Details
| Original language | English |
|---|---|
| Article number | 118459 |
| Number of pages | 19 |
| Journal | Engineering structures |
| Volume | 315 |
| Early online date | 25 Jun 2024 |
| Publication status | Published - 15 Sept 2024 |
Abstract
This study investigates the performance of multiple tuned mass-damper-inerter with multiple electromagnetic motor (TMDI-EM) for the dual objectives of enhancing energy harvesting and dynamic performance in offshore wind turbines (OWTs). OWTs, inherently susceptible to dynamic sensitivity under lateral loads such as wind and waves, necessitate effective solutions for vibration mitigation while harnessing energy from dynamic excitations. The TMDI-EM configuration integrates an electromagnetic motor (EM) as a shunt damper between a secondary mass and an inerter element in series. The scalable inertance of the inerter element allows for adaptability in practical device implementations. Genetic Algorithm (GA) is employed to find optimum parameters for the TMDI-EM system. The research focuses on the dynamic response of OWTs under real-world conditions, where wind and wave forces act as correlated random excitations. Parametric analyses assess the available energy for harvesting at the EM and the displacement variance of the OWT structure as the inertance of the TMDI-EM varies. The study employs methods to optimize the TMDI-EM parameters using Genetic Algorithm, ensuring the system's optimal performance for both enhanced energy harvesting and dynamic response. The findings indicate that lightweight TMDI-EMs, representing only 1.5 % of the OWT structure's mass, demonstrate improved vibration suppression and energy harvesting performance with increasing inertance. This study contributes into the potential integration of TMDI-EMs to enhance the dynamic performance and energy harvesting capabilities of offshore wind turbines under dynamical loading conditions. The use of Genetic Algorithm ensures the identification of optimal parameters for the TMDI-EM system, enhancing its practical applicability.
Keywords
- ANSYS, Energy harvesting offshore wind turbine, Random loading, Tuned mass damper inerter
ASJC Scopus subject areas
- Engineering(all)
- Civil and Structural Engineering
Cite this
- Standard
- Harvard
- Apa
- Vancouver
- BibTeX
- RIS
In: Engineering structures, Vol. 315, 118459, 15.09.2024.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - Vibration control and energy harvesting of offshore wind turbines installed with TMDI under dynamical loading
AU - Elias, Said
AU - Beer, Michael
N1 - Publisher Copyright: © 2024 The Authors
PY - 2024/9/15
Y1 - 2024/9/15
N2 - This study investigates the performance of multiple tuned mass-damper-inerter with multiple electromagnetic motor (TMDI-EM) for the dual objectives of enhancing energy harvesting and dynamic performance in offshore wind turbines (OWTs). OWTs, inherently susceptible to dynamic sensitivity under lateral loads such as wind and waves, necessitate effective solutions for vibration mitigation while harnessing energy from dynamic excitations. The TMDI-EM configuration integrates an electromagnetic motor (EM) as a shunt damper between a secondary mass and an inerter element in series. The scalable inertance of the inerter element allows for adaptability in practical device implementations. Genetic Algorithm (GA) is employed to find optimum parameters for the TMDI-EM system. The research focuses on the dynamic response of OWTs under real-world conditions, where wind and wave forces act as correlated random excitations. Parametric analyses assess the available energy for harvesting at the EM and the displacement variance of the OWT structure as the inertance of the TMDI-EM varies. The study employs methods to optimize the TMDI-EM parameters using Genetic Algorithm, ensuring the system's optimal performance for both enhanced energy harvesting and dynamic response. The findings indicate that lightweight TMDI-EMs, representing only 1.5 % of the OWT structure's mass, demonstrate improved vibration suppression and energy harvesting performance with increasing inertance. This study contributes into the potential integration of TMDI-EMs to enhance the dynamic performance and energy harvesting capabilities of offshore wind turbines under dynamical loading conditions. The use of Genetic Algorithm ensures the identification of optimal parameters for the TMDI-EM system, enhancing its practical applicability.
AB - This study investigates the performance of multiple tuned mass-damper-inerter with multiple electromagnetic motor (TMDI-EM) for the dual objectives of enhancing energy harvesting and dynamic performance in offshore wind turbines (OWTs). OWTs, inherently susceptible to dynamic sensitivity under lateral loads such as wind and waves, necessitate effective solutions for vibration mitigation while harnessing energy from dynamic excitations. The TMDI-EM configuration integrates an electromagnetic motor (EM) as a shunt damper between a secondary mass and an inerter element in series. The scalable inertance of the inerter element allows for adaptability in practical device implementations. Genetic Algorithm (GA) is employed to find optimum parameters for the TMDI-EM system. The research focuses on the dynamic response of OWTs under real-world conditions, where wind and wave forces act as correlated random excitations. Parametric analyses assess the available energy for harvesting at the EM and the displacement variance of the OWT structure as the inertance of the TMDI-EM varies. The study employs methods to optimize the TMDI-EM parameters using Genetic Algorithm, ensuring the system's optimal performance for both enhanced energy harvesting and dynamic response. The findings indicate that lightweight TMDI-EMs, representing only 1.5 % of the OWT structure's mass, demonstrate improved vibration suppression and energy harvesting performance with increasing inertance. This study contributes into the potential integration of TMDI-EMs to enhance the dynamic performance and energy harvesting capabilities of offshore wind turbines under dynamical loading conditions. The use of Genetic Algorithm ensures the identification of optimal parameters for the TMDI-EM system, enhancing its practical applicability.
KW - ANSYS, Energy harvesting offshore wind turbine
KW - Random loading
KW - Tuned mass damper inerter
UR - http://www.scopus.com/inward/record.url?scp=85196764238&partnerID=8YFLogxK
U2 - 10.1016/j.engstruct.2024.118459
DO - 10.1016/j.engstruct.2024.118459
M3 - Article
AN - SCOPUS:85196764238
VL - 315
JO - Engineering structures
JF - Engineering structures
SN - 0141-0296
M1 - 118459
ER -