Steady-State Analysis of Parallel-Operated Self-Excited Induction Generators Supplying an Unbalanced Load

Abstract

This paper proposed a multi-objective genetic algorithm (MOGA) based approach for determining the steady-state performance characteristics of three-phase self-excited induction generators (SEIGs) operating in parallel and supplying an unbalanced load. The symmetrical component theory is used for the transformation of a complex three-phase generatorscapacitances-load system to a simple equivalent circuit. The MOGA has been employed for the determination of unknown variables by minimizing the impedance module of the equivalent circuit. Using this approach, effects of various parameters on the terminal voltage control characteristics are examined for two parallel SEIGs with C2C connection under a single phase load.K e y w o r d s: induction generator, self-excitation, parallel operation, voltage control, multi-objective genetic algorithm

Evolutionary Algorithm for Calculating Available Transfer Capability

“…It represents an accidental bit variation of an individual, generally with a constant probability for each bit within a population. The mutation probability can further vary depending on the size of the population, application and preferences of the explorer [17], or be a fixed value, which is often kept during the whole genetic algorithm is used for each generation [20].…”