An enhanced binary dragonfly algorithm based on a V-shaped transfer function for optimization of pump scheduling program in water supply systems (case study of Iran)
•A binary dragonfly algorithm (BDA) with a new transfer function is proposed.•The proposed BDA is applied to minimize the energy consumption of pumping stations.•Results show the high performance of BDA comparing to the excited models. With the continual growth of population and shortage of energy r...
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| Vydáno v: | Engineering failure analysis Ročník 123; s. 105323 |
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| Hlavní autoři: | , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Elsevier Ltd
01.05.2021
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| ISSN: | 1350-6307, 1873-1961 |
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| Abstract | •A binary dragonfly algorithm (BDA) with a new transfer function is proposed.•The proposed BDA is applied to minimize the energy consumption of pumping stations.•Results show the high performance of BDA comparing to the excited models.
With the continual growth of population and shortage of energy resources, the optimal consumption of these resources is of particular importance. One of these energy sources is electricity, with a significant amount being used in pumping stations for water distribution systems (WDS). Determining the proper pumping schedule can make significant savings in energy consumption and particularly in costs. This study aims to present an improved population-based nature-inspired optimization algorithmfor pumping scheduling program in WDS. To address this issue, the binary dragonfly algorithm based on a new transfer-function coupled with the EPANET hydraulic simulation model is developed to reduce the energy consumption of pumping stations. The proposed model was firstly implemented and evaluated on a benchmark test example, then on a real water pumping station. Comparison of the proposed method and the genetic algorithm (GA), evolutionary algorithm (EA), ant colony optimization (ACO), artificial bee colony (ABC), particle swarm optimization (PSO), and firefly (FF) was conducted on the benchmark test example, while the obtained results indicate that the proposed framework is more computationally efficient and reliable. The results of the real case study show that while considering all different constraints of the problem, the proposed model can decrease the cost of energy up to 27% in comparison with the current state of operation. |
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| AbstractList | •A binary dragonfly algorithm (BDA) with a new transfer function is proposed.•The proposed BDA is applied to minimize the energy consumption of pumping stations.•Results show the high performance of BDA comparing to the excited models.
With the continual growth of population and shortage of energy resources, the optimal consumption of these resources is of particular importance. One of these energy sources is electricity, with a significant amount being used in pumping stations for water distribution systems (WDS). Determining the proper pumping schedule can make significant savings in energy consumption and particularly in costs. This study aims to present an improved population-based nature-inspired optimization algorithmfor pumping scheduling program in WDS. To address this issue, the binary dragonfly algorithm based on a new transfer-function coupled with the EPANET hydraulic simulation model is developed to reduce the energy consumption of pumping stations. The proposed model was firstly implemented and evaluated on a benchmark test example, then on a real water pumping station. Comparison of the proposed method and the genetic algorithm (GA), evolutionary algorithm (EA), ant colony optimization (ACO), artificial bee colony (ABC), particle swarm optimization (PSO), and firefly (FF) was conducted on the benchmark test example, while the obtained results indicate that the proposed framework is more computationally efficient and reliable. The results of the real case study show that while considering all different constraints of the problem, the proposed model can decrease the cost of energy up to 27% in comparison with the current state of operation. |
| ArticleNumber | 105323 |
| Author | Jafari-Asl, Jafar Azizyan, Gholamreza Monfared, Seyed Arman Hashemi Rashki, Mohsen Andrade-Campos, Antonio G. |
| Author_xml | – sequence: 1 givenname: Jafar surname: Jafari-Asl fullname: Jafari-Asl, Jafar organization: Department of Civil Engineering, Faculty of Engineering, University of Sistan and Baluchestan, Zahedan, Iran – sequence: 2 givenname: Gholamreza surname: Azizyan fullname: Azizyan, Gholamreza email: G.azizyan@eng.usb.ac.ir organization: Department of Civil Engineering, Faculty of Engineering, University of Sistan and Baluchestan, Zahedan, Iran – sequence: 3 givenname: Seyed Arman Hashemi surname: Monfared fullname: Monfared, Seyed Arman Hashemi organization: Department of Civil Engineering, Faculty of Engineering, University of Sistan and Baluchestan, Zahedan, Iran – sequence: 4 givenname: Mohsen surname: Rashki fullname: Rashki, Mohsen organization: Department of Architecture Engineering, Faculty of Arts and Architecture, University of Sistan and Baluchestan, Zahedan, Iran – sequence: 5 givenname: Antonio G. surname: Andrade-Campos fullname: Andrade-Campos, Antonio G. organization: Centre for Mechanical Technology & Automation, GRIDS Research Group, University of Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal |
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| Cites_doi | 10.1061/(ASCE)WR.1943-5452.0001198 10.1007/s00521-015-1920-1 10.1061/(ASCE)0733-9496(2008)134:4(337) 10.1061/(ASCE)0733-9437(2004)130:5(357) 10.1016/j.rser.2013.09.010 10.1007/s11269-020-02588-3 10.1061/(ASCE)0733-9496(2004)130:2(160) 10.1007/s11269-014-0721-0 10.1002/j.1551-8833.1993.tb06024.x 10.1016/j.advengsoft.2013.12.007 10.1016/j.swevo.2012.09.002 10.1007/s11269-017-1577-x 10.1016/j.eswa.2017.04.033 10.1007/s40899-020-00426-3 10.1080/1573062X.2013.795233 10.1002/ird.412 10.1061/(ASCE)0733-9496(1994)120:1(17) 10.1007/BFb0027177 10.1016/j.asoc.2020.107036 10.1155/2019/9293617 10.1162/EVCO_a_00035 10.1016/j.mcm.2012.09.015 10.1061/(ASCE)0733-9496(1989)115:2(148) 10.1016/j.ejor.2019.12.008 10.1061/(ASCE)0733-9496(1992)118:4(406) 10.1007/s00521-020-04866-y 10.1061/(ASCE)0733-9496(1996)122:5(374) 10.1007/978-3-030-26458-1_11 10.1016/j.knosys.2018.08.003 |
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| Keywords | Binary dragonfly algorithm Water supply system Energy cost Transfer function Pump scheduling program |
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| SubjectTerms | Binary dragonfly algorithm Energy cost Pump scheduling program Transfer function Water supply system |
| Title | An enhanced binary dragonfly algorithm based on a V-shaped transfer function for optimization of pump scheduling program in water supply systems (case study of Iran) |
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