An interior point method for power system weighted nonlinear li norm static state estimation

Hua Wei, H. Sasaki, J. Kubokawa, R. Yokoyama

    Research output: Contribution to journalArticle

    63 Citations (Scopus)

    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 languageEnglish
    Pages (from-to)617-623
    Number of pages7
    JournalIEEE Transactions on Power Systems
    Volume13
    Issue number2
    DOIs
    Publication statusPublished - 1998

    Keywords

    • Interior point methods
    • Norm estimation
    • Perturbed KKT conditions
    • Power system
    • State estimation
    • Weighted nonlinear L

    ASJC Scopus subject areas

    • Electrical and Electronic Engineering

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