Method for evaluating the faulted sections and states in a power transmission line

• US 5,712,796 A
• Filed: 07/12/1995
• Issued: 01/27/1998
• Est. Priority Date: 07/14/1994
• Status: Expired due to Fees

• Current Assignee: Hitachi Cable Limited (Proterial Ltd.)
• Original Assignee: Hitachi Cable Limited (Proterial Ltd.)
• Inventors: Matsubara, Ryouji, Ohura, Kazutaka, Kaneta, Masahisa
• Primary Examiner(s): Trammell, James P.
• Assistant Examiner(s): SMITH-STEWART, DEMETRA R
• Application Number:
  US08/501,573
• Time in Patent Office: 930 Days
• Field of Search: 364/492, 364/495, 395/21, 395/23, 395/22, 324/539, 361/63, 361/107
• US Class Current: 702/59
• CPC Class Codes: H02H 1/0092 concerning the data processing means, e.g. expert systems, neural networks
• CPC Class Codes: H02H 7/26 Sectionalised protection of cable or line systems, e.g. for disconnecting a section on which a short-circuit, earth fault, or arc discharge has occured locating faults in cables G01R31/08

Abstract

The faulted sections are evaluated by calculating the measuring information resulted from the faults in various positions by the previous fault simulative calculation, introducing the resulting fault simulative measuring information into a self-organizing neural network having output elements of which number being more than that of input elements to permit the self-organizing neural network to learn the classification of the simulative measuring information, preparing an evaluation rule representing the correspondent relation between the output from the classification of the stimulative measuring information and the faulted position, thereafter introducing actual measured information into the self-organizing neural network to permit the self-organizing neural network to classify the introduced actual measured information, and evaluating the faulted section from an output classified by the self-organized neural network on the basis of the evaluation rule.

Claims

1. A method for evaluating a faulted section in power transmission line by measuring the current flowing through an aerial earth wire at a plurality of places along the power transmission line to evaluate the fault section from the measured information, comprising the steps of calculating the measuring information resulted from the faults in various positions by the previous fault simulative calculation;

introducing the resulting fault simulative measuring information into a self-organizing neural network having output elements of which number being more than that of input elements to permit the self-organizing neural network to learn the classification of the simulative measuring information;

preparing an evaluation rule representing the correspondent relation between the output from the classification of the simulative measuring information and the faulted position;

thereafter introducing actual measured information into the self-organized neural network to permit the self-organizing neural network to classify the introduced actual measured information and evaluating the faulted section from an output classified by the self-organizing neural network on the basis of the evaluation rule.

3. The method for evaluating a faulted section in a power transmission line, according to claim 1 wherein said evaluation rule is prepared for every fault state, the fault state is discriminated from the waveform information measured in a transformation station, and the faulted section is evaluated on the basis of said faulted state evaluation rule.

2. A method for evaluating the faulted section and state in a power transmission line by measuring the current flowing through an aerial earth wire at a plurality of places along the power transmission line to evaluate the faulted section and state from the measured information, comprising the steps of calculating the measuring information resulted from the faults in various positions by the previous fault simulative calculation;

introducing the resulting fault simulative measuring information into a self-organizing neural network having output elements of which number being more than that of input elements to to permit the self-organizing neural network to learn the classification of the simulative measuring information;

preparing an evaluation rule representing the correspondent relation among the output from the classification of the simulative measuring information, the faulted position and the faulted state;

thereafter introducing actual measured information into the self-organizing neural network to permit the self-organizing neural network to classify the introduced actual measured information; and

evaluating the faulted section and faulted state from an output classified by the self-organized neural network on the basis of the evaluation rule.

4. The method for evaluating the faulted section and state in a power transmission line, according to claim 2 wherein said evaluation rule is prepared as to the earth-ground fault and steel tower-ground fault, and when the ground fault is determined to be a single line-to-ground fault from the waveform information measured in a transformation station, and the faulted section and state are evaluated on the basis of said evaluation rule.