Air conditioner cooling load real-time prediction algorithm applied to embedded type control system

Abstract

The invention provides an air conditioner cooling load real-time prediction algorithm applied to an embedded type control system and relates to the field of central air conditioner system control. The air conditioner cooling load real-time prediction algorithm comprises the following steps: 1, acquiring meteorological parameters for the outdoor environment prediction of a predicted day; 2, selecting the stable running representative day of an air conditioner system as a reference day, and calculating so as to obtain the hour-by-hour load distribution coefficient of the reference day; 3, calculating the maximum hourly cooling load on the predicted day; 4, calculating the load distribution condition on the predicted day; 5, carrying out online correction on predicted load on the current running day; and 6, comparing each actual hourly cooling load data with each predicted hourly cooling load data on the predicted day, and correcting the load distribution coefficient of the reference day according to deviation conditions. The algorithm carries out prediction according to the load distribution coefficient of the basic day and the outdoor prediction meteorological parameters so as to obtain the maximum hourly load on the predicted day, and carries out calculation so as to obtain load distribution on the whole predicted day. The algorithm has the characteristics of being small in data quantity demand, simple in calculation, accurate in prediction results and great in universality.

Description

technical field [0001] The invention relates to the field of central air-conditioning system control, in particular to an air-conditioning cooling load real-time prediction algorithm applied in an embedded central air-conditioning control system. Background technique [0002] Adopting a reasonable operation adjustment method is one of the main ways to improve the energy utilization efficiency of the central air-conditioning system. The implementation of cooling load forecasting is an effective basis for the optimal operation of the air-conditioning system, and it is also the key to the efficient and economical operation of the energy-storage air-conditioning system to play its advantages. The role of air-conditioning cooling load forecasting is to ensure that the air-conditioning parameters are stable and up to standard, to achieve reasonable deployment of different types of cold source equipment, to achieve efficient and safe operation, and at the same time, to adopt reasona...

AI Technical Summary

Problems solved by technology

The neural network analysis method has high prediction accuracy, but has the disadvantages of complex modeling and large data demand

In addition, the neural network analysis method cannot be automated in modeling. A considerable part of the work needs to rely on human analysis when selecting the network structure and training the network. There are a large number of trial calculation processes, which increases the difficulty of modeling.

In addition, if the load forecasting system established by the neural network analysis method is to be applied to another building, the network needs to be retrained. Therefore, it is not universal and the feasibility of engineering application is poor.

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