bluuebunny/crossref_metadata_2025 huggingface dataset:
Opinion Dynamics and Unifying Principles: A Global Unifying Frame
Authors: Galam Serge
Published: August 2022

I review and extend the set of unifying principles that allow comparing all models of opinion dynamics within one single frame. Within the Global Unifying Frame (GUF), any specific update rule chosen to study opinion dynamics for discrete individual choices is recast into a probabilistic update formula. The associated dynamics is deployed using a general probabilistic sequential process, which is iterated via the repeated reshuffling of agents between successive rounds of local updates. The related driving attractors and tipping points are obtained with non-conservative regimes featuring both threshold and threshold-less dynamics. Most stationary states are symmetry broken, but fifty–fifty coexistence may also occur. A practical procedure is exhibited for several versions of Galam and Sznajd models when restricted to the use of three agents for the local updates. Comparing these various models, some are found to be identical within the GUF. Possible discrepancies with numerical simulations are discussed together with the difference between the GUF procedure and a mean field approach.
Free-Energy-Based Discrete Unified Gas Kinetic Scheme for van der Waals Fluid
Authors: Yang Zeren , Liu Sha , Zhuo Congshan , Zhong Chengwen
Published: August 2022

The multiphase model based on free-energy theory has been experiencing long-term prosperity for its solid foundation and succinct implementation. To identify the main hindrance to developing a free-energy-based discrete unified gas-kinetic scheme (DUGKS), we introduced the classical lattice Boltzmann free-energy model into the DUGKS implemented with different flux reconstruction schemes. It is found that the force imbalance amplified by the reconstruction errors prevents the direct application of the free-energy model to the DUGKS. By coupling the well-balanced free-energy model with the DUGKS, the influences of the amplified force imbalance are entirely removed. Comparative results demonstrated a consistent performance of the well-balanced DUGKS despite the reconstruction schemes utilized. The capability of the DUGKS coupled with the well-balanced free-energy model was quantitatively validated by the coexisting density curves and Laplace’s law. In the quiescent droplet test, the magnitude of spurious currents is reduced to a machine accuracy of 10−15. Aside from the excellent performance of the well-balanced DUGKS in predicting steady-state multiphase flows, the spinodal decomposition test and the droplet coalescence test revealed its stability problems in dealing with transient flows. Further improvements are required on this point.
Disentangling the Regeneration Niche of Vatica odorata (Griff.) Symington Using Point Pattern Analysis
Authors: Nguyen Van Anh Thi , Blardoni Francesco , Manh Hung Bui , Schlicht Robert , Wagner Sven
Published: August 2022

Seed dispersal and environmental heterogeneity, and the effects of their interaction, are perceived to be determinants of the spatial patterns of trees. We applied the spatial point process to analyse Vatica odorata (Griff.) Symington (Dipterocarpaceae) in Cuc Phuong National Park of Vietnam to understand its spatial patterns, and to decipher the main factors affecting seedling establishment of the species. We established a total of 12 replicated plots, each of which had one or two seed trees in the centre, and recorded all regeneration plants of V. odorata with their positions. A total of 671 regeneration plants were found. Covariates, including canopy, ground cover, and distance to seed trees, were measured on systematic grids of 4 × 4 m. In the context of the spatial point processes, we used a generalised linear mixed model, considering a random effect of the plot. In the model, the greatest distance observed is about 35 m from the seed tree. The canopy and ground cover have a significant impact on the regeneration of the species: The intensity of regenerating stems was greatest with a canopy cover of 70%. The ground cover range for good development of regenerating plants was between 10 and 30%.
Three-Dimensional Hybrid Nanostructures of Fe3O4 Nanoparticles/Vertically-Aligned Carbon Nanotubes for High-Performance Supercapacitors
Authors: Zhao Bin
Published: August 2022

A three-dimensional (3D) hybrid nanostructure of Fe3O4 nanoparticles uniformly anchored on vertically-aligned carbon nanotubes (VACNTs) was fabricated by a facile two-step method. Assisted by supercritical carbon dioxide (SCCO2), the Fe precursor was firstly absorbed on CNT surface and then transformed into Fe3O4 nanoparticles by vacuum thermal annealing. Owing to the synergetic effects of well-distributed Fe3O4 nanoparticles (~7 nm) and highly conductive VACNTs, the hybrid electrode exhibits a high specific capacitance of 364.2 F g−1 at 0.5 A g−1 within the potential range from −0.9 to +0.1 V in Na2SO3 electrolyte and an excellent cycling stability of 84.8% capacitance retention after 2000 cycles at a current density of 4 A/g. This 3D hybrid architecture consisting of aligned CNTs and pseudocapacitive metal oxide may be a promising electrode for high-performance supercapacitors.
Capability for Hydrogeochemical Modelling within Discrete Fracture Networks
Authors: Applegate David , Appleyard Pete
Published: August 2022

A new method for simulating solute transport and geochemical interactions within fractured rock is presented. This will be an important capability for assessing the safety of radioactive waste disposal facilities that are located within fractured crystalline bedrock. Specifically, the discrete fracture network (DFN) module within the ConnectFlow groundwater flow and transport software has been updated to: (i) simulate the advection and diffusion of more than one solute species (with the flow and transport equations coupled by the evolving density and viscosity); (ii) model the diffusion of solutes into the rock matrix between fractures; and (iii) utilise the iPhreeqc library to model chemical reactions involving solutes, minerals on fracture/pore surfaces and rock minerals. The performance of ConnectFlow’s DFN module has also been significantly improved via parallelisation which allows more complex calculations to be attempted. These developments are significant because hydrogeochemistry within fractured rock is more accurately represented in an explicit DFN, rather than using more approximate equivalent continuous porous medium (ECPM) methods. Illustrative calculations have been completed for the disposal facility for spent nuclear fuel at Olkiluoto in Finland, and the former candidate site for spent fuel disposal, Laxemar, in Sweden. These calculations show that DFN simulations provide results that are qualitatively similar to results from ECPM calculations. However, because the ECPM is a less direct approach, notable differences exist when compared to the DFN approach.
Study on the Compatibility between Combined Control of Channel Plugging and Foam Flooding and Heterogeneous Reservoirs—Taking Bohai Z Oilfield as an Example
Authors: Zhang Yunbao , Wang Chengzhou , Liu Ming , Zhou Zhen , Quan Jiamei , Zheng Xulin , Zhan Zhaohai
Published: August 2022

With the oilfield developed to a later stage and its heterogeneity gradually becoming more serious, the adaptability of conventional profile control technologies for the reservoir becomes worse and worse. Therefore, the fitness of compatibility between combined patterns of profile control and target reservoir becomes an important factor for the efficient development of the oil field. Due to the importance of compatibility between the profile control and reservoir property, research on the remaining oil recovery with combined patterns of profile control and foam flooding were carried out. The experimental results showed that the combined profile control is highly consistent with the target reservoir. With a little lower initial viscosity (28.3–40.9 mPa·s), the channel plugging system is easy to inject. Due to the addition of a polymer, the reinforced foam is not easy to defoam when transporting in the pore throats of the core sample, and its spontaneous adaptability makes it match with the porous media of the formation automatically, which effectively prolongs the transporting distance for the foam in the deep part of the core sample. The segment plug with a gel-type profile control agent injected at the front stage is of great significance to the non-homogeneous reservoir, so it is necessary to inject a sufficient gel-type profile control agent into the high permeability layer to make it produce a seal. When the permeability differential was equal to 10, the maximum increase of oil recovery degree was 29.69%, and the development effect became worse after increasing or decreasing the permeability differential.
Energy Analysis of a NZEB Office Building with Rooftop PV Installation: Exploitation of the Employees’ Electric Vehicles Battery Storage
Authors: Stamatellos George , Zogou Olympia , Stamatelos Anastassios
Published: August 2022

Near zero energy buildings are increasing worldwide, exploiting low-carbon technologies in heating and electricity self-production. Commercial buildings are increasingly considered as candidates for the installation of smart micro-grids, which may profit from the added storage capacity of the batteries of employees electric vehicles, stationed during daytime in their charging lots. Smart exploitation of the interaction of these electricity sources and sinks may prove essential to address the complex electricity network demand patterns in today’s fast changing energy mixture. The interaction of an efficient office building’s energy system with a big rooftop photovoltaic installation and the aggregate storage capacity of 40 electric cars that are connected in the building’s charging lots is studied by means of transient simulation in TRNSYS environment. The 18-zone building’s heating, ventilation, and air conditioning system, the cars’ batteries, and photovoltaic systems’ interactions are analyzed on a monthly, seasonal, and hourly basis, against the respective demand curves of the Greek network. The results suggest that the specific system’s size may profitably support the operation of a smart micro-grid. The total annual electricity consumption of the building is computed to reach 112,000 kWh, or 20 kWh/m2y. The annual electricity needs of the 40 electric cars, amounting to 101,000 kWh, can be fully met with 30% of the photovoltaic electricity production. Thus, the building becomes a net exporter of electricity to the network, with maximum exported electricity occurring daily between 12:00 and 14:00, which is favorable to meeting the demand curve. Thus, the establishment of smart micro-grids in commercial buildings with large rooftop photovoltaic panels’ capacity and a significant number of electric cars in the employees’ car fleet is quite effective in this direction.
Inversion Study on Parameters of Cascade Coexisting Gas-Bearing Reservoirs in Huainan Coal Measures
Authors: Chen Baiping , Liu Bo , Du Yunfei , Dong Guoqi , Wang Chen , Wang Zichang , Wang Ran , Cui Fan
Published: August 2022

The prediction and development of three gases, mainly coalbed methane, shale gas, and tight sandstone gas, in the Huainan coal measures of China, has been the focus of local coal mines. However, due to the overlapping and coexisting characteristics of the three gas reservoirs in Huainan coal measure strata, it is challenging to develop the three gas. The coal mine has been creating a single pool for a long time, resulting in the severe waste of other gas resources in developing the gas-bearing resources in the coal measure strata. The gas-containing reservoir is predicted based on geological, seismic, and logging in Huainan Mining. In addition, determining the excellent area for reference for the development of three gas resources. First, using logging data, mathematical–statistical methods are used to analyze the physical parameters of gas-bearing reservoirs in multi-layered stacked coal seams. Then, based on the theory of prestack seismic inversion, parameters, such as the impedance of P-wave, the ratio of P-wave velocity and S-wave, Lamé constant, Young’s modulus, and Poisson’s ratio and lithological distribution, are obtained for the whole area. The gas-bearing information of the reservoir is received by the statistics and equation of the parameter intersection diagram and is closely related to exploration and development. Finally, the paper synthetically predicts the most favorable area of the gas-bearing reservoir in the study area. The prediction results are compared with the actual results of coalbed methane content in the existing extraction wells, proving that the method is feasible and can provide the basis for the deployment and development of the well location.
The Carbon Emission Reduction Effect of City Cluster—Evidence from the Yangtze River Economic Belt in China
Authors: Li Xin , Huang Chunlei , Zhan Shaoguo , Wu Yunxi
Published: August 2022

Climate anomalies are affecting the world. How to reduce carbon emissions has become an important issue for governments and academics. Although previous researchers have discussed the factors of carbon emission reduction from environmental regulation, economic development, and industrial structure, limited studies have explored the carbon emission reduction effect of a city’s spatial structure. Based on 108 Chinese cities from the Yangtze River Economic Belt between 2003 and 2017, this paper examines the impact of the city cluster policy on city carbon emissions using the difference-in-differences (DID) method. We find that: (1) The city cluster policy has significantly reduced the cities’ carbon emissions by 7.4%. Furthermore, after a series of robust and endogenous tests, such as parallel trend and PSM-DID, the core conclusion still remains. (2) We further identify possible economic channels through this effect, and find that city cluster policy would increase city productivity, city technological innovation, and industrial structure optimization. The conclusions of this paper have important practical significance for China to achieve carbon neutrality and facilitate future deep decarbonization.
Investigations of Vertical-Axis Wind-Turbine Group Synergy Using an Actuator Line Model
Authors: Zhang Ji Hao , Lien Fue-Sang , Yee Eugene
Published: August 2022

The presence of power augmentation effects, or synergy, in vertical-axis wind turbines (VAWTs) offers unique opportunities for enhancing wind-farm performance. This paper uses an open-source actuator-line-method (ALM) code library for OpenFOAM (turbinesFoam) to conduct an investigation into the synergy patterns within two- and three-turbine VAWT arrays. The application of ALM greatly reduces the computational cost of simulating VAWTs by modelling turbines as momentum source terms in the Navier–Stokes equations. In conjunction with an unsteady Reynolds-Averaged Navier–Stokes (URANS) approach using the k-ω shear stress transport (SST) turbulence model, the ALM has proven capable of predicting VAWT synergy. The synergy of multi-turbine cases is characterized using the power ratio which is defined as the power coefficient of the turbine cluster normalized by that for turbines in isolated operation. The variation of the power ratio is characterized with respect to the array layout parameters, and connections are drawn with previous investigations, showing good agreement. The results from 108 two-turbine and 40 three-turbine configurations obtained using ALM are visualized and analyzed to augment the understanding of the VAWT synergy landscape, demonstrating the effectiveness of various layouts. A novel synergy superposition scheme is proposed for approximating three-turbine synergy using pairwise interactions, and it is shown to be remarkably accurate.
Integrated Approach to Diagnostics of Failures and Cyber-Attacks in Industrial Control Systems
Authors: Syfert Michał , Ordys Andrzej , Kościelny Jan Maciej , Wnuk Paweł , Możaryn Jakub , Kukiełka Krzysztof
Published: August 2022

This paper is concerned with the issue of the diagnostics of process faults and the detection of cyber-attacks in industrial control systems. This problem is of significant importance to energy production and distribution, which, being part of critical infrastructure, is usually equipped with process diagnostics and, at the same time, is often subject to cyber-attacks. A commonly used approach would be to separate the two types of anomalies. The detection of process faults would be handled by a control team, often with a help of dedicated diagnostic tools, whereas the detection of cyber-attacks would be handled by an information technology team. In this article, it is postulated here that the two can be usefully merged together into one, comprehensive, anomaly detection system. For this purpose, firstly, the main types of cyber-attacks and the main methods of detecting cyber-attacks are being reviewed. Subsequently, in the analogy to “process fault”—a term well established in process diagnostics—the term “cyber-fault” is introduced. Within this context a cyber-attack is considered as a vector containing a number of cyber-faults. Next, it is explained how methods used in process diagnostics for fault detection and isolation can be applied to the detection of cyber-attacks and, in some cases, also to isolation of the components of such attacks, i.e., cyber-faults. A laboratory stand and a simulator have been developed to test the proposed approach. Some test results are presented, demonstrating that, similarly to equipment/process faults, residua can be established and cyber-faults can be identified based on the mismatch between the real data from the system and the outputs of the simulation model.
About Hydrophobicity of Lignin: A Review of Selected Chemical Methods for Lignin Valorisation in Biopolymer Production
Authors: Lisý Anton , Ház Aleš , Nadányi Richard , Jablonský Michal , Šurina Igor
Published: August 2022

Lignin is the second most abundant renewable natural polymer that occurs on Earth, and as such, it should be widely utilised by industries in a variety of applications. However, these applications and possible research seem to be limited or prevented by a variety of factors, mainly the high heterogeneity of lignin. Selective modifications of the structure and of functional groups allow better properties in material applications, whereas the separation of different qualitative lignin groups permits selective application in industry. This review is aimed at modification of the lignin structure, increasing the hydrophobicity of the produced materials, and focusing on several perspective modifications for industrial-scale production of lignin-based polymers, as well as challenges, opportunities, and other important factors to take into consideration.
Cognitive Computing—Will It Be the Future “Smart Power” for the Energy Enterprises?
Authors: Pilipczuk Olga
Published: August 2022

Nowadays, cognitive computing has become the popular solution to many problems arising in the energy industry, such as the creation of renewable technologies, energy saving, and searching for new sources. Last decade, a substantial number of scientific papers aiming to support these tasks were published. On the other hand, some years ago, the “cognitive enterprise” (CE) concept was introduced by the IBM company, which assumes, among others, the cognitive technologies used to increase enterprise intelligence. On the road to obtaining the status of a “cognitive enterprise”, it should overcome many challenges. Thus, the aim of the paper was to analyze the current state of research on the application of cognitive computing in the energy industry and to define the trends, challenges, milestones, and perspectives in scientific work’s development. The aim has been achieved using the bibliometric approach. The preliminary analysis was made by Web of Science data sources; 4182 records were retrieved. The results comprise the research field, geographic distribution of research, time analysis, and affiliation analysis. Additionally, descriptive statistics, as well as simple forecasting, were provided to present the research results. As a result of the research, the publication history road was created as well as the milestone framework on the path toward “cognitive enterprise”. The findings of this research can contribute to literature and practice by applying them to the process of cognitive enterprise models’ development as well as by adapting the education programs and training courses for enterprises and universities to market requirements.
Data-Driven Condition Monitoring of a Hydraulic Press Using Supervised Learning and Neural Networks
Authors: Makansi Faried , Schmitz Katharina
Published: August 2022

The automated evaluation of machine conditions is key for efficient maintenance planning. Data-driven methods have proven to enable the automated mapping of complex patterns in sensor data to the health state of a system. However, generalizable approaches for the development of such solutions in the framework of industrial applications are not established yet. In this contribution, a procedure is presented for the development of data-driven condition monitoring solutions for industrial hydraulics using supervised learning and neural networks. The proposed method involves feature extraction as well as feature selection and is applied on simulated data of a hydraulic press. Different steps of the development process are investigated regarding the design options and their efficacy in fault classification tasks. High classification accuracies could be achieved with the presented approach, whereas different faults are shown to require different configurations of the classification models.
Energy Security, Sustainable Development and the Green Bond Market
Authors: Orzechowski Arkadiusz , Bombol Małgorzata
Published: August 2022

Many countries are pursuing energy security (ES) in their economies while implementing sustainable development goals (SDGs). Relevant policies may include: (1) access to efficient alternative and preferably renewable energy sources (RESs); and (2) reductions in conventionally obtained energy consumption. As the demand for energy is growing and alternative energy resources are expensive, new ways of financing projects to improve ES are of special interest, e.g., issuing green bonds. In such cases, the obtained funds are allocated to projects that can both improve ES and help to achieve SDGs. The aim of the study was to explore the dependences (in the sense of Granger causality) between the green bond (GB) market, different aspects of sustainable development, as measured by global indicators taken from a family of environmental NASDAQ OMX indices, and ES represented by crude oil prices. The methodology is based on the vector autoregression model. The findings reveal evidence of a short-term dependence between the GB market, ES and the multidimensional nature of sustainable development.
The Economic Viability of PV Power Plant Based on a Neural Network Model of Electricity Prices Forecast: A Case of a Developing Market
Authors: Mišnić Nikola , Pejović Bojan , Jovović Jelena , Rogić Sunčica , Đurišić Vladimir
Published: August 2022

In this paper, a study was completed investigating the financial viability of a 5 MW solar power plant in Montenegro with direct access to the market, rather than a long-term power purchase agreement. The empirical research included an econometric analysis and forecast of the prices on the exchange market, using two methods, autoregressive integrated moving average (ARIMA) and neural network auto regression (NNAR), which are compared to the forecast electricity prices. The former was used in order to obtain the electricity prices forecast, since it showed significantly better predictive performances. Consequently, the financial analysis results indicated this business strategy is a financially more viable option, even though it implies increased risks. All investigated metrics and sensitivity analysis pointed in favor of this option, which has significantly higher profitability with a shorter payback period, compared to the usual market strategy. The main conclusion and recommendation drawn from the analysis are that taking into account the entire environment and prospects for the following years, a riskier business strategy of entering the market directly, or a so-called structured PPA, is put forward to improve project returns and speed up energy-transformation processes in a developing country.
Comparison of Phase-Shifting Transformers Properties
Authors: Albrechtowicz Paweł , Rozegnał Bartosz , Cisek Piotr
Published: August 2022

This article presents different phase shifting transformers (PSTs) types and their influence on the transmitted active power and energy parameters. Typical PSTs, both symmetrical (SPST) and asymmetrical (APST), are compared to the asymmetrical controllable PST (ACPST). The ACPST allows for regulating both quadrature and longitudinal voltage, which makes this type interesting in practical applications and power flow optimizations. The collected data enable a direct comparison of these PSTs’ properties. APST allows high power transfer, but the voltage increase in some cases cannot be acceptable. SPST type in taken tests has the best properties concerning the transferred power, output voltage, and internal voltage drop. ACPST, in its primary mode, can be efficiently used as a substitute for the SPST. However, in some range of injected quadrature voltages, it can achieve even better properties than the SPST. The laboratory and simulation tests allow the development of the ACPST regulation to achieve the best properties among other PSTs, with the possibility to operate, e.g., on the constant ACPST output voltage, in quasi-symmetrical mode and any other, which may be needed in power systems.
Effects of Solubilizer and Magnetic Field during Crystallization Induction of Ammonium Bicarbonate in New Ammonia-Based Carbon Capture Process
Authors: Dong Linhan , Feng Dongdong , Zhang Yu , Dong Heming , Zhao Zhiqi , Gao Jianmin , Zhang Feng , Zhao Yijun , Sun Shaozeng , Huang Yudong
Published: August 2022

As a chemical absorption method, the new ammonia carbon capture technology can capture CO2. Adding ethanol to ammonia can reduce the escape of ammonia to a certain extent and increase the absorption rate of CO2. The dissolution and crystallization of ethanol can realize the crystallization of ammonium bicarbonate and generate solid products. The induction of the crystallization process is influenced by many parameters, such as solution temperature, supersaturation, and solvating precipitant content. The basic nucleation theory is related to the critical size of nucleation. Accurate measurement of the induction period and investigating relevant factors can help to assess the nucleation kinetics. The effects of solubilizer content, temperature, and magnetic field on the induction period of the crystallization process of ammonium bicarbonate in the ethanol–H2O binary solvent mixture and determining the growth mechanism of the crystal surface by solid–liquid surface tension and surface entropy factor are investigated. The results indicate that under the same conditions of mixed solution temperature, the crystallization induction period becomes significantly longer, the solid–liquid surface tension increases, and the nucleation barrier becomes more significant and less likely to form nuclei as the content of solvating precipitants in the components increases. At the same solubilizer content, there is an inverse relationship between the solution temperature and the induction period, and the solid–liquid surface tension decreases. The magnetic field can significantly reduce the induction period of the solvate crystallization process. This gap tends to decrease with an increase in supersaturation; the shortening reduces from 96.9% to 84.0%. This decreasing trend becomes more and more evident with the rise of solvent content in the solution. The variation of surface entropy factor under the present experimental conditions ranges from 0.752 to 1.499. The growth mode of ammonium bicarbonate in the ethanol–H2O binary solvent mixture can be judged by the surface entropy factor as continuous growth.
Possibilities of Integrating Adsorption Chiller with Solar Collectors for Polish Climate Zone
Authors: Bujok Tomasz , Sowa Marcin , Boruta Piotr , Mika Łukasz , Sztekler Karol , Chaja Patryk Robert
Published: August 2022

Solar-powered adsorption chillers are a particularly interesting alternative to energy-intensive conventional refrigeration systems. Integration of the adsorption chiller with solar collectors is a very promising concept since the increase in solar radiation coincides with the increased demand for cooling. Such a solution is very economical and environmentally friendly. It also fits in with current trends related to energy policy and sustainable development. The article presents the results of tests conducted for a two-bed adsorption chiller integrated with solar collectors. The tests were performed on selected days of the summer period (July and August) at the KEZO Research Centre PAS in Jablonna (Poland). Based on the results obtained, the performance parameters of the adsorption chiller were determined, and the problems associated with the integration of all components of the system were identified and discussed. The values of the determined Coefficient of Performance (COP) and cooling capacity for the tested adsorption chiller are, depending on the day on which the tests were conducted, from 0.531 to 0.692 and from 5.16 kW to 8.71 kW, respectively. Analysis of the test results made it possible to formulate conclusions related to the design of integrated systems of adsorption chillers with solar collectors.
Investigation of the Adsorption Process of Biochar Açaí (Euterpea olerácea Mart.) Seeds Produced by Pyrolysis
Authors: Guerreiro Lauro Henrique Hamoy , Baia Ana Cláudia Fonseca , Assunção Fernanda Paula da Costa , Rodrigues Gabriel de Oliveira , e Oliveira Rafael Lopes , Junior Sergio Duvoisin , Pereira Anderson Mathias , de Sousa Erika Milene Pinto , Machado Nélio Teixeira , de Castro Douglas Alberto Rocha , Santos Marcelo Costa
Published: August 2022

This work aims to investigate the influence of temperature and chemical impregnation in the textural and morphological composition of the bio-adsorbent of bio-adsorption via thermal cracking of the seeds of açaí. The experiments were carried out at 400 °C and 450 °C using a pilot scale reactor. The efficiency of the organic process was calculated in terms of liquid and solid products selected with a chemical impregnation process with NaOH, mainly with the liquid that had a greater product conversion. The elementary samples of the solid products occur with the occurrence of carbonization with an increase in the temperature of the process and the presence of impregnation. The textural and morphological characterization occurred with an analysis of FT-IR, SEM/EDS, XRF, and B.E.T. The in-phase product was developed through the creation of açaí seed in nature and impregnated with NaOH solution (2 M) at temperatures of 400 °C and 450 °C. The adsorption kinetics of acetic acid were investigated at 5, 10, 15, 20, 60, 120, and 180 s. The adsorption is higher at 450 °C and with the chemical impregnation of NaOH since the experiments were able to remove an amount of 317.51 mg acid/g adsorbent acetic acid. All the models analyzed fit the experiments, both for the kinetic models (pseudo-first order and pseudo-second order) and for the equilibrium models (Langmuir and Freundlich).
Heavy Multi-Articulated Vehicles with Electric and Hybrid Power Trains for Road Freight Activity: An Australian Context
Authors: Allwright Joshua , Rahman Akhlaqur , Coleman Marcus , Kulkarni Ambarish
Published: August 2022

The electrification of vehicles from the automotive and public transport industries can reduce harmful emissions if implemented correctly, but there is little evidence of whether the electrification of heavy freight transportation vehicles (HFTVs), such as multi-articulated vehicles, used in the freight industry could see the same benefits. This work studied heavy multi-articulated freight vehicles and developed a comparative analysis between electric and conventional diesel power trains to reduce their total emissions. Real-world drive cycle data were obtained from a heavy multi-articulated freight vehicle operating around Melbourne, Australia, with a gross combination mass (GCM) of up to 66,000 kg. Numerical models of the case study freight vehicle were then simulated with diesel, through-the-road parallel (TTRP) hybrid and electric power trains over the five different drive cycles with fuel and energy consumption results quantified. Battery weights were added on top of the real-world operating GCMs to assure the operational payload did not have to be reduced to accommodate the addition of electric power trains. The fuel and energy consumptions were then used to estimate the real-world emissions and compared. The results showed a positive reduction in tailpipe emissions, but total greenhouse emission was worse for operation in Melbourne if batteries were charged off the grid. However, if Melbourne can move towards more renewable energy and change its emission factor for generating electricity down to 0.49 kg CO2-e/kWh, a strong decarbonization could be possible for the Australian road freight industry and could help meet emission reduction targets set out in the 2015 Paris Agreement.
DC-Link Voltage Stability Analysis of Grid-Tied Converters Using DC Impedance Models
Authors: Gaddala Ravi Kumar , Majumder Mriganka Ghosh , Rajashekara Kaushik
Published: August 2022

With the integration of renewable energy sources into the power grid, a number of power electronic converters need to be connected together in parallel. Due to this interconnection among the power converters with a common DC bus, the equivalent impedance of the DC network, i.e., DC network impedance (DCNI) of these parallel converters, may vary and can cause oscillations in the DC link voltage (DCLV). In the literature, impedance models of grid-tied converters (GCs) based on the AC side are well reported without including these variations in DCNI. In addition, the dynamics of a phase-locked loop (PLL) play a significant role in GC system stability. To evaluate these stability issues, this paper proposes small signal impedance models viewing from the DC side of a three-phase GC operating under different control modes considering the PLL dynamics and the DCNI variations. Using the proposed DC impedance models (DCIM), DCLV stability analysis is evaluated for a GC. It is verified through bode plots that the interaction between the proposed DCIM and DCNI leads to unstable operation of the closed-loop converter near the PLL bandwidth when the phase difference between DCIM and DCNI is more than 180 degrees. Finally, the analytically developed models are validated using hardware in-the-loop (HIL) testing.
Optimal Sizing, Control, and Management Strategies for Hybrid Renewable Energy Systems: A Comprehensive Review
Authors: Khan Akhlaque Ahmad , Minai Ahmad Faiz , Pachauri Rupendra Kumar , Malik Hasmat
Published: August 2022

To meet the expanding energy demand, all available energy sources must be utilized. Renewable energies are both eternal and natural, but their major downside is their inconsistency. Due to the rising costs of fossil fuels and the CO2 they emit, hybrid renewable energy (HRE) sources have gained popularity as an alternative in remote and rural areas. To address this issue, a hybrid renewable energy system (HRES) can be developed by combining several energy sources. In order to build modern electrical grids that have advantages for the economy, environment, and society, the hybrid system is preferable. A summary of various optimization methods (modeling techniques) of an HRES is presented in this paper. This study offers an in-depth analysis of the best sizing, control methodologies, and energy management strategies, along with the incorporation of various renewable energy sources to form a hybrid system. Modern hybrid renewable energy system utilities rely more on an optimal design to reduce the cost function. Reviews of several mathematical models put out by various academicians are presented in this work. These models were created based on reliability analyses incorporating design factors, objective functions, and economics. The reader will get familiar with numerous system modelling optimization strategies after reading this study, and they will be able to compare different models based on their cost functions. Numerous modeling approaches and software simulation tools have been created to aid stakeholders in the planning, research, and development of HRES. The optimal use of renewable energy potential and the meticulous creation of applicable designs are closely tied to the full analysis of these undoubtedly complicated systems. In this field, as well, several optimization restrictions and objectives have been applied. Overall, the optimization, sizing, and control of HRES are covered in this paper with the energy management strategies.
The Effect of the Load Power Factor of the Inductive CT’s Secondary Winding on Its Distorted Current’s Harmonics Transformation Accuracy
Authors: Kaczmarek Michal , Kaczmarek Piotr , Stano Ernest
Published: August 2022

In this paper, we present an investigation into the influence of the load power factor of secondary winding on the metrological performance of inductive CTs with frequencies from 50 Hz to 5 kHz of the harmonic of a transformed distorted current. The results clearly indicated that the inductive load caused a deterioration in the transformation accuracy of the inductive CT. To ensure the most advantageous conditions of their operation, a resistive load should be used. The inductive CTs for the frequencies of the transformed harmonic of a distorted primary current from 50 Hz to 5 kHz may ensure the accuracy class designated for the transformation of the sinusoidal current of a frequency of 50 Hz with the same limiting values of errors. Moreover, an analysis of the generated low-order harmonics by a 300 A/5 A CT determined for the power factor of 0.8 inductive and 1.0 of the secondary winding was investigated. These results for the transformed distorted currents of 3rd, 5th and 7th higher harmonics were evaluated for a rated load and 25% of this value.
Efficiency of Shaping the Value Chain in the Area of the Use of Raw Materials in Agro-Biorefinery in Sustainable Development
Authors: Bartkowiak Anna , Bartkowiak Piotr , Kinelski Grzegorz
Published: August 2022

Currently, one of the main directions of agricultural development in Poland is the pursuit of sustainable development, rational management of material resources, and striving for energy self-sufficiency, while maintaining low greenhouse gas emissions. It is an alternative to constantly supported coal solutions. Sustainable development in the sense of processes taking place in enterprises affects many key areas of their activity. One of them is the measurement of efficiency, another is the compatibility with nature and the environment, and the perception of humans and their role. Measures of enterprises’ effectiveness should be considered in relation to the objectives of the enterprise. Biorefineries play a special role in shaping the new energy reality, being a system that connects various devices and biomass conversion processes to produce energy, fuel, and other valuable products. The essence of the functioning of biorefineries is as value chains; that is, a series of interrelated activities of specific importance and market value. The study aims to identify the determinants and efficiency of value chains in agricultural biorefineries according to the concept of sustainable development and the use of biomass resources in biorefining processes. Identifying and analyzing individual stages allows one to demonstrate the effectiveness of the implementation of technology using renewable energy sources, according to the concept of sustainable development and the implementation of the direction of the circular economy.
Machine Learning Approach for Short-Term Load Forecasting Using Deep Neural Network
Authors: Alotaibi Majed A.
Published: August 2022

Power system demand forecasting is a crucial task in the power system engineering field. This is due to the fact that most system planning and operation activities basically rely on proper forecasting models. Entire power infrastructures are built essentially to provide and serve the consumption of energy. Therefore, it is very necessary to construct robust and efficient predictive models in order to provide accurate load forecasting. In this paper, three techniques are utilized for short-term load forecasting. These techniques are deep neural network (DNN), multilayer perceptron-based artificial neural network (ANN), and decision tree-based prediction (DR). New predictive variables are included to enhance the overall forecasting and handle the difficulties caused by some categorical predictors. The comparison among these three techniques is executed based on coefficients of determination R2 and mean absolute error (MAE). Statistical tests are performed in order to verify the results and examine whether these models are statistically different or not. The results reveal that the DNN model outperformed the other models and was statistically different from them.
Decision-Making Processes of Renewable Energy Consumers Compared to Other Categories of Ecological Products
Authors: Sobocińska Magdalena , Mazurek-Łopacińska Krystyna , Graczyk Andrzej , Kociszewski Karol , Krupowicz Joanna
Published: August 2022

In the scientific discourse on consumption, increasingly more attention is being paid to sustainable development. Regarding the fact that not only various types of enterprises, but also consumers contribute to the excessive consumption of natural resources, it is of crucial importance to reduce the knowledge gap in the field of sustainable consumer behavior and decision-making processes related to the choice of organic products. The paper aims to present the decision-making processes of Polish consumers of renewable energy against the background of other categories of ecological products. Special attention is paid to the extent in which the offer is adjusted to the needs of consumers of renewable energy in Poland, compared to other categories of ecological products. The paper also shows the perception of the consumer of ecological products by buyers of renewable energy and by people who do not buy ecological products. The paper is based on a literature review and the results of a quantitative empirical study. The quantitative research was performed on a nationwide sample of 1032 people, among whom 509 people bought an organic product in the last 3 months, and 523 people did not purchase such a product during this period. The analysis of the results allows us to conclude that in the case of renewable energy, factors such as price, quality and the producer’s certification play a crucial role in the decision-making processes of Polish consumers. The hierarchy of criteria considered in the decision-making process related to the purchase of renewable energy and equipment enabling the use of renewable energy sources is quite similar to the one observed when purchasing electric cars. At the same time, it should be noted that almost every second person purchasing renewable energy compares many offers and spends a relatively long time contemplating their choice.
Degradation Trend Prediction of Hydropower Units Based on a Comprehensive Deterioration Index and LSTM
Authors: Wang Yunhe , Xiao Zhihuai , Liu Dong , Chen Jinbao , Liu Dong , Hu Xiao
Published: August 2022

Deterioration trend prediction of hydropower units helps to detect abnormal conditions of hydropower units and can prevent early failures. The reliability and accuracy of the prediction results are crucial to ensure the safe operation of the units and promote the stable operation of the power system. In this paper, the long short-term neural network (LSTM) is introduced, a comprehensive deterioration index (CDI) trend prediction model based on the time–frequency domain is proposed, and the prediction accuracy of the situation trend of hydropower units is improved. Firstly, the time–domain health model (THM) is constructed with back-propagation neural network (BPNN) and condition parameters of active power, guide vane opening and blade opening and the time–domain indicators. Subsequently, a frequency-domain health model (FHM) is established based on ensemble empirical mode decomposition (EEMD), approximate entropy (ApEn), and k-means clustering algorithm. Later, the time–domain degradation index (TDI) is developed according to THM, the frequency-domain degradation index (FDI) is constructed according to FHM, and the CDI is calculated as a weighted sum by TDI and FDI. Finally, the prediction model of LSTM is proposed based on the CDI to achieve degradation trend prediction. In order to validate the effectiveness of the CDI and the accuracy of the prediction model, the vibration waveform dataset of a hydropower plant in China is taken as a case study and compared with four different prediction models. The results demonstrate that the proposed model outperforms other comparison models in terms of predicting accuracy and stability.
Diverse and Flexible Coping Strategy for Nuclear Safety: Opportunities and Challenges
Authors: Xu Hong , Zhang Baorui
Published: August 2022

The concept and methodology of traditional Defense in Depth (DID) was challenged in the Fukushima nuclear accident. In order to fix the weakness of the traditional emergency strategies of nuclear power plants (NPPs) and to enhance the DID for nuclear safety, the U.S. Nuclear Energy Institute (NEI) put forward the concept of Diverse and Flexible Coping Strategies (FLEX) for the special purpose of beyond-design-basis external event (BDBEE) hazard mitigation and the corresponding FLEX support guidelines (FSG). The theory has been wildly spread and accepted by many countries that generate nuclear power. The research on the FLEX strategy is a new trend in nuclear engineering in the recent decade. It provides not only fixed on-site equipment/devices but also on- and off-site portable resources to strengthen the reliability of the nuclear safety system, especially for the disaster/hazards (similar to the Fukushima nuclear accident) triggered by BDBEEs. After a brief introduction of the FLEX strategy, four opportunities and ten challenges are summarized. Subsequently, in view of these challenges and technical difficulties, five suggestions for future work are recommended.