Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği

Permanent URI for this collectionhttps://hdl.handle.net/11147/11

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  • Article
    Citation - WoS: 103
    Citation - Scopus: 122
    One-Day Ahead Wind Speed/Power Prediction Based on Polynomial Autoregressive Model
    (Institution of Engineering and Technology, 2017) Karakuş, Oktay; Kuruoğlu, Ercan Engin; Altınkaya, Mustafa Aziz
    Wind has been one of the popular renewable energy generation methods in the last decades. Foreknowledge of power to be generated from wind is crucial especially for planning and storing the power. It is evident in various experimental data that wind speed time series has non-linear characteristics. It has been reported in the literature that nonlinear prediction methods such as artificial neural network (ANN) and adaptive neuro fuzzy inference system (ANFIS) perform better than linear autoregressive (AR) and AR moving average models. Polynomial AR (PAR) models, despite being non-linear, are simpler to implement when compared with other non-linear AR models due to their linear-in-the-parameters property. In this study, a PAR model is used for one-day ahead wind speed prediction by using the past hourly average wind speed measurements of Ceşme and Bandon and performance comparison studies between PAR and ANN-ANFIS models are performed. In addition, wind power data which was published for Global Energy Forecasting Competition 2012 has been used to make power predictions. Despite having lower number of model parameters, PAR models outperform all other models for both of the locations in speed predictions as well as in power predictions when the prediction horizon is longer than 12 h.
  • 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.