Method and device for forecasting air-conditioning load and air-conditioner
An air-conditioning load and prediction method technology, applied in the field of air-conditioning, can solve the problems of not considering the dynamic changes of air-conditioning load, the inability of air-conditioning system equipment to operate, and the inconsistency of cooling capacity and air-conditioning load changes, so as to avoid energy waste.
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Embodiment 1
[0032] figure 1 It shows the flow chart of the implementation of the air conditioning load forecasting method provided by Embodiment 1 of the present invention, and the details are as follows:
[0033] In S101, initialize the weights and thresholds corresponding to the air-conditioning load forecasting neural network model;
[0034] In this embodiment, the initialized weights and thresholds can be arbitrary values.
[0035] In S102, obtain the parameter quantity affecting the load of the air conditioning system;
[0036] In this embodiment, the parameter quantity may include parameters such as indoor temperature, outdoor temperature, indoor humidity, outdoor humidity, supply and return water temperature and flow rate of the air-conditioning chilled water system, and the parameters may be adjusted according to actual conditions.
[0037] In S103, input the parameter amount into the pre-trained air-conditioning load forecasting neural network model, wherein the air-conditionin...
Embodiment 2
[0063] Figure 4 It shows the structural diagram of the air-conditioning load forecasting system provided by the second embodiment of the present invention. For the convenience of description, only the parts related to the embodiment of the present invention are shown. The system can be a software unit, a hardware unit or a built-in air-conditioning unit. Soft and hard combination unit.
[0064] The system includes: a parameter quantity acquisition unit 41 , a parameter quantity input unit 42 and a predicted value acquisition unit 43 .
[0065] A parameter quantity acquisition unit 41, configured to acquire parameter quantities that affect the load of the air conditioning system;
[0066] The parameter quantity input unit 42 is used to input the parameter quantity into the pre-trained air-conditioning load forecasting neural network model, wherein the air-conditioning load forecasting neural network model includes: an input layer, an intermediate layer, a feedback layer and a...
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