Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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Scopus Q: search.filters.scopusQuartile.Q3Subject: search.filters.subject.Wind turbines

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  • Article
    Citation - WoS: 1
    Citation - Scopus: 2
    Feasibility of Large Scale Wind Turbines for Offshore Gas Platform Installation
    (AIMS Press, 2018) Bingöl, Ferhat
    Although, offshore wind energy development emerged under way at the beginning of the millennium, Europe is planning to bring offshore wind energy capacity to over 11.6 GW until 2020. This is nearly 10 times todays installed offshore capacity and equal to nearly 50% of the new planned investment in the wind energy market. The North Sea and the Baltic Sea are the main investment areas due to the shallower sea depth. In this paper an approach to use old gas / oil platforms as the foundation for a wind turbine is examined. An off shore gas platform close to Istanbul Turkey with over 20 years more lifetime is taken as a real-life case, with the wind resource information extracted from the recent large-scale wind atlas study, Global Wind Atlas version 2. The study aims to combine recent offshore economical models with up-to-date scientific wind energy yield assessment models to have a more realistic look on the feasibility of such an approach. The results show that, with the assumption of no extra support structure and capital loan costs, a project can be feasible with bigger then 8MW wind turbines. These may involve a large initial investment but the return of the investment (ROI) can be as low as 8 years. With bigger turbines, profit can be increased, and ROI can be decreased while the Levelized Cost of Energy (LCOE) displays minor decrease after 10 MW.
  • Article
    Citation - WoS: 4
    Citation - Scopus: 8
    Fault Diagnosis of a Wind Turbine Simulated Model Via Neural Networks
    (IFAC Secretariat, 2018) Simani, Silvio; Turhan, Cihan
    The fault diagnosis of wind turbine systems has been proven to be a challenging task and motivates the research activities carried out through this work. Therefore, this paper deals with the fault diagnosis of wind turbines, and it proposes viable solutions to the problem of earlier fault detection and isolation. The design of the fault indicator involves a data-driven approach, as it represents an effective tool for coping with a poor analytical knowledge of the system dynamics, together with noise and disturbances. In particular, the data-driven proposed solution relies on neural networks that are used to describe the strongly nonlinear relationships between measurement and faults. The chosen network architecture belongs to the nonlinear autoregressive with exogenous input topology, as it can represent a dynamic evolution of the system along time. The developed fault diagnosis scheme is tested by means of a high-fidelity benchmark model, that simulates the normal and the faulty behaviour of a wind turbine. The achieved performances are compared with those of other control strategies, coming from the related literature. Moreover, a Monte Carlo analysis validates the robustness of the proposed solutions against the typical parameter uncertainties and disturbances.
  • Article
    Citation - WoS: 36
    Citation - Scopus: 38
    Optimum Seeking-Based Non-Linear Controller To Maximise Energy Capture in a Variable Speed Wind Turbine
    (Institution of Engineering and Technology, 2012) Iyasere, Erhun; Salah, Mohammed; Dawson, Darren M.; Wagner, John R.; Tatlıcıoğlu, Enver
    In this study, an optimum seeking-based robust non-linear controller is proposed to maximise wind energy captured by variable speed wind turbines at low-to-medium wind speeds. The proposed strategy simultaneously controls the blade pitch angle and tip-speed ratio, through the turbine rotor angular speed, to an optimal point at which the power coefficient, and hence the wind turbine efficiency, is maximum. The optimal points are given to the controller by an optimisation algorithm that seeks the unknown optimal blade pitch angle and rotor speed. The control method allows for aerodynamic rotor power maximisation without exact knowledge of the wind turbine model. A representative numerical simulation is presented to show that the wind turbine can be accurately controlled to achieve maximum energy capture. © 2012 The Institution of Engineering and Technology.