一种双线性抗差状态估计方法

传统状态估计方法一般需要求解某个非线性非凸优化问题,并用基于梯度的方法予以求解,因而存在难以保证获得全局最优解、可能收敛困难等问题。文中基于国外学者提出的精确线性化量测方程构建了一种双线性抗差状态估计方法。该方法仅需求解一个线性加权最小绝对值估计问题(等价为线性规划问题)、一个非线性变换以及一个线性加权最小二乘估计问题(二次规划问题),从数学上可保证获得全局最优解,并不存在收敛性问题。最后,通过仿真算例验证了所提方法的有效性。

A Bilinear Robust State Estimation Method for Power Systems

Traditional state estimation approaches need to solve nonlinear and non-convex optimization problems and gradient-based methods are often used to do this. However, the global optimum cannot be guaranteed mathematically and convergence issue may be confronted. This paper proposes a bilinear robust state estimation (BRSE) method based on exactly linearization measurement equations presented by a foreigner. In this method, only a linear weighted least absolute value (WLAV) problem (equivalent to a linear programming problem), a nonlinear transformation, and a linear weighted least squares (WLS) problem (quadratic programming problem) should be solved to ensure global optimum mathematically and no existence of convergence. Finally, simulation results show the effectiveness of the proposed method. This work is supported by National High Technology Research and Development Program of China (863 Program) (No. 2012AA050208), National Natural Science Foundation of China (No. 51407069) and Fundamental Research Funds for the Central Universities (No. 2014QN02).