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).
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Related Author
LI Chao
ZHU Kaiyu
LIN Jikeng
HAO Lili
KAN Yizhou
XUE Yusheng
XUE Feng
WANG Yuhong
Related Institution
College of Energy and Electrical Engineering, Hohai University
College of Electronics and Information Engineering, Tongji University
College of Electrical Engineering & Control Science, Nanjing Tech University
State Grid Electric Power Research Institute (NARI Group Corporation)
School of Electrical Engineering, Sichuan University