This study reports the thermodynamic analysis of a high-temperature recuperative organic Rankine cycle comprising a water heating system that can provide a net power of 585.7 kW and hot water for domestic use at 35 °C. The performance was analysed using seasonal ambient temperature and water temperature data from Seoul, South Korea. The working fluid was separated into two different mass fractions after emerging from the turbine 1 outlet; one fraction provided heat to recuperate the organic Rankine cycle, and the other fraction was transferred to the water heating system for heating water. Mass fractions were balanced based on the projected seasonal need for hot water. Four working fluids with high critical temperatures and five working fluids with low critical temperatures were examined for top and bottom cycles, respectively. Chlorobenzene was selected for the top cycle and R601 was selected for the bottom cycle. The system achievement in individual months was analysed using thermal... [more]

In order to improve the static start-up problem of Savonius wind turbines, a Savonius wind turbine with a modified blade is proposed. It was obtained by twisting the half-cylindrical blades of the basic Savonius wind turbine by 70°. The aerodynamic performance of the wind turbine before and after the modification was compared. Firstly, the static torque coefficient of two wind turbines at different azimuth angles were obtained by means of three-dimensional numerical simulation. The static flow field around the wind turbine was analyzed. Then, the output power and speed characteristics of a spiral Savonius wind turbine under different incoming wind speeds were evaluated in the wind tunnel. The results show that, compared with the Savonius wind turbine with half-cylindrical blades, the spiral wind turbine could start at any azimuths in one rotation cycle. The reverse torque was eliminated. The static torque coefficient fluctuation range was reduced by 10%. The start-up performance was ef... [more]

Wood is one of the basic building materials. It is a completely biodegradable raw industrial commodity, the resources of which, with proper forest management, are virtually inexhaustible. Additionally, its acquisition and processing does not require large inputs of fossil fuels. At the same time, forest areas which we obtain wood from neutralize the negative effects of producing and acquiring other raw materials, as one hectare of pine forest (the most popular in Poland) can absorb approx. 20−30 tons of CO2. Wood is characterised by low thermal and electrical conductivity, having simultaneously high sound insulation, which perfectly meets the requirements of the present market and its regulations. This study aimed at verifying the technical parameters of wood, i.e., its bending strength, with the use of an innovative method of the correlation between the bending strength measured along and across wood fibres. The procedure was envisaged as effective for testing the strength of beams in... [more]

Researchers have made great progress in developing cutting-edge solar energy forecasting methods. However, these methods are far from optimal in terms of their accuracy, generalizability, benchmarking, and other requirements. Particularly, no single method performs well across all climates and weather due to the large variations in meteorological data. This paper proposes SENERGY (an acronym for sustainable energy), a novel deep learning-based auto-selective approach and tool that, instead of generalizing a specific model for all climates, predicts the best performing deep learning model for global horizontal irradiance (GHI) forecasting in terms of forecasting error. The approach is based on carefully devised deep learning methods and feature sets created through an extensive analysis of deep learning forecasting and classification methods using ten meteorological datasets from three continents. We analyze the tool in great detail through a variety of metrics and means for performance... [more]

We propose efficient multiple machine learning (ML) models using specifically polynomial and logistic regression ML methods to predict the optimal design of proton exchange membrane (PEM) electrolyzer cells. The models predict eleven different parameters of the cell components for four different input parameters such as hydrogen production rate, cathode area, anode area, and the type of cell design (e.g., single or bipolar). The models fit well as we trained multiple machine learning models on 148 samples and validated the model performance on a test set of 16 samples. The average accuracy of the classification model and the mean absolute error is 83.6% and 6.825, respectively, which indicates that the proposed technique performs very well. We also measured the hydrogen production rate using a custom-made PEM electrolyzer cell fabricated based on the predicted parameters and compared it to the simulation result. Both results are in excellent agreement and within a negligible experiment... [more]

Shale and tight hydrocarbons are vital to global energy dynamics. The fluid flow in sub-micron pores of tight oil reservoirs varies from bulk fluid flow. The Darcy law is widely accepted to model creeping flow in petroleum reservoirs. However, traditional reservoir modeling approaches fail to account for the sub-micron mechanisms that govern fluid flow. The accuracy of tight oil reservoir simulators has been improved by incorporating the influence of sub-micron effects. However, there are still factors that affect sub-micron fluid mobility that need investigation. The influence of a chemical potential gradient on fluid flow in sub-micron pores was modeled by solving Darcy and the transport and diluted species equations. The findings indicate that when a chemical potential gradient acts in the opposite direction of a hydraulic pressure gradient (reverse osmosis), there exists a limiting pressure threshold below which a non-linear flow pattern deviating from the Darcy equation is observe... [more]

Recent economic anomalies, including the unprecedented lockdown generated by the COVID-19 crisis, have demonstrated that the weighted average cost of capital (WACC) remains an actual topic in the financial literature and in practice. Companies operate in an increasingly volatile environment, due to twin transitions and interlinked crises, and so they must have specific tools for measuring risk and profitability, in order to enable them to have a sound financial policy. Based on the earlier results obtained by Modigliani and Miller (1963), Harris and Pringle (1985), and Farber, Gillet, and Szafarz (2006), this study shows the relationship between WACC and interest rate. It offers a modified WACC formula that considers unstable market circumstances. The new redefined WACC can be a valuable tool in business planning for companies from different fields. The companies in the energy sector are very interested in the topic of WACC, considering not only the complex nature of the investments ma... [more]

Permanent magnet wall-climbing robots are widely used in the maintenance of tanks in the petrochemical industry and the overhaul of large-pressure pipelines in the hydropower industry. One of the difficulties is to achieve the safe and reliable adsorption of wall-climbing robots. Based on the Halbach array, a double-layer superposition magnetic circuit magnetization method is designed in this paper. Under the same constraints, the adsorption force of the permanent magnetic chuck is increased by at least 8% compared with the traditional magnetic circuit design method. Under the working air gap of 1∼9 mm, the average magnetic energy utilization rate is increased by at least 16.46%. This approach not only improves the magnetic energy utilization of the permanent magnetic chuck but also improves the adsorption safety of the wall-climbing robot.

In this paper, model predictive control (MPC) is proposed for single-phase electric springs (ESs) with the help of the existing δ control, which is realized by controlling the instantaneous phase angle of the predefined sinusoidal reference of a certain controller. System modeling is analyzed first to get differential forms of state variables. The discrete-time state space model is obtained through first-order approximation. Critical load (CL) voltage can be predicted by the prediction of ES voltage and line current. The operating modes of ESs can be determined and the reference signal for CL voltage can be provided by δ control. As a result, cost function is obtained as the absolute value of the error between predicted CL voltage and its predefined reference. Two typical operating functions such as pure reactive power compensation mode and power factor correction (PFC) mode are selected and simulated to validate the proposed control and analysis. It is revealed that both control objec... [more]

Over the past decade, decarbonization and environmental issues have taken a key role in worldwide politics [...]

Wind speed variations affect the performance of the wind energy conversion systems (WECSs) negatively. This paper addressed an advanced law of the backstepping controller (ABC) for enhancing the integration of doubly fed induction generator (DFIG)-based grid-connected WECS under wind range of wind speed. This enhancement was achieved through three control schemes, which were blade pitch control, rotor-side control, and grid-side control. The blade pitch control was presented to adjust the wind turbine speed when the wind speed exceeds its rated value. In addition, the rotor and grid-side converter controllers were presented for improving the direct current link voltage profile and achieving maximum power point tracking (MPPT) under speed variations, respectively. To evaluate the effectiveness of the proposed ABC control, a comparison between PI and sliding-mode control (SMC) was presented, considering the parameters of a 1.5 MW DFIG wind turbine in the Assilah zone in Morocco. Moreover... [more]

In recent years, it has been noted that deep learning, machine learning, and artificial intelligence models are growing in popularity when applying big data for energy control and decision-making processes [...]

Modern electrical traction uses asynchronous motors for driving railway vehicles because these motors have a lot of advantages in comparison with the classical, direct current motors. Reducing active and reactive electrical energy consumption is a concern in the case of these motors, meaning a decrease in exploitation costs. The research carried out shows, by results and simulations, the effects of the geometry optimization for the stator and rotor lamination and emphasizes how much the total and exploitation costs. Cross geometry optimization means preserving constant electromagnetic stresses, using the same gauge dimensions, preserving the constant ampere-turn for a pole pair, having a maximum torque exceeding the imposed limit, and increasing the air-gap magnetic induction. The results obtained indicatea decrease in the total cost, by 42,600 € (12.31%), for a asynchronous tractionmotor in comparison with the existing variant.

Utilizing electrostatic precipitators (ESPs) is an efficient particle removal method that sees a wide usage in industrial environments. This is mainly because of the low drop of the pressure flow, while retaining high collection efficiency, alongside being cost-effective. This paper reviewed previous works concerning optimizing the performance of single- and multi-stage ESPs by changing several design parameters and evaluating the effects on different performance indices, such as the corona power ratio, current-voltage characteristics, and overall collection efficiency. The review then goes through several modelling methodologies, showcasing their shortcomings and developments, as well as the relationship between the electrohydrodynamic (EHD) flow and the precipitation performance. The performance effects of using different electrode configurations and designs in terms of the number of electrodes, relative dimensions, spacings, channel lengths, and overall design were also reviewed.

In the modern induction motor (IM) drive system, the fault-tolerant control (FTC) solution is becoming more and more popular. This approach significantly increases the security of the system. To choose the best control strategy, fault detection (FD) and fault classification (FC) methods are required. Current sensors (CS) are one of the measuring devices that can be damaged, which in the case of the drive system with IM precludes the correct operation of vector control structures. Due to the need to ensure current feedback and the operation of flux estimators, it is necessary to immediately compensate for the detected damage and classify its type. In the case of the IM drives, there are individual suggestions regarding methods of classifying the type of CS damage during drive operation. This article proposes the use of the classical multilayer perceptron (MLP) neural network to implement the CS neural fault classifier. The online work of this classifier was coordinated with the active F... [more]

The paper deals with a techno-economic comparison between utility-scale diabatic compressed air energy storage (D-CAES) systems equipped with artificial storage and Battery Energy Storage (BES) systems based on consolidated technologies, such as Sodium-Sulfur (Na-S) and Lithium-ion (Li-Ion). The comparison is carried out on the basis of the levelized cost of storage (LCOS). Analyses have been performed by varying key inputs, such as the rated power, the storage capacity, the price of electricity absorbed from the grid during the charging phase, and the cost of fuel fed to D-CAES during the discharge phase. Na-S technology-based systems always show better techno-economic performance in respect to Li-Ion based ones. The economic performance of both D-CAES and BES improves by increasing the storage capacity. The D-CAES performance improvement rate, however, is higher than that estimated for BES based systems. Moreover, the economic performance of D-CAES systems is less sensitive to the pr... [more]

The exploration of superhydrophobic drag reduction has been and continues to be of significant interest to various industries. In the present work, direct numerical simulation (DNS) is utilized to investigate the effect of the parameters on the drag-reducing performance of superhydrophobic surfaces (SHS). Simulations with a friction Reynolds number of 180 were carried out at solid fraction values of ϕs=116,111, and 14, and three distribution shapes: aligned, staggered, and random. The top wall is the smooth one, and the bottom wall is a superhydrophobic surface (SHS). Drag reduction and Reynolds stress profiles are compared for all cases. The turbulent kinetic energy budget, including production, dissipation, and diffusion, is presented with respect to the solid fraction and type of distribution to investigate the drag reduction mechanism. The sizes of the longitudinal vortices and formation of hairpin vortices are investigated through the observation of coherent structures. The simula... [more]

The accurate extraction and analysis of slot harmonics caused by slotting in an induction motor are important for the motor’s performance evaluation and state monitoring. However, the frequency distribution of rotor slot harmonics (RSHs) varies along with the operating states of the motor, such as motor speed and slip ratio, and the voltage and current signals of the motor only contain small-amplitude RSHs compared with other harmonics; both make it difficult to extract and analyze the RSHs accurately online. While offline extraction and filters with constant parameters are mainly utilized in available works, a novel adaptive extraction method for RSHs in a multiphase induction motor is proposed here to realize online RSH extraction under different speed and load conditions. In this paper, the RSHs in the multiphase induction motors are firstly modeled by using the magnetic potential permeability method, and the influence of a skewed rotor on RSHs is analyzed through a multisection met... [more]

Power quality (PQ) problems, including voltage sag, flicker, and harmonics, are the main concerns for the grid operator. Among these disturbances, voltage sag, which affects the sensitive loads in the interconnected system, is a crucial problem in the transmission and distribution systems. The determination of the voltage sag relative location as a downstream (DS) and upstream (US) is an important issue that should be considered when mitigating the sag problem. Therefore, this paper proposes a novel approach to determine the voltage sag relative location based on voltage sag event records of the power quality monitoring system (PQMS) in the real distribution system. By this method, the relative location of voltage sag is defined by Gaussian naive Bayes (Gaussian NB) and K-nearest neighbors (K-NN) algorithms. The proposed methods are compared with support vector machine (SVM) and artificial neural network (ANN). The results indicate that K-NN and Gaussian NB algorithms define the relati... [more]

Sensitivity analysis aids in determining important factors affecting pipeline safety. Sensitivity analysis of stress inside gas pipelines with corrosion defects in a landslide region can provide a theoretical basis for the safe operation of pipelines. This study considered an X80 high-grade steel gas pipeline model with corrosion defects using finite element analysis (ABAQUS software) under lateral landslide conditions. Particularly, we studied the six major engineering elements of soil cohesion to understand the stress variations in buried gas pipelines and performed a sensitivity analysis of each influencing parameter. The calculation results revealed that all the factors influencing the stress in corroded gas pipelines during landslide conditions were positively correlated to the internal pipe stress, except for the axial position of corrosion defects. The factors in the descending order of influence on the sensitivity coefficient are stated as follows: landslide displacement, axial... [more]

Oil−water flows are widely encountered in petroleum, chemical, nuclear reactors, and other crucial industrial processes. Due to gravity and interaction between phases, horizontal and inclined oil−water two-phase flows are characterized by remarkable multi-scale structure characteristics, such as large-scale stratified interface and small-scale droplets entrainment. Moreover, a slight change in the pipe inclination will lead to significant changes in the local oil−water flow structures, which results in great challenges in the measurement of the interface structures. In this study, we design a 10 × 10 conductance wire-mesh sensor (WMS) to detect the interfacial characteristics of horizontal and inclined oil−water flows. Firstly, we carry out horizontal and inclined oil−water flow experiments. The influence of pipe inclinations on the flow transition boundary is analyzed. The three-dimensional (3D) structures of oil−water flows are visualized based on the WMS measurement response. Then,... [more]

Wearable technology represents a new technological paradigm for promoting physical activity, enabling monitoring of performances and athletic gestures. In addition, they can be employed for remote health monitoring applications, allowing continuous acquisition of users’ vital signs directly at home, emergency alerting, and computer-assisted rehabilitation. Commonly, these devices depend on batteries which are not the better option since researchers aim for dispositive who need minimal human intervention. Energy harvesting devices can be useful to extract energy from the human body, especially by integrating them into the garments, giving health monitoring devices enough energy for their independent operation. This review work focuses on the main new wearable technologies and devices to scavenge energy from the human body. First, the most suitable energy sources exploitable for wearable applications are investigated. Afterward, an overview of the main harvesting technologies (piezoelect... [more]

Energy monitors are indispensable for achieving efficient electrical grids and even more so in the age of the Internet of Things (IoT), where electrical system data are monitored from anywhere in the world. This paper presents the development of a two-channel electrical parameter-monitoring system based on the M5 Stack Core2 kit. The acquisition of variables is done through PZEM 004T V3.0 sensors, and the data are sent to the ThingSpeak cloud database. Local readings are done through the LCD, and data re stored on a micro SD card. Remote monitoring is done through two applications, namely a web application and a mobile application, each designed for different purposes. To validate this proposal, a commercial device with IoT features (Gen 2 Vue Energy Monitor) is used, comparing the active power and active energy readings recorded continuously for 7 days. The results indicate an accuracy of up to 1.95% in power and 0.81% in energy, obtaining a low-cost compact product with multiple feat... [more]

CO2 is the most emitted greenhouse gas and is mainly produced by human activity. In fact, about 75% is emitted in cities and 40% of global carbon emissions is produced by the building sector. Therefore, buildings are very important in terms of CO2 emissions. This importance is also reflected in the works that have been developed on this subject. This manuscript reviews the research that has shown or calculated the amounts of CO2 emitted in buildings. For a better understanding of the scope of the investigations, a classification is presented. With this, it is intended to help researchers interested in this area by summarizing the studies carried out to date on the amounts of CO2 emitted depending on the type of building.

Fly ash from waste incineration and waste poplar bark from furniture manufacturing are domestic wastes. In this study, fly ash and poplar bark were used as raw materials to prepare activated carbon via carbonization, steam activation and reagent modification. The effects of the raw material mixing ratio, carbonization temperature, activator concentration and modifier concentration on the physicochemical properties of the semi-coke and activated carbon were investigated through experiments. The experiment showed that when the carbonization temperature was 300 °C, the steam concentration was 20%, the mixing ratio of the poplar bark and fly ash (B:F) was 5:1, and the modifier was 6% K2CO3 reagent and 9% CaCl2. The prepared activated carbon had a better yield, specific surface area and pore structure, and had an abundant surface functional group structure. This paper points out the direction for the industrial directional production of activated carbon adsorbents with excellent physical an... [more]