Frequency regulation of modern power system using novel hybrid DE-DA algorithm

Sayantan Sinha, Ranjan Kumar Mallick

Abstract


An attempt has been made to regulate the frequency of an interconnected  modern power system using automatic generation control under a restructured market scenario. The system model considered consists of a thermal generation plant coupled with a gas turbine plant in both areas. The presence of deregulated market scenario in an interconnected power system makes it too vulnerable to small load disturbance giving rise to frequency and tie line power imbalances. An attempt has been made to introduce a novel Tilted Integral derivative controller to minimize the frequency and tie line power deviations and restrict them to scheduled values. A maiden attempt has been made to tune the controller gains with the help of a novel hybrid optimization scheme which includes the amalgamation of the exploitative nature of the Differential evolution technique and the explorative attributes of the Dragonfly Algorithm. This hybrid technique is therefore coined as Differential evolution- dragonfly algorithm (DE-DA) technique. Use of some standard benchmark fucntions are made to prove the efficacy of the proposed scheme in tunig the controller gains. The supremacy of the proposed TID controller is examined under two individual market scenarios and under the effect of a step load disturbance. The robustness of the controller in minimizing frequency deviations in the systems is broadly showcased. The superiority of the controller is also proved by comparing it with pre published results.


Full Text:

PDF


DOI: http://doi.org/10.11591/ijaas.v8.i2.pp103-116

Refbacks

  • There are currently no refbacks.


International Journal of Advances in Applied Sciences (IJAAS)
p-ISSN 2252-8814, e-ISSN 2722-2594
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.


Web Analytics View IJAAS Stats