexible multi-step prediction outputs, which allows multi-step prediction of system states using SOFC system experimental data. Comparing the proposed model with the traditional ARIMA model and LSTM recursive prediction model, it is shown that the multi-step L... [more]

To help the reverse Brayton cycle cool the refrigerant from 100 K to 50 K, an auxiliary generator, with a housed stator, is studied and optimized, and the influences of weights in the cost- function on the results are discussed. The power demand and adiabatic characteristics of reverse Brayton cycle expansion are analyzed, after which the optimization indexes, including output rated power, efficiency, the air gap between rotor and stator, loss, and volume, are decided. The initial model of the auxiliary generator is then constructed and the parameters to be optimized are also determined. Taking the low loss and sinusoidal back-EMF as the evaluation indexes, the single parameter optimizations of the auxiliary generator are carried out. The co-simulation of the generator and its corresponding driving circuit is investigated, with which the power generation efficiency is calculated. The global optimizations of the generator parameters are carried out using a genetic algorithm. A suitable... [more]

After over a century of internal combustion engines ruling the transport sector, electric vehicles appear to be on the verge of gaining traction due to a slew of advantages, including lower operating costs and lower CO2 emissions. By using the Vehicle-to-Grid (or Grid-to-Vehicle if Electric vehicles (EVs) are utilized as load) approach, EVs can operate as both a load and a source. Primary frequency regulation and congestion management are two essential characteristics of this technology that are added to an industrial microgrid. Industrial Microgrids are made up of different energy sources such as wind farms and PV farms, storage systems, and loads. EVs have gained a lot of interest as a technique for frequency management because of their ability to regulate quickly. Grid reliability depends on this quick reaction. Different contingency, state of charge of the electric vehicles, and a varying number of EVs in an EV fleet are considered in this work, and a proposed control scheme for fr... [more]

Stator faults are the most critical faults in induction motors as they develop quickly hence requiring fast online diagnostic methods. A number of online condition monitoring techniques are proposed in the literature to respond to such faults, including the signature analysis of the stator current, vibration monitoring, flux leakage monitoring, negative sequence components of voltage and current and sequence components monitoring based on the identification of asymmetrical behavior in a machine. Negative sequence components of voltage and current and sequence components monitoring are commonly considered for the identification of asymmetrical behavior of induction motors. Negative sequence current analysis is a sensitive technique for the detection of shorted turns as it directly measures the asymmetry produced by the fault. However, the technique is sensitive to other asymmetrical faults and disturbances, which can also produce negative sequence currents. These disturbances include se... [more]

In this study, the aerodynamic characteristics of the three-dimensional evacuated tube transportation (ETT) system based on the Reynolds-averaged Navier−Stokes κ−ω shear-stress transport turbulent model were investigated. The effects of two key parameters on the drag and flow topology of the ETT system, namely the travelling speed and ambient pressure in the tube, were studied. Compared with trains in the atmospheric environment without the tube (i.e., the open system), the ETT system shows considerable drag reduction with suitable operating parameters in the tube, particularly at a higher travelling speed range. The drag varying with the speed from subsonic to supersonic, shows various change trends at different speeds because of their distinct flow structures. The higher pressure in front of train head was observed to be reduced by choking, and a low pressure in the wake by expansion waves led to rapid increase in the drag and drag coefficient. The relationship between the drag and o... [more]

The structural parameters of an equal amplitude modulated magnetic pole is limited by the length of the air-gap. When the modulation ratio or carrier ratio is small, the spacing of permanent magnets is too large, which will lead to a worse cogging effect, and then the torque optimization effect is not satisfying. In order to improve the operation stability of a bearingless permanent magnet synchronous motor (bearingless PMSM), an unequal amplitude modulated magnetic pole structure is proposed according to the principle of magnetic pole modulation. The Taguchi method is used to optimize the structural parameters of the unequal amplitude modulated magnetic pole with the goal of reducing the torque and suspension force fluctuation. Three kinds of magnetic pole structures, named the whole magnetic pole, the equal amplitude modulated magnetic pole and the unequal amplitude modulated magnetic pole are compared and verified. The results show that the proposed structure of the unequal amplitud... [more]

Network reconfiguration is an effective way to avoid severe, large-scale power outages and to improve the resilience of active distribution networks (ADNs). Furthermore, the rapid development of distributed energy resources (DERs) provides new perspectives for network reconfiguration. In this paper, the effect of network reconfiguration and DER collaboration on ADN’s resilient restoration are studied. The applications of DERs are fully explored. In order to achieve a better resilient performance, a detailed multiperiod model considering both reconfiguration and multiple DERs is established. Some linearization techniques are used to simplify the proposed model. Then, we build a rolling horizon optimization framework to solve the model. The framework eliminates the adverse effect of prediction errors and speeds up the calculation. By introducing predictions into strategy determination, the framework achieves a better restoration effect than the traditional greedy method. The proposed fra... [more]

The Special Issue “Electrified Powertrains for a Sustainable Mobility: Topologies, Design and Integrated Energy Management Strategies” has been proposed with the main objective of contributing to the sustainable mobility agenda through enhanced scientific and multi-disciplinary topics, aimed at addressing concerns and real possibilities in the achievement of a greener mobility [...]

Building system operation faces the challenge of reducing energy use and implementing a demand response, which can be defined as a temporary modification in energy loads affecting dynamic energy price and reliability information. The heating, ventilation, and air-conditioning (HVAC) system in buildings provides an opportunity for implementing demand response strategies due to the thermal inertia in building zones. However, an HVAC-based demand response is not a prevalent strategy in actual facility management due to the lack of understanding among building operators of their facilities and occupants. Herein, we focus on developing a better understanding of the occupant side by obtaining a reliable prediction of occupants’ thermal satisfaction. We evaluate the prediction performance of a probabilistic model provided in our previous paper using a case study with a subset of the ASHRAE Global Thermal Comfort Database II. The influence of a better prediction of thermal satisfaction on the... [more]

Over the last few years, improving power extraction from the wind energy conversion system (WECS) under varying wind speeds has become a complex task. The current study presents the optimum maximum power point tracking (MPPT) control approach integrated with neural network (NN)-based rotor speed control and pitch angle control to extract the maximum power from the WECS. So, this study presents a reference model adaptive control (RMAC) for a direct-drive (DD) permanent magnet vernier generator (PMVG)-based WECS under real wind speed conditions. Initially, the RMAC-based rotor speed tracking control is presented with adaptive terms, which tracks a reference model that guarantees the expected exponential decay of rotor speed error trajectory. Then, to reduce the wind speed measurement errors, a recurrent neural network (RNN)-based training model is presented. Moreover, the asymptotic stability of the proposed control method is mathematically proven by Lyapunov theory. In addition, the pit... [more]

Total-factor energy efficiency (TFEE) is widely used to measure energy efficiency under the data envelopment analysis (DEA) framework, but the efficiencies obtained from DEA are structurally biased upward, and thus TFEE tends to overestimate energy efficiency. This research thus applies the bootstrapped DEA approach to correct the bias of TFEE. Using a dataset consisting of 30 provinces of China in the period 2016−2019, the bootstrapped-based test supports technology with variable returns to scale. The biased-corrected TFEE also indicates that energy consumption on average can be scaled down by 42.36%, rather than the biased value of 19.4%. The bootstrapped clustering partitions provinces into three groups: Cluster 1, with Guizhou as the representative medoid, includes half of the superior coastal provinces in terms of actual energy consumption and TFEE and half of the competitive inland provinces, whereas Cluster 3 outperforms Cluster 2 in terms of TFEE, but the actual energy consumpt... [more]

In these days, when complex, IT-controlled systems have found their way into many areas, models and the data on which they are based are playing an increasingly important role. Due to the constantly growing possibilities of collecting data through sensor technology, extensive data sets are created that need to be mastered. In concrete terms, this means extracting the information required for a specific problem from the data in a high quality. For example, in the field of condition monitoring, this includes relevant system states. Especially in the application field of machine learning, the quality of the data is of significant importance. Here, different methods already exist to reduce the size of data sets without reducing the information value. In this paper, the multidimensional binned reduction (MdBR) method is presented as an approach that has a much lower complexity in comparison on the one hand and deals with regression, instead of classification as most other approaches do, on... [more]

Reactive dyeing is primarily used in the textile industry to achieve a high level of productivity for high-quality products. This method requires heating a large amount of freshwater for dyeing and cooling for the biological treatment of discharged wastewater. If the heat of the wastewater discharged from the textile industry is recovered, energy used for heating freshwater and cooling wastewater can be significantly reduced. However, the energy efficiency of this industry remains low, owing to the limited use of waste heat. Hence, this study suggested a cost-optimal heat exchanger network (HEN) in a heat pump-assisted textile industry wastewater heat recovery system with maximizing energy efficiency simultaneously. A novel two-step approach was suggested to develop the optimal HEN in heat pump-assisted textile industry wastewater heat recovery system. In the first step, the system was designed to integrate the heat exchanger and heat pump to recover waste heat effectively. In the seco... [more]

The Qiongdongnan (QDN) basin in the northwestern South China Sea has been shown to be rich in petroleum resources and has significant exploration potential for deepwater oil and gas resources. Therefore, it is of great significance to clarify the gas accumulation process in the deepwater area of the QDN basin, specifically the Y8 area. In this study, fluid inclusion analysis, including the identification and localization of fluid inclusions under a microscope, laser Raman spectrum analysis and homogenization temperature (Th) measurement, reconstruction of the thermal evolution burial history, geochemical analysis, and typical seismic section analysis were comprehensively used to interpret the gas accumulation process of the Y8 area. The laser Raman spectrum analysis results of fluid inclusions verified the existence of methane and confirmed the hydrocarbon charging event in this area. However, the Th of fluid inclusions in the reservoir, the mixed compositions of hydrothermal compositi... [more]

Wind energy is expected to play a significant role in meeting emission targets over the next 20 years. Offshore wind turbines in deep water (>150 m) must be developed due to resource quality, environmental, and activity constraints. Floating offshore wind turbines (FOWT) will be the best technology for reaching these targets. The dynamic submarine electrical cable (DSEC) is a key component of FOWT. Its electric insulation system is intended to withstand a maximum conductor temperature of 90 °C. However, biofouling growth, particularly mussels, can modify the heat transfer around the cable and thus its maximum conductor temperature, as well as temperature fluctuation, affecting the fatigue lifetime. In our work we estimate the effective thermal conductivity of mussels of various ages, as well as the heat transfer coefficient of the water around them. The results revealed that the effective thermal conductivity of juvenile mussels is lower than that of mix (both juvenile and adult) and o... [more]