A multi-factor coordinated energy-saving optimization control method for greenhouse environment

Abstract

The invention relates to a multi-factor coordinated energy-saving optimization control method of a greenhouse environment. The method comprises: (1), an expected daily average temperature of the crop in each growth period is set and weather forecast data of next seven days are obtained; (2), a greenhouse ventilation system state is estimated; (3), setting values of all environmental factors in the greenhouse are set by using a multi-factor coordination algorithm according to the steps (1) and (2), wherein the environmental factors include a temperature, humidity, a light radiation intensity and carbon dioxide concentration; and (4), real-time environmental factor values are obtained and corresponding executing mechanisms in the greenhouse are regulated according to the environmental factor setting values. Compared with the prior art, on the basis of crop physiological properties like temperature accumulation, the energy consumption of the greenhouse can be reduced effectively. With corresponding strategies, secondary greenhouse environment factors are coordinated to main temperature factors equivalently, thereby guaranteeing the precision and efficiency of greenhouse regulation, avoiding unnecessary energy wasting, saving the regulation cost, and ensuring the precise and effective controlling.

Description

technical field [0001] The invention relates to the technical field of agricultural environment control, in particular to a multi-factor coordinated energy-saving optimization control method for a greenhouse environment. Background technique [0002] Greenhouses are the infrastructure for facility agriculture and factory agriculture. Greenhouse environment control is based on making full use of natural resources, by changing greenhouse environmental factors such as temperature, humidity, light, carbon dioxide, etc. to meet the quantitative requirements of the greenhouse climate in each growth period of crop growth, and realizing the control of greenhouse climate data through the computer control system. The acquisition and processing of the greenhouse, and the corresponding automatic control algorithm, realize the regulation of the greenhouse ventilation system (skylight and side window), sunshade system, heat preservation system, heating system, cooling system, carbon dioxi...

AI Technical Summary

Problems solved by technology

This method has the advantages of being simple and easy to operate, and makes full use of the advantage of crops’ adaptability to the environment, but the disadvantages are also obvious. First, when encountering extreme weather such as high temperature or cold wave, the cooling or heating system load will increase. Increase the energy consumption of greenhouse regulation; second, it cannot meet the needs of crops for environmental factors (such as humidity and carbon dioxide concentration) other than temperature

[0005] 2. Disharmony between regulatory means and environmental factors

Unreasonable control methods will also increase energy consumption. For example, in winter, the outdoor temperature is low and the humidity in the greenhouse is high. Too low temperature is not conducive to crop growth, and too high humidity may cause crop root rot and other hazards.

In terms of temperature, it is necessary to heat the greenhouse, and in terms of ventilation, it is necessary to ventilate the greenhouse for dehumidification, and ventilation will cause a large amount of heat loss, increasing the cost of greenhouse production

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