Induction Motor Efficiency Estimation using Genetic Algorithm
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32804
Induction Motor Efficiency Estimation using Genetic Algorithm

Authors: Khalil Banan, Mohammad B.B. Sharifian, Jafar Mohammadi

Abstract:

Due to the high percentage of induction motors in industrial market, there exist a large opportunity for energy savings. Replacement of working induction motors with more efficient ones can be an important resource for energy savings. A calculation of energy savings and payback periods, as a result of such a replacement, based on nameplate motor efficiency or manufacture-s data can lead to large errors [1]. Efficiency of induction motors (IMs) can be extracted using some procedures that use the no-load test results. In the cases that we must estimate the efficiency on-line, some of these procedures can-t be efficient. In some cases the efficiency estimates using the rating values of the motor, but these procedures can have errors due to the different working condition of the motor. In this paper the efficiency of an IM estimated by using the genetic algorithm. The results are compared with the measured values of the torque and power. The results show smaller errors for this procedure compared with the conventional classical procedures, hence the cost of the equipments is reduced and on-line estimation of the efficiency can be made.

Keywords: Genetic algorithm, induction motor, efficiency.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1070989

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2546

References:


[1] K. F. Cheek, P. Pillay, "Impact of Energy Efficient Motors in the Petrochemical Industry on Entergy’s Demand side Management Program”, Electric Power Systems Research 42, Vol. 1, 1997, pp. 11- 15.
[2] P. Pillay, V. Levin, P. Otaduy, J. Kueck, "In-situ Induction Motor Efficiency Determination Using the Genetic Algorithm”, IEEE trans. On Energy Conversion, Vol. 13, No. 4, Dec. 1998, pp. 326-333.
[3] J. D. Kueck, J. R. Gray, R. C. Driver, J. S. Hsu, "Assessment of Available Methods for evaluating In-Service Motor Efficiency”, Report on National Laboratory ORNL-TM-13237 managed by Lockheed Martin Energy Research Corporation, 1996.
[4] IEEE Power Engineering Society, IEEE Standard Test Procedure for Poly phase Induction Motors and Generators, IEEE Std. 112-1991, Dec. 5, 1991
[5] J. C. Hirzel, "Efficiency Measurement and Evaluation of Existing Motors”, IEEE Conf. Paper PCI-83-25, Petroleum and Chemical Industry Conference, 1983.
[6] H.K. Ozturka, O.E. Canyurta, A. Hepbaslib, Z. Utluc "Three Different Genetic Algorithm Approaches to the Estimation of Residential Energy Input/Output Values”, Elsevier, Building and Environment 39, 2004, pp. 807–816.
[7] H.K. Lam, S.H. Ling, F.H.F. Leung, P.K.S. Tam "Function Estimation using a Neural-Fuzzy Network and an Improved Genetic Algorithm”, Elsevier, International Journal of Approximate Reasoning 36, 2004, pp. 243–260.
[8] Marzio Marseguerra, Enrico Zio, Luca Podollini "Model Parameters Estimation and Sensitivity by Genetic Algorithms”, Elsevier, Annals of Nuclear Energy 30, 2003, pp. 1437–1456.