TY - GEN
T1 - Maximum power point tracking Algorithm Using ANFIS with Constant Power Generation Facility
AU - Noman, Abdullah M.
AU - Alkuhayli, Abdulaziz
AU - Al-Shamma'A, Abdullrahman A.
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - A new algorithm based on Adaptive Neuro-Fuzzy Inference System (ANFIS) controller is proposed in this paper for maximum power point tracking and constant power generation (MPPT-CPG) of PV modules. The proposed algorithm is investigated using PV module, DC-DC buck-boost converter, and a resistive load. Four input variable are used in the proposed algorithm, PV module's voltage, PV module's current, PV cell's temperature, and an input power limit variable. The power limit variable is the guidance of the proposed algorithm to work as an MPPT or to act as a CPG. If the power limit variable is higher than the maximum power of the PV module, the proposed algorithm tracks the available maximum power point (MPP). However, if the power limit is lower than the MPP, the proposed algorithm tracks the inserted power limit value. The proposed MPPT-CPG based ANFIS algorithm is modeled using MATLAB/SIMULINK. It is tested under disturbances in the weather conditions and under changing the power limit variable. The simulation results are presented to verify the proposed topology effectiveness and reliability.
AB - A new algorithm based on Adaptive Neuro-Fuzzy Inference System (ANFIS) controller is proposed in this paper for maximum power point tracking and constant power generation (MPPT-CPG) of PV modules. The proposed algorithm is investigated using PV module, DC-DC buck-boost converter, and a resistive load. Four input variable are used in the proposed algorithm, PV module's voltage, PV module's current, PV cell's temperature, and an input power limit variable. The power limit variable is the guidance of the proposed algorithm to work as an MPPT or to act as a CPG. If the power limit variable is higher than the maximum power of the PV module, the proposed algorithm tracks the available maximum power point (MPP). However, if the power limit is lower than the MPP, the proposed algorithm tracks the inserted power limit value. The proposed MPPT-CPG based ANFIS algorithm is modeled using MATLAB/SIMULINK. It is tested under disturbances in the weather conditions and under changing the power limit variable. The simulation results are presented to verify the proposed topology effectiveness and reliability.
KW - ANFIS
KW - Constant Power Generation
KW - DC-DC Buck-Boost Converter
KW - MPPT
KW - Solar Photovoltaic
UR - https://www.scopus.com/pages/publications/85139470576
U2 - 10.1109/CPE-POWERENG54966.2022.9880869
DO - 10.1109/CPE-POWERENG54966.2022.9880869
M3 - Conference contribution
AN - SCOPUS:85139470576
T3 - 2022 IEEE 16th International Conference on Compatibility, Power Electronics, and Power Engineering, CPE-POWERENG 2022
BT - 2022 IEEE 16th International Conference on Compatibility, Power Electronics, and Power Engineering, CPE-POWERENG 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 16th IEEE International Conference on Compatibility, Power Electronics, and Power Engineering, CPE-POWERENG 2022
Y2 - 29 June 2022 through 1 July 2022
ER -
