Application of improved bat algorithm for solar PV maximum power point tracking under partially shaded condition

Abstract The power output curves of solar photovoltaic (PV) system have multiple peaks under partially shaded condition. As the same as traditional MPPT (Maximum Power Point Tracking) search methods, bat algorithm often makes optimized results fall into local extremum. So an improved bat algorithm is proposed. Chaos search strategy is introduced in initial arrangement to improve the uniformity and ergodicity of population. Adapting weight is introduced to balance the global searching ability and the local searching ability. Dynamic contraction regain decreases the search range more effectively. Compared with the original algorithm, the rapidity and accuracy of algorithm have been improved. The simulation shows that improved bat algorithm can find the globally optimal point fast, with high precision, under the partially shaded condition.

[1]  N. Rajasekar,et al.  Modified Particle Swarm Optimization technique based Maximum Power Point Tracking for uniform and under partial shading condition , 2015, Appl. Soft Comput..

[2]  Saad Mekhilef,et al.  Experimental verification of P&O MPPT algorithm with direct control based on Fuzzy logic control using CUK converter , 2015 .

[3]  Anis Sakly,et al.  FPGA based hardware implementation of Bat Algorithm , 2017, Appl. Soft Comput..

[4]  Ye Chun-ming Bat Algorithm with Chaotic Search Strategy and Analysis of Its Property , 2013 .

[5]  Fei Xue,et al.  MPPT for PV systems based on a dormant PSO algorithm , 2015 .

[6]  Kok Soon Tey,et al.  Modified incremental conductance MPPT algorithm to mitigate inaccurate responses under fast-changing solar irradiation level , 2014 .

[7]  Fu Chao Application of PSO Algorithm in Global MPPT for PV Array , 2012 .

[8]  Kok Soon Tey,et al.  Modified Incremental Conductance Algorithm for Photovoltaic System Under Partial Shading Conditions and Load Variation , 2014, IEEE Transactions on Industrial Electronics.

[9]  Long Xia Fish swarm algorithm optimized by PSO applied in maximum power point tracking of photovoltaic power system , 2012 .

[10]  Xin-She Yang,et al.  New directional bat algorithm for continuous optimization problems , 2017, Expert Syst. Appl..

[11]  Xin-She Yang,et al.  An improved discrete bat algorithm for symmetric and asymmetric Traveling Salesman Problems , 2016, Eng. Appl. Artif. Intell..

[12]  Xiaoli Meng,et al.  A review of maximum power point tracking methods of PV power system at uniform and partial shading , 2016 .

[13]  Fei Xue,et al.  Tracking the global maximum power point of a photovoltaic system under partial shading conditions using a modified firefly algorithm , 2016 .

[14]  Saad Mekhilef,et al.  Implementation of a modified incremental conductance MPPT algorithm with direct control based on a fuzzy duty cycle change estimator using dSPACE , 2014 .

[15]  Saad Mekhilef,et al.  State of the art artificial intelligence-based MPPT techniques for mitigating partial shading effects on PV systems – A review , 2016 .

[16]  Yie-Tone Chen,et al.  Jumping maximum power point tracking method for PV array under partially shaded conditions , 2016 .

[17]  Ali M. Eltamaly,et al.  A comprehensive comparison of different MPPT techniques for photovoltaic systems , 2015 .

[18]  Rubiyah Yusof,et al.  Maximum power point tracking of partial shaded photovoltaic array using an evolutionary algorithm: A particle swarm optimization technique , 2014 .

[19]  Ruoli Tang,et al.  Maximum power point tracking of large-scale photovoltaic array , 2016 .

[20]  D. Devaraj,et al.  Artificial neural network based modified incremental conductance algorithm for maximum power point tracking in photovoltaic system under partial shading conditions , 2013 .

[21]  D. Devaraj,et al.  Development and analysis of adaptive fuzzy controllers for photovoltaic system under varying atmospheric and partial shading condition , 2013, Appl. Soft Comput..