摘要
基于云理论的知识表示,首次将云理论与电力系统有效结合来解决配电系统原始数据不足的问题。在对原始数据进行模糊聚类的基础上,提出了一种组合云发生器,将正向云发生器和逆向云发生器有效组合成一种闭环结构。结合配电网负荷数据的实际特点,在组合云发生器中加入了约束方程组和系统工况数据补充两个单元,保证了生成的负荷数据既能够包含系统的大部分情况,又不会出现实际不会发生的不可能数据,生成的云滴很好的反映了负荷数据所具有的模糊性和随机性。并在此基础上进行了基于T-S模糊模型的负荷辨识,将辨识结果与当前通用的几类模型对比显示了所提出方法的有效性和实用性。
Based on the knowledge representation of cloud theory,power system and cloud theory were integrated effectively to solve the load origin data shortage of distribution system.With the origin data fuzzy clustered,a combination cloud generator was put forward,which combined forward cloud generator and backward cloud generator to a close-loop structure.Considering of the distribution system load data characteristic,the restriction equations and system data complement unit were joined to combination cloud generator,which ensured that the created load data covered most of the system situation without impossible data.The cloud drop reflected the fuzziness and randomness of the load data.The loads were identified by T-S fuzzy model based on the generation cloud drop.The identification result implies the effectiveness and usefulness of the approach by the contrast with some kinds of universal load model.
出处
《系统仿真学报》
EI
CAS
CSCD
北大核心
2008年第2期341-344,共4页
Journal of System Simulation
基金
国家自然科学基金资助项目(60325311
60274017
60572070
60534010)
辽宁省自然科学基金(20022030)
关键词
云模型
组合云发生器
配电系统
负荷建模
模糊T-S模型
cloud model
combination clouds generator
distribution system
load model
fuzzy T-S model
