KaydedilenlerDerginizi ekleyin

Dergiler / Turkish Journal of Electrical Engineering and Computer Science / 2009 / Cilt: 17 - Sayı: 1

Voltage Control of Self-Excited Induction Generator using Genetic Algorithm

Dheeraj JOSHI
Kanwarjit Singh SANDHU
Mahender Kumar SONI
Sayfa
87–97
Yayın Tarihi
2009-01-01
DOI
—
🏛️Bu makalenin bibliyografik verileri ve tam metin bağlantısı DergiPark üzerinden sağlanmıştır.
DergiPark Kaydı ↗
✨

Yapay Zeka Hızlı Bakış & Çıkarımlar

AI Insight
⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

A close agreement between the computed and experimental results confirms the validity of the approach adopted.

📌 3 Maddede Bu Makale

🎯
Amaç & Hipotez:Self-excited induction generators (SEIG) are found to be most suitable candidate for wind energy conversion application required at remote windy locations.
📊
Temel Bulgular & Veri:A new methodology based upon Genetic Algorithm (GA) is proposed to compute the steady state performance of the model including core loss branch.
💡
Sonuç & Katkı:A close agreement between the computed and experimental results confirms the validity of the approach adopted.
🔬Tür:Uygulamalı Anket & Alan Araştırması
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Asychronous generators · Genetic Algorithm · Self-excited induction generator

Özet

Self-excited induction generators (SEIG) are found to be most suitable candidate for wind energy conversion application required at remote windy locations. Such generators are not able to maintain the terminal voltage with load as, a literature survey reveals, the voltage profile falls sharply with load. In this paper an attempt has been made to improve the voltage profile of a self-excited induction generator. A new methodology based upon Genetic Algorithm (GA) is proposed to compute the steady state performance of the model including core loss branch. Further efforts are made to control the terminal voltage under loaded conditions. Simulated results using proposed modeling have been compared with experimental results. A close agreement between the computed and experimental results confirms the validity of the approach adopted.

Abstract

Self-excited induction generators (SEIG) are found to be most suitable candidate for wind energy conversion application required at remote windy locations. Such generators are not able to maintain the terminal voltage with load as, a literature survey reveals, the voltage profile falls sharply with load. In this paper an attempt has been made to improve the voltage profile of a self-excited induction generator. A new methodology based upon Genetic Algorithm (GA) is proposed to compute the steady state performance of the model including core loss branch. Further efforts are made to control the terminal voltage under loaded conditions. Simulated results using proposed modeling have been compared with experimental results. A close agreement between the computed and experimental results confirms the validity of the approach adopted.

🔖

Bu Makaleye Atıf Yap

JOSHI, D., SANDHU, K. S., SONI, M. K. (2009). Voltage Control of Self-Excited Induction Generator using Genetic Algorithm. Turkish Journal of Electrical Engineering and Computer Science, Cilt: 17 - Sayı: 1, 87–97. https://ajindex.com/articles/188983

📄 Tam Metin PDF Okuyucu

📄

PDF görüntüleyici hazırlanıyor...

Kaynakça (6)

  1. S. S. Murthy, O. P. Malik, and A.K.Tandon, “Analysis of self -excited induction generators,” Proc. IEE,vol. 129,pt. C, no. 6,pp. 260-265, 1982. L. Quazene and G. McPherson, “Analysis of the isolated induction generator,” IEEE Trans. Power Apparatus and Systems, vol. PAS-102, no. 8, pp. 2793-2798, 1983. G. Raina and O. P. Malik, “Wind energy conversion using a self-excited induction generator,” IEEE Trans. Power Apparatus and Systems, vol. PAS-102, no. 12,pp. 3933-3936,1983.
  2. A. K. Tandon, S. S. Murthy and C. S. Jha, “New method of computing steady-state response of capacitor self-excited induction generator,” IE (I) Journal-EL, vol. 65, pp. 196-201,1985. N. H. Malik and S. E. Haque, “Steady-state analysis and performance of an isolated self-excited induction generator,” IEEE Trans. Energy Conversion, vol. EC-1, no.3, pp.134-139, 1986. T. F. Chan, “Analysis of self-excited induction generators using an iterative method,” IEEE Trans. Energy Con- version, vol. 10, no. 3,pp. 502-507,1995. K. S. Sandhu and S. K. Jain, “Operational aspects of self-excited induction generator using a new model,” Electric Machines and Power Systems, vol. 27, no. 2, pp. 169-180,1999. K. S. Sandhu, “Iterative model for the analysis of self-excited induction generators,” Electric Power Components and Systems, vol. 31, no. 10, pp. 925-939, 2003. S.M. Alghuwainem, “Steady state analysis of induction generator self excited by a capacitor in parallel with a saturable reactor,” Electric Machines and Power Systems, vol 26, pp. 617-625, 1998. J. A. Barrado and R. Grino, “Voltage and frequency control for a self excited induction generator using a three phase four wire electronic converter,” Proc. Power Electronics and Motion Control Conference, ISBN:1-4224-0121-6,2006.
  3. B. Singh, S. S. Murthy and S. Gupta, “STATCOM based voltage regulator for self excited induction generator feeding non linear loads,” Industrial Electronics Society, IECON, pp. 709-714, 2003.
  4. D. Joshi, K. S. Sandhu and M. K. Soni, “Constant voltage constant frequency operation for a self-excited induction generator”, IEEE Trans. Energy Conversion, vol. 21, no. 1, pp. 228-234, 2006.
  5. D. E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning, Asia: Pearson Education, H. G. Beyer and K. Deb, “On self-adaptive features in real-parameter evolutionary algorithms”, IEEE Transactions on Evolutionary Computation, 5 (3). 250-270, 2001
  6. K. Deb, A. Anand, and D. Joshi, “A computationally efficient evolutionary algorithm