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Design, optimization, and data analysis of solar-tidal hybrid renewable energy system for Hurawalhi, Maldives
•Study all the renewable energy resource assessments at Hurawalhi, the Maldives, using linear regression-based data analysis.•Planning Hierarchies in Operations of Multi-Network Renewable Energy System by HOMER software.•Cost optimization is done through the chaotic particle swarm optimization and c...
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Published in: | Cleaner Energy Systems 2023-12, Vol.6, p.100088, Article 100088 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | •Study all the renewable energy resource assessments at Hurawalhi, the Maldives, using linear regression-based data analysis.•Planning Hierarchies in Operations of Multi-Network Renewable Energy System by HOMER software.•Cost optimization is done through the chaotic particle swarm optimization and cuckoo optimization technique.•Survival test is done through the logrank and probit analysis.
In the modern era, every country work towards sustainable development with the help of effective utilization of renewable energy system. The design and planning of multi-renewable energy system networks for Hurawalhi, Maldives, with an approximate 450.09 KW load, is proposed in this study. The first resource assessment for solar radiation, wind velocity, and the tidal range is done through linear regression and decision tree-based data analysis. Design of the system is done through the HOMER software, where the electricity production (KWh/Year) through the solar and tidal systems are 1,401,086 and 197,509, respectively. The energy generation through the proposed system is 1593.6 kWh/day (Baseline) and 2424.25 (Scaled). Cost optimization is done through the Chaotic Particle Swarm Optimization and Cuckoo Optimization techniques. Further survival measurement is done through the logrank and probit analysis.
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ISSN: | 2772-7831 2772-7831 |
DOI: | 10.1016/j.cles.2023.100088 |