Enhancing the performance of hybrid wave-wind energy systems through a fast and adaptive chaotic multi-objective swarm optimisation method

Hybrid offshore renewable energy platforms have been proposed to optimise power production and reduce the levelised cost of energy by integrating or co-locating several renewable technologies. One example is a hybrid wave-wind energy system that combines offshore wind turbines with wave energy conve...

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Veröffentlicht in:	Applied energy Jg. 362; S. 122955
Hauptverfasser:	Neshat, Mehdi, Sergiienko, Nataliia Y., Nezhad, Meysam Majidi, da Silva, Leandro S.P., Amini, Erfan, Marsooli, Reza, Astiaso Garcia, Davide, Mirjalili, Seyedali
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 15.05.2024
Schlagworte:	acceleration algorithms Australia coasts damping decline energy Genetic algorithms Hybrid wave-wind energy system Hybrid wave-wind energy systems Hybrid waves hybrids income longevity Multi-objective optimisation algorithm Multi-objective optimization algorithm Multi-objectives optimization Multiobjective optimization Offshore oil well production Offshore wind turbine Offshore wind turbines Optimization algorithms power generation Power quality Power takeoffs spring Sustainable energy Swarm intelligence algorithms swarms system optimization water power wave energy Wave energy conversion Wave energy converters Wave wind wind Wind energy systems Wind power wind turbine wind turbines Australia Swarm-intelligence algorithms Offshore wind turbine Hybrid wave-wind energy systems Sustainable energy Wave energy converters Multi-objective optimisation algorithm Genetic algorithms
ISSN:	0306-2619, 1872-9118, 1872-9118
Online-Zugang:	Volltext
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