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International Journal of Power Electronics and Drive Systems (IJPEDS)

IJPEDS
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Published by Institute of Advanced Engineering and Science

ISSN : - EISSN : 20888694 DOI : -

Core Subject : Engineering,

Control & Systems Engineering Electrical & Electronics Engineering

International Journal of Power Electronics and Drive Systems (IJPEDS, ISSN: 2088-8694, a SCOPUS indexed Journal) is the official publication of the Institute of Advanced Engineering and Science (IAES). The scope of the journal includes all issues in the field of Power Electronics and drive systems. Included are techniques for advanced power semiconductor devices, control in power electronics, low and high power converters (inverters, converters, controlled and uncontrolled rectifiers), Control algorithms and techniques applied to power electronics, electromagnetic and thermal performance of electronic power converters and inverters, power quality and utility applications, renewable energy, electric machines, modelling, simulation, analysis, design and implementations of the application of power circuit components (power semiconductors, inductors, high frequency transformers, capacitors), EMI/EMC considerations, power devices and components, sensors, integration and packaging, induction motor drives, synchronous motor drives, permanent magnet motor drives, switched reluctance motor and synchronous reluctance motor drives, ASDs (adjustable speed drives), multi-phase machines and converters, applications in motor drives, electric vehicles, wind energy systems, solar, battery chargers, UPS and hybrid systems and other applications.

Arjuna Subject : -

Articles 2,594 Documents

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Implementation of SVM for five-level cascaded H-Bridge multilevel inverters utilizing FPGA Maher Abd Ibrahim Al jewari; Auzani Jidin; Siti Azura Ahmad Tarusan; Mohammed Rasheed
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 11, No 3: September 2020
Publisher : Institute of Advanced Engineering and Science

The Space Vector Modulation SVM technique has won large acceptance for AC drive applications. However the utilization of multilevel inverters connected with SVM by Digital signal processor (DSP) raise the intricacy of control algorithm or computational load, increases of the obtaining distortions output voltage. The development of SVM in multilevel inverters may offer higher numbers of switching vectors for acquiring further enhancements of output voltage performances and implement by using Field Programmer Gate Array (FPGA), investigate lower Total Hormonic Distortion (THD). This paper reports the performance evaluation of SVM for five-level of Cascaded H-Bridge Multilevel Inverter CHMI using MATLAB/Simulink, which is sampled at the minimum sampling time, i.e. DT = 5 μs. The switching signals for driving insulated gate bipolar transistor (IGBTs) which are stored in MATLAB workspaces, are then used to be programmed in FPGA using a Quartus II software. Which can be stated the lower THD of the simulation result is about 14.48% for five-level CHMI and experiment result is about 14.31% for five-level CHMI at modulation index M_i=0.9. The error percentage between the simulation results and experimental results of the fundamental output voltage in SVM is small which is approximately less than 1 %.

Multiple Switching Patterns for SHEPWM Inverters Using Differential Evolution Algorithms Ayong Hiendro
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 1, No 2: December 2011
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (503.857 KB)

An investigation on multiple patterns for both odd and even number of switching angles in a three-phase selective harmonic elimination pulse width modulation (SHEPWM) inverter is presented. The switching patterns are examined and classified on the basis of the harmonic performance of the waveforms output from the inverter. Differential evolution algorithms are employed to calculate the optimum switching angles. Selected cases are verified experimentally by a digital signal processor-based hardware implementation. The experimental results show that all types of the patterns offer low harmonic distortions on the inverter output after filtering. However, one type gives better harmonic performance is identified.DOI: http://dx.doi.org/10.11591/ijpeds.v1i2.101

Intelligent Control for Doubly Fed Induction Generator Connected to the Electrical Network Anass Bakouri; Hassane Mahmoudi; Ahmed Abbou
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 7, No 3: September 2016
Publisher : Institute of Advanced Engineering and Science

In this paper we are interested in optimizing the wind power capture, using the Doubly Fed Induction Generator (DFIG). This machine is preferred to other types of variable speed generator because of their advantages in economic terms and control. The Artificial Neural Network (ANN) based on Direct Torque Control (DTC) which is used to control the electromagnetic torque in order to extract the maximum power, The main objective of this intelligent technique is to replace the conventional switching table by a voltage selector based on (ANN) to reduce torque and flux ripples. Moreover, the fuzzy logic controller is used to grid side converter to keep DC link voltage constant, and also to achieve unity power factor operation. The main advantage of the two control strategies proposed in this paper is that they are not influenced by the variation of the machine parameter. The pitch control is also presented to limit the generator power at its rated value. Simulation results of 1,5 MW, for (DFIG) based Wind Energy Conversion System (WECS) confirm the effectiveness and the performance of the global proposed approaches.

Analysis and Design of Single Phase High Efficiency Transformer less PV Inverter Topology Jayalakshmi N. S.; Ankit Kumar; Ashish Kumar
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 9, No 2: June 2018
Publisher : Institute of Advanced Engineering and Science

An inclination towards renewable energy resources has been increased due to the requirement of clean environment and to satisfy the increasing power demand for the long run. A grid connected system requires the availability of a transformer in its power conversion stages that provides galvanic isolation between the grid and the power system. But inclusion of transformer results in making the system bulky and more expensive. In this paper different transformer-less PV inverter topologies are analyzed by comparing their efficiency, leakage current and THD of load current using MATLAB/Simulink environment. In order to achieve maximum power, maximum power point tracking (P&O algorithm) is used. From the simulation results, modified HB-ZVR is found to have minimum leakage current and constant common mode voltage with higher efficiency. Also, the hardware results are obtained for modified HB-ZVR topology.

Application of artificial neural network in sizing a stand-alone photovoltaic system: a review Ahmad Fateh Mohamad Nor; Suriana Salimin; Mohd Noor Abdullah; Muhammad Nafis Ismail
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 11, No 1: March 2020
Publisher : Institute of Advanced Engineering and Science

Artiﬁcial Neural Network (ANN) techniques are becoming useful in the current era due to the vast development of the current computer technologies. ANN has been used in various fields especially in the field of science and technology. One of the advantage that makes ANN so interesting is the ANN’s ability to learn the input and output relationship even though the relationship is non-linear. In addition, ANN is also useful for modelling, optimization, prediction, forecasting, and controlling systems. The main objective of this paper is to present a review of the ANN techniques for sizing a stand-alone photovoltaic (PV) system. The review in this paper shows the potential of ANN as a design tool for a stand-alone PV. In addition, ANN is very useful to improve the sizing process of the stand-alone PV system. The sizing process is of paramount importance to a stand-alone PV system in order to make sure the system can generate ample electrical energy to supply the load demand.

A New Control Method for Grid-Connected PV System Based on Quasi-Z-Source Cascaded Multilevel Inverter Using Evolutionary Algorithm Hamid Reza Mohammadi; Ali Akhavan
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 6, No 1: March 2015
Publisher : Institute of Advanced Engineering and Science

In this paper, a new control method for quasi-Z-source cascaded multilevel inverter based grid-connected photovoltaic (PV) system is proposed. The proposed method is capable of boosting the PV array voltage to a higher level and solves the imbalance problem of DC-link voltage in traditional cascaded H-bridge inverters. The proposed control system adjusts the grid injected current in phase with the grid voltage and achieves independent maximum power point tracking (MPPT) for the separate PV arrays. To achieve these goals, the proportional-integral (PI) controllers are employed for each module. For achieving the best performance, this paper presents an optimum approach to design the controller parameters using particle swarm optimization (PSO). The primary design goal is to obtain good response by minimizing the integral absolute error. Also, the transient response is guaranteed by minimizing the overshoot, settling time and rise time of the system response. The effectiveness of the new proposed control method has been verified through simulation studies based on a seven level quasi-Z-Source cascaded multilevel inverter.

Neural Adaptive Kalman Filter for Sensorless Vector Control of Induction Motor Ghlib Imane; Messlem Youcef; Gouichiche Abdelmadjid; Chedjara Zakaria
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 8, No 4: December 2017
Publisher : Institute of Advanced Engineering and Science

This paper presents a novel neural adaptive Kalman filter for speed sensorless field oriented vector control of induction motor. The adaptive observer proposed here is based on MRAS (model reference adaptive system) technique, where the linear Kalman filter calculate the stationary components of stator current and the rotor flux and the rotor speed is calculated with an adaptive mechanism. Moreover, to improve the performance of the PI classical controller under different conditions, a novel adaptation scheme based on ADALINE (ADAptive LInear NEuron) neural network is used. It offers a solution to the PI parameters to stabilize automatically about their optimum values and speed estimation to converge quicker to the real. The proposed adaptive Kalman filter represents a good comprise between estimation accuracy and computationally intensive. The simulation results showed the robustness, efficiency, and superiority of the proposed scheme compared to the classical method even in low speed region.

Fault detection and classification in wind turbine by using artificial neural network N. F. Fadzail; S. Mat Zali
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 10, No 3: September 2019
Publisher : Institute of Advanced Engineering and Science

Wind turbine is one of the present renewable energy sources that has become the most popular. The operational and maintenance cost is continuously increasing, especially for wind generator. Early fault detection is very important to optimise the operational and maintenance cost. The goal of this project is to study fault detection and classification for a wind turbine (WT) by using artificial neural network (ANN). In this project, a single phase fault was placed at 9 MW doubly-fed induction generator (DFIG) WT in MATLAB Simulink. The WT was tested under different conditions, i.e., normal condition, fault at Phase A, Phase B and Phase C. The simulation results were used as inputs in the ANN model for training. Then, a new set of data was taken under different conditions as inputs for ANN fault classifier. The target outputs of ANN fault classifier were set as ‘0’ or ‘1’, based on the fault condition. Results obtained showed that the ANN fault classifier outputs had followed the target outputs. In conclusion, the WT fault detection and classification method by using ANN were successfully developed.

Adaptive Fuzzy Logic Control of Wind Turbine Emulator Bouzid Mohamed Amine; Zine Souhila; Allaoui Tayeb; Massoum Ahmed
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 4, No 2: June 2014
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (323.54 KB)

In this paper, a Wind Turbine Emulator (WTE) based on a separately excited direct current (DC) motor is studied. The wind turbine was emulated by controlling the torque of the DC motor. The WTE is used as a prime mover for Permanent Magnet Synchronous Machine (PMSM). In order to extract maximum power from the wind, PI and Fuzzy controllers were tested. Simulation results are given to show performance of proposed fuzzy control system in maximum power points tracking in a wind energy conversion system under various wind conditions. The strategy control was implemented in simulation using MATLAB/Simulink.DOI: http://dx.doi.org/10.11591/ijpeds.v4i2.5809

Different Control Schemes for Sensor Less Vector Control of Induction Motor Srinivas Gangishetti; Tarakalyani Sandipamu
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 8, No 2: June 2017
Publisher : Institute of Advanced Engineering and Science

This paper deals with the design of different control schemes for sensorless vector control of induction motor.Induction motor is most widely used A.C. Motor but the major draw back is flux and torque cannot be controlled individually.This can be obtained by implementing sensorless vector control methods.The control strategy of induction motor is by different controllers like conventional control methods and artificial intelligence control methods.The conventional control methods are sensitive to parameter changes and will not be accurate. This paper proposes to design a controller to over come the above draw backs by using intelligent control techniques like fuzzy logic, artificial neutral networks (ANN) and genetic algorithm (GA).The above conventional control methods are compared with intelligent control techniques. The simulation studies are carried out using Matlab/Simulink and the wave forms for speed, torque and voltage components for various controlles are plotted. Numerical analysis for speed and torque components considering parameters like peakover shoot and peak time are presented.

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