BP neural network heating system energy consumption prediction method based on similar sample screening

A BP neural network and heating system technology, which is applied in the field of BP neural network heating system energy consumption prediction, can solve the problems of low energy consumption prediction accuracy

Inactive Publication Date: 2019-06-07
NORTH CHINA UNIV OF WATER RESOURCES & ELECTRIC POWER
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  • Abstract
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  • Application Information

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Problems solved by technology

[0005] The technical problem to be solved by the present invention is to provide a BP neural network heating system energy consumption prediction method based on similar sample screening. This method overcomes the pro

Method used

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  • BP neural network heating system energy consumption prediction method based on similar sample screening
  • BP neural network heating system energy consumption prediction method based on similar sample screening
  • BP neural network heating system energy consumption prediction method based on similar sample screening

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Effect test

Embodiment 1

[0088] Embodiment 1 A BP neural network heating system energy consumption prediction method based on similar sample screening

[0089] A residential building located in Tianjin is selected as the test object, and its heating system energy consumption and related meteorological parameters are tested. The test dates are from November 15, 2013 to March 14, 2014 (120-day heating cycle data), November 15 to December 5, 2014 (21-day heating initial data), and January 24, 2015 As of January 30 (7-day mid-term heating data), a total of 148 days of test data. Taking the energy consumption of the heating system from November 15, 2013 to March 14, 2014 as the historical data, the energy consumption of the heating system from November 15 to December 5, 2014 and from January 24 to January 30, 2015 was analyzed. predict. The following indicators are used to judge the prediction accuracy of the model, as shown in the following formula:

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[0091]

[0092]

[0093] Among th...

Embodiment 2

[0157] Embodiment 2 Comparison of different energy consumption prediction methods for building energy consumption prediction

[0158] In order to verify the accuracy and scientificity of the BP neural network heating system energy consumption prediction method based on similar sample screening provided by the present invention, this embodiment compares different BP neural network heating system energy consumption prediction methods, and the P group is The BP neural network heating system energy consumption prediction method based on similar sample screening provided by this embodiment 1; Q group is the traditional BP neural network heating system energy consumption prediction method; R group is the BP neural network heating system energy consumption based on genetic algorithm Prediction method; Q group and R group are the existing prediction methods to predict the energy consumption of the heating system of the building, and the specific prediction results are as follows:

[0...

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Abstract

The invention discloses a BP neural network heating system energy consumption prediction method based on similar sample screening. The method comprises the following steps successively: constructing an initial training sample set A, screening main influence factors, and constructing a training sample set; constructing an influence factor matrix B, calculating a comprehensive similarity coefficient, and screening similar sample subsets; and constructing a final training sample set; predicting energy consumption of heating system of building by utilizing BP neural network. According to the method, the problem that a traditional BP neural network heating system is low in energy consumption prediction precision is solved, the method is simple, the process is easy to calculate, the accuracy ishigh, and engineering personnel can master and learn the energy consumption easily; the method is suitable for predicting the energy consumption of the heating system of the building.

Description

technical field [0001] The invention belongs to the field of energy consumption prediction of heating systems, and in particular relates to a BP neural network energy consumption prediction method for heating systems based on similar sample screening. Background technique [0002] In recent years, the proportion of my country's building energy consumption in the total energy consumption of the society has continued to increase. Among them, the energy consumption of HVAC systems accounts for as high as 40-60% of the entire building energy consumption, making it a "big household" of building energy consumption. Improving the energy efficiency of the HVAC system and reducing the energy consumption of the HVAC system are of great significance to improving the current situation of building energy consumption. How to not only ensure the comfort requirements of indoor personnel, but also reduce building energy consumption has been a long-term focus of scientific research workers an...

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06G06N3/08
Inventor 袁天昊陈娟娟周国峰谢松甫杨伟张琳琳
Owner NORTH CHINA UNIV OF WATER RESOURCES & ELECTRIC POWER
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