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The present paper identifies the root causes of current ringing in a Dual Active Bridge (DAB) power converter and proposes a novel methodology to design the magnetic tank (transformer, primary and secondary inductances) configuration to minimizeit. In particular, two metrics proportional to the current harmonic content on each transformer side are correspondingly proposed based on a steady-state frequency analysis of primary and secondary ac voltages and impedance of the magnetic tank. To get the metrics, different combinations of dv/dt, switching frequency, primary and secondary inductance configuration, and stray capacitance of the magnetic tank (model inputs) are simulated to generate primary and secondary harmonic current indicators (model outputs). Then, a machine-learning model is trained to predict the harmonic current metrics for each given operating setpoint. The model is able to make predictions beyond its training data, therefore generalizing to unseen inputs and enabling rapid evaluation of various designs. Experimental results are presented to evaluate the performance of the metric model for 4 different magnetic tank configurations. Designers can use the methodology to rapidly analyze the generation of current ringing under multiple operating parameters, identifying operating zones with low harmonic content and reduced sensitivity to parameter shifts for the converter's operation

Voltage boost converters are one of the most important components of DC microgrids, since they are used to enhance the voltage of naturally intermittent energy sources such as solar panels in order to feed unknown demands. In this work, a novel tuning algorithm for Composite Nonlinear Feedback (CNF) is studied in depth to improve transient performance and address output voltage regulation for a DC-DC boost converter in the presence of DC input uncertainty. The proposed CNF controller comprises both linear and nonlinear feedback terms. The linear part contributes to the stability and output tracking with a small damping ratio and a quick response. The nonlinear part, i.e., damping term, reduces the overshoot stemming from the linear feedback law and increases the damping ratio of the overall closed-loop system. The nonlinear part is automatically tuned whereby the transient performance of the DC-DC boost converter improves significantly. To assess the performance of the proposed technique, a boost converter is simulated in MATLAB Simulink considering different scenarios such as changing load, DC input, and voltage reference. The numerical results demonstrate that the tuned CNF controller outperforms the linear controller in the DC boost converter. Additionally, several experiments are conducted to validate the efficacy of the suggested technique.

This paper proposes a real-time algorithm for identifying the grid parameters, which is concurrently used for online tuning of the predictive controller in each iteration, in a gridtied active front end (AFE) voltage source converter (VSC) applications. The algorithm is designed by inspiring from the concepts of the extended Kalman filter (EKF) and the model predictive controller (MPC). The performance of the algorithm highly depends on the weighting factors of the algorithm. The artificial neural networks (ANN)-based algorithm is used to find the optimal set of weighting factors among the ones in a parameter search block. An offline particle swarm optimization (PSO) is run to provide the data source for the parameter search block. The algorithm identifies not only the inductance but also the resistance of the grid. Additionally, the hard constraints on the amplitude of the input and output variables are guaranteed. The validation of the proposed approach is performed experimentally and compared with the state-of-the-art conventional methods. The experimental results show the proposed method could effectively stabilize the system in weak grid conditions and under wide impedance variations. Additionally, the accuracy of the proposed impedance identification method is 96%.

This paper proposes a novel attack identification mechanism for internet-of-things-based (IoT-based) converter-composed DC grids, where each agent collects its own and neighbours’ measurement data for output regulation to meet a preceding power-sharing consensus. Independent from model-free or average-model-based attack detection theories, this mechanism is mainly inspired by converter stitching behavior analysis. Correspondingly, when facing latent signal substitution or agent instigation attacks, through comparing estimated signals with received ones for signal source authentication, both self-sensors and neighbours will be inspected. Eventually, not only can such attacks be detected, but also will respective attack sources be identified. A simulation case of 4-agent 800V IoT-based DC grid on Simulink and a hardware case of 3-agent 90V IoT-based DC grid on dSpace testing platform were investigated. Experimental results revealed that the estimation ratio error kept lower than 3.9% and all attacks were successfully identified, verifying the effectiveness of the proposed mechanism.

This paper proposes a novel attack identification mechanism for internet-of-things-based (IoT-based) converter-composed DC grids, where each agent collects its own and neighbours’ measurement data for output regulation to meet a preceding power-sharing consensus. Independent from model-free or average-model-based attack detection theories, this mechanism is mainly inspired by converter stitching behavior analysis. Correspondingly, when facing latent signal substitution or agent instigation attacks, through comparing estimated signals with received ones for signal source authentication, both self-sensors and neighbours will be inspected. Eventually, not only can such attacks be detected, but also will respective attack sources be identified. A simulation case of 4-agent 800V IoT-based DC grid on Simulink and a hardware case of 3-agent 90V IoT-based DC grid on dSpace testing platform were investigated. Experimental results revealed that the estimation ratio error kept lower than 3.9% and all attacks were successfully identified, verifying the effectiveness of the proposed mechanism.

Grid-connected voltage source converters (VSCs), which are the key block of the future power electronics-based power systems, are at a high risk of losing stability and robust performance. These challenges in industrial applications require analyzing and designing a simple, robust, and advanced controller to guarantee not only reliable operation but also the performance of the VSCs. This paper proposes a novel constraint and unconstraint continuous control set (CCS) model predictive controller (MPC) for VSCs. In the unconstraint MPC, the optimal control law is analytically calculated. However, for the constraint MPC, the analytical solution is not available. So, the convex optimization methods are used to find the suboptimal solution. Generally, the key novelties of this paper can be enumerated as using CCS-MPC to obtain fixed switching frequency, considering hard constraints on the amplitude of the input and output signals, and analytically obtain the optimal solution for unconstraint MPC. Finally, to evaluate the validity of the proposed approaches, some experimental tests on the laboratory-scale stand-alone VSC are extracted.

This paper deals with the problem of controller design for DC microgrids that feed constant power loads. To design the proposed controller, first by the use of the exact feedback linearization approach, the linear model of Brunovsky's canonical representation of the system has been obtained to address the nonlinearity problem of the system. Then, the desired control technique is developed by a combination of sliding mode and backstepping control approaches in which a nonlinear disturbance observer is utilized to estimate the disturbance. The overall stability of the system is analyzed based on the Lyapunov approach. A suitable and practical sliding surface is one of the controller strengths that allow the bus voltage to track the reference voltage with high accuracy and fast transient response. Finally, to prove the mentioned claims, an experimental setup has been constructed and the proposed controller is implemented. The experimental results have been analyzed and error analysis is performed. The results confirm the superiority of the proposed controller compared to state-of-the-art controllers.

This paper proposes a robust cooperative distributed secondary control strategy for DC microgrids, with the main focus on reducing communication burdens. To this end, we adopt a sparsity-promoting consensus-based distributed secondary control framework for converter-interfaced DC microgrids consisting of multiple distributed generation (DG) units. The proposed control strategy relies on less (sparse) information exchange over a communication network and does not require exchanging voltage signals or their estimated values amongst neighbouring DG units. Rigorous Lyapunov-based stability certificates for DC microgrids are derived. The stability conditions can be verified without the knowledge of distribution lines connecting different DG units. The effectiveness of the proposed secondary control approach is verified by experimental results and a comparative simulation case study on a multiple-DG DC microgrid.

This paper proposes a distributed intelligent secondary control (SC) approach based on brain emotional learning-based intelligent controller (BELBIC) for power electronic-based ac microgrid (MG). The BELBIC controller is able to learn quick-auto and handle model complexity, non-linearity, and uncertainty of the MG. The proposed controller is fully model-free, indicating that the voltage amplitude and frequency deviations are regulated without previous knowledge of the system model and parameters. This approach ensures low steady-state variations with higher bandwidth and maintains accurate power-sharing of the droop mechanism. Furthermore, primary control is realized with a robust finite control set-model predictive control (FCS-MPC) in the inner level to increase the system frequency bandwidth and a droop control in the outer level to regulate the power-sharing among the distributed generations. Finally, experimental tests obtained from a hardware-in-the-loop testbed validate the proposed control strategy for different cases.

Nonlinear behavior of constant power loads (CPLs) and their negative incremental impedance, which impose adverse effects on system damping and stability margins, necessitate developing proper strategies for efficient implementation framework of DC microgrid. In this paper, a fixed-time sliding mode disturbance observer (SMDO) is first addressed to provide an estimation of the instantaneous power flow moving along the uncertain CPLs with time-varying nature within a fixed time. It not only expedites the estimation rate but also improves the robustness against physical parameter variation. The fast fixed-time backstepping technique is then developed based on the estimated load power to control the duty cycle of the boost converter such that the entire power grid becomes stable and the desired voltage of the DC bus is tracked within a fixed time irrespective of the initial conditions. A rigorous Lyapunov-based approach is represented to guarantee the fixed-time stability of the proposed scheme. Finally, to validate the merits and implementation feasibility of the proposed methodology, the experimental realization is represented under various operating case studies.

Ensuring the reliability of power electronic converters is a matter of great importance, and data-driven condition monitoring techniques are cementing themselves as an important tool for this purpose. However, translating methods that work well in controlled lab environments to field applications presents significant challenges, notably because of the limited diversity and accuracy of the lab training data. By enabling the use of field data, online machine learning can be a powerful tool to overcome this problem, but it introduces additional challenges in ensuring the stability and predictability of the training processes. This work presents an edge computing method that mitigates these shortcomings with minimal additional memory usage, by employing an autonomous algorithm that prioritizes the storage of training samples with larger prediction errors. The method is demonstrated on the use case of a self-commissioning condition monitoring system, in the form of a thermal anomaly detection scheme for a variable frequency motor drive, where the algorithm self-learned to distinguish normal and anomalous operation with minimal prior knowledge. The obtained results, based on experimental data, show a significant improvement in prediction accuracy and training speed, when compared to equivalent models trained online without the proposed data selection process.

To cope with the weak grid stability issue of grid-tied Voltage Source Converters (VSCs), this letter proposes an Artificial Neural Network (ANN)-based approach for online stabilization control of the grid-tied VSC with the pole-tracking feature. First, an ANN is adopted to establish the mapping between the control parameters and the closed-loop poles of the grid-VSC system, serving as a computationally light model surrogate that is favorable for real-time control applications. Then, an online parameter search algorithm enabling simultaneous tuning of multiple controllers and parameters is developed, by which the systems poles under a new grid condition can be pulled to the reference ones, i.e., achieving the pole-tracking-based stabilization control of this work. Finally, the efficacy of the proposed method along with its stabilization effect is verified by MATLAB simulations and experimental results.

Grid-connected power electronic converters are the fundamental building blocks of future power electronic-based power systems. Their fast dynamic performance and robustness are the key requirements for ensuring the reliable operation of such systems. This letter proposes a simple optimal model predictive controller (MPC) to control the active and the reactive current of the three-phase voltage source grid-connected converters. Better performance over other state-of-the-art controllers is evaluated based on quantitative criteria comprising the settling time, and the percentage of the overshoot. Finally, the experimental tests are provided to prove the applicability of the proposed approach.

The parallel connection of DC-DC converters requires the development of an appropriate control strategy that regulates load voltage and shares current amongst participating converters. This paper proposes a resilient and robust cooperative distributed control approach that simultaneously ensures voltage regulation and balanced current sharing in parallel DC-DC converters in the presence of false data injection attacks on control input channels. Based on analytical tools from network control and Lyapunov stability theory, concise stability certificates are derived. The proposed cooperative distributed control strategy guarantees resilience against unknown bounded attacks on the actuators of DC-DC converters and the robustness to uncertainties in load parameters and the physical parameters of converters. Furthermore, the control design for each converter does not require any knowledge about the number of participating converters. The detailed simulation and experimental results verify the satisfactory performance of the proposed method in voltage regulation and balanced current sharing in parallel converters, as well as resilience to bounded false data injection attacks.

Finite set model predictive control (FS-MPC) has been identified as one of the most favorable controllers for power electronic applications due to its capability over real-time solutions to multiple objectives and constraints. However, the main challenge in the FS-MPC is the choice of appropriate weighting factors in the cost function to reach the best switching state of the inverter. This study proposes an approach based on brain emotional learning (BEL) to provide online tuning of weighting factors in FS-MPC of a power converter, which prevents the dependency of the converter control system on the various uncertainties coming from operating conditions and loading conditions. The proposed BEL approach is fully model-free, indicating that the weighting factors are adjusted without previous knowledge of the system model and parameters. Simulation and experimental results validate the proposed control scheme’s effectiveness under different load conditions.

Sharp LC resonance peak may enlarge inherent harmonics, dominant harmonics of the supply voltage generated by a three-phase diode rectifier, around the resonance frequency, which will intensify fluctuations of the DC-link voltage and grid currents in motor drives with small DC-link capacitor. In this paper, a novel resonance suppression strategy based on inherent harmonics impedance shaping is proposed specially for three-phase input PMSM drives with small DC-link capacitor. Instead of increasing the damping of the whole system for resonance suppression, the motor side power disturbance can be reduced by designing the impedance for inherent harmonics around LC resonance frequency, based on the new model with the consideration of motor side characteristic. For damping current generation, the angle of the virtual admittance is modified to eliminate the influence of the DC-link voltage sampling delay. Experimental results show the effectiveness of the method on a prototype of electrolytic capacitorless PMSM drive.

This paper proposes a novel approach to uncover deficiencies of the existing cyber-attack detection schemes and thereby to serve as a foundation for establishing more reliable cybersecure solutions, with particular application in DC microgrids. For this purpose, a multi-agent deep Reinforcement Learning (RL) based algorithm is proposed to automatically discover the vulnerable spots on the conventional index-based cyberattack detection schemes, and automatically generate coordinated stealthy destabilizing False Data Injection (FDI) attacks on cyberprotected islanded DC microgrids. To enable a continuous action space for the trained RL agents and enhance the algorithm’s precision and convergence rate, Deep Deterministic Policy Gradient DDPG) is incorporated. Using this approach, susceptibility of a state-of-the-art detection scheme to several different coordinated FDI attacks on the distributed communication links is identified. The proposed algorithm is also enhanced with a sniffing feature to enable maintaining the stealthy attacks even under the sudden disconnection of any of the compromised links. To address the discovered deficiencies within the index-based detection scheme, a complementary multi-agent RL detection algorithm using Deep Q-Network (DQN) is integrated, which provides a more reliable overall identification performance. Taking into account the communication delays and load changes, the effectiveness of the proposed algorithm is verified by the experimental tests.

This paper presents the application of Model Predictive Control (MPC) in high-performance drives. A wide variety of machines have been considered: induction machines, synchronous machines, linear motors, switched reluctance motors, and multiphase machines. The control of these machines has been done by introducing minor and easy-to-understand modifications to the basic predictive control concept, showing the high flexibility and simplicity of the strategy. The second part of the paper is dedicated to the performance comparison of MPC with classical control techniques such as field-oriented control and direct torque control. The comparison considers the dynamic behavior of the drive and steady-state performance metrics such as inverter losses, current distortion in the motor, and acoustic noise. The main conclusion is that MPC is very competitive concerning classic control methods by reducing the inverter losses and the current distortion with comparable acoustic noise.

Virtual synchronous generator (VSG), recognized as a grid-friendly control technique, contributes to providing inertia and damping support from the grid-tied power electronic systems. However, similar to conventional synchronous generator (SG), the VSG is vulnerable to wideband oscillations, and can even become unstable when the system is subjected to a variety of disturbances. To tackle this issue, this paper proposes a magnitude-phase motion equation (MPME) for grid-forming VSG attached to weak grid. Besides, a feedback analytical method is introduced to identify the frequency dynamic stability, judged by the sign of (d/dt)/. Besides, the rate of change of frequency (RoCoF) and frequency nadir (FN) are evaluated by the two indices, i.e., d/dt and . In addition, the relationship between low-inertia-RoCoF-FN-related stability and the weak-damping-oscillation-related stability is illustrated by the feedback analysis. Moreover, in the framework of MPME, a reactive-power feedforward (PPFF) decoupling control strategy is proposed for enhancement of stability and robustness performance of the VSG-system. Finally, the proposed modeling and the reactive-power feedforward decoupling control strategy are demonstrated with the experiments.

The application of Model Predictive Control (MPC) in electrical drives has been studied extensively in the last decade. This paper presents what the authors consider the most relevant contributions published in the last years, mainly focusing on three relevant issues: weighting factor calculation when multiple objectives are utilized in the cost function, current/torque harmonic distortion optimization when the power converter switching frequency is reduced, and robustness improvement under parameters uncertainties. Therefore, this paper aims to enable readers to have a more precise overview while facilitating their future research work in this exciting area.

Beat phenomenon is an important issue for the practical application of electrolytic capacitorless motor drives. In this study, the characteristics of stator current harmonics caused by the voltage sampling delay are analyzed. Further, the beat phenomenon generated from the interaction between the harmonics and the fundamental currents is investigated, and the envelope feature of the stator current is derived mathematically. For the purpose of suppressing the beat phenomenon, a voltage reconstruction strategy is proposed to reduce the influence of DC link voltage sampling delay at the six times of grid frequency. By utilizing the reconstructed DC link voltage for calculation of PWM duty ratio, the beat phenomenon can be attenuated significantly. The proposed method can be integrated into motor control system easily. Experimental results show the effectiveness of the proposed strategy in a prototype of electrolytic capacitorless permanent magnet synchronous motor drive.

Multilevel inverters (MLIs) have gained wide attention in industry and academia to provide higher voltage levels with lower harmonics, power losses, and cost. This study proposes a new asymmetrical MLI topology with reduced component count (RCC). The proposed topology can be extended in a three-phase structure and both modular and cascaded configurations to generate the required number of voltage levels for high-voltage applications. To minimize the power losses and the voltage stress on the switches, this configuration has the potential to produce negative polarity without an H-bridge configuration, thereby the active switches are reduced to only three switches in the conduction path. Due to the possibility of applying different switching patterns, this paper proposes a new solution by employing particle swarm optimization (PSO) algorithm to determine the optimized DC sources’ magnitude. To improve the voltage quality and minimize the total harmonic distortion (THD), the optimal switching angle (OSA) modulation technique is applied to determine the optimum switching angles by PSO algorithm. Moreover, the proposed topology’s effectiveness compared to the conventional cascaded H-bridge (CHB) MLI with 15-levels is illustrated by providing comparative results that express fewer power losses. Finally, the proposed topology’s feasibility and its optimization approach are validated by a single-phase prototype utilizing 15- and 25-levels.

A first-order complex bandpass filter (CBF) derived in the discrete frequency domain is proposed as a building block for the complex signal processing unit in three-phase converter systems. The first-order discrete CBF can be directly implemented in a digital system, is stable at all center frequencies and has a low computational burden. The first-order CBF is extended to a pth-order discrete CBF. A normalized frequency-locked loop (FLL) is then developed that allows the frequency adaption to satisfy a desired settling time regardless of the input signal magnitude or discrete CBF form. The pth-order discrete CBF-FLL was tested on an FPGA in the form of two industrial applications: voltage synchronization under grid fault and extraction of an unknown frequency component. The second-order discrete CBF-FLL offered significantly improved stopband attenuation and frequency estimation relative to the first-order discrete CBF-FLL, for a small increase in computational burden.

Direct drive high temperature superconducting (HTS) wind turbine generators have been proposed to tackle challenges for ever increasing wind turbine ratings. Due to smaller reactances in HTS generators, higher fault currents and larger transient torques could occur if sudden short circuits happen at generator terminals. In this paper, a finite element model that couples magnetic fields and the generator’s equivalent circuits is developed to simulate short circuit faults. Afterwards, the model is used to study the transient performance of a 10 MW HTS wind turbine generator under four different short circuits, i.e., three-phase, phase-phase clear of earth, phase-phase-earth, and phase-earth. The stator current, fault torque, and field current under each short circuit scenario are examined. Also included are the forces experienced by the HTS field winding under short circuits. The results show that the short circuits pose great challenges to the generator, and careful consideration should be given to protect the generator. The findings presented in this paper would be beneficial to the design, operation and protection of an HTS wind turbine generator., DC systems, Energy conversion & Storage

Direct drive high temperature superconducting (HTS) wind turbine generators have been proposed to tackle challenges for ever increasing wind turbine ratings. Due to smaller reactances in HTS generators, higher fault currents and larger transient torques could occur if sudden short circuits happen at generator terminals. In this paper, a finite element model that couples magnetic fields and the generator’s equivalent circuits is developed to simulate short circuit faults. Afterwards, the model is used to study the transient performance of a 10 MW HTS wind turbine generator under four different short circuits, i.e., three-phase, phase-phase clear of earth, phase-phase-earth, and phase-earth. The stator current, fault torque, and field current under each short circuit scenario are examined. Also included are the forces experienced by the HTS field winding under short circuits. The results show that the short circuits pose great challenges to the generator, and careful consideration should be given to protect the generator. The findings presented in this paper would be beneficial to the design, operation and protection of an HTS wind turbine generator., DC systems, Energy conversion & Storage

Direct Drive high-temperature superconducting (HTS) wind turbine generators have been proposed to tackle challenges for ever increasing wind turbine ratings. Due to smaller reactances in HTS generators, higher fault currents and larger transient torques could occur if sudden short circuits take place at generator terminals. In this paper, a finite element model that couples magnetic fields and the generator's equivalent circuits is developed to simulate short-circuit faults. Afterward, the model is used to study the transient performance of a 10-MW HTS wind turbine generator under four different short circuits, i.e., three-phase, phase–phase clear of earth, phase-phase-earth, and phase-earth. The stator current, fault torque, and field current under each short circuit scenario are examined. Also included are the forces experienced by the HTS field winding under short circuits. The results show that the short circuits pose great challenges to the generator, and careful consideration should be given to protect the generator. The findings presented in this paper would be beneficial to the design, operation and protection of an HTS wind turbine generator.

A 2-MW high-temperature superconducting (HTS) generator with 24 pole pairs has been designed for the wind turbine application. In order to identify potential challenges and obtain practical knowledge prior to production, a full-size stationary experimental setup, which is one pole pair segment of the full generator, has been built and tested. The experimental setup comprises a consequent-pole HTS rotor and a conventional three-phase copper stator. This paper first presents the electromagnetic designs of the full generator and the setup, then it goes to compare the performance of the full generator and the setup in terms of the flux density, the operating condition of the HTS winding, and the force-generation capability. Finite element (FE) software MagNet is used to carry out numerical simulations. The findings show that the HTS winding in the setup is a good surrogate for these that would be used in the full generator. The FE simulations also tell that the maximum tangential force generated in the setup is 3.77% lower than that in the full generator. Good agreement between the values of interest in the setup and those projected in the full generator has revealed a cost-effective prototyping methodology for developing HTS machines.

A full-size stationary experimental setup, which is a pole pair segment of a 2 MW high-temperature superconducting (HTS) wind turbine generator, has been built and tested under the HTS-GEN project in Denmark. The performance of the HTS coil is crucial to the setup, and further to the development of the full generator. This paper deals with the HTS coil employed in the setup. The coil utilizing YBCO tapes is double-layered with 152 turns per layer and is wound on an FeNi9 iron core. Several sensors are installed to monitor the operating status of the coil, e.g., temperature, field, and voltage. The coil is tested in LN2 first, and then tested in the setup so that the magnetic environment in a real generator is reflected. The experimental results are reported, followed by a finite-element simulation and a discussion on the deviation of the results. The tested and estimated Ic in LN2 are 148 A and 143 A, respectively. When tested in the setup, the maximum temperature of the coil is controlled at 77 K and 40 K, and the I-V curves under both conditions are presented. It is found that the lower half coil that is closer to the stator has a smaller Ic due to a higher field level. The study is of significance to the development of HTS generators.

Rare earth permanent magnets can be reused directly as an alternative to traditional recycling methods, in which scrapped magnets are reprocessed into new magnets by undergoing many of the original energy-intensive and expensive production processes. Direct reuse entails using segmented magnet assemblies built by several small standard-sized magnets that can be reused directly in a number of different applications. A central part of the direct reuse strategy is to separate and demagnetize magnets by heating them to the Curie temperature. We investigated the validity of direct reuse as a rare earth magnet recycling strategy by evaluating the extent to which the heat-driven demagnetization cycles affected magnetic properties, as well as the integrity of the protective coating of Nd–Fe–B magnets. The experimental investigation consisted of four different tests, and was applied to 300 magnets that had either been heated once, five times, or none at all. The tests included $J$ – $H$ measurements, coating pull-off test, corrosion salt spray test, and optical microscopy of the interface between coating and magnet. Magnets coated with Zn, Epoxy, Ni–Cu–Ni, and Ni–Cu+Epoxy were investigated, of which Ni–Cu+Epoxy showed no degradation after heat treatment. Direct reuse as a recycling strategy could therefore be a valuable alternative to traditional recycling.

The phase variable model is used commonly when simulating a motor drive system with a three-phase permanent magnet brushless DC (PMBLDC) motor. The phase variable model neglects core losses and this affects its accuracy when modelling fractional-slot machines. The inaccuracy of phase variable model of fractional-slot machines can be attributed to considerable armature flux harmonics, which causes an increased core loss. This study proposes a nonlinear phase variable model of PMBLDC motor that considers the core losses induced in the stator and the rotor. The core loss model is developed based on the detailed analysis of the flux path and the variation of flux in different components of the machine. A prototype of fractional slot axial flux PMBLDC in-wheel motor is used to assess the proposed nonlinear dynamic model.

Direct drive high temperature superconducting (HTS) wind turbine generators have been proposed to tackle challenges for ever increasing wind turbine ratings. Due to smaller reactances in HTS generators, higher fault currents and larger transient torques could occur if sudden short circuits happen at generator terminals. In this paper, a finite element model that couples magnetic fields and the generator’s equivalent circuits is developed to simulate short circuit faults. Afterwards, the model is used to study the transient performance of a 10 MW HTS wind turbine generator under four different short circuits, i.e., three-phase, phase-phase clear of earth, phase-phase-earth, and phase-earth. The stator current, fault torque, and field current under each short circuit scenario are examined. Also included are the forces experienced by the field winding under short circuits. The results show that the short circuits pose great challenges to the generator, and careful consideration should be given to protect the generator. The results presented in this paper would be beneficial to the design, operation and protection of an HTS wind turbine generator., DC systems, Energy conversion & Storage

Direct drive high temperature superconducting (HTS) wind turbine generators have been proposed to tackle challenges for ever increasing wind turbine ratings. Due to smaller reactances in HTS generators, higher fault currents and larger transient torques could occur if sudden short circuits happen at generator terminals. In this paper, a finite element model that couples magnetic fields and the generator’s equivalent circuits is developed to simulate short circuit faults. Afterwards, the model is used to study the transient performance of a 10 MW HTS wind turbine generator under four different short circuits, i.e., three-phase, phase-phase clear of earth, phase-phase-earth, and phase-earth. The stator current, fault torque, and field current under each short circuit scenario are examined. Also included are the forces experienced by the field winding under short circuits. The results show that the short circuits pose great challenges to the generator, and careful consideration should be given to protect the generator. The results presented in this paper would be beneficial to the design, operation and protection of an HTS wind turbine generator., DC systems, Energy conversion & Storage

This paper discusses design synthesis of a permanent magnet brushless DC (PMBLDC) machine using a finite element (FE) model. This work differentiates itself from the past studies by following a synthesis approach, in which many designs that satisfy performance criteria are considered instead of a unique solution. The designer can later select a design, based on comparing parameters of the designs, which are critical to the application that the motor will be used. The presented approach makes it easier to define constraints for a design synthesis problem. A detailed description of the setting up of a FE based design synthesis problem, starting from the definition of design variables, FE model of the machine, how the design synthesis is carried out, and to, how a design is finalised from a set of designs that satisfy performance criteria, is included in this paper. The proposed synthesis program is demonstrated by designing a segmented axial torus PMBLDC motor for an electric two-wheeler.

Direct drive high temperature superconducting (HTS) wind turbine generators have been proposed to tackle challenges for ever increasing wind turbine ratings. Due to smaller reactances in HTS generators, higher fault currents and larger transient torques could occur if sudden short circuits happen at generator terminals. In this paper, a finite element model that couples magnetic fields and the generator’s equivalent circuits is developed to simulate short circuit faults. Afterwards, the model is used to study the transient performance of a 10 MW HTS wind turbine generator under four different short circuits, i.e., three-phase, phase-phase clear of earth, phase-phase-earth, and phase-earth. The stator current, fault torque, and field current under each short circuit scenario are examined. Also included are the forces experienced by the field winding under short circuits. The results show that the short circuits pose great challenges to the generator, and careful consideration should be given to protect the generator. The results presented in this paper would be beneficial to the design, operation and protection of an HTS wind turbine generator.

Generator bearing defects, e.g. ball, inner and outer race defects, are ranked among the most frequent mechanical failures encountered in wind turbines. Diagnosis and prognosis of bearing faults can be successfully implemented using vibration based condition monitoring systems, where tracking and trending of specific condition indicators can be used to evaluate the former, current and potentially future condition of these components. The latter, i.e. evaluation of the fault progression rate and remaining useful lifetime (RUL), is of essential importance to owners and operators in regards to maintenance planning and component replacement. The above approach offers numerous benefits from financial and operational perspective, such as increased availability, uptower repairs and minimization of secondary and catastrophic damages. In this work, a non-speed related condition indicator, measuring the signal energy between 10Hz to 1000Hz is utilized as feature to characterize the severity of developing bearing faults. Furthermore, local trend models are employed to predict the progression of bearing defects from a vibration standpoint in accordance with the limits suggested in ISO 10816. Predictions of vibration trends from multi-megawatt wind turbine generators are presented, showing the effectiveness of the suggested approach on the calculation of the RUL and fault progression rate.

In this work, the classical linear model of a permanent magnet synchronous motor (PMSM) is modified by adding d and q-axes harmonic inductances so that the modified model can consider non-linearities present in an interior permanent magnet (IPM) motor. Further, a method has been presented to assess the effect of saturation and cross-saturation on constant torque curves of PMSM. Two IPM motors with two different rotor topologies and different specifications are designed to evaluate the effect of saturation on synchronous and harmonic inductances, and on operating points of the machines

In transient operations or fault conditions, hightemperature superconducting (HTS) machines suffer ac losses, which have an influence on the thermal stability of superconducting windings. In this paper, a method to calculate ac losses and their thermal effect in HTS machines is presented. The method consists of three submodels that are coupled only in one direction. The magnetic field distribution is first solved in a machine model, assuming a uniform current distribution in HTS windings. The magnetic fields on the boundaries are then used as inputs for an ac loss model that has a homogeneous approximation and solves the H formulation. Afterward, the computed ac losses are considered as the heat source in a thermal model to study the temperature profile in HTS windings. The method proposed is able to evaluate ac losses and their thermal effect, thus providing a reference to design an HTS machine and its cooling system.

Vibration diagnosis is one of the most common techniques in condition evaluation of wind turbine equipped with gearbox. On the other side, gearbox is one of the key components of wind turbine drivetrain. Due to the stochastic operation of wind turbines, the gearbox shaft rotating speed changes with high percentage, which limits the application of traditional vibration signal processing techniques, such as fast Fourier transform. This paper investigates a new approach for wind turbine high speed shaft gear fault diagnosis using discrete wavelet transform and time synchronous averaging. First, the vibration signals are decomposed into a series of subbands signals with the use of amultiresolution analytical property of the discrete wavelet transform.Then, 22 condition indicators are extracted fromthe TSA signal, residual signal, and difference signal.Through the case study analysis, a new approach reveals the most relevant condition indicators based on vibrations that can be used for high speed shaft gear spalling fault diagnosis and their tracking abilities for fault degradation progression. It is also shown that the proposed approach enhances the gearbox fault diagnosis ability in wind turbines. The approach presented in this paper was programmed in Matlab environment using data acquired on a 2MWwind turbine.

The classical dq-axes model of permanent magnet synchronous machines (PMSM) uses linear approximation. This was not an issue in earlier versions of PMSM drives because they mostly used surface magnet motors. With the arrival of interior permanent magnet (IPM) machines, which use reluctance torque along with magnet torque, the accuracy of linear models are found to be insufficient. In this work, the effect of air gap flux harmonics is included in the classical model of PMSM using d and q-axes harmonic inductances. Further, a method has been presented to assess the effect of saturation and cross-saturation on constant torque curves of PMSM. Two interior permanent magnet motor with two different rotor topologies and different specifications are designed to evaluate the effect of saturation on synchronous and harmonic inductances, and operating points of the machines.

The price fluctuations of rare earth metals and the uncertainty in their availability has generated an increased interest in ferrite magnet machines. The influence of temperature on BH characteristics of the ferrite magnet differ considerably from that of the rare earth magnet and hence, requires a different approach when deciding their operating point. In this work, laboratory measured BH curves of a ferrite magnet are used for estimating the possibility of demagnetization in a segmented axial torus (SAT) permanent magnet brushless DC (PMBLDC) motor. The BH characteristics for different temperatures have been used to study the performance variation of the ferrite magnet SAT PMBLDC motor with temperature. A detailed analysis is carried out to ensure that, the designed ferrite magnet motor is capable of delivering the specified torque throughout the operating speed, without any irreversible demagnetization of magnets. It has been shown that the ferrite magnet PMBLDC motor operation is influenced by the magnet temperature and the maximum motor speed for a given load torque decreases as the magnet temperature drops.

Efficient fault detection in generators often require prior knowledge of fault behavior, which can be obtained from theoretical analysis, often carried out by using discrete models of a given generator. Mathematical models are commonly represented in the DQ0 reference frame, which is convenient in many areas of electrical machine analysis. However, for fault investigations, the phase-coordinate representation has been found more suitable. This paper presents a mathematical model in phase coordinates of the DFIG with two parallel windings per rotor phase. The model has been implemented in Matlab and its properties in context of fault simulations and investigations has been investigated. Some of the most common faults have been simulated, namely broken rotor bars or windings, dynamic eccentricities and stator phase winding short circuits. These fault conditions propagate to the stator current as undesired spectral components, which can be detected by applying frequency spectrum analysis.

The accelerated evolution and explosion of the Internet and social media is generating voluminous quantities of data (on zettabyte scales). Paramount amongst the desires to manipulate and extract actionable intelligence from vast big data volumes is the need for scalable, performance-conscious analytics algorithms. To directly address this need, we propose a novel MapReduce implementation of the exemplar-based clustering algorithm known as Affinity Propagation. Our parallelization strategy extends to the multilevel Hierarchical Affinity Propagation algorithm and enables tiered aggregation of unstructured data with minimal free parameters, in principle requiring only a similarity measure between data points. We detail the linear run-time complexity of our approach, overcoming the limiting quadratic complexity of the original algorithm. Experimental validation of our clustering methodology on a variety of synthetic and real data sets (e.g. images and point data) demonstrates our competitiveness against other state-of-the-art MapReduce clustering techniques.

This chapter will discuss emerging technologies that are expected to continue the development of the wind sector to embrace new markets and to become even more competitive.

Condition monitoring of wind turbines is a field of continu- ous research and development as new turbine configurations enter into the market and new failure modes appear. Systems utilising well established techniques from the energy and in- dustry sector, such as vibration analysis, are commercially available and functioning successfully in fixed speed and vari- able speed turbines. Power performance analysis is a method specifically applicable to wind turbines for the detection of power generation changes due to external factors, such as ic- ing, internal factors, such as controller malfunction, or delib- erate actions, such as power de-rating. In this paper, power performance analysis is performed by sliding a time-power window and calculating the two eigenvalues corresponding to the two dimensional wind speed - power generation dis- tribution. The power is classified into five bins in order to achieve better resolution and thus identify the most proba- ble root cause of the power deviation. An important aspect of the proposed technique is its independence of the power curve provided by the turbine manufacturer. It is shown that by detecting any changes of the two eigenvalues trends in the five power bins, power generation anomalies are consistently identified

A HTS machine could be a way to address some of the technical barriers offshore wind energy is about to face. Due to the superior power density of HTS machines, this technology could become a milestone on which many, including the wind industry, will rely on in the future. The work presented in this thesis is a part of a larger endeavor, the Superwind project that focused on identifying the potentials that HTS machines could offer to the wind industry and addressing some of the challenges in the process. In order to identify these challenges, I have designed and constructed an HTS machine experimental setup which is made to serve as precursor, leading towards an optimized HTS machine concept proposed for wind turbines. In part, the work presented in this thesis will focus on the description of the experimental setup and reasoning behind the choices made during the design. The setup comprises an HTS synchronous machine where a revolv- ing armature winding spins around an open bath liquid nitrogen cryostat, which contains the HTS coils cooled down to 77 K. A significant part of the thesis is allocated to the description of the setup, particularly the torque transfer element and the compact cryostat design, where a concept with 20 W of heat transfer is achieved. Following the setup description, the focus turns to the electromagnetic design of the HTS machine. Particularly, an approach to increase the performance of HTS coils and the influence of the armature reaction to the HTS field winding will be discussed. Two design strategies are proposed, novel in a machine design, in order to reduce the amount of HTS required in a machine whereby the merits of both have been experimentally verified. The first employs a multiple HTS types in the machine design, since each type of the HTS tape has a specific magnetic characteristic with respect to the critical current. I have showed that the potential for the reduction of HTS conductor can be significant, if the coils are pla

This paper presents experimental results from the Superwind laboratory setup. Particular focus in the paper has been placed on describing and quantifying the in influence of armature reaction on performance of the HTS fled winding. Presented experimental results have confrmed the HTS feld winding sensitivity to both armature reaction intensity and angular position with respect to the HTS coils. Furthermore, the characterization of the HTS feld winding has been correlated to the electromagnetic torque of the machine where the maximal Ic reduction of 21% has been observed for the maximum torque.