Maximal network reliability for a stochastic power transmission network
Creators
- 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.2011.04.001Additional 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.