A Study On Automatic Tracking And Intelligent Charging Of Photovoltaic System

The solar power has become one of strong competitors in the resource competitivefield, as confronted with the shortage fossil resource state. And solar panel is the mainchannel to utilize the solar energy. But the low conversion efficiency is a big obstacle forextensive application of the solar panel. Thus, more and more people have paid attention tothe methods of improving the conversion efficiency. Firstly, tracking the sun systemappeared to get the strongest light at any time with the sunrise and sunset. But thesingle-axis tracking method does not conform to the law of long time movement of the sun,and the common double-axis tracking methods also exist the inaccuracy. Secondly, in theprocess of maximum power point tracking (MPPT), the common methods can lead to falsetracking because of changeable environment. At last but not least, both the unstable outputcurrent of the solar panel and very short various time demand an intelligent chargingsystem to charge the battery fast and safely. The charging current should be controlledbased on the state of the battery.According to the above problems, the main studies are listed as follows:(1)Based on the output of the panels it can be seen that the illumination intensity isstronger, the output power of photovoltaic panels is greater. In this paper, the sun trackingsystem is designed regarding the sunlight illumination as a control parameter, which isused to improve the generation of photovoltaic. The double-axis with fuzzy control methodis employed to track the sunlight, ensure that the sunlight can irradiate the solar panelvertically.(2)The maximum power of the panels will shift because of the change of temperatureand illumination intensity, which leads to that the maximum power point tracking becomesmore difficult. In this paper, the improved particle swarm optimization algorithm isadopted to search the best value. And the maximum power point can be tracked with theparticle swarm algorithm in the change environment.(3)The stairs type constant current charging method is adopted with short timedischarging based on the Mas curve in this paper. Because the common charging methodscan not shorten the charging time and can not ensure the battery’s safety. Charging directlywhen the output current is small, and charging the battery with stairs type constant currentmethod when the output current is big. Then charging the battery with very small currentwhen the battery is full. In this way, the battery can be charged safely and quickly. To better understand and solve the above problems, in this paper, tracking the sun,MPPT and charging the battery system are researched. The results indicate that the angleoffset is smaller than3, when the double-axis with fuzzy control method is adopted. Themaximum power point can be tracked within1second by the particle swarm algorithm.And the65AH battery can be charged within2hours using stairs type constant currentcharging method. These algorithms can be achieved in FPGA(field programmable gatearray).