Harmonic Reduction Comparison In Multilevel Inverters For Industrial Application

This paper presents the simulation studies adapters’ type of multi-level consists of H-bridge cascade imposed to reduce harmonic for high power applications.Applications of multilevel converters are able to reduce the number of harmonics contained in the system of low-voltage electrical distribution.This study deals with a comparative analysis between the three stages of imposed multilevel inverter circuits cascaded H-bridge inverter with sinusoidal pulse width modulation (SPWM) strategies.Used five to nine levels SPWM inverter with the functions of the switching of the principles of mitigation of harmonic components of the output voltage of the multilevel converters operation.The simulation results show that the total harmonic distortion of the effort (THDV) adapters for multiple outputs levels and decreased both realized on the basis of the content of the low standard IEC

Vector Control Drive Of Permanent Magnet Synchronous Motor Based Dsspace DS1103 Implementation

This paper presented a vector controlled drives of permanent Magnet Synchronous Motor (PMSM) by using Proportional-Integral (PI) Speed controller based dSPACE implementation. The concept of vector control is applied to PMSM to obtain linear dynamics similar to that of a DC motor. The model consist of two control loops, hysteresis current controller is used for inner loop current control and PI controller for outer loop speed control. PI speed controller selected due to simplicity compare to fuzzy, neutral etc. to make sure dSPACE DS1103 successfully implemented. The PMSM vector control algorithm for a theoretical basic has been verified by experimental results and created a rapid control prototype environment by using MATLAB/ Simulink and the DS1103 DSP of dSPACE

Vector Controlled Drives Of Permanent Magnet Synchronous Motor Using Pi Speed Controller For Long Cable Application

This paper present a vector controlled drives of Permanent Magnet Synchronous Motor (PMSM) by using Proportional-Integral (PI) Speed controller for long cable application. As known, long cable caused an over voltage problem at motor terminal and could be double from the pulse output voltage at inverter terminal. This caused instability of the speed performances. PI speed controller is implemented to drive a PMSM with different cables length to investigated the speed performances, load disturbances and parameter variations of the system. Hysteresis current controller is used for inner loop current control and PI controller for outer loop speed control. Simulation results are provided to show performances on different cable length driving a PMSM

DETECTION OF HIGH IMPEDANCE FAULT USING A PROBABILISTIC NEURAL-NETWORK CLASSFIER

In this paper, a simple and efficient method for detection high impedance fault (HIF) on power distribution systems using an intelligent approach the probabilistic neural network (PNN) combined with wavelet transform technique is proposed. A high impedance fault has impedance enough high so that conventional overcurrent devices, like overcurrent relays and fuses, cannot detect it. While low impedance faults, which include comparatively large fault currents are easily detected by conventional overcurrent devices. Both frequency and time data are needed to get the exact information to classify and detect no fault from HIF. In the proposed method, DWT is used to extract feature of the no fault and HIF signals. The features extracted which comprise the energy of detail and approximate coefficients of the voltage, current and power signals calculated at a chosen level frequency are utilized to train and test the probabilistic neural network (PNN) for a precise classification of no fault from HIFs

Adaptive Neural Subtractive Clustering Fuzzy Inference System for the Detection of High Impedance Fault on Distribution Power System

High impedance fault (HIF) is abnormal event on electric power distribution feeder which does not draw enough fault current to be detected by conventional protective devices. The algorithm for HIF detection based on the amplitude ratio of second and odd harmonics to fundamental is presented. This paper proposes an intelligent algorithm using an adaptive neural- Takagi Sugeno-Kang (TSK) fuzzy modeling approach based on subtractive clustering to detect high impedance fault. It is integrating the learning capabilities of neural network to the fuzzy logic system robustness in the sense that fuzzy logic concepts are embedded in the network structure. It also provides a natural framework for combining both numerical information in the form of input/output pairs and linguistic information in the form of IF– THEN rules in a uniform fashion. Fast Fourier Transformation (FFT) is used to extract the features of the fault signal and other power system events. The effect of capacitor banks switching, non-linear load current, no-load line switching and other normal event on distribution feeder harmonics is discussed. HIF and other operation event data were obtained by simulation of a 13.8 kV distribution feeder using PSCAD. The results show that the proposed algorithm can distinguish successfully HIFs from other events in distribution power syste

Using Probabilistic Neural Network for Classification High Impedance Faults on Power Distribution Feeders

An intelligent approach probabilistic Neural Network (PNN) combined with advanced signalprocessing techniques such as Discrete Wavelet Transform (DWT) is presented for detection High impedance faults (HIFs) on power distribution networks. HIFs detection is usually very difficult using the common over current devices, both frequency and time data are needed to get the exact information to classify and detect no fault from HIF. In this proposed method, DWT is used to extract features of the no fault and HIF signals. The features extracted using DWT which comprises the energy, standard deviation, mean, root mean square and mean of energy of detail and approximate coefficients of the voltage, current and power signals are utilized to train and test the PNN for a precise classification of no fault from HIFs. The proposed method shows that it is more convenient for HIF detection in distribution systems with ample varying in operating cases

Detection of high impedance faul on power distribution system using probabilistic neural network

High impedance fault (HIF) is abnormal event currents on electric power distribution feeder which does not draw sufficient fault current to be detected by conventional protective devices. The waveforms of normal and HIF current signals on electric power distribution feeders are investigated and analysis the characteristic of HIF. The purpose of this study is to use a new feature which indicates HIF faults. Fast Fourier Transformation (FFT) is used to extract the feature of the fault signal and other power system events, odd harmonics frequency components of the phase currents are analyzed. The effect of capacitor banks and other events on distribution feeder harmonics is discussed. The features extracted are using to train and test the probabilistic neural network (PNN) which is used as the classifier to detect HIF from other normal event in power distribution system

Detecting High Impedance Fault in Power Distribution Feeder with Fuzzy Subtractive Clustering Model

An irregular activity on electric power distribution feeder, which does not draw adequate fault current to be detected by general protective devices, is called as High impedance fault (HIF). This paper presents the algorithm for HIF detection based on the amplitude of third and fifth harmonics of current, voltage and power. This paper proposes an intelligent algorithm using the Takagi Sugeno- Kang (TSK) fuzzy modeling approach based on subtractive clustering to detect the high impedance fault. The Fast Fourier Transformation (FFT) is used to extract the feature of the faulted signals and other power system events. The effect of capacitor bank switching, non-linear load current, no-load line switching and other normal event on distribution feeder harmonics is discussed. The HIF and other operation event data were obtained by simulation of a 13.8 kV distribution feeder using PSCAD. It is evident from the outcomes that the proposed algorithm can effectively differentiate the HIFs from other events in power distribution feeder

Comparative study of different PWM control scheme for three-phase three-wire shunt active power filter

Instantaneous reactive power theory was the most popular control theory used when dealing with harmonics compensations. In conjunction with the instantaneous theory, switching signal generation techniques plays an important role to ensure the correct compensation signal injected in the system. Therefore, this paper discussed on comparative study of five (5) methods used in instantaneous theory namely; p-q method, modified p-q, d-q method, p-q-r method and vectorial with three (3) types. of signal generation namely; carrier current control, hysteresis current control and space vector modulation control. Continuous reductions of the total harmonics distortion (THD) are expected at the supply current when applied different types of switching technique. The compnrison was examining using MATLAB/Sirnulink (MLS) environment

COMPARISON PERFORMANCE OF INDUCTION MOTOR USING SVPWM AND HYSTERESIS CURRENT CONTROLLER

This paper presents the comparative performances of three phase induction motors using space vector pulse width modulation (SVPWM) and hysteresis current controller. An indirect field orientation is applied to ensure decoupling control between torque and flux of the induction motor. The hysteresis current controller is built in with PI speed controller and three hysteresis current bands while the SVPWM system is embedded with the two control loops, the inner current control loop and the outer speed control loop using PI controller. Both systems were run and tested using MATLAB/SIMULINK software. The simulation results demonstrate that the SVPWM can improve the quality of the stator current and reduce the torque ripple while maintaining the other performance characteristics of the system