bluuebunny/crossref_metadata_2025 huggingface dataset:
Introducing Artificial/Computational Intelligence-Derived Non-Parametric Transfer Functions for the Implementation of Dynamic Circular Economy Decision-Making Systems
Authors: Yu Minghua , Zheng Junjun
Published: February 2023

With the development of science and technology, resource consumption has increasingly become a social problem. The circular economy is an economic form of a comprehensive utilization of resources. At present, China’s circular economy industry has begun to develop towards intensification, scale and specialization. With the deepening of research on the value of a comprehensive utilization of resources, the traditional economic field has undergone tremendous changes. According to the current situation of circular economy industry, an intelligent decision-making system is designed using artificial intelligence technology. Empirically, using the circular economy model and combining the sequence parameters to determine the sequence parameter indicators of the scientific and technological innovation subsystem and the energy saving and emission reduction subsystem, the correlation analysis of each indicator is carried out, and the order degree of the two subsystems is obtained respectively, so as to obtain for the enterprise the degree of synergy of the evolution system of the circular economy synergy of industries and industrial clusters. After repeated exploratory tests, it is found that the calculation has achieved over 98% of the precision of an astute direction, and has specific use and value because of the enormous number of preparing modes and trial dependability. Making a specific commitment to the circular economy is a trusted and logical solution.
An Improved Vision Transformer Network with a Residual Convolution Block for Bamboo Resource Image Identification
Authors: Zou Qing , Jin Xiu , Song Yi , Wang Lianglong , Li Shaowen , Rao Yuan , Zhang Xiaodan , Gao Qijuan
Published: February 2023

Bamboo is an important economic crop with up to a large number of species. The distribution of bamboo species is wide; therefore, it is difficult to collect images and make the recognition model of a bamboo species with few amount of images. In this paper, nineteen species of bamboo with a total of 3220 images are collected and divided into a training dataset, a validation dataset and a test dataset. The main structure of a residual vision transformer algorithm named ReVI is improved by combining the convolution and residual mechanisms with a vision transformer network (ViT). This experiment explores the effect of reducing the amount of bamboo training data on the performance of ReVI and ViT on the bamboo dataset. The ReVI has a better generalization of a deep model with small-scale bamboo training data than ViT. The performances of each bamboo species under the ReVI, ViT, ResNet18, VGG16, Densenet121, Xception were then compared, which showed that ReVI performed the best, with an average accuracy of 90.21%, and the reasons for the poor performance of some species are discussed. It was found that ReVI offered the efficient identification of bamboo species with few images. Therefore, the ReVI algorithm proposed in this manuscript offers the possibility of accurate and intelligent classification and recognition of bamboo resource images.
A 3.4–3.6 GHz High-Selectivity Filter Chip Based on Film Bulk Acoustic Resonator Technology
Authors: Yang Qinghua , Xu Yao , Wu Yongle , Wang Weimin , Lai Zhiguo
Published: February 2023

The development of mobile 5G technology poses new challenges for high-frequency and high-performance filters. However, current commercial acoustic wave filters mainly focus on 4G LTE, which operates below 3 GHz. It is necessary to accelerate research on high-frequency acoustic wave filters. A high-selectivity film bulk acoustic resonator (FBAR) filter chip for the 3.4–3.6 GHz range was designed and fabricated in this paper. The design procedure includes FBAR parameter fitting, filter schematic analysis, and the generation principle of transmission zeros (TZs). The measured results show that the filter chip is of high roll-off and stopband suppression. Most of the stopband suppression is better than 35 dB. Finally, error analysis was conducted, and FBAR parameters were modified after testing for future filter design work.
Cooperative Jamming with AF Relay in Power Monitoring and Communication Systems for Mining
Authors: Meng Wei , Gu Yidong , Bao Jianjun , Gan Li , Huang Tao , Kong Zhengmin
Published: February 2023

In underground mines, physical layer security (PLS) technology is a promising method for the effective and secure communication to monitor the mining process. Therefore, in this paper, we investigate the PLS of an amplify-and-forward relay-aided system in power monitoring and communication systems for mining, with the consideration of multiple eavesdroppers. Explicitly, we propose a PLS scheme of cooperative jamming and precoding for a full-duplex system considering imperfect channel state information. To maximize the secrecy rate of the communications, an effective block coordinate descent algorithm is used to design the precoding and jamming matrix at both the source and the relay. Furthermore, the effectiveness and convergence of the proposed scheme with high channel state information uncertainty have been proven.
A DDoS Attack Detection Method Based on Natural Selection of Features and Models
Authors: Ma Ruikui , Chen Xuebin , Zhai Ran
Published: February 2023

Distributed Denial of Service (DDoS) is still one of the main threats to network security today. Attackers are able to run DDoS in simple steps and with high efficiency to slow down or block users’ access to services. In this paper, we propose a framework based on feature and model selection (FAMS), which is used for detecting DDoS attacks with the aim of identifying the features and models with a high generalization capability, high prediction accuracy, and short prediction time. The FAMS framework is divided into four main phases. The first phase is data pre-processing, including operations such as feature coding, outlier processing, duplicate elimination, data balancing, and normalization. In the second stage, 79 features are extracted from the dataset and selected by the feature selection algorithms filter, wrapper, embedded, variance, mutual information, backward elimination, Lasso.L1, and random forest. The purpose of feature selection is to simplify the model, avoid dimensional disasters, reduce computational costs, and reduce the prediction time. The third stage is model selection, which aims to select the most ideal algorithm from GD, SVM, LR, RF, HVG, SVG, HVR, and SVR using a model selection algorithm for the selected 21 features, and the results show that RF is far ahead in all evaluation indexes compared to the other models. The fourth stage is model optimization, which aims to further improve the performance of the RF algorithm in detecting DDoS attacks by optimizing the parameters max_samples, max_depth, n_estimators for the initially selected RF by the RF optimization algorithm. Finally, by testing the 100,000 CIC-IDS2018, CIC-IDS2017, and CIC-DoS2016 synthetic datasets, the results show that all the results have achieved excellent performance in the same category. Moreover, the framework also shows an excellent generalization performance by testing over 1 million synthetic datasets and over 330,000 CIC-DDoS2019 datasets.
Comparative Life Cycle Assessment of Catalytic Intermediate Pyrolysis of Rapeseed Meal
Authors: Soleymani Angili Tahereh , Grzesik Katarzyna , Jerzak Wojciech
Published: February 2023

Biowaste valorization is a means for tackling resource depletion and climate change, which gives rise to environmental benefits and economic growth. One of the most known technological routes to convert biowaste into bioproducts is pyrolysis, which may conduct with and without catalyst application. The purpose of this study was to investigate an early-stage life-cycle assessment (LCA) for catalytic intermediate pyrolysis to valorize rapeseed meal, split over the scenarios using ZSM-5 and zeolite Y catalysts. Four selected environmental impact categories were assessed by IMPACT 2002+ methodology. The results revealed that the ZSM-5 catalytic pyrolysis led to bigger environmental impacts than the pyrolysis utilizing zeolite Y in all compared impact categories except global warming. The scenario that involved zeolite Y had around 20% GHG intensity greater than ZSM-5 pyrolysis. The bulk of GHG emissions mostly involved CO2 and methane generated from electricity consumption, which was provided by fossil resources. Applying ZSM-5 in the pyrolysis increased environmental burdens in non-renewable energy, respiratory inorganics, and terrestrial ecotoxicity by 140.88 MJ primary, 8.83 × 10−3 kg PM2.5 eq. and 125.63 kg TEG soil, respectively. The major driving factor of high value in mentioned categories was the manufacturing process of the ZSM-5 catalyst by utilizing natural gas and chemicals, such as phosphorus trichloride, sodium hydroxide and sodium silicate. Given that catalysts can play a substantial role in the emissions resulting from bio-based products, hence LCAs of pyrolysis should consider the potential influence of catalysts in the valorization processes. This study can predict environmental hotspots in the early stages of bio-waste valorization and show the potential defects of implanted biorefinery at pilot/industrial scales.
Design and Comparative Analysis of Several Model Predictive Control Strategies for Autonomous Vehicle Approaching a Traffic Light Crossing
Authors: Cvok Ivan , Pavelko Lea , Škugor Branimir , Deur Joško , Tseng H. Eric , Ivanovic Vladimir
Published: February 2023

Recent advancements in automated driving technology and vehicle connectivity are associated with the development of advanced predictive control systems for improved performance, energy efficiency, safety, and comfort. This paper designs and compares different linear and nonlinear model predictive control strategies for a typical scenario of urban driving, in which the vehicle is approaching a traffic light crossing. In the linear model predictive control (MPC) case, the vehicle acceleration is optimized at every time instant on a prediction horizon to minimize the root-mean-square error of velocity tracking and RMS acceleration as a comfort metric, thus resulting in a quadratic program (QP). To tackle the vehicle-distance-related traffic light constraint, a linear time-varying MPC approach is used. The nonlinear MPC formulation is based on the first-order lag description of the vehicle velocity profile on the prediction horizon, where only two parameters are optimized: the time constant and the target velocity. To improve the computational efficiency of the nonlinear MPC formulation, multiple linear MPCs, i.e., a parallel MPC, are designed for different fixed-lag time constants, which can efficiently be solved by fast QP solvers. The performance of the three MPC approaches is compared in terms of vehicle velocity tracking error, root-mean-square acceleration, traveled distance, and computational time. The proposed control systems can readily be implemented in future automated driving systems, as well as within advanced driver assist systems such as adaptive cruise control or automated emergency braking systems.
Experimental Electrical Assessment Evaluation of a Vertical n-PERT Half-Size Bifacial Solar Cell String Receiver on a Parabolic Trough Solar Collector
Authors: Cabral Diogo , Hayati Abolfazl , Gomes João , Gorouh Hossein Afzali , Nasseriyan Pouriya , Salmanzadeh Mazyar
Published: February 2023

A two-trough parabolic-shaped concentrating photovoltaic solar collector with a vertical half-size ‘phosphorus-passivated emitter rear totally diffused’ bifacial cell string receiver was designed and built for household applications, with the aim of smooth the electrical ‘duck curve’. The study consisted in testing the concentrating photovoltaic solar collector outdoors, under real weather conditions, for its daily electrical peak power and efficiency, as well as for its electrical transversal and longitudinal Incidence Angle Modifier direction. The outdoor testing measurements were conducted in a parabolic trough with low concentration coupled with a central vertical half-size ‘phosphorus-passivated emitter rear totally diffused’ bifacial cell string receiver. Furthermore, the electrical transversal Incidence Angle Modifier showed to be very delicate due to the position and outline of the receiver, which led to an electrical peak efficiency close to 10% at ±25° (i.e., for an electrical power output of around 49.3 W/m2). To validate the measured parameters, a ray-tracing software has been used, where the measured Incidence Angle Modifiers have a very good agreement with the simulated Incidence Angle Modifiers (e.g., deviation of <4%). Consequently, the concentrating solar collector met the objective of lowering the Photovoltaic cell stress and high radiation intensity, by shifting the electrical peak power at normal (e.g., at 0°) to higher incidence angles (e.g., ±25°); this aids the electrical demand peak shaving, by having the highest electrical power production displaced from the highest intensity solar radiation during the day.
Adaptive Finite Element Simulation of Double-Diffusive Convection
Authors: Milhazes Jorge , Coelho Pedro J.
Published: February 2023

Double-diffusive convection plays an important role in many physical phenomena of practical importance. However, the numerical simulation of these phenomena is challenging since fine meshes are often required to capture the flow physics. Hence, several different numerical methods have been employed in the past. This work reports the development and application of an adaptive finite element method for the simulation of these phenomena, thereby avoiding the need for the use of very fine meshes over the whole domain. The weak formulation of the conservation equations for mass, momentum, energy and species concentration is used. The Boussinesq approximation relates the density of the fluid to the temperature and/or the species concentration. A second-order backward difference method is used for time discretization and the Galerkin method is employed for spatial discretization. Both adaptive time step and grid refinement techniques are employed, and the code is parallelized using MPI. Three different stabilization methods of the convective-diffusion equations are compared; namely, the streamline upwind Petrov–Galerkin (SUPG) method, and two modified methods aimed at diminishing spurious oscillations that include an artificial diffusion term. This diffusion term may be either isotropic or orthogonal to the streamlines. The addition of artificial isotropic diffusion to the SUPG method provides enhanced stability. The method is applied to double-diffusive finger convection in a sucrose-salt aqueous mixture and a stratified salt solution heated from below. The method accurately reproduces the experimentally observed temporal evolution of the salt fingers in the former case and the location of the interfaces between convective and non-convective zones in the latter.
An Improved Integrated Numerical Simulation Method to Study Main Controlling Factors of EUR and Optimization of Development Strategy
Authors: Du Yihe , Liu Hualin , Sun Yuping , Sheng Shuyao , Wei Mingqiang
Published: February 2023

Gas reservoir numerical simulation is an important method to optimize the development strategy of shale gas reservoirs which has been influenced by the multi-stage fracture. The regular fracture network model was used to build a conventional numerical simulation, in which it was difficult to show the true situation of fracture propagation. However, the physical parameters not only affect the production, but also influence the stimulation effect; moreover, the quality of the fracturing effect also affects the production which causes the input and out parameters to be inaccurate. To solve this problem, the process simulation must be completed from geology to engineering to gas reservoir. The main controlling factors of production are identified with geological and engineering factors such as horizontal stage length, the volume of fracturing fluid, well spacing, production allocation, and proppant mass. Therefore, on the basis of the integrated simulation method of a hydraulic fracturing network simulation and an unstructured grid high-precision numerical simulation, this paper builds an integrated numerical simulation of a shale gas reservoir coupled with geology and engineering to optimize the development strategy with production as the target. Taking four wells of a platform as an example, the EUR (estimated ultimate recovery) has increased by 25% after the optimization of the development strategy.
Inter-Turn Breakdown Fault Analysis and Winding Structure Optimisation of Winding of Dry-Type Transformers in Wind Farms
Authors: Pu Ziheng , Yu Xinyun , Wang Yaoqiang , Liu Hao , Feng Zihao
Published: February 2023

To address the problem of winding turn-to-turn breakdown faults in 35 kV dry-type transformers in wind farms under overvoltage conditions, this paper establishes a simulation model based on the structural dimensions and material parameters of the transformer windings. The winding distribution parameters were calculated using the finite element method. The transient processes inside the high-voltage coil were calculated by constructing a multi-conductor transmission line model (MTL) that took into account the influence of the secondary winding. The voltage distribution of the winding was analysed for both lightning shock and extra-fast transient overvoltage conditions. The simulation results show that the maximum overvoltage between turns of the transformer winding under lightning shock is 5.282 kV; the maximum overvoltage between turns of the winding under very fast transient overvoltage is 11.6 kV, which occurs between the first 2–3 layers of the section, close to the insulation breakdown margin. On this basis, the transformer winding structure was optimised and the maximum inter-turn overvoltage after optimisation was 9.104 kV, reducing the likelihood of insulation breakdown by 24.1%. Finally, the accuracy of the winding structure optimisation simulation study was verified by testing the transformer’s impulse voltage before and after optimisation, providing a reference for the stable operation of 35 kV dry-type transformers in wind farm practical applications.
Pore Structure and Fractal Characteristics of Tight Sandstone: A Case Study for Huagang Formation in the Xihu Sag, East China Sea Basin, China
Authors: Dong Jin , Huang Zhilong , Chen Jinlong , Li Tianjun , Zhao Jing , Pan Yongshuai , Qu Tong
Published: February 2023

Various experiments, including routine petrophysical measurements, thin section and scanning electronic microscope (SEM), high-pressure mercury intrusion (HPMI), and nuclear magnetic resonance (NMR), were performed to characterize the microscopic pore structure of tight sandstone in the Huagang Formation (E3h), Xihu Sag, East China Sea Basin, China. Specifically, NMR was used to investigate the dynamic variation of fractal dimensions during centrifugation, and the comparison of HPMI and NMR were used to clarify the difference of fractal dimensions. The results showed that there were four types of pores observed in thin section and SEM images: primary intergranular pores, intergranular dissolution pores, intragranular dissolution pores, and micropores within clay aggregates. The geometric shape and pore size of different pore types showed huge differences, indicating the formation of complex and diverse pore structures in the E3h formation. The flow capability of the reservoir was dominated by large pores, while the storage capacity was determined by small pores. The dynamic variation of fractal dimensions calculated by NMR data showed the water residing in the pore structure with low fractal dimensions was removed preferentially, and the pore structure of the resided water was always more complicated than the pore structure of removed water, which indicated the flow capability of the reservoir was affected by the complexity of the pore structure. Based on the comparison of the fractal dimension data from HPMI and NMR, it was found that the variation trends of the fractal dimensions were consistent, as the radius of the pore throat increased, the fractal dimensions increased, and the pore structure became more complicated. Both fractal dimensions of macropores (Dmac) and movable-fluid pores (Dmov) can reflect the flow capability of reservoir effectively, but the correlations between fractal dimensions from HMPI and NMR were poor, which could be due to the different working mechanism in these methods.
Load Frequency Control in Two-Area Multi-Source Power System Using Bald Eagle-Sparrow Search Optimization Tuned PID Controller
Authors: Raj T. Dharma , Kumar C. , Kotsampopoulos Panos , Fayek Hady H.
Published: February 2023

For power system engineers, automated load frequency control (LFC) for multi-area power networks has proven a difficult problem. With the addition of numerous power generation sources, the complexity of these duties becomes even more difficult. The dynamic nature of linked power networks with varied generating sources, such as gas, thermal, and hydropower plants, is compared in this research. For the study to be more accurate, frequency and tie-line power measurements are used. For precise tuning of proportional-integral-derivative (PID) controller gains, the Bald Eagle Sparrow search optimization (BESSO) technique was used. The BESSO algorithm was created by combining the characteristics of sparrows and bald eagles. The performance of BESSO is determined by comparing its findings to those acquired using traditional approaches. In terms of Integral Time Absolute Error (ITAE), which is the most important criterion used to reduce system error, the findings presented in this study indicate the effectiveness of the BESSO-PID controller. Finally, sensitivity analysis and stability analysis proved the robustness of the developed controller. The settling times associated with the tie-line power flow, frequency variation in area-1, and frequency variation in area-2, respectively, were 10.4767 s, 8.5572 s, and 11.4364 s, which were all less than the traditional approaches. As a result, the suggested method outperformed the other strategies.
A Discrete Electrical Model for Photovoltaic Solar Cells—d1MxP
Authors: Torres João Paulo N. , Marques Lameirinhas Ricardo A. , Correia V. Bernardo Catarina P. , Veiga Helena Isabel , dos Santos Pedro Mendonça
Published: February 2023

Solar cell equivalent circuit modelling is usually based on continuous I-V models, with a set of data obtained by analytical expressions. This work proposes an almost discrete novel mathematical method and correspondent electrical model, based on the I-V curve adjustment at every two adjacent points. It is based on the discretisation of any diode model behaviour, such as the 1M5P (also known as 1D5P) or the 1M7P (also known as 2D7P). For this reason, the model is named d1MxP, meaning that it is a discrete (d) model (1M) with x parameters (xP). The modelling methodology validation process uses experimental data already published in the literature. According to the presented results, the proposed method shows increased accuracy when compared to the 1M5P or 1M7P equivalent models. The accuracy on the maximum power point and fill factor determination is relevant, resulting in an improvement of up to 3.34% in the maximum power, up to 5.70% in its voltage and up to 8.20% in its current, for the analysed data. Furthermore, Fill Factor values, have variation from up to 35.98%. The temperature influence on the silicon solar cell is also analysed, to validate the results. The proposed method allows highly accurate curve fitting to the (experimental) points and consequently, to obtain a more accurate model to analyse the performance of solar cells under different conditions.
Investigating Divergent Energy Policy Fundamentals: Warfare Assessment of Past Dependence on Russian Energy Raw Materials in Europe
Authors: Wiśniewski Tomasz P.
Published: February 2023

The Russian invasion of Ukraine and the resulting warfare within direct proximity to the European Union (EU) have significantly changed the conditions of Europe’s energy policy. Consequently, the energy security agencies and governments have been deliberating over an energy trilemma: the problem of balancing affordability, security, and environmental considerations, with much greater ramifications than before the breakout of the current military conflict. The past structural similarities and differences of the EU member states’ dependence on Russian energy raw materials, and the factors that might have determined those differences, may be among the key drivers of future energy policy choices in Europe and the prospective paths of the European Green Deal (EGD). Historical convergence might encourage an EGD consensus, while divergent past patterns might not allow for such a single direction throughout the EU. The multifaceted research proposed in this paper, from descriptive statistics to multiple linear regression model analyses, identifies structural dissimilarities among the EU economies relating to their dependence on Russia. Key findings suggest that the past dependencies on Russian energy raw materials have not been similar across the EU countries, and have been associated with the economic size of the EU member states and their proximity to or remoteness from Russia. In this regard, economic size and distance from Russia may be significant determinants of certain dissimilarities. Some countries, especially Estonia, Lithuania, and Poland, have demonstrated a structurally different energy mix dependence on Russian fossil energy raw materials than countries more remote from Russia that boast a higher GDP per capita.
Hybrid PEM Fuel Cell Power Plants Fuelled by Hydrogen for Improving Sustainability in Shipping: State of the Art and Review on Active Projects
Authors: Dall’Armi Chiara , Pivetta Davide , Taccani Rodolfo
Published: February 2023

The interest in hybrid polymer electrolyte membrane fuel cells (PEMFC) fuelled by hydrogen in shipping has seen an unprecedented growth in the last years, as it could allow zero-emission navigation. However, technical, safety, and regulatory barriers in PEMFC ship design and operation are hampering the use of such systems on a large scale. While several studies analyse these aspects, a comprehensive and up-to-date overview on hydrogen PEMFCs for shipping is missing. Starting from the survey of past/ongoing projects on FCs in shipping, this paper presents an extensive review on maritime hydrogen PEMFCs, outlining the state of the art and future trends for hydrogen storage and bunkering, powertrain, and regulations. In addition to the need for a clear regulatory framework, future studies should investigate the development of an efficient fuel supply chain and bunkering facilities ashore. As for the onboard power system, health-conscious energy management, low-temperature heat recovery, and advancements in fuel processing have emerged as hot research topics.
Techno-Economic Assessment of PV Power Systems to Power a Drinking Water Treatment Plant for an On-Grid Small Rural Community
Authors: Amoroso Fernando , Hidalgo-León Rubén , Muñoz Kevin , Urquizo Javier , Singh Pritpal , Soriano Guillermo
Published: February 2023

This paper shows the technical–economic assessment of two power systems based on renewable electricity to cover the energy consumption requirements of a drinking water treatment plant in the town of Pile, Ecuador, with a planning horizon of 15 years. A stand-alone and a grid-connected solar PV system were proposed to power this plant, which was designed considering the maximum daily potable water supply condition. This plant operated under two scenarios: (1) 12 h during daylight hours and (2) 24 h. Both schedules were proposed to assess the impact of PV power systems on plant operation. We modeled and optimized a total of four scenarios, where each scenario consisted of one of the proposed PV power systems and the plant with one of its operating schedules. Homer Pro software was used to size and find an optimal solution in each scenario, considering the net present cost (NPC) as the main criterion for optimization. The results showed that the change in the plant operation schedule significantly influenced the parameters of each scenario, such as component sizing, electricity production, initial capital, NPC, and electricity purchase/sale capacity from the plant as a grid power service user to the electric utility company.
The Effects of γ-Radiation on the Physical and Electrical Properties of Silicone Encapsulation for Electronic Power Conditioners
Authors: Hu Cong , Zheng Wei , Zhao Bin , Fan Yu , Li Hong , Zheng Kun , Wang Gang
Published: February 2023

Since the electronic power conditioner (EPC) is a crucial part of a space traveling-wave tube amplifier (STWTA), its reliability issue must be considered. The most effective way to prevent insulation breakdown is potting. Silicone elastomers are commonly used as an encapsulant for the EPC because of their good physical and electrical properties. The properties of the encapsulant and the interfaces change under the influence of γ-radiation, which may result in the failure of the potted modules. In this work, a comprehensive evaluation methodology is proposed for silicone-based potted modules, where besides physical and electrical properties, the effect of γ-radiation on the encapsulated interface is also considered. The results show that with the increase of the irradiation dose, the crosslinking density, hardness, elastic modulus, volume resistivity, dielectric constant, and storage modulus are increased by 301.6%, 76.3%, 289.7%, 396.1%, 5.0%, and 589.8%, respectively. In contrast, the elongation at break and dielectric loss factor are decreased by 83.8% and 57.8%. In addition, the tensile strength and breakdown strength first increase and then decrease, while the coefficient of thermal expansion of the interface shows the opposite trend. Since the interface bonding state does not change and the electric field strength of the tip decreases slightly with an increasing dielectric constant, the average value of the partial discharge inception voltage increased slightly.
Natural Gas Prices in the Framework of European Union’s Energy Transition: Assessing Evolution and Drivers
Authors: Ribeiro Vitor Miguel , Soutinho Gustavo , Soares Isabel
Published: February 2023

This study analyzes European natural gas (NG) prices since the eve of the 2008 financial crisis. Spearman’s rank correlation coefficients associate prices with and without taxation, whereas a hierarchical clustering analysis clarifies similarities in NG pricing behavior. After performing econometric tests to ensure the satisfaction of classical hypotheses and identify a system of endogenous variables, structured unrestricted and restricted vector autoregressive models are applied to panel data composed of 34 spatial units and 31 units of time drawn from 2007–2022 to confirm the presence of short-term and long-term causal dependencies. The nonparametric analysis identifies three groups of countries that exhibit a differentiated pricing behavior. The parametric analysis reveals a significant and asymmetric short run relation, which is imposed by liquefied natural gas (LNG) imports from Nigeria on the logarithm of NG prices. However, the sign of coefficients associated with lagged LNG imports varies across spatial units belonging to the sample. The error correction term is negative and significant, which implies evidence of cointegration. Since the main result identifies ambiguous short-term effects emerging from the diversification in favor of LNG imports from Nigeria, a straightforward policy recommendation is that this strategic option may be ill advised for Europe and, indirectly, it legitimizes the suggestion that alternative decarbonization options can play a prominent role in European NG markets in the near future.
Impulsive Noise Suppression Methods Based on Time Adaptive Self-Organizing Map
Authors: Hazaveh Seyed Hamidreza , Bayandour Ali , Khalili Azam , Barkhordary Ali , Farzamnia Ali , Moung Ervin Gubin
Published: February 2023

Removal of noise and restoration of images has been one of the most interesting topics in the field of image processing in the past few years. Existing filter-based methods can remove image noise; however, they cannot preserve image quality and information such as lines and edges. In this article, various classifiers and spatial filters are combined to achieve desirable image restoration. Meanwhile, the time adaptive self-organizing map (TASOM) classifier is more emphasized in our feature extraction and dimensionality reduction approaches to preserve the details during the process, and restore the images from noise. The TASOM was compared with the self-organizing map (SOM) network, and a suitable noise reduction method for images was attempted. As a result, we achieved an optimum method to reduce impulsive noise. In addition, by using this neural network, better noise suppression was achieved. Experimental results show that the proposed method effectively removes impulse noise and maintains color information as well as image details.
Examining the Energy Efficiency and Economic Growth Potential in the World Energy Trilemma Countries
Authors: Alola Andrew Adewale , Adebayo Tomiwa Sunday , Olanipekun Ifedolapo Olabisi
Published: February 2023

The World Energy Council has consistently formulated useful policies and ranked countries in term of their performances in environmental sustainability, energy equity, and energy security. In a novel approach, and possibly in one of the most unique studies in the World Energy Trilemma literature, the current study examines the interaction of energy efficiency and economic growth of several top-performing economies (Austria, Denmark, France, Finland, Germany, New Zealand, Sweden, Switzerland, and the United Kingdom) in respect to environmental sustainability, energy equity, and energy security. Importantly, while affirming the inappropriateness of the linear econometric approach, the study utilized the newly developed quantile-on-quantile approach to examine the dataset for the period 1990Q1 to 2018Q4. As such, the result largely indicates a significant and positive effect of economic growth toward the energy efficiency across the quantiles for the examined countries (Austria, Denmark, France, Finland, Germany, New Zealand, Sweden, Switzerland, and the United Kingdom). On the other hand, energy efficiency also impacts economic growth in most parts of the quantiles in the examined countries. However, the results show weak and negative interaction in the lower quantiles (average of 0.1–0.3) only for Denmark, Germany, and New Zealand, while the results further reveal weak and negative interaction in the middle quantile (average 0.4–0.6) for France, Finland, and Sweden. Importantly, this study presents useful economic-related policy inferences from the aspects of energy efficiency, energy security, energy equity, and environmental sustainability.
An All-Vanadium Redox Flow Battery: A Comprehensive Equivalent Circuit Model
Authors: Yesilyurt Muhammed Samil , Yavasoglu Huseyin Ayhan
Published: February 2023

In this paper, we propose a sophisticated battery model for vanadium redox flow batteries (VRFBs), which are a promising energy storage technology due to their design flexibility, low manufacturing costs on a large scale, indefinite lifetime, and recyclable electrolytes. Primarily, fluid distribution is analysed using computational fluid dynamics (CFD) considering only half-cells. Based on the analysis results, a novel model is developed in the MATLAB Simulink environment which is capable of identifying both the steady-state and dynamic characteristics of VRFBs. Unlike the majority of published studies, the inherent characteristics of the flow battery, such as shunt current, ion diffusion, and pumping energy consumption, are considered. Furthermore, simplified charge transfer resistance (CTR) is taken into account based on electrochemical impedance spectroscopy (EIS) measurement results. The accuracy of the model was determined by comparing the simulation results generated by the equivalent circuit battery model developed in this study with real datasets. The obtained results indicate that the developed model has an accuracy of 3% under the sample operating conditions selected. This study can also be used to fill the gap left by the absence of the VRFB battery model in commonly used programs for renewable energy systems, such as TRNSYS.
Review of Vibroacoustic Analysis Methods of Electric Vehicles Motors
Authors: Król Emil , Maciążek Marcin , Wolnik Tomasz
Published: February 2023

The dynamic development of electromobility has resulted in new directions of research, one of which is the analysis of the noise of traction motors. The designs of the motors used in electric vehicles are relatively new and often modified. In addition, strong competition also forces an increase in the power generated per unit mass of the motor, often at the expense of weakening the mechanical structure. This may result in an increase in the noise level generated by the electric drive, so this issue should be analyzed at the motor design stage. Different construction and operating conditions in relation to industrial or railway traction motors make it necessary to constantly develop methods for the noise analysis of the motors for electric vehicles. The aim of this article is to review the methods used so far in an analysis of the noise generated by the motors for electric vehicles. Three main methods are used by the authors of this paper: the analytical method, the hybrid method using two-dimensional models, and the hybrid method using three-dimensional models. In addition to the review of these methods, the paper also focuses on a synthetic summary of the most important factors determining the level and nature of the noise generated by electric vehicle motors.
Statistical Image Analysis on Liquid-Liquid Mixing Uniformity of Micro-Scale Pipeline with Chaotic Structure
Authors: Wang Haotian , Yang Kai , Wang Hua , Wu Jingyuan , Xiao Qingtai
Published: February 2023

The aim of this work is to introduce a novel statistical technique for quantifying the concentration field uniformity of the liquid-liquid mixing process within a micro-scale chaotic pipeline. For illustration, the microscale liquid-liquid mixer in which the inlet direction is parallel to the mixing unit is designed by using the chaotic pipeline with Baker map. Meanwhile, the non-uniformity coefficient method is adopted quantificationally instead of qualitatively estimating the concentration field uniformity of the chaotic micromixer based on uniform design theory and image analysis. Results show that the concentration distribution of the chaotic mixing process of liquid-liquid under various working conditions is obtained by solving the steady-state Navier–Stokes and diffusion convection equations. The average contribution ratio of the three basic mixing units of the chaotic Baker pipeline to the concentration field uniformity is approximately 6:3:1, which is calculated aligned with the fluid flow direction successively. The optimal mixing uniformity can be obtained as the initial velocity is 0.05 m/s and the diffusion coefficient is 5 × 10−9 m2/s, respectively. The reliability of the new method for estimating the concentration field uniformity parameters is explained from three dimensions. The statistical image analysis technique is illustrated to be reliable and effective in yielding accurate concentration field information of the simulated chaotic mixer. Furthermore, it can be adapted to examine a variety of concentration distribution issues in which concentrations are evaluated under distinct scales.
Robust Control Based on Observed States Designed by Means of Linear Matrix Inequalities for Grid-Connected Converters
Authors: Koch Gustavo G. , Osório Caio R. D. , Oliveira Ricardo C. L. F. , Montagner Vinícius F.
Published: February 2023

This paper provides a procedure to design robust controllers based on observed states applied to three-phase inverters with LCL filters connected to a grid with uncertain and possibly time-varying impedances, which can arise in renewable energy systems and microgrid applications. Linear matrix inequalities are used to rapidly compute, off-line, based only on the choice of two scalar parameters for pole location, sets of gains for the controller and the observer, and also to provide a theoretical certificate of the closed-loop stability, including a limit for the rate of variations of the grid impedances. The proposed design procedure allows the easy implementation of robust state feedback controllers with a reduced number of sensors, ensuring good performance for different sets of grid impedances. Additionally, larger regions of guaranteed stability are provided by the proposed procedure, when compared with a similar condition from the literature. The control law using the observed states can ensure grid currents with low harmonic content, complying with the IEEE 1547 Standard requirements, with negligible loss of performance concerning the feedback of the measured state variables. Three optimal state feedback controllers from the literature are reproduced here and successfully implemented using the observed state variables based on the proposed procedure. In all cases, the viability of the proposal was confirmed by simulations and experimental results.
The Pyrolysis Behaviors of Blended Pellets of Pine Wood and Urea-Formaldehyde Resin
Authors: Li Xiaoteng , Luo Siyi , Zuo Zongliang , Zhang Weiwei , Ren Dongdong
Published: February 2023

TG-FTIR and PY-GC/MS were used to analyze the pyrolysis behaviors of pine wood, urea-formaldehyde resin (UF resin) and their blended pellets. The pyrolysis process was divided into three stages: water evaporation, devolatilization and pyrolysis residue decomposition. During the pyrolysis process of the blended pellets, with the increase of the addition ratio of UF resin, the peak value of the weight loss decreased in the decomposition stage of the pyrolysis residue, while the temperature shifted to the low-temperature region. This was mainly due to the structural stability of pyrolytic carbon produced by UF resin, which hindered the thermal decomposition of lignin-produced residues in pine. FTIR showed that CO2 was the main product of pyrolysis. For UF resin, nitrogen compounds accounted for a large proportion. With the addition of UF resin, the nitrogen in the blended pellets increased significantly. Since the synergistic effect promoted the further decomposition of the organic oxygen-containing structure, the NO release was still increased. PY-GC/MS showed that co-pyrolysis produced more nitrogen-containing compounds and promoted the decomposition of macromolecular phenol derivatives, lipids and ketones, resulting in more small-molecule acids and alcohols.
Energy-Efficient Optimization Method of Urban Rail Train Based on Following Consistency
Authors: Xu Ruxun , Meng Jianjun , Li Decang , Chen Xiaoqiang
Published: February 2023

Because of the short distance between stations in urban rail transit, frequent braking of urban rail trains during operation will generate a large amount of regenerative braking energy. Urban rail trains can reduce their actual traction energy consumption using regenerative braking energy. Therefore, an energy-efficient optimization method for urban rail trains is proposed. By taking the punctuality of trains as the premise, the weighted acceleration of trains is taken as the synergetic variable, the synergetic coefficient is introduced to construct the following consistency model, and its convergence is proved. By analyzing the influencing factors of the following consistency coordination time, an adaptive parameter adjustment strategy is designed to solve the latest secondary traction time and the corresponding maximum speed of the primary traction. In order to save communication resources, the event trigger function is used to construct trigger conditions, and the consistency algorithm is used to update the cooperative controller. The simulation results show that the weighted acceleration of the follower train achieves the following consistency on the premise of ensuring punctuality, and the actual traction energy consumption of the follower train is reduced by 5.73%. The proposed method provides a new strategy for the energy-efficient operation of urban rail trains.
Current Trends in Electric Vehicle Charging Infrastructure; Opportunities and Challenges in Wireless Charging Integration
Authors: Dimitriadou Konstantina , Rigogiannis Nick , Fountoukidis Symeon , Kotarela Faidra , Kyritsis Anastasios , Papanikolaou Nick
Published: February 2023

Nowadays, the imperative need for the reduction of Greenhouse Gas (GHG) emissions leads to the wider adoption of environmentally friendly transportation means. As a result, various policies underpinning the Electric Vehicle (EV) deployment are legislated globally, and several technical advances contributing to the electrification of the transportation sector are pursued. In this paper, a comprehensive overview of the current status of the infrastructure utilized for the realization of both conductive and contactless (wireless) charging of an EV battery is conducted. Furthermore, the issue of EV integration in conventional distribution networks, as well as in future power system architectures, is discussed in detail. Particular focus is given to wireless (i.e., inductive) charging. A detailed presentation of the respective standards and charging levels, as well as the magnetic couplers and the compensation network configurations, is carried out. Moreover, innovative concepts such as dynamic and quasi-dynamic wireless charging, as well as future challenges and opportunities, are presented and discussed. Finally, smart control and communication techniques applicable to EV charging are presented in the context of the future Internet of Energy (IoE) concept.