Artificial intelligence (AI) techniques are increasingly used to address problems in electricity systems that result from the growing supply of energy from dynamic renewable sources. Researchers have started experimenting with data-driven AI technologies to, amongst other uses, forecast energy usage, optimize cost-efficiency, monitor system health, and manage network congestion. These technologies are said to, on the one hand, empower consumers, increase transparency in pricing, and help maintain the affordability of electricity in the energy transition, while, on the other hand, they may decrease transparency, infringe on privacy, or lead to discrimination, to name a few concerns. One key concern is how AI will affect energy justice. Energy justice is a concept that has emerged predominantly in social science research to highlight that energy related decisions—in particular, as part of the energy transition—should produce just outcomes. The concept has been around for more than a deca... [more]

Kicks can lead to well control risks during petroleum drilling, and even more serious kicks may lead to serious casualties, which is the biggest threat factor affecting the safety in the process of petroleum drilling. Therefore, how to detect kicks early and efficiently has become a focus practical problem. Traditional machine learning models require a large amount of labeled data, such kicked sample, and it is difficult to label data, which requires a lot of labor and time. To address the above issues, the deep forest is extended to a transfer learning model to improve the generalization ability. In this paper, a transfer learning model is built to detect kicks early. The source domain model adopts the deep forest model. Deep forest is an ensemble learning model with a hierarchical structure similar to deep learning. Each layer contains a variety of random forests. It is an integration of the model in depth and breadth. In the case of a small sample size (20−60 min), kick can be ident... [more]

At present, papers concerning energy consumption and forecasting are predominantly dedicated to various known techniques and their combinations. On the other hand, the research on load modeling and forecasting methodologies is quite limited. This paper presents a new approach concerning hourly energy consumption using a multivariate linear regression model. The proposed technique provides a way to accurately model day-to-day energy consumption using just a few selected variables. The number of data points required to describe a whole day’s consumption depends on the demanded precision, which is up to the user. This model is self-configurable and very fast. The applied model shows that four hours are sufficient to describe energy consumption during the remainder of a given day. We show that for about 84% of the data points, the relative error of the model is below 2.5%, and for all the data points the error does not exceed 7.5%. We obtained a mean relative uncertainty of 1.72% in the le... [more]

Digital transformation has emerged as a key driver of business innovation and growth in the 21st century. As organizations increasingly rely on digital technologies to operate and interact with customers, digital transformation has become an essential strategy for remaining competitive in today’s rapidly evolving business landscape. Simultaneously, the relevance of environmental, social, and governance (ESG) issues has increased in the context of consumers, investors, and regulators, as the negative consequences of business activities on the natural environment and society become increasingly evident. In this research article, we examine the relationship between ESG and the triple transformation of business, people, and technology, as well as how organizations can use digital technologies to enhance their ESG performance. Our aim is to identify the principal drivers and mechanisms that shape ESG performance in the context of triple transformation and to investigate the trade-offs and s... [more]

From conventional turbines to cutting-edge bladeless turbines, energy harvesting from wind has been well explored by researchers for more than a century. The vortex bladeless wind turbine (VBT) is considered an advanced design that alternatively harvests energy from oscillation. This research investigates enhancing the output electrical power of VBT through simulation of the fluid−solid interactions (FSI), leading to a comprehensive dataset for predicting procedure and optimal design. Hence, the long short-term memory (LSTM) method, due to its time-series prediction accuracy, is proposed to model the power of VBT from the collected data. To find the relationship between the parameters and the variables used in this research, a correlation matrix is further presented. According to the value of 0.3 for the root mean square error (RMSE), a comparative analysis between the simulation results and their predictions indicates that the LSTM method is suitable for modeling. Furthermore, the LST... [more]

Worldwide, the design, renovation, and sustainable management of port buildings play a crucial role for sustainability. In this framework, a computer simulation of a building’s thermal behaviour is an almost mandatory tool for making informed decisions. However, the development of a building energy model is a challenging task that could discourage its adoption. A possible solution would be to exploit an existing Building Information Modeling (BIM) model to automatically generate an accurate and flexible Building Energy Modeling (BEM) one. Such a method, which can substantially improve decision-making processes, still presents some issues and needs to be further investigated, as also detectable from the literature on the topic. In this framework, a novel workflow to extrapolate BIM data for energy simulation is proposed and analysed in this paper. Here, the BIM to BEM approach was tested as a useful tool for the maritime industry to improve the implementation of effective energy-saving... [more]

In Hong Kong, buildings consume 90% of the electricity generated and over 60% of the city’s carbon emissions are attributable to generating power for buildings. In 2018, Hong Kong residential sector consumed 41,965 TJ (26%) of total electricity generated, with private housing accounting for 52% and public housing taking in 26%, making them the two major contributors of greenhouse gas emissions. Furthermore, air conditioning was the major source consuming 38% of the electricity generated for the residential building segment. Strategizing building energy efficiency measures to reduce the cooling energy consumption of the residential building sector can thus have far-reaching benefits. This study proposes a hybrid simulation strategy that integrates artificial intelligence techniques with a building energy simulation tool (EnergyPlus™) to predict the annual cooling energy consumption of residential buildings in Hong Kong. The proposed method predicts long-term thermal energy demand (annua... [more]

High-voltage direct current (HVDC) has received considerable attention due to several advantageous features such as minimum transmission losses, enhanced stability, and control operation. An appropriate model of HVDC is necessary to assess the operating conditions as well as to analyze the transient and steady-state stabilities integrated with the AC networks. Nevertheless, the construction of an HVDC model is challenging due to the high computational cost, which needs huge ranges of modeling experience. Therefore, advanced dynamic modeling of HVDC is necessary to improve stability with minimum power loss. This paper presents a comprehensive review of the various dynamic modeling of the HVDC transmission system. In line with this matter, an in-depth investigation of various HVDC mathematical models is carried out including average-value modeling (AVM), voltage source converter (VSC), and line-commutated converter (LCC). Moreover, numerous stability assessment models of HVDC are outline... [more]

Social acceptance is increasingly becoming a limiting factor in implementing the energy transition in Germany. From today’s perspective, the expansion of wind energy and future transmission grids is only somewhat a technical or economic challenge rather than a social one. Since political decisions on the energy system transformation are often derived from findings of energy system modeling, it seems necessary to increasingly integrate the effects of socio-ecological aspects, such as acceptance issues in energy models. In this paper, an approach is introduced to address effects of social acceptance in energy system models by comparing the influence of different distribution scenarios of wind energy in Germany on the expansion need for future transmission lines. The results show that a socio-ecologic distribution of onshore wind installations according to a balanced burden of the German society does not reduce the grid expansion need significantly compared to an economic siting. An actua... [more]

This work proposes a piecewise modeling of output-voltage ripple for linear charge pumps. The proposed modeling can obtain a more accurate design expression of power-conversion efficiency. The relationship between flying and output capacitance, as well as switching frequency and optimize power-conversion efficiency can be calculated. The proposed modeling is applied to three charge-pump circuits: 1-stage linear charge pump, dual-branch 1-stage linear charge pump and 4× cross-coupled charge pump. Circuit-level simulation is used to verify the accuracy of proposed modeling.

Globally, buildings account for nearly 40% of the total primary energy consumption and are responsible for 20% of the total greenhouse gas emissions. Energy consumption in buildings is increasing with the increasing world population and improving standards of living. Current global warming conditions will inevitably impact building energy consumption. To address this issue, this report conducted a comprehensive study of the impact of climate change on residential building energy consumption. Using the methodology of morphing, the weather files were constructed based on the typical meteorological year (TMY) data and predicted data generated from eight typical global climate models (GCMs) for three representative concentration pathways (RCP2.6, RCP4.5, and RCP8.5) from 2020 to 2100. It was found that the most severe situation would occur in scenario RCP8.5, where the increase in temperature will reach 4.5 °C in eastern Australia from 2080−2099, which is 1 °C higher than that in other cli... [more]

In this study, the influence of architectural design parameters (the exterior window area, the wall height at a corridor-side, and the door gap of a toilet unit) on the airflow patterns and malodorous volatile substance (acetic acid) distributions within toilet units were investigated via computational fluid dynamics (CFD), with the restrooms in K−12 public schools (kindergarten through grade 12) of Taiwan as research objects. The results show that when there is a 2 m/s north wind in winter, all the cases exceed the required 12 air changes per hour (ACH), and most are above 43.75 ACH. When there is a 0.5 m/s south wind in summer, nearly half of the cases fail to reach 12 ACH. Maintaining an adequate natural ventilation rate and an acceptable level of odor pollution through passive design and architectural design is difficult. Thinking about how to improve the ventilation efficiency of toilet units with the aid of simple, appropriate, and energy-saving mechanical ventilation approaches... [more]

The recent advances in computing technologies and the increasing availability of large amounts of data in smart grids and smart cities are generating new research opportunities in the application of Machine Learning (ML) for improving the observability and efficiency of modern power grids. However, as the number and diversity of ML techniques increase, questions arise about their performance and applicability, and on the most suitable ML method depending on the specific application. Trying to answer these questions, this manuscript presents a systematic review of the state-of-the-art studies implementing ML techniques in the context of power systems, with a specific focus on the analysis of power flows, power quality, photovoltaic systems, intelligent transportation, and load forecasting. The survey investigates, for each of the selected topics, the most recent and promising ML techniques proposed by the literature, by highlighting their main characteristics and relevant results. The r... [more]

In the paper, a model of a three-phase frequency-controlled induction electric drive has been developed in Simulink Matlab 2019 (MathWorks, Natick, MA, USA). This model is mathematically converted into a two-phase model by transforming equations. It is proposed to compensate the voltage drop in the power system during start-up operation under load by using supercapacitors as a buffer power source. A block of supercapacitors was calculated. Simulation modeling was performed at a different voltage than the network. The diagrams of the transient processes occurring in the electric drive when the power supply is changed were prepared. It was found that such a principle of implementing an additional source of electric energy allows to start induction electric drives in areas remote from industrial networks without significantly affecting their static and dynamic characteristics.

Empty fruit bunch, a significant by-product of the palm oil industry, represents a tremendous and hitherto neglected renewable energy resource for many countries in South East Asia and Sub-Saharan Africa. The design and simulation of a plant producing pure hydrogen through autothermal reforming (ATR) of palm empty fruit bunch (PEFB) was carried out based on successful laboratory experiments of the core process. The bio-oil feed to the ATR stage was represented in the experiments and in the simulation by a surrogate bio-oil mixture of 11 organic compounds shown to be main constituents of PEFB oil from previous work, and whose combined elemental composition and volatility was determined to be as close as possible to that of the real PEFB bio-oil. The experiments confirmed that H2 yields close to equilibrium predictions were achievable using an in-house synthetised Rh-Al2O3 catalyst in a packed bed reactor. Initial sensitivity analysis on the plant revealed that feed molar steam to carbon... [more]

The Frontier Observatory for Research in Geothermal Energy (FORGE) site is a multi-year initiative funded by the U.S. Department of Energy for enhanced geothermal system research and development. The site is located on the margin of the Great Basin near the town of Milford, Utah. Work has so far resulted in the compilation of a large amount of subsurface data which have been used to improve the geologic understanding of the site. Based on the compiled data, a three-dimensional geologic model describing the structure, composition, permeability, and temperature at the Utah FORGE site was developed. A deep exploratory well (Well 58-32) and numerous tests conducted therein provide information on reservoir rock type, temperature, stress, permeability, etc. Modeling and simulation will play a critical role at the site and need to be considered as a general scientific discovery tool to elucidate the behavior of enhanced geothermal systems and as a deterministic (or stochastic) tool to plan an... [more]

Cyberattacks against the elements of technological data transmission networks represent a rather significant threat of disrupting the management of regional electric power complexes. Therefore, evaluating the functioning quality of data transmission networks in the context of cyberattacks is an important task that helps to make the right decisions on the telecommunication support of electric power systems. The known models and methods for solving this problem have limited application areas determined by the admissible packet distribution laws. The paper proposes a new method for evaluating the quality of the functioning of data transmission networks, based on modeling the process of functioning of data transmission networks in the form of a stochastic network. The proposed method removes restrictions on the form of the initial distributions and makes the assumptions about the exponential distribution of the expected time and packet servicing in modern technological data transmission ne... [more]

Radiant cooling systems (RCS) are gaining acceptance as a heating, ventilation, and air conditioning (HVAC) solution for achieving adequate thermal comfort and maintaining acceptable indoor air quality inside buildings. RCS are well known for their energy-saving potential; however, serious condensation problem hinders the growth of this technology. In order to prevent the risk of condensation, the supply water temperature is kept higher than the dew point temperature of the air inside the room. The full potential of the cooling power of a radiant cooling panel is limited. Therefore, this article is on maximizing the cooling capacity of a radiant cooling panel, in terms of flow configuration. Radiant cooling panels (RCP) with different chilled water pipe configurations are designed and compared, side by side with the conventional serpentine flow configuration. The cooling performance of the radiant cooling panels is evaluated by using computational fluid dynamics (CFD) with Ansys Fluent... [more]

The paper presents the results of experimental and model tests of transport of dispersed fluid droplets forming a cloud of aerosol in a stream of air ventilating a selected section of the underground excavation. The excavation selected for testing is part of the ventilation network of the Experimental Mine Barbara of the Central Mining Institute. For given environmental conditions, such as temperature, pressure, relative humidity, and velocity of air, the distribution of aerosol droplet changes in the mixture of air and water vapor along the excavation at a distance was measured at 10 m, 25 m, and 50 m from the source of its emission. The source of aerosol emission in the excavation space was a water nozzle that was located 25 m from the inlet (inlet) of the excavation. The obtained results of in situ tests were related to the results of numerical calculations using computational fluid dynamics (CFD). Numerical calculations were performed using Ansys-Fluent and Ansys-CFX software. The... [more]

In this paper, we used a self-developed anisotropic cubic core holder to test anisotropic relative permeability by the unsteady-states method, and introduced the anisotropic relative permeability to the traditional numerical simulator. The oil−water two-phase governing equation considering the anisotropic relative permeability is established, and the difference discretization is carried out. We formed a new oil−water two-phase numerical simulation method. It is clear that in a heterogeneous rock with millimeter to centimeter scale laminae, relative permeability is an anisotropic tensor. When the displacement direction is parallel to the bedding, the residual oil saturation is high and the displacement efficiency is low. The greater the angle between the displacement direction and the bedding strike, the lower the residual oil saturation is, the higher the displacement efficiency is, and the relative permeability curve tends towards a rightward shift. The new simulator showed that the a... [more]

The article deals with the problems of single-phase short-circuit current distribution in overhead power lines. Short-circuit disturbances cause many negative phenomena in power networks. Since experimental studies of short-circuits in real networks are practically impossible to perform, these effects can be evaluated only theoretically, based on short-circuit current calculations with the use of appropriate mathematical models. Although short-circuit modeling is considered to be one of the simplest power system calculations, the exact mathematical description of the phenomena occurring at short-circuits is complex. Simplified normative methods are often used for short-circuit current calculations; however, this does not give ground for a thorough analysis of short-circuit current distribution in power lines. The distributions are analyzed using power line models with different degrees of complexity in line with the assumptions made for a given model. The paper presents the problem of... [more]

The charge transport in polypropylene was studied under DC electric fields at different temperatures. By the experimental measurement and simulation of the BCT model, we studied conduction currents, breakdown strength, and space charge distribution. In particular, the conduction characteristics under high temperature and high field, especially the conduction characteristics before the breakdown, were studied by systematic experiments, and the conduction characteristics and the breakdown mechanism were further studied by simulation. The results show that in the process of measuring conduction currents until breakdown, both high temperature and high electric field will promote charge transport. However, the free volume will increase at high temperature, which will easily lead to faster charge transport and breakdown. In the breakdown process at different temperatures, there are different breakdown mechanisms. At 20−60 °C, the electric breakdown process has mainly occurred in polypropylen... [more]

Plasma Pulse Geo Drilling (PPGD) is a contact-less drilling technique, where an electric discharge across a rock sample causes the rock to fracture. Experimental results have shown PPGD drilling operations are successful if certain electrode spacings, pulse voltages, and pulse rise times are given. However, the underlying physics of the electric breakdown within the rock, which cause damage in the process, are still poorly understood. This study presents a novel methodology to numerically study plasma generation for electric pulses between 200 and 500 kV in rock pores with a width between 10 and 100 μm. We further investigate whether the pressure increase, induced by the plasma generation, is sufficient to cause rock fracturing, which is indicative of the onset of drilling success. We find that rock fracturing occurs in simulations with a 100 μm pore size and an imposed pulse voltage of approximately 400 kV. Furthermore, pulses with voltages lower than 400 kV induce damage near the ele... [more]

Oil and gas well productivity can be affected by a number of different skin factors, the combined influences of which contribute to a well’s total skin factor. The skin caused by deviated wells is one such well-known factor. The present study aimed to investigate skin effects caused by deviated well slants when considering vertical-to-horizontal permeability anisotropy. The research employed computational fluid dynamics (CFD) software to simulate fluid flows in inclined wells through the injection of water with Darcy flow using 3D geometric formations. The present work investigates the effects of four main characteristics—namely, the permeability anisotropy, wellbore radius, reservoir thickness, and deviation angle—of open-hole inclined wells. Additional investigations sought to verify the effect of the direction of perforations on the skin factor or pressure drop in perforated inclined wells. In the case of an inclined open hole well, the novel correlation produced in the current stud... [more]

Natural gas sweetening is an essential process within hydrocarbon processing operations, enabling compliance with product quality specifications, avoiding corrosion problems, and enabling environmental care. This process aims to remove hydrogen sulfide (H2S), carbon dioxide, or both contaminants. It can be carried out in fixed-bed adsorption towers, where iron oxide-based solid sorbent reacts with the H2S to produce iron sulfides. This study is set out to develop a fluid-dynamic model that allows calculating the pressure drop in the H2S adsorption towers with the novelty to integrate reactivity aspects, through an iron sulfide layer formation on the solid particles’ external skin. As a result of the layer formation, changes in the particle diameter and the bed void fraction of the solid sorbent tend to increase the pressure drop. The shrinking-core model and the H2S adsorption front variation in time support the model development. Experimental data on pressure drop at the laboratory sc... [more]