抗不良杠杆量测的稳定收敛状态估计方法

不良杠杆量测使得传统的含有不良数据辨识的状态估计方法失效,严重降低了状态估计的精度,为了能够自动排除不良杠杆量测的干扰,同时保证状态估计计算的数值稳定性和收敛性,提出了抗不良杠杆量测的稳定收敛状态估计方法。在利用等价权原理并统一量测残差尺度的基础上,提出了采用标准化残差的指数型权函数,并基于此得到抗差状态估计模型。该模型能够根据量测残差自动修正量测权重,具有较强地抵抗不良杠杆量测的能力,能有效保证算法的数值稳定性和收敛速度。分别采用3节点和IEEE118节点算例对该方法的特点进行了验证。

Stable Convergence State Estimation Method for Bad Leverage Measurements

Traditional state estimation methods which include bad data identification fail in bad leverage measurements, resulting the degradation of state estimation precision. In order to exclude the interference of bad leverage measurements automatically, while ensuring the numerical stability and convergence of state estimation calculation, this paper proposes a stable convergence state estimation method for bad leverage measurements. On the base of utilizing the principle of equivalent weight and unifying the scales of measurement residuals, this paper presents the exponential weight function by using the standardized residual and builds the model of robust state estimation. This model can correct the weight of measurement automatically according to the measurement residual, therefore, shows the strong ability to resist bad leverage measurements and effectively guarantee the numerical stability and convergence speed. The characteristics of the proposed method are demonstrated on the 3-bus and the 118-bus systems.