Application of improved genetic algorithms for loss minimisation in power system

Abstract

This paper presents the application of improved genetic algorithms (IGA) for optimal reactive power planning in loss minimisation scheme. In this study, IGA engine was developed to implement the optimisation of reactive power planning. The selection and steady state elitism combined with the conventional anchor spin techniques are incorporated into the traditional genetic algorithms (GA) for the development of the IGA. In each probing, identical initial population is supplied to the mechanism of IGA and traditional GA in order to have consistency during the initial population. The proposed IGA technique was tested on the IEEE reliability test system (IEEE-RTS), and revealed that the total loss has been significantly reduced. Comparative studies on the results obtained from the IGA with respect to the traditional GA, indicating that IGA outperformed the traditional GA in terms of accuracy and number of iteration. Consecutive efforts can be made to further explore the flexibility and capability of the developed IGA to be implemented in solving other optimisation problems in power system.