Comparison Of Cascaded H-bridge Inverters for Harmonic Mitigation Considering Various Loads

2017 ◽  
Vol 8 (1) ◽  
pp. 10
Author(s):  
Suresh Natarajan ◽  
R. Samuel Rajesh
Keyword(s):  
Fourier Analysis ◽  
Lower Order ◽  
Optimization Technique ◽  
Harmonic Distortion ◽  
Evolutionary Optimization ◽  
Total Harmonic Distortion ◽  
Electrical Parameters ◽  
Evolutionary Optimization Technique ◽  
Motor Load ◽  
Harmonic Mitigation

This paper compares the reduction of harmonics in various level cascaded H-bridge inverters. The switching angles for the cascaded H-bridge inverter were calculated by evolutionary optimization technique. Fourier analysis is used to determine the switching angles for the desired electrical parameters. Lower order harmonics such as third, fifth, seventh, ninth and eleventh order harmonics were taken into consideration to reduce the total harmonic distortion. Simulation was done for thirteen, fifteen and seventeen level cascaded H-bridge inverters using Matlab. Total harmonic distortion of voltage and current for R, RL and  Motor load were analyzed.

scholarly journals Selective Harmonic Elimination of an Eleven Level Inverter Using Whale Optimization Technique

2018 ◽  
Vol 9 (4) ◽  
pp. 1944 ◽  
Author(s):  
Srikanta Kumar Dash ◽  
Byamakesh Nayak ◽  
Jiban Ballav Sahu
Keyword(s):  
Lower Order ◽  
Optimization Technique ◽  
Harmonic Distortion ◽  
Optimization Techniques ◽  
Total Harmonic Distortion ◽  
Multilevel Inverters ◽  
Harmonic Elimination ◽  
Whale Optimization ◽  
Selective Harmonic Elimination ◽  
Cascaded Multilevel Inverter

Reduction of total harmonic distortion in multilevel inverters is a difficult optimization problem that includes nonlinear transcendent equations having more than one local minima.This paper deals with the harmonic elimination of cascaded multilevel inverter with equal D.C. sources using a new optimization technique. The objective of this paper is to find the best combination of switching angles to minimize the lower order harmonics and the total harmonic distortion is reduced. For this purpose, a new optimization techniques i.e. whale optimization technique is considered.This algorithm is applied to an 11-level cascaded H-bridge inverter.Results shows that WOA gives better results and effectively minimizes the THD and lower order harmonics

Predetermination of Higher Order Harmonics by Dual Phase Analysis

2014 ◽  
Vol 573 ◽  
pp. 13-18 ◽  
Author(s):  
V.J. Vijayalakshmi ◽  
C.S. Ravichandran ◽  
A. Amudha
Keyword(s):  
Phase Analysis ◽  
Lower Order ◽  
Optimization Technique ◽  
Harmonic Distortion ◽  
Harmonic Spectrum ◽  
Higher Order ◽  
Accurate Estimation ◽  
Dual Phase ◽  
Order Spectrum ◽  
Order Components

Previous research was mainly concentrated on eliminating the selected lower order harmonics depending on the level of inverter which was assumed to be high. The harmonics may be present even in the higher order also. The analysis of harmonic spectrum by Finite Fourier Transform yields a very accurate result for lower order harmonics. For obtaining accurate Total Harmonic Distortion (THD) value and the harmonic spectrum, inclusion of higher order harmonics is essential. The method for accurate estimation is proposed in this paper. In normal practice, the higher order harmonics present in the output of the inverter are suppressed by using filters. In order to obtain more optimized higher order harmonics, it is necessary to obtain an accurate assessment of the higher order spectrum. The higher order spectrum is predetermined by proposed technique termed as Dual Phase Analysis (DPA) so as to obtain more optimized switching angles with the application of any Optimization Technique. This is an effective tool to analyze the various higher order components of the harmonic spectrum.

Psoriasis Lesion Detection Using Hybrid Seeker Optimization Based Image Clustering

2021 ◽  
Vol 17 ◽  
Author(s):  
Manoranjan Dash ◽  
Narendra Digambar Londhe ◽  
Subhojit Ghosh ◽  
Ritesh Raj ◽  
Rajendra Sonawane
Keyword(s):  
Swarm Intelligence ◽  
Clustering Algorithms ◽  
Optimization Technique ◽  
Evolutionary Optimization ◽  
Superior Performance ◽  
Initial Population ◽  
Psoriatic Lesion ◽  
Lesion Segmentation ◽  
Evolutionary Optimization Technique ◽  
Psoriasis Lesion

Background: In recent years, there has been a massive increase in the number of people suffering from psoriasis. For proper psoriasis diagnosis, psoriasis lesion segmentation is a pre-requisite for quantifying the severity of this disease. However, segmentation of psoriatic lesion cannot be evaluated just by visual inspection as they exhibit inter and intra variability among the severity classes. Most of the approaches currently pursued by dermatologists are subjective in nature. The existing conventional clustering algorithm for objective segmentation of psoriasis lesion suffers from limitations of premature local convergence. Objective: An alternative method for psoriatic lesion segmentation with the objective analysis is sought in the present work. The present work aims at obtaining optimal lesion segmentation by adopting an evolutionary optimization technique which possesses a higher probability of global convergence for psoriasis lesion segmentation. Method: A hybrid evolutionary optimization technique based on the combination of two swarm intelligence algorithms; namely Artificial Bee Colony and Seeker Optimization algorithm has been proposed. The initial population for the hybrid technique is obtained from the two conventional local-based approaches i.e. Fuzzy C-means and K-means clustering algorithms. Results: The initial population selection from the convergence of classical techniques reduces the effect of population dynamics on the final solution and hence yields precise lesion segmentation with Jaccard Index of 0.91 from 720 psoriasis images. Conclusion: The performance comparison reflects the superior performance of the proposed algorithm over other swarm intelligence and conventional clustering algorithms.

Forecast of Power Quality Index Based on the Discrete Fourier Decomposition and AR Model

2013 ◽  
Vol 732-733 ◽  
pp. 1420-1426 ◽  
Author(s):  
Cong Xi Wen ◽  
Shan Gao ◽  
Xiang Ning Xiao ◽  
Yong Hai Xu ◽  
Shun Tao
Keyword(s):  
Fourier Transform ◽  
Fourier Analysis ◽  
Discrete Fourier Transform ◽  
Harmonic Distortion ◽  
Low Frequency ◽  
Total Harmonic Distortion ◽  
Ar Model ◽  
Frequency Noise ◽  
Discrete Fourier Analysis ◽  
Frequency Components

A method of autoregressive (AR) based on discrete Fourier analysis is proposed to forecast the indexes of unbalance factor and total harmonic distortion. The discrete Fourier transform of the index sequence is analyzed and the low frequency components are extracted. Autoregressive method is applied to forecast each low frequency component. Through inverse discrete Fourier transform, the forecasting low frequency components are inverted to forecasting sequence of the index in time domain. Actual data is used to test this method and the results show that discrete Fourier analysis is possible to reduce the influence of high frequency noise and that the AR method based on Fourier transform can effectively forecast the indexes of unbalance factor and total harmonic distortion.

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