Electric Power Quality Optimization Using Genetic Algorithm

Electrical power networks experience a growing proportion of electrical loads that degrade the electric power quality. Such loads occur due to the operation of electrical power equipment based on silicon rectifiers, arc steel furnaces, electrolysis plants, and blooming mills. At the same time, the number of high-tech consumers sensitive to electric power quality degradation is increasing: computers, computer network hardware, telecommunications equipment, medical, banking, and office equipment. This study considers the application of a genetic algorithm to optimize electric power quality. The selected genetic algorithm uses a fixed number of mating pairs per generation instead of the crossover rate. Each mating pair produces two offspring. Parental pairs were selected by the elitist and exclusion selection methods. The objective function of active power losses considers the distribution of compensating power filters in the electrical power network, permissible voltage levels, and active power losses due to non-sinusoidal voltage. A program has been developed that selects the power of compensating power filters in the electrical power network nodes, as well as their installation locations, where active power losses will be minimal.