TY - GEN
T1 - Modified particle swarm optimization method for MPPT in photovoltaic module arrays
AU - Chang, Long Yi
AU - Chung, Yi Nung
AU - Chao, Kuei Hsiang
AU - Kao, Jia Jing
PY - 2016/7/2
Y1 - 2016/7/2
N2 - This paper first is to study the output characteristics of partial photovoltaic module array under shading. Then, it applies the modified particle swarm optimization (MPSO) to track the maximum power point (MPP) of characteristic curve with peaks. The MPSO makes the weighting and cognition learning factor decrease along with the increasing of iteration times, whereas the social learning factor increase along with the increasing of iteration times, which thus can elevate the performance of maximum power point tracker (MPPT). In addition, the weighting is making fine tuning according to the characteristic curve slope and power deviation, used to speed up the dynamic tracking speed and promote the steady-state performance. Finally, we use the MATLAB software to make simulation, proving that the MPSO algorithm will successfully track the maximum power point of photovoltaic module array output curve with multi-peaks, and the tracking performance is far better than the conventional particle swarm optimization (CPSO) one.
AB - This paper first is to study the output characteristics of partial photovoltaic module array under shading. Then, it applies the modified particle swarm optimization (MPSO) to track the maximum power point (MPP) of characteristic curve with peaks. The MPSO makes the weighting and cognition learning factor decrease along with the increasing of iteration times, whereas the social learning factor increase along with the increasing of iteration times, which thus can elevate the performance of maximum power point tracker (MPPT). In addition, the weighting is making fine tuning according to the characteristic curve slope and power deviation, used to speed up the dynamic tracking speed and promote the steady-state performance. Finally, we use the MATLAB software to make simulation, proving that the MPSO algorithm will successfully track the maximum power point of photovoltaic module array output curve with multi-peaks, and the tracking performance is far better than the conventional particle swarm optimization (CPSO) one.
UR - http://www.scopus.com/inward/record.url?scp=85012915661&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85012915661&partnerID=8YFLogxK
U2 - 10.1109/INDIN.2016.7819360
DO - 10.1109/INDIN.2016.7819360
M3 - Conference contribution
T3 - IEEE International Conference on Industrial Informatics (INDIN)
SP - 1256
EP - 1261
BT - Proceedings - 2016 IEEE 14th International Conference on Industrial Informatics, INDIN 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 14th IEEE International Conference on Industrial Informatics, INDIN 2016
Y2 - 19 July 2016 through 21 July 2016
ER -