摘要
混沌优化方法利用混沌运动的随机性、规律性、遍历性寻优,能以较大的概率搜索到全局最优点。将一种高精度的混沌优化策略用于电力系统静态负荷模型参数辨识,克服了传统的基于梯度寻优的辨识方法容易陷入局部最优点的不足。此方法使用了三步混沌搜索,并引入随机数来增强遍历性。实际算例的辨识结果证实了此方法在静态负荷模型参数辨识中的有效性和准确性。
Chaotic optimization method searches optima by means of regularity, ergodicity and intrinsic stochastic properties of chaotic motion and can find out global optimum in great probability. A high precision chaotic optimization strategy was applied to parameter identification of power system static load model and the deficiency of traditional methods were effectively overcome which are easily being trapped in local optima. The proposed algorithm uses three search steps and introduces random numbers to enforce ergodicity. The results of a practical example prove its validity and accuracy when applied in parameter identification of static load model.
出处
《系统仿真学报》
EI
CAS
CSCD
北大核心
2006年第10期2742-2745,共4页
Journal of System Simulation
关键词
混沌优化
逻辑映射
静态负荷模型
参数辨识
chaotic optimization
logistic mapping
static load model
parameter identification
