Intelligent building air conditioner cooler system operation optimization method based on PSO-ELM algorithm

Abstract

The invention relates to the technical field of air conditioner energy conservation, and discloses an intelligent building air conditioner cooler system operation optimization method based on a PSO-ELM algorithm, which comprises the following steps: S1, a data acquisition module adopts a data acquisition mode to acquire data for a sensor in an air conditioner system, the collected data are adjustable parameters and process variable values of the air conditioning system, the adjustable parameters serve as to-be-optimized parameters, and after data processing is conducted on the process variable values, energy efficiency data of the air conditioning cooling-water machine are obtained and serve as predicted output values; S2, the data set is divided into a training set and a test set; S3, an ELM prediction algorithm module predicts an intermediate value in a subsequent energy efficiency model, hyper-parameters which mainly need to be determined in the model include w, b and [beta], w and b are determined through the model in S3, and [beta] is determined through data set training. According to the method, the optimized parameter combination of the system can be quickly and efficiently obtained, so that the system efficiency is improved and the energy consumption is reduced on the premise of ensuring the refrigeration requirement.

Description

technical field [0001] The invention relates to the technical field of air-conditioning energy saving, in particular to an operation optimization method for an intelligent building air-conditioning refrigerator system based on a PSO-ELM algorithm. Background technique [0002] With the rapid development of society, buildings have become the basic places for people to live and work, and the energy consumed by buildings accounts for 36% of the total energy consumption of society, and the air conditioning system accounts for more than 50% of the energy consumed by buildings. Therefore, improving the performance of the air conditioning system and reducing energy consumption is an important part of the construction of smart cities today. The air-conditioning system is a large-scale system distributed in time and space. Improper control strategies in actual engineering will cause problems such as low system operation efficiency, energy waste, and high operating costs. Therefore, ...

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Problems solved by technology

[0009] The embodiment of the present application provides a PSO-ELM algorithm-based operation optimization method for an intelligent building air-conditioning chiller system, which solves the problem that the experience-based manual parameter adjustment method in the prior art is not efficient, and due to differences between systems, The optimization parameters are not comprehensive. Most of the methods are based on the technical problems of the system's own adjustment parameters as the optimization parameters, which realizes the fast and efficient acquisition of the optimal parameter combination of the system, and then improves the system efficiency and reduces the energy consumption under the premise of ensuring the cooling demand. The purpose of consumption is to provide an intelligent building air-conditioning chiller system operation optimization method based on PSO-ELM algorithm

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