bluuebunny/crossref_metadata_2025_split huggingface dataset:
Modelling and control of district heating networks with reduced pump utilisation
Authors: Bastida Hector , Ugalde‐Loo Carlos E. , Abyesekera Muditha , Qadrdan Meysam 
Published: January 2021

AbstractDistrict heating systems (DHS) provide thermal energy to a range of consumers. Hence, an adequate sizing of the key elements involved in the energy supply system and their management are critical. Pumps and valves are essential components of a DHS as they ensure hydraulic operating conditions are met for the energy distribution process. To achieve this, a hydraulic system is typically controlled by defining a differential pressure set‐point at a critical location in the network. However, a good understanding of the dynamic behaviour of the hydraulic system during the diverse operating conditions is required for its efficient control and to maximise its performance. This paper presents a control strategy based on suitable dynamic models of the hydraulic system. These non‐linear models enable the simulation of the behaviour of mass flow rate, pressure drops in pipes, power consumption of the pump and the heat delivery to meet the thermal loads. Control system design is carried out in MATLAB, and the designed controller is verified with Apros—a commercial process simulation software. It is shown that the hydraulic behaviour of a DHS is well described by the dynamic models presented. In addition, the designed control scheme reduces the electricity consumption of pumps compared with a conventional mass flow rate controller based on a look‐up table and a differential pressure valve.
Two‐dimensional analytical model for double field excitation synchronous machines
Authors: Hosseinpour Alireza , Mardaneh Mohammad , Rahideh Akbar 
Published: January 2021

AbstractThis paper examines a two‐dimensional analytical magnetic model presented for double excitation synchronous machines (DESMs). DESMs employ both permanent magnets (PMs) and excitation coils (ECs), and therefore they offer the advantages of permanent magnet synchronous machines and electrically excited synchronous machines. Due to the linearity assumptions, the problem is divided in three sub‐problems: magnetic field of the PMs, magnetic field of the ECs, and magnetic field of the armature reaction. ECs, which have non‐overlapping structure, are in the rotor slots and carrying DC currents. The armature reaction field prediction is presented for both overlapping and non‐overlapping windings. The magnetic flux density of a brushless PM motor with six stator slots and four rotor slots has been calculated by the proposed analytical method. The results of the analytical method are compared with those of the finite element method to evaluate the effectiveness of proposed model. The presented model can be used for machines with any radius independent magnetization pattern PM and here radial, parallel and multi‐segment Halbach magnetization patterns are used as examples. Moreover, results are validated by numerical method.
UDA‐Net: Densely attention network for underwater image enhancement
Authors: Li Yang , Chen Rong 
Published: January 2021

AbstractUnderwater imaging usually suffers from negative impacts due to the absorption and scattering effects in water. Underwater images thus have unfavourable visual quality to support the work in such environment. This paper addresses the problem of image improvement for single underwater image. The core idea lies in a new enhancement model based on deep learning architecture, in which a feature‐level attention model is developed. This model is a multi‐scale grid convolutional neural network that can facilitate fusing different types of information during representation learning. According to this information combination, a synergistic pooling mechanism is proposed to extract the channel‐wise attention maps to derive the locally weighted features. Therefore, this model can adaptively focus on the feature regions corresponding to degraded patches in one underwater image and improve these patches consistently. Comprehensive experiments are conducted on benchmark and natural underwater images, and it can be demonstrated that this model is effective.
Effect of atomic layer deposited ultra‐thin SiO2 layer on vapour‐liquid‐solid (VLS) grown high dielectric TiO2 film for Si‐based MOS device applications
Authors: Lodh Soham , Chakraborty Rajib , Das Anindita 
Published: January 2021

AbstractTitanium dioxide (TiO2) ultra‐thin films (≈13 nm) are grown on p‐type Si substrate <400> with and without atomic layer deposited SiO2 (5 nm) passivation layer by employing vapour‐liquid‐solid technique. Scanning electron microscope images reveal high quality film for both the samples. The formation of a crystalline TiO2 film is confirmed by X‐ray diffraction pattern, the orthorhombic (brookite) TiO2 films with [130], [160] and [212] planes are seen from peaks at 2θ= 33.5°, 61.7° and 75.7° on SiO2/Si and Si substrates, respectively. Current–voltage (I–V) characteristics reveal leakage current of ≈8.61 × 10‐8 and ≈4.05 × 10‐6 A/cm2 at +2 V for film with and without SiO2 passivation layer, respectively. Leakage current of TiO2/SiO2/Si device follows Fowler–Nordheim (FN) tunnelling at low field and Poole–Frenkel (PF) tunnelling at high field, whereas TiO2/Si device follows Schottky emission at low field and PF tunnelling at high field. Capacitance–voltage (C–V) characteristics reveal superior quality TiO2 films with high dielectric constant of 44.5 and 35.8 for TiO2/SiO2/Si and TiO2/Si samples, respectively. Significant improvement in frequency dispersion and hysteresis voltage is observed for the sample with SiO2 passivation layer. Introduction of SiO2 passivation layer also improves interface traps and reliability of the device. Hence, a low cost novel alternative technique to grow high quality TiO2 film on p‐type Si substrate with SiO2 as passivation layer is suggested for development of high performance MOS devices.
Photonic scheme for implementing quantum square root controlled Z gate using phase and intensity encoding of light
Authors: Mandal Minakshi , Mukhopadhyay Sourangshu 
Published: January 2021

AbstractQuantum logic gate operates on a number of qubits, where a controlled Z gate operates on two qubit data. Similarly, the square root of controlled Z (SRCZ) operates also on two qubit data. The SRCZ gate is very much advantageous in quantum computing. Different quantum gates are implemented by using the physical properties of light such as phase, polarization, intensity, and frequency. Here, the authors propose a photonic scheme for implementing quantum SRCZ logic gate using phase as well as intensity encoding. The non‐linear property of Pockels material with proper external biasing voltage is used to develop the scheme.
All‐optical half adder based on non‐linear triangular lattice photonic crystals with improved contrast ratio
Authors: Saadi Keivan , Kashaninia Alireza , Sabbaghi‐Nadooshan Reza 
Published: January 2021

AbstractAn all‐optical half adder based on two‐dimensional photonic crystals is proposed. The proposed structure is composed of a triangular array of dielectric rods made of non‐linear optical material in air. The structure consists of four waveguides and one ring resonator which are formed by removing a number of dielectric rods. The structure has been simulated and analysed by the plane wave expansion method and the finite‐difference time‐domain method. The size of the proposed structure is small with dimensions of 17 μm × 14.8 μm, and the material of the rods and lattice constant are uniform across the structure. The proposed half adder has a minimum contrast ratio of 13.51 dB in the steady state, with a maximum time delay of 2 ps.
Stability of sliding mode controlled buck converters with unmodelled dynamics of circuit elements and hall sensor
Authors: Wang Yanmin , Niu Ziming , Yang Mingyang , Sun Lanxin , Zhang Weiqi 
Published: January 2021

AbstractThis paper investigates the stability problem of sliding mode controlled buck converters affected by unmodelled dynamics of circuit elements and Hall sensor. The parasitic resistors of all elements are contained in the modelling of buck converters. Different from the traditional sliding mode approach based on the nominal model, the circuit parasitic parameters are directly included in the controller design and stability analysis, which divide the regulation region located in the right half axis into four sub‐ranges. It is more accurate and has no need of extra compensator. For Hall sensor, singular perturbation theory is adopted for modelling and analysing, giving a stable condition concerning its dynamic and static parameters. Finally, the influence of the two types of unmodelled dynamics on the whole closed‐loop system is investigated by constructing an equivalent model, giving a more strict stability condition. Simulations and experiments are presented to illustrate the non‐negligible influence of these unmodelled dynamics.
Optimal switching sequence model predictive control for three‐level NPC grid‐connected inverters
Authors: Lyu Jianguo , Yan Han , Ding Jinyong , Wu Qiuwei , Lyu Xun , Sun Zhuang 
Published: January 2021

AbstractIn order to concentrate the frequency spectrum of the output voltage and improve the quality of grid currents for the three‐level neutral point clamped inverter with the model predictive control, this paper proposes an optimal switching sequence model predictive control algorithm. Based on the increments of grid currents and the neutral‐point voltage, the predictive model of the inverter is established in αβ frame. Moreover, including grid currents and the neutral point voltage tracking, the cost function is designed and simplified by arranging the voltage vector sequence in a sampling cycle appropriately. Meanwhile, the calculation of the optimal dwell time for each voltage vector sequence is derived by Lagrange multiplier method, and its solving process is simplified to reduce online computations. Furthermore, according to different voltage vector sectors, a voltage vector sequence preselection principle is introduced in this paper, besides, considering redundant small vectors in a pair have opposite affections on the neutral point voltage, the amount of voltage vector sequence that needs to be verified is further cut down, for obtaining the optimal voltage vector sequence. Finally, the experimental results show that the proposed method can concentrate the output frequency spectrums, which maintains a good quality of grid currents with a small neutral‐point voltage fluctuation.
Discrete‐time sliding mode control based on disturbance observer applied to current control of permanent magnet synchronous motor
Authors: Smidt Gabbi Thieli , Gründling Hilton Abílio , Padilha Vieira Rodrigo 
Published: January 2021

AbstractThis paper proposes a robust current control technique based on a discrete‐time sliding mode controller and a disturbance observer for high‐performance permanent magnet synchronous motor (PMSM) drives. This scheme is applied in the PMSM current control loops to enable the decoupling between the dq current axes, rejection of disturbances caused by mechanical load changes and robustness under parametric uncertainties. In order to ensure the discrete‐time sliding mode properties, which make the system cross the sliding surface at each sampling period, the PMSM model is extended, including the digital implementation delay resulting from the discrete‐time algorithm execution. The development of this method allows direct implementation in microcontrollers and digital signal processors. Stability and convergence analysis are developed in the discrete‐time domain. Simulation and experimental results demonstrate the effectiveness and good performance of the proposed current control approach.
Harmonic mitigation and power quality improvement in utility grid with solar energy penetration using distribution static compensator
Authors: Mahela Om Prakash , Khan Baseem , Alhelou H. H. , Tanwar Sudeep , Padmanaban Sanjeevikumar 
Published: January 2021

AbstractDistribution static compensator is based on power electronic devices technology which is utilized to supply rapid changes in active power as well as reactive power of utility grids. This is useful to achieve corrections in power factor, balancing of load, compensation of current and filtering of harmonics. Therefore, proposed work investigates the improvement of the power quality by utilizing the distribution static compensator, which is equipped by battery energy storage system and interfaced to distribution network with solar photo voltaic (PV) energy integration. In the present study, distribution static compensator is controlled using a control strategy based on the synchronous reference frame theory. Customised IEEE‐13 nodes test system incorporating solar PV generation and distribution static compensator, is utilized to perform the harmonic mitigation and power quality analysis. Disturbances of power quality and harmonics have been investigated due to abrupt changes in the insolation of solar radiation, outage of PV plant from grid and synchronization of PV plant to grid. MATLAB/Simulink environment is utilized to perform the study. Effectiveness of a developed approach is validated by comparing results of simulation with results extracted in real time using real time digital simulator. Results indicate that the developed method is more effective for harmonic mitigation and improving power quality of electrical power in distribution network integrated with solar PV generation. Performance of the approach is compared with the performance of methods reported in the literature to establish the suitability of the method for harmonics mitigation and power quality improvement in grid with solar energy.
Design and implementation of an improved power‐electronic system for feeding loads of smart homes in remote areas using renewable energy sources
Authors: Zamanzad Ghavidel Behnam , Maalandish Mohammad , Hosseini Seyed Hossein , Sabahi Mehran , Mohammadi‐Ivatloo Behnam 
Published: January 2021

AbstractThis paper suggests an improved step‐up step‐down DC‐DC system along with three‐input and four‐output for smart home applications. In this configuration, two unidirectional power ports have been identified as an Input power supply and one bidirectional power port for the power‐saving element, which can be used as a bidirectional converter for the hybrid vehicle to discharge in a dependent structure. This system can be used to combine renewable energy sources like photovoltaic (PV), fuel cell, battery and hybrid vehicle (HV) to prepare power for remote smart homes. By using this system, serving different loads with different voltage range from high voltage to ultra‐low voltage is possible, also battery charge and discharge with the energy‐saving method can be achieved. In this system, the condition of all possible low‐voltage load and high‐voltage load conditions has been assumed. In this structure, nine power switches have been used, in which all of these switches are in control with independent and dependent duty cycles. By using these cycles, maximum power can be earned from PV sources, bus‐bar voltage regulation, and battery power control is possible too. In this topology, depending on environmental conditions, five scenarios have been identified. To prove the capability of the system before the build, some valid simulations are needed. In this study, the suggested system has been simulated with power system computer aided design/electromagnetic transients including DC (PSCAD/EMTDC).
Natural gas unavailability, price uncertainty, and emission reduction policy in stochastic programming‐based optimal bidding of compressed air energy storage and wind units
Authors: Akbari Ebrahim , Hooshmand Rahmat‐Allah , Gholipour Mehdi , Parastegari Moein 
Published: January 2021

AbstractToday, with growing expansion of renewable energy resources, electricity production is accompanied by uncertainties. The usage and optimal management of energy storage is one of the effective ways to compensate for these uncertainties. Compressed air energy storage (CAES) is one of the two bulk electricity storage methods for power systems, burning natural gas (NG) to extract the stored energy. Therefore, the NG price uncertainty and gas availability along with carbon emission resulting from burning NG can affect optimal bidding result of this unit. Hence, this study addresses the optimal bidding problem of CAES and wind units, considering the aforementioned issues, while taking into account uncertainties of day‐ahead (DA) and balancing market prices, wind speeds, and NG prices and availability. Furthermore, the dynamics of natural gas flow in the pipeline is modelled. The stochastic programming (SP) method is proposed for solving this problem while taking risk into consideration. The scheduling has been presented for participation of generating company in DA and carbon emission markets. Simulation results indicate the capability of the proposed method in optimal bidding of CAES units while taking gas‐burning related constraints into consideration.
Axial flux generator with novel flat wire for direct‐drive wind turbines
Authors: Cakal Gokhan , Keysan Ozan 
Published: January 2021

AbstractWith the increased demand for renewable energy resources, the direct‐drive wind turbine generators have been studied intensely in the last few decades. One megawatt direct‐drive axial flux permanent magnet generator is presented. The novelty in this design is that instead of conventional stranded wires, the windings of the generator are manufactured from a conductor sheet by cutting and bending processes. This creates critical advantages of superior current ratings, ease of manufacturing, and reduced structural mass. An optimization study is conducted with the presented fully analytical model, and the optimum design is compared with the other wind power generators presented in the literature. At the end, a 1 MW, 480 kNm, and 16 tons direct‐driven generator is achieved.
Optimal operation scheduling of a pump hydro storage system coupled with a wind farm
Authors: Graça Gomes João , Telhada João , Xu Huijin , Sá da Costa António , Zhao Changying 
Published: January 2021

AbstractThe variability in non‐dispatchable power generation makes essential the improvement of production management. This study focuses on the development of an optimisation model for a renewable power unit, composed of a wind farm and a hydro‐pump storage power plant, to maximise its revenue. The combination of the two technologies allows the mitigation of risks associated with wind production and electricity price variability. The problem is formulated using linear programming and encompasses the selling of electricity in the Iberian day‐ahead market and through a bilateral contract. The model is tested and scrutinised with sets of real historical generation and price data. In the day‐ahead market scenario, the proposed methodology leads to an average yearly increase of net revenue ranging between 5% and 20%. In the bilateral contract scenario, the coupling of the wind farm and hydropower plant can reduce the imbalances costs substantially. Furthermore, the work identifies a positive correlation between reservoir dimension, turbine capacity and revenue value. The study also detects a revenue reduction tendency related to the decrease in the volatility of electricity prices.
Deep‐learning–based method for faults classification of PV system
Authors: Zaki Sayed A. , Zhu Honglu , Fakih Mohammed Al , Sayed Ahmed Rabee , Yao Jianxi 
Published: January 2021

AbstractThe installation of photovoltaic (PV) system, as a renewable energy source, has significantly increased. Therefore, fast and efficient fault detection and diagnosis technique is highly needed to prevent unpredicted power interruptions. This is obtained in this study in the following steps. First, an efficient meta‐heuristic algorithm is proposed for extracting the optimal five parameters of the PV model in order to assist the MATLAB simulation model. It is used due to its simplicity and high efficiency in building the PV array simulation. Second, a new PV system deep‐learning convolutional neural network (CNN) fault classification method is presented for the advantage of automatic feature extraction, which reduces the computational burden and increases the high classification capability. Finally, for the practical and theoretical validation of the employed CNN model, normal and six fault cases are selected based on different atmospheric conditions. At same time, three electrical indicators are analysed and accordingly chosen as inputs to the proposed classification model. Moreover, the proposed model is compared with other machine‐learning models.
Optimised yaw model for adaptive wind direction characteristic based on a data‐driven approach
Authors: Dong Xinghui , Wang Yizhou , Wang Hui , Kong Lingxing 
Published: January 2021

AbstractThe wind direction characteristics of different wind turbines (WTs) in different wind farms are diverse and some may have obvious differences. The WTs are prone to ‘over‐yaw’ and ‘under‐yaw’ conditions adopting constant yaw threshold and the same control strategy, which reduces the utilisation efficiency of wind energy. This study makes statistics on the variation characteristics of the WT historical wind direction record data, and obtains the maximum probability angle of wind direction change that is used as the control error angle of yaw start (CEAYS). Then, the wind direction value is monitored in real‐time, and the average wind direction change angle in the sliding window is calculated. When the deviation angle is larger than CEAYS, the characteristics of current wind direction are classified based on the clustering of historical wind direction, and a back‐propagation neural network is used to predict the deviation angle of future short‐term wind direction. The adaptive yaw strategy is constructed by CEAYS and deviation angle. The yaw calculation model is analysed and verified with the increase of power extraction and power consumption as the optimisation indexes. The calculation results show that each WT achieved an average 1% increase in power extraction.
Analysis and design of gradient descent based pre‐synchronization control for synchronverter
Authors: R Hariharan , Mishra Mahesh K. 
Published: January 2021

AbstractSynchronverter (SV) control has emerged as a popular method for distributed energy resources (DERs), to emulate response of a synchronous generator. In this work, a simple gradient descent based pre‐synchronization control for SV scheme is proposed that varies the reference frequency in SV control alone. Thus, local load connection to DER can remain intact during synchronization with proposed pre‐synchronization method, unlike virtual current based methods. Normally, phase‐locked loop used for synchronization purpose, uses a first order loop filter such as a PI controller. In the proposed pre‐synchronization control, the inherent low pass filter of SV scheme itself is used as a loop filter. Transient response analysis is presented in this work, based on small signal transfer functions derived from the proposed method. From the theoretical analysis of proposed pre‐synchronisation control, design of the parameters is presented. Thus, there is no trial and error basis for parameters tuning in the proposed method, as compared to virtual current based methods. Validation of proposed pre‐synchronisation control through experiments are presented for all initial conditions. The transient response analysis, effectiveness of proposed method during local load changes and grid integration are verified by experimental results.