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Machine learning assistance-based centralized water chilling unit air conditioning system operation control optimization method

A chiller and air-conditioning system technology, applied in the direction of mechanical equipment, can solve the problems that affect the stable operation of the air-conditioning system and cannot give the optimal solution, so as to achieve the effect of ensuring the accuracy of the optimization model, strong practicability, and improving the energy efficiency of operation

Active Publication Date: 2022-01-21
BEIJING JINMAO GREEN BUILDING TECH CO LTD
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Problems solved by technology

The traditional mathematical programming method has many disadvantages, and it may not be able to give the optimal solution under certain conditions, which will affect the stable operation of the air conditioning system

Method used

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  • Machine learning assistance-based centralized water chilling unit air conditioning system operation control optimization method
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  • Machine learning assistance-based centralized water chilling unit air conditioning system operation control optimization method

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Embodiment Construction

[0035] The present invention will be described in detail below in conjunction with specific embodiments. The following examples will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that those skilled in the art can make several changes and improvements without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0036] The present invention is a machine-learning-assisted centralized chiller air-conditioning system operation control optimization method. By establishing an integrated mathematical model of the air-conditioning system equipment, and establishing a performance prediction model of the chiller through a machine learning algorithm, the particle swarm optimization algorithm is used for optimization. This method can provide an optimized air conditioning system operation strategy and improve the economy of...

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Abstract

The invention provides a machine learning assistance-based centralized water chilling unit air conditioning system operation control optimization method. According to the method, a water chilling unit air conditioning system model based on energy conservation and personalized equipment operation parameter constraint is established, and a deep learning neural network is used for predicting an optimization algorithm combining machine operation parameters and a particle swarm optimization algorithm. By using the model and the algorithm provided by the invention, an efficient and energy-saving operation strategy of a water chilling unit can be obtained, and a guidance basis is provided for optimization of building operation.

Description

technical field [0001] The present invention relates to the technical field of intelligent operation of building energy, in particular, to a method for optimizing the operation control of centralized chiller air-conditioning systems based on machine learning, especially using the deep learning method and particle swarm optimization algorithm in machine learning. A method for optimizing the operation of an air-conditioning system of a water-cooled unit. Background technique [0002] Air-conditioning operation energy consumption accounts for a considerable share of building operation energy consumption. The stable and efficient operation of the air-conditioning system has positive significance for building energy-saving management and improving building energy utilization. In actual engineering, the operating characteristics of the air conditioning system often deviate from the performance test results before leaving the factory with the passage of time, changes in the system...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): F24F11/64F24F11/61F24F11/85F24F11/58
CPCF24F11/64F24F11/61F24F11/85F24F11/58Y02B30/70
Inventor 李威葳封智博
Owner BEIJING JINMAO GREEN BUILDING TECH CO LTD
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