TY - JOUR
T1 - Multi-mode wave energy converter design optimisation using an improved moth flame optimisation algorithm
AU - Neshat, Mehdi
AU - Sergiienko, Nataliia Y.
AU - Mirjalili, Seyedali
AU - Nezhad, Meysam Majidi
AU - Piras, Giuseppe
AU - Garcia, Davide Astiaso
N1 - Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2021/7/1
Y1 - 2021/7/1
N2 - Ocean renewable wave power is one of the more encouraging inexhaustible energy sources, with the potential to be exploited for nearly 337 GW worldwide. However, compared with other sources of renewables, wave energy technologies have not been fully developed, and the produced energy price is not as competitive as that of wind or solar renewable technologies. In order to commercialise ocean wave technologies, a wide range of optimisation methodologies have been proposed in the last decade. However, evaluations and comparisons of the performance of state-ofthe-art bio-inspired optimisation algorithms have not been contemplated for wave energy converters’ optimisation. In this work, we conduct a comprehensive investigation, evaluation and comparison of the optimisation of the geometry, tether angles and power take-off (PTO) settings of a wave energy converter (WEC) using bio-inspired swarm-evolutionary optimisation algorithms based on a sample wave regime at a site in the Mediterranean Sea, in the west of Sicily, Italy. An improved version of a recent optimisation algorithm, called the Moth–Flame Optimiser (MFO), is also proposed for this application area. The results demonstrated that the proposed MFO can outperform other optimisation methods in maximising the total power harnessed from a WEC.
AB - Ocean renewable wave power is one of the more encouraging inexhaustible energy sources, with the potential to be exploited for nearly 337 GW worldwide. However, compared with other sources of renewables, wave energy technologies have not been fully developed, and the produced energy price is not as competitive as that of wind or solar renewable technologies. In order to commercialise ocean wave technologies, a wide range of optimisation methodologies have been proposed in the last decade. However, evaluations and comparisons of the performance of state-ofthe-art bio-inspired optimisation algorithms have not been contemplated for wave energy converters’ optimisation. In this work, we conduct a comprehensive investigation, evaluation and comparison of the optimisation of the geometry, tether angles and power take-off (PTO) settings of a wave energy converter (WEC) using bio-inspired swarm-evolutionary optimisation algorithms based on a sample wave regime at a site in the Mediterranean Sea, in the west of Sicily, Italy. An improved version of a recent optimisation algorithm, called the Moth–Flame Optimiser (MFO), is also proposed for this application area. The results demonstrated that the proposed MFO can outperform other optimisation methods in maximising the total power harnessed from a WEC.
KW - Bio-inspired
KW - Evolutionary algorithms
KW - Meta-heuristics
KW - Moth Flame Optimisation
KW - Optimisation algorithms
KW - Power take-off
KW - Renewable energy systems
KW - Swarm intelligence
KW - Wave energy converters
UR - http://www.scopus.com/inward/record.url?scp=85109089297&partnerID=8YFLogxK
U2 - 10.3390/en14133737
DO - 10.3390/en14133737
M3 - Article
AN - SCOPUS:85109089297
SN - 1996-1073
VL - 14
JO - Energies
JF - Energies
IS - 13
M1 - 3737
ER -