基于预测—校正内点法的WLAV输电网参数估计

A Weighted Least Absolute Value Transmission Network Parameter Estimation Based on Predictor-Corrector Interior Point Method

针对基于加权最小二乘法(WLS)参数估计难于处理不良数据且数值稳定性差的不足,提出加权最小绝对值(WLAV)参数估计方法。在原对偶内点法(PDIPM)的基础上,通过每次迭代中增加预测—校正两步的少许计算量,利用2阶信息对中心参数动态调整,保证解的迭代过程高阶逼近中心路径,从而减少了迭代次数,节省了计算时间。结合输电网参数估计法,利用WLAV估计出不良数据和可疑支路的运行状态,使抗差、参数估计和拓扑结构辨识在计算中一次完成。最后,对IEEE标准系统和国内某省级电网进行参数估计试验,与含不良数据辨识的WLS方法进行比较。

Due to the drawbacks of bad data and numerical condition of the weighted least squares( WLS) transmission network parameter estimation,a weighted least absolute value( WLAV) method is proposed. The proposed method is based on the predictor-corrector primal dual interior point method( PCPDIPM),which ensures the iteration point closer to the center track and improve the convergence property,therefore the number of iterations and computing time is reduced. The bad data and correct state of dubious branch can be obtained by the identical algorithm of parameter estimation and can be completed in one calculation process. Finally,the IEEE standard test systems and a provincial power grid are employed to verify the usefulness of the proposed approach. Comparison results between the proposed method and the widely used WLS algorithm with bad data identification module illustrate that the proposed method have high convergence speed and numerical stability.