Energy saving thermal comfort control method of air conditioning system

Abstract

The invention discloses an energy saving thermal comfort control method of an air conditioning system. The method comprises the following steps: (1) when an air conditioner is started, a preset value of thermal comfort PMV is obtained; (2) the clothing thermal resistance and the human body metabolic rate are obtained; (3) an indoor thermal environment initial state point and an energy consumption value corresponding to the initial state point are obtained; (4) an optimizing method is used for enabling a set value of the air conditioning system to continuously approach an optimal combination; and (5) when the indoor PMV value dose not satisfy a thermal comfort range, the steps (3) and (4) are repeated. The method can precisely control the thermal comfort, can effectively reduce the air conditioner energy consumption under the precondition of guaranteeing the thermal comfort, can be suitable for thermal comfort control of different building types and different air conditioning systems at different times without needing sample data, and is wide in application range.

Description

technical field [0001] The invention relates to a thermal comfort control method of an air-conditioning system, in particular to an energy-saving and thermal comfort control method of an air-conditioning system. Background technique [0002] There are many factors that affect the energy consumption of the air conditioning system. Different buildings, different air conditioning systems, and different usage situations have different energy consumption. Under different outdoor weather conditions, the energy consumption is also different. When these factors change, the combination of indoor environment parameters corresponding to the minimum energy consumption of the air conditioning system is quite different. In actual operation, these influencing factors of the air-conditioning system are often changed, especially the outdoor meteorological parameters, which change more frequently. The system realizes real energy saving. [0003] Taking PMV and SET* (the Chinese meanings of ...

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Problems solved by technology

The sample data is generally obtained through actual measurement, but the workload of the actual test is very large. It is necessary to test the indoor and outdoor parameters under various outdoor climate conditions throughout the year, which will affect the accuracy of the model prediction results.

CN200610128692.3 discloses an energy-saving thermal comfort controller and control method. According to the difference between the PMV actual value and the PMV set value, the neural network control algorithm is used to output the control signal to the device that can change the indoor heat and humidity conditions. For the same A building and air-conditioning system needs to measure sample data under a period of time, but the outdoor meteorological conditions and the length of the measurement period during the measurement period limit the comprehensiveness of the sample data, which in turn affects the accuracy of the neural network model; at the same time, an existing building The thermal comfort control of the existing air-conditioning system in the building corresponds to a neural network model. If other air-conditioning forms are used or the air-conditioning form is applied to other buildings, the neural network model will also change accordingly, which limits the use of neural network control methods. Range of Thermal Comfort Control

[0007] (3) Most of the previous studies did not fully consider the six parameters related to human thermal comfort

CN02136099.5 discloses a thermal comfort fuzzy control air conditioner, which only considers four parameters such as air temperature, relative humidity, average radiation temperature, and wind speed, so it is difficult to precisely control the thermal comfort

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