In this paper, we propose a mitigation method for reducing lightning-induced insulator voltages based on the installation of low-voltage surge arresters aligned parallelly to the insulator. The three-dimensional finite-difference time-domain (FDTD) method is applied to numerically model a real surge arrester residual voltage evaluation system. The application of a transient current pulse, typical of lightning discharges, is considered in our numerical model. We considered cases with one or two surge arresters installed per phase, in three different geometric and parametric configurations for installing distribution surge arresters. In addition to the Kirchhoff current division, which reduces both the absorbed energy and the thermal stress, the results associated with the installation of two surge arresters parallelly aligned to the insulator show that the interaction of magnetic fields generated by the surge arresters’ currents can produce an additional strong reduction in lightning-in... [more]

Energy theft causes a lot of economic losses every year. In the practical environment of energy theft detection, it is required to solve imbalanced data problem where normal user data are significantly larger than energy theft data. In this paper, a variational autoencoder-generative adversarial network (VAE-GAN)-based energy theft-detection model is proposed to overcome the imbalanced data problem. In the proposed model, the VAE-GAN generates synthetic energy theft data with the features of real energy theft data for augmenting the energy theft dataset. The obtained balanced dataset is applied to train a detector which is designed as one-dimensional convolutional neural network. The proposed model is simulated on the practical dataset for comparing with various generative models to evaluate their performance. From simulation results, it is confirmed that the proposed model outperforms the other existing models. Additionally, it is shown that the proposed model is also very useful in t... [more]

This paper introduces a brand-new, inspired optimization algorithm (the chaotic billiards optimization (C-BO) approach) to effectively develop the optimal parameters for fuzzy PID techniques to enhance the dynamic response of the solar−hydrogen drive of an induction motor. This study compares fuzzy-PID-based C-BO regulators to fuzzy PID regulators based on particle swarm optimization (PSO) and PI-based PSO regulators to provide speed control in solar−hydrogen, induction-motor drive systems. The model is implemented to simulate the production and storage of hydrogen while powering an induction-motor drive which provides a great solution for the renewable energy storage problem in the case of solar pumping systems. MATLAB/Simulink 2021a is used to simulate and analyze the entire operation. The laboratory prototype is implemented in real time using a DSP-DS1104 board. Based on the simulation and experimental results, the proposed fuzzy-PID-based C-BO has reduced speed peak overshoot by 45... [more]

The problem of the output voltage regulation in a DC-DC boost converter feeding a DC microgrid is addressed in this research via the passivity-based control theory with a proportional−integral action (PI-PBC). Two external input estimators were implemented in conjunction with the proposed controller to make it sensorless and adaptive. The first estimator corresponds to the immersion & invariance (I&I) approach applied to calculate the expected value of the DC load, which is modeled as an unknown DC current. The second estimator is based on the disturbance−observer (DO) approach, which reaches the value of the voltage input. The main advantage of both estimators is that these ensure exponential convergence under steady-state operating conditions, and their parametrization only requires the definition of an integral gain. A comparative analysis with simulations demonstrates that the proposed PI-PBC approach is effective in regulating/controlling the voltage profile in unknown DC loads as... [more]

Anaerobic digestion (AD) is a promising way to produce renewable energy. The solid-state anaerobic digestion (SSAD) with a dry matter content more than 15% in the reactors is seeing its increasing potential in biogas plant deployment. The relevant processes involve multiple of evolving chemical and physical phenomena that are not crucial to conventional liquid-state anaerobic digestion processes (LSAD). A good simulation of SSAD is of great importance to better control and operate the reactors. The modeling of SSAD reactors could be realized either by theoretical or statistical approaches. Both have been studied to a certain extent but are still not sound. This paper introduces the existing mathematical tools for SSAD simulation using theoretical, empirical and advanced statistical approaches and gives a critical review on each type of model. The issues of parameter identifiability, preference of modeling approaches, multiscale simulations, sensibility analysis, particularity of SSAD o... [more]

Most climatic changes are not just the result of human activity, but also of business models that harm the environment. An attempt to attain an ecological balance is an answer to the challenge posed by this situation. The combustion of liquid fuels results in the atmospheric emissions of pollutants, such as nitrogen oxides (NOx), sulfur dioxide and hydrocarbons. To reduce emissions of these pollutants and at the same time attain an ecological balance, specific modifiers are applied. This paper presents an analysis of the energy efficiency and ecological efficiency of fuel oil combustion in power plant boilers based on the results of tests carried out by the present authors, in which a Fe/Mg/Ce modifier was used. The tests were carried out for system capacities ranging from 1 to 5 MW. It was found that savings on fuel, which resulted from the implementation of a system for the control and supervision of power plant operation, were in the range of 4 to 6%, and those resulting from the us... [more]

The objective of this research is to propose an efficient energy management system for photovoltaic (PV) generation units connected to monopolar DC distribution networks via convex optimization while considering a day-ahead dispatch operation scenario. A convex approximation is used which is based on linearization via Taylor’s series expansion to the hyperbolic relations between voltages and powers in the demand nodes. A recursive solution methodology is introduced via sequential convex programming to minimize the errors introduced by the linear approximation in the power balance constraints. Numerical results in the DC version of the IEEE 33-bus grid demonstrate the effectiveness of the proposed convex model when compared to different combinatorial optimization methods, with the main advantage that the optimal global solution is found thanks to the convexity of the solution space and the reduction of the error via an iterative solution approach. Different objective functions are analy... [more]

Ferromagnetic materials are widely used in the manufacturing of key parts of energy equipment, due to their good mechanical properties, such as in nuclear power and pipes. Mechanical stress exists inside of these key parts during operation. Stress can be estimated indirectly by nondestructive testing methods that measure the magnetic flux leakage signals on the surface of the structure, which is of great importance for ensuring the safety of the equipment. However, the physical mechanism of the stress and magnetic field in the magnetization of ferromagnetic materials is still unclear, leading to limited applications of the technique in practice. In this paper, magnetization tests were carried out to investigate magnetization changes under the coupling effect of stress and a noncoaxial magnetic field. Two identical Q195 low-carbon steel specimens were tested. Specimen 1 was subjected to magnetic field values successively increasing from 0 A/m to 6000 A/m under constant uniaxial tension... [more]

Corporate social responsibility can assist in reducing the noise caused by pricing volatility and a lack of energy-efficient business solutions. The study’s objective is twofold: (i) to investigate the role of corporate social responsibility (CSR) in reducing volatility through the contribution of energy-efficient strategies; (ii) to identify research trends in the field that may indicate future research directions for the development of more dynamic strategies that will help in mitigating the impact of pricing volatility. A five-step bibliometric analysis was applied to address the research question. The findings were visualized by using bibliometric tools such as R Studio, Biblioshiny, and VOSViewer. Chinese academics have been revealed as pioneers in integrating CSR into corporate strategies to reduce volatility and support energy-efficient investments. Moreover, results indicate that financial institutions must embrace a new business model based on both CSR and environmental, socia... [more]

After overcoming COVID-19, the tourism demand around the world is on the rise again. At the same time, the interest in eco-friendliness is growing again, and efforts are being made to build an eco-friendly tourism ecosystem. In this study, assuming that a battery-powered electric city tour bus is adopted instead of an existing internal combustion engine city tour bus, we tried to develop optimal design and operation algorithms for battery-powered electric city tour bus systems. The developed algorithm pursues the maximization of the profit, which is calculated through the ticket price paid by tourists using the city tour bus and the overall cost of the electric city tour bus system. In addition, the decision variables of the algorithm are the daily number and interval of operations of the electric city tour bus, which are related to the tourism demand, the battery capacity of the electric city tour bus, and whether a pantograph-type wireless charger is installed or not at the bus stop.... [more]

Wind energy forecasting is a critical aspect for wind energy producers, given that the chaotic nature and the intermittence of meteorological wind cause difficulties for both the integration and the commercialization of wind-produced electricity. For most European producers, the quality of the forecast also affects their financial outcomes since it is necessary to include the impact of imbalance penalties due to the regularization in balancing markets. To help wind farm owners in the elaboration of offers for electricity markets, the EOLO predictor model can be used. This tool combines different sources of data, such as meteorological forecasts, electric market information, and historic production of the wind farm, to generate an estimation of the energy to be produced, which maximizes its financial performance by minimizing the imbalance penalties. This research study aimed to evaluate the performance of the EOLO predictor model when it is applied to the different Spanish electricity... [more]

A power conversion interface for a small-capacity photovoltaic power generation system (PPGS) is proposed in this paper. The proposed power conversion interface is composed of a DC−DC converter (DDC), a battery pack and a buck−boost inverter (BBI). The battery pack is integrated to the power conversion interface to store or release energy for smoothing the power fluctuation of the small-capacity PPGS. The battery pack is only activated when a large power change occurs in the photovoltaic array (PV array). The DC power, no matter whether is from the PV array or the battery pack, needs to be converted into AC power only by the BBI in the proposed power conversion interface. Moreover, the PV array charges the battery pack only through the DDC, which simplifies the power circuit and improves the power conversion efficiency. To verify the feasibility of the proposed power conversion interface, a hardware prototype is established for practical experiments.

The conditions for the mild initiation of the detonation of homogeneous stoichiometric ethylene-oxygen mixtures diluted with nitrogen up to ~40%vol. in a planar semi-confined slit-type combustor with a slit 5.0 ± 0.4 mm wide, simulating the annular combustor of a Rotating Detonation Engine (RDE), are determined experimentally using self-luminous high-speed video recording and pressure measurements. To ensure the mild detonation initiation, the fuel mixture in the RDE combustor must be ignited upon reaching a certain limiting (minimal) fill with the mixture and the arising flame must be transformed to a detonation via deflagration-to-detonation transition (DDT). Thus, for mild detonation initiation in a C2H4 + 3O2 mixture filling the slit, the height of the mixture layer must exceed the slit width by approximately 10 times (~50 mm), and for the C2H4 + 3(O2 + 2/5 N2) mixture, by approximately 60 times. The limiting height of the mixture layer required for DDT exhibits a sharp increase at... [more]

For the rotor, achieving relatively high aerodynamic performance in specific wind conditions is a long-term goal. Inspired by the remarkable flight characteristics of owls, an optimal trailing edge serration design is investigated and proposed for a wind turbine rotor blade. Fluid flow interaction with the proposed serrations is explored for different wind conditions. The result is supported by subsequent validation with three-dimensional numerical tools. The present work employs a statistical-numerical method to predict and optimize the shape of the serrations for maximum aerodynamic improvement. The optimal combination is found using the Taguchi method with three factors: Amplitude, wavelength, and serration thickness. The viability of the solution on an application is assessed using the Weibull distribution of wind in three selected regions. Results show that the presence of serration is capable of improving the annual power generation in all the investigated cities by up to 12%. Th... [more]

The rapid development of natural gas pipelines has highlighted the need to utilize SCADA (supervisory control and data acquisition) system data. In this paper, a heat transfer model of a natural gas pipeline based on data feature extraction and first principle models, which makes full use of the measured temperatures at each end of the pipeline, is proposed. Three methods, the NARX neural network (nonlinear autoregressive neural network with exogenous inputs), time series decomposition, and system identification, were used to model the changes of gas temperatures of the pipeline. The NARX neural network method uses a cyclic neural network to directly model the relationship of temperature between the start and the end of the pipeline. The measured temperature series at the pipeline inlet and outlet were decomposed into trend items, fluctuation items, and noise items based on the time series decomposition method. Then the three items were fitted separately and combined to form a new temp... [more]

Currently, studies on the energy efficiency of manufacturing systems usually lack synthetic and systematic techniques. In this paper, a holistic framework is demonstrated in order to achieve more sustainable manufacturing, which covers machine-level, system-level and life-cycle-level energy efficiency techniques. Based on these, the mechanism of how energy consumption is affected by machining processes and system operation is analyzed to achieve a comprehensive decision on energy efficiency optimization. Four main topics are included in this paper: (1) Hierarchical sustainability goals and metrics for energy-efficient manufacturing; (2) Machine-level machining processes optimization for energy efficiency enhancement; (3) System-level innovations for efficient consumption management; (4) Life-cycle level energy flow modeling and energy recycling strategy. An automotive engine manufacturing system is taken as an example to build a concrete understanding of the application of the framewor... [more]

This paper presents the design and an analysis of a surface PM vernier generator (SPMVG) for MW-scale direct-drive (DD) wind turbine application. An SPMVG has the advantage of higher torque density; however, especially at higher power ratings with increased electrical loadings, the power factor worsens and there are some serious concerns including magnetic saturation of cores and PM demagnetization. These issues are directly related to machine design parameters such as PM dimensions, applied electrical loading, slot geometry and the choice of slot−pole combination. It is determined that depending on the PM thickness and a few other design variables, each slot−pole combination has an optimal value of specific electrical loading. The use of the optimal value of specific electrical loading ensures that the machine is not saturated, the performance is optimum and the power factor is not unnecessarily degraded. Moreover, under certain design constraints, design criteria are developed that e... [more]

LLCL filters for grid-tied inverters have been adopted to get better performance for the harmonics near the switching frequency than commonly used LCL filters. However, the resonant peak caused by a pair of unstable resonance poles of the LLCL filters is introduced and makes the system become unstable. In this paper, a biquad filter composed of a notch filter and a resonator is introduced to restrain the resonant peak. In this method, the resonance point and the notch point of the biquad filter are placed at the appointed frequency, and the resonant peak is transferred to the stable area by phase transformation, so that the system does not cross −180° at the resonant peak. This method makes the system have higher control bandwidth and stronger robustness even in a weak power grid. Meanwhile, a proportional-integral multiresonant repetitive controller is used to restrain low-frequency current harmonics and improve the steady-state and dynamic performance of the control system. Furthermo... [more]

Urea electrolysis is regarded as a prospective method for energy-saving hydrogen production. However, the practical application of this technology is limited by the lack of high-performance bifunctional catalysts for hydrogen evolution reaction (HER) and urea oxidation reaction (UOR). Herein, a heterostructure catalyst composed of NiFe layered double hydroxide (LDH) and sulfides (NiFe LDH-NiFeSx/NF) catalysts is prepared via a simple one-step hydrothermal approach. Remarkably, the prepared NiFe LDH-NiFeSx/NF required 138 mV and 1.34 V to achieve 10 mA cm−2 for HER and UOR in 1 M KOH and 0.33 M urea, respectively. Furthermore, when NiFe LDH-NiFeSx/NF is used as a cathode for urea electrolysis, only 1.44 V is required at 10 mA cm−2, which is much lower than the 1.53 V needed for overall water splitting.

Daylight penetration significantly affects building thermal-daylighting performance, and serve a dual function of permitting sunlight and creating a pleasant indoor environment. More recent attention has focused on the provision of daylight in the rear part of indoor spaces in designing sustainable buildings. Passive Anidolic Daylighting Systems (ADS) are effective tools for daylight collection and redistribution of sunlight towards the back of the room. As affordable and low-maintenance systems, they can provide indoor daylight and alleviate the problem of daylight over-provision near the window and under-provision in the rear part of the room. Much of the current literature on the ADS pays particular attention to visual comfort and rarely to thermal comfort. Therefore, a reasonable compromise between visual and thermal comfort as well as energy consumption becomes the main issue for energy-optimized aperture design in the tropics and subtropics, in cities such as Sydney, Australia. T... [more]

Waste straw contains a large amount of lignin, and its resource utilization is not only in line with the national double carbon development strategy, but also to alleviate environmental pollution. Hydrothermal carbonization is a new thermochemical conversion technology, which has attracted much attention because it can directly transform carbon containing waste raw materials with high moisture content and low energy density. To investigate the physicochemical properties and aromatization changes of lignin hydrochar, hydrothermal carbonization experiments were carried out at 290 °C and a solid−liquid ratio of 1:20 for 0.00, 0.25, 0.50, 1.00, 1.50, 2.00, 4.00, 8.00 h, respectively. The experimental results shows that hydrothermal carbonization can increase the combustion quality of lignin. Physical and chemical properties analysis shows that with the increase of hydrothermal carbonization time from 0 to 2 h, the hydrochar content increased from 21.21% to 26.02% and the HHV of hydrochar i... [more]

To elucidate the wind-direction dependence of the rotor performance in closely spaced vertical-axis wind turbines, wind-tunnel experiments were performed at a uniform wind velocity. In the experiments, a pair/trio of three-dimensional printed model turbines with a diameter of D = 50 mm was used. The experiments were performed systematically by applying incremental adjustments to the rotor gap g and rotational direction of each rotor and by changing the wind direction. For tandem layouts, the rotational speed of the downwind rotor is 75−80% that of an isolated rotor, even at g/D = 10. For the average rotational speed of the rotor pair, an origin-symmetrical and a line-symmetrical distribution are observed in the co-rotating and inverse-rotating configurations, respectively, thereby demonstrating the wind-direction dependence for the rotor pair. The inverse-rotating trio configuration yields a higher average rotational speed than the co-rotating trio configuration for any rotor spacing u... [more]

Cold stress in sheep is usually overlooked, even though the animals’ welfare and productivity are affected by low temperatures. The aim of this research was to find out if and to what extent the temperature inside a sheep barn could be maintained within the range of the thermoneutral zone during winter, primarily to increase feed conversion and to reduce GHG emissions. For this reason, an automation system was installed at a sheep barn in northern Greece, and heat losses from the building were calculated. The biogas potential of the sheep barn waste was examined in the laboratory via the BMP method. The results showed that the installation of an automation system together with a hypothetical biogas heating system could maintain the barn’s temperature in the range of a sheep’s thermoneutral zone during winter for the 94% of the scenarios examined if the total energy of the biogas was utilized, while heating energy that was instantly and continuously used succeeded in 48% of the investig... [more]

This article introduces a device for the precise testing of the non-linearities of inductive voltage dividers and digitizers used in digital impedance bridges. The device is based on switched capacitors composed of an NP0 dielectric, in addition to high-quality microwave relays. The article discusses issue concerning the symmetrization of the device as one of the main ways to achieve a high accuracy. Furthermore, a temperature-stabilization system for the device is presented. The system uses a battery management system to estimate the quantity of the energy available in the supply battery. The article further discusses problems encountered with the design of heating elements, which are situated on a laminate with an aluminum substrate.

The design and implementation of efficient photovoltaic (PV) plants and wind farms require a precise analysis and definition of specifics in the region of interest. Reliable Artificial Intelligence (AI) models can recognize long-term spatial and temporal variability, including anomalies in solar and wind patterns, which are necessary to estimate the generation capacity and configuration parameters of PV panels and wind turbines. The proposed 24 h planning of renewable energy (RE) production involves an initial reassessment of the optimal day data records based on the spatial pattern similarity in the latest hours and their follow-up statistical AI learning. Conventional measurements comprise a larger territory to allow the development of robust models representing unsettled meteorological situations and their significant changes from a comprehensive aspect, which becomes essential in middle-term time horizons. Differential learning is a new unconventionally designed neurocomputing stra... [more]