基于改进混沌优化算法的船舶综合负荷模型参数辨识

摘要

On-line parameter identification is the main method of power system load modeling, and the optimization al-gorithm is mainly used in the identification method. Firstly, the flow of the chaos optimization algorithm is improved, the function of the automatic reduction of the parameter search scope is added, and the steps of the generation of a chaotic se-quence are reduced. The optimization results of the test function show that the improved algorithm can greatly improve the search speed based on the guaranteed precision. Then, the improved algorithm is applied to the parameter identification of ship integrative load model. The simulation results show that the algorithm is fast and accurate. Through the analysis of the simulation results, it is pointed out that, for the load model parameter identification, the reasonable reduction of the paramet-er optimization range is helpful to improve the accuracy of the algorithm.%参数在线辨识是目前电力系统负荷建模的主要手段,而在辨识方法上主要使用了优化类算法.首先改进以往混沌优化算法的流程,增加参数搜索范围自动缩小的功能,减少一次混沌序列生成的步骤.对测试函数的优化结果表明改进算法在保证精度的基础上大大提高了寻优速度.然后,将该改进算法应用到了船舶综合负荷模型的参数辨识上,仿真结果说明该算法寻优速度快,并且有良好的辨识精度.通过对仿真结果的分析指出,对于负荷模型参数辨识,合理缩小参数寻优范围有助于提高算法的精度.