Abstract
This paper presents a new interior point algorithm to solve power system weighted nonlinear L; norm state estimation problems ( IPWNLj). On the basis of the perturbed Karush-Kuhn-Tucker (KKT) conditions of the primal problem, we derive the IPWNL, algorithm for solving the state estimation problems. Compared with the sequential linear programming approach[13] and logarithmic barrier function method[12], the proposed IPWNL, algorithm possesses excellent convergence property. That is, the number of iterations until convergence is roughly constant with system size and measurement redundancy and mostly less than 10. Moreover, it has another valuable property that the convergence of the algorithm is quite insensitive to changes in weighting factors. To greatly enhance the computational efficiency, two schemes of the correction equation are proposed which have been realized by the rearrangement of the correction equation. Simulation experiments on test systems, which range in size from 5 to 1047 buses, have shown that the proposed algorithm has reached the level of practical applications due to its fast and robust property.
| Original language | English |
|---|---|
| Pages (from-to) | 617-623 |
| Number of pages | 7 |
| Journal | IEEE Transactions on Power Systems |
| Volume | 13 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 1998 |
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Keywords
- Interior point methods
- Norm estimation
- Perturbed KKT conditions
- Power system
- State estimation
- Weighted nonlinear L
ASJC Scopus subject areas
- Electrical and Electronic Engineering
Cite this
An interior point method for power system weighted nonlinear li norm static state estimation. / Wei, Hua; Sasaki, H.; Kubokawa, J.; Yokoyama, R.
In: IEEE Transactions on Power Systems, Vol. 13, No. 2, 1998, p. 617-623.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - An interior point method for power system weighted nonlinear li norm static state estimation
AU - Wei, Hua
AU - Sasaki, H.
AU - Kubokawa, J.
AU - Yokoyama, R.
PY - 1998
Y1 - 1998
N2 - This paper presents a new interior point algorithm to solve power system weighted nonlinear L; norm state estimation problems ( IPWNLj). On the basis of the perturbed Karush-Kuhn-Tucker (KKT) conditions of the primal problem, we derive the IPWNL, algorithm for solving the state estimation problems. Compared with the sequential linear programming approach[13] and logarithmic barrier function method[12], the proposed IPWNL, algorithm possesses excellent convergence property. That is, the number of iterations until convergence is roughly constant with system size and measurement redundancy and mostly less than 10. Moreover, it has another valuable property that the convergence of the algorithm is quite insensitive to changes in weighting factors. To greatly enhance the computational efficiency, two schemes of the correction equation are proposed which have been realized by the rearrangement of the correction equation. Simulation experiments on test systems, which range in size from 5 to 1047 buses, have shown that the proposed algorithm has reached the level of practical applications due to its fast and robust property.
AB - This paper presents a new interior point algorithm to solve power system weighted nonlinear L; norm state estimation problems ( IPWNLj). On the basis of the perturbed Karush-Kuhn-Tucker (KKT) conditions of the primal problem, we derive the IPWNL, algorithm for solving the state estimation problems. Compared with the sequential linear programming approach[13] and logarithmic barrier function method[12], the proposed IPWNL, algorithm possesses excellent convergence property. That is, the number of iterations until convergence is roughly constant with system size and measurement redundancy and mostly less than 10. Moreover, it has another valuable property that the convergence of the algorithm is quite insensitive to changes in weighting factors. To greatly enhance the computational efficiency, two schemes of the correction equation are proposed which have been realized by the rearrangement of the correction equation. Simulation experiments on test systems, which range in size from 5 to 1047 buses, have shown that the proposed algorithm has reached the level of practical applications due to its fast and robust property.
KW - Interior point methods
KW - Norm estimation
KW - Perturbed KKT conditions
KW - Power system
KW - State estimation
KW - Weighted nonlinear L
UR - http://www.scopus.com/inward/record.url?scp=0032071008&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0032071008&partnerID=8YFLogxK
U2 - 10.1109/59.667390
DO - 10.1109/59.667390
M3 - Article
AN - SCOPUS:0032071008
VL - 13
SP - 617
EP - 623
JO - IEEE Transactions on Power Systems
JF - IEEE Transactions on Power Systems
SN - 0885-8950
IS - 2
ER -