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Title: Distribution feeder loss computation by artificial neural network

Conference ·
OSTI ID:397852
;  [1]
  1. National Kaohsiung Inst. of Tech. (Taiwan, Province of China). Dept. of Electrical Engineering

This paper proposes an artificial neural network (ANN) based feeder loss calculation model for distribution system analysis. In this paper, the functional-link network model is examined to form the artificial neural network architecture to derive the various loss calculation models for feeders with different configuration. Such artificial neural network is a feedforward network that uses standard back-propagation algorithm to adjust weights on the connection path between any two processing elements (PEs). Feeder daily load curve on each season are derived by field test data. Three-phase load flow program is executed to create the training sets with exact loss calculation results. A sensitivity analysis is executed to determine the key factors included power factor, feeder loading, primary conductors, secondary conductors, and transformer capacity as the variables for components located at input layer. By artificial neural network with the pattern recognition ability, this study has developed seasonal and yearly loss calculation models for overhead and underground feeder configuration. Two practical feeders with both overhead and underground configuration in Taiwan Power Company (TPC or Taipower) distribution system are selected for computer simulation to demonstrate the effectiveness and accuracy of the proposed models. As comparing with models derived by the conventional regression technique, results indicate that the proposed models provide more efficient tool to District engineer for feeder loss calculation.

OSTI ID:
397852
Report Number(s):
CONF-9505342-; ISBN 0-7803-2480-3; TRN: IM9649%%60
Resource Relation:
Conference: 1995 IEEE industrial and commercial power systems technical conference, San Antonio, TX (United States), 7-11 May 1995; Other Information: PBD: 1995; Related Information: Is Part Of 1995 IEEE industrial and commercial power systems technical conference; PB: 225 p.
Country of Publication:
United States
Language:
English

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