TY - GEN
T1 - Artificial Neural Network Based Dynamic Voltage Restorer for Improvement of Power Quality
AU - Sunny, Md Samiul Haque
AU - Hossain, Eklas
AU - Ahmed, Mikal
AU - Un-Noor, Fuad
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/12/3
Y1 - 2018/12/3
N2 - Dynamic Voltage Restorer (DVR) is a custom power device used as an effective solution in protecting sensitive loads from voltage disturbances in power distribution systems. The efficiency of the control technique, that conducts the switching of the inverters, determines the DVR efficiency. Proportional-Integral-Derivative (PID) control is the general technique to do that. The power quality restoration capabilities of this controller are limited, and it produces significant amount of harmonics - all of which stems from this linear technique's application for controlling non-linear DVR. As a solution, this paper proposes an Artificial Neural Network (ANN) based controller for enhancing restoration and harmonics suppression capabilities of DVR. A detailed comparison of Neural Network controller with PID driven controller and Fuzzy logic driven controller is also illustrated, where the proposed controller demonstrated superior performance with a mere 13.5% Total Harmonic Distortion.
AB - Dynamic Voltage Restorer (DVR) is a custom power device used as an effective solution in protecting sensitive loads from voltage disturbances in power distribution systems. The efficiency of the control technique, that conducts the switching of the inverters, determines the DVR efficiency. Proportional-Integral-Derivative (PID) control is the general technique to do that. The power quality restoration capabilities of this controller are limited, and it produces significant amount of harmonics - all of which stems from this linear technique's application for controlling non-linear DVR. As a solution, this paper proposes an Artificial Neural Network (ANN) based controller for enhancing restoration and harmonics suppression capabilities of DVR. A detailed comparison of Neural Network controller with PID driven controller and Fuzzy logic driven controller is also illustrated, where the proposed controller demonstrated superior performance with a mere 13.5% Total Harmonic Distortion.
KW - Artificial Neural Network (ANN)
KW - Dynamic Voltage Restorer (DVR)
KW - Fuzzy logic
KW - PID
KW - Power quality
UR - http://www.scopus.com/inward/record.url?scp=85060310804&partnerID=8YFLogxK
U2 - 10.1109/ECCE.2018.8558470
DO - 10.1109/ECCE.2018.8558470
M3 - Conference contribution
AN - SCOPUS:85060310804
T3 - 2018 IEEE Energy Conversion Congress and Exposition, ECCE 2018
SP - 5565
EP - 5572
BT - 2018 IEEE Energy Conversion Congress and Exposition, ECCE 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th Annual IEEE Energy Conversion Congress and Exposition, ECCE 2018
Y2 - 23 September 2018 through 27 September 2018
ER -