Metaheuristic Optimized Semi-Active Structural Control Approaches for a Floating Offshore Wind Turbine
Source abstract
Abstract
Among all the existing possibilities within the renewable energies field, wind energy stands out due to the significant expansion of offshore turbines installed in coastal and deep-sea areas. Although the latter represent considerable energy generation potential due to their larger size and location in areas of strong winds, they are exposed to harsh environmental disturbances, particularly waves, causing these structures to experience vibrations, increasing in this way fatigue, reducing efficiency, and leading to higher maintenance and operational costs. In this work, vibration reduction is achieved using two structural control systems for a 5 MW barge-type floating offshore wind turbine (FOWT), tuned via a metaheuristic method, with genetic algorithms (GAs). Firstly, the standard deviation of the Top Tower Displacement (TTD) is used as a cost function in the GA to optimize a passive Tuned Mass Damper (TMD), resulting in a vibration suppression rate of 34.9% compared to a reference standard TMD. Additionally, two semi-active structural control systems based on a gain scheduling approach are proposed. In one of the approaches, the TMD parameters are optimized based on the amplitude of oscillations, achieving a suppression rate of 45.4%. In the second approach, the TMD parameters are optimized in real time for the identified wave frequencies, demonstrating superior performance for medium-high frequencies compared to the other TMDs.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Wave and Wind Energy Systems · Fluid Dynamics and Vibration Analysis · Wind Energy Research and Development
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Faculty of Informatics, University Complutense of Madrid, 28040 Madrid, Spain
School of Engineering and Mathematical Sciences, The City University, London EC1V 0HV, UK
Digitalization Department, University of Burgos, 09006 Burgos, Spain
Institute of Knowledge Technology, University Complutense of Madrid, 28040 Madrid, Spain
Funding
Spanish Ministry of Science, Innovation and Universities
References (27)
Show source-provided references
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