两级线性迭代策略下的混合状态估计的研究

Research on hybrid state estimation under two-level linear iteration strategy

基于卡尔曼滤波及线性迭代基本原理,针对当前电力系统混合状态估计精度低、滤波效果差及收敛能力低等问题,提出了一种基于两级线性迭代的电力系统混合状态估计的研究策略:第1级利用相量测量单元(PMU)的量测数据进行线性估计;第2级将其与传统量测值相结合用于状态估计,并利用PMU的高频特性对两级的量测数据进行多次迭代采样。将其在IEEE 14和IEEE 57节点测试系统进行测试,并将结果与其他混合模型比较,结果表明,该策略的估计精度、数据收敛度及量测参数误差均优于其他混合模型。

A study strategy of hybrid state estimation for power system based on two-stage linear iteration and basic principles of Kalman filter and linear iteration was proposed,it is designed to solve the problems of lower accuracy of power system mixed state estimation,poorer filtering effect and weaker convergence ability,etc.In the first stage,the measurement data of phasor measurement unit(PMU)were used for linear estimation.In the second stage,where the content of the first stage was combined with the traditional measurement value to estimate the state,and the high frequency characteristic of PMU was used to sample the two-stage measurement data iteratively.Which was tested in IEEE 14 and IEEE 57 bus test system,and the results were compared with other hybrid models.The results showed that the estimation accuracy,data convergence and measurement parameter error of this strategy were better than those of other hybrid models.