AS-ACO-MTTP Control Strategy For Mismatched Photovoltaic Systems

With the global energy crisis and environmental pollution increasing,people urgently need green energy to replace traditional fossil energy.As a sustainable,clean and inexhaustible new energy,solar energy has attracted attention and developed rapidly,and has become one of the effective conventional technologies for photovoltaic power generation.With the continuous promotion of the photovoltaic industry,photovoltaic power generation technology is becoming more and more mature.How to improve the efficiency of photovoltaic power generation has become a research hotspot in recent years.In particular,the Maximum Power Point Tracking(MPPT)of photovoltaic occurs under the condition of shading and other mismatches.This paper adopts intelligent ant colony algorithm to control the photovoltaic MPPT,starting from the MPPT control problem and model establishment of photovoltaic power generation system,three different algorithms,standard ant colony algorithm,simplified ant colony algorithm and improved AS-ACO,are applied as control strategies in the MPPT control of photovoltaic power generation system,carrying out numerical simulation experiment and engineering experiment,and making comparative analysis of the experimental results in depth,and coming to conclusions: in photovoltaic MPPT control,compared with the standard ant colony algorithm and the simplified ant colony algorithm,the improved AS-ACO algorithm can find the maximum output power in a short time and ensure the minimum error of steady state.In this paper,combined with photovoltaic power generation system,principle of photovoltaic battery and mathematical model,the control problem of photovoltaic system under the mismatch of shadow occlusion is proposed,and the control model of photovoltaic MPPT under mismatch is established.The specific research contents of this paper are as follows:First,the numerical simulation experiment platform and the innovative design engineering experiment platform ”Intelligent Photovoltaic Power System” are briefly introduced,which lays a good foundation for the later control method analysis.Then,applying the standard ant colony algorithm(ACO)to the photovoltaic MPPT control,combining the two experiments for data acquisition;proposing the basic evaluation index of the photovoltaic MPPT performance,analyzing the collected data;it is found that the photovoltaic MPPT control of the standard algorithm requires a large number of ant colony to quickly search for the maximum power point,and the algorithm is complex.Aiming at the problem of the standard algorithm,simplify it,and use the simplified ant colony algorithm(S-ACO)to realize the MPPT control of photovoltaic,compared with the standard algorithm,it is found that the process of the simplified algorithm is simple,and the maximum power point of the search output is also higher than the standard algorithm in the case of using fewer ant colony groups.Finally,aming at the problem of oscillating near the maximum power point of the simplified ant colony algorithm,an improved ant colony algorithm(AS-ACO)is proposed.The path search is performed by the decimal idea,and the decoding mode is changed,the maximum output power of the tracking is larger than the previous two methods,and the time is shorter,the error of steady state is smaller,which makes the photovoltaic MPPT efficiency significantly improved.