Performance characteristics and reliability assessment of self‐excited induction generator for wind power generation

Abstract The paper presents the performance analysis‐based reliability estimation of a self‐excited induction generator (SEIG) using the Monte‐Carlo simulation (MCS) method with data obtained from a self‐excited induction motor operating as a generator. The global acceptance of a SEIG depends on its...

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Main Authors: Lokesh Varshney, Aanchal Singh S. Vardhan, Akanksha Singh S. Vardhan, Sachin Kumar, R.K. Saket, P. Sanjeevikumar
Format: Article
Language:English
Published: Wiley 2021-07-01
Series:IET Renewable Power Generation
Subjects:
Online Access:https://doi.org/10.1049/rpg2.12116
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author Lokesh Varshney
Aanchal Singh S. Vardhan
Akanksha Singh S. Vardhan
Sachin Kumar
R.K. Saket
P. Sanjeevikumar
author_facet Lokesh Varshney
Aanchal Singh S. Vardhan
Akanksha Singh S. Vardhan
Sachin Kumar
R.K. Saket
P. Sanjeevikumar
author_sort Lokesh Varshney
collection DOAJ
description Abstract The paper presents the performance analysis‐based reliability estimation of a self‐excited induction generator (SEIG) using the Monte‐Carlo simulation (MCS) method with data obtained from a self‐excited induction motor operating as a generator. The global acceptance of a SEIG depends on its capability to improve the system's poor voltage regulation and frequency regulation. In the grid‐connected induction generator, the magnetizing current is drawn from the grid, making the grid weak. In contrast, in the SEIG stand‐alone operation, an external capacitor arrangement is implemented to render the reactive power support. This capacitor arrangement is connected across the stator terminals during the stand‐alone configuration of SEIG. The capacitor serves two purposes, which include voltage build‐up and power factor improvement. Therefore, the paper deals with obtaining the minimum capacitor value required for SEIG excitation in isolated mode applications, including stand‐alone wind power generation. The SEIG performance characteristics have been evaluated for different SEIG parameters. The simulation and experimental results are then compared and found satisfactory. Then, SEIG reliability is estimated considering the MCS method utilizing SEIG excitation's failure and success rates during experimental work in the laboratory. Finally, the SEIG reliability evaluation is performed considering different wind speeds.
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spelling doaj.art-684ec19fdd234b01bb17d5be33d57bc72022-12-22T04:30:43ZengWileyIET Renewable Power Generation1752-14161752-14242021-07-011591927194210.1049/rpg2.12116Performance characteristics and reliability assessment of self‐excited induction generator for wind power generationLokesh Varshney0Aanchal Singh S. Vardhan1Akanksha Singh S. Vardhan2Sachin Kumar3R.K. Saket4P. Sanjeevikumar5Department of Electrical Engineering Galgotias University Greater Noida Uttar Pradesh IndiaDepartment of Electrical Engineering Shri G.S. Institute of Technology and Science Indore Madhya Pradesh IndiaDepartment of Electrical Engineering Shri G.S. Institute of Technology and Science Indore Madhya Pradesh IndiaDepartment of Electrical Engineering Indian Institute of Technology (BHU) Varanasi Uttar Pradesh IndiaDepartment of Electrical Engineering Indian Institute of Technology (BHU) Varanasi Uttar Pradesh IndiaCenter for Bioenergy and Green Engineering Department of Energy Technology Aalborg University Esbjerg DenmarkAbstract The paper presents the performance analysis‐based reliability estimation of a self‐excited induction generator (SEIG) using the Monte‐Carlo simulation (MCS) method with data obtained from a self‐excited induction motor operating as a generator. The global acceptance of a SEIG depends on its capability to improve the system's poor voltage regulation and frequency regulation. In the grid‐connected induction generator, the magnetizing current is drawn from the grid, making the grid weak. In contrast, in the SEIG stand‐alone operation, an external capacitor arrangement is implemented to render the reactive power support. This capacitor arrangement is connected across the stator terminals during the stand‐alone configuration of SEIG. The capacitor serves two purposes, which include voltage build‐up and power factor improvement. Therefore, the paper deals with obtaining the minimum capacitor value required for SEIG excitation in isolated mode applications, including stand‐alone wind power generation. The SEIG performance characteristics have been evaluated for different SEIG parameters. The simulation and experimental results are then compared and found satisfactory. Then, SEIG reliability is estimated considering the MCS method utilizing SEIG excitation's failure and success rates during experimental work in the laboratory. Finally, the SEIG reliability evaluation is performed considering different wind speeds.https://doi.org/10.1049/rpg2.12116Wind power plantsAsynchronous machinesVoltage controlControl of electric power systemsMonte Carlo methodsMonte Carlo methods
spellingShingle Lokesh Varshney
Aanchal Singh S. Vardhan
Akanksha Singh S. Vardhan
Sachin Kumar
R.K. Saket
P. Sanjeevikumar
Performance characteristics and reliability assessment of self‐excited induction generator for wind power generation
IET Renewable Power Generation
Wind power plants
Asynchronous machines
Voltage control
Control of electric power systems
Monte Carlo methods
Monte Carlo methods
title Performance characteristics and reliability assessment of self‐excited induction generator for wind power generation
title_full Performance characteristics and reliability assessment of self‐excited induction generator for wind power generation
title_fullStr Performance characteristics and reliability assessment of self‐excited induction generator for wind power generation
title_full_unstemmed Performance characteristics and reliability assessment of self‐excited induction generator for wind power generation
title_short Performance characteristics and reliability assessment of self‐excited induction generator for wind power generation
title_sort performance characteristics and reliability assessment of self excited induction generator for wind power generation
topic Wind power plants
Asynchronous machines
Voltage control
Control of electric power systems
Monte Carlo methods
Monte Carlo methods
url https://doi.org/10.1049/rpg2.12116
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