TY - GEN
T1 - Self-Optimized Drift-Avoidance MPPT Algorithm for Photovoltaic Systems
AU - Zhang, Xiaofeng
AU - Song, Jiaxing
AU - Chen, Zhaotong
PY - 2022/12/27
Y1 - 2022/12/27
N2 - Generally, photovoltaic (PV) power generation is easily affected by changes in environmental conditions, such as irradiance and temperature. To extract the power at maximum power point (MPP), the perturbation and observation (P&O) method is widely adopted in industrial maximum power point tracking (MPPT), considering the low implementing complexity. However, the drift issue easily occurs in conventional P&O MPPT under the rapidly increasing irradiance, which might reduce the conversion efficiency. To address this issue, a self-optimized drift-avoidance MPPT algorithm is proposed in this paper, introducing the PV current pointer and self-adaptive step size regulation ability. The effectiveness of the proposed MPPT algorithm is validated by various operating scenarios in MATLAB/Simulink. A fair comparison with other advanced MPPT controls is accrued to highlight the advances of the proposed control. The simulation comparison shows that the proposed algorithm has a faster tracking speed, higher steady-state accuracy, and more reliable drift suppression capability.
AB - Generally, photovoltaic (PV) power generation is easily affected by changes in environmental conditions, such as irradiance and temperature. To extract the power at maximum power point (MPP), the perturbation and observation (P&O) method is widely adopted in industrial maximum power point tracking (MPPT), considering the low implementing complexity. However, the drift issue easily occurs in conventional P&O MPPT under the rapidly increasing irradiance, which might reduce the conversion efficiency. To address this issue, a self-optimized drift-avoidance MPPT algorithm is proposed in this paper, introducing the PV current pointer and self-adaptive step size regulation ability. The effectiveness of the proposed MPPT algorithm is validated by various operating scenarios in MATLAB/Simulink. A fair comparison with other advanced MPPT controls is accrued to highlight the advances of the proposed control. The simulation comparison shows that the proposed algorithm has a faster tracking speed, higher steady-state accuracy, and more reliable drift suppression capability.
KW - Drift
KW - MPPT Algorithms
KW - P&O
KW - Photovoltaic power
KW - Self-Optimized
UR - http://www.scopus.com/inward/record.url?scp=85146430241&partnerID=8YFLogxK
U2 - 10.1109/ICCASIT55263.2022.9986947
DO - 10.1109/ICCASIT55263.2022.9986947
M3 - Chapter in a published conference proceeding
AN - SCOPUS:85146430241
T3 - Proceedings of 2022 IEEE 4th International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2022
SP - 739
EP - 743
BT - Proceedings of 2022 IEEE 4th International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2022
A2 - Sun, Huabo
PB - IEEE
T2 - 4th IEEE International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2022
Y2 - 12 October 2022 through 14 October 2022
ER -
