TY - GEN
T1 - Method for instantly determining line drop compensator parameters of low-voltage regulator using multiple classifiers
AU - Kikusato, Hiroshi
AU - Takahashi, Naoyuki
AU - Yoshinaga, Jun
AU - Fujimoto, Yu
AU - Hayashi, Yasuhiro
AU - Kusagawa, Shinichi
AU - Motegi, Noriyuki
PY - 2015/1/30
Y1 - 2015/1/30
N2 - A complicated voltage fluctuation in distribution systems and a decline in power quality occur when a large number of photovoltaic (PV) systems are installed. In this paper, the installation of a low-voltage regulator is assumed, and a method for instantly and accurately determining the line drop compensator (LDC) parameters is proposed to perform efficient voltage management, which consists of prediction, operation, and control. In the proposed method, the computational cost to derive the LDC parameters can be reduced by learning the optimality of the parameters in a series of load demands and the PV output using multiple classifiers. We performed numerical simulations to verify the validity of the proposed method. From the results, the classification accuracy is found to improve by considering the majority vote of multiple classifiers. Additionally, the improvement in the voltage control performance is verified.
AB - A complicated voltage fluctuation in distribution systems and a decline in power quality occur when a large number of photovoltaic (PV) systems are installed. In this paper, the installation of a low-voltage regulator is assumed, and a method for instantly and accurately determining the line drop compensator (LDC) parameters is proposed to perform efficient voltage management, which consists of prediction, operation, and control. In the proposed method, the computational cost to derive the LDC parameters can be reduced by learning the optimality of the parameters in a series of load demands and the PV output using multiple classifiers. We performed numerical simulations to verify the validity of the proposed method. From the results, the classification accuracy is found to improve by considering the majority vote of multiple classifiers. Additionally, the improvement in the voltage control performance is verified.
KW - Distribution system
KW - K-nearest-neighbor algorithm
KW - LVR
KW - Random forests
KW - Support vector machine
UR - http://www.scopus.com/inward/record.url?scp=84936973076&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84936973076&partnerID=8YFLogxK
U2 - 10.1109/ISGTEurope.2014.7028851
DO - 10.1109/ISGTEurope.2014.7028851
M3 - Conference contribution
AN - SCOPUS:84936973076
T3 - IEEE PES Innovative Smart Grid Technologies Conference Europe
BT - 2014 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2014
PB - IEEE Computer Society
T2 - 2014 IEEE PES Innovative Smart Grid Technologies Conference Europe, ISGT-Europe 2014
Y2 - 12 October 2014 through 15 October 2014
ER -