Abstract
The harmonic reduction and power factor improvement are conflict to each other under non sinusoidal supply conditions. Optimization of total harmonic distortion (THD) and power factor subjected to power quality constraints for the evaluation of proposed APLC is carried out in this paper. Non dominated sorting genetic algorithm-II is used to obtain the reference source current to optimize both power factor and THD. The proposed APLC is evaluated using neural network and fuzzy logic. Neural network is trained from the samples obtained using conventional fixed frequency variable slope (FFVS) method. Fuzzy logic rule base is created from the same samples. Computer simulations of the proposed APLC have been performed using MATLAB and the results are encouraging. The results show that the proposed APLC can reduce the total harmonics distortion of a specific non-linear load from 13 % to about 3 % and improve the power factor close to unity under non sinusoidal conditions.
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Kavitha, D., Renuga, P., Suresh Kumar, V. (2015). Artificial Neural Network and Fuzzy Logic Controlled Single Phase Active Power Line Conditioner Under Non Sinusoidal Supply Condition: A Comparison. In: Kamalakannan, C., Suresh, L., Dash, S., Panigrahi, B. (eds) Power Electronics and Renewable Energy Systems. Lecture Notes in Electrical Engineering, vol 326. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2119-7_47
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DOI: https://doi.org/10.1007/978-81-322-2119-7_47
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