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Air conditioning self-learning optimal control system

An optimal control, self-learning technology, applied in air conditioning systems, heating and ventilation control systems, heating and ventilation safety systems, etc., to reduce economic costs, reduce peak-to-valley load differences, and improve flexibility and compatibility.

Active Publication Date: 2018-11-20
INST OF AUTOMATION CHINESE ACAD OF SCI
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In order to solve the above problems in the prior art, that is, to solve the technical problem of how to minimize the economic cost of using air conditioners for users, the present invention provides an air conditioner self-learning optimal control system

Method used

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Embodiment Construction

[0041] Preferred embodiments of the present invention are described below with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are only used to explain the technical principles of the present invention, and are not intended to limit the protection scope of the present invention.

[0042] The air conditioner self-learning optimal control system in the embodiment of the present invention will be described below with reference to the accompanying drawings.

[0043] See attached figure 1 , figure 1 The main structure of the air conditioner self-learning optimal control system is shown as an example. Such asfigure 1 As shown, the air-conditioning self-learning optimal control system in this embodiment is suitable for ice-storage air-conditioners. The cooling load demand of the air conditioner. The air conditioner self-learning optimal control system in this embodiment includes a cooling load demand acquisition device 1 ,...

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Abstract

The invention relates to the technical field of ice storage air conditioning, and particularly provides an air conditioning self-learning optimal control system. The air conditioning self-learning optimal control system aims to solve the technical problem of how to reduce the economic cost of using air conditioners by users. For the purpose, the air conditioning self-learning optimal control system is applicable to an ice storage air conditioner. The ice storage air conditioner includes an ice storage device, an air conditioner refrigerator and a cold quantity converter, wherein the ice storage device is connected with the cold quantity converter. The air conditioning self-learning optimal control system includes a cold load demand acquisition device for acquiring a cold load demand, an approximate optimal control strategy acquisition device for obtaining an approximate optimal control strategy, a local iterative judging device used for updating an optimal performance index value and the approximate optimal control strategy and a global iterative judging device for obtaining the optimal control strategy and calculating the user cost. Through the air conditioning self-learning optimal control system, the cold supply load can be balanced, the cold supply requirements of the users are met, and the economic cost for the users to use the air conditioners is saved.

Description

technical field [0001] The invention relates to the technical field of ice storage air conditioners, in particular to an air conditioner self-learning optimal control system. Background technique [0002] Ice storage air-conditioning technology is to control the air-conditioning system to make ice at night when the electricity consumption is low, and release the cooling capacity during the daytime peak electricity consumption, so as to realize the peak-shaving and valley-filling of the power grid, so as to develop low-peak electricity consumption, optimize resource allocation, The role of protecting the ecological environment. [0003] However, the current control strategies commonly used in ice storage air-conditioning technology lead to high air-conditioning costs due to insufficient ice storage, excessive ice storage, or improper operation of refrigerators. In addition, due to the limitations of the control strategy itself, users cannot achieve the highest economic benef...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): F24F11/62F24F11/46F24F5/00
CPCF24F5/0017F24F11/46F24F11/62Y02E60/14
Inventor 魏庆来廖泽华宋睿卓
Owner INST OF AUTOMATION CHINESE ACAD OF SCI
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