Presently, hydrogen-fuel-cell medium-duty trucks utilize two or more modular proton exchange membrane fuel-cell stacks due to package space and economic concerns. The fuel-cell system of medium-duty trucks requires high power demand under a regular driving schedule. Since the high power demands produces significant heat generation within a very small packaging space, thermal management is crucial for maintaining the performance and long term durability of medium-duty trucks. This study was designed to investigate the various cooling configurations of dual stacks to understand the dual-stack response under thermal management conditions. A dynamic fuel-cell system model is developed to investigate the layout effect of the cooling system under load follow-up. Three different layouts of cooling system were investigated such as series cooling, parallel cooling, and two independent cooling modules with minimum cooling components. The results show that the series cooling system shows a minimu... [more]

The paper deals with an optimization of a magnetic circuit of the field exciter designed to control magnetorheological fluid (MRF) in a hybrid soft−rigid jaw gripper. The case discussed includes sealing of the MRF inside a cushion made of thermoplastic polyurethane (TPU). The shear stress distributions in the MRF upon magnetic field excitation have been analyzed for various permanent magnet, yoke, and air gap dimensions. In the developed numerical model of the magnetic field exciter, the geometry of the considered domain was parameterized. As part of the simulation study, more than 4600 variants of the magnetic circuit were analyzed, for which the shear stress distribution in the MRF inside the cushion was determined. The numerical model has been implemented in the Ansys Electronics Desktop 2020 finite element method (FEM) package. Research was focused on finding dimensions of the magnetic circuit that ensure the desired distribution of the shear stress in the MRF inside the cushion. T... [more]

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]

This paper investigates the month-wise impact of COVID-19 conditions on residential load due to people’s presence at home during office hours in Memphis city, Tennessee, USA. The energy consumption patterns of four consumers are analyzed based on the data available from pre-COVID to continuing COVID-19 situations. It is observed that the energy consumptions from April 2020 to June 2021 for all families have increased during office hours than that of pre-COVID months. Therefore, the impacts of the increased loads on distribution transformer are analyzed in terms of hottest spot, top-oil temperature, and loss of transformer life. Moreover, an experimental setup is made to produce the harmonics in currents of non-linear residential load which has detrimental effects on temperature rise of distribution transformer. In addition, this work proposes implementation of harmonic filter at the load side considering the impact of harmonics produced by loads to reduce the temperature rise due to th... [more]

This research presents the findings of an evaluation of off-grid photovoltaic (PV) systems and their sustainability models in Colombia within the “Evaluation of Isolated Photovoltaic Systems and Their Sustainability Models” project supported by the Global Environment Fund (GEF). It involves the analysis of primary and secondary information on the photovoltaic energy projects for rural electrification in this country. Part of the information was obtained through interviews with different stakeholders who work in solar electrification in non-interconnected zones (NIZ), covering rural and island contexts. It was complemented by a comparative analysis of international projects implemented in Latin America. The results are shown as lessons learned, with a SWOT (strengths, weaknesses, opportunities, and threats) study representing the current situation of rural electrification with PV technology as perceived and describing the opportunities for the improvement of rural electrification strate... [more]

Nowadays, sustainability-related issues have attracted growing attention due to fossil fuel depletion and environmental concerns. Considering many cities have gradually replaced taxis with electric vehicles (EVs), to reduce greenhouse gas emissions and traditional energy consumption, this paper studies the optimization strategy of battery swapping for electric taxis (ETs), and it is not only to ease congestion in the battery swapping station (BSS) but also for electric taxis to address their range anxiety and maximize their benefits. Firstly, based on the road network, the Dijkstra algorithm is adopted to provide the optimal path for ETs to BSSs with the minimum energy consumption. Then, this paper proposes the optimization objective function with minimum cost, which contains the battery service cost based on the battery’s state of charge, waiting cost caused by waiting for swapping battery in BSSs and the carbon emission reduction benefit generated during ETs driving to BSSs, and uses... [more]

The need to reduce greenhouse gas emissions is driving many actions to decarbonize the most impactful sectors. Among these, the energy sector accounts for almost one third of emissions. Increasing the penetration of renewable energy in the energy mix could easily reduce the emissions of this sector. Theoretically, the target to aim for would be 100% renewable energy production. However, the variable nature of power production from photovoltaic and wind systems, which are expected to play a key role in the energy transition, may pose several limitations to the effective penetration of renewable energy. Many concerns arise when one considers the large diffusion of renewable energy that would be required to meet green targets, and the operating conditions of other systems in charge of compensating for renewable energy variations. This study aims to investigate the potential impact of an increase in the amount of renewable energy installed in a country, particularly in Italy. A simplified... [more]

This paper proposes a modular inverter based on Cuk converters for solar photovoltaic (PV) systems to mitigate the voltage and current mismatch issue at the PV module level. The proposed modular Cuk inverter (MCI) is formed by connecting several low-voltage (LV) microinverters (MIs) in series and linking their output sides to the distribution network. This architecture does not require a central inverter, and hence, it eliminates the need for large dc-link intermediate capacitors. The proposed MCI provides more controllability over the PV system by having a decentralized structure. The MCI will improve the PV system efficiency by reducing the voltage and current stresses in the MIs and will enable better voltage regulation due to the provided controllability. Since the proposed MI topology is based on the Cuk converter, it offers continuous input and output currents that will reduce the required filtering capacitance and will provide a wide range of voltage regulation for either supply... [more]

As a bi-directional converter, the Buck-Boost converter, which has the advantages of simple structure and taking the SOC of the battery as the balance variable, is adopted as the balance topology in this paper. In view of the shortcomings of traditional balance topology, which can only balance two adjacent batteries, resulting in a long balance time and insufficient balance accuracy, a cascade active balance charging topology that can balance in intra-group and inter-group situations simultaneously is proposed. At the same time, the fuzzy control algorithm and model predictive control are used as the balance control strategies, respectively, to control whether the MOSFET is on or off in the balance topology circuit. The duty cycle is dynamically adjusted to the size of the balance current to achieve the balance of the battery pack. The results show that the cascade Buck-Boost balance topology based on model prediction control can accurately control the balancing current and improve the... [more]

Wind energy is one of the most relevant clean energies today, so wind turbines must have good health and be reliable in operation. Current wind turbines have slender and elastic structures that can be easily damaged through vibrations and compromise their health; therefore, vibration monitoring is essential to ensure safe operation. Here, we present a method for simple wind turbine vibration monitoring in the laboratory by means of an accelerometer placed on a weathervane under different scenarios, with recording of different amplitudes of vibrations caused at a constant speed of 10 km/h. The variables, trends, and data captured during vibration monitoring were then used to implement a prediction system of synthetic failure using machine learning methods such as: Medium Trees, Cubic SVN, Logistic Regression Kernel, Optimized Neural Network, and Bagged Trees, with the last demonstrating an accuracy of up to 0.87%.

With the start of the intelligent age, textiles are no longer limited to safety protection, warmth, and aesthetic purposes. They have become intelligent textiles, which combine functionality, intelligence, and information technology to adapt to the era and enrich our lives, such as wearable textiles and energy harvesting electronics. However, the limited stretchable smart textiles and complex fabrication methods have largely hindered their development. Here, a mass-manufactured 3D stitching double weave fabric-based elastic triboelectric nanogenerator (3DWE-TENG) is developed. Based on its stable electrical output performances and rapid response to external tensile strain, it can be used for energy harvesting and self-powered sensing simultaneously through both the lining layer and the exterior layer. With an advanced 3D structural design and using the improved woven method, 3DWE-TENG can be stretched to 300% and achieves a stable mechanical structure, breathability, and excellent flex... [more]

University buildings have high energy requirements due to their size, numerous users, and activities, which considerably contribute to environmental contamination. Implementing energy-saving solutions in these structures has a favorable influence on the economics and the conservation of energy resources. A higher education building’s energy behavior can be simulated using software to identify the optimal strategies that result in energy savings. In this research, Autodesk Revit, Autodesk Insight, and Green Building Studio are among the programs utilized to examine the energy efficiency of the university building in four European cities. Following the development of several energy-saving scenarios for the building, the offered solutions are evaluated based on their annual energy consumption, energy costs, and CO2 emissions. Finally, multicriteria analysis techniques such as the AHP and PROMETHEE are applied to choose the best scenario for each instance. The study’s findings indicate th... [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]

Distribution system state estimation (DSSE) has been introduced to monitor distribution grids; however, due to the incorporation of distributed generations (DGs), traditional DSSE methods are not able to reveal the operational conditions of active distribution networks (ADNs). DSSE calculation depends heavily on real measurements from measurement devices in distribution networks. However, the accuracy of real measurements and DSSE results can be significantly affected by false data injection attacks (FDIAs). Conventional FDIA detection techniques are often unable to identify FDIAs into measurement data. In this study, a novel deep neural network approach is proposed to simultaneously perform DSSE calculation (i.e., regression) and FDIA detection (i.e., binary classification) using real measurements. In the proposed work, the classification nodes in the DNN allow us to identify which measurements on which phasor measurement unit (PMU), if any, were affected. In the proposed approach, we... [more]

Waste heat air-source heat pump water heater (WH-ASHPWH) systems have been widely used to provide water heating in buildings due to their advantages of high efficiency and low environmental impact. It is important to determine reasonable operating conditions for WH-ASHPWH systems to improve their heating efficiency, especially for systems using industrial waste heat. In this study, a semiempirical parametric model of a WH-ASHPWH system was established to simulate heating performance under different working conditions and determine the optimum operating range of the system. A new discrete model for a tube-in-tube condenser was also generated. Taking the equipment of a pharmaceutical factory as an example, the heat exchanger model was first calibrated; then, the global model was used to study the effects of different air-side and condenser-side waste heat conditions on the heating performance of the system. According to the simulation results, the coefficient of performance (COP) reached... [more]

The study presents an optimal control approach for managing a hybrid Photovoltaic/Wind Turbine/Battery system in an isolated area. The system includes multiple energy sources connected to a DC bus through DC/DC converters for maximum power point tracking. The proposed hybrid MPPT approach (HMPPT) manages the energy production from different sources, while the power flow method is used to balance the load and renewable power. The study shows that integrating the HMPPT algorithm and power flow approach results in improved system performance, including increased power generation and reduced stress on the batteries. The study also proposes an accurate sizing method to further improve system efficiency. The study demonstrates the effectiveness of the proposed approach by presenting results for twelve different days with varying weather conditions. The results show that the proposed approach effectively manages the energy production and load, resulting in optimal system performance. This stu... [more]

In this work, an induced pre-saturation tower (IPST) for oil−water separation was built on a semi-industrial scale, based on experimental results obtained on a laboratory scale prototype. The main strategy for generating these criteria was to increase the efficiency of the bench scale prototype, which is limited by conditions of low levels of automation and control, with the use of a biosurfactant as an auxiliary collector. The validation of the developed criteria allowed the construction of an IPST with three stages, all fed with previously saturated effluents. The IPST was built in stainless steel, with multistage centrifugal pumps and adapted to generate microbubbles without the use of saturation tanks or compressors. The most relevant operational parameters were selected using a fractional factorial design, while a central composite rotatable design (CCRD) followed by the application of the desirability function allowed to optimize the conditions for partial and global variables, t... [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]

The cooling capacity needed by ultra-low temperature apparatus cannot be reached economically with a single vapor compression refrigeration cycle due to the constraint of the high compressor pressure ratio. The auto-cascade refrigeration cycle is a good alternative. In this work, a novel concept that applies the principle of the auto-cascade refrigeration cycle to store cold energy is conducted. The environment-friendly refrigerants of R600a/R290/R170 zeotropic mixtures are used to study the performance of the modified auto-cascade refrigeration cycle (MACRC) as an alternative for cold-energy applications. The simulation results show that a cooling capacity of 500 W can be provided below −60 °C. The mixture with a mass fraction of 0.25/0.35/0.40 yields a COP of 0.695 and an exergy efficiency of 0.262 at −66 °C. The performance of the MACRC system was investigated at an ambient temperature of 20 to 40 °C for indoor small-scale applications. It is concluded that the performance would be... [more]

The design of hydrokinetic plants in hydropower canals involves the choice of the array layout, rotor geometry, turbine spacing, and array spacing, and necessitates the control of the resultant backwater to avoid upstream flooding hazards. Several works in the literature have shown that array power optimization is feasible with small spacings between the arrays, disregarding the limitation in the power output induced by backwater upstream. In this study, a 1-D channel model with a Double Multiple Streamtube code and wake sub-models are integrated to predict an array layout that will maximize the array power. The outputs of the conducted sensitivity analysis confirm that this design enabled improved power conversion with closely spaced turbines and largely spaced arrays, thus allowing for a partial recovery of the total head variation for a new array deployed upstream. In addition to the quantitative assessment of the mechanical power converted, the tool enables depth control from the d... [more]

Isentropic processes in thermodynamics are fundamental to our understanding of numerous physical phenomena across different scientific and engineering fields. They provide a theoretical reference case for the evaluation of real thermodynamic processes and observations. Yet, as analytical relations for isentropic transformations in gas dynamics are limited to ideal gases, the inability to analytically describe isentropic processes for non-ideal gases is a fundamental shortcoming. This work presents generalised isentropic relations in thermodynamics based on the work by Kouremenos et al., where three isentropic exponents γPv, γTv and γPT are introduced to replace the ideal gas isentropic exponent γ to incorporate the departure from the non-ideal gas behaviour. The general applicability of the generalised isentropic relations is presented by exploring its connections to existing isentropic models for ideal gases and incompressible liquids. Generalised formulations for the speed of sound,... [more]

Thanks to smart grids, more intelligent devices may now be integrated into the electric grid, which increases the robustness and resilience of the system. The integration of distributed energy resources is expected to require extensive use of communication systems as well as a variety of interconnected technologies for monitoring, protection, and control. The fault location and diagnosis are essential for the security and well-coordinated operation of these systems since there is also greater risk and different paths for a fault or contingency in the system. Considering smart distribution systems, microgrids, and smart automation substations, a full investigation of fault location in SGs over the distribution domain is still not enough, and this study proposes to analyze the fault location issues and common types of power failures in most of their physical components and communication infrastructure. In addition, we explore several fault location techniques in the smart grid’s distribu... [more]

The Gonghe Basin is one of the most important regions for the exploration and development of hot dry rock geothermal resources in China. However, there is still some controversy about the main heat source of hot dry rock geothermal resources in the Gonghe Basin. Combined with previous research results including three-dimensional magnetotelluric imaging and linear inversion of Rayleigh wave group and phase velocity result, we obtained a high-resolution underground spatial density distribution model of the Gonghe Basin based on satellite gravity data by using 3-D gravity focusing inversion method. According to the results, there are widely distributed low density anomalies relative to surrounding rock in the middle crust of the study area. The low-density layer is speculated to be a low-velocity, high-conductivity partial melting layer in the crust of the Gonghe Basin. The inversion result confirms for the first time the existence of a partial melt layer from the gravity point of view, a... [more]

Due to the emission of carbon dioxide and other greenhouse gases, the global climate is warming. As the world’s biggest emitter of carbon emissions, China faces a more severe challenge in reducing carbon emissions than developed countries. A reasonable prediction of the carbon peak in China will help the government to formulate effective emission reduction paths. This paper analyzes the changes in carbon emissions in China from 2004 to 2020, uses the STIRPAT model and scenario analysis method to predict carbon emissions from 2021 to 2030, and then calculates the carbon efficiency during carbon peaking to select the most effective carbon peak path for China. The results show that China’s carbon emissions increased year by year from 2004 to 2020. Under the baseline scenario, China is unlikely to reach its carbon peak before 2030. Under the regulatory scenarios, China can reach its carbon peak before 2030. The peak values from high to low are seen with the rapid development-weak carbon co... [more]

The estimation of electric power utilization, its baseload, and its heating, light, ventilation, and air-conditioning (HVAC) power component, which represents a very large portion of electricity usage in commercial facilities, are important for energy consumption controls and planning. Non-intrusive load monitoring (NILM) is the analytical method used to monitor the energy and disaggregate total electrical usage into appliance-related signals as an alternative to installing multiple electricity meters in the building. However, despite considerable progress, there are a limited number of tools dedicated to the problem of reliable and complete energy disaggregation. This paper presents an experiment consisting in designing an electrical system with electrical energy receivers, and then starting NILM disaggregation using machine learning algorithms (MLA). The quality of this disaggregation was assessed using dedicated indicators. Subsequently, the quality of these MLA was also verified us... [more]