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Sensitive equipment and non-linear loads are now more common in both the industrial/commercial sectors and the domestic environment. Because of this a heightened awareness of power quality is developing amongst electricity users. Therefore, power quality is an issue that is becoming increasingly important to electricity consumers at all levels of usage. This article presents the fuzzy system to determine the power quality. The performance of three-phase induction motor is observed for different power quality conditions in laboratory. The power quality is in terms of voltage is intentionally disturbed by means of three-phase motor alternator set and chopper circuit. It is observed that the fuzzy system is able to make correct diagnosis of power quality. It is also observed that as the power quality become poor, the motor efficiency decreases, causing significant rise in power input to meet the rated load demand, and thereby rise in electric bill.
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Tom
Strony
61--66
Opis fizyczny
Bibliogr. 14 poz., rys.
Twórcy
autor
- Maharashtra State Electricity Transmission Co. Ltd, 400 kV Testing subdivision, Khadka, Bhusaval, India-425 201
autor
autor
Bibliografia
- 1. Dashand P.K., Salama M.M.A., and Mishra S.: Classification of power system disturbances using fuzzy expert system and a Fourier linear combiner. IEEE Trans.Power Delivery, vol. 15, pp. 472–477, Apr. 2000.
- 2. Santoso S., Lamoree J., Grady W.M., Powers E.J., and Bhatt S.C.: A scalable PQ event identification system. IEEE Trans.Power Delivery, vol. 15, pp. 738–742, Apr. 2000.
- 3. Angrisani L., Daponte P., and D’Apuzo M.: Wavelet network based detection and classification of transients. IEEE Trans. Instrum. And Meas., vol. 50, no. 5, pp. 1425–1430, Oct. 2001.
- 4. Santoso S.,Grady W.M., and Powers E.J.: Characterization of distribution power quality events with Fourier and wavelet transforms. IEEE Trans. Power Delivery, vol. 15, no. 1, pp. 247–254, Jan. 2000.
- 5. Wang Y.J.: Analysis of effects of three phase voltage unbalance on induction motors with emphasis on the angle of the complex voltage unbalance factor. IEEE Trans. Energy Conversion, vol. 16, no. 3, pp. 270–275, Sep. 2001.
- 6. Styvaktakis E., Bollen M.H.J., and Gu Y.H.: Expert system for classification and analysis of power system events. IEEE Trans. Power Delivery, vol. 17, no. 2, pp. 423–428, Apr. 2002.
- 7. Wael R., Ibrahim A., and Morcos M.M.: Artificial intelligence and advanced mathematical tools for power quality applications: A survey. IEEE Trans. Power Delivery, vol. 17, no. 2, pp. 668–673, Apr. 2002.
- 8. Wael R., Ibrahim A., and Morcos M.M.: A power quality perspective to system operational diagnosis using fuzzy logic and adaptive techniques. IEEE Trans. Power Delivery, vol. 18, no. 3, pp. 903–909, Jul. 2003.
- 9. Wa n g M . , a n d M a m i s h e v A . V. : Classification of power quality events using optimal time frequency representations part 1: Theory. IEEE Trans. Power Delivery, vol. 19, no. 3, pp. 1488–1495, Jul. 2004.
- 10. Gerek Ö.N., and Ece D.G.: Power quality event analysis using higher order cumulants and quadratic classifiers. IEEE Trans. Power Delivery, vol. 21, no. 2, pp. 883–889, Apr. 2006.
- 11. Ballal M.S., Khan Z.J., Suryawanshi H.M. and Sonolikar R.L.: Induction Motor: Fuzzy System for the detection of winding insulation condition and bearing wear. Electric Power Components and System, Vol. 34, 2, Feb. 2006, pp. 159–171.
- 12. Ballal M.S., Khan Z.J., Suryawanshi H.M. and Sonolikar R.L. : Adaptive neural fuzzy inference system for the detection of interturn insulation and bearing wear fault in induction motor. IEEE Transaction on Industrial Electronics, Vol. 54, 1, Feb. 2007, pp. 250–258.
- 13. Grady W.M., and Santoso S.: Understanding power system harmonics. IEEE Power Engineering Review, pp. 8–11, Nov. 2001.
- 14. Jang J.S.R. and Gulley N.: Fuzzy-Logic Toolbox for use with MATLAB. The Math Works Inc., Natick, Massachusetts, pp. 2.25–2.4, 1995
Typ dokumentu
Bibliografia
Identyfikator YADDA
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