Research Article | OPEN ACCESS
Competence-Oriented Decision Model for Optimizing the Operation of a Cascading Hydroelectric Power Reservoir
Tilahun Derib Asfaw, Khamaruzaman Wan Yusof and Ahmad Mustafa Hashim
Department of Civil Engineering, Universiti Teknologi PETRONAS (UTP), 31750, Tronoh, Malaysia
Research Journal of Applied Sciences, Engineering and Technology 2013 10:1895-1901
Received: November 24, 2012 | Accepted: January 11, 2013 | Published: July 20, 2013
Abstract
The operation of the four Perak cascading reservoirs namely, Temenggor, Bersia, Kenering and Chenderoh analyzed using the newly developed genetic algorithm model. The reservoirs are located in the state of Perak of Peninsular Malaysia that used for hydroelectric power generation and flood mitigation. The hydroelectric potential of the cascading scheme is 578 MW. However, the actual annual average generation was 228 MW, which is about 39% of the potential. The research aimed to improve the annual average hydroelectric power generation. The result of the fitness value used to select the optimal option from the test of eight model runs options. After repeated runs of the optimal option, the best model parameters are found. Therefore, optimality achieved at population size of 150, crossover probability of 0.75 and generation number of 60. The operation of GA model produced an additional of 12.17 MW per day. The additional power is found with the same total annual volume of release and similar natural inflow pattern. The additional hydroelectric power can worth over 22 million Ringgit Malaysia per year. In addition, it plays a significant role on the growing energy needs of the country.
Keywords:
Cascading reservoirs, fitness value , genetic algorithm, hydroelectric power,
Competing interests
The authors have no competing interests.
Open Access Policy
This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Copyright
The authors have no competing interests.
|
|
![](http://www.maxwellsci.com/images/RJASET-maxw.jpg) |
ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
![Submit Manuscript](../images/sub.jpg) |
Information |
|
|
|
Sales & Services |
|
|
|