General water-cooling central air conditioner energy consumption prediction method based on long-short-term memory recurrent neural network

Abstract

The invention discloses a general water-cooling central air conditioner energy consumption prediction method based on a long-short-term memory recurrent neural network. The general water-cooling central air conditioner energy consumption prediction method comprises the following steps of 1, acquiring water-cooling central air conditioner data and corresponding environment data of normal operationof a plurality of water-cooling central air conditioner projects provided by a large-stroke energy company; step 2, performing data preprocessing on the obtained water-cooling central air conditionerdata in normal operation and the corresponding environment data, and integrating a plurality of data sets to obtain a comprehensive data set; step 3, training the data set to predict the energy consumption of the air conditioner, and adopting a LSTM-RNN long-term and short-term memory cycle neural network, and using the pre-processed data set and corresponding power consumption as input to LSTM-RNN long-term and short-term memory cycle neural network to be subjected to network training to obtain a final prediction model; and 4, inputting the test data into the prediction model to obtain the energy consumption value of the air conditioner under the current working condition. According to the method, the model training process is simplified, and the prediction accuracy is improved.

Description

technical field [0001] The invention relates to a method for predicting energy consumption of a general water-cooled central air conditioner based on a long-short-term memory cycle neural network. Background technique [0002] Building automation system (BAS) is a system that integrates technologies such as Internet of Things technology, control technology, and network technology. It provides owners and users with a safe, comfortable, convenient and efficient working and living environment by implementing comprehensive automatic monitoring and management of various equipment in the building (group), and makes the entire system and various equipment in it at the best working status. At the same time, in the BAS system, a large amount of air-conditioning data such as temperature, humidity, flow, power, etc. are recorded in the database. The analysis and modeling of the air-conditioning system through a large amount of data can better predict the energy consumption of the air...

AI Technical Summary

Problems solved by technology

[0003] In order to overcome the disadvantages of complex energy modeling and prediction steps and limited modeling area of ​​existing air conditioners, the present invention provides a general-purpose water-cooled center based on long-term short-term memory cyclic neural network with high accuracy and certain versatility. Air Conditioning Energy Consumption Prediction Method

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