Techno-economic assessment of a stand-alone hybrid solar-wind-battery system for a remote island using genetic algorithm.
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| Title: | Techno-economic assessment of a stand-alone hybrid solar-wind-battery system for a remote island using genetic algorithm. |
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| Authors: | Javed, Muhammad Shahzad1 (AUTHOR), Song, Aotian2 (AUTHOR), Ma, Tao1,2 (AUTHOR) tao.ma@connect.polyu.hk |
| Source: | Energy. Jun2019, Vol. 176, p704-717. 14p. |
| Subjects: | Genetic algorithms, Hybrid systems, Renewable energy sources, Capital costs, Power resources, Wind turbines |
| Abstract: | Hybrid renewable energy systems are proving to be capable and emission-free sources of power generation, especially for off-grid/remote areas. This study develops a mathematical model to optimize a hybrid solar-wind energy system with storage for a remote island with genetic algorithm (GA). Four different cases are evaluated and the results are compared with that, the widely-used HOMER software, illustrating that GA method can output a more optimal system than HOMER in respect of cost and system reliability. Moreover, two systems with different wind turbine size are analyzed and their results present very little difference in terms of system cost and reliability, indicating that wind turbine size has little impact on the results. Furthermore, the simulated performance of the system and the effects of loss of power supply probability (LPSP), variation of load and renewable energy resources on the system cost are analyzed. Sensitivity analysis on some key parameters indicates that by considering a slight (1–5%) LPSP there is a significant decrease in initial capital cost (25–30%), operating cost (15–17%) as well as COE. It is evident from the sensitivity analysis that initially it is better to energize the off-grid/remote areas with small LPSP than no electricity. • Techno-economic study of a hybrid solar-wind-battery system is conducted. • Genetic algorithm offer better results than HOMER in terms of cost and reliability. • Wind turbine size has little impact on system cost. • Considering a slight LPSP (1%) brings considerable decrease in COE value (13%–16%). • Effect of LPSP on COE remains same after considering the different load demands. [ABSTRACT FROM AUTHOR] |
| Copyright of Energy is the property of Pergamon Press - An Imprint of Elsevier Science 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 |
| FullText | Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 136179052 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Techno-economic assessment of a stand-alone hybrid solar-wind-battery system for a remote island using genetic algorithm. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Javed%2C+Muhammad+Shahzad%22">Javed, Muhammad Shahzad</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Song%2C+Aotian%22">Song, Aotian</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ma%2C+Tao%22">Ma, Tao</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> tao.ma@connect.polyu.hk</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Energy%22">Energy</searchLink>. Jun2019, Vol. 176, p704-717. 14p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Genetic+algorithms%22">Genetic algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Hybrid+systems%22">Hybrid systems</searchLink><br /><searchLink fieldCode="DE" term="%22Renewable+energy+sources%22">Renewable energy sources</searchLink><br /><searchLink fieldCode="DE" term="%22Capital+costs%22">Capital costs</searchLink><br /><searchLink fieldCode="DE" term="%22Power+resources%22">Power resources</searchLink><br /><searchLink fieldCode="DE" term="%22Wind+turbines%22">Wind turbines</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Hybrid renewable energy systems are proving to be capable and emission-free sources of power generation, especially for off-grid/remote areas. This study develops a mathematical model to optimize a hybrid solar-wind energy system with storage for a remote island with genetic algorithm (GA). Four different cases are evaluated and the results are compared with that, the widely-used HOMER software, illustrating that GA method can output a more optimal system than HOMER in respect of cost and system reliability. Moreover, two systems with different wind turbine size are analyzed and their results present very little difference in terms of system cost and reliability, indicating that wind turbine size has little impact on the results. Furthermore, the simulated performance of the system and the effects of loss of power supply probability (LPSP), variation of load and renewable energy resources on the system cost are analyzed. Sensitivity analysis on some key parameters indicates that by considering a slight (1–5%) LPSP there is a significant decrease in initial capital cost (25–30%), operating cost (15–17%) as well as COE. It is evident from the sensitivity analysis that initially it is better to energize the off-grid/remote areas with small LPSP than no electricity. • Techno-economic study of a hybrid solar-wind-battery system is conducted. • Genetic algorithm offer better results than HOMER in terms of cost and reliability. • Wind turbine size has little impact on system cost. • Considering a slight LPSP (1%) brings considerable decrease in COE value (13%–16%). • Effect of LPSP on COE remains same after considering the different load demands. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Energy is the property of Pergamon Press - An Imprint of Elsevier Science 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: BibEntity: Identifiers: – Type: doi Value: 10.1016/j.energy.2019.03.131 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 14 StartPage: 704 Subjects: – SubjectFull: Genetic algorithms Type: general – SubjectFull: Hybrid systems Type: general – SubjectFull: Renewable energy sources Type: general – SubjectFull: Capital costs Type: general – SubjectFull: Power resources Type: general – SubjectFull: Wind turbines Type: general Titles: – TitleFull: Techno-economic assessment of a stand-alone hybrid solar-wind-battery system for a remote island using genetic algorithm. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Javed, Muhammad Shahzad – PersonEntity: Name: NameFull: Song, Aotian – PersonEntity: Name: NameFull: Ma, Tao IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2019 Type: published Y: 2019 Identifiers: – Type: issn-print Value: 03605442 Numbering: – Type: volume Value: 176 Titles: – TitleFull: Energy Type: main |
| ResultId | 1 |
