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Yutaka Sasaki
Hiroshima University
Computer Science & IT

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An Adaptive Internal Model for Load Frequency Control Using Extreme Learning Machine Adelhard Beni Rehiara; He Chongkai; Yutaka Sasaki; Naoto Yorino; Yoshifumi Zoka
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 16, No 6: December 2018
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v16i6.11553

Abstract

As an important part of a power system, a load frequency control has to be prepared with a better controller to ensure internal frequency stability. In this paper, an Internal Model Control (IMC) scheme for a Load Frequency Control (LFC) with an adaptive internal model is proposed. The effectiveness of the IMC control has been tested in a three area power system. Results of the simulation show that the proposed IMC with Extreme Learning Machine (ELM) based adaptive model can accurately cover the power system dynamics. Furthermore, the proposed controller can effectively reduce the frequency and mechanical power deviation under disturbances of the power system.
Co-Authors Adelhard Beni Rehiara He Chongkai Naoto Yorino Yoshifumi Zoka