Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
Browse
Search Results
Now showing 1 - 2 of 2
Article Citation - WoS: 4Citation - Scopus: 8Fault Diagnosis of a Wind Turbine Simulated Model Via Neural Networks(IFAC Secretariat, 2018) Simani, Silvio; Turhan, CihanThe 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 Active Fault Tolerant Control of a Wind Farm System(IFAC Secretariat, 2018) Simani, Silvio; Turhan, CihanIn order to enhance the 'sustainability’ of offshore wind farms, thus skipping unplanned maintenance operations and costs, that can be important for offshore systems, the earlier management of faults represents the key point. Therefore, this work studies the development of an adaptive sustainable control scheme with application to a wind farm benchmark consisting of nine wind turbine systems. They are described via their nonlinear models, as well as the wind and wake effects among the wind turbines of the wind park. The fault tolerant control strategy uses the recursive estimation of the faults provided by nonlinear estimators designed via a nonlinear differential algebraic tool. This aspect of the study, together with the more straightforward solution based on a data-driven scheme, is the key issue when on-line applications are proposed for a viable implementation of the proposed solutions.