Yazar "Karatepe, E" seçeneğine göre listele

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  • Küçük Resim Yok
    Öğe
    Neural network based solar cell model
    (Pergamon-Elsevier Science Ltd, 2006) Karatepe, E; Boztepe, M; Colak, M
    This paper presents a neural network based approach for improving the accuracy of the electrical equivalent circuit of a photovoltaic module. The equivalent circuit parameters of a PV module mainly depend on solar irradiation and temperature. The dependence on environmental factors of the circuit parameters is investigated by using a set of current-voltage curves. It is shown that the relationship between them is nonlinear and cannot be easily expressed by any analytical equation. Therefore, the neural network is utilized to overcome these difficulties. The neural network is trained once by using some measured current-voltage curves, and the equivalent circuit parameters are estimated by only reading the samples of solar irradiation and temperature very quickly without solving any nonlinear implicit equations that is necessary in conventional methods. To verify the proposed model, an experimental set up is installed. The comparison between the measured values and the proposed model results shows higher accuracy than the conventional model for all operating conditions. (c) 2005 Elsevier Ltd. All rights reserved.
  • Küçük Resim Yok
    Öğe
    A new approach to fuzzy wavelet system modeling
    (Elsevier Science Inc, 2005) Karatepe, E; Alci, M
    In this paper, we propose simple but effective two different fuzzy wavelet networks (FWNs) for system identification. The FWNs combine the traditional Takagi-Sugeno-Kang (TSK) fuzzy model and discrete wavelet transforms (DWT). The proposed FWNs consist of a set of if-then rules and, then parts are series expansion in terms of wavelets functions. In the first system, while the only one scale parameter is changing with it corresponding rule number, translation parameter sets are fixed in each rule. As for the second system, DWT is used completely by using wavelet frames. The performance of proposed fuzzy models is illustrated by examples and compared with previously published examples. Simulation results indicate the remarkable capabilities of the proposed methods. It is worth noting that the second FWN achieves high function approximation accuracy and fast convergence. (c) 2005 Elsevier Inc. All rights reserved.