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Application of intelligent optimization techniques and investigating the effect of reservoir size in calibrating the reservoir operating policy

In this study, we applied the most recently developed artificial bee colony (ABC) optimization technique in search of an optimal reservoir release policy. The effect of the optimization algorithms was also investigated in terms of reservoir size and operational complexities. Particle swarm optimizat...

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Main Authors: Hossain Md.S., El-Shafie A., Mohtar W.H.M.W.
Other Authors: 55579596900
Format: Article
Published: IWA Publishing 2023
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spelling my.uniten.dspace-222082023-05-29T13:59:38Z Application of intelligent optimization techniques and investigating the effect of reservoir size in calibrating the reservoir operating policy Hossain Md.S. El-Shafie A. Mohtar W.H.M.W. 55579596900 16068189400 25637975300 In this study, we applied the most recently developed artificial bee colony (ABC) optimization technique in search of an optimal reservoir release policy. The effect of the optimization algorithms was also investigated in terms of reservoir size and operational complexities. Particle swarm optimization, genetic algorithm and neural network-based stochastic dynamic programming are used to compare the model performances. Two different reservoir data were used to achieve the detailed analysis and complete understanding of the application efficiency of these optimization techniques. Release curves were developed for every month as guidance for the decisionmaker. Simulation was carried out for each method using actual inflow data, and reliability, resiliency and vulnerability are measured. The release policy provided by ABC optimization algorithms outperformed in terms of reliability, less waste of water and handling critical situations of low inflow. Also, the ABC showed better performance in the case of complex reservoirs. � 2015 IWA Publishing. Final 2023-05-29T05:59:38Z 2023-05-29T05:59:38Z 2015 Article 10.2166/wp.2015.023 2-s2.0-84955473434 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84955473434&doi=10.2166%2fwp.2015.023&partnerID=40&md5=c3ba0ed1deddaf4598db661887bf3ce2 https://irepository.uniten.edu.my/handle/123456789/22208 17 6 1143 1162 IWA Publishing Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
description In this study, we applied the most recently developed artificial bee colony (ABC) optimization technique in search of an optimal reservoir release policy. The effect of the optimization algorithms was also investigated in terms of reservoir size and operational complexities. Particle swarm optimization, genetic algorithm and neural network-based stochastic dynamic programming are used to compare the model performances. Two different reservoir data were used to achieve the detailed analysis and complete understanding of the application efficiency of these optimization techniques. Release curves were developed for every month as guidance for the decisionmaker. Simulation was carried out for each method using actual inflow data, and reliability, resiliency and vulnerability are measured. The release policy provided by ABC optimization algorithms outperformed in terms of reliability, less waste of water and handling critical situations of low inflow. Also, the ABC showed better performance in the case of complex reservoirs. � 2015 IWA Publishing.
author2 55579596900
author_facet 55579596900
Hossain Md.S.
El-Shafie A.
Mohtar W.H.M.W.
format Article
author Hossain Md.S.
El-Shafie A.
Mohtar W.H.M.W.
spellingShingle Hossain Md.S.
El-Shafie A.
Mohtar W.H.M.W.
Application of intelligent optimization techniques and investigating the effect of reservoir size in calibrating the reservoir operating policy
author_sort Hossain Md.S.
title Application of intelligent optimization techniques and investigating the effect of reservoir size in calibrating the reservoir operating policy
title_short Application of intelligent optimization techniques and investigating the effect of reservoir size in calibrating the reservoir operating policy
title_full Application of intelligent optimization techniques and investigating the effect of reservoir size in calibrating the reservoir operating policy
title_fullStr Application of intelligent optimization techniques and investigating the effect of reservoir size in calibrating the reservoir operating policy
title_full_unstemmed Application of intelligent optimization techniques and investigating the effect of reservoir size in calibrating the reservoir operating policy
title_sort application of intelligent optimization techniques and investigating the effect of reservoir size in calibrating the reservoir operating policy
publisher IWA Publishing
publishDate 2023
_version_ 1806426485086486528
score 13.222552

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