RSM-Based Optimization of Excitation Capacitance and Speed for a Self-Excited Induction Generator
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A wind turbine system with a self-excited induction generator (SEIG) is one of the best options as power supplier in rural areas because of its low cost, wide speed operation range, brushless structure and low maintenance. Beside its advantages, it has poor voltage and frequency regulation which depend on the generator speed, load impedance, excitation capacitance and magnetizing reactance. This restriction leads the researchers to select the best value of excitation capacitor to maintain the terminal voltage within the upper and lower acceptable limits. The determination of generator speed is another point to be focused to remain frequency at desired level.
In this paper, the response surface method (RSM) is applied in order to determine the optimal steady state performance for the SEIG instead of the commonly used nodal admittance method or the loop impedance technique. Proposed method does not need knowledge of induction machine parameters which makes it superior against classical methods. The main objective of the proposed approach is to determine the excitation capacitance and shaft speed to maintain a constant terminal voltage magnitude and frequency of the SEIG. Consequently, a response surface model is established in which the capacitance value and the shaft speed are considered the inputs, whereas the voltage magnitude and frequency are assumed to be the outputs. The simulation results show the effectiveness of the method proposed in this paper since the regression value (R2) obtained was 99.98%. In particular, for a 4 kW squirrel cage induction generator with a 950 Ω resistive load per phase, the excitation capacitance and shaft speed were found to be 6.897 μF and 1504 rpm respectively. Moreover, the output voltage magnitude and frequency obtained were 230.2 V and 50 Hz, respectively.
This study was supported by Balikesir University (Project No: BAP 2018/03). The authors would also like to thank University of Derby, whose valuable supports lead to reveal this paper.
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