Research On Greenhouse Temperature Model In Chongqing Area

Plastic greenhouse is the main horticultural facility type south of china, which is also the most popular greenhouse type established in Chongqing. The environment in the greenhouse has involved various kinds of environmental factors,such as temperature, illumination, humidity, as well as the density of carbon dioxide .etc, which is a complex system. This paper will use the unified modelling languanges(UML) to carry on the model to the greenhouse and analyse,in a qualitative way,every influencing factor in the greenhouse. The establishment of this model on the one hand is advantageous for following analysis to the greenhouse environment,and serves for the greenhouse's maintenance management, which also unifies this model and the design,plus the movement of greenhouse, for carring on the transformation of the greenhouse, on the other hand, based on this model ,it can do all kinds of simulation and illation,which has provided a good platform for the control of indoor environment of greenhouse..In the foundation of UML model, this paper establishes three models to the greenhouse temperature: 1), the physical model reflecting changes of the greenhouse's temperature;2),the temperature estimate coefficient model;3),the greenhouse's temperature prediction model based on genetic algorithm(GA).which also compares these three models.The physical model is based on the previous research work,using the thermodynamic principle, the technology and experience formula of solar energy, establishing a dynamic model of greenhouse's temperature prediction,which quantificationally describes many physical processes ,such as the solar radiation, long-wave radiation, convection heat transfer, the evaporation of earth's surface, natural ventilation, crop transpiration leading to the exchange between manifested heat and latent heat, etc, and also make a confirmation with Matlab, finding that the model is so precise that it can be both used as a prediction of greenhouse's temperature and the theory basis for the establishment of the greenhouse's temperature prediction model,however,due to the consideration of the flowing of all the greenhouse energy,the model is complicated,so it is inconveniences to the system model which used as control.The temperature estimate coefficient model and the greenhouse's temperature prediction model based on genetic algorithm(GA) are obtained by carrying on the essential simplification,based on the theory of physical model with considering the quite complex features of the physical model.The temperature estimate coefficient model is based on the theory of physical model, according to climate characteristics in Chongqing,carrying on the analysis of the heating greenhouse. Futhermore,after paying more analysis, it turnes be found that, in the situation of neglecting and simplifying some factors of the indoor temperature and the utilise of the least squares method established a static model,the precision is higher when the solar radiation is in a weaker situation,which can give a better guidance to the greenhouse's construction and management, especially to the choice of the appropriate fans.The greenhouse's temperature prediction model based on the genetic algorithm is another model considering the fact that the accuracy of the greenhouse's temperature estimate coefficient is not high enough, which is based on the characteristic of the greenhouse and the time delay of the temperature, regarding the greenhouse as a whole, To ensure the accuracy of the forecast, this paper also uses the genetic algorithm(GA) to check and calculate the model,which comes to few errors. As a simple model, The model, with a lag of pure inertia simulation system links to the model, can examine the process in the actual movement of the greenhouse environmentand predict the greenhouse's temperature, this model may directly use every existing mature control theory to control the greenhouse, which is helpful in the optimized control and the scientific management of the greenhousetheTo summarize,using these models can provide predictability to the changes of greenhouse's temperature,minimize the energy consumption, improve efficiency,plus increase economic benefits.