TY - GEN
T1 - An AN-GA Controlled SEPIC Converter for Photovoltaic Grid Integration
AU - Priyadarshi, Neeraj
AU - Padmanaban, Sanjeevikumar
AU - Holm-Nielsen, Jens Bo
AU - Ramachandaramurthy, Vigna K.
AU - Bhaskar, Mahajan Sagar
PY - 2019/4
Y1 - 2019/4
N2 - In this paper, Artificial Neural Network (ANN) optimization with Genetic Algorithm (GA) is implemented. The optimized training to ANN is provide using Bayesian regulation. For this study, a Photovoltaic (PV) system has considered and optimal power tracking been interpreted with proper adjustment of ANN weights using GA approach, which reduces the Root Mean Square Error (RMSE). In this work, the single-ended primary-inductor converter (SEPIC) has been utilized for better power tracking from PV modules. SEPIC Converter accomplish with impedance matching power device and provides utmost PV power tracking. Space vector pulse width modulation-dSPACE interface been utilized as an inverter control. Simulated responses show the potency of the proposed system under sag, swell and varying loading conditions.
AB - In this paper, Artificial Neural Network (ANN) optimization with Genetic Algorithm (GA) is implemented. The optimized training to ANN is provide using Bayesian regulation. For this study, a Photovoltaic (PV) system has considered and optimal power tracking been interpreted with proper adjustment of ANN weights using GA approach, which reduces the Root Mean Square Error (RMSE). In this work, the single-ended primary-inductor converter (SEPIC) has been utilized for better power tracking from PV modules. SEPIC Converter accomplish with impedance matching power device and provides utmost PV power tracking. Space vector pulse width modulation-dSPACE interface been utilized as an inverter control. Simulated responses show the potency of the proposed system under sag, swell and varying loading conditions.
KW - Artificial neural networks
KW - Genetic algorithms
KW - Inverters
KW - Voltage control
KW - Matlab
KW - Power quality
KW - Photovoltaic systems
UR - https://ieeexplore.ieee.org/document/8862395/
U2 - 10.1109/CPE.2019.8862395
DO - 10.1109/CPE.2019.8862395
M3 - Article in proceeding
SN - 978-1-7281-3203-7
T3 - International Conference on Compatibility, Power Electronics and Power Engineering (CPE-POWERENG). Proceedings.
BT - 2019 IEEE 13th International Conference on Compatibility, Power Electronics and Power Engineering (CPE-POWERENG)
PB - IEEE (Institute of Electrical and Electronics Engineers)
T2 - 2019 IEEE 13th International Conference on Compatibility, Power Electronics and Power Engineering (CPE-POWERENG)
Y2 - 23 April 2019 through 25 April 2019
ER -