Published October 2011 | Version v1
Journal article

Maximal network reliability for a stochastic power transmission network

  • 1. Department of Industrial Management, National Taiwan University of Science and Technology, Taipei 106, Taiwan (China)

Description

Many studies regarded a power transmission network as a binary-state network and constructed it with several arcs and vertices to evaluate network reliability. In practice, the power transmission network should be stochastic because each arc (transmission line) combined with several physical lines is multistate. Network reliability is the probability that the network can transmit d units of electric power from a power plant (source) to a high voltage substation at a specific area (sink). This study focuses on searching for the optimal transmission line assignment to the power transmission network such that network reliability is maximized. A genetic algorithm based method integrating the minimal paths and the Recursive Sum of Disjoint Products is developed to solve this assignment problem. A real power transmission network is adopted to demonstrate the computational efficiency of the proposed method while comparing with the random solution generation approach.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.ress.2011.04.001

Additional details

Identifiers

DOI
10.1016/j.ress.2011.04.001;
PII
S0951-8320(11)00077-9;

Publishing Information

Journal Title
Reliability Engineering and System Safety
Journal Volume
96
Journal Issue
10
Journal Page Range
p. 1332-1339
ISSN
0951-8320
CODEN
RESSEP

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
43055040
Subject category
S42: ENGINEERING;
Descriptors DEI
ALGORITHMS; EFFICIENCY; ELECTRIC POTENTIAL; ELECTRIC POWER; MATHEMATICAL SOLUTIONS; POWER PLANTS; POWER TRANSMISSION; POWER TRANSMISSION LINES; PROBABILITY; RANDOMNESS; RELIABILITY; STOCHASTIC PROCESSES
Descriptors DEC
MATHEMATICAL LOGIC; POWER

Optional Information

Copyright
Copyright (c) 2011 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.