bluuebunny/crossref_metadata_2025 huggingface dataset:
Unstable Landing Platform Pose Estimation Based on Camera and Range Sensor Homogeneous Fusion (CRHF)
Authors: Sefidgar Mohammad , Landry Rene
Published: February 2022

Much research has been accomplished in the area of drone landing and specifically pose estimation. While some of these works focus on sensor fusion using GPS, or GNSS, we propose a method that uses sensors, including four Time of Flight (ToF) range sensors and a monocular camera. However, when the descending platform is unstable, for example, on ships in the ocean, the uncertainty will grow, and the tracking will fail easily. We designed an algorithm that includes four ToF sensors for calibration and one for pose estimation. The landing process was divided into two main parts, the rendezvous and the final landing. Two important assumptions were made for these two phases. During the rendezvous, the landing platform movement can be ignored, while during the landing phase, the drone is assumed to be stable and waiting for the best time to land. The current research modifies the landing part as a stable drone and an unstable landing platform, which is a Stewart platform, with a mounted AprilTag. A novel algorithm for calibration was used based on color thresholding, a convex hull, and centroid extraction. Next, using the homogeneous coordinate equations of the sensors’ touching points, the focal length in the X and Y directions can be calculated. In addition, knowing the plane equation allows the Z coordinates of the landmark points to be projected. The homogeneous coordinate equation was then used to obtain the landmark’s X and Y Cartesian coordinates. Finally, 3D rigid body transformation is engaged to project the landing platform transformation in the camera frame. The test bench used Software-in-the-Loop (SIL) to confirm the practicality of the method. The results of this work are promising for unstable landing platform pose estimation and offer a significant improvement over the single-camera pose estimation AprilTag detection algorithms (ATDA).
Probability Distribution on Full Rooted Trees
Authors: Nakahara Yuta , Saito Shota , Kamatsuka Akira , Matsushima Toshiyasu
Published: February 2022

The recursive and hierarchical structure of full rooted trees is applicable to statistical models in various fields, such as data compression, image processing, and machine learning. In most of these cases, the full rooted tree is not a random variable; as such, model selection to avoid overfitting is problematic. One method to solve this problem is to assume a prior distribution on the full rooted trees. This enables the optimal model selection based on Bayes decision theory. For example, by assigning a low prior probability to a complex model, the maximum a posteriori estimator prevents the selection of the complex one. Furthermore, we can average all the models weighted by their posteriors. In this paper, we propose a probability distribution on a set of full rooted trees. Its parametric representation is suitable for calculating the properties of our distribution using recursive functions, such as the mode, expectation, and posterior distribution. Although such distributions have been proposed in previous studies, they are only applicable to specific applications. Therefore, we extract their mathematically essential components and derive new generalized methods to calculate the expectation, posterior distribution, etc.
An Improved Multi-Objective Cuckoo Search Approach by Exploring the Balance between Development and Exploration
Authors: Ye Shao-Qiang , Zhou Kai-Qing , Zhang Cheng-Xu , Mohd Zain Azlan , Ou Yun
Published: February 2022

In recent years, multi-objective cuckoo search (MOCS) has been widely used to settle the multi-objective (MOP) optimization issue. However, some drawbacks still exist that hinder the further development of the MOCS, such as lower convergence accuracy and weaker efficiency. An improved MOCS (IMOCS) is proposed in this manuscript by investigating the balance between development and exploration to obtain more accurate solutions while solving the MOP. The main contributions of the IMOCS could be separated into two aspects. Firstly, a dynamic adjustment is utilized to enhance the efficiency of searching non-dominated solutions in different periods utilizing the Levy flight. Secondly, a reconstructed local dynamic search mechanism and disturbance strategy are employed to strengthen the accuracy while searching non-dominated solutions and to prevent local stagnation when solving complex problems. Two experiments are implemented from different aspects to verify the performance of the IMOCS. Firstly, seven different multi-objective problems are optimized using three typical approaches, and some statistical methods are used to analyze the experimental results. Secondly, the IMOCS is applied to the obstacle avoidance problem of multiple unmanned aerial vehicles (UAVs), for seeking a safe route through optimizing the coordinated formation control of UAVs to ensure the horizontal airspeed, yaw angle, altitude, and altitude rate are converged to the expected level within a given time. The experimental results illustrate that the IMOCS can make the multiple UAVs converge in a shorter time than other comparison algorithms. The above two experimental results indicate that the proposed IMOCS is superior to other algorithms in convergence and diversity.
A 12-Bit, 100 MS/s SAR ADC Based on a Bridge Capacitor Array with Redundancy and Non-Linearity Calibration in 28 nm CMOS
Authors: Zheng Yan , Ye Fan , Ren Junyan
Published: February 2022

This paper presents a 12-bit, 100 MS/s successive approximation register (SAR) analog-to-digital converter (ADC) based on a bridge capacitor array with redundancy and non-linearity calibration. The differential non-linearity calibration method was proposed to compensate for the linearity, which is degraded by the parasitic capacitance of the bridge capacitor. To reduce the power dissipation and alleviate the settling error of the DAC capacitor array, a hybrid redundant scheme was proposed. A low-power, high-performance SAR ADC was implemented based on the proposed techniques. This SAR ADC prototype was implemented in 28 nm CMOS technology. Measurement results showed that the proposed SAR ADC could achieve a (signal-to-noise distortion ratio) SNDR of 61.46 dB and 58.82 dB at low and Nyquist input frequencies, respectively, resulting in figure of merits (FOMs) of 8.69 fJ/conversion and 11.8 fJ/conversion step, respectively. The SAR ADC core occupied an active area 0.0227 mm2.
From Biological Synapses to “Intelligent” Robots
Authors: Dresp-Langley Birgitta
Published: February 2022

This selective review explores biologically inspired learning as a model for intelligent robot control and sensing technology on the basis of specific examples. Hebbian synaptic learning is discussed as a functionally relevant model for machine learning and intelligence, as explained on the basis of examples from the highly plastic biological neural networks of invertebrates and vertebrates. Its potential for adaptive learning and control without supervision, the generation of functional complexity, and control architectures based on self-organization is brought forward. Learning without prior knowledge based on excitatory and inhibitory neural mechanisms accounts for the process through which survival-relevant or task-relevant representations are either reinforced or suppressed. The basic mechanisms of unsupervised biological learning drive synaptic plasticity and adaptation for behavioral success in living brains with different levels of complexity. The insights collected here point toward the Hebbian model as a choice solution for “intelligent” robotics and sensor systems.
CAN-Based Vibration Control for Networked Vehicle Active Suspension with Both Network-Induced Delays and Packet-Dropouts
Authors: Han Shi-Yuan , Liang Tong , Zhou Jin , Chen Yue-Hui
Published: February 2022

Ride comfort and driving safety are highly vulnerable to the undesirable excessive vibrations caused by road surface irregularities and the imperfect in-vehicle network (IVN). The main contribution of this paper consists of proposing a near-optimal vibration control approach for networked vehicle active suspension under irregular road excitations in a discrete-time domain, in which the uncertain time delay and packet dropout in CAN are taken into consideration. More specially, by virtue of two buffers of the sensor-to-controller network channel and the controller-to-actuator network channel in CAN, by introducing a designed state-transformation-based method, the original vibration control problem under the constraints of the irregular road excitations and imperfect CAN is transformed into a two-point boundary value (TPBV) problem without advanced and delayed items. After that, the near-optimal vibration control approach is presented to isolate the vehicle body from the road excitations and compensate the time delay and packet dropout from CAN synchronously. The stability condition of the networked vehicle active suspension under the proposed vibration controller is obtained based on the Lyapunov function. In numerous scenarios with different road roughnesses and network-induced time delays and packet dropouts, the simulation results illustrate the effectiveness and superiority of the proposed near-optimal vibration controller.
A Novel Fragile Zero-Watermarking Algorithm for Digital Medical Images
Authors: Ali Zulfiqar , Fazal-e-Amin  , Hussain Muhammad
Published: February 2022

The wireless transmission of patients’ particulars and medical data to a specialised centre after an initial screening at a remote health facility may cause potential threats to patients’ data privacy and integrity. Although watermarking can be used to rectify such risks, it should not degrade the medical data, because any change in the data characteristics may lead to a false diagnosis. Hence, zero watermarking can be helpful in these circumstances. At the same time, the transmitted data must create a warning in case of tampering or a malicious attack. Thus, watermarking should be fragile in nature. Consequently, a novel hybrid approach using fragile zero watermarking is proposed in this study. Visual cryptography and chaotic randomness are major components of the proposed algorithm to avoid any breach of information through an illegitimate attempt. The proposed algorithm is evaluated using two datasets: the Digital Database for Screening Mammography and the Mini Mammographic Image Analysis Society database. In addition, a breast cancer detection system using a convolutional neural network is implemented to analyse the diagnosis in case of a malicious attack and after watermark insertion. The experimental results indicate that the proposed algorithm is reliable for privacy protection and data authentication.
An Efficient Adaptive Fuzzy Hierarchical Sliding Mode Control Strategy for 6 Degrees of Freedom Overhead Crane
Authors: Pham Hung Van , Hoang Quoc-Dong , Pham Minh Van , Do Dung Manh , Phi Nha Hoang , Hoang Duy , Le Hai Xuan , Kim Thai Dinh , Nguyen Linh
Published: February 2022

The paper proposes a new approach to efficiently control a three-dimensional overhead crane with 6 degrees of freedom (DoF). Most of the works proposing a control law for a gantry crane assume that it has five output variables, including three positions of the trolley, bridge, and pulley and two swing angles of the hoisting cable. In fact, the elasticity of the hoisting cable, which causes oscillation in the cable direction, is not fully incorporated into the model yet. Therefore, our work considers that six under-actuated outputs exist in a crane system. To design an efficient controller for the 6 DoF crane, it first employs the hierarchical sliding mode control approach, which not only guarantees stability but also minimizes the sway and oscillation of the overhead crane when it transports a payload to a desired location. Moreover, the unknown and uncertain parameters of the system caused by its actuator nonlinearity and external disturbances are adaptively estimated and inferred by utilizing the fuzzy inference rule mechanism, which results in efficient operations of the crane in real time. More importantly, stabilization of the crane controlled by the proposed algorithm is theoretically proved by the use of the Lyapunov function. The proposed control approach was implemented in a synthetic environment for the extensive evaluation, where the obtained results demonstrate its effectiveness.
A Gradually Linearizing Kalman Filter Bank Designing for Product-Type Strong Nonlinear Systems
Authors: Wen Chenglin , Lin Zhipeng
Published: February 2022

Our study aimed to improve the poor performance of existing filters, such as EKF, UKF and CKF, that results from their weak approximation ability to nonlinear systems. This paper proposes a new extended Kalman filter bank focusing on a class of product-type strong nonlinear systems composed by system state variables, time-varying parameters and non-linear basic functions. Firstly, the non-linear basic functions are defined as hidden variables corresponding to system state variables, and then the strong nonlinear systems are described simplistically. Secondly, we discuss building two dynamic models between their future values of parameters, as well as hidden variables and their current values based on the given prior information. Thirdly, we recount how an extended Kalman filter bank was designed by gradually linearizing the strong nonlinear systems about system state variables, time-varying parameters and hidden variables, respectively. The first extended Kalman filter about future hidden variables was designed by using these estimates of the state variables and parameters, as well as hidden variables at current. The second extended Kalman filter about future parameters variables was designed by using these estimates of the current state variables and parameters, as well as future hidden variables. The third extended Kalman filter about future state variables was designed by using these estimates of the current state variables, as well as future parameters and hidden variables. Fourthly, we used digital simulation experiments to verify the effectiveness of this method.
Revolution in Flexible Wearable Electronics for Temperature and Pressure Monitoring—A Review
Authors: Butt Muhammad A. , Kazanskiy Nikolay L. , Khonina Svetlana N.
Published: February 2022

In the last few decades, technology innovation has had a huge influence on our lives and well-being. Various factors of observing our physiological characteristics are taken into account. Wearable sensing tools are one of the most imperative sectors that are now trending and are expected to grow significantly in the coming days. Externally utilized tools connected to any human to assess physiological characteristics of interest are known as wearable sensors. Wearable sensors range in size from tiny to large tools that are physically affixed to the user and operate on wired or wireless terms. With increasing technological capabilities and a greater grasp of current research procedures, the usage of wearable sensors has a brighter future. In this review paper, the recent developments of two important types of wearable electronics apparatuses have been discussed for temperature and pressure sensing (Psensing) applications. Temperature sensing (Tsensing) is one of the most important physiological factors for determining human body temperature, with a focus on patients with long-term chronic conditions, normally healthy, unconscious, and injured patients receiving surgical treatment, as well as the health of medical personnel. Flexile Psensing devices are classified into three categories established on their transduction mechanisms: piezoresistive, capacitive, and piezoelectric. Many efforts have been made to enhance the characteristics of the flexible Psensing devices established on these mechanisms.
An IoT-Aware Smart System Exploiting the Electromagnetic Behavior of UHF-RFID Tags to Improve Worker Safety in Outdoor Environments
Authors: Montanaro Teodoro , Sergi Ilaria , Motroni Andrea , Buffi Alice , Nepa Paolo , Pirozzi Marco , Catarinucci Luca , Colella Riccardo , Chietera Francesco Paolo , Patrono Luigi
Published: February 2022

Recently, different solutions leveraging Internet of Things (IoT) technologies have been adopted to avoid accidents in agricultural working environments. As an example, heavy vehicles, e.g., tractors or excavators, have been upgraded with remote controls. Nonetheless, the community continues to encourage discussions on safety issues. In this framework, a localization system installed on remote-controlled farm machines (RCFM) can help in preventing fatal accidents and reduce collision risks. This paper presents an innovative system that exploits passive UHF-RFID technology supported by commercial BLE Beacons for monitoring and preventing accidents that may occur when ground-workers in RCFM collaborate in outdoor agricultural working areas. To this aim, a modular architecture is proposed to locate workers, obstacles and machines and guarantees the security of RCFM movements by using specific notifications for ground-workers prompt interventions. Its main characteristics are presented with its main positioning features based on passive UHF-RFID technology. An experimental campaign discusses its performance and determines the best configuration of the UHF-RFID tags installed on workers and obstacles. Finally, system validation demonstrates the reliability of the main components and the usefulness of the proposed architecture for worker safety.
Formulations, Solving Algorithms, Existing Problems and Future Challenges of Pre-Programmed PWM Techniques for High-Power AFE Converters: A Comprehensive Review
Authors: Jing Tao , Maklakov Alexander , Radionov Andrey , Gasiyarov Vadim , Liang Yuehua
Published: February 2022

Considering the development of the hybrid wind and solar photovoltaic generation and smart grid, Active Front-End (AFE) converters for high-power applications are facing significant opportunities and challenges related to power quality and efficiency. The Pre-programmed Pulse-Width Modulation (PPWM) techniques can strictly control the harmonic spectrum of a specified voltage or current waveform generated by a high-power AFE converters, and have been extensively applied to reduce or even eliminate the harmonic distortion with low switching losses for high-power converters in order to deal with these issues aforementioned. For the PPWM techniques with low switching frequency, Selective Harmonic Elimination (SHE) and Selective Harmonic Mitigation (SHM) have been the prevailing solutions and gain widespread popularity, among which SHM can provide further control of the harmonic spectrum in cases of similar switching losses to SHE. Over the past several decades, the applications of SHE and SHM have been extended to high-power AFE converters. Thus, the aim of this study is to provide a comprehensive literature review regarding their various formulations, solving algorithms, and existing problems to high-power AFE converters. In addition, the suggestions for future applications of PPWM in high-power AFE converters are also discussed.
Analyzing Europe’s Biggest Offshore Wind Farms: A Data Set with 40 Years of Hourly Wind Speeds and Electricity Production
Authors: Grothe Oliver , Kächele Fabian , Watermeyer Mira
Published: February 2022

We provide an open, available, and ready-to-use data set covering 40 years of hourly wind speeds and synthetic hourly production signals for the 29 biggest offshore wind farms in Europe. It enables researchers and industry experts to include realistic offshore time series into their analyses. In particular, we provide data from 1980 to 2019 for wind farms already in operation and those that will be in operation by 2024. We document in detail how the data set was generated from publicly available sources and provide manually collected details on the wind farms, such as the turbine power curves. Correspondingly, the users can easily keep the data set up to date and add further wind farm locations as needed. We give a descriptive analysis of the data and its correlation structure and find a relatively high volatility and intermittency for single locations, with balancing effects across wind farms.
Plasma Scenarios for the DTT Tokamak with Optimized Poloidal Field Coil Current Waveforms
Authors: Castaldo Antonio , Albanese Raffaele , Ambrosino Roberto , Crisanti Flavio
Published: February 2022

In the field of nuclear fusion, the power exhaust problem is still an open issue and represents one of the biggest problems for the realization of a commercial fusion power plant. According to the “European Fusion Roadmap”, a dedicated facility able to investigate possible solutions to heat exhaust is mandatory. For this purpose, the mission of the Divertor Tokamak Test (DTT) tokamak is the study of different solutions for the divertor. This paper presents the plasma scenarios for standard and alternative configurations in DTT. The Single Null scenario is described in detail. The alternative configurations are also presented, showing the good flexibility of the machine.
Temperature Variation Law of Core Tube Wall during Coring in Different Strength Coal Seams: Experiment and Modelling
Authors: Wang Qiao , Wang Zhaofeng , Yue Jiwei , An Fenghua , Dong Jiaxin , Sun Yongxin
Published: February 2022

Temperature is the primary factor affecting the law of coal gas desorption. When the core method is used to measure the coal seam gas content (CSGS), the temperature of the coal core sample (CCS) will increase. The heat generated by the core bit cutting and rubbing the coal during coring is transferred to the CCS through the core tube, resulting in the temperature rising of the CCS. Because the CCS entering the core tube during coring is a dynamic process, the temperature of CCS is difficult to measure. To solve this problem, the temperatures of the core tube wall during coring in the Jiulishan coal mine (JLS), Guhanshan coal mine (GHS) and Zhaogu coal mine (ZG) at the core depth of 20 m were measured by the self-designed temperature measuring device. The thermodynamic models of the core bit and the core tube during coring were established. The reliability of the model was verified by comparing the numerical simulation results with the field measurement results. The verified model was used to predict the temperature changes of the core tube wall during coring in different strength coal seams and different core depths. The results show that the temperature change of the core tube wall was divided into a slowly temperature rising stage Ⅰ, a fast temperature rising stage Ⅱ and a slowly temperature rising and slowly temperature falling stage Ⅲ, which correspond to the process of pushing the core tube, drilling the CCS and early stage and later stage of withdrawing the core tube, respectively. The maximum temperature of the core tube wall appears in the first 3 min of withdrawing the core tube, and increases with the core depth increasing. The temperature of the measuring point at the end of drilling the CCS and the maximum temperature during coring linearly increase with the core depth. The temperature heating rate of the core tube is negatively linear, with the coal seam strength during pushing the core tube wall process. However, the temperature heating rate of the core tube wall is positively linear with the coal seam strength during drilling the CCS process. This study can provide a basis for further research on the dynamic distribution characteristics of temperature in the CCS during coring, which is of profound significance to calculate the gas loss amount and CSGC.
An Improved Sliding Mode Control with Integral Surface for a Modular Multilevel Power Converter
Authors: Luo Bo-Yu , Subroto Ramadhani Kurniawan , Wang Chang-Zhi , Lian Kuo-Lung
Published: February 2022

This paper presents a novel method for current control for a modular multilevel converter (MMC). The proposed current control methodology is based on a modified sliding mode control (SMC) with proportional and integral (PI) sliding surface which allows fast transient responses and improves the robustness of the MMC control performance. As the proposed method is derived via Lyapunov direct method, the closed-loop stability is ensured and results in globally asymptotically stable. Furthermore, the reaching time is also guaranteed by the proposed method, leading to fast transient responses. The proposed method is validated by comparing with some existing methods, which are proportional integral controller and conventional SMC, via offline and hardware-in-loop (HIL) simulations where a 10 MW, medium-voltage MMC system is tested. According to these results, the proposed method is able to provide fast transient responses, zero overshoot, and robustness to the weak grid and short-circuit conditions.
A Type-2 Fuzzy Controller for Floating Tension-Leg Platforms in Wind Turbines
Authors: Firouzi Behnam , Alattas Khalid A. , Bakouri Mohsen , Alanazi Abdullah K. , Mohammadzadeh Ardashir , Mobayen Saleh , Fekih Afef
Published: February 2022

This paper proposes a type-2 fuzzy controller for floating tension-leg platforms in wind turbines. Its main objective is to stabilize and control offshore floating wind turbines exposed to oscillating motions. The proposed approach assumes that the dynamics of all units are completely unknown. The latter are approximated using the proposed Sugeno-based type-2 fuzzy approach. A nonlinear Kalman-based algorithm is developed for parameter optimization, and linear matrix inequalities are derived to analyze the system’s stability. For the fuzzy system, both rules and membership functions are optimized. Additionally, in the designed approach, the estimation error of the type-2 fuzzy approach is also considered in the stability analysis. The effectiveness and performance of the proposed approach is assessed using a simulation study of a tension leg platform subject to various disturbance modes.
The Effect of J-Groove on Vortex Suppression and Energy Dissipation in a Draft Tube of Francis Turbine
Authors: Luo Zhumei , Nie Cong , Lv Shunli , Guo Tao , Gao Suoming
Published: February 2022

The vortex rope in the draft tube is considered as the major contributor to pressure pulsation at partial load (PL) conditions, which causes the hydro unit to operate unstably. Based on the prototype Francis turbine HLA551-LJ-43 in the laboratory, J-grooves are designed on its conical section in this paper. We used numerical simulation to study the effect of the J-grooves on vortex suppression and energy dissipation in the draft tube. Four typical operating conditions were chosen to analyze the vortex suppression; the corresponding flow ratios Q* are 100%, 82%, 69%, and 53%, respectively. Entropy production theory is used to calculate the energy losses and assess the effect of the J-groove on energy dissipation under part-load conditions. By comparing entropy production, circumferential and axial velocity components, swirl intensity, pressure pulsation, and vortex distribution in a draft tube with and without J-grooves at different operating conditions, it can be concluded that the entropy production on the wall containing a conical section with J-grooves is obviously smaller than that without J-grooves, the effects of J-grooves on reducing circumferential velocity component Vu, pressure pulsation, and weakening vortex intensity and vortex rope in the conical section are obvious, especially at part load and deep part-load operating conditions. Using J-grooves shows better performance on vortex control and energy dissipation in the draft tube of a Francis turbine at partial load conditions.
The Estimation of Lightning Impulses Superimposed onto Pre-Stressed DC Breakdown Voltages Using the Leader Propagation Method
Authors: Meer Rashed , Khan Yasin , Wani Nissar Rasool , Al-Arainy Abdulrahman Ali
Published: February 2022

The impulse breakdown attributes are of rudimentary importance in the insulation coordination in the gas-insulated switchgear (GIS). The critical voltage waveshape for the insulation is the surge over voltages. Usually, such over-voltages will emerge on the electrical equipment while these are burdened under DC or AC working voltages. Therefore, during relatively small-time intervals, the undermined devices are exposed to surge voltages that are superimposed upon the already running DC or AC voltages. From a safety point of view, and for providing reliable power to the consumer, we need to study the breakdown characteristics under such over-voltages, with reference to normal operating voltages (DC or AC). The breakdown mechanism of the GIS under compressed SF6 gas is known to be controlled by a stepped leader propagation method. Although different experimental studies have been conducted by many researchers for different experimental conditions under DC, AC, or impulse high voltages alone, not much research has been performed, in a systematic way, to model and estimate the breakdown voltages of the GIS under such superimposed conditions. This paper presents a systematic model, using a leader propagation technique for the estimation of breakdown voltages for complex voltage conditions, i.e., a lightning impulse (LI) superimposed on pre-stressed DC for different experimental conditions. The estimated values are in good agreement with the measured experimental results.
Energy Potential of Biogas Production in Ukraine
Authors: Kucher Oleg , Hutsol Taras , Glowacki Szymon , Andreitseva Iryna , Dibrova Anatolii , Muzychenko Andrii , Szeląg-Sikora Anna , Szparaga Agnieszka , Kocira Sławomir
Published: February 2022

Manufacturing and the further utilization of biogas is an efficient way of complementing or replacing primary energy resources. Ukraine has followed the global tendency to substitute fossil energy sources with renewable ones, which particularly includes biogas. Considering the experience of European countries, as well as the potential and needs of Ukraine, the necessity of biogas plant building implies three main factors: obtaining the energy sources, selling agricultural products and by-products of biogas production, and managing the environmental issues surrounding biogas generation. The growth dynamics of biogas plants and their productivity were analyzed for the period of 2012–2019. In doing so, the capacity and potential capabilities of biogas production in Ukraine by means of biological waste and agricultural raw materials were assessed. The article focuses on the importance of resolving the issues of sanitary and technogenic protection in biogas plant building and biogas manufacturing. It also points out the reasons that prevent Ukraine from going forward with biogas projects, as well as the main factors that affect biogas plant viability and efficiency. Based on the statistical data of previous years and regression analysis, the authors calculated the production output and biogas transformation. Herein, the trend model and Excel software were applied.
The Energy Potential of the Lower Vistula River in the Context of the Adaptation of Polish Inland Waterways to the Standards of Routes of International Importance
Authors: Woś Krzysztof , Wrzosek Krzysztof , Kolerski Tomasz
Published: February 2022

Based on new policies of the European Union, green technologies are to be mostly considered for power generation. Hydropower generation is one of the essential elements of sustainable energy production. Therefore, specific attention, both economically and technically, needs to be given to this sector of energy production. The Vistula River in Poland is considered an international waterway. The power production potential of the river has been taken into account over the years. However, further configurations are needed to obtain a more in-depth ecological knowledge-base and economic plans, which are socially approved. In an attempt to make the project environmentally friendly, specific attention was put into sustainable transport. Different methods of transport were researched to find the most renewable transport combination, mainly based on waterways. Having performed a cost–benefit analysis related to the economic aspects of the project, it was found that such an investment is highly profitable (B/C = 2.81).
Modeling, Simulation and Control of Wind Diesel Power Systems
Authors: Sebastián Rafael
Published: February 2022

Wind diesel power systems (WDPS) are isolated microgrids which combine diesel generators (DGs) with wind turbine generators (WTGs) [...]
Circular Economy Approach on Energy Cogeneration in Petroleum Refining
Authors: Pinto Luiz Fernando Rodrigues , Tucci Henrricco Nieves Pujol , Mummolo Giovanni , Neto Geraldo Cardoso de Oliveira , Facchini Francesco
Published: February 2022

The heat recovery of hot exhaust air in petroleum refining for energy cogeneration is a circular strategy to reduce costs and environmental impact. Despite several articles on this subject, there is a lack of study on the assessment of the economic and environmental advantages of energy cogeneration in petroleum refining. The objective of this research was to evaluate the economic and environmental gains obtained by energy cogeneration from the heat dissipated in the calcination of green petroleum coke. The research method was a case study in a petrochemical industry in Brazil. From an economic point of view, the cogeneration unit project has shown positive results: a discounted payback period of eight years and nine months, net present value (NPV) over a span of a twenty-year period of US$43,825,592, a return on investment (ROI) estimated to be 14%, and an internal rate of return (IRR) of 12%. From an ecological perspective, the produced energy in the cogeneration process reduced 163,992 ton CO2eq per year of greenhouse gas emissions into the atmosphere. This study has increased the knowledge of heat recovery in energy cogeneration in petroleum refining. This work contributes by providing some advantages of heat recovery as a circular economy strategy for business development.
Sensorless Switched Reluctance Machine and Speed Control: A Study to Remove the Position Encoder at High Speed of Operation
Authors: Costa Jonathan Velasco , Branco Paulo J. C.
Published: February 2022

High-speed electrical machines have been of great research interest because of their excellent efficiency and high storage capacity. In the case of switched reluctance machines (SRMs), position feedback is required for effective operation. The installation of this sensor in a high-speed flywheel is difficult and expensive. This paper proposes and analyses a methodology to estimate the position of a SRM and remove the position encoder to apply the machine as a flywheel at 50,000 rpm. The machine is modeled with non-linear characteristics, and is simulated under single-pulse operation due to the high-speed. Two configurations of the sensorless method are presented: Robust Method and Sequential Method. The robust configuration identifies the firing angles position only, while the sequential setup can track any position. Both configurations present advantages and disadvantages in relation to the error of estimation and to the number of estimations. The methods are tested in closed-loop speed control. In the two cases, the position estimation supports satisfactory results for simulating operation of the machine at high speed.
Bioresource Technology for Bioenergy: Development and Trends
Authors: Bennamoun Lyes
Published: February 2022

In 2020, the World Bioenergy Association published an interesting report about the global development of using biomass and bioenergy along with statistics and trends [...]
A Comparison between Analog Ensemble and Convolutional Neural Network Empirical-Statistical Downscaling Techniques for Reconstructing High-Resolution Near-Surface Wind
Authors: Rozoff Christopher M. , Alessandrini Stefano
Published: February 2022

Empirical-statistical downscaling (ESD) can be a computationally advantageous alternative to dynamical downscaling in representing a high-resolution regional climate. Two distinct strategies of ESD are employed here to reconstruct near-surface winds in a region of rugged terrain. ESD is used to reconstruct the innermost grid of a multiply nested mesoscale model framework for regional climate downscaling. An analog ensemble (AnEn) and a convolutional neural network (CNN) are compared in their ability to represent near-surface winds in the innermost grid in lieu of dynamical downscaling. Downscaling for a 30 year climatology of 10 m April winds is performed for southern MO, USA. Five years of training suffices for producing low mean absolute error and bias for both ESD techniques. However, root-mean-squared error is not significantly reduced by either scheme. In the case of the AnEn, this is due to a minority of cases not producing a satisfactory representation of high-resolution wind, accentuating the root-mean-squared error in spite of a small mean absolute error. Homogeneous comparison shows that the AnEn produces smaller errors than the CNN. Though further tuning may improve results, the ESD techniques considered here show that they can produce a reliable, computationally inexpensive method for reconstructing high-resolution 10 m winds over complex terrain.
Power Hardware-In-the-Loop Approach for Autonomous Power Generation System Analysis
Authors: Racewicz Szymon , Kutt Filip , Sienkiewicz Łukasz
Published: February 2022

The article presents the Power Hardware-In-the-Loop (PHIL) dynamic model of a synchronous generator of 125 kVA for autonomous power generation system analysis. This type of system is typically composed of electrical energy sources in the form of several diesel generator units with synchronous machines, the main distribution switchboard and different loads. In modern power distribution systems, the proposed power management strategies are typically aimed at the minimization of fuel consumption by maintaining the operation of diesel generator units at peak efficiency. In order to design and test such a system in conditions as close as possible to the real operating conditions, without constructing an actual power distribution system, a PHIL model in the form of a power inverter that emulates the behaviour of a real synchronous generator is proposed. The PHIL model was prepared in the MATLAB/Simulink environment, compiled to the C language and fed into a 150 kVA bidirectional DC/AC commercial-grade converter driven by a HIL real-time simulation control unit. Experimental research was performed in the LINTE2 laboratory of the Gdańsk University of Technology (Poland), where the PHIL emulator was developed. The proposed model was validated by comparing the output voltages and currents as well as an excitation current with the measurements performed on the 125 kVA synchronous generator. The obtained results proved satisfactory compliance of the PHIL model with its real counterpart.
Research on Multi-Objective Compound Energy Management Strategy Based on Fuzzy Control for FCHEV
Authors: Lin Cuixia , Luo Wenguang , Lan Hongli , Hu Cong
Published: February 2022

A compound energy management strategy is proposed to improve the fuel cell’s durability and the economy of fuel cell hybrid electric vehicles (FCHEV). A control strategy that combines fuzzy control and switching control is proposed, taking into account factors that affect the fuel cell’s durability and the supercapacitor park’s safety. To smooth the output power of fuel cells under frequent variable load conditions, a moving average filtering algorithm has been added. Finally, co-simulation using Advisor and Matlab/Simulink under the World Light Vehicle Test Cycle (WLTC) compares the proposed strategy with fuzzy control and power following strategies. The experimental results show that the proposed strategy ensures the safety of the supercapacitor park and improves the durability of the fuel cell while improving the economy of the whole vehicle.
Research on Straw-Based High-Quality Energy in China under the Background of Carbon Neutrality
Authors: Ren Ji-Qin , Yang Ya-Wen , Chi Yuan-Ying
Published: February 2022

It is imperative to use clean energy in order to achieve “carbon neutrality” and “carbon peaking”. This research aims to explore the impact of the agricultural mechanization level, the rural infrastructure construction level, and the rural economic development level on the utilization of high-quality straw energy, and, resultingly, this study aims to help provide suggestions for promoting high-quality straw energy utilization, develop the potential of high-quality straw energy, and alleviate China’s energy shortage problem. This paper develops a measurement model using the ridge regression model with panel fixed effects, which overcomes the multi-collinearity problem among the various factors influencing the utilization of high-quality energy from straw. Panel data from 24 provinces and cities, from 2009 to 2017, are used. The results show that the improvements of the agricultural mechanization level, the rural infrastructure construction level, and the rural economic development level all promote the use of high-quality straw energy. Moreover, the level of rural economic development plays a mediating role in the agricultural mechanization level and the rural infrastructure construction level pertaining to straw-based high-quality energy. Policy implications can be easy to derive based on our findings, and these include strengthening governmental investment in agricultural machinery in rural areas, paying more attention to areas with backward rural energy infrastructure construction, ensuring the steady improvement of economic development in rural areas, providing the necessary economic foundation for agricultural supply, and promoting the use of high-quality energy from straw.
Artificial Neural Network and Regression Models for Predicting Intrusion of Non-Reacting Gases into Production Pipelines
Authors: Chala Girma Tadesse , Negash Berihun Mamo
Published: February 2022

Wax deposition and gelation of waxy crude oil in production pipelines are detrimental to crude oil transportation from offshore fields. A waxy crude oil forms intra-gel voids in pipelines under cooling mode, particularly below the pour point temperature. Consequently, intrusion of non-reacting gas into production pipelines has become a promising method to lessen the restart pressure required and clear the clogged gel. A trial-and-error method is currently employed to determine the required restart pressure and restart time in response to injected gas volume. However, this method is not always accurate and requires expert knowledge. In this study, predictive models based on an Artificial Neural Network (ANN) and multilinear regression are developed to predict restart pressure and time as a function of seabed temperature and non-reacting gas injected volume. The models’ outcomes are compared against experimental results available from the literature. The empirical models predicted the response variables with an absolute error of below 5% compared to the experimental studies. Thus, such models would allow accurate estimation of restart pressure, thereby improving transportation efficiency in offshore fields.
A Two-Stage Decision-Making Method Based on WebGIS for Bulk Material Transportation of Hydropower Construction
Authors: Wang Hao , Liu Quan , Zhang Hongyang , Jin Yinlong , Yu Wenzhen
Published: February 2022

Bulk materials are necessary for hydropower construction. The bulk materials transportation (BMT) scheme is a guiding document for material supply, and its selection has a significant influence on hydropower construction. Since the BMT problem includes transportation planning and scheme selection issues simultaneously, only a small number of studies have focused on it. This paper presents a theoretical two-stage decision-making method (TDM), which innovatively combines the path optimization method and the multi-criteria decision-making (MCDM) method to solve the BMT problem. In the first stage, a multi-source path optimization model is established to optimize the transportation network and obtain a set of alternatives from each supply point to the construction site. In the second stage, considering the factors of economy, risk and construction progress, the MCDM method is adopted to select the optimal scheme from the alternatives. In addition, web crawler technology is used to obtain the transportation network data from the public WebGIS automatically. Case results show that the TDM can effectively solve this problem, and its result keeps consistent with engineering practice; with the help of the web crawler, it can reduce the design task time from months to days. Therefore, the TDM based on WebGIS can benefit hydropower construction design efficiency.
Social Media Engagement in Shaping Green Energy Business Models
Authors: Czarnecka Marzena , Kinelski Grzegorz , Stefańska Magdalena , Grzesiak Mateusz , Budka Borys
Published: February 2022

Recent years have seen an increase in the role of social media in the communication of energy sector companies (ESCs) with consumers. Currently, consumers look for information, create it themselves, and share it with other Internet users. eWOM communication means that energy companies, firstly, must be present in social media so that consumers can get to know them better, and secondly, they must consciously shape their image according to the expectations of their customers. One-way communication, such as customer satisfaction measurements, is no longer enough to know their preferences. Market trends indicate that for current buyers—both consumer and non-consumer products—the image of a “green product” or a “green company” is expected. Only a few companies report that they are harmful for environment. All companies report that they are generally community friendly. The consumer would like to know, in particular, about the harmfulness to the environment. Thus, there is a knowledge gap that the companies are not filling. In addition to the advertised satisfaction indicators, you can also test customers’ perceptions of environmental responsibility. That is, the research and results in the area of social responsibility must also be accompanied by environmental responsibility. Therefore, the article aims to indicate whether the level of consumer engagement in social media affects the perception of the green energy business model and how the attitude and pro-environmental behavior of social media users affects this perception. The paper also identifies factors related to social media that influence the perception of ESCs.
Enhanced Seismic Protection System for an Emergency Diesel Generator Unit
Authors: Bustamante Ricardo , Mosqueda Gilberto , Kim Minkyu
Published: February 2022

Nuclear power plants are required to maintain operation after an earthquake, leading to a safe shutdown if necessary. In the case of a loss of offsite power, the onsite emergency diesel generator is critical to ensure procedural operations of the nuclear power plant. As a means to reduce the overall seismic risk, a three-dimensional seismic protection system is proposed to enhance the seismic performance of the emergency diesel generator. The proposed seismic isolation system decouples the horizontal and vertical components of shaking and considers available hardware to achieve an effective isolation solution over the range of excitation frequencies considered. Numerical analysis of the proposed system demonstrates a reduction in seismic demands on the emergency diesel generator and provides a higher safety margin than conventional base installation procedures. Umbilical lines that cross the isolation plane are considered and impose additional constraints on the displacement capacity of the isolation system. However, increasing the displacement capacity of these components can significantly increase the safety margin against failure. The seismic protection system can be customized depending on the seismic hazard and application to different seismic regions.