Parameter Optimization Analysis of Cold Source System Based on Genetic Algorithm

With the rapid development of urban modernization and industrialization, the global energy shortage and the increasing degree of environmental damage, the problems represented by building energy consumption, especially the energy consumption of central air-conditioning system, have attracted widespread attention. As the main part of building energy consumption, the optimization of the central air-conditioning cooling system is of great significance for achieving energy conservation and emission reduction. However, there are still many deficiencies in the modeling technology and energy consumption optimization of the central air conditioning cold source system, including the low accuracy of the model and the inaccurate prediction of energy consumption. In order to solve these problems, this paper proposes an optimization scheme of chilled water system of central air conditioning based on genetic algorithm to improve the parameters of the cooling source system, so as to improve the accuracy of energy consumption prediction and the effectiveness of system optimization.