Multi-Reservoir System Optimization Based on Hybrid Gravitational Algorithm to Minimize Water-Supply Deficiencies
The growing prevalence of droughts and water scarcity have increased the importance of operating dam and reservoir systems efficiently. Several methods based on algorithms have been developed in recent years in a bid to optimize water release operation policy, in order to overcome or minimize the im...
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| Format: | Article |
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Springer Verlag
2019
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| author | Karami, Hojat Farzin, Saeed Jahangiri, Aylin Ehteram, Mohammad Kisi, Ozgur El-Shafie, Ahmed |
| author_facet | Karami, Hojat Farzin, Saeed Jahangiri, Aylin Ehteram, Mohammad Kisi, Ozgur El-Shafie, Ahmed |
| author_sort | Karami, Hojat |
| collection | UM |
| description | The growing prevalence of droughts and water scarcity have increased the importance of operating dam and reservoir systems efficiently. Several methods based on algorithms have been developed in recent years in a bid to optimize water release operation policy, in order to overcome or minimize the impact of droughts. However, all of these algorithms suffer from some weaknesses or drawbacks – notably early convergence, a low rate of convergence, or trapping in local optimizations – that limit their effectiveness and efficiency in seeking to determine the global optima for the operation of water systems. Against this background, the present study seeks to introduce and test a Hybrid Algorithm (HA) which integrates the Gravitational Search Algorithm (GSA) with the Particle Swarm Optimization Algorithm (PSOA) with the goal of minimizing irrigation deficiencies in a multi-reservoir system. The proposed algorithm was tested for a specific important multi-reservoir system in Iran: namely the Golestan Dam and Voshmgir Dam system. The results showed that applying the HA could reduce average irrigation deficiencies for the Golestan Dam substantially, to only 2 million cubic meters (MCM), compared to deficiency values for the Genetic Algorithm (GA), PSOA and GSA of 15.1, 6.7 and 5.8 MCM respectively. In addition, the HA performed very efficiently, reducing substantially the computational time needed to achieve the global optimal when compared with the other algorithms tested. Furthermore, the HA showed itself capable of assuring a high volumetric reliability index (VRI) to meet the pattern of water demand downstream from the dams, as well as clearly outperforming the other algorithms on other important indices. In conclusion, the proposed HA seems to offer considerable potential as an optimizer for dam and reservoir operations world-wide. © 2019, Springer Nature B.V. |
| first_indexed | 2024-03-06T06:02:03Z |
| format | Article |
| id | um.eprints-24189 |
| institution | Universiti Malaya |
| last_indexed | 2024-03-06T06:02:03Z |
| publishDate | 2019 |
| publisher | Springer Verlag |
| record_format | dspace |
| spelling | um.eprints-241892020-04-09T11:09:58Z http://eprints.um.edu.my/24189/ Multi-Reservoir System Optimization Based on Hybrid Gravitational Algorithm to Minimize Water-Supply Deficiencies Karami, Hojat Farzin, Saeed Jahangiri, Aylin Ehteram, Mohammad Kisi, Ozgur El-Shafie, Ahmed TA Engineering (General). Civil engineering (General) The growing prevalence of droughts and water scarcity have increased the importance of operating dam and reservoir systems efficiently. Several methods based on algorithms have been developed in recent years in a bid to optimize water release operation policy, in order to overcome or minimize the impact of droughts. However, all of these algorithms suffer from some weaknesses or drawbacks – notably early convergence, a low rate of convergence, or trapping in local optimizations – that limit their effectiveness and efficiency in seeking to determine the global optima for the operation of water systems. Against this background, the present study seeks to introduce and test a Hybrid Algorithm (HA) which integrates the Gravitational Search Algorithm (GSA) with the Particle Swarm Optimization Algorithm (PSOA) with the goal of minimizing irrigation deficiencies in a multi-reservoir system. The proposed algorithm was tested for a specific important multi-reservoir system in Iran: namely the Golestan Dam and Voshmgir Dam system. The results showed that applying the HA could reduce average irrigation deficiencies for the Golestan Dam substantially, to only 2 million cubic meters (MCM), compared to deficiency values for the Genetic Algorithm (GA), PSOA and GSA of 15.1, 6.7 and 5.8 MCM respectively. In addition, the HA performed very efficiently, reducing substantially the computational time needed to achieve the global optimal when compared with the other algorithms tested. Furthermore, the HA showed itself capable of assuring a high volumetric reliability index (VRI) to meet the pattern of water demand downstream from the dams, as well as clearly outperforming the other algorithms on other important indices. In conclusion, the proposed HA seems to offer considerable potential as an optimizer for dam and reservoir operations world-wide. © 2019, Springer Nature B.V. Springer Verlag 2019 Article PeerReviewed Karami, Hojat and Farzin, Saeed and Jahangiri, Aylin and Ehteram, Mohammad and Kisi, Ozgur and El-Shafie, Ahmed (2019) Multi-Reservoir System Optimization Based on Hybrid Gravitational Algorithm to Minimize Water-Supply Deficiencies. Water Resources Management, 33 (8). pp. 2741-2760. ISSN 0920-4741, DOI https://doi.org/10.1007/s11269-019-02238-3 <https://doi.org/10.1007/s11269-019-02238-3>. https://doi.org/10.1007/s11269-019-02238-3 doi:10.1007/s11269-019-02238-3 |
| spellingShingle | TA Engineering (General). Civil engineering (General) Karami, Hojat Farzin, Saeed Jahangiri, Aylin Ehteram, Mohammad Kisi, Ozgur El-Shafie, Ahmed Multi-Reservoir System Optimization Based on Hybrid Gravitational Algorithm to Minimize Water-Supply Deficiencies |
| title | Multi-Reservoir System Optimization Based on Hybrid Gravitational Algorithm to Minimize Water-Supply Deficiencies |
| title_full | Multi-Reservoir System Optimization Based on Hybrid Gravitational Algorithm to Minimize Water-Supply Deficiencies |
| title_fullStr | Multi-Reservoir System Optimization Based on Hybrid Gravitational Algorithm to Minimize Water-Supply Deficiencies |
| title_full_unstemmed | Multi-Reservoir System Optimization Based on Hybrid Gravitational Algorithm to Minimize Water-Supply Deficiencies |
| title_short | Multi-Reservoir System Optimization Based on Hybrid Gravitational Algorithm to Minimize Water-Supply Deficiencies |
| title_sort | multi reservoir system optimization based on hybrid gravitational algorithm to minimize water supply deficiencies |
| topic | TA Engineering (General). Civil engineering (General) |
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