bluuebunny/crossref_metadata_2025 huggingface dataset:
Automating Component-Level Stress Measurements for Inverter Reliability Estimation
Authors: Flicker Jack , Johnson Jay , Hacke Peter , Thiagarajan Ramanathan
Published: July 2022

In the near future, grid operators are expected to regularly use advanced distributed energy resource (DER) functions, defined in IEEE 1547-2018, to perform a range of grid-support operations. Many of these functions adjust the active and reactive power of the device through commanded or autonomous operating modes which induce new stresses on the power electronics components. In this work, an experimental and theoretical framework is introduced which couples laboratory-measured component stress with advanced inverter functionality and derives a reduction in useful lifetime based on an applicable reliability model. Multiple DER devices were instrumented to calculate the additional component stress under multiple reactive power setpoints to estimate associated DER lifetime reductions. A clear increase in switch loss was demonstrated as a function of irradiance level and power factor. This is replicated in the system-level efficiency measurements, although magnitudes were different—suggesting other loss mechanisms exist. Using an approximate Arrhenius thermal model for the switches, the experimental data indicate a lifetime reduction of 1.5% when operating the inverter at 0.85 PF—compared to unity PF—assuming the DER failure mechanism thermally driven within the H-bridge. If other failure mechanisms are discovered for a set of power electronics devices, this testing and calculation framework can easily be tailored to those failure mechanisms.
Magnetic Circuit Design and Experiment of Novel Lorentz Magnetic Bearing with Double Air Gap
Authors: Cao Shinan , Niu Pingjuan , Wang Wei , Liu Qiang , Li Jing , Sheng Sha
Published: July 2022

A uniform magnetic density distribution in the air gap is key for the Lorentz magnetic bearing to achieve high precision control and large torque output. To overcome the small magnetic field strength in an explicit magnetic bearing and a high magnetic density fluctuation rate in an implicit Lorentz magnetic bearing, a second air gap design method is proposed based on the maximum magnetic density distribution in the winding area. A novel Lorentz bearing with a double second air gap is designed. The maximum magnetic field strength in the winding area is calculated by the finite element method, and the structure of the double second air gap is designed. To reduce the calculation error of the magnetic field strength, the division of the reluctance by the magnetic induction line is proposed. The reluctance calculation formula is given. Based on Ohm’s law, the calculation of the magnetic field strength is obtained. Finally, a prototype of the novel Lorentz magnetic bearing is made. The magnetic field strength in the winding area and the magnetic density fluctuation rate are measured with a magnetic density measurement instrument. The maximum magnetic flux density in the winding area is 0.631 T, and the magnetic field strength is 0.58%. Less difference is found between the measurement result and the finite element result.
Implementation of an Improved Motor Control for Electric Vehicles
Authors: Men Xiaojin , Guo Youguang , Wu Gang , Chen Shuangwu , Shi Chun
Published: July 2022

Electric vehicles are regarded as a significant way to mitigate the global energy crisis and the environmental pollution problem. Motor control is a very important part for electric vehicles. As for hardware, a motor controller usually has components such as a power module, microprocessor unit, IGBT driver, sensors, and resolver-to-digital convertor. As for software, a field-oriented control (FOC) with space vector pulse width modulation (SVPWM) is a popular method, while model predictive control (MPC) has recently shown great potential in motor drives. In this paper, both FOC and MPC are discussed and the performances are compared based on experiments. As the implementation is on a digital processor, the discretization and normalization are addressed, and the flux observer and speed estimation are discussed. Some practical issues for implementation are also talked about, such as field weakening control, overmodulation, etc. This paper focuses on how to implement the improved motor control for electric vehicles as industrial applications. The steady-state torque performances of this motor controller are verified by motor test-bench experiments. MPC shows as good performance as FOC in these experiments.
Just Transitions for Oil and Gas Regions and the Role of Regional Development Policies
Authors: Krawchenko Tamara Antonia , Gordon Megan
Published: July 2022

The oil and gas industry is a major economic driver in many regions and countries, providing workers with well-paid jobs and spurring investments and economic growth. The need to transition these industries in order to meet climate commitments presents a major challenge. How can the costs and risks to workers and communities of the transition be mitigated? How can stakeholders be included in decisions that impact them? How do transitions impact the broader economy of these regions and what are they transitioning to? Importantly, how can regional development policies support this process? This comparative policy review explores just transition management in three oil and gas dependent regions that have signified the need to transition away from the oil and gas sector, i.e., Taranaki (New Zealand), the northeast of Scotland, and the Jutland peninsula in southwest Denmark, drawing out key lessons and leading practices. These cases are positioned within an empirically grounded, conceptual framework of national and regional just transition policies.
Study on the Influence of Working-Fluid’s Thermophysical Properties on the Stirring-Heating
Authors: Liu Xingran , Sun Xianpeng , He Jinhong , Wang Da , Qiu Xinyang , Bi Shengshan , Cao Yanfei
Published: July 2022

The thermophysical properties of a working-fluid play an important role in the process of stirring-heating. The heating process of stirring is accompanied by two processes: the friction between the solid mechanism and the working-fluid and the viscous dissipation of the working liquid. Traditionally, the sensible heat of water-based working-fluids is low, while that of oil-based working-fluids is higher, but the load capacity is relatively low. In order to find a balance between the two, an optimal stirring working-fluid should be selected. In this study, an experimental method was used to study the heating process of 30 kinds of working-fluids. The numerical evaluation model of the effects of thermophysical properties on the comprehensive evaluation index of heat (CEIH) was established by multiple linear regression methods, and a computational fluid dynamics (CFD) tool was used to analyze the heat generation and flow field of different working-fluids in the stirring-heating device. The results show that viscous dissipation is the most important way of stirring-heating. CFD can completely replace the experiment to study the heating effect of stirring. The thermophysical properties of the working-fluid affect the upper circulation and the overall velocity of the double circulation flow. The experimental results and regression model analysis show that specific heat capacity has the greatest effect on the heating effect, but density will also play a positive role in the stirring-heating. Water-based salt solutions such as KCl can achieve a better heating effect, and oil-based working-fluids are not always the best choice.
Using OLTC-Fitted Distribution Transformer to Increase Residential PV Hosting Capacity: Decentralized Voltage Management Approach
Authors: Aydin Muhammed , Alnaser Sahban , Althaher Sereen
Published: July 2022

The increasing Photovoltaic (PV) penetration in residential Low Voltage (LV) networks is likely to result in a voltage rise problem. One of the potential solutions to deal with this problem is to adopt a distribution transformer fitted with an On-Load Tap Changer (OLTC). The control of the OLTC in response to local measurements reduces the need for expensive communication channels and remote measuring devices. However, this requires developing an advanced decision-making algorithm to estimate the existence of voltage issues and define the best set point of the OLTC. This paper presents a decentralized data-driven control approach to operate the OLTC using local measurements at a distribution transformer (i.e., active power and voltage at the secondary side of the transformer). To do so, Monte Carlo simulations are utilized offline to produce a comprehensive dataset of power flows throughout the distribution transformer and customers’ voltages for different PV penetrations. By the application of the curve-fitting technique to the resulting dataset, models to estimate the maximum and the minimum customers’ voltages are defined and embedded into the control logic to manage the OLTC in real time. The application of the approach to a real UK LV feeder shows its effectiveness in improving PV hosting capacity without the need for remote monitoring elements.
Cross Entropy Covariance Matrix Adaptation Evolution Strategy for Solving the Bi-Level Bidding Optimization Problem in Local Energy Markets
Authors: Dabhi Dharmesh , Pandya Kartik , Soares Joao , Lezama Fernando , Vale Zita
Published: July 2022

The increased penetration of renewables in power distribution networks has motivated significant interest in local energy systems. One of the main goals of local energy markets is to promote the participation of small consumers in energy transactions. Such transactions in local energy markets can be modeled as a bi-level optimization problem in which players (e.g., consumers, prosumers, or producers) at the upper level try to maximize their profits, whereas a market mechanism at the lower level maximizes the energy transacted. However, the strategic bidding in local energy markets is a complex NP-hard problem, due to its inherently nonlinear and discontinued characteristics. Thus, this article proposes the application of a hybridized Cross Entropy Covariance Matrix Adaptation Evolution Strategy (CE-CMAES) to tackle such a complex bi-level problem. The proposed CE-CMAES uses cross entropy for global exploration of search space and covariance matrix adaptation evolution strategy for local exploitation. The CE-CMAES prevents premature convergence while efficiently exploring the search space, thanks to its adaptive step-size mechanism. The performance of the algorithm is tested through simulation in a practical distribution system with renewable energy penetration. The comparative analysis shows that CE-CMAES achieves superior results concerning overall cost, mean fitness, and Ranking Index (i.e., a metric used in the competition for evaluation) compared with state-of-the-art algorithms. Wilcoxon Signed-Rank Statistical test is also applied, demonstrating that CE-CMAES results are statistically different and superior from the other tested algorithms.
Fault Diagnosis Methods and Fault Tolerant Control Strategies for the Electric Vehicle Powertrains
Authors: Wu Chenyun , Sehab Rabia , Akrad Ahmad , Morel Cristina
Published: July 2022

With the challenges of global climate anomalies and energy crises, vehicle electrification has an increasing trend as an exciting solution for reducing greenhouse gas emissions and fossil fuel-based energy consumption [...]
Modal Analysis of a Lithium-Ion Battery for Electric Vehicles
Authors: Garafolo Nicholas Gordon , Farhad Siamak , Koricherla Manindra Varma , Wen Shihao , Esmaeeli Roja
Published: July 2022

The battery pack in electric vehicles is subjected to road-induced vibration and this vibration is one of the potential causes of battery pack failure, especially once the road-induced frequency is close to the natural frequency of the battery when resonance occurs in the cells. If resonance occurs, it may cause notable structural damage and deformation of cells in the battery pack. In this study, the natural frequencies and mode shapes of a commercial pouch lithium-ion battery (LIB) are investigated experimentally using a laser scanning vibrometer, and the effects of the battery supporting methods in the battery pack are presented. For this purpose, a test setup to hold the LIB on the shaker is designed. A numerical analysis using COMSOL Multiphysics software is performed to confirm that the natural frequency of the designed test setup is much higher than that of the battery cell. The experimental results show that the first natural frequency in the two-side supported and three-side supported battery is about 310 Hz and 470 Hz, respectively. Although these frequencies are more than the road-induced vibration frequencies, it is recommended that the pouch LIBs are supported from three sides in battery packs. The voltage of the LIB is also monitored during all experiments. It is observed that the battery voltage is not affected by applying mechanical vibration to the battery.
Adaptive Sliding-Mode Control for Electric Spring in Microgrids with Distributed Renewable Energy
Authors: Yin Fagen , Wang Chun , Wang Weizhang
Published: July 2022

Electric springs (ESs) are novel electric-power devices that alleviate power-quality problems such as voltage fluctuations induced by grid access to renewable energy resources. However, with the continuous increase of uncertain factors such as parameter perturbation and external disturbance, the environment becomes more complicated, so traditional linear controllers for ESs are finding it increasingly difficult to meet the control requirements due to narrow stability regions, low precision, and poor robustness. To overcome this problem, we propose herein a control method that combines adaptive control and sliding-mode control and apply it to ESs. First, an inexact model of the ES system was established and analyzed. Next, an ES control system was designed based on adaptive sliding-mode control, and then the asymptotic stability of the closed-loop system is proven. Finally, the proposed control system was verified through a MATLAB simulation. The results show that adaptive sliding-mode control not only ensures the voltage stability of critical loads in the microgrid but also resists the influence of parameter perturbation and external disturbances, leading to better steady-state and dynamic performance than a linear controller.
DYN3D and CTF Coupling within a Multiscale and Multiphysics Software Development (Part II)
Authors: Davies Sebastian , Litskevich Dzianis , Merk Bruno , Levers Andrew , Bryce Paul , Detkina Anna
Published: July 2022

Traditionally, the complex coupled physical phenomena in nuclear reactors has resulted in them being treated separately or, at most, simplistically coupled in between within nuclear codes. Currently, coupling software environments are allowing different types of coupling, modularizing the nuclear codes or multi-physics. Several multiscale and multi-physics software developments for LWR are incorporating these to deliver improved or full coupled reactor physics at the fuel pin level. An alternative multiscale and multi-physics nuclear software development between NURESIM and CASL is being created for the UK. The coupling between DYN3D nodal code and CTF subchannel code can be used to deliver improved coupled reactor physics at the fuel pin level. In the current journal article, the second part of the DYN3D and CTF coupling was carried out to analyse a parallel two-way coupling between these codes and, hence, the outer iterations necessary for convergence to deliver verified improved coupled reactor physics at the fuel pin level. This final verification shows that the DYN3D and CTF coupling delivers improved effective multiplication factors, fission, and feedback distributions due to the presence of crossflow and turbulent mixing.
Application of Hydro Borehole Mining (HBM) Technology for Lignite Extraction—An Environmental Assessment (LCA) and a Comparative Study with the Opencast Method
Authors: Maksymowicz Marcin , Frejowski Aleksander , Bajcar Adam , Jura Bartłomiej
Published: July 2022

The article presents the impact of lignite mining on the environment associated with the introduction of hydro borehole mining (HBM) technology. The results are partially based on the HydroCoal Plus project results, where an environmental assessment of lignite HBM technology was performed. In order to reach the goals of the task, a life cycle assessment (LCA) study was used to assess selected environmental aspects of the HBM single-borehole lignite production process covering selected environmental impact categories such as energy consumption, fuel consumption, water consumption and carbon footprint. The LCA procedure was adapted in an innovative way, constituting another added value to the shown research. The second part of this paper describes opportunities identified by the authors to minimize the environmental impact of lignite production by implementing the HBM method compared to the conventional opencast method.
Special Issue: Rock Burst Disasters in Coal Mines
Authors: Chen Yulong , Zhang Junwen , Chen Jianhang , Deng Xuejie
Published: July 2022

Rock bursts are often encountered in coal mines worldwide [...]
A Fuzzy-PSO-PID with UPFC-RFB Solution for an LFC of an Interlinked Hydro Power System
Authors: Joshi Milan , Sharma Gulshan , Bokoro Pitshou N. , Krishnan Narayanan
Published: July 2022

An LFC plays a vital part in passing on quality electric energy to energy consumers. Furthermore, with cutting-edge designs to move to modern and pollution-free energy generation, it may be conceivable to have a major hydropower in the future. Hydro plants are not suitable for continuous load alteration due to the large response time of hydroturbines. Hence, this paper shows a novel control design for an LFC of a hydro-hydro interlinked system based on joint actions of fuzzy logic with PID effectively optimized through particle swarm optimization (PSO) resulting in a Fuzzy-PSO-PID. The outcome of Fuzzy-PSO-PID is evaluated for step load variation in one of the regions of hydropower, and the outcomes of Fuzzy-PSO-PID are compared with a recently published LFC with respect to integral time absolute error (ITAE) value, values of PID, and graphical outcomes to show the impact of the proposed LFC action. The numerical results show that the ITAE value (0.002725) obtained through the proposed design is minimum in comparison to error values achieved through other LFC actions, and the pickup values obtained on these error values are considered to achieve the desired LFC. However, there is still scope for LFC enhancement as responses of hydropower are sluggish with higher oscillations; hence the UPFC and RFB are integrated into the interlinked hydro-hydro system, and the application outcomes are evaluated again considering the non-linearity, standard load alteration, random load pattern, and in view of parametric alterations. It is seen that the ITAE value reduces to 0.002471 from 0.002725 when UPFC is connected to the tie-line, and it further reduces to 0.001103 when a UPFC-RFB combination is used with Fuzzy-PSO-PID for a hydro leading system. The positive impact of the UPFC-RFB for hydropower is also seen from the application results.
Non-Stationary Random Medium Parameter Estimation of Petrophysical Parameters Driven by Seismic Data
Authors: Lin Ying , Zhang Guangzhi , Huang Minmin , Wang Baoli , Chen Siyuan
Published: July 2022

The estimation of non-stationary random medium parameters of petrophysical parameters is the key to the application of random medium theory in fine seismic exploration. We proposed a method for estimating non-stationary random medium parameters of petrophysical parameters using seismic data. Based on the linear petrophysical model, the relationship between seismic data and porosity, clay volume, and water saturation in the random medium was described, and the principle and method of estimating the autocorrelation parameters of the petrophysical parameter random medium were introduced in this study. Subsequently, the specific steps of applying the power spectrum method, for parameter estimation in non-stationary random media with petrophysical parameters, were explained. The feasibility and correctness of the method were verified through the estimation test of the two-dimensional theoretical model. Eventually, the estimation test of non-stationary random medium parameters of petrophysical parameters was carried out by field seismic data, and the results indicated that the non-stationary random medium parameters can better portray the information of subsurface medium petrophysical parameters. The method can provide a reference for the construction of a priori information on petrophysical parameters, and it can also provide a theoretical basis for the in-depth application of random medium theory to practical data.
Virtual Signal Injection Maximum Torque per Ampere Control Based on Inductor Identification
Authors: Jin Ning-Zhi , Chen Hong-Chao , Sun Dong-Yang , Wu Zhi-Qiang , Zhou Kai , Zhang Long
Published: July 2022

The high-frequency signal injection-type maximum torque per ampere (MTPA) algorithm is usually employed to control the operation of interior permanent magnet synchronous motors (IPMSMs). The MTPA algorithm exhibits good dynamic performance and anti-interference ability. However, due to the injection of a high-frequency current signal, problems such as torque ripple and additional loss are encountered. Therefore, in this paper, a virtual signal injection control (VSIC) method that does not require actual injection is proposed for solving the aforementioned problems while yielding good performance. However, in the control process of the proposed method, the d-axis inductance parameter affects the accuracy of the torque information, resulting in errors in the system. To solve this problem, an online identification algorithm of model reference adaptive systems (MRAS) based on the Popov super stability theory as the basis for the design of the adaptive law is proposed in this paper. The d-axis inductance parameter of the motor is obtained in real-time and then introduced into the control system by using the VSIC method. Finally, VSIC-type MTPA control based on inductance identification is realized. The proposed algorithm does not depend on the design parameters of the motor and exhibits good dynamic response and anti-interference performance.
Energy Consumption Analysis for Coupling Air Conditioners and Cold Storage Showcase Equipment in a Convenience Store
Authors: Kusnandar  , Permana Indra , Chiang Weiming , Wang Fujen , Liou Changyu
Published: July 2022

The energy use intensity (EUI) of convenience stores was substantially higher than that of office buildings and hotels, due to a compact footprint but a high density of equipment yielded a higher EUI. As a result, it is critical to assess and maintain the state of the convenience store in order to obtain a lower EUI and reduce energy consumption. This study utilizes a convenience store to evaluate energy consumption and perform a CFD simulation to see how the environment influences by cold storage showcase (CSS) equipment. On the basis of field testing and on-site web-based monitoring data, a survey of baseline information through data collecting and energy benchmarking data has been provided and extensively examined. According to energy monitoring, the convenience store’s highest electricity use is 23,055 kWh in June, and the lowest power consumption is 15,216 kWh in February. The CFD simulation results revealed that the temperature near the CSS can be 3–5 °C lower than in other regions. The temperature nearby return air will be lower as a result of the low-temperature air impacts from CSS. The AC sensor detects that the environment has met the indoor requirements and performs the load reduction operation. After adjusting the AC temperature, it is discovered that the unit is unable to attain the appropriate temperature. Energy consumption can be reduced, resulting in more energy-efficient AC and CSS operations. Furthermore, the CSS’s cold air effect might be taken advantage of by raising the AC-2 temperature set point to generate energy savings.
Recent Studies on the Environmentally Benign Alkaline-Earth Silicide Mg2Si for Middle-Temperature Thermoelectric Applications
Authors: Shiojiri Daishi , Iida Tsutomu , Hirayama Naomi , Imai Yoji , Sugawara Hiroharu , Kusaka Jin
Published: July 2022

Most primary energy sources, such as the fossil fuels of oil, coal, and natural gas, produce waste heat. Recycling of this unused thermal energy is necessary in order to increase the efficiency of usage. Thermoelectric (TE) conversion technologies, by which waste heat is directly converted into electricity, have been extensively studied, and the development of these technologies has continued. TE power-generation has attracted significant attention for use in self-powered wireless sensors, which are important for our increasingly sophisticated information society. For the middle-temperature range (i.e., 600–900 K), with applications such as automobiles, intensive studies of high-performance TE materials have been conducted. In this study, we review our recent experimental and theoretical studies on alkaline-earth silicide Mg2Si TE materials, which consist of nontoxic abundant earth elements. We demonstrate improvements in TE performance brought about by lightly doping Mg2Si with isoelectronic impurities. Furthermore, we examine the electrode formation and material coatings. Finally, we simulate the exhaust heat requirements for the practical application of TE generators.
A Low-Cost, Open-Source Peer-to-Peer Energy Trading System for a Remote Community Using the Internet-of-Things, Blockchain, and Hypertext Transfer Protocol
Authors: Baig Mirza Jabbar Aziz , Iqbal M. Tariq , Jamil Mohsin , Khan Jahangir
Published: July 2022

A low-cost, open-source peer-to-peer (P2P) energy trading system for a remote community is presented in this paper. As a result of its geographic location, this community has never been able to access electricity and other modern amenities. This study aims to design and implement a P2P energy trading system for this remote community that allows residents to take advantage of distributed energy resources. A Raspberry Pi 4 Model B (Pi4B) hosts the main server of the trading system that includes the user interface and a local Ethereum blockchain server. The Ethereum blockchain is used to deploy smart contracts. The Internet-of-Things (IoT) servers run on ESP32 microcontrollers. Sensors and actuators connected to the ESP32 are field instrumentation devices that facilitate acquiring, monitoring, and transferring energy data in real-time. To perform trading activities, React.JS open-source library was used to develop the blockchain-enabled user interface. An immutable blockchain network keeps track of all transactions. The proposed system runs on a local Wi-Fi network with restricted authorization for system security. Other security measures such as login credentials, private key, firewall, and secret recovery phrases are also considered for information security and data integrity. A Hypertext Transfer Protocol is implemented for communication between the servers and the client. This explains the overall system design, implementation, testing, and results.
A Comprehensive Energy Model for an Optimal Design of a Hybrid Refrigerated Van
Authors: Maiorino Angelo , Mota-Babiloni Adrián , Petruzziello Fabio , Del Duca Manuel Gesù , Ariano Andrea , Aprea Ciro
Published: July 2022

The path towards decarbonization requires a progressive adaptation of all refrigeration systems, but only stationary ones have been intensely studied to improve their environmental performance. However, refrigerated transport is vital in the cold chain and must be considered in the green transition. In this paper, we propose a model for a hybrid refrigerated van that includes photovoltaic panels and electric batteries to decrease total greenhouse gas emissions from the engine. Thermal, electrical, and battery sub-models are considered and integrated into the comprehensive hybrid solar-powered refrigerated van model. Different technologies are compared, including lithium and lead-acid batteries and three different types of photovoltaic panels. The model was validated regarding van fuel consumption, showing a 4% deviation. Single and multiple delivery scenarios are considered to assess the energy, economic, and environmental benefits. Monthly CO2,e emissions could be reduced by 20% compared to a standard refrigerated van. Despite the environmental benefits provided by this sustainable solution, the payback period is still too long (above 20 years) because of the necessary investment to adapt the vehicle and considering fuel and electricity prices currently.
Modelling and Control Development of a Cascaded NPC-Based MVDC Converter for Harmonic Analysis Studies in Power Distribution Networks
Authors: Alghamdi Thamer A. H. , Anayi Fatih , Packianather Michael
Published: July 2022

Today’s power distribution networks are predicted to incorporate more Power Electronics (PE)-based power conversion systems, widely acknowledged as harmonic sources. Concerns about power harmonic severity in the distribution networks can arise, especially with the growing numbers of Medium Voltage Direct Current (MVDC) systems, which are also facilitated by such power converters. Yet, an accurate harmonic model of the MVDC converter is required to investigate its harmonic emissions, propagations, effects, and solutions in today’s distribution networks. This article is devoted to the development of a detailed model of a cascaded Neutral Point-Clamped (NPC)-based MVDC converter for accurate harmonic analysis studies. An appropriate control system with a simple Proportional Integral (PI) controller tuned using the loop-shaping technique is developed. An interleaved Sinusoidal Pulse-Width Modulation (SPWM) scheme aiming to improve the harmonic performance of such an application is introduced. The detailed model of the MVDC system was developed using the Simulink/MATLAB simulation environment, for which the concept of operation was validated, control system performance was investigated, and the effectiveness of the harmonic reduction method was analysed. The key finding is that the interleaved SPWM technique has significantly reduced the Total Harmonic Distortion (THD) to 2% with no significant even-order harmonic components in comparison to the reported models.
Influence of the Working Parameters of the Chassis Dynamometer on the Assessment of Tuning of Dual-Fuel Systems
Authors: Chojnowski Janusz , Karczewski Mirosław
Published: July 2022

The article presents the justification for the necessity to use chassis dynamometers in the tuning process of dual-fuel trucks. The research system used and the research methodology are presented. The research results present the approach to solving problems related to setting the technical (physical) data of the tested vehicle on the dynamometer, selection of the vehicle engine operation range, the impact of the value of the forced load on the vehicle drive axle, selection of the dyno operation mode for the expected tasks and the impact of the correctness of the selection of the scope of the analysis of data on losses in the drive system. The article shows the above-mentioned influence on the test results on the dynamometer and on the tuning results. The article closes with a conclusion detailing prospects for developing the presented results.
Dynamic Response of SPAR-Type Floating Offshore Wind Turbine under Wave Group Scenarios
Authors: Liu Baolong , Yu Jianxing
Published: July 2022

Numerical simulations are performed within the time domain to investigate the dynamic behaviors of an SPAR-type FOWT under wave group conditions. Towards this goal, the OC3 Hywind SPAR-type FOWT is adopted, and a JONSWAP (Joint North Sea Wave Project)-based wave group is generated by the envelope amplitude approach. The FOWT motion under wave group conditions, as well as the aerodynamic, hydrodynamic, and mooring performances, is simulated by our established in-house code. The rotating blades are modelled by the blade element momentum theory. The wave-body interaction effect is calculated by the three-dimensional potential theory. The mooring dynamics are also taken into consideration. According to the numerical results, the SPAR buoy motions are slightly increased by the wave group, while the heave motion is significantly amplified. Both the aerodynamic performance and the mooring tension are also influenced by the wave group. Furthermore, the low-frequency resonant response could be more easily excited by the wave group.
Numerical Modeling of Horizontal Axis Wind Turbine: Aerodynamic Performances Improvement Using an Efficient Passive Flow Control System
Authors: Belamadi Riyadh , Settar Abdelhakim , Chetehouna Khaled , Ilinca Adrian
Published: July 2022

In this paper, we explore the improvement of the aerodynamic characteristics of wind turbine blades under stall conditions using passive flow control with slots. The National Renewable Energy Laboratory (NREL) Phase II rotor, for which detailed simulations and experimental data are available, served as a baseline for assessing the flow control system effects. The position and configuration of the slot used as a flow control system were determined using CFD analysis. The 3D-RANS equations are solved with ANSYS FLUENT using the k-ω SST turbulence closure model. The pressure coefficient for different wind speeds for the baseline configuration is compared to the available experimental data. The comparison shows that CFD results were better for the attached flow. The current work consists of a 3-D CFD modeling of a rotating blade equipped with different flow control systems: single-slot (S-S) and two-slots (T-S). The computation provides a better understanding of the influence of these flow control devices on the performance of wind turbine blades, the control of boundary layer separation, and the rotation effect. These control systems increase the power output by over 60% at high wind speeds with large separated boundary layer regions. For the configuration with the control system, the slot has shown its ability to delay the boundary layer separation. However, the improved aerodynamic performance has been proven for medium and high angles of attack where the flow is generally in the stall condition. The addition of the second slot changed the flow behavior, and an improvement was observed compared to the single slot configuration. The results are helpful for the design and development of a new generation of wind turbine blades.
Land Subsidence Assessment for Wind Turbine Location in the South-Western Part of Madagascar
Authors: Knez Dariusz , Rajaoalison Herimitsinjo
Published: July 2022

Finding a suitable location is a key factor for long-term investment in wind turbine energy. It includes understanding the area of interest, such as the subsidence of the land. Land subsidence is a gradual decrease in the surface of the Earth due to natural and/or induced causes. It can cause damage, such as settlement problems in the ground near infrastructure including buildings and wind turbines, thus not being a suitable place for long-term investment. Here, we show a case study of land subsidence prediction and assessment of the Atsimo Andrefana region, the great south-western part of Madagascar, using theoretical simulation and satellite images from the Sentinel-1 mission using D-InSAR method. The predicted land subsidence related to the depletion of groundwater reservoirs in the Atsimo Andrefana region is around 12 mm. We found ~5 mm of subsidence related to the growing city of Toliary and with an average subsidence of 124 mm and the highest record of 167 mm in the most southern part of the region for a period of 6 months. The spatial distribution of land subsidence allows us to choose the ideal location for wind turbine settlement, where land subsidence is not that severe, i.e., the areas with subsidence relatively low of equal or less than 10 mm within 6 months of observation, based on the processed data. Such results are essential for future environmentally friendly investments in the affected region, as the demand for green energy will always grow.
Energy Consumption Forecasting in Korea Using Machine Learning Algorithms
Authors: Shin Sun-Youn , Woo Han-Gyun
Published: July 2022

In predicting energy consumption, classic econometric and statistical models are used to forecast energy consumption. These models may have limitations in an increasingly fast-changing energy market, which requires big data analysis of energy consumption patterns and relevant variables using complex mathematical tools. In current literature, there are minimal comparison studies reviewing machine learning algorithms to predict energy consumption in Korea. To bridge this gap, this paper compared three different machine learning algorithms, namely the Random Forest (RF) model, XGBoost (XGB) model, and Long Short-Term Memory (LSTM) model. These algorithms were applied in Period 1 (prior to the onset of the COVID-19 pandemic) and Period 2 (after the onset of the COVID-19 pandemic). Period 1 was characterized by an upward trend in energy consumption, while Period 2 showed a reduction in energy consumption. LSTM performed best in its prediction power specifically in Period 1, and RF outperformed the other models in Period 2. Findings, therefore, suggested the applicability of machine learning to forecast energy consumption and also demonstrated that traditional econometric approaches may outperform machine learning when there is less unknown irregularity in the time series, but machine learning can work better with unexpected irregular time series data.
A Review and Case Analysis on Biaxial Synchronous Loading Technology and Fast Moment-Matching Methods for Fatigue Tests of Wind Turbine Blades
Authors: Lu Liang , Zhu Minyan , Wu Haijun , Wu Jianzhong
Published: July 2022

Wind power utilization is attracting worldwide attention in the renewable energy field, and as wind power develops from land to sea, the size of the blades is becoming incredibly larger. The fatigue test, especially the biaxial synchronous fatigue test for the blades, is becoming an indispensable step to ensure the blade’s quality before mass production, which means the biaxial independent test presently used may have difficulty reproducing the real damage for large-sized blades that oscillate simultaneously in flap-wise and edgewise directions in service conditions. The main point of the fatigue test is to carry out accelerated and reinforced oscillations on blades in the experimental plan. The target moments of critical blade sections are reached or not during the test are treated as one significant evaluation criterion. For independent tests, it is not hard to realize moment matching using additional masses fixed on certain critical blade sections, which may be not easy to put into effect for biaxial synchronous tests, since the mechanical properties and target moments in the flap-wise and edgewise directions are widely varied. To realize the mechanical decoupling for loading force or additional mass inertia force in two directions is becoming one of the key issues for blade biaxial synchronous fatigue testing. For this problem, the present paper proposed one mechanical decoupling design concept after a related literature review. After that, the blade moment design and target matching approach are also proposed, using the Transfer Matrix Method (TMM) for moment quick calculation and Particle Swarm Optimization (PSO) for case optimization.
Visualisation and Thermovision of Fuel Combustion Affecting Heat Release to Reduce NOx and PM Diesel Engine Emissions
Authors: Cisek Jerzy , Leśniak Szymon , Borowski Andrzej , Przybylski Włodzimierz , Mokretskyy Vitaliy
Published: July 2022

Research was conducted on fuels with additives that selectively affect the rate of kinetic (dQk/dα) and diffusion (dQd/dα) combustion in the diesel engine cylinder. In addition to the base fuel (DFB), DFKA fuel with an additive reducing dQk/dα, DFDA fuel with an additive increasing dQd/dα, and DFS fuel with both additives were tested. The main purpose of such dQ/dα course control in the engine cylinder was to simultaneously reduce the emissions of nitrogen oxides (NOx) and particulate matter (PM), and to increase the efficiency of the combustion process. Similar to the course of the dQ/dα, the course of the combustion temperature (Tc(α)) affects the NOx produced and the number of afterburned solid particles; the influence of the fuel additives on the functional curves was analysed. In addition to analysis of the temperature Tc(α) calculated from the indicator diagrams, Tc(α) analysis was conducted using the two-colour method, which allows the analysis of the isotherm distributions locally and temporarily. The two-colour method required prior endoscopic visualisation of the fast-changing processes inside the engine cylinder. Parameters defined by pressure, temperature, heat release rate, and visualisation and thermovision in the engine cylinder (as a function of the crank angle) allowed for an in-depth cause and effect analysis. It was determined why combustion of DFS fuel with both additives produced a synergy resulting in the simultaneous reduction in NOx and PM emissions in the exhaust gas and an increase in combustion efficiency. This publication relates to the field of Mechanical Engineering.
Use of Hybrid Photovoltaic Systems with a Storage Battery for the Remote Objects of Railway Transport Infrastructure
Authors: Shavolkin Olexandr , Shvedchykova Iryna , Gerlici Juraj , Kravchenko Kateryna , Pribilinec František
Published: July 2022

The use of a grid-tied photovoltaic system with a storage battery to increase the power of objects of railway transport infrastructure above the limit on consumption from the grid with the possibility of energy saving is considered. The methods of analysis of energy processes in photovoltaic systems with a storage battery are used. They are added via the processing of archival data of power generation of a photovoltaic battery and computer modeling results. A technique of system parameter calculation to increase the power according to the given load schedule of the object at constant and maximum possible degree of power increasing is developed. The values of the average monthly generation of a photovoltaic battery at the location point of the object based on archival data are used. The principle of the control of power, consumed from the grid, according to the given values of the added and total load is developed. Using the basic schedule of added load power in connection with the graph of photovoltaic battery generation allows reducing the installed power of the storage battery. The additional reduction in the installed power of the photovoltaic and storage batteries is possible at the corresponding choice of the degree of power load increasing. The joint formation of current schedules with reference to the added power value and state of charge of the battery according to the short-term forecast of the generation of a photovoltaic battery is proposed. The value of added power at certain intervals of time is set according to the graph of actual generation of the photovoltaic battery, which contributes to the maximum use of its energy. With the average monthly generation of a photovoltaic battery in the spring–autumn period, the discharge of the battery during the hours of the morning load peak is not used. This reduces the number of deep discharge cycles and extends the battery life. The description of energy processes in steady-state conditions for the daily cycle of system functioning is formalized. On this basis, a mathematical model is developed in MATLAB with an estimation of the costs of electricity consumed from the grid. When modeling, archival data are used for days when the generation of a photovoltaic battery over time intervals is close to average monthly values. This makes it possible to evaluate the effectiveness of system management under conditions close to real during the year.
A Review of Hybrid Soft Computing and Data Pre-Processing Techniques to Forecast Freshwater Quality’s Parameters: Current Trends and Future Directions
Authors: Khudhair Zahraa S. , Zubaidi Salah L. , Ortega-Martorell Sandra , Al-Ansari Nadhir , Ethaib Saleem , Hashim Khalid
Published: July 2022

Water quality has a significant influence on human health. As a result, water quality parameter modelling is one of the most challenging problems in the water sector. Therefore, the major factor in choosing an appropriate prediction model is accuracy. This research aims to analyse hybrid techniques and pre-processing data methods in freshwater quality modelling and forecasting. Hybrid approaches have generally been seen as a potential way of improving the accuracy of water quality modelling and forecasting compared with individual models. Consequently, recent studies have focused on using hybrid models to enhance forecasting accuracy. The modelling of dissolved oxygen is receiving more attention. From a review of relevant articles, it is clear that hybrid techniques are viable and precise methods for water quality prediction. Additionally, this paper presents future research directions to help researchers predict freshwater quality variables.
Barriers to the Effective Adhesion of High-Density Hardwood Timbers for Glue-Laminated Beams in Australia
Authors: Leggate William , McGavin Robert L. , Outhwaite Andrew , Gilbert Benoit P. , Gunalan Shanmuganathan
Published: July 2022

A number of international timbers of high commercial importance are extremely difficult to glue, which is significantly hindering access to global market opportunities for engineered wood products, especially for heavily demanded structural products. Some particularly problematic timbers in Australia are the dominant commercial hardwood species, including spotted gum (Corymbia spp.) and Darwin stringybark (Eucalyptus tetrodonta). These species are renowned for their very high mechanical properties, natural durability and attractive aesthetic appeal. However, they are notoriously difficult to glue, especially for sawn laminate-based engineered wood products, such as structural glue-laminated beams. Despite considerable effort and testing of diverse internationally established best-practice approaches to improve adhesion, glue-laminated beam samples of these timbers still frequently fail to meet the requirements of the relevant standard, mainly due to excessive glue line delamination. This paper discusses the key barriers to effective adhesion of these high-density timbers and particularly emphasises the necessity of achieving greater adhesive penetration. Greater adhesive penetration is required to enhance mechanical interlocking, entanglement and molecular interactions between the adhesive and the wood to achieve stronger and more durable bonds. Potential solutions to enhance adhesive penetration, as well as to improve gluability in general, are discussed in terms of their likelihood to satisfactorily prevent delamination and the potential to be applied at an industrial scale. This new fundamental understanding will assist the development of solutions, allowing industry to commercialise newly engineered wood products made from high-density timbers.