电力系统状态估计多算法融合  

Fusion algorithm for state estimation in power systems

作　　者：方航[1] 葛愿[1] 余诺[1] 汪石农[1] 

机构地区：[1]安徽工程大学电气工程学院,安徽芜湖241000

出　　处：《计算机工程与设计》2015年第2期502-506,共5页Computer Engineering and Design

基　　金：国家自然科学基金项目(61203034);安徽省自然科学基金项目(1308085QF120);安徽省级优秀青年人才基金重点项目(2012SQRL086ZD;2013SQRL035Z)

摘　　要：为解决复杂电网大数据背景下单一算法难以满足状态估计要求的问题,提出一种电力系统状态估计多算法融合系统。基于数据融合思想,将加权最小二乘法、快速分解法、量测状态变换法与Sigmoid函数法相互融合实现电网状态估计,支持串行融合模式和并行融合模式。实验结果表明,融合算法使得估计结果保留了各自算法的优点,避免了单一算法的缺点,提高了状态估计的精度和效率。To deal with the problem that a single algorithm fails to meet the requirements of the state estimation with big data, an algorithm fusion system was proposed.The proposed system was based on the idea of data fusion,including the method of weighted least square algorithm,the fast decoupled method,the state estimation algorithm based on measurement transformation and the Sigmoid function.The fusion algorithm can be run on the serial fusion model and parallel fusion model.Experimental results show that the proposed method has the advantages of each algorithm,avoids the shortcomings of single algorithm and improves the accuracy and efficiency of the state estimation.

关 键 词：电力系统 状态估计 数据融合 融合模式 算法 

分 类 号：TP273.5[自动化与计算机技术—检测技术与自动化装置]