Structure in total least squares parameter estimation for electrical networks

Adair Lang; Iman Shames; Michael Cantoni

doi:10.1016/j.ifacol.2018.12.072

Structure in total least squares parameter estimation for electrical networks

Adair Lang, Iman Shames, Michael Cantoni

Research output: Contribution to journal › Article › peer-review

1 Citation (Scopus)

Abstract

A total least squares approach to estimating the line admittances of an electrical network for power distribution is explored. It is observed that the Newton iterates for solving the corresponding non-linear Karush-Kuhn-Tucker (KKT) optimality conditions are structured for path and tree networks. In particular, it is revealed that a condensed form of the linear system of equations to be solved at each Newton step has a sparse block arrow-head structure, which can be exploited to improve the scalability of the approach. A numerical example for a path network is presented.

Original language	English
Pages (from-to)	420-425
Number of pages	6
Journal	IFAC-PapersOnLine
Volume	51
Issue number	23
DOIs	https://doi.org/10.1016/j.ifacol.2018.12.072
Publication status	Published - 1 Jan 2018
Externally published	Yes

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10.1016/j.ifacol.2018.12.072

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title = "Structure in total least squares parameter estimation for electrical networks",

abstract = "A total least squares approach to estimating the line admittances of an electrical network for power distribution is explored. It is observed that the Newton iterates for solving the corresponding non-linear Karush-Kuhn-Tucker (KKT) optimality conditions are structured for path and tree networks. In particular, it is revealed that a condensed form of the linear system of equations to be solved at each Newton step has a sparse block arrow-head structure, which can be exploited to improve the scalability of the approach. A numerical example for a path network is presented.",

keywords = "electrical networks, error in variables, large-scale systems, Parameter estimation",

author = "Adair Lang and Iman Shames and Michael Cantoni",

note = "Publisher Copyright: {\textcopyright} 2018",

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T1 - Structure in total least squares parameter estimation for electrical networks

AU - Lang, Adair

AU - Shames, Iman

AU - Cantoni, Michael

PY - 2018/1/1

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N2 - A total least squares approach to estimating the line admittances of an electrical network for power distribution is explored. It is observed that the Newton iterates for solving the corresponding non-linear Karush-Kuhn-Tucker (KKT) optimality conditions are structured for path and tree networks. In particular, it is revealed that a condensed form of the linear system of equations to be solved at each Newton step has a sparse block arrow-head structure, which can be exploited to improve the scalability of the approach. A numerical example for a path network is presented.

AB - A total least squares approach to estimating the line admittances of an electrical network for power distribution is explored. It is observed that the Newton iterates for solving the corresponding non-linear Karush-Kuhn-Tucker (KKT) optimality conditions are structured for path and tree networks. In particular, it is revealed that a condensed form of the linear system of equations to be solved at each Newton step has a sparse block arrow-head structure, which can be exploited to improve the scalability of the approach. A numerical example for a path network is presented.

KW - electrical networks

KW - error in variables

KW - large-scale systems

KW - Parameter estimation

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U2 - 10.1016/j.ifacol.2018.12.072

DO - 10.1016/j.ifacol.2018.12.072

M3 - Article

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VL - 51

SP - 420

EP - 425

JO - IFAC-PapersOnLine

JF - IFAC-PapersOnLine

IS - 23

ER -

Structure in total least squares parameter estimation for electrical networks

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