【摘要】 电力系统4大参数辨识是国内各电网公司正积极开展的一项工作,遗传算法(GA)在电力系统参数辨识中得到了成功的应用,但与其他辨识方法相比,GA辨识法所需时间长,效率低。针对该问题,提出了一种新的基于SIMULINK和遗传算法的辨识法——智能辨识法,其基本思想是:通过直接设置系统SIMULINK模型状态变量的初始值,使系统在零时刻即达到初始稳态,减少GA辨识法建立初始稳态所需时间,提高辨识效率。智能辨识法已用于福建电网主要机组励磁系统和调速器系统的参数辨识,辨识结果证明了其有效性和实用性。该辨识法同样适用于电力系统其他参数辨识。更多还原

【Abstract】 As parameter identification problem can be formulated as optimization problem,genetic algorithm(GA) is introduced for parameter identification recently.However,compared with time-domain and frequency-domain methods,the efficiency of the GA-based method is lower because of the excessively long running time of GA-based method.The key reason is that the initial state of the simulation model in SIMULINK is preset to zero,but the initial stable state of the corresponding real system is non-zero.It will take long simulation time for GA-based method to setup the non-zero initial stable state.In the paper,a new Intelligent Identification Method(IIM) based on SIMULINK and genetic algorithm(GA) is proposed.In IIM,the initial values of the state variables of the model system to be identified is set directly according to the sampling data of real system,the model system could get into the non-zero initial stable state at the beginning of the simulation,so that the running time of IIM deducts tremendously and the efficiency of IIM increases.The detailed flow chart of IIM is described.The IIM has been successfully used for excitation system modeling and parameter identification in Fujian Power Corporation of China.The simulation results and field testing given in the paper show that the IIM is superior to other GA-based methods.更多还原