TY - JOUR
T1 - Design of an optimal fuzzy controller to obtain maximum power in solar power generation system
AU - Farajdadian, Shahriar
AU - Hosseini, S. M.Hassan
N1 - Publisher Copyright:
© 2019 International Solar Energy Society
PY - 2019/4
Y1 - 2019/4
N2 - P-V characteristic of the solar cells are nonlinear and depends on the environmental conditions such as irradiations, sunlight incident angle, cell temperature, and load conditions. Therefore it is crucial to operate the photovoltaic module at its maximum power point (MPP) all the time. Hence, a Maximum power point tracking (MPPT) methods are used to maximize the PV module output power by tracking continuously the MPP. In this paper, fuzzy logic controllers (FLC) are designed for maximum power point tracking (MPPT) in a photovoltaic system and then fuzzy membership functions of the fuzzy controller are optimized using Firefly Algorithm (FA) to generate the proper duty cycle. FA which is inspired by natural species to optimize nonlinear functions is one of the most successful and low-cost algorithms in this field. Finally, PV system with FLC-FA is compared with other methods like perturbation and observation (P&O) and fuzzy controller- Particle swarm optimization (PSO). According to the simulation results, asymmetric fuzzy membership functions based on FA increase tracking speed of MPPT and improve tracking accuracy compared to P&O, symmetric fuzzy membership functions and asymmetric fuzzy membership functions based on PSO.
AB - P-V characteristic of the solar cells are nonlinear and depends on the environmental conditions such as irradiations, sunlight incident angle, cell temperature, and load conditions. Therefore it is crucial to operate the photovoltaic module at its maximum power point (MPP) all the time. Hence, a Maximum power point tracking (MPPT) methods are used to maximize the PV module output power by tracking continuously the MPP. In this paper, fuzzy logic controllers (FLC) are designed for maximum power point tracking (MPPT) in a photovoltaic system and then fuzzy membership functions of the fuzzy controller are optimized using Firefly Algorithm (FA) to generate the proper duty cycle. FA which is inspired by natural species to optimize nonlinear functions is one of the most successful and low-cost algorithms in this field. Finally, PV system with FLC-FA is compared with other methods like perturbation and observation (P&O) and fuzzy controller- Particle swarm optimization (PSO). According to the simulation results, asymmetric fuzzy membership functions based on FA increase tracking speed of MPPT and improve tracking accuracy compared to P&O, symmetric fuzzy membership functions and asymmetric fuzzy membership functions based on PSO.
KW - Firefly Algorithm
KW - Fuzzy logic controller
KW - Maximum power point tracking
KW - Particle swarm optimization
KW - Perturbation and observation
KW - Photovoltaic
UR - http://www.scopus.com/inward/record.url?scp=85061959606&partnerID=8YFLogxK
U2 - 10.1016/j.solener.2019.02.051
DO - 10.1016/j.solener.2019.02.051
M3 - Journal article
AN - SCOPUS:85061959606
SN - 0038-092X
VL - 182
SP - 161
EP - 178
JO - Solar Energy
JF - Solar Energy
ER -