2012East China Electric PowerRequires access

Line Parameter Calculation and Estimation Method Based on π-Type Equivalent Model

KONG Fanxiang

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Abstract

The line parameter estimation is of vital importance to the power system analysis,especially distribution network analysis because the low parameter accuracy makes the analysis difficult to conduct.Based on the π-type equivalent model for transmission lines and using the measured data of line ends,this paper estimates and calculates the basic circuit parameters,in which the transformation ratio is implied.Besides,the sample data errors can be eliminated by means of minimum estimation algorithm;or weighted average is obtained based on multiple sample data.The actual application proves that the proposed algorithm is an effective inverse method.

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What this paper is about

The line parameter estimation is of vital importance to the power system analysis,especially distribution network analysis because the low parameter accuracy makes the analysis difficult to conduct.Based on the π-type equivalent model for transmission lines and using the measured data of line ends,this paper estimates and calculates the basic circuit parameters,in which the transformation ratio is implied.Besides,the sample data errors can be eliminated by means of minimum estimation algorithm;or weighted average is obtained based on multiple sample data.The actual application proves that the proposed algorithm is an effective inverse method.

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Available abstract

The line parameter estimation is of vital importance to the power system analysis,especially distribution network analysis because the low parameter accuracy makes the analysis difficult to conduct.Based on the π-type equivalent model for transmission lines and using the measured data of line ends,this paper estimates and calculates the basic circuit parameters,in which the transformation ratio is implied.Besides,the sample data errors can be eliminated by means of minimum estimation algorithm;or weighted average is obtained based on multiple sample data.The actual application proves that the proposed algorithm is an effective inverse method.

Key concepts: Transformation (genetics), Transmission line, Line (geometry), Inverse, Algorithm, Estimation theory, Sample (material), Equivalent circuit

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