Hybrid Immune Genetic Method for Dynamic Reactive Power Optimization

Abstract

In this paper, a hybrid optimization technique, in which immune genetic algorithm is combined with interior point method, is proposed for solving the dynamic reactive power optimization problem. The switching time limits of shunt capacitors and transformer tap ratios, which make the problem to be dynamic, are only related with discrete variables. In the proposed hybrid method, the immune genetic algorithm deals with the discrete variables, such as the adjustment schedules of shunt capacitors or transformer tap ratios; interior point method deals with the continuous variables, such as the voltage/reactive profiles of generators. An improved encoding scheme of the immune genetic algorithm is also introduced so that the time-related dynamic constraints of discrete variables can be satisfied automatically. The proposed method has been applied to IEEE 14 bus system over a 24-hour period to demonstrate its effectiveness.