The need for a greener and more sustainable energy system evokes a need for more extensive energy system transition research. The penetration of distributed energy resources and Internet of Things technologies facilitate energy system transition towards the next generation of energy system concepts. The next generation of energy system concepts include “integrated energy system”, “multi-energy system”, or “smart energy system”. These concepts reveal that future energy systems can integrate multiple energy carriers with autonomous intelligent decision making. There are noticeable trends in using the agent-based method in research of energy systems, including multi-energy system transition simulation with agent-based modeling (ABM) and multi-energy system management with multi-agent system (MAS) modeling. The need for a comprehensive review of the applications of the agent-based method motivates this review article. Thus, this article aims to systematically review the ABM and MAS applica... [more]

Compared with film condensation, dropwise condensation based on droplet growth can significantly improve the condensing equipment’s water collection and thermal efficiency in the vapor condensate system. Therefore, as a critical behavior affecting the evolution of dropwise condensation, research on droplet growth is of great significance to further understanding the evolutionary characteristics and heat transfer mechanism of dropwise condensation. In this paper, a model for simulating the entire evolution process of dropwise condensation is improved and constructed, and the evolution process of dropwise condensation with different condensation nucleus densities on the vertical wall is simulated based on certain assumptions. Moreover, parameters such as evolution rate and size contribution are proposed to measure droplet growth’s influence on the evolution process of dropwise condensation. In the simulation, the Cassie model was used to describe the condensation growth of droplets. The... [more]

Lightning represents one of the most critical issues for electrical infrastructure. In dealing with overhead distribution line systems, indirect lightning strikes can lead to induced voltages overcoming the critical flashover value of the line, thus damaging the insulators. The computation of lightning-induced voltages requires the modeling of the lightning current, the evaluation of the lightning electromagnetic fields and the solution of the field-to-line coupling equations. The numerical calculation of the lightning electromagnetic fields is time-consuming and is strongly dependent on the lightning channel modeling and soil properties. This article presents a review of the most widely adopted methods to calculate the lightning electromagnetic fields, starting from the classical formulation, which requires numerical integration, and highlighting the most effective approaches that have been developed to reduce computational effort. This is done first for the case of a perfectly conduc... [more]

Most of the practical inductive power transfer (IPT) systems are the ones with variable coupling coefficients and loads. The output voltage, current and power are affected by the variation in coupling coefficient and load. In this paper, a novel approach based on a nonlinear resonator is proposed to obtain stable output voltage, which is independent of coupling coefficient and load variation. First, the theory and properties of nonlinear resonators are analyzed by Duffing equation. Then, a nonlinear IPT system with a magnetic saturation inductor is proposed, and the saturable inductor modeling and its effect on system performance are further studied. Finally, the experimental prototype is built to validate the effectiveness of the nonlinear IPT system. The experimental results show that when the coupling coefficient varies from 0.32 to 0.24 and the load resistance varies from 80Ω to 120Ω, the system works in a nonlinear state, the output voltage ripple is 1.77%, and the overall efficie... [more]

The perovskite solar cell has recently gained momentum within the renewable energy industry due to its unique advantages such as high efficiency and cost-effectiveness. However, its instability remains a challenge to its commercialization. In this study, a singlet fission material, namely tetracene, is coupled with the perovskite solar cell to simulate its effect on the solar cell. The amount of thermalization loss and the temperature of the perovskite layer are simulated and analyzed to indicate the mechanism’s effectiveness. We found that coupling the tetracene layer resulted in a drastic reduction in thermalization loss and a slower slope in perovskite layer temperature. This indicates that tetracene would stabilize the perovskite solar cell and minimize its potential losses. The thickness of the solar cell layers is also analyzed as a factor of the overall effectiveness of singlet fission on solar cells.

Earth−rock dams are typical soil−rock mixtures with high heterogeneity. Mastering the effect of dam heterogeneity on seismic wavefields is the premise of accurately detecting hidden risks in dams. In this paper, based on the soil−rock mixture characteristics of actual dams, a soil−rock mixture model that can reflect the heterogeneity of dams is established through local segmentation and reassignment of random disturbances. The influence of local area size on model heterogeneity is described. The seismic wavefield in a soil−rock mixture dam is numerically simulated through a staggered-grid finite-difference algorithm with second-order accuracy in time and sixth-order accuracy in space. Then, the effect of dam heterogeneity on effective wavefields is analyzed. The results show that the heterogeneity of the earth−rock dam can lead to scattered waves in the seismic wavefield, and the scattered waves are mainly generated by Rayleigh surface waves. In the seismic record, scattered waves with... [more]

Since P.O. Fanger proposed PMV, it has been the most widely used index to estimate thermal comfort. However, in some cases, it is challenging to measure all six parameters within indoor spaces, which are essential for PMV estimation; a couple of parameters, such as Clo or Met, tend to show a large deviation in accuracy. For these reasons, several studies have suggested methods to estimate PMV but their accuracies were significantly compromised. In this vein, this study proposed a way to reduce the dimensions of parameters for PMV prediction utilizing the machine learning method, in order to provide fast PMV calculations without compromising its prediction accuracy. Throughout this study, the most influential features for PMV were pinpointed using PCA, Best Subset, and the Gini Importance, with each model compared to the others. The results showed that PCA and ANN achieved the highest accuracy of 89.70%, and the combination of Best Subset and Random Forest showed the fastest prediction... [more]

Oxygen lances are key equipment for copper converters. The effect of the lance arrangement on the mixing of a gas−slag two−phase is discussed using numerical simulation and experimental verification with a water model, and the stirring characteristics enhanced by variable−velocity blowing are explored. The results showed that the single−row lance arrangement (SA) increased the average velocity in the slag phase by 17.93% and reduced the disturbance to the metal phase by 27.78% compared to the double−row lance arrangement (DA). Compared to the constant−velocity blowing system (CSB), the sine−wave blowing system (SWB) and rectangular−wave blowing system (RWB) increased the average velocity in the slag phase by 24.03% and 13.96%, respectively, and reduced the proportion of the low−velocity area by more than 46.2%. The velocity imbalance in the SA local area enhances the mixing of the gas−slag two−phase. The variable−speed blowing improves the mass transfer and mixing effect.

Sustainable energy development requires environment-friendly energy-generating methods. Pricing system constraints influence the efficient use of energy resources. Real-Time Pricing (RTP) is theoretically superior to previous pricing systems for allowing demand response (DR) activities. The DR approach has been useful for correcting supply−demand imbalances as technology has evolved. There are several systems for determining and controlling the DR. However, most of these solutions are unable to control rising demand or forecast prices for future time slots. This research provides a Real-Time Pricing DR model for energy management based on deep learning, where the learning framework is trained on demand response and real-time pricing. The study data in this article were taken from the Australian Energy Market Operator (AEMO), and the learning framework was trained over 17 years of data to forecast the real future energy price and demand. To investigate the suggested deep learning-based... [more]

Due to stringent emission regulations, it is of practical significance to understand cycle-to-cycle variations in the combustion of fossil or renewable fuels to reach future emission regulations. The present study aims to conduct a parametric investigation to analyse the influence of the valve lift and different mass flows of an inlet valve of the test engine “Flex-OeCoS” on the flow structures. To gain a deeper understanding of the flow behaviour, an optical test bench for 2D Particle Image Velocimetry (PIV) and a Large Eddy Simulation (LES) are used. Turbulence phenomena are investigated using Proper Orthogonal Decomposition (POD) with a quadruple decomposition and the Reynolds stress transport equation. The results show good agreement between the PIV and LES. Moreover, the main flow structures are primarily affected by valve lift while being unaffected by mass flow variation. The turbulent kinetic energy within the flow field increases quadratically to the mass flow and to the decre... [more]

The temperature effect caused by high slip has an important influence on the operation performance and reliability of magnetic coupling. Taking the self-developed single disk asynchronous magnetic coupling as the research object, the heat loss equation of the magnetic coupling is established. Based on the three-dimensional transient magnetic field simulation model of the magnetic coupling, the eddy current loss, torque, and eddy current distribution law of the magnetic coupling are obtained through simulation. The space flow field and structure temperature field distribution of the magnetic coupling are analyzed by using the fluid-thermal coupling simulation method, and the heat dissipation coefficient and temperature distribution law of the structure surfaces such as copper disk, the back lining yoke iron disk, and the aluminum disk are obtained. The test platform was built to test the torque and temperature of the magnetic coupling. The results show that the error between the test an... [more]

Shale oil stored in the shale system occurs mainly in adsorbed and free states, and ascertaining the amount of adsorbed crude oil in shale is a method of ascertaining its free oil content, which determines the accuracy of shale oil resource evaluation. Both inorganic minerals and kerogen have the ability to adsorb crude oil, but there is controversy surrounding which plays the greatest part in doing so; clarifying this would be of great significance to shale oil resource evaluation. Therefore, in this study, the evolution states of inorganic minerals and kerogen in shale were changed using pyrolysis, and the adsorbents were prepared for crude oil adsorption experiments, to explore the effects of inorganic minerals and kerogen on the crude oil adsorption of shale. The results showed that the differences in kerogen’s structural units and content in organic-rich shale (TOC = 1.60−4.52%) had no obvious effects on its crude oil adsorption properties. On the contrary, inorganic minerals, as... [more]

Power transformers play a crucial role in maintaining the stability and reliability of energy systems. Accurate moisture assessment of transformer oil-paper insulation is critical for ensuring safe operating conditions and power transformers’ longevity in large interconnected electrical grids. The moisture can be predicted and quantified by extracting moisture-sensitive dielectric feature parameters. This article suggests a deep learning technique for transformer moisture diagnostics based on long short-term memory (LSTM) networks. The proposed method was tested using a dataset of transformer oil moisture readings, and the analysis revealed that the LSTM network performed well in diagnosing oil insulation moisture. The method’s performance was assessed using various metrics, such as R-squared, mean absolute error, mean squared error, root mean squared error, and mean signed difference. The performance of the proposed model was also compared with linear regression and random forest (RF)... [more]

Porous carbons as solid adsorbent materials possess effective porosity characteristics that are the most important factors for gas storage. The chemical activating routes facilitate hydrogen storage by adsorbing on the high surface area and microporous features of porous carbon-based adsorbents. The present research proposed to predict H2 storage using four nature-inspired algorithms applied in the random forest (RF) model. Various carbon-based adsorbents, chemical activating agents, ratios, micro-structural features, and operational parameters as input variables are applied in the ML model to predict H2 uptake (wt%). Particle swarm and gray wolf optimizations (PSO and GWO) in the RF model display accuracy in the train and test phases, with an R2 of ~0.98 and 0.91, respectively. Sensitivity analysis demonstrated the ranks for temperature, total pore volume, specific surface area, and micropore volume in first to fourth, with relevancy scores of 1 and 0.48. The feasibility of algorithms... [more]

The present study focused on the analysis of a new geometrical modification of the conventional zig-zag channel for Printed Circuit Heat Exchangers. The research was carried out using OpenFOAM and Salome software, which were used for the CFD analysis and the construction of the computational domain. For the development of the study, three types of channel geometries were defined: a modified zig-zag channel, a conventional zig-zag channel, and a straight channel. The results show that the modified zig-zag channel achieves better thermal hydraulic performance compared to that of the conventional zig-zag channel, evidenced by a 7.6% increase in the thermal performance factor. The modified zig-zag channel proposed in the research caused a 1.5% reduction of the power consumption of supercritical Brayton cycle compressors. Additionally, the modified zig-zag channel achieves a maximum efficiency of 49.1%, which is 1.5% higher compared to that of the conventional zig-zag channel. The above res... [more]

The lead halide-based perovskite solar cells have attracted much attention in the photovoltaic industry due to their high efficiency, easy manufacturing, lightweight, and low cost. However, these lead halide-based perovskite solar cells are not manufactured commercially due to lead-based toxicity. To investigate lead-free inorganic perovskite solar cells (PSCs), we investigated a novel Cs3Bi2I9-based perovskite configuration in SCAPS-1D software using different hole transport layers (HTLs). At the same time, WS2 is applied as an electron transport layer (ETL). Comparative analysis of the various design configurations reveals that ITO/WS2/Cs3Bi2I9/PEDOT:PSS/Au offers the best performance with 20.12% of power conversion efficiency (PCE). After optimizing the thickness, bandgap, defect density, and carrier density, the efficiency of the configuration is increased from 20.12 to 24.91%. Improvement in other performance parameters such as short circuit current (17.325 mA/cm2), open circuit v... [more]

The fracture field and permeability distribution model of comprehensive working face goaf was integrated upon the theoretical examination to investigate the fracture field distribution law of goaf and gas migration and accumulation characteristics, and this model has been applied to the mathematical model of gas migration and accumulation in goaf. The ANSYS FLUENT numerical simulation software was used to obtain the characteristics of gas migration and accumulation in goaf and its influencing factors and analyze the applicability of solving the features of gas migration and proliferation using the porosity model of layer division in goaf. The results were as follows: the porosity around the caving zone was a little big, whereas the porosity in the middle was a little small. The porosity was almost equal along the inclination and strike in a symmetrical distribution. The porosity occurred at the fracture zone with an “O” shape. As the gob layer height increased, the porosity tended to b... [more]

The need for a “smarter” energy grid infrastructure, with the large-scale integration of renewables and a better demand−response mechanism, is leading to an ever-increasing complexity of next-generation energy networks [...]

Renewable energies, such as solar and wind power, have become promising sources of energy to address the increase in greenhouse gases caused by the use of fossil fuels and to resolve the current energy crisis. Integrating wind energy into a large-scale electric grid presents a significant challenge due to the high intermittency and nonlinear behavior of wind power. Accurate wind power forecasting is essential for safe and efficient integration into the grid system. Many prediction models have been developed to predict the uncertain and nonlinear time series of wind power, but most neglect the use of Bayesian optimization to optimize the hyperparameters while training deep learning algorithms. The efficiency of grid search strategies decreases as the number of hyperparameters increases, and computation time complexity becomes an issue. This paper presents a robust and optimized long-short term memory network for forecasting wind power generation in the day ahead in the context of Ethiop... [more]

In order to study the dynamic characteristics of the 660 MW ultra-supercritical circulating fluidized bed (CFB) boiler when the main fuel trip (MFT) and boiler trip (BT) are triggered, a dynamic simulation model of the 660 MW ultra-supercritical circulating fluidized bed boiler was established on the Apros simulation platform. The model dynamically simulated the MFT and BT processes at 100% BMCR, 75% THA, and 50% THA conditions, respectively. The steady-state simulation results showed a high accuracy compared with the designed parameters. The dynamic simulation results showed that after triggering the MFT and BT, owing to the huge thermal inertia, the bed temperature and steam temperature decreased lowly. For 100% BMCR and 75% THA conditions, the moisture separator always worked in dry state during the MFT and BT processes. For the 50% THA condition, the moisture separator quickly switched from dry to wet operation after the boiler triggers MFT and BT and gradually switched from wet to... [more]

In the study of solar greenhouses, microclimate, soil, and back walls have an important influence on the greenhouse thermal environment because of their good heat storage and release characteristics. The transpiration of crops makes indoor humidity increase sharply, which is the main factor affecting indoor humidity distribution. Therefore, it is of great significance to grasp the microclimate change law of solar greenhouses and study the coupling effect of thermal and humidity environment. In this paper, based on computational fluid dynamics (CFD), a three-dimensional model of the thermal and humidity environment of a solar greenhouse is established, and the indoor temperature and humidity distribution under the influence of soil, crops, and back walls are considered. The CFD model initialization uses binary fitting functions to fit the temperature distribution of soil, back wall, and air. The distribution law of the temperature field and relative humidity field of the solar greenhous... [more]

A new energy ship is being developed to address energy shortages and greenhouse gas emissions. New energy ships feature low operational costs and zero emissions. This study discusses the characteristics and development of solar-powered ships, wind-powered ships, fuel cell-powered ships, and new energy hybrid ships. Three important technologies are used for the power system of the new energy ship: new-energy spatio-temporal prediction, ship power scheduling, and Digital Twin (DT). Research shows that new energy spatio-temporal prediction reduces the uncertainty for a ship power system. Ship power scheduling technology guarantees safety and low-carbon operation for the ship. DT simulates the navigational environment for the new energy ship to characterize the boundary of the shipboard’s new energy power generation. The future technical direction for new energy ship power systems is also being discussed.

Stochastic simulations enable researchers to incorporate uncertainties beyond numerical discretization errors in computational fluid dynamics (CFD). Here, the authors provide examples of stochastic simulations of incompressible flows and numerical solutions for validating these newly emerging stochastic modeling methods. A numerical scheme is constructed for finding solutions to stochastic parabolic equations. The scheme is second-order accurate in time for the constant coefficient of the Wiener process term. The stability analysis of the scheme is also provided. The scheme is applied to the dimensionless heat and mass transfer model of mixed convective non-Newtonian nanofluid flow over oscillatory sheets. Both the deterministic and stochastic energy equations use temperature-dependent thermal conductivity. The stochastic model is more general than the deterministic model. The results are calculated for both flat and oscillatory plates. Casson parameter, mixed convective parameter, the... [more]

Wireless Underground Sensor Networks (WUGSNs) transmit data collected from underground objects such as water substances, oil substances, soil contents, and others. In addition, the underground sensor nodes transmit the data to the surface nodes regarding underground irregularities, earthquake, landslides, military border surveillance, and other issues. The channel difficulties of WUGSNs create uncertain communication barriers. Recent research works have proposed different types of channel assessment techniques and security approaches. Moreover, the existing techniques are inadequate to learn the real-time channel attributes in order to build reactive data transmission models. The proposed system implements Deep Learning-based Multi-Channel Learning and Protection Model (DMCAP) using the optimal set of channel attribute classification techniques. The proposed model uses Multi-Channel Ensemble Model, Ensemble Multi-Layer Perceptron (EMLP) Classifiers, Nonlinear Channel Regression models... [more]

Forecasting the electrical load is essential in power system design and growth. It is critical from both a technical and a financial standpoint as it improves the power system performance, reliability, safety, and stability as well as lowers operating costs. The main aim of this paper is to make forecasting models to accurately estimate the electrical load based on the measurements of current electrical loads of the electricity company. The importance of having forecasting models is in predicting the future electrical loads, which will lead to reducing costs and resources, as well as better electric load distribution for electric companies. In this paper, deep learning algorithms are used to forecast the electrical loads; namely: (1) Long Short-Term Memory (LSTM), (2) Gated Recurrent Units (GRU), and (3) Recurrent Neural Networks (RNN). The models were tested, and the GRU model achieved the best performance in terms of accuracy and the lowest error. Results show that the GRU model achi... [more]