Control method of power station house cold source system based on machine learning and particle swarm optimization

A particle swarm algorithm and machine learning technology, applied in machine learning, heating and ventilation control systems, heating and ventilation safety systems, etc., can solve problems such as large interference, load fluctuations, high efficiency and energy saving, and difficult to accurately control, to improve COP indicators, the effect of reducing total energy consumption
CN112503746AActive Publication Date: 2021-03-16SHANGHAI ANYO ENERGY SAVING TECH
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Patent Information

Authority / Receiving Office
CN ยท China
Patent Type
Applications(China)
Current Assignee / Owner
SHANGHAI ANYO ENERGY SAVING TECH
Publication Date
2021-03-16

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Abstract

The invention discloses a control method of a power station house cold source system based on machine learning and particle swarm optimization. The control method comprises the following steps that S1, modeling is carried out on the power station house cold source system according to an air conditioning refrigeration process mechanism, a refrigerator model, the actual refrigerating capacity of a refrigerator, the chilled water outlet temperature of the refrigerator, the wet bulb temperature and the cooling water supply and return temperature difference are input, and the cooling water inlet temperature of the single refrigerator is output; S2, modeling prediction is carried out on energy consumption of the power station house cold source system based on historical data; and S3, for predicted load demand data, the control parameters of the air conditioner cold source system are optimized in combination with the particle swarm optimization. According to the control method of the power station house cold source system based on machine learning and the particle swarm optimization, a mechanism model and a data driving model of the cold source system are combined, and the PSO intelligentcontrol algorithm is applied to optimize the air conditioner cold source system, so that the total energy consumption of the cold source system is reduced, and therefore the COP index is improved.
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Description

technical field

[0001] The invention relates to a control method of a cold source system, in particular to a control method of a cold source system of a power station room based on machine learning and particle swarm algorithm. Background technique

[0002] The cold source system of the power station room in the factory is one of the most important components of the central air-conditioning system, and it is the source of the air-conditioning system. It accounts for 20% to 30%, and reasonable control and optimized operation can achieve huge energy saving. The HVAC refrigeration process has the characteristics of nonlinearity, strong coupling, large interference, and load fluctuation, so it is difficult to precisely control its high efficiency and energy saving. The central air-conditioning cold source system equipment includes chillers, chilled water pumps, cooling water pumps, cooling towers and other equipment. The parameters between the equipment are coupled with each ot...

Claims

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