Study on optimization model control method of light and temperature coordination of greenhouse crops with benefit priority

Abstract

Facility agriculture is the foundation of modern agriculture. In recent years, energy consumption has become a major bottleneck restricting the development of greenhouse. However, with the support of intelligent control methods, the greenhouse energy-saving market with cost reduction and efficiency has gained increasing attention. Therefore, there is a great potential to expand the research on coordinated energy conservation and optimal control of greenhouse environment, with the objective of improving greenhouse yield and reducing production costs. In this study, a phototemperature coupled net photosynthetic rate (Pn) model was established by using the rectangular hyperbolic correction model of temperature correction, and the model parameters were obtained by Nlinfit fitting. Based on the NSGA-II algorithm, the Pareto optimal frontier was obtained with the objective of minimizing energy consumption and maximizing predicted crop yield. The artificial fish swarm algorithm was used to find the maximum point for the three-dimensional interpolation network of the established crop model. Different evaluation strategies were used to evaluate the optimal solution. The results showed that the average power consumption before and after optimization was reduced by 4.31 %, when Pn remained basically unchanged. When the power consumption remained basically unchanged, the average increase in Pn was about 9.59 %.