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Research on Reactive Power Optimization Based on Immunity Genetic Algorithm

DOI: 10.1007/11816157_72
Source: DBLP

ABSTRACT This paper proposed a new kind of immune genetic algorithm (IGA) according to the current algorithms solving the reactive
power optimization. The hybrid algorithm is applied in reactive power optimization of power system. Adaptive crossover and
adaptive mutation are used according to the fitness of individual. The substitution of individuals is implemented and the
multiform of the population is kept to avoid falling into local optimum. The decimal integer encoding and reserving the elitist
are used to improve the accuracy and computation speed. The flow chart of improved algorithm is presented and the parameter
of the immune genetic algorithm is provided. The procedures of IGA algorithm are designed. A standard test system of IEEE
30-bus has been used to test. The results show that the improved algorithm in the paper is more feasible and effective than
current known algorithms.

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