Central air conditioner energy consumption control method based on improved particle swarm optimization

Abstract

The invention relates to a central air conditioner energy consumption control method based on improved particle swarm optimization. The method includes the following steps that COP curves of differentunits of a central air conditioner are acquired, and energy consumption functions of all the units are obtained through fitting; based on the energy consumption functions of all the units, in combination with an exterior penalty manner, a central air conditioner energy consumption optimization model is established; the central air conditioner energy consumption optimization model is solved through the improved particle swarm optimization, and optimal load distribution rates of all the units are obtained; and load switching of all the units is controlled according to the optimal load distribution rates of all the units, and central air conditioner energy consumption optimization control is completed. Compared with the prior art, by means of the improved particle swarm optimization, the early ergodicity of the particle swarm optimization is improved through a sinusoidal chaotic sequence, particle groups have the mechanism of getting away from local optimal points by adding sinusoidal chaotic disturbance, the inertia weights of particles are adaptively adjusted in the optimization process, the optimization speed can be effectively increased, the optimization precision can be effectively improved, thus, the method is suitable for complex operation working conditions of the central air conditioner, and it is guaranteed that the operation energy consumption of the air conditioner isminimized.

Description

technical field [0001] The invention relates to the technical field of central air conditioning energy saving, in particular to a central air conditioning energy consumption control method based on an improved particle swarm algorithm. Background technique [0002] Central air conditioning can meet people's needs for indoor air quality in the new era, but when using central air conditioning, it will also generate a lot of energy consumption, which does not meet the requirements of energy conservation and environmental protection. In order to cope with various extreme situations, the air-conditioning equipment is designed according to the full load state during manufacture and design. However, in the ordinary environment, the air conditioner operates at partial load 90% of the time, of which the load is only 50% of the time. half of the design load. Therefore, adjusting the settings of the air conditioner as needed can significantly reduce energy consumption. [0003] With ...

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Problems solved by technology

[0004] The PSO algorithm has the advantages of simple algorithm structure, less dependence on key parameters, strong robustness, and easy engineering implementation, so it is widely used in the field of industrial optimization production, and is also used in the optimal control of air conditioning systems, but the PSO algorithm is prone to population diversity Due to the low stability, the algorithm falls into the local optimal solution, and its optimization speed and accuracy cannot adapt to complex working conditions. Since most central air-conditioning systems contain multiple units, the load distribution of the units is not uniform, and the operating conditions are more complicated. PSO Algorithms cannot quickly and accurately optimize unit load distribution, and cannot guarantee effective energy saving

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