CN107559944A - Method for identifying regulation mode of central heating system - Google Patents

Method for identifying regulation mode of central heating system Download PDF

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CN107559944A
CN107559944A CN201710864326.2A CN201710864326A CN107559944A CN 107559944 A CN107559944 A CN 107559944A CN 201710864326 A CN201710864326 A CN 201710864326A CN 107559944 A CN107559944 A CN 107559944A
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temperature
correlation
flow
supply
secondary water
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CN107559944B (en
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田喆
季翔
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Tianjin University
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Abstract

The invention relates to a method for identifying a regulation mode of a central heating system, and provides a set of data mining models which can be applied to identification of existing operation regulation strategies of secondary water supply temperature of the central heating system. The method solves the problem of strategy identification deviation caused by incomplete method and incomplete parameters in the identification process, and has the advantages of strong operability, high reliability, rapid processing and high digitization degree compared with the prior method. The conclusion is intuitive and reliable, and deviation is not easy to cause.

Description

A kind of method for identifying central heating system shaping modes
Technical field
The present invention relates to a kind of data mining model for identifying central heating system runing adjustment pattern, more particularly to identification The data mining model of secondary water-supply temperature runing adjustment strategy in heating system, belong to heat supply process optimization and building energy conservation neck Domain.
Background technology
In recent years, for northern cities and towns heating energy consumption according to remaining high, its one of the main reasons is heating system runing adjustment plan Formulation slightly is unreasonable or the not strict caused heating system efficiency of execution is low.As the most important regulation of central heating system Parameter, the secondary water-supply temperature of heat exchange station ensure heat user heating demand and the heating according to need that becomes more meticulous in terms of have it is very important Effect.Therefore, the existing runing adjustment strategy for grasping secondary water-supply temperature is optimization heating system heat supply efficiency, to heat supply system System carries out the basis of fault diagnosis.But each heat exchange station administrative staff professional knowledge is generally less, operation is lack of standardization, performs not tight Lattice, empirically adjust and all cause the actual motion strategy of secondary water-supply temperature and be difficult to obtain.Traditional secondary water-supply temperature fortune The tactful method for digging of row is simple, and reference data is single, harsh to data demand, and factors above all causes conclusion confidence level It is low.
In order to obtain the existing runing adjustment strategy of central heating system secondary water-supply temperature, it is necessary to using more comprehensively data And more professional reliable method for digging.With the smooth development of heat metering improvement project, can obtain imply heat supply system The heating operation number of the bulk information such as the actual characteristic of equipment, system operation conditions, system maintenance maintenance and operation note in system According to these data are often multidimensional, comprising time attribute.In recent years, data mining research and development is very fast, and it is processing sea The complicated algorithm of amount data is attached in traditional data analysing method, so as to excavate useful knowledge from data, with number According to the gradual maturation of digging technology, more professional reliable data digging method can be obtained.Utilize Data Mining Tools, identification The data mining model of central heating system runing adjustment pattern, it will bring certain reform and wound to heat supply running industry Newly.
The content of the invention
It is an object of the invention to overcome the shortcomings of in conventional analysis method, it is proposed that a set of to can apply to central heating The data mining model of the existing runing adjustment strategy identification of secondary system supply water temperature, by primary side parameter, secondary side ginseng The Conjoint Analysis such as number and meteorologic parameter, obtain secondary water-supply temperature has including follow-up adjustment, active regulation, secondary side influence etc. Close the conclusion of regulation strategy.Solve in identification process because method imperfection, the not comprehensive caused strategy identification of parameter are inclined The problem of poor, workable compared to previous methods, with a high credibility, processing is rapid, and digitized degree is high.
Technical scheme is as follows:
A kind of method for identifying central heating system shaping modes;Comprise the following steps that:
1st, using the universal method in time series analysis field --- auto-correlation function probability chart method examines secondary water-supply Whether temperature changes, and judges whether time series is steady according to the feature of figure, as a result Simple visual;When system uses constant two During the strategy operation of secondary supply water temperature, its time series belongs to stationary time series, and now auto-correlation function value is with hysteresis number Increase, decline quickly and tend to 0;
2nd, correlation analysis is carried out on the basis of judging whether secondary water-supply temperature keeps constant, judges first and second confession Whether coolant-temperature gage is relevant;If 0.3<Correlation≤1, then relevant, otherwise the two is unrelated;
If the 3, secondary water-supply temperature is constant and unrelated with a supply water temperature, it is " secondary water-supply that can obtain adjusting strategy Temperature is constant from main regulation, keeping temperature " conclusion;
If the 4th, secondary water-supply temperature change and first and second supply water temperature is unrelated, to secondary water-supply temperature and a flow Carry out correlation analysis;" secondary water-supply temperature is relevant with a flow " (0.8≤correlation≤1) can be now obtained, " with two Secondary side relating to parameters " (0<Correlation<0.3), (0.3≤correlation " with a flow and secondary side relating to parameters "<0.8) three kinds Possible regulation strategy;
If the 5, first and second supply water temperature is relevant, no matter whether secondary water-supply temperature changes, partial correlation point is all further done Analysis, that is, a supply water temperature is controlled, judges the relation between secondary water-supply temperature and outdoor temperature;When 0.3≤partial correlation value≤1 When, then secondary water-supply temperature is relevant with outdoor temperature, otherwise unrelated;
It is related to a flow progress to secondary water-supply temperature if the 6, unrelated between secondary water-supply temperature and outdoor temperature Property analysis, can obtain " secondary water-supply temperature is relevant with a flow " (0.8≤correlation≤1);" have with secondary side parameter Close " (0<Correlation<0.3);" with a flow and secondary side relating to parameters " (0.3≤correlation<0.8) three kinds of possible regulations Strategy;Secondary side parameter includes secondary flow, secondary return water temperature etc.;Above 1-6 is as shown in Figure 1;
If the 7, secondary water-supply temperature is relevant with outdoor temperature, correlation analysis is done to secondary water-supply temperature and a flow; Available " secondary water-supply temperature is with the servo-actuated change of a supply water temperature " (0<Correlation<0.3);" it is servo-actuated with a supply water temperature Change, relevant with a flow " (0.8≤correlation≤1);" with the servo-actuated change of supply water temperature, with a flow and secondary Side relating to parameters " (0.3≤correlation<0.8) three kinds of possible regulation strategies;As shown in Figure 2;
If the 8, secondary water-supply temperature is relevant with a flow, correlation analysis is done to a flow and outdoor temperature, excavates two The relevance of person, if 0.3≤correlation≤1, the two is relevant, otherwise unrelated;
If the 9, a flow is relevant with outdoor temperature, to a flow, secondary water-supply temperature and outdoor temperature three do Partial Correlation Analysis;Outdoor temperature is controlled, calculates a flow and the correlation of secondary water-supply temperature;" secondary water-supply can be obtained Temperature is with the servo-actuated change of a flow " (0.3≤correlation≤1);" according to a flow from main regulation, and a flow and room Outer temperature is relevant " (0<Correlation<0.3) two kinds of possible regulation strategies;
If the 10, a flow is unrelated with outdoor temperature, it can obtain that " secondary water-supply temperature is according to a flow from homophony The regulation strategy of section ";
If the 11, obtaining secondary water-supply temperature with the servo-actuated change of a flow or the conclusion from main regulation, further sentence A disconnected flow and the correlation of time;It is available " according to flow of time adjustment, secondary water-supply temperature by calculating correlation Degree is with the servo-actuated change of flow or from main regulation " (0.3≤correlation≤1) and " secondary water-supply temperature with a flow with Dynamic to change or from main regulation, one time flow is unrelated with other factors " (0<Correlation<0.3) two kinds of possible regulation strategies.With Upper 8-11 is as shown in Figure 3.
The present invention compared with prior art, has advantages below:
1st, analyzed, overcome in the past using the deficiency of single method analysis using a variety of data digging methods.And pin To different situations, the method for selecting to be more suitable for is analyzed.Conclusion is intuitive and reliable, is not easy to cause deviation.
2nd, using the method for multivariable association analysis, the accurate conclusion about regulation strategy can be obtained, it is with a high credibility.Mesh The data that preceding heating system is monitored include thermal source, the supply and return water temperature of heat supply network and heat exchange station, pressure, system maintenance maintenance and behaviour Data, and the room temperature of user end, design temperature, valve state, accumulation heat, flow, supply and return water temperature, the room such as note down The parameters such as outer meteorology, and used monitoring system be typically by by when or by carrying out record data in units of half an hour.One Aspect, these data are a large amount of and comprehensive, make full use of these information, undoubtedly optimal so as to obtain the operation reserve of system Scheme.On the other hand, it is past in the data collected due to being influenceed by measurement means, sensor stability and measurement accuracy Toward there is missing, mistake, the data of exception, therefore only rely on single data and analyzed, conclusion easily produces deviation.Supplying In hot systems, secondary water-supply temperature suffers from the influence of other multiple variables, including primary side supply water temperature, a flow, Secondary flow, meteorologic parameter, time factor and secondary side other specification etc..By other specification from different perspectives to being identified Secondary water-supply temperature runing adjustment strategy is verified that the degree of accuracy is high.
Brief description of the drawings
Fig. 1:The data analysis flowcharts of the present invention, it can obtain the main conclusions about regulation strategy.
Fig. 2:Secondary water-supply temperature regulation strategy that may be present in the case of relevant with outdoor temperature.
Fig. 3:Two supply water temperatures regulation strategy that may be present in the case of relevant with secondary flow.
Embodiment
The example of the present invention is as follows, but is not limited to this, and all similar replacements and change are to those skilled in the art For be it will be apparent that they are considered as being included in spirit of the invention, scope and content.
Example 1:
1st, the genial Yuan Di areas heat exchange station heat supply data in dim season Tianjin Hexi District are adopted using 2015-2016 to be analyzed, Secondary water-supply temperature is examined using auto-correlation function probability chart method first and understood, the heat exchange station takes the regulation of secondary side matter Operation reserve.
2nd, the correlation of first and second supply water temperature is calculated, obtains correlation=0.4, i.e. first and second supply water temperature is relevant.
3rd, due to secondary water-supply temperature change and relevant with a supply water temperature, step 3 situation is not present in this example.
4th, step 4 situation is not present in this example.
5th, partial Correlation Analysis is further done, controls a supply water temperature, is calculated between secondary water-supply temperature and outdoor temperature Correlation, obtain correlation=0.5, i.e. secondary water-supply temperature is relevant with outdoor temperature.
6th, calculate the correlation of secondary water-supply temperature and a flow, obtain correlation=0.8, i.e., secondary water-supply temperature with Supply water temperature change, it is relevant with a flow.
7th, because secondary water-supply temperature is relevant with outdoor temperature, therefore step 6 situation is not present in this example.
8th, a flow and the correlation of outdoor temperature are calculated, obtains correlation=0.6, i.e. a flow and outdoor temperature It is relevant.
9th, outdoor temperature is controlled, the correlation of a flow and secondary water-supply temperature is calculated, obtains correlation=0.2, i.e., One time flow is relevant with secondary water-supply temperature.
10th, flow is relevant with outdoor temperature due to one time, therefore step 10 is not present.
11st, a flow and the correlation of time are calculated, obtains correlation=0.6, i.e. a flow is relevant with the time.
The operation reserve of secondary water-supply temperature, which may finally be obtained, is:On the basis of with the servo-actuated change of a supply water temperature According to a flow from main regulation, and a flow is relevant with outdoor temperature, time change.
Example 2:
1st, dim season Tianjin Hexi District Rongcheng Yuan Di areas heat exchange station heat supply data are adopted using 2015-2016 to be analyzed, Secondary water-supply temperature is examined using auto-correlation function probability chart method first and understood, the heat exchange station takes the regulation of secondary side matter Operation reserve.
2nd, the correlation of first and second supply water temperature is calculated, obtains correlation=0.5, i.e. first and second supply water temperature is relevant.
3rd, due to secondary water-supply temperature change and relevant with a supply water temperature, step 3 situation is not present in this example.
4th, step 4 situation is not present in this example.
5th, partial Correlation Analysis is further done, controls a supply water temperature, is calculated between secondary water-supply temperature and outdoor temperature Correlation, obtain correlation=0.2, i.e. secondary water-supply temperature is unrelated with outdoor temperature.
6th, calculate the correlation of secondary water-supply temperature and a flow, obtain correlation=0.2, i.e., secondary water-supply temperature with Secondary side relating to parameters.
7th, because secondary water-supply temperature is unrelated with outdoor temperature, therefore step 7 situation is not present in this example.
8th, because secondary water-supply temperature is unrelated with a flow, therefore step 8 situation is not present in this example.
9th, step 9 situation is not present in this example.
10th, step 10 situation is not present in this example.
11st, step 11 situation is not present in this example.
The operation reserve of secondary water-supply temperature, which may finally be obtained, is:On the basis with the servo-actuated change of a supply water temperature On, secondary side supply water temperature changes with the change of secondary side parameter.
Example 3:
1st, adopt dim season Tianjin Hexi District Qumran garden heat exchange station heat supply data using 2015-2016 to be analyzed, first Secondary water-supply temperature is examined using auto-correlation function probability chart method and understood, the heat exchange station takes the operation of secondary side matter regulation Strategy.
2nd, using data set 3, the correlation of first and second supply water temperature is calculated, obtains correlation=0.2, i.e., first and second supplies Coolant-temperature gage is unrelated.
3rd, it is due to secondary water-supply temperature change and unrelated with a supply water temperature, therefore step 3 situation is not deposited in this example .
4th, calculate the correlation of secondary water-supply temperature and a flow, obtain correlation=0.9, i.e., secondary water-supply temperature with One time flow is relevant.
5th, step 5 situation is not present in this example.
6th, step 6 situation is not present in this example.
7th, step 7 situation is not present in this example.
8th, a flow and the correlation of outdoor temperature are calculated, obtains correlation=0.2, i.e. a flow and outdoor temperature It is unrelated.
9th, flow is unrelated with outdoor temperature due to one time, therefore step 9 situation is not present in this example.
10th, flow is relevant with outdoor temperature due to one time, therefore can obtain:Secondary water-supply temperature according to flow from Main regulation.
11st, a flow and the correlation of time are calculated, obtains correlation=0.5, i.e. a flow is relevant with the time.
The operation reserve of secondary water-supply temperature, which may finally be obtained, is:According to flow of time adjustment, secondary water-supply temperature A flow is spent from main regulation.
A kind of method for identification central heating system shaping modes that the present invention is disclosed and proposed, those skilled in the art can By using for reference present disclosure, the appropriate links such as condition route that change are realized, although the method and technology of preparing of the present invention have passed through Preferred embodiment is described, person skilled substantially can not depart from present invention, in spirit and scope to this Methods and techniques route described in text is modified or reconfigured, to realize final technology of preparing.In particular It is that all similar replacements and change are apparent to those skilled in the art, and they are considered as being included in In spiritual, scope and content of the invention.

Claims (1)

  1. A kind of 1. method for identifying central heating system shaping modes, it is characterized in that step is as follows:
    1) universal method in time series analysis field is used --- auto-correlation function probability chart method examines secondary water-supply temperature Whether change, judge whether time series is steady according to the feature of figure;When system uses the strategy of constant secondary water-supply temperature During operation, its time series belongs to stationary time series, and now auto-correlation function value declines simultaneously quickly with the increase of hysteresis number Tend to 0;
    2) correlation analysis is carried out on the basis of judging whether secondary water-supply temperature keeps constant, judges first and second water supply temperature Whether degree is relevant;If 0.3<Correlation≤1, then relevant, otherwise the two is unrelated;
    If 3) secondary water-supply temperature is constant and unrelated with a supply water temperature, it is " secondary water-supply temperature that can obtain adjusting strategy It is constant from main regulation, keeping temperature " conclusion;
    If 4) secondary water-supply temperature change and first and second supply water temperature is unrelated, secondary water-supply temperature and a flow are carried out Correlation analysis, now obtain " secondary water-supply temperature is relevant with a flow ", 0.8≤correlation≤1);" with secondary side parameter It is relevant ", 0<Correlation<0.3;" with a flow and secondary side relating to parameters ", 0.3≤correlation<0.8;
    If 5) first and second supply water temperature is relevant, no matter whether secondary water-supply temperature changes, partial Correlation Analysis is all further done, A supply water temperature is controlled, judges the relation between secondary water-supply temperature and outdoor temperature;When 0.3≤partial correlation value≤1, then Secondary water-supply temperature is relevant with outdoor temperature, otherwise unrelated;
    If 6) unrelated between secondary water-supply temperature and outdoor temperature, correlation point is carried out to secondary water-supply temperature and a flow Analysis, obtains " secondary water-supply temperature is relevant with a flow ", 0.8≤correlation≤1;" with secondary side relating to parameters ", 0<It is related Value<0.3;" with a flow and secondary side relating to parameters ", 0.3≤correlation<0.8;
    If 7) secondary water-supply temperature is relevant with outdoor temperature, correlation analysis is done to secondary water-supply temperature and a flow;Obtain " secondary water-supply temperature is with the servo-actuated change of a supply water temperature ", 0<Correlation<0.3;" change with a supply water temperature is servo-actuated, with One time flow is relevant ", 0.8≤correlation≤1;" with the servo-actuated change of a supply water temperature, have with a flow and secondary side parameter Close ", 0.3≤correlation<0.8;
    If 8) secondary water-supply temperature is relevant with a flow, correlation analysis is done with outdoor temperature to a flow, excavates the two Relevance, if 0.3≤correlation≤1, the two is relevant, otherwise unrelated;
    If 9) flow is relevant with outdoor temperature, to a flow, secondary water-supply temperature and outdoor temperature three do inclined phase Close analysis;Outdoor temperature is controlled, calculates the correlation of a flow and secondary water-supply temperature, obtains that " secondary water-supply temperature is with one The servo-actuated change of secondary flow ", 0.3≤correlation≤1;" according to a flow from main regulation, and a flow has with outdoor temperature Close " 0<Correlation<0.3;
    If 10) flow is unrelated with outdoor temperature, can obtain " secondary water-supply temperature according to a flow from main regulation " Regulation strategy;
    If 11) obtain secondary water-supply temperature with the servo-actuated change of a flow or the conclusion from main regulation, one is determined whether Secondary flow and the correlation of time;Obtain that " according to flow of time adjustment, secondary water-supply temperature is with one by calculating correlation The servo-actuated change of secondary flow or from main regulation, 0.3≤correlation≤1;" secondary water-supply temperature with the servo-actuated change of flow or From main regulation, one time flow is unrelated with other factors ", 0<Correlation<0.3.
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Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111023224A (en) * 2019-12-05 2020-04-17 珠海横琴能源发展有限公司 Control method and system for hydraulic imbalance of cold/heat supply pipe network

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102069094A (en) * 2010-11-16 2011-05-25 北京首钢自动化信息技术有限公司 Data mining-based plate shape control key process parameter optimization system
CN102607103A (en) * 2012-04-05 2012-07-25 尹延京 Intelligent regional heat energy management system
CN103760968A (en) * 2013-11-29 2014-04-30 理光软件研究所(北京)有限公司 Method and device for selecting display contents of digital signage
CN105701123A (en) * 2014-11-27 2016-06-22 阿里巴巴集团控股有限公司 Passenger-vehicle relationship identification method and apparatus

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102069094A (en) * 2010-11-16 2011-05-25 北京首钢自动化信息技术有限公司 Data mining-based plate shape control key process parameter optimization system
CN102607103A (en) * 2012-04-05 2012-07-25 尹延京 Intelligent regional heat energy management system
CN103760968A (en) * 2013-11-29 2014-04-30 理光软件研究所(北京)有限公司 Method and device for selecting display contents of digital signage
CN105701123A (en) * 2014-11-27 2016-06-22 阿里巴巴集团控股有限公司 Passenger-vehicle relationship identification method and apparatus

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
高晓宇: "基于数据挖掘的换热站运行规律研究", 《中国优秀硕士学位论文全文数据库》 *

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111023224A (en) * 2019-12-05 2020-04-17 珠海横琴能源发展有限公司 Control method and system for hydraulic imbalance of cold/heat supply pipe network

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