Power system state estimation based on nonlinear programming

State estimation base on a nonlinear programming model is presented (NLSE), which is applied the vectorization mode. We choose the L2 norm estimation as object. The nonlinear programming with equality constraint introduced slack variables, can guarantee the robust of the algorithm and dispose the co...

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Veröffentlicht in:2008 International Conference on Electrical Machines and Systems S. 3996 - 4001
Hauptverfasser: Yang Yude, Deng Lijun
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.10.2008
Schlagworte:
Equations
Iterative algorithms
Mathematical model
Matrix converters
Newton Algorithm
Power measurement
Power system measurements
Power system modeling
Power systems
Reordering algorithm
Sparse matrices
Sparse technology
State estimation
Vectorization mode
Weighted least squares (WLS) state estimation
ISBN:1424438268, 9781424438266
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Zusammenfassung:State estimation base on a nonlinear programming model is presented (NLSE), which is applied the vectorization mode. We choose the L2 norm estimation as object. The nonlinear programming with equality constraint introduced slack variables, can guarantee the robust of the algorithm and dispose the convergence problem. The symmetric coefficient matrix of correction equation can be used by apply the AMD reordering algorithm and LDL T algorithm on the solution, which can speed up the calculation striking. The whole model of nonlinear state estimation applies vectorization form, so the complexity extent is simplified and both versatility and maintainability of code are improved. Numerical simulations use IEEE14, IEEE57, IEEE118, IEEE300, N1047 system to validate the correctness of the proposed model and method.
ISBN:1424438268
9781424438266