From the perspective of a virtual power plant (VPP) with electric vehicles (EVs), a self-scheduling strategy considering the response time margin (RTM) and state of charge margin (SOCM) is proposed. Firstly, considering the response state of the state of charge (SOC) and charge-discharge state of EVs, a VPP based response capacity determination model of EVs is established. Then, RTM and SOCM indexes are introduced on the basis of the power system scheduling target and the EV users’ traveling demands. The RTM and SOCM indices are calculated and then are used to generate a priority sequence of responsive EVs for the VPP. In the process of the scheduling period and rolling iteration, the scheduling schemes of the EVs in the VPP for multiple time periods are determined. Finally, the VPP self-scheduling strategy is validated by taking an VPP containing three kinds of EV users as an example. Simulation results show that with the proposed strategy, the VPP is able to respond to the scheduling power from the power system, while ensuring the traveling demands of the EV users at the same time.

The paper aims at the higher reactive power management complexity caused by the access of distributed power, and the problem such as large data exchange capacity, low accuracy of reactive power distribution, a slow convergence rate, and so on, may appear when the controlled objects are large. This paper proposes a reactive power and voltage control management strategy based on virtual reactance cloud control. The coupling between active power and reactive power in the system is effectively eliminated through the virtual reactance. At the same time, huge amounts of data are treated to parallel processing by using the cloud computing model parallel distributed processing, realize the uncertainty transformation between qualitative concept and quantitative value. The power distribution matrix is formed according to graph theory, and the accurate allocation of reactive power is realized by applying the cloud control model. Finally, the validity and rationality of this method are verified by testing a practical node system through simulation.

The multi-phase permanent-magnet machines with a fractional-slot concentrated-winding (FSCW) are a suitable choice for certain purposes like aircraft, marine, and electric vehicles, because of the fault tolerance and high power density capability. The paper aims to design, optimize and prototype a five-phase fractional-slot concentrated-winding surface-mounted permanent-magnet motor. To optimize the designed multi-phase motor a multi-objective optimization technique based on the genetic algorithm method is applied. The machine design objectives are to maximize torque density of the motor and maximize efficiency then to determine the best choice of the designed machine parameters. Then, the two-dimensional Finite Element Method (2D-FEM) is employed to verify the performance of the optimized machine. Finally, the optimized machine is prototyped. The paper found that the results of the prototyped machine validate the results of theatrical analyses of the machine and accurate consideration of the parameters improved the acting of the machine.

To improve the power quality of a multi-pulse rectifier, a zigzag 18-pulse uncontrolled rectifier with an auxiliary circuit at the DC side is proposed. When the grid-side currents are sinusoidal waves, the required DC side injection currents to be compensated can be obtained by analyzing the AC-DC side relationship of diode bridge rectifiers. Then the 6 compensation currents generated by an active auxiliary circuit are injected into the DC side to eliminate the grid-side harmonics of the rectifier. The simulation results verifying the correctness of the theoretical analysis show that the proposed rectifier can mitigate the harmonic content, as the total harmonic distortion of the grid-side current is about 1.45%. In addition, the single-phase inverter used in the active auxiliary circuit has the characters of simple circuit structure and easy controllability.

The paper presents research on the development of a line-start synchronous reluctance motor (LSSynRM) and line-start permanent magnet synchronous motor (LSPMSM) based on components of a mass-produced three-phase low-power squirrel cage induction motor (IM). The aim of the research was to modify the squirrel cage rotor structure for which the best functional parameters characterizing the steady state of the LSSynRM and LSPMSM were obtained, while meeting the additional requirements for asynchronous start-up. Field-circuit models of the LSSynRM and LSPMSM have been developed in the professional finite element method (FEM) package, MagNet, and applied in the design and optimization calculations of the considered machines. Experimental testing on the designed LSSynRM and LSPMSM prototypes were carried out. The obtained results were compared with the performance of the reference IM. The conclusions resulting from the comparative analysis of these three motors are given and proposals for further work are discussed.

With the rapid advancement of digital processors, filters have been commonly implemented using microcomputers. In this study, a low-cost and compact Arduino Uno development board was used to realize digital lead and lag compensators. Arduino boards are very affordable. Consequently, they were investigated to see if they were capable of preserving the frequency response of continuous-time compensators. The experiments required a set of equipment including a function generator, an Arduino Uno development board, a PC-based oscilloscope, and a laptop. The signal frequency was varied from 0 to 500 Hz. Two discretization methods were employed, namely bilinear transformation and matched pole-zero mapping. The results showed that an Arduino Uno board can be utilized to implement lead and lag compensators to some extent. The discrete-time compensator preserved the capability of filtering out certain frequencies. The change in DC gain was negligible, however, there was a significant difference in the cut-off frequency and transient slope. For both discretization methods, the frequency responses at high frequency experienced a rippling profile.

This paper presents an improved Virtual Flux-based Direct Power Control (VF-DPC) applied for a three-phase pulse width modulation rectifier. The proposed control approach incorporates an enhanced Virtual Flux estimator made up of a cascade second-degree low-pass filter. This latter guarantees the attenuation of the highest harmonics. The introduced control concept presented in this paper has interesting features such as reducing the current harmonics distortion. In other words, it ensures that the input current drawn from the power supply is perfectly sinusoidal whatever the state of the network voltage. The proposed method also allows to maintain the DC side capacitor voltage at the required level and assure that the input current is in phase with the respective voltage to satisfy the unity power factor function. The results obtained from the numerical simulation have proved the effectiveness of the proposed method for disturbed grid voltage and system parameters variation.

Power big data contains a lot of information related to equipment fault. The analysis and processing of power big data can realize fault diagnosis. This study mainly analyzed the application of association rules in power big data processing. Firstly, the association rules and the Apriori algorithm were introduced. Then, aiming at the shortage of the Apriori algorithm, an IM-Apriori algorithm was designed, and a simulation experiment was carried out. The results showed that the IM-Apriori algorithm had a significant advantage over the Apriori algorithm in the running time. When the number of transactions was 100 000, the running of the IM-Apriori algorithm was 38.42% faster than that of the Apriori algorithm. The IM-Apriori algorithm was little affected by the value of supportmin. Compared with the Extreme Learning Machine (ELM), the IM-Apriori algorithm had better accuracy. The experimental results show the effectiveness of the IM-Apriori algorithm in fault diagnosis, and it can be further promoted and applied in power grid equipment.

Low-power consumption and long-distance transmission are two problems that have to be solved by the application of broadband power line communication for the automatic meter reading system. To reduce the power consumption of the communication module, based on the analysis of the composition of the power consumption, some methods are proposed. From the communication chip level and the module circuit level, the design scheme of low-power consumption is given. To solve the problem of transmission distance, a frequency band of 2.44 MHz~5.6 MHz is used as the main working frequency band. The communication module supports multiple frequency bands. Using this feature, the optimal frequency band is adaptively selected for communication and automatic switching, which further improve the transmission distance. Field application shows that the above methods effectively decrease the power consumption of the communication module and extend the transmission distance.

The paper deals with hardware solution of a fully digital dead-time generator. The circuit is applicable to the H-bridges based on any type of semiconductor switching devices including SiC, IGBT, Si-MOSFET and up-to-date GaN HEMTs. The generation of dead-times is ensured by commercially available silicon delay lines. High temperature stability is obtained by self-compensation of propagation delay of logic elements thanks to the symmetry of design topology. The circuit can be set-up to generate dead-times in the range from 10 ns to 500 ns. Longer dead-times are also available by simple cascading of the silicon delay lines. The key motivation for development of the circuit was unavailability of ready to use integrated solutions on the market. Moreover, contrary to the other solutions the proposed circuit is immune to prospective oscillations of an input PWM signal. The paper brings a detailed analysis of the circuit principle, results of the verification of a sample solution and an example of practical application as well.

In order to realize constant current and constant voltage charging for batteries by inductively coupled power transfer (ICPT) technology, a single-switch CL/LCL circuit is designed. The single-switch CL/LCL circuit is composed of a CL/LCL compensation network and single-switch inverter. The proposed circuit is compared with the traditional constant current and constant voltage circuit in the structure. The operating process of the single-switch CL/LCL circuit and the principle to realize a zero-voltage switch (ZVS) are analysed in detail in this paper. The voltage gain and current gain of the circuit are cal- culated, which demonstrates that the circuit is able to suppress higher harmonics strongly. By using Fourier decomposition, the voltage on the primary-side compensation capaci- tor can be obtained. After constructing the equivalent mutual inductance model of the circuit, the formulas and parameters are deduced and calculated. Finally, an experiment platform is built to verify the proposed circuit can realize constant current and constant voltage.

The polarized electromagnetic waves have significant impact on the performance of adaptive antenna arrays. In this paper we investigate the effect of polarized desired and undesired signals on the performance of electronically steered beam adaptive antenna arrays. To achieve this goal, we built an analytical signal model for the adaptive array, in order to analyze, and compare the effect of polarized signals on the output SINRs (signal to interference plus noise ratios) of single-dipole, and cross-dipole adaptive antenna arrays. Based on a proof-of-concept experiment, and on MATLAB simulation results, it will be shown that cross-dipole adaptive antenna arrays exhibit better performance in comparison with single-dipole adaptive antenna arrays in presence of randomly polarized signals. However, single-dipole arrays show better performance under certain operating conditions.

The presence of an open-circuit fault subjects a three-phase induction motor to severely unbalanced voltages that may damage the stator windings consecutively causing total shutdown of systems. Unplanned downtime is very costly. Therefore, fault diagnosis is essential for making a predictive plan for maintenance and saving the required time and cost. This paper presents a model-based diagnosis technique for diagnosing an open-circuit fault in any phase of a three-phase induction motor. The proposed strategy requires only current signals from the faulty machine to compare them with the healthy currents from an induction motor model. Then the errors of comparison are used as an objective function for a genetic algorithm that estimates the parameters of a healthy model, which they employed to identify and localize the fault. The simulation results illustrate the behaviours of basic parameters (stator and rotor resistances, self-inductances, and mutual inductance) and the number of stator winding turn parameters with respect to the location of an open-circuit fault. The results confirm that the number of stator winding turns are the useful parameters and can be utilized as an identifier for an open-circuit fault. The originality of this work is in extracting fault diagnosis features from the variations of the number of stator winding turns.

Controlling and reducing the radiation emitted by various systems helps the board designer improve systems’ performance. One proposed way to achieve these goals is to use an algorithm to control the radiation applied to systems. According to the executive structure of the algorithm and considering the nature of the existing signals in several components, the separation of the signal components is on the agenda of the algorithm. In fact, the goal is to create an intuitive view of the multi-component signals around the systems that enter the systems from different angles and have a detrimental effect on their performance. Using signal processing methods, we will be able to break down the signal into different components and simulate each component separately. To prevent high computational repetitions and increase simulation time in signal component analysis, by reducing the components, we reduce the number of mesh cells in the software and, using linear approximation, determine the exact position of the radiation signal applied to systems and thus the best linear relationship. The signal entry path is used to apply the rules required for prediction design.

The Synchronous Reluctance Machine (SynRM) is an electrical machine in which the useful electromagnetic torque is produced due to rotor saliency. Its high power- and torque-to-mass ratio and very good efficiency make it a cheap and simple alternative for permanent magnet or induction motors, e.g. in electromobility applications. However, because of magnetic nonlinearities, the rotational speed and torque control of a SynRM is a nontrivial task. In the paper, a control algorithm based on a Hamiltonian mathematical model is presented. The model is formulated using measurement results, obtained by the drive controller. An algorithm is tested in the drive system consisting of a SynRM with the classical rotor and a fast prototyping card. The drive dynamic response in transient states is very good, but the proposed algorithm does not ensure the best efficiency after steady state angular velocity is achieved.

Large-signal input characteristics of three DC–DC converter types: buck, boost and flyback working in the discontinuous conduction mode (DCM), obtained by precise large signal PSpice simulations, calculations based on averaged models and measurements are presented. The parasitic resistances of the converter components are included in the simulations. The specific features of the input characteristics in theDCMand the differences between the continuous conduction mode (CCM) and DCM are discussed.