skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Calculation of transmission system losses for the Taiwan Power Company by the artificial neural network with time decayed weight

Conference ·
OSTI ID:433794
; ;  [1]
  1. Tatung Inst. of Tech., Taipei (Taiwan, Province of China)

For energy conservation and improvement of power system operation efficiency, how to reduce the transmission system losses becomes an important topic of grave concern. To understand the cause, and to evaluate the amount, of the losses are the prior steps to diminish them. To simplify the evaluation procedure without losing too much accuracy, this paper adopts the artificial neural network, which is a model free network, to analyze the transmission system losses. As the artificial neural network with time decayed weight has the capability of learning, memorizing, and forgetting, it is more suitable for a power system with gradually changing characteristics. By using this artificial neural network, the estimation of transmission system losses will be more precise. In this paper, comparison will be made between the results of artificial neural network analysis and polynomial loss equations analysis.

OSTI ID:
433794
Report Number(s):
CONF-951136-; ISBN 0-7803-2981-3; TRN: IM9709%%228
Resource Relation:
Conference: 1995 International conference on energy management and power delivery, Singapore (Singapore), 21-23 Nov 1995; Other Information: PBD: 1995; Related Information: Is Part Of 1995 international conference on energy management and power delivery: Proceedings. Volume 1; PB: 479 p.
Country of Publication:
United States
Language:
English

Similar Records

On-line evaluation of capacity and energy losses in power transmission systems by using artificial neural networks
Journal Article · Sun Oct 01 00:00:00 EDT 1995 · IEEE Transactions on Power Delivery · OSTI ID:433794

Distribution feeder loss computation by artificial neural network
Conference · Sun Dec 31 00:00:00 EST 1995 · OSTI ID:433794

Artificial neural-network based feeder reconfiguration for loss reduction in distribution systems
Journal Article · Thu Jul 01 00:00:00 EDT 1993 · IEEE Transactions on Power Delivery (Institute of Electrical and Electronics Engineers); (United States) · OSTI ID:433794