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Manta ray foraging optimization algorithm with mathematical spiral foraging strategies for solving economic load dispatching problems in power systems.

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Title: Manta ray foraging optimization algorithm with mathematical spiral foraging strategies for solving economic load dispatching problems in power systems.
Authors: Zhang, Xing-Yue1 (AUTHOR), Hao, Wen-Kuo1 (AUTHOR), Wang, Jie-Sheng1 (AUTHOR) wang_jiesheng@126.com, Zhu, Jun-Hua1 (AUTHOR), Zhao, Xiao-Rui1 (AUTHOR), Zheng, Yue1 (AUTHOR)
Source: Alexandria Engineering Journal. May2023, Vol. 70, p613-640. 28p.
Subjects: Optimization algorithms, Mathematical optimization, Economic efficiency, Bees algorithm, Industrial costs, Mathematical economics
Abstract: Economic Load Dispatch (ELD) is an effective dispatch strategy to improve economic efficiency while ensuring the safety and stability of the power system. It minimizes production costs by rationally allocating the power generated by each power system unit. In this paper, an Manta Ray Foraging Optimization (MRFO) algorithm based on the mathematical spiral foraging strategy is proposed to solve the ELD problem in power systems considering transmission losses. Eight different mathematical spirals were introduced into the MRFO algorithm's foraging strategy, including the Rose spiral, Archimedes spiral, Fermat spiral, Cycloid spiral, Hypotrochoid spiral, Epitrochoid spiral, Inverse spiral and Lituus spiral. The mathematical spiral foraging strategy can enhance the global search ability of the MRFO algorithm and improves its convergence velocity. To verify the performance of the proposed improved MRFO algorithm, 30 benchmark functions are tested and the optimization performances are compared with BOA, AOA, SCA, HHO, WOA, RSA, and GWO. The simulation experimental results show that the performance and application of the manta ray foraging optimization algorithm based on the mathematical spiral foraging strategy outperform other intelligent optimization algorithms tested on 30 benchmark functions. Finally, two ELD cases with total demands of 2500 MW and 10500 MW are selected and solved using the improved manta ray foraging optimization algorithm. Comparing the simulation results with other optimization algorithms, it is shown that the proposed improved algorithm obtains the best fuel cost and smaller transmission loss in almost every test case, which canl help to improve the economic efficiency of the power system and achieve the goal of economic load dispatch. [ABSTRACT FROM AUTHOR]
Copyright of Alexandria Engineering Journal is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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Header DbId: egs
DbLabel: Engineering Source
An: 163482935
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PubTypeId: academicJournal
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  Label: Title
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  Data: Manta ray foraging optimization algorithm with mathematical spiral foraging strategies for solving economic load dispatching problems in power systems.
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  Data: <searchLink fieldCode="AR" term="%22Zhang%2C+Xing-Yue%22">Zhang, Xing-Yue</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Hao%2C+Wen-Kuo%22">Hao, Wen-Kuo</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wang%2C+Jie-Sheng%22">Wang, Jie-Sheng</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> wang_jiesheng@126.com</i><br /><searchLink fieldCode="AR" term="%22Zhu%2C+Jun-Hua%22">Zhu, Jun-Hua</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zhao%2C+Xiao-Rui%22">Zhao, Xiao-Rui</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Zheng%2C+Yue%22">Zheng, Yue</searchLink><relatesTo>1</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Alexandria+Engineering+Journal%22">Alexandria Engineering Journal</searchLink>. May2023, Vol. 70, p613-640. 28p.
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  Data: <searchLink fieldCode="DE" term="%22Optimization+algorithms%22">Optimization algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+optimization%22">Mathematical optimization</searchLink><br /><searchLink fieldCode="DE" term="%22Economic+efficiency%22">Economic efficiency</searchLink><br /><searchLink fieldCode="DE" term="%22Bees+algorithm%22">Bees algorithm</searchLink><br /><searchLink fieldCode="DE" term="%22Industrial+costs%22">Industrial costs</searchLink><br /><searchLink fieldCode="DE" term="%22Mathematical+economics%22">Mathematical economics</searchLink>
– Name: Abstract
  Label: Abstract
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  Data: Economic Load Dispatch (ELD) is an effective dispatch strategy to improve economic efficiency while ensuring the safety and stability of the power system. It minimizes production costs by rationally allocating the power generated by each power system unit. In this paper, an Manta Ray Foraging Optimization (MRFO) algorithm based on the mathematical spiral foraging strategy is proposed to solve the ELD problem in power systems considering transmission losses. Eight different mathematical spirals were introduced into the MRFO algorithm's foraging strategy, including the Rose spiral, Archimedes spiral, Fermat spiral, Cycloid spiral, Hypotrochoid spiral, Epitrochoid spiral, Inverse spiral and Lituus spiral. The mathematical spiral foraging strategy can enhance the global search ability of the MRFO algorithm and improves its convergence velocity. To verify the performance of the proposed improved MRFO algorithm, 30 benchmark functions are tested and the optimization performances are compared with BOA, AOA, SCA, HHO, WOA, RSA, and GWO. The simulation experimental results show that the performance and application of the manta ray foraging optimization algorithm based on the mathematical spiral foraging strategy outperform other intelligent optimization algorithms tested on 30 benchmark functions. Finally, two ELD cases with total demands of 2500 MW and 10500 MW are selected and solved using the improved manta ray foraging optimization algorithm. Comparing the simulation results with other optimization algorithms, it is shown that the proposed improved algorithm obtains the best fuel cost and smaller transmission loss in almost every test case, which canl help to improve the economic efficiency of the power system and achieve the goal of economic load dispatch. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Alexandria Engineering Journal is the property of Elsevier B.V. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
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    Identifiers:
      – Type: doi
        Value: 10.1016/j.aej.2023.03.017
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 28
        StartPage: 613
    Subjects:
      – SubjectFull: Optimization algorithms
        Type: general
      – SubjectFull: Mathematical optimization
        Type: general
      – SubjectFull: Economic efficiency
        Type: general
      – SubjectFull: Bees algorithm
        Type: general
      – SubjectFull: Industrial costs
        Type: general
      – SubjectFull: Mathematical economics
        Type: general
    Titles:
      – TitleFull: Manta ray foraging optimization algorithm with mathematical spiral foraging strategies for solving economic load dispatching problems in power systems.
        Type: main
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          Name:
            NameFull: Zhang, Xing-Yue
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            NameFull: Hao, Wen-Kuo
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            NameFull: Wang, Jie-Sheng
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            NameFull: Zhu, Jun-Hua
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            NameFull: Zhao, Xiao-Rui
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            NameFull: Zheng, Yue
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          Dates:
            – D: 01
              M: 05
              Text: May2023
              Type: published
              Y: 2023
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              Value: 11100168
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              Value: 70
          Titles:
            – TitleFull: Alexandria Engineering Journal
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