๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

Optimal allocation of tie points in radial distribution systems using a genetic algorithm

โœ Scribed by M.-R. Haghifam


Publisher
John Wiley and Sons
Year
2004
Tongue
English
Weight
488 KB
Volume
14
Category
Article
ISSN
1430-144X

No coin nor oath required. For personal study only.

โœฆ Synopsis


Abstract

For reliability enhancement of radial distribution systems, normally open tie switches are located in feeders. Using tie switches and sectionalizers, the configuration of feeders can be changed in fault conditions for supplying customers from other routes. This is called load restoration in radial distribution systems. In this paper, it is shown that reliability and success of load restoration have a connection with location and number of tie switches. Also, a novel approach for optimal determination of the number and location of tie switches using a genetic algorithm is proposed. In the optimization procedure, load importance using fuzzy membership functions, cost of energy not supplied and cost of tie switches are considered. The effectiveness of the proposed method is shown by simulation results in a radial distribution network.


๐Ÿ“œ SIMILAR VOLUMES


Probe-fed microstrip antenna feed point
โœ J. Namkung; E. L. Hines; R. J. Green; M. S. Leeson ๐Ÿ“‚ Article ๐Ÿ“… 2006 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 428 KB

## Abstract A new application of genetic algorithms (GAs) for feed point optimization of a coaxial probe fed Eโ€shape microstrip patch antenna is presented. The GA shows excellent results for finding the best feed point in a given antenna structure. The method of moments is used in this paper, emplo

Multistage control of a stochastic syste
โœ Janusz Kacprzyk ๐Ÿ“‚ Article ๐Ÿ“… 1998 ๐Ÿ› John Wiley and Sons ๐ŸŒ English โš– 107 KB ๐Ÿ‘ 2 views

We consider the classic Bellman and Zadeh multistage control problem under fuzzy constraints imposed on applied controls and fuzzy goals imposed on attained states with a stochastic system under control that is assumed to be a Markov chain. An optimal sequence of controls is sought that maximizes th