Determination of arc parameters by using particle swarm optimization algorithm

One of the important components of high-voltage networks is the insulators which take a specific shape according to the voltage and environmental conditions in terms of pollution and humidity, the pollution on the insulator surface produce dry band on the surface of the insulator, which results electric sparks in that area. One of the most important problems in high pressure insulators is its surface sparks due to pollution. The electric discharge on the contaminated insulator is generally when the surface of the insulator is wet, due to fog and dew or rain. An electric flashover phenomenon is a condition of electric discharge in the air or other environments that are usually non-conductor. An electric flashover is generated when the electricity flow is transmitted through the air between two conductors that are not directly in contact. This flashover depends on the voltage, electrical conductivity of the environment and the distance between two conductors. The electrical flashover in contaminated insulators has not been reported through a precise mathematical model yet. The main problem is the definition of flashover constants, which occurs in dry bands and rising voltage more than critical value. In this study, a particle swarm algorithm optimization (PSO) has been proposed for determination of flashover constants which is simulated by using results and laboratory values obtained from artificial insulators in various papers. First, Obenhaus’s well-known model for occurs flashovers in contaminated insulators has been used. Using the PSO algorithm allows the definition of flashover constants and then calculates the critical voltage under conditions of salinity and surface conductivity and compared with the results obtained with the previous methods. The results showed that it is improved in compare of previous methods and the proposed method reduces cost and time than the laboratory method.

Determination of arc parameters by using particle swarm optimization algorithm Keywords:

insulator , Electrical discharge , Electrical flashover , Mathematical model , Obenhaus , Contaminated insulators , Flashover constants , Critical voltage.