An Adaptive Internal Model for Load Frequency Control Using Extreme Learning Machine

Adelhard Beni Rehiara (Hiroshima University)
He Chongkai (Hiroshima University)
Yutaka Sasaki (Hiroshima University)
Naoto Yorino (Hiroshima University)
Yoshifumi Zoka (Hiroshima University)

TELKOMNIKA (Telecommunication Computing Electronics and Control)
Vol 16, No 6: December 2018

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.