Using genetic algorithm to calculate solar tracking deviation

The four-quadrant sensor algorithm is a good choice for sun tracking deviation detection because of its simple configuration circuit, strong anti-interference ability, fast and accurate tracking ability. The traditional four-quadrant sensor algorithm includes a sum-difference algorithm, diagonal subtraction algorithm, etc. The traditional method is simple but calculation errors exist, while very high tracking accuracy of the solar tracker is required in concentrating photovoltaic systems. To improve the accuracy of deviation estimation, we need to use an iterative method. The running time of the iterative algorithm may not be able to meet the real-time requirements of the sun tracking system. In the meanwhile it is necessary to control the ratio of the solution’s accuracy to algorithmic complexity, making it possible to scheme out the algorithm in hardware. This paper estimates the tracking deviation of four-quadrant sensor feedback based on a genetic algorithm. Key factors in coding strategy, selection mechanism, crossover operator and mutation operator were customized. Simulation experiments show that this method was a real-time one and with small error, which is convenient for hardware implementation and can also meet the needs of the solar tracking system.