Reactive power optimization and voltage control using an improved genetic algorithm

Abstract

This paper presents an improved dynamic genetic algorithm (IDGA) for reactive power optimization and voltage control. The problem is formulated as a mixed integer, nonlinear optimization problems considering both continuous and discrete control variables. The objective of optimization is minimizing active power losses while maintaining the quality of voltages. During evolution process, the crucial parameters, including mutation and crossover rate, are adjusted dynamically in order to get the optimal global solution. The IEEE standards 14 and 30 bus systems were used as test systems to demonstrate the applicability and efficiency of the proposed method. The results, compared with classical genetic algorithm and previous approaches reported in the literature, show that IDGA could find high-quality solutions with more reliability and efficiency.