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Showing papers in "The Journal of Engineering in 2019"


Journal ArticleDOI
TL;DR: The dynamic model has been developed for the quadcopter and then the controller was designed, tuned, and tested, and the overall performance of the LQR controller was analysed.
Abstract: This paper presents an analysis and performance of a LQR control algorithm for quadrotor helicopters. For a successful analysis, first the dynamic model has been developed for the quadcopter and then the controller was designed, tuned, and tested. In tuning the LQR, much attention was given to the feedback gain matrix (K). The controller's performance was verified in terms of delay time, rise time, overshoot, settling time, and tolerance limits. The overall performance of the LQR controller was analysed.

61 citations


Journal ArticleDOI
TL;DR: In this paper, the magnetic biochar (Fe2O3-EC) derived from water hyacinth was used in the removal of Cu+2 and Zn+2 from aqueous solution.
Abstract: This study evaluates the effectiveness of magnetic biochar (Fe2O3-EC) derived from water hyacinth in the removal of Cu+2 and Zn+2 from aqueous solution. Fe2O3-EC was prepared by chemical coprecipitation of a mixture of FeCl2 and FeCl3 on water hyacinth biomass followed by pyrolysis. The adsorbent was characterized by Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM) coupled with energy dispersive spectroscopy (EDX). Batch adsorption studies on the effects of temperature, biosorbent dosage, contact time, and initial metal ion concentration were carried out. Fe2O3-EC exhibited optimum contact time, biosorbent dosage, and pH values of 65 min, 1.2 g, and 6, respectively. Fe2O3-EC exhibited strong magnetic separation ability and high sorption capability. Metal ion adsorption onto the biochar conformed to the Langmuir isotherm. Kinetic studies revealed that the adsorption process followed pseudo-second-order model. The calculated thermodynamic parameters showed that the adsorption process was feasible and exothermic in nature. These results have demonstrated that the use of Fe2O3-EC in metal ion removal could provide an alternative way to manage and utilize this highly problematic invasive species.

46 citations


Journal ArticleDOI
TL;DR: A unique benchmark to integrate and systematically evaluate advanced functionalities of microgrid and downstream device controllers and a real-time controller hardware-in-the-loop prototyping platform to test the responses of the controllers and verify decision-making algorithms are provided.
Abstract: This article provides a unique benchmark to integrate and systematically evaluate advanced functionalities of microgrid and downstream device controllers. The article describes Banshee, a real-life power distribution network. It also details a real-time controller hardware-in-the-loop (HIL) prototyping platform to test the responses of the controllers and verify decision-making algorithms. The benchmark aims to address power industry needs for a common basis to integrate and evaluate controllers for the overall microgrid, distributed energy resources (DERs), and protective devices. The test platform will accelerate microgrid deployment, enable standard compliance verification, and further develop and test controllers' functionalities. These contributions will facilitate safe and economical demonstrations of the state-of-the-possible while verifying minimal impact to existing electrical infrastructure. All aspects of the benchmark and platform development including models, configuration files, and documentation are publicly available via the electric power HIL controls collaborative (EPHCC).

41 citations


Journal ArticleDOI
TL;DR: The potential of using Fast Frequency Response (FFR) to enhance frequency control in power systems with low inertia is investigated in detail and the design and operation of the EFCC scheme are presented, along with a case study demonstrating its effectiveness in enhancing the frequency control.
Abstract: The increasing penetration of renewable generation has led to the decrease of power systems’ overall inertia, which introduces significant challenges to frequency stability. In this paper, the potential of using Fast Frequency Response (FFR) to enhance frequency control in power systems with low inertia is investigated in detail. A Generic System Frequency Response (GSFR) model taking into account of the penetration level of Non-Synchronous Generation (NSG) and FFR has been developed and used to investigate the impact of reduced inertia on frequency control and demonstrate that the amount of reserve power to be scheduled can be significantly reduced with the deployment of FFR. The impact of the different FFR resources' characteristics (e.g. response delay, ramp rate, etc.) on the effectiveness of frequency control is also investigated, based on which the desirable specifications for FFR schemes are summarised. These desirable properties of FFR schemes are taken into account in the design of a wide-area monitoring and control system termed ‘Enhanced Frequency Control Capability (EFCC)’, which is proposed for the delivery of FFR in the future Great Britain transmission system. The design and operation of the EFCC scheme are presented, along with a case study demonstrating its effectiveness in enhancing the frequency control.

40 citations


Journal ArticleDOI
TL;DR: It is presented that a hybrid AC/DC microgrid is modelled with some renewable energy sources, typical storage facilities, and AC, DC load, and also the power could be transformed smoothly between the AC and DC sub-grids by the bidirectional AC/ DC converter.
Abstract: The hybrid AC/DC microgrid is considered to be the more and more popular in power systems as increasing DC loads. In this study, it is presented that a hybrid AC/DC microgrid is modelled with some renewable energy sources (e.g. solar energy, wind energy), typical storage facilities (e.g. batteries), and AC, DC load, and also the power could be transformed smoothly between the AC and DC sub-grids by the bidirectional AC/DC converter. Meanwhile, coordination control strategies are proposed for power balance under various operations. In grid-connected mode, the U–Q (DC bus voltage and reactive) or PQ method is adopted for the bidirectional AC/DC converter according to the amount of exchange power between AC and DC system in order to improve the DG utilisation efficiency, protecting the converter and maintain the stable operation of the system. In islanded mode, V/F control is applied to stabilising the entire system voltage and frequency, achieving the power balance between the AC and DC systems. Finally, these control strategies are verified by simulation with the results showing that the control scheme would maintain stable operation of the hybrid AC/DC microgrid.

37 citations


Journal ArticleDOI
TL;DR: In this article, the authors explored the impacts of increasing EV penetration levels in a Norwegian distribution grid, by using real power measurements obtained from household smart meters in load flow analyses, and the implications of installing a fast charger in the grid have been assessed, and an optimal location for it is proposed, aiming at minimizing both grid losses and voltage deviations.
Abstract: Norway has implemented economic incentives over several years to encourage a transition from conventional vehicles to electric vehicles (EVs), and now has the largest share of EVs per capita in the world. In this study, the authors explore the impacts of increasing EV penetration levels in a Norwegian distribution grid, by using real power measurements obtained from household smart meters in load flow analyses. The implications of installing a fast charger in the grid have been assessed, and an optimal location for it is proposed, aiming at minimising both grid losses and voltage deviations. Moreover, the potential for reactive power injection to reduce the voltage deviations caused by fast chargers has been investigated. Results show that the EV hosting capacity of the grid is good for a majority of the end-users, but the weakest power cable in the system will be overloaded at a 20% EV penetration level. The network tolerated an EV penetration of 50% with regard to the voltage levels at all end-users. Injecting reactive power at the location of an installed fast charger proved to significantly reduce the largest voltage deviations otherwise imposed by the charger.

35 citations


Journal ArticleDOI
TL;DR: The authors’ results demonstrate that convolutional neural networks have strong ability to distinguish active jamming and thus provide them adequate preparation for anti-jamming process.
Abstract: Radar application in modern warfare becomes more and more rigorous because of the rapidly developed radar countermeasures, especially active jamming in recent years. It costs a radar many resources for anti-jamming in order to detect a target. Hence, it is of great value to recognise the active jamming and thereafter take measures to distinguish target from the numerous jamming. Traditional methods of recognition jamming are blamed for its low efficiency and low accuracy. Radar researchers are looking forward to a new way to do the recognition work. Machine learning has made great advancements in many areas such as image classification, language translation, signal processing and many other recognition tasks, due to its great performance and high accuracy. The authors applied a machine learning method, i.e. convolutional neural networks, to recognise active jamming here. The authors’ results demonstrate that convolutional neural networks have strong ability to distinguish active jamming and thus provide them adequate preparation for anti-jamming process.

31 citations


Journal ArticleDOI
TL;DR: In this article, a review of the use of additive manufacturing for acoustic panels made of agricultural waste is presented. But the authors do not discuss the use and performance of natural fibers as reinforcement in terms of mechanical properties.
Abstract: Natural fibers and their composites are being widely used in almost all the applications in this modern era. However, the properties of natural fibers have to be enhanced in order to compete with synthetic fibers. This review paper opens up additive manufacturing, as a novel method for developing an acoustic panel using natural fiber composites with enhanced mechanical and acoustical properties. This approach will help to replace synthetic-based acoustic absorbers with biodegradable composite panels in acoustic applications. This review also covers, poly(lactic acid) as a polymer matrix and its advantages, the available variety of natural fibers as reinforcement in terms of mechanical and acoustical properties. The natural fiber-based filaments used in additive manufacturing and acoustic panels made from the available natural fibers are also elaborated here. This review shows the importance of additive manufacturing and its application to develop novel acoustic panels made of agricultural waste.

30 citations


Journal ArticleDOI
TL;DR: In this article, a market platform for peer-to-peer (P2P) energy trading in transactive energy (TE) systems is designed, where prosumers and consumers actively participate in the market as seller or buyer to trade energy.
Abstract: This study designs a market platform for peer-to-peer (P2P) energy trading in transactive energy (TE) systems, where prosumers and consumers actively participate in the market as seller or buyer to trade energy. An auction-based approach is used for market clearing in the proposed platform and a review of different types of auctions is performed. The appropriate auction approach for market clearing in the proposed platform is designed. The proposed auction mechanism is implemented in three steps namely determination, allocation and payment. This study identifies important P2P market clearing performance indices, which are used to compare and contrast the designed auction with different types of auction mechanisms. Comparative studies demonstrate the efficacy of the proposed auction mechanism for market clearing in the P2P platform.

28 citations


Journal ArticleDOI
TL;DR: A comprehensive comparison and analysis of the differences between NIBB and conventional buck boost converters was conducted in terms of their operation principles, which includes multi-mode control strategy and dual-edge modulation here, and also the characteristics of switches and passive components in the two converters were analysed.
Abstract: The non-inverting buck boost (NIBB) converter has attracted significant attention in recent years, as it shares ground between input and output, and the voltage stress of switches is lower. In order to investigate the differences between NIBB and conventional buck boost converters, a comprehensive comparison and analysis of these two converters were conducted in terms of their operation principles, which includes multi-mode control strategy and dual-edge modulation here, and also the characteristics of switches and passive components in the two converters were analysed. The results show that NIBB is better than conventional buck boost circuit in these aspects of electrical stress, power loss, cost, passive component volume, and so on. Two prototypes for the two converters with 10 kW/20 kHz were designed and simulated, respectively, for verifying the results. Analytical and simulated results confirmed the conclusions.

27 citations


Journal ArticleDOI
TL;DR: An adaptive neuro-fuzzy inference system (ANFIS)-based forecasting model shows better forecasting accuracy with both PV and wind forecast, therefore, the fuzzy c means clustering (FCM) with hybrid optimisation algorithm-based ANFIS model is implemented as PV andWind forecasting agent for microgrid EMS.
Abstract: This paper proposes a PV and wind output power generation forecasting agent for a multi-agent-based energy management system (EMS) in a smart microgrid. The microgrid EMS requires both generation forecast and load forecast to provide effective dispatch strategies. The efficiency of the EMS significantly relies on its forecasting accuracy. Firstly, this paper develops an adaptive neuro-fuzzy inference system (ANFIS)-based forecasting model and then utilise it for the development of wind and PV generation forecasting agent for microgrid energy management. ANFIS adopt the self-learning capability from the neural network and linguistic expression function from fuzzy logic inference and stands at the top of both the technologies in performance. The proposed model has been tested using two data sets, i.e., PV historical data and historical wind data. The fuzzy c means clustering (FCM) with hybrid optimisation algorithm-based ANFIS model shows better forecasting accuracy with both PV and wind forecast, therefore, implemented as PV and wind forecasting agent for microgrid EMS.

Journal ArticleDOI
Niklas Fritz, Mohamed Rashed, Serhiy Bozhko, Fabrizio Cuomo1, Patrick Wheeler 
TL;DR: Analytical models of the operating waveforms, the losses and the weight of all DAB components are developed and the proposed design algorithm is used for designing a 3 kW high-frequency DAB for an aircraft DC power system.
Abstract: A design procedure for the dual active bridge (DAB) converter is presented, which aims to optimised power density and computational effort. When designing a DAB, the selection of circuit design parameters such as switching frequency, leakage inductance and semiconductor technologies is a complex question when targeting losses and weight minimisation of the final design. In this study, analytical models of the operating waveforms, the losses and the weight of all DAB components are developed. The proposed design algorithm is used for designing a 3 kW high-frequency DAB for an aircraft DC power system.

Journal ArticleDOI
TL;DR: Experimental results show that the improved RANSAC algorithm has high matching accuracy, good robustness, and short running time, which lays the foundation for the subsequent fast image stitching.
Abstract: For the speed of traditional SIFT algorithm in the feature extraction and matching is slow, the article proposes an improved RANSAC features image matching method based on speeded up robust features (SURF). First of all, detect images features and extract with SURF method, use the fast library for approximate nearest neighbours-based matcher method to perform initial matching on image feature points. Improve the RANSAC algorithm to increase the probability of correct matching points being sampled. Experimental results show that the improved RANSAC algorithm has high matching accuracy, good robustness, and short running time. It lays the foundation for the subsequent fast image stitching.

Journal ArticleDOI
TL;DR: In this article, a compact ultra-wideband (UWB) multiple-input multiple-output (MIMO) antenna is presented, which consists of four monopoles which are printed on FR4 substrate, whose impedance bandwidth is from 2 to 12 GHz, and the isolation of two adjacent antennas is less than−20 dB in mostly frequency band.
Abstract: A compact ultra-wideband (UWB) multiple-input multiple-output (MIMO) antenna is presented. The MIMO antenna consists of four monopoles which are printed on FR4 substrate, whose impedance bandwidth is from 2 to 12 GHz, and the isolation of two adjacent antennas is less than−20 dB in mostly frequency band. The current distribution of the antenna is discussed by simulation, and the radiation characteristics of the antenna are improved by increasing the parasitic radiation patch and digging holes in the radiation patch. Four monopoles are placed with polarisation orthogonality, and the adjacent units are separated by slot to cut off the coupling current on the floor, thus effectively improving the isolation of the antenna.

Journal ArticleDOI
TL;DR: A fault diagnosis method for rolling bearing based on ensemble empirical mode decomposition (EEMD) sample entropy and probabilistic neural network (PNN) is proposed for non-steady and non-linear signals, which proves the effectiveness of the proposed method.
Abstract: A fault diagnosis method for rolling bearing based on ensemble empirical mode decomposition (EEMD) sample entropy and probabilistic neural network (PNN) is proposed for non-steady and non-linear signals. First, the rolling bearing signals are decomposed into intrinsic mode function (IMF) using EEMD. Then, the kurtosis of each component is calculated. Five components with large kurtosis are selected and the sample entropy is extracted to form the feature vectors. Finally, the feature vectors are input to the PNN for fault diagnosis. The method is used to classify the type of the rolling bearing fault. The results show that the accuracy of fault diagnosis of the proposed method is 100%, which proves the effectiveness of the proposed method.

Journal ArticleDOI
TL;DR: In this paper, a progressive approach to assess the wind-solar complementarities in Shandong province, China for the preliminary planning of hybrid energy systems is proposed, based on the NASA database, the long-term wind speed and solar irradiation data are obtained and transformed into capacity factors by virtual energy system models.
Abstract: The inherent complementarity of wind and solar energy resources is beneficial to smooth aggregate power and reduce ramp reserve capacity. This article proposes a progressive approach to assess the wind-solar complementarities in Shandong province, China for the preliminary planning of hybrid energy systems. Based on the NASA database, the long-term wind speed and solar irradiation data are obtained and transformed into capacity factors by virtual energy system models. Then, the local assessment that focuses on temporal characteristics is carried out to measure the complementarities in different time scales and search the optimal scale. Progressively, the space scale is extended from a local site to the whole study region and the global assessment is conducted to extract the spatial complementary characteristics. The assessment results are useful to provide the optimal temporal scale and spatial combination of wind-solar complementarity and the proposed approach can be generalised to other regions.

Journal ArticleDOI
TL;DR: Zhangbei demonstration project will be the world's highest voltage level and largest capacity VSC-HVDC power grid, by which millions of kilowatts of renewable energy and pumped storage power will be supplied to Beijing as mentioned in this paper.
Abstract: Zhangbei demonstration project will be the world's highest voltage level and largest capacity VSC-HVDC power grid, by which millions of kilowatts of renewable energy and pumped storage power will be supplied to Beijing. Due to the uncertainty of wind power and solar power, and the operating range restriction of pumped storage unit, it is urgent to find the solution to the problem of plan making of pumped storage generation and convertor substation after the Zhangbei demonstration project completes. This paper analyses the fluctuation characteristics of renewable energy generation in converter substation, based on the t-location scale, then proposes a multi-objective optimal scheduling strategy for wind power, PV, and pumped storage plant in VSC-HVDC grid, with maximum energy consumption and minimum power fluctuation at the load side and vicinity of the adjusting side as the target, considering the constraints from day-ahead forecasts, VSC-HVDC capacity, unit start-up–shutdown, and state conversion. Simulation results show that authors’ strategy can make use of pumped storage power plant to inhibit the fluctuation of renewable energy power and make the maximum renewable energy consumption within the allowed power fluctuation at the sides, attaining a good balance between energy consumption and grid security.

Journal ArticleDOI
TL;DR: An image segmentation algorithm that applies morphology to Canny edge detection uses morphological opening to erode and dilate the binary image after Canny algorithm processing, and removes redundant edge information to obtain a complete fan blade image.
Abstract: When a single image segmentation method is used for image segmentation of wind turbine blade images under a complex background, the results obtained are not accurate and complete. This article proposes an image segmentation algorithm that applies morphology to Canny edge detection. It uses morphological opening to erode and dilate the binary image after Canny algorithm processing, and removes redundant edge information to obtain a complete fan blade image. Experimental results show that the results obtained by the image segmentation method proposed here have good integrity and accuracy, and can improve the segmentation effect of the image.

Journal ArticleDOI
TL;DR: A machine learning algorithm ESRT (enhanced streaming random tree) model is proposed that shows better detection rate and accuracy compared with Bayesian classifiers available in WEKA.
Abstract: In this study, the authors present a system for shadow detection and removal from images using machine learning technique. A machine learning algorithm ESRT (enhanced streaming random tree) model is proposed. The image is converted to HSV and 26 parameters are taken as image measurements. A dataset in Attribute Relation File Format is created for shadow and non-shadow images. The algorithm is trained using the training dataset and tested using the test dataset. Segmentation is performed. The similar threshold homogeneity pixel is grouped. Colour chromaticity is used to remove cast shadow. Morphological processing is performed to remove the shadow from the image. The algorithm shows better detection rate and accuracy compared with Bayesian classifiers available in WEKA.

Journal ArticleDOI
TL;DR: It is concluded that the SOC fuzzy weighting algorithm studied here is superior to the SOC algorithm based on GA-BP neural network.
Abstract: In view of the GA-BP neural network model for estimating the state of charge (SOC) of batteries be greatly influenced by the voltage sampling accuracy. Here, a SOC estimation model based on fuzzy weighting algorithm is proposed which is modified by combining GA-BP neural network with ampere integration method. In addition, the block diagram of the fuzzy weighted SOC estimation model and the specific design process of the model and the determination of input and output and the formulation of fuzzy rules are given here. Through comparing the simulation of SOC model based on GA-BP neural network with the simulation of SOC fuzzy weighting algorithm model based on GA-BP neural network and ampere integral method, it is concluded that the SOC fuzzy weighting algorithm studied here is superior to the SOC algorithm based on GA-BP neural network.

Journal ArticleDOI
TL;DR: In this article, a three-phase motor inverter with sinusoidal output voltages based on the application of gallium nitride transistors and advanced control is analyzed, and the dimensioning and design of the used two-stage LC filter including motor current control based on proportionalintegral-type phase current controllers are described.
Abstract: In this study, a three-phase motor inverter with sinusoidal output voltages based on the application of gallium nitride transistors and advanced control is analysed. In comparison to standard silicon-insulated gate bipolar transistors much higher feasible switching frequencies of 100 kHz and above are possible and reduce the output sine filter component size such that the filter can be directly included into the inverter. This considerably improves the electromagnetic interference (EMI) behaviour of the drive system as well as the acoustic noise, eases the inverter-to-motor wiring and protects the motor isolation against high d u /d t rates. The study describes the dimensioning and design of the used two-stage LC filter including motor current control based on proportional-integral-type phase current controllers. The LC filter damping is performed actively by capacitor current feedback. Using this active damping scheme avoids additional losses of conventional sine filters and guarantees high system efficiency up to 98%. Finally, experimental results of a laboratory prototype verify the proper behaviour of the proposed concept.

Journal ArticleDOI
TL;DR: The droop-based control strategies have been identified as reliable, flexible, and expandable with high dynamic performance and minimal communication needs in MTDC grids and are suitable and adaptable for stable and secure operation of the proposed multi-terminal MVDC distribution network.
Abstract: The multi-terminal voltage sourced converter medium-voltage DC (VSC-MVDC) distribution network has high prospects for future development, hence the proposed alternative for the AC distribution in commercial and industrial applications. However, a number of obstacles stand on its way in realising its immense potential in the modern power system. This study presents a review and focuses on the complexity of controlling DC voltage/power flow in the multi-terminal DC (MTDC) grids and the possible DC voltage coordinated control approaches aimed at identifying the suitable control strategies for the proposed MVDC distribution grids. Several centralised and distributed DC voltage control strategies for MTDC have been considered. In conclusion, the droop-based control strategies have been identified as reliable, flexible, and expandable with high dynamic performance and minimal communication needs in MTDC grids. These strategies are suitable and adaptable for stable and secure operation of the proposed multi-terminal MVDC distribution network. The study recommends a comparative study of the key DC voltage coordination control features of the droop-based control strategies using the multi-terminal VSC-MVDC distribution network dynamic model for future studies.

Journal ArticleDOI
TL;DR: This study explores the possibility of applying the Hilbert–Huang transform to the detection of stator short-circuit faults in permanent magnet synchronous machine (PMSM) through real-time hardware-in-the-loop simulation and experimental results.
Abstract: The Hilbert–Huang transform (HHT) is a time-frequency signal analysis method based on empirical mode decomposition and the Hilbert transform. It is well suited for reliable fault detection since it is unaffected by transient conditions which might cause false alarms. The method has been demonstrated in recent years for bearing fault detection of induction machines (IM). This study explores the possibility of applying the technique to the detection of stator short-circuit faults in permanent magnet synchronous machine (PMSM). A method based on the online statistical analysis of the instantaneous frequency calculated by the HHT is proposed and demonstrated through real-time hardware-in-the-loop simulation and experimental results.

Journal ArticleDOI
TL;DR: This work studies the application of short-time Fourier transform to extract current harmonics of various fault types to design a protection method for meshed multi-terminal voltage source converter-high-voltage direct current grids and shows the accurate detection and discrimination between faulty sections using the proposed harmonic-based method.
Abstract: This work studies the application of short-time Fourier transform (STFT) to extract current harmonics of various fault types to design a protection method for meshed multi-terminal voltage source converter-high-voltage direct current (VSC-HVDC-MTDC) grids. The frequency spectrum of fault current harmonics is used to detect internal and external faults, the faulty pole and fault type. The method does not need the implementation of series inductance on the sides of the DC lines and it is also effective for lines combining overhead lines and cables. The window function and hop size play the primary role in STFT, which are investigated in a sensitivity analysis. A modified version of CIGRE meshed DC grid system is simulated in PSCAD in order to show the robustness of the method, and further signal processing analysis is done in MATLAB. The results show the accurate detection and discrimination between faulty sections using the proposed harmonic-based method and how important the STFT parameters are in order to have a robust protection algorithm.

Journal ArticleDOI
TL;DR: This work focuses on adaptive controller design using fuzzy Logic (FL) controller to get better dynamic performance under non-linearities and parameter uncertainties to highlight the merits of the controller.
Abstract: This work focuses on adaptive controller design using fuzzy Logic (FL) controller to get better dynamic performance under non-linearities and parameter uncertainties. In the proposed controller, the membership function (MF) parameters are tuned in line with the parameter variations of the motor. The steady state, regulatory and servo response of the proposed controller are analysed to highlight the merits of the controller. The simulation results indicate that the proposed controller possesses good tracking capability and faster response time in comparison with conventional schemes.

Journal ArticleDOI
TL;DR: In this article, an optimized mu-near-zero metamaterial (MNZ MM) was proposed for shielding leaked electromagnetic field in four-coil wireless power transfer (WPT) systems.
Abstract: The wireless power transfer (WPT) has attracted considerable attention due to its convenience and reliability. However, the electromagnetic leakage of WPT can be harmful to humans and environment. In order to meet safety requirements, electromagnetic leakage to the nearby transmission channel should be controlled below a certain level. Beyond ferrite and metallic shields, several researchers have proposed mu-near-zero metamaterial (MNZ MM). However, little work researches the application of MNZ MM in four-coil WPT systems. Here, the authors propose an optimised MNZ MM for shielding leaked electromagnetic field. Next, the authors setup a miniaturised WPT system loaded with MNZ slab at 13.56 MHz. It can serve as a frequency selector that reflected a specified frequency of 13.56 MHz, while allowing all other frequencies to pass undisturbed. As a result, the transmission efficiency is dramatically reduced at a 30 cm distance. The magnetic field magnitude of the receiver has been decreased. Obviously, the proposed MNZ MM has good performance in magnetic field shielding for WPT systems.

Journal ArticleDOI
TL;DR: A novel adapted de-loading control strategy without MPPT for grid-connected inverters is proposed here and an online output Active Power-Voltage Matching technique is implemented in this control strategy to make it possible to adjust PV output voltage performance matching different active power demand with different operation modes.
Abstract: Existence PV generation mostly operates under the Maximum Power Point Tracking (MPPT) mode and has no ability to increase or decrease active power, accordingly, PV generation does not participate in grid frequency regulation. Due to an increasing penetration of grid-connected PV generation, when a frequency contingency event occurs, grid may have neither enough inertia response nor governor support and frequency deviation may have a risk of exceeding the limit. Therefore, a novel adapted de-loading control strategy without MPPT for grid-connected inverters is proposed here. This control strategy provides a reserve power in PV system to meet the frequency control demand and an online output Active Power-Voltage Matching (APVM) technique, which is generated as a control flowchart, is implemented in this control strategy to make it possible to adjust PV output voltage performance matching different active power demand with different operation modes. The proposed control strategy of PVs is simulated using PSCAD/EMTDC Software. Results verify the correctness and effectiveness of the proposed adapted de-loading control strategy under several operating conditions.

Journal ArticleDOI
TL;DR: The authors give the background of entomological lidar, summarise the authors’ recent progress and put it in context with contemporary work, and outline applications, ongoing activities and state of the art.
Abstract: During the past decade, the authors have developed and applied optical remote sensing instrumentation for in situ remote surveillance and quantification of the aerofauna. The sparse structure of aerofauna makes optical focusing challenging, but the authors solved this issue through applying the century old Scheimpflug condition. With this approach, the authors have managed to reduce size, cost and complexity of atmospheric lidars and accomplished an effective tool for ecological entomology capable of counting thousands of insects per hour. Due to the high sensitivity and resolution in time and space, the authors can retrieve target modulation signatures in the kHz range for target classification purposes. As opposed to the cm waves in entomological radar, the authors rely on near infrared (IR) light ∼1 μm. This allows superior beam quality, negligible ground clutter and applications close over ground or within vegetation structure. Near IR light can assess both molecular and microstructural properties of the target through differential absorption and depolarisation. Here the authors give the background of entomological lidar, summarise the authors’ recent progress and put it in context with contemporary work. The authors outline applications, ongoing activities and state of the art. The authors discuss future prospects and challenges.

Journal ArticleDOI
TL;DR: This study presents a new islanding detection method (IDM) that is based on deep learning approach, using a convolution neural network (CNN).
Abstract: Distributed generation (DG) has seen tremendous growth to meet the needs of ever-increasing energy demand. Most of these distributed sources are renewable in nature and connected at the consumer end. The increasing penetration of DG sources has made their control and operation complex. One of the issues that are responsible for this increased complexity is islanding. This study presents a new islanding detection method (IDM) that is based on deep learning approach, using a convolution neural network (CNN). The proposed method first converts time-series data to images and then uses them to train and test the designed CNN. A CNN is specifically designed to perform islanding detection. The results using the designed CNN are compared with IDMs based on artificial NN and support vector machine. These comparisons show that islanding detection performed using deep learning technique has better detection accuracy. Also, the proposed method performs well even for noisy data.

Journal ArticleDOI
TL;DR: Simulation experimental results of the DITC control method have effectively reduced the torque ripple and the fractional-integral controller has reduced the overshoot and adjustment time and improved the robustness and disturbance resistance of the system.
Abstract: Switch reluctance motor is suitable for an electric vehicle driving system, which has the advantages of simple structure, high reliability of system and wide range of speed adjustment. In order to reduce the torque ripple of the system and improve the dynamic performance, a strategy of direct instantaneous torque control (DITC) based on a fractional-order proportion integration differentiation (PID) controller is proposed. According to the mathematical characteristics of the fractional-order controller, the form of the fractional-order speed loop controller is determined. Also, the parameters of the speed regulator are designed using the frequency-domain design theory of the control system. Then, the fractional-order controller is discretised. Compared with the traditional proportion integration (PI) controller, the fractional-order controller can have a better control effect. Simulation experimental results of the system show that the DITC control method has effectively reduced the torque ripple and the fractional-integral controller has reduced the overshoot and adjustment time and improved the robustness and disturbance resistance of the system.