CN109726876A - Space heating load evaluation method and system - Google Patents
Space heating load evaluation method and system Download PDFInfo
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Abstract
The invention discloses a kind of space heating load evaluation method and systems, this method comprises: designing heating index data based on geothermal heating system region, obtain heating index probability-distribution function；Based on geothermal heating system district heating area, geothermal heating system regional population number and heating community's occupancy rate, heat user area amount probability-distribution function is obtained；Based on heating number of days, heating season heating duration probability-distribution function is obtained；Based on the heating index probability-distribution function, the heat user area amount probability-distribution function and the heating season heating duration probability-distribution function, overall thermal demand probability-distribution function is obtained.The space heating load evaluation method can provide the space heating load evaluation method and system of science, accurate budget for space heating load.
Description
Technical field
The invention belongs to thermal technology fields, more particularly, to a kind of space heating load evaluation method and system.
Background technique
Currently, domestic community's building heating is from coal fired boiler into clean energy resource heating upgrading.It is scientific accurately right
The demand of community's building heating energy carries out the important prerequisite that assessment is heating upgrading.On the one hand, for it is different when
The building of phase, energy saving building standard is different, and on the other hand, with the aggravation of movement of population, winter, practical inhabitation heating user became
Change is also increasing, and there are larger uncertainties, therefore, central heating household metering independent for one community heating season heat
The scientific algorithm of load variations range is particularly important, however currently, this calculating process lacks universal effective calculating to analogy
Method is directly calculated according to architectural design thermic load parameter, show that fixed theoretical thermic load numerical value directly utilizes,
Or actual heating load requirements simply are obtained multiplied by an empirical coefficient on this basis, since existing calculation method is excessively simple
Single, therefore influence of the non-many changing factors of scientific algorithm to thermic load sets area in actual design central heating household metering
When heating system, be not design heating system heat source proportion ability it is excessive be exactly it is too low, be unfavorable for effectively arranging heat supply in winter
Energy source dispensing.
Therefore, it is necessary to develop one kind, and the space heating load evaluation of science, accurate budget can be provided for space heating load
Method and system.
Summary of the invention
The present invention provides a kind of space heating load evaluation method and system, which solves existing
Too simple problem present in the calculating of community's space heating load present in technology, provides science to community's space heating load
Calculation Estimation method, provide scientific basis for heating season ENERGY PLANNING.
To achieve the goals above, a kind of space heating load evaluation method is provided according to an aspect of the present invention, comprising:
Heating index data is designed based on geothermal heating system region, obtains heating index probability-distribution function；
Based on geothermal heating system district heating area, geothermal heating system regional population number and heating community's occupancy rate, obtains heat and use
Family area amount probability-distribution function；
Based on heating number of days, heating season heating duration probability-distribution function is obtained；
Based on the heating index probability-distribution function, the heat user area amount probability-distribution function and the heating season
Heating duration probability-distribution function obtains overall thermal demand probability-distribution function.
It is preferably based on geothermal heating system region design heating index data, obtaining heating index probability-distribution function includes:
Heating index data, construction area data are designed based on heating area, obtains geothermal heating system district heating area, in turn
Obtain heating index probability-distribution function.
It is preferably based on heating number of days, obtaining heating season heating duration probability-distribution function includes:
It is determined and is extended during heating season number of days and history or heating in advance time model based on heating area geographic location
It encloses, determines heating season heating duration probability distribution range, and then obtain heating season heating duration probability-distribution function.
It is preferably based on the heating index probability-distribution function, the heat user area amount probability-distribution function and institute
Heating season heating duration probability-distribution function is stated, the specific formula of overall thermal demand probability-distribution function is obtained are as follows:
F (E)=F (A) × F (T) × F (D) × 24 (1)
Wherein, F (E) is overall thermal demand probability-distribution function, and F (A) is heat user area amount probability-distribution function,
F (T) is heating index probability-distribution function, and F (D) is heating season heating duration probability-distribution function.
Preferably, further includes: be based on heating index probability-distribution function, underground heat heating area underground heat is set for heating area
Well.
A kind of space heating load evaluation system is provided according to another aspect of the present invention, which includes:
Memory is stored with computer executable instructions；
Processor, the processor run the computer executable instructions in the memory, execute following steps:
Heating index data is designed based on geothermal heating system region, obtains heating index probability-distribution function；
Based on geothermal heating system district heating area, geothermal heating system regional population number and heating community's occupancy rate, obtains heat and use
Family area amount probability-distribution function；
Based on heating number of days, heating season heating duration probability-distribution function is obtained；
Based on the heating index probability-distribution function, the heat user area amount probability-distribution function and the heating season
Heating duration probability-distribution function obtains overall thermal demand probability-distribution function.
Preferably, described that heating index data is designed based on geothermal heating system region, obtain heating index probability-distribution function:
Heating index data, construction area data are designed based on heating area, obtains geothermal heating system district heating area, in turn
Obtain heating index probability-distribution function.
It is preferably based on heating number of days, obtaining heating season heating duration probability-distribution function includes:
It is determined and is extended during heating season number of days and history or heating in advance time model based on heating area geographic location
It encloses, determines heating season heating duration probability distribution range, and then obtain heating season heating duration probability-distribution function.
It is preferably based on the heating index probability-distribution function, the heat user area amount probability-distribution function and institute
Heating season heating duration probability-distribution function is stated, the specific formula of overall thermal demand probability-distribution function is obtained are as follows:
F (E)=F (A) × F (T) × F (D) × 24 (1)
Wherein, F (E) is overall thermal demand probability-distribution function, and F (A) is heat user area amount probability-distribution function,
F (T) is heating index probability-distribution function, and F (D) is heating season heating duration probability-distribution function.
Preferably, further includes: be based on heating index probability-distribution function, underground heat heating area underground heat is set for heating area
Well.
The beneficial effects of the present invention are: the present invention is based on heating index probability-distribution functions, heat user area amount probability
Distribution function and heating season heating duration probability-distribution function, the space heating load evaluation method solve existing in the prior art
Too simple problem present in the calculating of community's space heating load, provides the Calculation Estimation side of science to community's space heating load
Method provides scientific basis for heating season ENERGY PLANNING.
Other features and advantages of the present invention will then part of the detailed description can be specified.
Detailed description of the invention
Exemplary embodiment of the invention is described in more detail in conjunction with the accompanying drawings, it is of the invention above-mentioned and its
Its purpose, feature and advantage will be apparent, wherein in exemplary embodiment of the invention, identical reference label
Typically represent same parts.
Fig. 1 shows the flow chart of space heating load evaluation method according to an embodiment of the invention.
Fig. 2 shows the low area's heating heating index probability distribution signals of the community M according to an embodiment of the invention heating
Figure.
Fig. 3 shows heating season thermal demand probability distribution schematic diagram in the community M according to an embodiment of the invention.
Specific embodiment
The preferred embodiment of the present invention is described in more detail below.Although the following describe preferred implementations of the invention
Mode, however, it is to be appreciated that may be realized in various forms the present invention without that should be limited by the embodiments set forth herein.Phase
Instead, these embodiments are provided so that the present invention is more thorough and complete, and can be by the scope of the present invention completely
It is communicated to those skilled in the art.
Embodiment 1
A kind of space heating load evaluation method is provided according to an aspect of the present invention, comprising:
Heating index data is designed based on geothermal heating system region, obtains heating index probability-distribution function；
Based on geothermal heating system district heating area, geothermal heating system regional population number and heating community's occupancy rate, obtains heat and use
Family area amount probability-distribution function；
Based on heating number of days, heating season heating duration probability-distribution function is obtained；
Based on the heating index probability-distribution function, the heat user area amount probability-distribution function and the heating season
Heating duration probability-distribution function obtains overall thermal demand probability-distribution function.
Specifically, it the present invention is based on the probability Distribution Model of community's relevant parameter to be evaluated, is calculated using Monte Carlo method
Multiple correlation factors control the probability distribution of lower community's heating season demand geothermal energy, and each calculating parameter is adopted according to specific actual conditions
It is stated with probability distribution, can be Normal probability distribution, triangle probability distribution, is uniformly distributed equal distribution form.The evaluation side
Method can be widely applied in various community's heating thermal demand evaluation procedures, and science easily recognizes the acquirement of community's heating demands
Know, provides scientific basis for heating season ENERGY PLANNING, use manpower and material resources sparingly resource.
The following detailed description of the specific steps of space heating load evaluation method according to the present invention.
Heating index data is designed based on geothermal heating system region, obtains heating index probability-distribution function.
In one example, heating index data, construction area data are designed based on heating area, obtains geothermal heating system region
Heating area, and then obtain heating index probability-distribution function.
Specifically, design heating index data, the construction area data of community's acceptance(check) to be evaluated, including different buildings are collected
The detailed area data of layer, unit, and then obtain heating index probability-distribution function.
Based on geothermal heating system district heating area, geothermal heating system regional population number and heating community's occupancy rate, obtains heat and use
Family area amount probability-distribution function.
Specifically, according to community planning population and the occupancy rate of estimation, judge to determine heat user area amount probability point
Cloth range obtains heat user area amount probability-distribution function.
Based on heating number of days, heating season heating duration probability-distribution function is obtained.
In one example, determined based on heating area geographic location extend during heating season number of days and history or
Heating in advance time range determines heating season heating duration probability distribution range, and then obtains heating season heating duration probability point
Cloth function.
Specifically, it is determined and is extended during heating season number of days and history or when heating in advance according to community geographic location
Between range, determine heating season heating duration probability distribution range, determine heating season heating duration probability-distribution function, and then obtain
Heating season heating duration probability-distribution function.
Based on the heating index probability-distribution function, the heat user area amount probability-distribution function and the heating season
Heating duration probability-distribution function obtains overall thermal demand probability-distribution function.
In one example, the heating index probability-distribution function, the heat user area amount probability distribution letter are based on
The several and described heating season heating duration probability-distribution function obtains the specific formula of overall thermal demand probability-distribution function are as follows:
F (E)=F (A) × F (T) × F (D) × 24 (1)
Wherein, F (E) is overall thermal demand probability-distribution function, and F (A) is heat user area amount probability-distribution function,
F (T) is heating index probability-distribution function, and F (D) is heating season heating duration probability-distribution function.
Based on heating index probability-distribution function, underground heat heating area geothermal well is set for heating area.
Embodiment 2
A kind of space heating load evaluation system is provided according to another aspect of the present invention, comprising:
Memory is stored with computer executable instructions；
Processor, the processor run the computer executable instructions in the memory, execute following steps:
Heating index data is designed based on geothermal heating system region, obtains heating index probability-distribution function；
Based on geothermal heating system district heating area, geothermal heating system regional population number and heating community's occupancy rate, obtains heat and use
Family area amount probability-distribution function；
Based on heating number of days, heating season heating duration probability-distribution function is obtained；
Based on the heating index probability-distribution function, the heat user area amount probability-distribution function and the heating season
Heating duration probability-distribution function obtains overall thermal demand probability-distribution function.
Preferably, described that heating index data is designed based on geothermal heating system region, obtain heating index probability distribution letter
Number includes:
Heating index data, construction area data are designed based on heating area, obtains geothermal heating system district heating area, in turn
Obtain heating index probability-distribution function.
Preferably, based on heating number of days, obtaining heating season heating duration probability-distribution function includes:
It is determined and is extended during heating season number of days and history or heating in advance time model based on heating area geographic location
It encloses, determines heating season heating duration probability distribution range, and then obtain heating season heating duration probability-distribution function.
Preferably, the heating index probability-distribution function, the heat user area amount probability distribution letter are based on
The several and described heating season heating duration probability-distribution function obtains the specific formula of overall thermal demand probability-distribution function are as follows:
F (E)=F (A) × F (T) × F (D) × 24 (1)
Wherein, F (E) is overall thermal demand probability-distribution function, and F (A) is heat user area amount probability-distribution function,
F (T) is heating index probability-distribution function, and F (D) is heating season heating duration probability-distribution function.
Preferably, further includes: be based on heating index probability-distribution function, underground heat heating area is set for heating area
Geothermal well.
Embodiment
Fig. 1 shows the flow chart of space heating load evaluation method according to an embodiment of the invention.Fig. 2 shows
Heat low area's heating heating index probability distribution schematic diagram for the community M according to an embodiment of the invention.Fig. 3 is shown according to this
The community the M heating season thermal demand probability distribution schematic diagram of one embodiment of invention.
As shown in Figure 1-Figure 3, the space heating load evaluation method, comprising:
1) the design heating index data for collecting community's acceptance(check) to be evaluated, establishes heating index probability-distribution function F (T),
Collect gross floors area parameter A, the detailed area data including different heating index floors, unit.By taking the community M as an example, total is built
Building area A is 280,000 square meters, wherein heat low area's area AlFor 100,000 square meters, heating heating index highest Tlmax45W/m2, minimum
36TlminW/m2, most probable heating heating index Tlmode38W/m2；Heat high area's area AhFor 180,000 square meters, heating heating index highest
Thmax42W/m2, minimum 38ThminW/m2, most probable heating heating index Thmode40W/m2。
Wherein, it heats low area's heating heating index F (T)l, meet angular distribution, may be expressed as:
Tlmax--- heat low area's heating heating index peak (W/m2), Tlmin--- the low area's heating heating index that heats is minimum
It is worth (W/m2), Tlmode--- heat low area's heating heating index most probable value (W/m2), Ci--- the equally distributed puppet in [0,1] section
Random number；
It heats high area's heating heating index F (T)h, meet angular distribution, may be expressed as:
Thmax--- heat high area's heating heating index peak (W/m2), Thmin--- heat high area's heating heating index highest
It is worth (W/m2), Thmode--- heat high area's heating heating index most probable value (W/m2), Ci--- the equally distributed puppet in [0,1] section
Random number；
2) according to community planning population and the occupancy rate of estimation, judge to determine heat user area amount probability-distribution function
F(A).By taking the community M as an example, heat low area's area AlFor 100,000 square meters, heat user number minimum 60%, that is, low area's heat user face of heating
The minimum A of product amountlminFor ten thousand square meter of 10*60%=6, heat user number highest 100% heats low area's heat user area amount most
High AlmaxFor 100,000 square meters, heat user number most probable 90%, that is, heat low area's heat user area amount most probable value AlmodeFor 10*
Ten thousand square meter of 90%=9；Heat high area's area AhFor 180,000 square meters, heat user number minimum 60%, that is, heat high area's heat user area
The minimum A of quantityhminFor ten thousand square meter of 18*60%=10.8, heat user number highest 100%, that is, heat high area's heat user area amount
Highest AhmaxFor 180,000 square meters, heat user number most probable 80%, that is, heat high area's heat user area amount most probable value AhmodeFor
Ten thousand square meter of 18*90%=16.2, heat low area, high area's heat user area amount probability function F (A for communityl)、F(Ah) meet three
Angle distribution:
Almax--- heat low area's heat user area amount peak (m2), Almin--- heat low area's heat user area number
Measure minimum (m2), Almode--- heat low area's heat user area amount most probable value (W/m2), Ci--- [0,1] section is uniform
The pseudo random number of distribution；
Ahmax--- heat high area's heat user area amount peak (m2), Ahmin--- heat high area's heat user area number
Measure minimum (m2), Ahmode--- heat high area's heat user area amount most probable value (W/m2), Ci--- [0,1] section is uniform
The pseudo random number of distribution；
3) the repair and maintenance phase needs to stop during determining heating season producing days, and heating according to geothermal well geographic location
The time range of production determines heating season heating duration probability distribution range.The community M normally heats 120 days in location winter, root
It heats according to needing longest to shift to an earlier date 15 days, can at most shift to an earlier date the heating of stopping in 2 days, therefore heating duration can be distributed by triangle probability
It calculates, obtains heating season heating duration probability-distribution function F (D), wherein minimum heating number of days 118 days, highest heating number of days
135, most probable heats number of days 120 days.F (D) can be indicated are as follows:
Dmax--- highest heats number of days (d), Dmin--- minimum heating number of days (d), Dmode--- most probable heating number of days
(d), Ci--- the equally distributed pseudo random number in [0,1] section；
4) according to step 1), 2) and 3) described in community heat parameter probability distribution, calculate the community heating season M thermal demand
Probability distribution, that is, community heat load distribution probability function F (E) may be expressed as:
F (E)=(F (Al)×F(Tl)+F(Ah)×F(Th))×F(D)×24
Calculated result is as shown in figure 3, the heating season of the community one needs to provide 2.69 × 10 under the conditions of accumulated probability 10%7
The thermal energy of kilowatt hour, the heating season of the community one needs to provide 3.42 × 10 under the conditions of accumulated probability 90%7Kilowatt hour
Thermal energy is 3.01 × 10 under the conditions of average probability7The thermal energy of kilowatt hour.
5) in embodiment, according to the thermal energy magnitude of the community M difference accumulated probability condition next heating season heating heat demand,
Estimated energy that can be scientific supplies deployment, reduces energy arrangement and energy market fluctuates bring risk.
Various embodiments of the present invention are described above, above description is exemplary, and non-exclusive, and
It is not limited to disclosed each embodiment.Without departing from the scope and spirit of illustrated each embodiment, for this skill
Many modifications and changes are obvious for the those of ordinary skill in art field.
Claims (10)
1. a kind of space heating load evaluation method, which is characterized in that this method comprises:
Heating index data is designed based on geothermal heating system region, obtains heating index probability-distribution function；
Based on geothermal heating system district heating area, geothermal heating system regional population number and heating community's occupancy rate, heat user face is obtained
Product amount probability-distribution function；
Based on heating number of days, heating season heating duration probability-distribution function is obtained；
It is heated based on the heating index probability-distribution function, the heat user area amount probability-distribution function and the heating season
Time probability distribution function obtains overall thermal demand probability-distribution function.
2. space heating load evaluation method according to claim 1, which is characterized in that described to be set based on geothermal heating system region
Heating index data is counted, obtaining heating index probability-distribution function includes:
Heating index data, construction area data are designed based on heating area, and then obtains heating index probability-distribution function.
3. space heating load evaluation method according to claim 1, which is characterized in that based on heating number of days, obtain heating
Season, heating duration probability-distribution function included:
It is determined and is extended during heating season number of days and history or heating in advance time range based on heating area geographic location,
It determines heating season heating duration probability distribution range, and then obtains heating season heating duration probability-distribution function.
4. space heating load evaluation method according to claim 1, which is characterized in that be based on the heating index probability distribution
Function, the heat user area amount probability-distribution function and the heating season heating duration probability-distribution function obtain overall
The specific formula of thermal demand probability-distribution function are as follows:
F (E)=F (A) × F (T) × F (D) × 24 (1)
Wherein, F (E) is overall thermal demand probability-distribution function, and F (A) is heat user area amount probability-distribution function, F (T)
For heating index probability-distribution function, F (D) is heating season heating duration probability-distribution function.
5. space heating load evaluation method according to claim 1, which is characterized in that further include: it is based on heating index probability
Underground heat heating area geothermal well is arranged for heating area in distribution function.
6. a kind of space heating load evaluation system, which is characterized in that the system comprises:
Memory is stored with computer executable instructions；
Processor, the processor run the computer executable instructions in the memory, execute following steps:
Heating index data is designed based on geothermal heating system region, obtains heating index probability-distribution function；
Based on geothermal heating system district heating area, geothermal heating system regional population number and heating community's occupancy rate, heat user face is obtained
Product amount probability-distribution function；
Based on heating number of days, heating season heating duration probability-distribution function is obtained；
It is heated based on the heating index probability-distribution function, the heat user area amount probability-distribution function and the heating season
Time probability distribution function obtains overall thermal demand probability-distribution function.
7. space heating load evaluation system according to claim 6, which is characterized in that described to be set based on geothermal heating system region
Heating index data is counted, obtaining heating index probability-distribution function includes:
Heating index data, construction area data are designed based on heating area, and then obtains heating index probability-distribution function.
8. space heating load evaluation system according to claim 6, which is characterized in that based on heating number of days, obtain heating
Season, heating duration probability-distribution function included:
It is determined and is extended during heating season number of days and history or heating in advance time range based on heating area geographic location,
It determines heating season heating duration probability distribution range, and then obtains heating season heating duration probability-distribution function.
9. space heating load evaluation system according to claim 6, which is characterized in that be based on the heating index probability distribution
Function, the heat user area amount probability-distribution function and the heating season heating duration probability-distribution function obtain overall
The specific formula of thermal demand probability-distribution function are as follows:
F (E)=F (A) × F (T) × F (D) × 24 (1)
Wherein, F (E) is overall thermal demand probability-distribution function, and F (A) is heat user area amount probability-distribution function, F (T)
For heating index probability-distribution function, F (D) is heating season heating duration probability-distribution function.
10. space heating load evaluation system according to claim 6, which is characterized in that further include: it is based on heating index probability
Underground heat heating area geothermal well is arranged for heating area in distribution function.
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| CN104408563A (en) * | 2014-11-27 | 2015-03-11 | 国网宁夏电力公司 | Regional planning method for wind power heating |
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