Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Citation - WoS: 103Citation - Scopus: 122One-Day Ahead Wind Speed/Power Prediction Based on Polynomial Autoregressive Model(Institution of Engineering and Technology, 2017) Karakuş, Oktay; Kuruoğlu, Ercan Engin; Altınkaya, Mustafa AzizWind 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.Conference Object Citation - Scopus: 1Nonlinear Robust Control To Maximize Energy Capture in a Variable Speed Wind Turbine Using an Induction Generator(Institute of Electrical and Electronics Engineers Inc., 2009) Iyasere, Erhun; Dawson, Darren M.; Wagner, John R.; Salah, Mohammed; Tatlıcıoğlu, EnverThe emergence of wind turbine systems for electric power generation can help satisfy the growing global demand. This paper proposes a control strategy to maximize the wind energy captured in a variable speed wind turbine, with an internal induction generator, at low to medium wind speeds. The proposed strategy controls the tip speed ratio, via the rotor angular speed, to an optimum point at which the efficiency constant (or power coefficient) is maximal for a particular blade pitch angle and wind speed. This control method allows for aerodynamic rotor power maximization without exact wind turbine model knowledge.