Performance of three phase 11-level inverter with reduced number of switches using different PWM techniques

Nair, Ramesh Nammily; Mahalakshmi, R.; Thampatty, K. C. Sindhu

doi:10.1109/tapenergy.2015.7229648

Cited by 14 publications

(10 citation statements)

References 8 publications

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“…Which is describe single phase circuit configuration for any loads like inductive, capacitive and resistive, here in this fig.1 Resistive load is connected. In this new topology 8 switches are used for each different level [5].…”

Section: New Topology Of Multilevel Invertermentioning

confidence: 99%

“…Here for each level four switches are operating simultaneously. Also here S1', S2', S3'and S4' switches operating states for each level is inverse from S1, S2, S3 and S4 switches [5]. Shown in table 1.…”

Section: International Journal Of Advance Engineering and Research Dementioning

confidence: 99%

“…Alternating staircase waveforms with higher harmonics produce from conventional bipolar inverter [5]. Thus the multilevel inverters (MLI) are developed.…”

Section: Introductionmentioning

confidence: 99%

“…Here for basic topology 11-level MLI used components like in diode clamped MLI require 20 switches, 90 diodes and 10 main DC-bus capacitors per phase, which is produce a staircase as the output voltage wave form, in capacitor clamped MLI require 20 switches, 45 clamping capacitors and 10 main DC-bus capacitors per phase, and cascaded H-bridge inverter require only 24 switches per phase for produce the output wave form [5]. Now here this paper is describing the new topology for 11-level MLI, here this topology is used with only 8 switches.…”

Section: Introductionmentioning

confidence: 99%

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Implementation of 11-Level Inverter With Reducing Number of Switches

2016

IJAERD

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Section: New Topology Of Multilevel Invertermentioning

confidence: 99%

Section: International Journal Of Advance Engineering and Research Dementioning

confidence: 99%

“…Alternating staircase waveforms with higher harmonics produce from conventional bipolar inverter [5]. Thus the multilevel inverters (MLI) are developed.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Implementation of 11-Level Inverter With Reducing Number of Switches

2016

IJAERD

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“…It is a challenge in power electronics field to obtain higher number of levels, less harmonics AC output from the light weight inverter with less number of switches. Hence different control strategies have been adopted by researchers [7][8][9][10]. The percentage of Total Harmonic Distortion (%THD) of a multi-level inverter output is a very important factor in measuring its performance.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Multi Level Current SourceInverter for LowTorque Applications

Mahalakshmi

Deepa

Thampatty

2018

JGE

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This paper proposes a control strategy for a multi-level Current Source Inverter (CSI) which acts as an interface between renewable energy sources such as wind, solar, fuel cell etc. and grid/loads to satisfy the power demand. The control strategy aims to reduce the number of switches and the number of input sources used in the CSI and obtain an output with least Total Harmonic Distortion (THD) and increased number of levels (13). The proposed system uses seven switches and three current sources to obtain a 13 level output. The new control strategy is tested in different operating conditions in a split phase single phase low torque induction motor. The Simulation model is developed in MATLAB/Simulink. THDs of 13 level outputs from current source inverter is analyzed and compared in detail. A comparative analysis of the proposed CSI with existing CSI topologies is made. It is observed that the proposed topology uses less number of switches and inductors to obtain different levels at the output. The proposed inverter provides better performance with satisfactory results.

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Introducing AI applications in engineering education (PBL): An implementation of power generation at minimum wind velocity and turbine faults classification using AI

Khan,

Alam,

Rizvi

et al. 2023

Comp Applic In Engineering

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This article explores the integration of artificial intelligence (AI) applications into project‐based learning (PBL) education as a means to enhance students' education. Specifically, the implementation of AI in the context of power generation is addressed, focusing on achieving power generation at minimum wind velocity and classifying turbine faults using AI techniques. The researchers have proposed a novel generating unit which is going to generate 1 KW of electric power at a specific flow rate of air and the generated power will be stored in the battery bank through the charge controller and then the load is driven from the battery through an inverter. Iron or core losses (Hysteresis, Eddy Current losses) can be acknowledged as one of the major reasons for the inefficiency of conventional generators, therefore anovel coreless model generator was proposed which also improved efficiency and reduces drag. Wind Turbine prototype was fabricated and deployed for the testing and validation of the proposed novel design. The design produced outstanding power ratings and electrical generation characteristics compared with other existing strategies at minimal air flow. Results proved that the proposed coreless axial flux generator has the capability to produce a better power rating compared with the existing wind turbine generators. Proposed Axial flux achieved 10.73 watt power at wind velocity at around 80 rpm. At a wind velocity of 10 m/s and around 800 rpm 313–330 kwh was produced by the proposed generator while the conventional generator produced around 300 kwh. The proposed generator design performed 35% better in terms of production efficiency under load and no load conditions. Moreover, faults in turbines are very common due to the various temperatures, therefore the faults have been classified using state‐of‐the‐art AI‐based classifiers. A comparison of space vector modulation (SVM) and Naive Bayes classifiers was performed in the study to classify wind turbine faults. It was found that both classifiers performed well in achieving high accuracy. SVM achieved a slightly higher accuracy of 0.9861 compared with Naive Bayes, which achieved an accuracy of 0.967. Based on the results, it can be inferred that SVM may be a more suitable classifier for wind turbine fault classification. The case study results demonstrated the potential of AI applications in PBL education, offering students a multidisciplinary learning experience that enhances their technical knowledge, problem‐solving skills, and teamwork abilities.

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Performance of three phase 11-level inverter with reduced number of switches using different PWM techniques

Cited by 14 publications

References 8 publications

Implementation of 11-Level Inverter With Reducing Number of Switches

Implementation of 11-Level Inverter With Reducing Number of Switches

Analysis of Multi Level Current SourceInverter for LowTorque Applications

Introducing AI applications in engineering education (PBL): An implementation of power generation at minimum wind velocity and turbine faults classification using AI

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