Title : ( Optimization of Tailraces by Ant Colony Algorithm )
Authors: ALI MAGHDOORI , Saeed Reza Khodashenas , atena pezeshki , Sara Dadar ,Access to full-text not allowed by authors
Abstract
Hydroelectric power plants are one of the most common methods of energy supply these days. In these power plants, the energy from the waterfall is converted directly into electricity. Saxo turbines are capable of generating hydropower along the flow path without a large tank and minimal environmental damage. In order to optimize the use of the dam’s head, it is better to Minimize head loss along the outlet channel path. The purpose of this study is to use the Ant Colony System technique (ACS) And Ranked Based Ant System algorithm (RBAS) to optimize the output channel of the power plant and finally comparing them to each other in order to have the most usage of these turbines. So, the most influential factors in channel design Such as slop of channel bottom and channel length in different parts (contraction, expansion, fixed) and also channel cross-section geometry was evaluated for different discharges. A comparison of the two algorithms showed that the performs of the RBAS algorithm is better than the ACS algorithm. Eventually, the optimal channel shape for different flow rates with the least head loss is presented
Keywords
, Hydropower plants, Saxo turbines, Ant colony Algorithm , RBAS, Visual basic, Tailrace@article{paperid:1080303,
author = {MAGHDOORI, ALI and Khodashenas, Saeed Reza and Pezeshki, Atena and سارا دادار},
title = {Optimization of Tailraces by Ant Colony Algorithm},
journal = {International Journal of Advanced Science and Technology},
year = {2020},
volume = {29},
number = {7},
month = {July},
issn = {2005-4238},
pages = {5384--5407},
numpages = {23},
keywords = {Hydropower plants; Saxo turbines; Ant colony Algorithm ،RBAS; Visual basic;
Tailrace},
}
%0 Journal Article
%T Optimization of Tailraces by Ant Colony Algorithm
%A MAGHDOORI, ALI
%A Khodashenas, Saeed Reza
%A Pezeshki, Atena
%A سارا دادار
%J International Journal of Advanced Science and Technology
%@ 2005-4238
%D 2020