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Non-Cartesian Frame Transformation-Based Control of a Three-Phase Power Converter During Unbalanced Voltage Dip – Part II: Simulation And Experiment

Abstract

The paper presents a control method for the three-phase power converter operating under unbalanced grid voltage conditions. The method uses a new transformation to the non-Cartesian frame, which makes the controlled current vector components balanced in this frame even if originally the three-phase current is referenced as unbalanced. Furthermore, Park’s transformation makes the controlled variables constant, which allows to apply proportional–integral terms as current controllers independent of the required control target. Several control targets known from literature have been analyzed with regard to the required new transformation parameters, and the transformation parameters for all targets have been found. Simulation results are shown to prove the theoretical analysis, and the experimental test results are presented as practical validation of the proposed use of the non-Cartesian frame in control.

Open access
A Review on Big Data Management and Decision-Making in Smart Grid

Abstract

Smart grid (SG) is the solution to solve existing problems of energy security from generation to utilization. Examples of such problems are disruptions in the electric grid and disturbances in the transmission. SG is a premium source of Big Data. The data should be processed to reveal hidden patterns and secret correlations to extrapolate the needed values. Such useful information obtained by the so-called data analytics is an essential element for energy management and control decision towards improving energy security, efficiency, and decreasing costs of energy use. For that reason, different techniques have been developed to process Big Data. This paper presents an overview of these techniques and discusses their advantages and challenges. The contribution of this paper is building a recommender system using different techniques to overcome the most obstacles encountering the Big Data processes in SG. The proposed system achieves the goals of the future SG by (i) analyzing data and executing values as accurately as possible, (ii) helping in decision-making to improve the efficiency of the grid, (iii) reducing cost and time, (iv) managing operating parameters, (v) allowing predicting and preventing equipment failures, and (vi) increasing customer satisfaction. Big Data process enables benefits that were never achieved for the SG application.

Open access
Analysis of Direct Torque Control with Space Vector Modulation for Synchronous Reluctance Motor Motion Control Applications and a Comparison with Other Torque-Control Algorithms

Abstract

Motion control is facing an increasing popularity in the present research activities. Owing to the expected wide spreading of motion control applications, it can be predicted that the advancements in the field of electric motor drives will have a high level of influence on the new results in the field of motion control. The synchronous reluctance motor drives mean an excellent and yet cost-effective solution for actuators in motion control applications. In this article, the direct torque control with space vector modulation is analysed as a possible candidate for synchronous reluctance motor motion control applications. Its torque-control performance is investigated as a function of torque-control sample time, and a comparison of the torque ripples is made with other torque-control algorithms by an FFT analysis.

Open access
Analysis of Transients in a Three-Level DC–DC Flying Capacitor Converter. Time Domain Approach

Abstract

The paper considers a discrete state-space model for transients in a three-level flying capacitor DC–DC converter. A transition matrix is obtained for a pulse width modulation (PWM) period. The matrix elements are expanded into a power series using a selected small parameter. The matrix eigenvalues that determine the natural balancing dynamics transients are presented in the form of power series as well. Four separate transients are constructed based on four possible PWM period initial states (topologies). Inductor current and capacitor voltage transients are found for the voltage source power-up as the arithmetic average of the four separate transients. The discrete solutions are replaced by continuous ones. The resulting transients that are elementary functions of the circuit parameters, PWM period, and voltage reference demonstrate good agreement with the simulation results.

Open access
An Investigation of Direct Torque Control and Hysteresis Current Vector Control for Motion Control Synchronous Reluctance Motor Applications

Abstract

Synchronous reluctance motor drives are one of the most attractive alternatives of permanent magnet synchronous motor drives and induction motor drives in the field of conventional industrial and household applications. This tendency is expected to be continued in the case of motion control applications as well. This article investigates two torque-control algorithms that are possible candidates for motion control synchronous reluctance motor applications. The examined torque-control algorithms are direct torque control (DTC) and hysteresis current vector control (HCVC).

Open access
Multiobjective Improved Particle Swarm Optimisation for Transmission Congestion and Voltage Profile Management using Multilevel UPFC

Abstract

This paper proposes a multiobjective improved particle swarm optimisation (IPSO) for placing and sizing the series modular multilevel converter-based unified power flow controller (MMC-UPFC) FACTS devices to manage the transmission congestion and voltage profile in deregulated electricity markets. The proposed multiobjective IPSO algorithm is perfect for accomplishing the close ideal distributed generation (DG) sizes while conveying smooth assembly qualities contrasted with another existing algorithm. It tends to be reasoned that voltage profile and genuine power misfortunes have generous upgrades along ideal speculation on DGs in both the test frameworks. The proposed system eliminates the congestion and the power system can be easily used to solve complex and non-linear optimisation problems in a real-time manner.

Open access
Automated Guided Vehicles by Permanent Magnet Synchronous Motor: Future of In-house Logistics

Abstract

Material handling and logistics management that involve transportation of work pieces on production floor are important aspects to manufacturing that affect productivity and efficiency. Tow vehicles that are manually driven are currently used for this purpose. These processes can be better performed through automation. Automated guided vehicle (AGV) is an apt solution. AGVs are unmanned autonomous vehicles that can be programmed to perform versatile tasks. AGVs available in market are imported and hence have high capital cost and increased lead time for spare parts. Proposed AGV is built with a capital cost that is less than half of the existing AGVs. Its design is made indigenously, with most of its parts locally sourced. It can achieve a speed of 0.83 m/s, with a pulling capacity of 1,300 kg. Its rechargeable batteries sustain four hours of continuous operation for one complete discharge. It has been tested and found to effectively replace tow vehicles.

Open access
An Overview of Carrier-based Modulation Methods for Z-Source Inverter

Abstract

Single-stage energy converters, in particular, the Z-Source Inverter (ZSI) or impedance source inverter, has gained significant attention in the recent years. ZSI ensures flexible energy conversions (dc–dc, dc–ac, ac–ac and ac–dc) because of its unique ability to boost the output voltage in typical renewable energy systems. The impedance network integrated between the energy source and the load contributes to the unique functionality of the ZSI. As substantial research has been conducted on the ZSI, this article provides a review on the operation of ZSI. The article initially examines the various topologies commonly adopted for the application of the ZSI. Subsequently, details of the various modulation methods that are commonly used to obtain the voltage boosting using ZSI are documented. Additionally, the phenomenon of neutral point formation, which is an important impediment to the adoption of multilevel ZSIs and the limitation of the modulation methods, is explained.

Open access
Derivation of Motor Mean Phase Currents in PMSM Drives Operating with Low Switching-to- Fundamental Frequency Ratio

Abstract

Pulse width modulation (PWM) of inverter output voltage causes the waveforms of motor phase currents to consist of distinctive ripples. In order to provide suitable feedback for the motor current controllers, the mean value must be extracted from the currents’ waveforms in every PWM cycle. A common solution to derive the mean phase currents is to sample their value at the midpoint of a symmetrical PWM cycle. Using an assumption of linear current changes in steady PWM subintervals, this midpoint sample corresponds to the mean current in the PWM cycle. This way no hardware filtering or high-rate current sampling is required. Nevertheless, the assumption of linear current changes has been recently reported as over simplistic in permanent magnet synchronous motor (PMSM) drives operating with low switching-to-fundamental frequency ratio (SFFR). This, in turn, causes substantial errors in the representation of the mean phase currents by the midpoint sample. This paper proposes a solution for deriving mean phase currents in low SFFR PMSM drives, which does not rely on the linear current change assumption. The method is based on sampling the currents at the start point of a PWM cycle and correcting the sampled value using a model-based formula that reproduces the current waveforms. Effectiveness of the method is verified by simulation for an exemplary setup of high-speed PMSM drive. The results show that the proposed method decreases the error of determining the mean phase currents approximately 10 times when compared to the classical midpoint sampling technique.

Open access
Novel Fuzzy-Based Self-Adaptive Single Neuron PID Load Frequency Controller for Power System

Abstract

This paper proposes a newly adaptive single-neuron proportional integral derivative (SNPID) controller that uses fuzzy logic as an adaptive system. The main problem of the classical controller is lacking the required robustness against disturbers, measurement noise in industrial applications. The new formula of the proposed controller helps in fixing this problem based on the fuzzy logic technique. In addition, the genetic algorithm (GA) is used to optimize parameters of the SNPID controller. Because of the high demands on the availability and efficiency of electrical power production, the design of robust load-frequency controller is becoming increasingly important due to its potential in increasing the reliability, maintainability and safety of power systems. So, the proposed controller has been applied for load-frequency control (LFC) of a single-area power system. The effectiveness of the proposed SNPID controller has been compared with the conventional controllers. The simulation results show that the proposed controller approach provides better damping of oscillations with a smaller settling time. This confirms its superiority against its counterparts. In addition, the results show the robustness of the proposed controller against the parametric variation of the system.

Open access