Browsing by Author "Cetin, NS"

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    NEURAL PREDICTION OF POWER FACTOR IN WIND TURBINES
    Ata, R; Cetin, NS
    The power generated by wind turbines depends on several factors. One of them is the power factor also known as blade efficiency. In this study, the power factor is predicted using Artificial Neural Networks (ANN) and comparisons made with conventional model approach for the selected turbine profiles mostly used in practice. The study has shown that the prediction of power factors from seven input parameters by ANN yields better results than those of the conventional model.
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    Energy management for on-grid and off-grid wind/PV and battery hybrid systems
    Basaran, K; Cetin, NS; Borekci, S
    Renewable energy systems such as photovoltaic (PV) and wind energy systems are widely designed grid connected or autonomous. This is a problem especially in small powerful system due to the restriction on the inverter markets. Inverters which are utilised in these kinds of energy systems operate on grid or off grid. In this study, a novel power management strategy has been developed by designing a wind-PV hybrid system to operate both as an autonomous system and as a grid-connected system. The inverter used in this study has been designed to operate both on-grid and off-grid. Due to the continuous demand for energy, gel batteries are used in the hybrid system. The designed Power Management Unit performs measurement from various points in the system and in accordance with this measurement; it provides an effective energy transfer to batteries, loads and grid. The designed control unit provided the opportunity to work more efficiently up to 10% rate.
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    Identifying system characteristics of autonomous wind turbines: Measurement system design
    Ates, AM; Cetin, NS
    In this study, an autonomous wind turbine system has been simulated. Meteorological data gathered at the turbine's location and the turbine's characteristics have been measured in one-second periods of time. Based on these measurement values, simulation values and measured values have been compared synchronously, using a software program prepared in a graphic media. The study initially used the MATLAB program for turbine simulation. However, the MATLAB program ran too slowly because of the study's large amount of data calculations. Moreover, observation of measured data simulation results on the same graph and simultaneous Internet results proved to be inefficient. For these reasons, a new program, Turbine Analyzer, was prepared, using Delphi programming language. Simulation results taken from MATLAB and Turbine Analyzer were compared, and the newly written program was tested. In this study, an original system, created to conduct turbine tests, has achieved characteristics tests of small-scale (20 kW and below) autonomous wind turbines. (C) 2013 AIP Publishing LLC.