Load frequency control in power systems via GA based IMC and model order reduction

In the conventional two degree of freedom (TDF)-internal model controller (IMC) design, obtaining the optimal value of tuning parameter is much more difficult task. In most of the cases either formula based conventional techniques or trial and error based approaches have been suggested. In this paper, the approach of genetic algorithm (GA) is proposed to obtain optimized value of tuning parameter used in TDF-IMC controller design. The different second-order reduced-models, (which are considered as internal/predictive models for TDF-IMC structure) using different model reduction techniques are intentionally derived to perform a comparative study. The applicability of the proposed technique has been illustrated with the help of a numerical example. The simulation results clearly indicate much improvement in the response of load frequency control (LFC) during load disturbance and in the presence of uncertainties, over some other existing results.