โ Scribed by N.H. Abbasy; S.M. Shahidehpour
No coin nor oath required. For personal study only.
This paper presents a nonlinear programming approach to the power system state estimation problem. The proposed technique combines the estimation, detection and identification steps applied to the classical weighted least square method and rejects the corrupted data while estimating the state of the system. The nonlinear programming approach is compared with least square and linear programming algorithms and the results are presented. This technique is very reliable, efficient, and does not require separate testing of the system observability.
In the LS method, the objective is to minimize the sum of the squares of the weighted deviations of the estimated measurements z from the actual measurements. In order to estimate the actual value of a vector x using n m measurements, we express the objective function as "m [Zi --5(X)] ~ min j(x) = ~ (1) i=1 Oi 2
๐ SIMILAR VOLUMES
The effects of the weighting matrices used in the weighted least squares (WLS) method when applied to the problem of power system state estimation (PSSE) are studied. In particular, the effects of two weighting matrices are examined: the first is the inverse of the covariance matrix of the measureme
A method of multirate nonlinear state obserยฎer design, which can use directly a nonlinear process model in the obserยฎer design without any linear approximation, is presented. The multirate nonlinear state obserยฎer is easy to design and implement, and is computationally efficient. Furthermore, for a