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Method for identifying regulation mode of central heating system

A centralized heating and mode technology, applied in the field of data mining model, identifying the secondary water supply temperature operation adjustment strategy in the heating system, can solve the problems of policy identification deviation, high degree of digitalization, and imperfect methods, etc. Achieve the effect that is not easy to cause deviation

Active Publication Date: 2018-01-09
TIANJIN UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Solve the problem of policy identification deviation caused by imperfect methods and incomplete parameters in the identification process. Compared with previous methods, it has strong operability, high reliability, rapid processing, and high degree of digitization

Method used

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  • Method for identifying regulation mode of central heating system
  • Method for identifying regulation mode of central heating system
  • Method for identifying regulation mode of central heating system

Examples

Experimental program
Comparison scheme
Effect test

example 1

[0026] 1. Using the heat supply data of the heat exchange station in the low area of ​​Shunhe Park, Hexi District, Tianjin City in the heating season of 2015-2016 to analyze, firstly, the temperature of the secondary water supply is tested by the autocorrelation function graph test method. It can be seen that the heat exchange station has adopted two The operating strategy of the secondary side quality regulation.

[0027] 2. Calculate the correlation between the primary and secondary water supply temperatures, and get the correlation value = 0.4, that is, the primary and secondary water supply temperatures are related.

[0028] 3. Since the temperature of the secondary water supply changes and is related to the temperature of the primary water supply, the situation in step 3 does not exist in this example.

[0029] 4. The situation in step 4 does not exist in this example.

[0030] 5. Further conduct partial correlation analysis, control the primary water supply temperature,...

example 2

[0039]1. Using the heat supply data of the heat exchange station in the low area of ​​Rongcheng Park, Hexi District, Tianjin City in the heating season of 2015-2016 to analyze, first of all, the temperature of the secondary water supply is tested by the autocorrelation function graph test method. The operating strategy of the secondary side quality regulation.

[0040] 2. Calculate the correlation between the primary and secondary water supply temperatures, and get the correlation value = 0.5, that is, the primary and secondary water supply temperatures are related.

[0041] 3. Since the temperature of the secondary water supply changes and is related to the temperature of the primary water supply, the situation in step 3 does not exist in this example.

[0042] 4. The situation in step 4 does not exist in this example.

[0043] 5. Further conduct partial correlation analysis, control the primary water supply temperature, calculate the correlation between the secondary water ...

example 3

[0052] 1. Using the heat supply data of the Kunlanyuan Heat Exchange Station in Hexi District, Tianjin City in the heating season of 2015-2016 to analyze, firstly, the secondary water supply temperature is tested by the autocorrelation function graph test method. The operating strategy of side mass regulation.

[0053] 2. Using data set 3, calculate the correlation between the primary and secondary water supply temperatures, and get a correlation value = 0.2, that is, the primary and secondary water supply temperatures are irrelevant.

[0054] 3. Since the secondary water supply temperature changes and has nothing to do with the primary water supply temperature, the situation in step 3 does not exist in this example.

[0055] 4. Calculate the correlation between the secondary water supply temperature and the primary flow, and get the correlation value = 0.9, that is, the secondary water supply temperature is related to the primary flow.

[0056] 5. The situation in step 5 doe...

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Abstract

The invention relates to a method for identifying a regulation mode of a central heating system. A set of data mining models capable of being applied to identification of an existing operation regulation strategy of the secondary water supply temperature of the central heating system is provided, and through conjoint analysis of a primary side parameter, a secondary side parameter, a meteorological parameter and the like, the conclusion that the related regulation strategies of the secondary water supply temperature comprise follow-up regulation, active regulation, secondary side influence andthe like is obtained. The problem of strategy identification deviation caused by an imperfect method and incomprehensive parameters in the identifying process is solved, compared with an original method, the operability is high, the reliability is high, processing is rapid, and the digitized degree is high. The conclusion is visual and reliable, and the deviation is not liable to generate.

Description

technical field [0001] The invention relates to a data mining model for identifying an operation adjustment mode of a centralized heating system, in particular to a data mining model for identifying an operation adjustment strategy of secondary water supply temperature in a heating system, and belongs to the fields of heating technology optimization and building energy conservation. Background technique [0002] In recent years, heating energy consumption in northern cities and towns has remained high. One of the main reasons is the low efficiency of the heating system caused by the unreasonable formulation of the operation regulation strategy of the heating system or the lax implementation. As the most important adjustment parameter of the central heating system, the secondary water supply temperature of the heat exchange station plays a pivotal role in ensuring the heating needs of heat users and refining on-demand heating. Therefore, mastering the existing operation adjus...

Claims

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Application Information

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IPC IPC(8): F24D19/10
Inventor 田喆季翔
Owner TIANJIN UNIV
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