The improved aquila optimization approach for cost-effective design of hybrid renewable energy systems
© 2024 The Authors..
The growing demand for renewable energy systems is driven by climate change concerns, government support, technological advancements, economic viability, and energy security. These factors combine to create a strong momentum towards a clean and sustainable energy future. Governments, governments, and individuals are increasingly aware of the environmental impacts of traditional energy sources and adopting renewable energy solutions. Hybrid Renewable Energy Systems (HRES) are developed as an effective way of meeting the energy demands in remote locations. The complexity of the system components and the fluctuation of renewable energy sources make it difficult to design an economical and effective HRES. In this study, the Improved Aquila Optimization (IAO) approach has been suggested as a powerful tool to optimize the HRES design. The study addresses the implementation of the IAO approach in the design of HRES and emphasizes its advantages over other optimization techniques. Through extensive simulations and analyses, our findings demonstrate the superior performance of the IAO algorithm in improving the efficiency and cost-effectiveness of HRES. The optimization process using IAO resulted in a significant reduction in overall system costs, achieving an estimated Net Present Cost (NPC) of $201,973. It translates to a cost reduction of 25% compared to conventional optimization techniques. Furthermore, our analysis reveals that the IAO approach enhances the utilization of renewable energy sources, leading to a 15% increase in overall energy generation efficiency. These results highlight the effectiveness of the IAO approach in addressing the challenges associated with designing HRES. By significantly reducing costs and improving efficiency, it facilitates the adoption of sustainable energy systems in remote areas. The outcomes of this study emphasize the importance of utilizing advanced optimization techniques, such as IAO, to ensure the economic viability and environmental sustainability of HRES.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:10 |
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| Enthalten in: |
Heliyon - 10(2024), 6 vom: 30. März, Seite e27281 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Zhou, Yin [VerfasserIn] |
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| Links: |
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| Themen: |
Cost-effectiveness |
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| Anmerkungen: |
Date Revised 22.03.2024 published: Electronic-eCollection Citation Status PubMed-not-MEDLINE |
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| doi: |
10.1016/j.heliyon.2024.e27281 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM369995260 |
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| 520 | |a © 2024 The Authors. | ||
| 520 | |a The growing demand for renewable energy systems is driven by climate change concerns, government support, technological advancements, economic viability, and energy security. These factors combine to create a strong momentum towards a clean and sustainable energy future. Governments, governments, and individuals are increasingly aware of the environmental impacts of traditional energy sources and adopting renewable energy solutions. Hybrid Renewable Energy Systems (HRES) are developed as an effective way of meeting the energy demands in remote locations. The complexity of the system components and the fluctuation of renewable energy sources make it difficult to design an economical and effective HRES. In this study, the Improved Aquila Optimization (IAO) approach has been suggested as a powerful tool to optimize the HRES design. The study addresses the implementation of the IAO approach in the design of HRES and emphasizes its advantages over other optimization techniques. Through extensive simulations and analyses, our findings demonstrate the superior performance of the IAO algorithm in improving the efficiency and cost-effectiveness of HRES. The optimization process using IAO resulted in a significant reduction in overall system costs, achieving an estimated Net Present Cost (NPC) of $201,973. It translates to a cost reduction of 25% compared to conventional optimization techniques. Furthermore, our analysis reveals that the IAO approach enhances the utilization of renewable energy sources, leading to a 15% increase in overall energy generation efficiency. These results highlight the effectiveness of the IAO approach in addressing the challenges associated with designing HRES. By significantly reducing costs and improving efficiency, it facilitates the adoption of sustainable energy systems in remote areas. The outcomes of this study emphasize the importance of utilizing advanced optimization techniques, such as IAO, to ensure the economic viability and environmental sustainability of HRES | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Cost-effectiveness | |
| 650 | 4 | |a Efficiency | |
| 650 | 4 | |a Energy demand | |
| 650 | 4 | |a Hybrid renewable energy systems (HRES) | |
| 650 | 4 | |a Improved aquila optimization (IAO) | |
| 700 | 1 | |a Chen, Zhimin |e verfasserin |4 aut | |
| 700 | 1 | |a Gong, Ziwei |e verfasserin |4 aut | |
| 700 | 1 | |a Chen, Ping |e verfasserin |4 aut | |
| 700 | 1 | |a Razmjooy, Saeid |e verfasserin |4 aut | |
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