摘要
引入模糊聚类方法识别电力系统同调机群。首先对原有的基于模糊相关自组织数据分析算法(iterativese lf-organ iz ing data ana lys is techn iques a lgorithm,ISODATA)的同调机群识别法的各个控制参数的选取问题进行了大量仿真实验,给出了优化参数取值的一些经验值。特别在如何确定最优分类数的问题上引入了模糊F统计量的方法,并根据电力系统同调识别的特点改进了模糊相关自组织数据分析算法的同调机群识别算法,使其更能适用于工程应用。最后用EPR I_36节点纯交流系统的仿真计算验证了该方法的有效性。
In this paper, the fuzzy clustering method is introduced to identify coherent generator groups in power system. A large number of simulations are performed to choose the control parameters of primary fuzzy ISODATA method, and some experienced values of the optimization parameters are given. The best categorizing number is determined by adopting fuzzy F statistical value. The algorithm is improved according to the features of coherent generator groups identification, which makes it much more adaptive to engineering application. Finally, the simulation on EPRI 36-bus AC system shows the effectiveness of the proposed method.
出处
《电力系统及其自动化学报》
CSCD
北大核心
2006年第6期43-47,共5页
Proceedings of the CSU-EPSA
