Open AccessUnified Control with fuzzy MPPT and PSO based Parameter Optimization for Single Stage PV System based on Energy Saving
Author(s) -
Abdoul Aziz Ismailou,
Honghua Wang,
Tao Lü,
Fan Shi,
YangQuan Chen
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/706/1/012017
Subject(s) - control theory (sociology) , maximum power point tracking , robustness (evolution) , particle swarm optimization , photovoltaic system , pulse width modulation , computer science , harmonics , matlab , fuzzy logic , inverter , grid , engineering , mathematics , control (management) , algorithm , voltage , biochemistry , chemistry , artificial intelligence , electrical engineering , gene , operating system , geometry
This paper presents a unified control for single stage grid-connected system with non-linear load. The proposed control not only ensures power injection into the grid, but also shows its advantage of controlling both active and reactive powers as well as harmonics restraints. This paper explains also the advantage of single stage using quasi- z source inverter (QZSI) which plays the buck/boost operation using space vector pulse width modulation technique (SVPWM) for shoot through insertion during the modulation period. Instantaneous power theory is used to simplify the implementation of the control design for both the inner and outer layer as well as for the reference current generation. To take off the challenge of tracking the maximum power point (MPPT) in any condition, including change in solar irradiance, fuzzy technique is used. Thereby, exhibiting its robustness and adaptability. Besides, to ameliorate the efficiency of the system, the well repute particle swarm optimization algorithm (PSO) is employed to improve the PI controllers’ parameters. Finally matlab/Simulink environment is used to implement and to confirm the effectiveness and the feasibility of the proposed control strategy as well as the optimization method.