Building indoor environment optimization method based on model order reduction technology

Abstract

The invention discloses a building indoor environment optimization method based on the model order reduction technology. The method mainly includes the three steps: (1) using CFD (computational fluid dynamics) software for steady-state simulation of the indoor environment, and constructing variation spaces of various environmental parameters; 2) reconstructing low-order parameter variation subspaces by the aid of the POD (proper orthogonal decomposition) technology; and 3) searching the optimal air conditioner air supply temperature and the optimal air conditioner air supply speed by operating the genetic algorithm. The variation subspaces of the indoor environmental parameters are constructed by the aid of the POD technology, so that influences of spatial distribution on the environmental parameters are considered fully in an optimizing strategy, and optimization accuracy is improved. The POD model order reduction method maps a control equation in an original space into one orthogonal subspace, and accordingly mapping error can be guaranteed to minimum in the energy sense. Besides, compared with a present environment optimization strategy, the building indoor environment optimization method based on the model order reduction technology has the advantages of high optimization precision, high speed and the like.

Description

Technical field [0001] The invention relates to a building indoor environment optimization method based on model reduction technology, and belongs to the field of building environment and building energy saving. Background technique [0002] With the continuous improvement of people's requirements for living quality and building energy efficiency, how to coordinate and optimize the indoor environment comfort and air conditioning energy consumption of buildings has attracted more and more attention. At present, many scholars have proposed a variety of system-level multi-objective optimization control strategies. Optimization algorithms have developed from the early optimization methods relying on gradients to various intelligent optimization algorithms (such as evolutionary programming, genetic algorithms, etc.) that are widely used. The optimization parameters cover all aspects of the indoor environment, including thermal comfort and air quality. And air conditioning energy cons...

AI Technical Summary

Problems solved by technology

This method takes into account the influence of the spatial distribution of environmental parameters, but the neural network model is essentially an empirical model and can only model specified environmental indicators

When the performance index changes, or the indoor user area of ​​concern changes, it must be remodeled, and the adaptability is poor

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