This paper deals with voltage control in a buck DC-DC converter. In fact, dynamic mathematical equations describing the principle behavior of the above system have been derived. Due to the nonlinearity of the established model, a nonlinear control algorithm is adopted. It is based on the sliding mode control approach. To highlight the performance of the latter, a comparative study with four control algorithms is carried out. The validity of the model and the performance of the conceived algorithms are verified in simulation. Both the system and the algorithm controls are implemented in the Matlab/Simulink environment. Extensive results under different operational conditions are presented and discussed.

Pneumatic conveying is widely used in coal mining. As the lowest conveying velocity of materials, the pickup velocity is the key to the study of gas−solid two-phase flow. In this study, the pickup velocity of pebble particles was experimentally investigated. When the particle size is 3−9 mm, the airflow velocity was found to suitably describe the results as a function of the pickup velocity and have a high correlation. When the swirl number is 0.2, the optimal swirl number was found for which the highest particle pickup ratio was observed. Based on four different methods, namely, visual observation, mass weighing, coefficient of difference analysis, and determination of the peak-average ratio of the pressure drop in the flow field to measure the pickup velocity of the spraying material, the results showed that the accuracy of the particle pickup velocity obtained through visual observation was the lowest, and when the mass−loss rate of the particle was selected as the measurement index... [more]

The current work presents an effective fault detection and diagnosis (FDD) technique in wind energy converter (WEC) systems. The proposed FDD framework merges the benefits of kernel principal component analysis (KPCA) model and the bidirectional long short-term memory (BiLSTM) classifier. In the developed FDD approach, the KPCA model is applied to extract and select the most effective features, while the BiLSTM is utilized for classification purposes. The developed KPCA-based BiLSTM approach involves two main steps: feature extraction and selection, and fault classification. The KPCA model is developed in order to select and extract the most efficient features and the final features are fed to the BiLSTM to distinguish between different working modes. Different simulation scenarios are considered in this study in order to show the robustness and performance of the developed technique when compared to the conventional FDD methods. To evaluate the effectiveness of the proposed KPCA-based... [more]

Wind turbine wake redirection drawn by a yaw control has been proposed as a strategy to improve the performance of wind farms. However, the characteristics and the development of the curled wake structure deformed by the yaw action of the rotor are not well understood. In the present study, the structure of the wake behind a wind turbine imparted with various yaw angles subjected to uniform inflow was investigated using large-eddy simulation. The NREL 5MW reference wind turbine was modeled with an actuator disk with rotation to study the deformation process of the curled wake. The source of the vertical asymmetry in the wake deformation was found to be based on the interaction of global wake rotation and a counter-rotating vortex pair induced by the yaw angle. The yaw angle had a profound influence on the distortion of the wake and its trajectory, whose effect was naturally mitigated with downstream distance.

The modern-day urban energy sector possesses the integrated operation of various microgrids located in a vicinity, named cluster microgrids, which helps to reduce the utility grid burden. However, these cluster microgrids require a precise electric load projection to manage the operations, as the integrated operation of multiple microgrids leads to dynamic load demand. Thus, load forecasting is a complicated operation that requires more than statistical methods. There are different machine learning methods available in the literature that are applied to single microgrid cases. In this line, the cluster microgrids concept is a new application, which is very limitedly discussed in the literature. Thus, to identify the best load forecasting method in cluster microgrids, this article implements a variety of machine learning algorithms, including linear regression (quadratic), support vector machines, long short-term memory, and artificial neural networks (ANN) to forecast the load demand i... [more]

Numerous numerical and experimental studies have been conducted regarding the Concentrated Photovoltaic Thermal (CPVT) system because of its significant potential for efficient conversion of solar energy. The overall efficiency of the CPVT system is strongly dependent on the device, which extracts excess heat from photovoltaic cells. The most efficient cooling technology involves active cooling, which means that heat is collected from the PV cell via the forced flow of heat transfer fluid. This research paper provides an extensive discussion on devices dedicated to active-cooling CPVT systems, taking into account the latest solutions. First, a short introduction regarding CPVT systems and their main components is presented. The second part of this study presents state-of-the-art solutions in the field of heat extraction devices for the active cooling of photovoltaic cells. The available solutions are classified into two main groups depending on the scale of internal channels: macro- an... [more]

Due to their large and increasing size and the corrosive nature of salt water and high wind speeds, offshore wind turbines are required to be more robust, more rugged and more reliable than their onshore counterparts. The dynamic characteristics of the blade and its response to applied forces may be influenced dramatically by rotor rotational speed, which may even threaten the stability of the wind turbine. An accurate and computationally efficient structural dynamics model is essential for offshore wind turbines. A comprehensive model that takes the centrifugal stiffening effect into consideration could make rapid and accurate decisions with live data sensed from the structure. Moreover, this can enhance both the performance and reliability of wind turbines. When a rotating blade deflects in its plane of rotation or perpendicular to it, the centrifugal force exerts an inertia force that increases the natural frequencies and changes the mode shapes, leading to changes in the dynamic re... [more]

In the development of deep geological repositories (DGRs), performance assessment modeling is used to evaluate the integrity and performance of the engineered and geological barriers for thousands or millions of years of evolution of the disposal system. To evaluate the suitability of a site for a DGR, geoscientific data from dedicated site investigation programs are integrated into site-specific assessments. This paper presents the development and implementation of a modeling workflow aimed at comparing three potential siting areas for a DGR in Switzerland from the viewpoint of long-term safety and technical feasibility. The workflow follows the guidelines of the national regulator addressing safety relevant criteria such as the barrier efficiency of the host rock and its mechanical and chemical integrity in response to repository-induced influences and the long-term stability of the repository site over geological scales. In the regulatory requirements, the role of parametric, concep... [more]

Compared with oil, natural gas has been the focus of the energy industry in recent years. Renewable energy is the goal and trend of future developments, and it has made considerable progress; however, it has not reached the ideal popularization rate. Therefore, natural gas is still very important so far. In this paper, the influence of thermal gas injection and room temperature gas injection on gas reservoir recovery is analyzed, and the method of water plugging by hot gas injection in tight gas reservoir is put forward. Indoor simulation experiments were carried out to evaluate the effect of hot-gas injection in cut pore water and the degree of water blockage. On this basis, the numerical simulation of removing water blockage by hot-gas injection was carried out. The changes in core temperature and remaining water saturation were discussed by using simulation models. Results of this study can provide a theoretical basis for removing water blockage in actual oil and gas reservoirs.

In the pursuit of more efficient vehicles on the world’s roads, the vehicle thermal management system has become a limiting factor when it comes to EV range and battery life. In extreme climates, if the thermal system cannot pull down or warm up the EV powertrain in a timely manner, the battery is at serious risk of capacity loss or accelerated degradation. As waste heat is inherently limited with EVs, the way in which we provide the heat for warm-up must be as efficient as possible to reduce the load on the battery. In this paper, a revolutionary waste heat recovery (WHR) thermal management system designed by Tesla, nicknamed the ‘Octovalve’, is described, modelled, and simulated. This paper contributes to collective knowledge by presenting an in-depth breakdown of the key operating modes and outlining the potential benefits. Modelled in the multidomain Simulink Simscape software, the octovalve’s performance is directly compared to a typical EV WHR thermal management system. The syste... [more]

Energy-saving is a mandatory research topic since the growing population demands additional energy yearly. Moreover, climate change requires more attention to reduce the impact of generating more CO2. As a result, some new research areas need to be explored to create innovative energy-saving alternatives in electrical devices that have high energy consumption. One research area of interest is the computer visual classification for reducing energy consumption and keeping thermal comfort in thermostats. Usually, connected thermostats obrtain information from sensors for detecting persons and scheduling autonomous operations to save energy. However, there is a lack of knowledge of how computer vision can be deployed in embedded digital systems to analyze clothing insulation in connected thermostats to reduce energy consumption and keep thermal comfort. The clothing classification algorithm embedded in a digital system for saving energy could be a companion device in connected thermostats... [more]

Eddy current losses in magnets are a major consideration in the rotor design of permanent magnet synchronous motors (PMSMs). Stator design choices and the use of modern inverters with high switching frequency introduce harmonics that can contribute to significant losses in the magnets, causing the rotor to heat up. In typical PMSMs, the lack of rotor cooling can cause the magnet’s performance to degrade at high temperatures and eventually demagnetize. This review examines a large number of studies analyzing magnet eddy current losses using analytical methods and finite-element analysis. In some of these studies, magnet segmentation is carried out to reduce the losses; however, their loss-reduction effects depend highly on the type of PMSM and the mix of stator harmonics. Magnet segmentation without considering these effects can, in fact, increase the magnet losses, in addition to the extra manufacturing efforts. Multiple design analysis show the influence of rotor−stator geometric feat... [more]

The leakage of the tribological contact in axial piston pumps significantly impacts the pump efficiency. Leakage observations can be used to optimize the pump design and monitor the behavior of the tribological contact. However, due to assembly limitations, it is not always feasible to observe the leakage of each tribological contact individually with a flow rate sensor. This work developed a data-driven virtual flow rate sensor for monitoring the leakage of cradle bearings in axial piston pumps under different operating conditions and recess pressures. The performance of neural network, support vector regression, and Gaussian regression methods for developing the virtual flow rate sensor was systematically investigated. In addition, the effect of the number of datasets and label distribution on the performance of the virtual flow sensor were systematically studied. The findings are verified using a data-driven virtual flow rate sensor to observe the leakage. In addition, they show tha... [more]

The COVID-19 pandemic and Russia’s war on Ukraine have impacted the global economy, including the energy sector. The pandemic caused drastic fluctuations in energy demand, oil price shocks, disruptions in energy supply chains, and hampered energy investments, while the war left the world with energy price hikes and energy security challenges. The long-term impacts of these crises on low-carbon energy transitions and mitigation of climate change are still uncertain but are slowly emerging. This paper analyzes the impacts throughout the energy system, including upstream fuel supply, renewable energy investments, demand for energy services, and implications for energy equity, by reviewing recent studies and consulting experts in the field. We find that both crises initially appeared as opportunities for low-carbon energy transitions: the pandemic by showing the extent of lifestyle and behavioral change in a short period and the role of science-based policy advice, and the war by highlight... [more]

Wastewater treatment is an energy-intensive process for treating liquid-phase pollutants in urban settlements. The aerobic processes of the biological treatment involve a significant air demand. An optimal control strategy could be used to minimize the amount of excess air entering the system due to safety factors applied in the design procedures. A plant-wide mechanistic modeling approach including an activated sludge model and one-dimensional settler model was proposed as an effective tool for predicting the actual air demand and for selecting the optimal aeration strategy. In this study, a sewage treatment plant receiving strong influent flow was investigated. At the sludge ages of 14−18 days, the plant was capable of achieving a 90% organic matter reduction and 85% nutrient reduction. By applying a constant dissolved oxygen concentration of 1.5 mg/L, the air demand decreased by 25%, which could be further increased by 10% if the cascade ammonium control approach was applied at peak... [more]

Electric vehicle (EV) charging may impose a substantial power demand on existing low voltage (LV) and medium voltage (MV) networks, which are usually not prepared for high power demands in short time intervals. The influx of E-mobility may require an increase in grid reinforcements, but these can be reduced and optimized by a combination of new technologies, tools, and strategies, such as the deployment of solar PV generation integrated with aggregated energy storage systems. One of the challenges in the implementation of charging infrastructures in public stations is coupling the projected sizes of energy demand and power requirements in each location for each charger. This paper describes a method to estimate projected values for energy consumption and power demand in EV fast charging stations (CS). The proposed ideas were applied in a concept facility located in Campinas, Brazil, in a structure equipped with two 50 kW DC Fast Chargers, local 12.5 kW/13.2 kWp PV generation (to reduce... [more]

With the increasingly obvious DC characteristics at both ends of the source and load sides of the low-voltage distribution network, the application scenarios of low-voltage DC microgrid gradually appear. Compared with the AC system, the DC microgrid has the characteristics of low inertia, weak damping, and poor anti-disturbance capabilities, all of which are important for improving operational stability. A virtual inertia adaptive control approach for fast-tracking energy storage under varied disturbances is presented using energy storage as a virtual inertia unit. Firstly, a stability analysis model including constant power load is constructed for the low-voltage DC microgrid; then, the control logic of the virtual inertia of the energy storage system is designed. Finally, the corresponding model is built in MATLAB/SIMULINK and the experiment platform to verify the correctness and effectiveness of the proposed control strategy.

In industrial-scale biogas production from cereal straw, large quantities of solid fiber-rich digestate are produced as residual material. These residues usually contain high amounts of cellulose, hemicellulose and lignin and thus have potential for further utilization. However, they also contain impurities such as ammonia and minerals, which could negatively affect further utilization. Against this background, the present study investigates how this fibrous straw digestate can be fractionated by a combined hydrothermal and enzymatic treatment and what influence the impurities have in this process. Therefore, it is analyzed how the fractions cellulose, hemicellulose and lignin are modified by this two-stage treatment, using either raw digestate (including all impurities) or washed digestate (containing only purified fibers) as the substrate. For both substrates, around 50% of the hemicellulose is solubilized to xylans after 50 min of hydrothermal treatment using steam at 180 ∘C. Furthe... [more]

This paper presents proposals for using the direct-contact gravel, ground, air heat exchanger in single-family residential buildings with a passive house standard, according to the Passive House Institute (PHI). The methodology of their application consists of using heat and cold from the ground at an insignificant depth (about 1.5−4.0 m below the ground level for the central European climate) through an aggregate that is buried in the ground. This solution of simple installations is used for preheating and cooling fresh air drawn into the building through a mechanical ventilation system with heat recovery. In more complex applications it can be integrated with the source of heat and cold in passive buildings to create complete heating, cooling, and ventilation systems. In both cases, the air flowing through the exchanger is cooled and dried in summer, heated and humidified in winter, and filtered from pollen and bacteria all year. Direct contact of the deposit with the surrounding nat... [more]

Harmonic pollution sources in microgrids have the characteristics of high penetration and decentralization, as well as forming a full network. Local harmonic mitigation is a traditional harmonic mitigation method, which has the disadvantages of complexity and costly operation. Based on the idea of the decentralized autonomy of power quality, this paper establishes a comprehensive optimization model of the active power and harmonic mitigation capacities of grid-connected inverters based on two-layer optimization and realizes harmonic mitigation. Firstly, based on the harmonic sensitivity analysis, the calculation method of harmonic mitigation capacity is given. Secondly, a two-layer model of harmonic mitigation optimization is established. The upper-layer optimization model takes the minimum operation cost of the microgrid as the objective and the active power reduction in the multi-functional grid-connected inverter (MFGCI) as the optimization variable. The lower-layer optimization mod... [more]

This work focuses on the use of a one-phase direct current (DC) power supply equipped with a shunt active filter feature, which enabled the possibility of compensation (minimisation) of reactive and distortion power, generated by a group of loads, that was connected to the same power grid node as the power supply. A tuned inductor, which was included at the input of the controlled current source (constituting the main part of the power supply) allowed for an improvement in the quality of the compensation process, compared to a device with a fixed inductive filter This resulted in a visible reduction of the nonlinear distortions of the grid current. The improvement was made possible by extending the frequency response of the current source, which allowed to increase the dynamics of the current changes at the input of the power supply. This solution represents a new approach to such power devices. This work describes the principle of operation of the proposed converter solution and prese... [more]

A deep review of the state of the electromobility in urban public transport by bus was conducted from all different charging strategies, types of chargers, and e-buses with a general overview and SWOT analysis. A review of five case studies worldwide was also conducted and a real case study with real data was shown in depth: EMT Madrid, where all chargers and charging systems were developed in a single operation center. Total Cost of Ownership (TCO) from the literature and from the case study for e-buses were shown as compared with different bus technologies.

Electrostatic energy harvesters convert kinetic energy into electrical energy via variable capacitors. Efforts to improve their power output are hampered by a lack of understanding of the fundamental limit for energy conversion efficiency. In heat engines, the theoretical limit of conversion efficiency is intrinsically related to entropy and the second law of thermodynamics. Laying the foundation for similar concepts for kinetic energy harvesters may be necessary for establishing a conversion efficiency limit. Thus, the mixing entropy concept is borrowed from statistical mechanics and is adapted here, for the first time, to characterize the energy transfer between coupled mechanical−electrical oscillators. The investigated system is composed of a spring-mass coupled to an inductance-capacitor circuit via a variable capacitor. Combining the two subsystems (electrical and mechanical) generates entropy, referred to as mixing entropy. A non-dimensional study of the governing equations of t... [more]

The carbon emissions of sectors and households enabled by primary inputs have practical significance in reality. Considering the mutual effect between the industrial sector and the household, this paper firstly constructed an environmentally extended semi-closed Ghosh input−output model with an endogenized household sector to analyze the relationship between carbon emissions and the Chinese economy from the supply-side perspective. The structural decomposition analysis and the hypothetical extraction method were remodified to identify the supply-side driving effects of the changes in carbon emissions and investigate the net carbon linkage. The results show that the electricity, gas, and water supply sector was the key sector with the highest carbon emission intensity enabled by primary inputs. The household sector had an above 93% indirect effect of the enabled intensity, with its enabled intensity dropping significantly by more than 55% from 2007 to 2017. The operating surplus and mix... [more]

To comprehensively study the influence of the guide vane inlet slope on the axial-flow pump, eight groups of axial-flow pumps with different guide vane inlet slopes are designed and studied in this paper. Four groups of schemes increase the relative slope at the rim of the guide vane blade, and the other four groups increase the relative slope at the hub. Numerical simulations have been verified experimentally and show good simulation accuracy. The numerical simulation results show that reducing the hub height of the guide vane can improve the head and efficiency of the axial-flow pump. Compared with the original scheme, the scheme H2/S2 is more stable in velocity and turbulent kinetic energy and has fewer vortices and low-speed areas at the guide vane. The scheme H3/S3 also exhibits excellent hydraulic performance and internal flow characteristics. It is recommended that when designing an axial-flow pump, the distance between the impeller and the guide vane at the hub can be appropria... [more]