现代重工持续发力中国电气市场

Study on Parameter Identification of Excitation System Based on Chaos Genetic Algorithm

新世纪以来,中国电力市场的高速发展为众多国外电气制造企业创造了机会,他们争先恐后地搭上了中国电力市场＂快车＂。如今,中国发电量更是稳居全球之首,其发展潜力不言而喻。不管是＂先来者＂,还是＂后到者＂,国内外电气企业纷纷凭借日新月异的技术,力争在这场中国电力市场发展大潮中＂分一杯羹＂。现代重工（中国）投资有限公司系韩国现代重工集团在中国的全资子公司,成立于2006年5月,总部位于上海。

Aiming at the problems of parameter identification of excitation system, which needs long time and is easy to get into the local optimization, chaos genetic algorithm（CGA） for parameter identification of excitation system is presented in the paper. CGA develops the SGA and overcomes its disadvantages. Chaos sequence is combined with standard genetic algorithm（SGA） in two aspects. One is to initialize the population of genetic algorithm （GA）, which can guarantee the initial values of identified parameters to be ergodic in the ranges; the other is to reconstruct the newer individual after crossover and mutation by chaos sequence, which can prevent premature convergence and local optimal solution. In order to verify the effect, two methods of parameter identification, i.e., CGA and SGA are used and compared in MEC3300T excitation system. From the results, it is shown that the output curves to actual excitation system and identified system by using CGA is better than SGA. The model obtained through CGA approach reflects the physical properties of the real system and may be more useful for power engineers.