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Information Journal Paper

Title

INDUCTION MOTOR ELECTRIC PARAMETERS ESTIMATION USING ARTIFICIAL NEURAL NETWORKS AND ITS APPLICATION IN INDUSTRIAL LOAD MODELING

Pages

  19-30

Keywords

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Abstract

 Load modeling is widely used in power system studies. Two types of modeling, namely, static and dynamic, are employed. The current industrial practice is the static modeling. Static models are algebraic equations of active and reactive power changes in terms of voltage and frequency deviations. In this paper, a component based on static modeling is employed in which the aggregate model is derived based on the sensitivity coefficients and participation factors of load components. As an induction motor comprises a significant portion of industrial loads, Artificial Neural Network (ANN) is employed to derive its static model readily from nameplate data as accurately as possible.

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    APA: Copy

    YOUSEFI, G.R., & SEYFI, H.. (2001). INDUCTION MOTOR ELECTRIC PARAMETERS ESTIMATION USING ARTIFICIAL NEURAL NETWORKS AND ITS APPLICATION IN INDUSTRIAL LOAD MODELING . ESTEGHLAL, 19(2), 19-30. SID. https://sid.ir/paper/5933/en

    Vancouver: Copy

    YOUSEFI G.R., SEYFI H.. INDUCTION MOTOR ELECTRIC PARAMETERS ESTIMATION USING ARTIFICIAL NEURAL NETWORKS AND ITS APPLICATION IN INDUSTRIAL LOAD MODELING . ESTEGHLAL[Internet]. 2001;19(2):19-30. Available from: https://sid.ir/paper/5933/en

    IEEE: Copy

    G.R. YOUSEFI, and H. SEYFI, “INDUCTION MOTOR ELECTRIC PARAMETERS ESTIMATION USING ARTIFICIAL NEURAL NETWORKS AND ITS APPLICATION IN INDUSTRIAL LOAD MODELING ,” ESTEGHLAL, vol. 19, no. 2, pp. 19–30, 2001, [Online]. Available: https://sid.ir/paper/5933/en

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