CN109933850A - A kind of residential architecture thermic load model step calibration method - Google Patents
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Abstract
The invention discloses a kind of residential architecture thermic load model step calibration method, include the following steps: to collect data information relevant to residential architecture thermic load within the period of setting；It uses energy simulation software to carry out the foundation of heating load model according to the obtained data information is collected, and the parameter to be calibrated in heating load model is divided into building thermal technique parameter and people's behavior relevant parameter；It obtains influencing maximum building thermal technique parameter to heating load using Morris Sensitivity Analysis and it is calibrated；Step 4: carrying out clustering to outdoor temperature obtains different classifications, then people's behavior relevant parameter in each classification is calibrated；Step 5: determine that calibration result meets the requirement of calibration accuracy, otherwise repeatedly requirement of step 2~step 4 process up to meeting calibration accuracy.The present invention can go out inhabitation building thermal technique parameter and people's behavior relevant parameter with accurate alignment, true to reflect heating load situation.
Description
Technical field
The present invention relates to energy simulation field more particularly to a kind of residential architecture thermic load model step calibration sides
Method.
Technical background
With being continuously increased for energy consumption, 29,100,000,000 tons of CO have been discharged since 20062Since, China has become
Maximum CO in the world2Discharge state.Other than industry and transport service, construction industry has become the third-largest energy consumption row of China
Industry.The building trade scale of construction of China is huge, and compared to western developed country, there is certain for Chinese energy-saving building technology
Backwardness, within the following quite a long time, building energy conservation is trend of the times in China.
As people are higher and higher to architectural environment quality requirement and the hair at full speed of China's green low-carbon building trade
Exhibition, the effect of simulation of energy consumption is more and more prominent, energy simulation have become the design of architectural environment and control system with it is excellent
Change, building energy-saving renovation, green building assessment important component, be one essential tool of building energy saving field,
It can the progress of accessory building energy conservation and the work of building energy consumption related fields well.
Although simulation of energy consumption software development is quite mature so far, there is also a problems very serious:
The simulation of energy consumption value of energy simulation software has differences with practical building energy consumption measured value, and even big arrive can not for this species diversity
The stage ignored.The change of deterioration, the constructing operation operation of the deviation, building thermal technique performance of construction and design and personnel activity
The influences of the factors such as randomness can all cause the phenomenon of this analog result inaccuracy to occur.In order to enable building energy consumption model
Enough fittings are practical, need to carry out model calibration to it, set the parameters to change output quantity by adjusting model, make itself and reality
Measurement result is close.
Summary of the invention
It is an object of the invention to overcome the problems, such as current energy simulation inaccuracy, it is negative to be particularly directed to Building Heat
Lotus, inhabitation building thermal technique parameter and people's behavior relevant parameter can be gone out with accurate alignment by providing one kind, really reflect heating load
The method of situation residential architecture thermic load model step calibration.
A kind of residential architecture thermic load model step calibration method, comprising the following steps:
Step 1: collecting data information relevant to residential architecture thermic load, the data within the period of setting
Information includes architectural exterior-protecting construction information, being layouted by representative temperature characterizes the temperature letter of obtained architecture indoor
The heat consumption information of breath, outdoor weather information and building；
Step 2: carrying out heating load using energy simulation software according to the obtained data information is collected
The foundation of model, and classify to the parameter to be calibrated in heating load model, the parameter to be calibrated includes building
Thermal parameter and people's behavior relevant parameter, people's behavior relevant parameter include disturbing generation amount parameter and ventilation is changed in building
Gas number；
Step 3: obtaining influencing maximum building thermal technique to heating load first with Morris Sensitivity Analysis
Parameter, removing influences small building thermal technique parameter to heating load to reduce building thermal technique number of parameters to be calibrated；Then
Using the PSO algorithm of mixing GPS, with energy simulation value and the practical building minimum target of heat dissipation magnitude error to Building Heat
The maximum building thermal technique parameter of loading effects is calibrated；
Step 4: carrying out clustering to outdoor temperature obtains different classifications, then to people's behavior in each classification
Relevant parameter is calibrated, calibration method are as follows:
The first step is set separately in building and disturbs generation amount parameter and ventilation rate initial value and change with time coefficient
Calibration range, calibration range are empirically determined according to practical investigation situation combination professional knowledge；
Second step builds heat dissipation magnitude error most with energy simulation value and reality using the PSO algorithm of mixing GPS
It is small that the change with time coefficient that generation amount parameter and ventilation rate are disturbed in building is calibrated for target；
Third step, initial value is multiplied with change with time coefficient calibration value disturbs generation amount parameter and ventilation Ji Wei in building
The change with time calibration value of number；
Step 5: by the heating load analogue value and step of building thermal technique parameter and people's behavior relevant parameter after calibration
The practical heat consumption of building in one is compared, if meeting the requirement of calibration accuracy, terminates to calibrate；If not satisfied, then repeating
Step 2~step 4 process, adjust building thermal technique parameter and human behavior relevant parameter calibration before initial value setting and
The calibration range of building thermal technique parameter and human behavior relevant parameter is expanded or shunk, then step 5 is carried out and is wanted until meeting
It asks.
The present invention has the advantage that and good effect:
1, by being calibrated to residential architecture thermic load model, it is possible to reduce since parameter setting is inaccurate in modeling process
The really larger situation of caused simulation of energy consumption resultant error improves simulation precision.
2, the quantity of parameter to be calibrated can be reduced under the premise of guaranteeing calibration accuracy by Morris sensitivity analysis,
Improve calibration efficiency.
3, more personal behavior relevant parameter timetables are calibrated according to outdoor temperature cluster result, is guaranteeing calibration essence
Under the premise of degree, it can fully consider effect of people's behavior in heating load simulation, improve simulation precision and improve calibration
Efficiency.
Detailed description of the invention
Fig. 1 is a kind of residential architecture thermic load model step calibration method flow chart of the embodiment of the present invention；
Fig. 2 is the Morris susceptibility assays choice of parameters result figure in the embodiment of the present invention；
Fig. 3 is that the thermal parameter to be calibrated in the embodiment of the present invention influences result figure to thermic load；
Fig. 4 is the outdoor temperature cluster result figure in the embodiment of the present invention；
Fig. 5 be the embodiment of the present invention in building in disturb change with time calibration value figure；
Fig. 6 is the ventilation rate change with time calibration value figure in the embodiment of the present invention.
Specific embodiment
In the following with reference to the drawings and specific embodiments to the tool of residential architecture thermic load model step calibration method in the present invention
Body step is described in detail.
A kind of residential architecture thermic load model step calibration method of the invention, detailed process are shown in Fig. 1, including following step
It is rapid:
Step 1: collecting data information relevant to residential architecture thermic load, the data within the period of setting
Information includes architectural exterior-protecting construction information, being layouted by representative temperature characterizes the temperature letter of obtained architecture indoor
The heat consumption information of breath, outdoor weather information and building.
The architectural exterior-protecting construction information establishes required building specifying information in model, including Building class to be subsequent
Type, construction area, building orientation, building geometric dimension (length, width and height), building storey layer is high, builds window-wall ratio, building thermal technique ginseng
Number (predominantly architectural exterior-protecting construction parameter) etc..These information can generally be obtained by design drawing；In addition, some old
Building can not find design drawing, and finding reckoning on the spot can be combined according to the building information such as age and building type
The general information of building.In addition to above-mentioned Architecural Physics information, it is also necessary to investigate actual indoor temperature information, indoor temperature
It is directly related to the thermic load of building to spend information, therefore an accurate room temperature monitoring data help to improve final school
Quasi- precision.
The outdoor weather information be it is subsequent establish required weather information in model, including outdoor by when dry bulb temperature
Degree and by when solar radiation etc., these information can from local weather station or pass through researcher oneself be arranged it is small
Type weather station obtain its by when data, therefore, the meteorological data influence factor determining as one does not need to carry out it
Calibration.
The heat consumption information of the building be subsequent calibration procedure in building by when practical heat consumption information.Heat consumption
Comparative run of the data as model calibration, need to carry out it by when monitoring.For central heating system, by building
Consumer heat inlet monitor its by when supply and return water temperature and flow can calculate building by when heat consumption situation.
By taking a residential architecture of Xi'an City, Shanxi Province as an example.This is built in 2015, there is 32 layers, and the high 2.9m of layer is built
Building area is 12990m2, actual building thermal performance design parameter information is obtained from architectural design drawing, is shown in Table 1.
In winter, this building takes the mode of central heating to carry out continuous heating, and measured data includes supply water temperature, return water
Temperature, circular flow and room temperature data are divided into 1 hour between monitoring time, time span be on December 14th, 2017~
Totally 76 days on 2 28th, 2018.Since this interior heating system is in 18 layers of height subregion, the position of point layout are as follows:
(1) confession, return water temperature and the circular flow monitoring for building the high area in heating power inlet and low area, can calculate the heat dissipation of building
Amount；(2) 4 representative temperature are chosen to layout to characterize the temperature conditions of architecture indoor, chooses 1 layer, 17 layers, 19 respectively
Layer and 32 layers a family other carry out room temperature monitoring, in modeling process, carried out using other true room temperature of this 4 family
Simulation.
In addition, being obtained from official, China Meteorological Administration local practical in time period to keep analog result more accurate
Meteorological data, including outdoor temperature and solar radiation data.
Table 1 builds main Thermal Design parameter list
Step 2: carrying out heating load using energy simulation software according to the obtained data information is collected
The foundation of model, and classify to the parameter to be calibrated in heating load model, the parameter to be calibrated includes building
Thermal parameter and people's behavior relevant parameter, people's behavior relevant parameter include disturbing generation amount parameter and ventilation is changed in building
Gas number.
The data of above-mentioned collection can do a preliminary description to heating load model, in energy simulation software
In establish model, specify adjustable parameter in model.
Using TRNSYS simulation of energy consumption software as platform, heating load model is established simultaneously according to the data information of above-mentioned collection
Calibration parameter is treated to classify, it, can be by the calibration of heating load model according to the difference for influencing thermic load action mode
Parameter is divided into two classes: (1) building thermal technique parameter: the physical-property parameter of architectural exterior-protecting construction, packet are inputted in TRNSYS software
Wall heat transfer coefficient, wall specific heat capacity, wall density, wall-body energy saving solar absorptance, exterior surface of wall solar energy is included to inhale
Yield, roof heat transfer coefficient, roof specific heat capacity, roof density, interior surface of roof solar absorptance, roof outer surface solar energy
Absorptivity, the infrared emittance of window-glass, the heat transfer coefficient of window, furniture thermal capacitance and building air-tightness；(2) people's behavior is related
Parameter: generation amount parameter and ventilation parameter are disturbed in building.It includes that equipment heat disturbs parameter, Ren Yuanre that parameter is disturbed in building mainly
It disturbs parameter and light heat disturbs this three parts of parameter, actually this three is to influence Building Heat by distributing heat outward to bear
Lotus, the mechanism of action is substantially similar, and the period that difference is that these three occur is different, but this three produces thermic load
Raw influence can be overlapped mutually, therefore when calibrating to this three, can be comprehensive at disturbing calorific value in one by three
It is calibrated.It mainly include two kinds of forms in winter during central heating for ventilation parameter: first is that being enclosed by building
The Air Infiltration of protection structure, second is that the ventilation generated by opening of doors and windows.Air Infiltration building thermal technique argument section with
The name of building air-tightness parameter is calibrated, and ventilation refers to as caused by windowing behavior in people's behavior relevant parameter
Ventilation.Therefore, people's behavior relevant parameter needs to calibrate two class parameters: generation amount parameter and ventilation time are disturbed in building
Number.
Step 3: obtaining influencing maximum building thermal technique to heating load first with Morris Sensitivity Analysis
Parameter, removing influences small building thermal technique parameter to heating load to reduce building thermal technique number of parameters to be calibrated, thus
Only more important parameter is influenced on thermic load to calibrate.Then using the PSO algorithm of mixing GPS, with energy simulation
Value influences maximum building thermal technique parameter to heating load with the practical building minimum target of heat dissipation magnitude error and calibrates.
Heating load model is an extremely complex and highly nonlinear model, and input parameter is numerous, if right
Its all thermal parameter is calibrated, it will is taken a substantial amount of time and is produced little effect.By sensitivity analysis, can ignore
It is some that small parameter is influenced on heating load analog result, to improve the efficiency of model calibration.What the present invention used
Morris method is a kind of global sensitivity analysis method of classics, is widely used in the identification and screening of most sensitive parameter
In, Morris Sensitivity Analysis will be used to analyze building thermal technique parameter, ignoring influences very little to heating load
Parameter, more important thermal parameter is influenced on thermic load emphatically and is calibrated.
When calibrating building thermal technique parameter, need to exclude influence of the human behavior to calibration result, during night 0~5 point,
Personnel many places are disturbed in the building as caused by human behavior and tend to be steady with ventilation fluctuating change in sleep state in residential architecture
It is fixed, it is therefore preferable that selecting the building thermal technique supplemental characteristic in 0~5 period, obtained using Morris Sensitivity Analysis
Maximum building thermal technique parameter is influenced on heating load, can preferably realize the calibration of building thermal technique parameter.
It is exemplified below:
Sensitivity analysis is carried out to 14 thermal parameters first, is specifically shown in Table 2.
2 sensitivity analysis parameter of table and its range table
* furniture thermal capacitance refers to the total thermal capacitance for building interior all furniture with heat storage performance, equipment etc.；Air-tightness is built with cold
Wind permeates number to indicate.
Sensitivity analysis range refers to the range of value when sensibility calculates, generally according to the practical investigation situation of building and specially
Industry knowledge determines range, and value is to determine range with design value ± 50% in this example.
Fig. 2 illustrates the parameter in table 2 and carries out the result after Morris sensitivity analysis.The amendment shown in the abscissa is equal
From the point of view of value μ *, this 6 parameters of x14, x1, x12, x2, x3 and x13 are most sensitive parameters, and other parameters are to heating load
Influence it is smaller；From the point of view of the standard deviation sigma shown in the ordinate, the phase of x14, x12, x1, x2 and x3 this 5 parameters and other parameters
Mutual coupling effect is maximum.In conjunction with the quantitative analysis of these parameters in Fig. 3, it can be found that x14, x1, x12, x2, x3 and x13 this 6
Parameter affects 96% heating load output, and other 8 parameters then only influence 4% heating load output.Therefore, lead to
Cross sensitivity analysis, it is determined that building thermal technique calibration parameter is building air-tightness, wall heat transfer coefficient, window's heat transfer coefficient, wall
This 6 parameters of body specific heat capacity, wall density and furniture thermal capacitance.
GenOpt is a optimization software, can carry out coupling optimization calculating with TRNSYS simulation of energy consumption software, will lead to
The energy simulation value that simulation of energy consumption software obtains is crossed to join above-mentioned 6 with the practical building minimum target of heat dissipation magnitude error
Number is calibrated, and the optimization algorithm of selection is a kind of PSO algorithm (Hybrid Generalized Pattern for mixing GPS
Search Algorithm with Particle Swarm Optimization Algorithm)。
The calibration result of this 6 parameters is as shown in table 3.
3 building thermal technique parametric calibration table of table
Step 4: carrying out clustering to outdoor temperature obtains different classifications, then to people's behavior in each classification
Relevant parameter is calibrated, calibration method are as follows:
The first step is set separately in building and disturbs generation amount parameter and ventilation rate initial value and change with time coefficient
Calibration range, calibration range are empirically determined according to practical investigation situation combination professional knowledge；
Second step builds heat dissipation magnitude error most with energy simulation value and reality using the PSO algorithm of mixing GPS
It is small that the change with time coefficient that generation amount parameter and ventilation rate are disturbed in building is calibrated for target；
Third step, initial value is multiplied with change with time coefficient calibration value disturbs generation amount parameter and ventilation Ji Wei in building
The change with time calibration value of number.
It is exemplified below:
After completing building thermal technique parametric calibration, need to calibrate people's behavior relevant parameter.Fig. 4 is illustrated to outdoor
Temperature carries out the distribution situation after k-means cluster, cluster result show December 14~2018 year in 2017 28 days 2 months this 76
It outdoor temperature is divided into 3 classifications, then calibrates respectively to people's behavior relevant parameter in each classification.
The first step, in conjunction with actual investigation situation and professional knowledge, and with reference to " civil buildings heating ventilator and air tune
Save design specification " codes and standards such as (GB50736-2016) and " standard for lighting design of buildings " (GB50034-2013), to building
It inside disturbs and is configured with the initial value of ventilation rate and change with time coefficient calibration range, as shown in table 4 and table 5.
Second step carries out coupling optimization using GenOpt and TRNSYS and calculates, using the PSO algorithm of mixing GPS, with simulation
Value and the minimum target of actual value error carry out the change with time coefficient that generation amount parameter and ventilation rate are disturbed in building
Calibration, calibration result are shown in Table 4 and table 5.
Initial value is multiplied with change with time coefficient calibration value in third step, table 4 and table 5 disturbs generation amount parameter Ji Wei in building
With the change with time calibration value of ventilation rate, specific visible Fig. 5 and Fig. 6.
Table 4 disturbs generation amount parameter calibration in building
The calibration of 5 building ventilation rate of ventilation of table
Initial value is multiplied with change with time coefficient calibration value in table 4 and table 5 disturbs generation amount parameter and ventilation Ji Wei in building
The change with time calibration value of rate of ventilation, specific visible Fig. 5 and Fig. 6.
Step 5: by the heating load analogue value and step of building thermal technique parameter and people's behavior relevant parameter after calibration
The practical heat consumption of building in one is compared, if meeting ASHRAE Guideline 14, IPMVP, FEMP these standards to school
The requirement of quasi- precision then terminates to calibrate；If not satisfied, then repeating step 2~step 4 process, part ginseng therein is adjusted
Setting is counted, main method includes that the initial value before adjusting building thermal technique parameter and the calibration of human behavior relevant parameter is arranged and fits
When the calibration range for expanding or shrinking building thermal technique parameter and human behavior relevant parameter, then carry out step 5 until meet
It is required that.
After above-mentioned building thermal technique parameter and the calibration of people's behavior relevant parameter, the simulation of energy consumption error result of this building
As shown in table 6.
The calibration of table 6 front and back error result table
The requirement of ASHRAE Guideline 14, IPMVP, FEMP these standards to calibration accuracy is as shown in table 7.
Each standard of table 7 requires table to calibration accuracy
Its calibration accuracy meets the requirement of above-mentioned 3 standards after being calibrated using this method to heating load model,
Complete calibration tasks.
It is to be understood that the content of present invention and specific embodiment are intended to prove the reality of technical solution provided by the present invention
Border application, should not be construed as limiting the scope of the present invention.Those skilled in the art open in spirit and principles of the present invention
Give, can various modifications may be made, equivalent replacement or improve.But these changes or modification are being applied within pending protection scope.
Claims (1)
1. a kind of residential architecture thermic load model step calibration method, it is characterised in that the following steps are included:
Step 1: collecting data information relevant to residential architecture thermic load, the data information within the period of setting
The temperature information for the architecture indoor that characterization obtains of layouting including architectural exterior-protecting construction information, by representative temperature, room
The heat consumption information of outer weather information and building；
Step 2: carrying out heating load model using energy simulation software according to the obtained data information is collected
Foundation, and classify to the parameter to be calibrated in heating load model, the parameter to be calibrated includes building thermal technique
Parameter and people's behavior relevant parameter, people's behavior relevant parameter include that generation amount parameter and ventilation time are disturbed in building
Number；
Step 3: obtaining influencing maximum building thermal technique ginseng to heating load first with Morris Sensitivity Analysis
Number, removing influences small building thermal technique parameter to heating load to reduce building thermal technique number of parameters to be calibrated；Then make
It is negative to Building Heat with energy simulation value and the practical building minimum target of heat dissipation magnitude error with the PSO algorithm of mixing GPS
Lotus influences maximum building thermal technique parameter and is calibrated；
Step 4: carrying out clustering to outdoor temperature obtains different classifications, it is then related to people's behavior in each classification
Parameter is calibrated, calibration method are as follows:
The first step is set separately in building and disturbs generation amount parameter and ventilation rate initial value and the calibration of change with time coefficient
Range, calibration range are empirically determined according to practical investigation situation combination professional knowledge；
Second step, it is minimum with energy simulation value and practical building heat dissipation magnitude error using the PSO algorithm of mixing GPS
Target calibrates the change with time coefficient that generation amount parameter and ventilation rate are disturbed in building；
Third step, initial value is multiplied with change with time coefficient calibration value disturbs generation amount parameter and ventilation rate Ji Wei in building
Change with time calibration value；
Step 5: by the heating load analogue value of building thermal technique parameter and people's behavior relevant parameter after calibration and step 1
The practical heat consumption of building be compared, if meeting the requirement of calibration accuracy, terminate to calibrate；If not satisfied, then repeating step
The process of two~step 4, initial value setting and expansion before adjusting building thermal technique parameter and the calibration of human behavior relevant parameter
Or the calibration range of building thermal technique parameter and human behavior relevant parameter is reduced, then step 5 is carried out until meeting the requirements.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN110570024A (en) * | 2019-08-16 | 2019-12-13 | 天津大学 | refrigerating station operation evaluation method based on partial operation data and model calibration |
| CN110851762A (en) * | 2019-08-30 | 2020-02-28 | 北京中环合创环保能源科技有限公司 | Building dynamic simulation model building method of solar centralized heating system |
| CN112836396A (en) * | 2021-03-10 | 2021-05-25 | 同济大学 | Building real-time energy consumption abnormity diagnosis system |
| CN113343334A (en) * | 2021-05-28 | 2021-09-03 | 同济大学 | Cross-building air conditioner energy consumption prediction method and device based on air conditioner energy consumption sensitive variable |
| CN113486422A (en) * | 2021-06-17 | 2021-10-08 | 上海发电设备成套设计研究院有限责任公司 | Building energy consumption model parameter calibration method, device, equipment and storage medium |
| CN114048928A (en) * | 2022-01-12 | 2022-02-15 | 汉谷云智(武汉)科技有限公司 | Building short-term load prediction method with high migratability |
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Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110570024A (en) * | 2019-08-16 | 2019-12-13 | 天津大学 | refrigerating station operation evaluation method based on partial operation data and model calibration |
| CN110851762A (en) * | 2019-08-30 | 2020-02-28 | 北京中环合创环保能源科技有限公司 | Building dynamic simulation model building method of solar centralized heating system |
| CN112836396A (en) * | 2021-03-10 | 2021-05-25 | 同济大学 | Building real-time energy consumption abnormity diagnosis system |
| CN113343334A (en) * | 2021-05-28 | 2021-09-03 | 同济大学 | Cross-building air conditioner energy consumption prediction method and device based on air conditioner energy consumption sensitive variable |
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| CN114048928A (en) * | 2022-01-12 | 2022-02-15 | 汉谷云智(武汉)科技有限公司 | Building short-term load prediction method with high migratability |
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