CN115115089A - Building carbon emission prediction analysis method, system, terminal and medium - Google Patents
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Abstract
The invention discloses a method, a system, a terminal and a medium for predicting and analyzing carbon emission of a building, which relate to the technical field of carbon emission analysis, and have the technical scheme that: establishing a data balance model according to the type of the consumed energy and the type of the energy utilization system; inputting carbon emission data into a data balance model to obtain balance coefficients between each energy consumption system type and each energy consumption type; establishing a balance change curve changing along with time according to the balance coefficient, and intercepting the predicted balance coefficient of a future period; selecting type data with minimum volatility as a reference value, and analyzing by combining predicted balance coefficients to obtain predicted values of various energy consumption types and energy consumption system types; and inputting the predicted value into a carbon emission calculation model to obtain the predicted value of the carbon emission. The method can accurately and reliably analyze the carbon emission prediction result under the influence of factors such as human activities and the like, and is suitable for the carbon emission analysis of the target object under different space and time environments.
Description
Technical Field
The invention relates to the technical field of carbon emission analysis, in particular to a method, a system, a terminal and a medium for predicting and analyzing building carbon emission.
Background
Carbon emissions are a general or short term for greenhouse gas emissions, the most prominent of which is carbon dioxide, and therefore the term carbon is used as a representative. In each industry, the building industry consumes about 30% -40% of energy globally and discharges greenhouse gases which account for almost 30% of the world, so that effective monitoring and analysis of building carbon emission are necessary to provide basic data for achieving the carbon emission reduction target.
The carbon emission monitoring technology which is common in the prior art is distributed monitoring, and the carbon emission condition of a single region or country can be obtained by accurately monitoring a single target object, such as individuals, unit enterprises, single buildings and the like, and summarizing monitoring results. To ensure the timeliness of carbon emission analysis, the prior art has documented that carbon emission results in the future time are analyzed by data modeling of various targets and combining existing activity data predictions. However, carbon emission is an artificially dominant behavior result, and as a result of a plurality of factors such as seasons, alternation between off-seasons and high-seasons of the industry, nature of the industry, and geographical conditions, the artificially dominant behavior result has differences in different areas, and if the factors are added in consideration of design on the basis of the existing data prediction model, the computational complexity of the prediction result is inevitably improved, and the application difficulty is high.
Therefore, how to design a method, a system, a terminal and a medium for predicting and analyzing the carbon emission of the building, which can overcome the above defects, is a problem which is urgently needed to be solved at present.
Disclosure of Invention
In order to solve the defects in the prior art, the invention aims to provide a method, a system, a terminal and a medium for predicting and analyzing the carbon emission of a building, which can accurately and reliably analyze the carbon emission prediction result under the influence of factors such as artificial activities and the like and are suitable for the carbon emission analysis of a target object in different space and time environments.
The technical purpose of the invention is realized by the following technical scheme:
in a first aspect, a method for predicting and analyzing carbon emission of a building is provided, which comprises the following steps:
establishing a data balance model related to each carbon emission data according to the type of the consumed energy and the type of the energy utilization system;
inputting carbon emission data in a plurality of historical periods into a data balance model to obtain balance coefficients between each energy consumption system type and each energy consumption type in the corresponding historical period;
establishing a balance change curve changing along with time according to the same type of balance coefficients in a plurality of historical periods, and intercepting the predicted balance coefficients of a future period from the balance change curve;
selecting type data with minimum volatility from each consumed energy type and each energy utilization system type as a reference value, and analyzing by combining with each predicted balance coefficient to obtain predicted values of each consumed energy type and each energy utilization system type;
and inputting the predicted values of the various energy consumption types and the energy utilization system types into the carbon emission calculation model to obtain the predicted value of the carbon emission.
Further, the calculation formula of the data balance model is specifically as follows:
wherein, P (b, a) represents a balance coefficient between the energy consumption system type b and the energy consumption type a; e a Representing consumption corresponding to the type a of consumed energyAn amount; e b Representing the consumption corresponding to the energy consumption system type b; e i Represents the consumption amount of the ith consumed energy type; n represents the number of types of consumed energy; e j Represents the consumption of the jth energy usage system type; m represents the number of energy usage system types.
Further, the analysis process of the predicted value specifically includes:
establishing a check matrix according to all predicted balance coefficients;
correcting and analyzing the predicted balance coefficients of the corresponding rows according to the fluctuation conditions of all the predicted balance coefficients in the check matrix to obtain first correction coefficients of the predicted balance coefficients of the corresponding rows;
correcting and analyzing the predicted balance coefficients of the corresponding columns according to the fluctuation conditions of all the predicted balance coefficients in the check matrix to obtain second correction coefficients of the predicted balance coefficients of the corresponding columns;
comprehensively correcting the corresponding predicted balance coefficient according to the first correction coefficient and the second correction coefficient to obtain a final balance coefficient;
and solving according to the reference value and the final balance coefficient to obtain predicted values of various energy consumption system types and energy consumption types.
Further, the calculation formula of the first correction coefficient is specifically:
wherein, P k,g Representing the balance coefficient of the kth prediction in the g row in the check matrix; x is the number of k,g A first correction coefficient corresponding to a balance coefficient representing a kth prediction in a g-th row; q represents the number of columns in the check matrix; h denotes the number of rows in the check matrix.
Further, the calculation formula of the final balance coefficient is specifically as follows:
P Z ＝P 0 (1+0.5X 1 +0.5X 2 )
wherein, P Z Representing the final equilibrium coefficient; p 0 Representing predicted equilibrium coefficients; x 1 Represents a first correction coefficient; x 2 Indicating the second correction factor.
Further, the balance change curve is constructed by a least square method.
Further, the calculation formula of the carbon emission calculation model is specifically as follows:
wherein the content of the first and second substances,
representing the actual carbon emissions of the target building over a fixed period; e i Represents the consumption amount of the ith consumed energy type; f i A carbon emission factor representing an ith type of energy consumed; n represents the number of types of consumed energy; c p Representing greening carbon reduction amount; e i(j) A category i energy consumption representing a jth energy usage system type; r i(j) Indicating that the jth energy system type consumes the ith type of energy provided by the renewable energy system; m represents the number of energy usage system types.
In a second aspect, a system for predictive analysis of carbon emissions from a building is provided, comprising:
the model building module is used for building a data balance model related to each item of carbon emission data according to the type of the consumed energy and the type of the energy utilization system;
the balance calculation module is used for inputting the carbon emission data in the plurality of historical periods into the data balance model to obtain balance coefficients between each energy consumption system type and each energy consumption type in the corresponding historical period;
the balance predicting module is used for establishing a balance change curve changing along with time according to the same type of balance coefficients in a plurality of historical periods and intercepting the predicted balance coefficients of a future period from the balance change curve;
the prediction analysis module is used for selecting type data with minimum volatility from each consumed energy type and energy utilization system type as a reference value and analyzing by combining each predicted balance coefficient to obtain predicted values of each consumed energy type and energy utilization system type;
and the prediction calculation module is used for inputting the predicted values of the various consumed energy types and the energy system types into the carbon emission calculation model to obtain the predicted value of the carbon emission.
In a third aspect, a computer terminal is provided, which includes a memory, a processor and a computer program stored in the memory and executable on the processor, and when the processor executes the computer program, the method for predicting and analyzing the carbon emission of a building according to any one of the first aspect is implemented.
In a fourth aspect, a computer-readable medium is provided, on which a computer program is stored, the computer program being executed by a processor to implement the building carbon emission prediction analysis method according to any one of the first aspect.
Compared with the prior art, the invention has the following beneficial effects:
1. according to the building carbon emission prediction analysis method provided by the invention, the balance coefficients between each energy system type and each energy consumption type are analyzed through the data balance model, the predicted balance coefficients of the future period are obtained according to a nonlinear fitting mode, and the carbon emission prediction result under the influence of factors such as artificial activities can be accurately and reliably analyzed according to at least one relatively stable data and the determined predicted balance coefficients, so that the building carbon emission prediction analysis method is suitable for the carbon emission analysis of target objects under different space and time environments;
2. the invention corrects the predicted balance coefficient from two dimensions of the energy consumption system type and the energy consumption type, thereby effectively reducing the prediction error.
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The accompanying drawings, which are included to provide a further understanding of the embodiments of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the principles of the invention. In the drawings:
FIG. 1 is a flow chart in an embodiment of the invention;
fig. 2 is a block diagram of a system in an embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to examples and accompanying drawings, and the exemplary embodiments and descriptions thereof are only used for explaining the present invention and are not meant to limit the present invention.
Example 1: the method for predicting and analyzing the carbon emission of the building, as shown in figure 1, comprises the following steps:
s1: establishing a data balance model related to each carbon emission data according to the type of the consumed energy and the type of the energy utilization system;
s2: inputting carbon emission data in a plurality of historical periods into a data balance model to obtain balance coefficients between each energy consumption system type and each energy consumption type in the corresponding historical period;
s3: establishing a balance change curve changing along with time by adopting a least square method according to the balance coefficients of the same class in a plurality of historical periods, and intercepting the predicted balance coefficients of a future period from the balance change curve;
s4: selecting type data with minimum volatility from each consumed energy type and each energy utilization system type as a reference value, and analyzing by combining with each predicted balance coefficient to obtain predicted values of each consumed energy type and each energy utilization system type;
s5: and inputting the predicted values of the various energy consumption types and the energy utilization system types into the carbon emission calculation model to obtain the predicted value of the carbon emission.
The method considers the influence of external factors such as artificial dominance on the carbon emission data, and performs characterization according to the incidence relation among the data, namely, the balance coefficients between each energy consumption system type and each energy consumption type are analyzed through a data balance model, the predicted balance coefficients of the future period are obtained according to a nonlinear fitting mode, and the carbon emission prediction result under the influence of factors such as artificial activities can be accurately and reliably analyzed according to at least one relatively stable data and the determined predicted balance coefficients, so that the method is suitable for the carbon emission analysis of the target object under different space and time environments.
In this embodiment, the calculation formula of the data balance model is specifically:
wherein, P (b, a) represents a balance coefficient between the energy consumption system type b and the energy consumption type a; e a Representing the consumption corresponding to the consumed energy type a; e b Representing the consumption corresponding to the energy consumption system type b; e i Represents the consumption amount of the ith consumed energy type; n represents the number of types of consumed energy; e j Represents the consumption of the jth energy system type; m represents the number of energy usage system types.
In addition, the data balance model can be constructed from the overall distribution of all energy consumption system types and all energy consumption types, can also be constructed from a single energy consumption system type corresponding to all energy consumption types, and can also be constructed from a single energy consumption type corresponding to all energy consumption system types, and is not limited to the single energy consumption system type corresponding to the single energy consumption type.
The analysis process of the predicted value specifically comprises the following steps: establishing a check matrix with the size of n multiplied by m according to all predicted balance coefficients; correcting and analyzing the predicted balance coefficients of the corresponding rows according to the fluctuation conditions of all the predicted balance coefficients in the check matrix to obtain first correction coefficients of the predicted balance coefficients of the corresponding rows; correcting and analyzing the predicted balance coefficients of the corresponding columns according to the fluctuation conditions of all the predicted balance coefficients in the check matrix to obtain second correction coefficients of the predicted balance coefficients of the corresponding columns; comprehensively correcting the corresponding predicted balance coefficient according to the first correction coefficient and the second correction coefficient to obtain a final balance coefficient; and solving according to the reference value and the final balance coefficient to obtain predicted values of various energy consumption system types and energy consumption types.
In this embodiment, the first correction coefficient and the second correction coefficient have the same calculation formula principle, and taking the first correction coefficient as an example, the calculation formula is specifically:
wherein, P k,g Representing the balance coefficient of the kth prediction in the g row in the check matrix; x is the number of k,g A first correction coefficient corresponding to a balance coefficient representing a kth prediction in a g-th row; q represents the number of columns in the check matrix; h denotes the number of rows in the check matrix.
In this embodiment, the calculation formula of the final balance coefficient is specifically:
P Z ＝P 0 (1+0.5X 1 +0.5X 2 )
wherein, P Z Representing the final equilibrium coefficient; p 0 Representing predicted equilibrium coefficients; x 1 Represents a first correction coefficient; x 2 Indicating the second correction factor.
In this embodiment, the calculation formula of the carbon emission calculation model is specifically:
wherein the content of the first and second substances,
representing the actual carbon emissions of the target building over a fixed period; e i Represents the consumption amount of the ith consumed energy type; f i A carbon emission factor representing an ith type of energy consumed; n represents the number of types of consumed energy; c p Representing greening carbon reduction amount; e i(j) A category i energy consumption representing a jth energy usage system type; r i(j) Indicating that the jth energy system type consumes the ith type of energy provided by the renewable energy system; m represents the number of energy usage system types.
It should be noted that the carbon emission calculation model may also be a model that is analyzed according to specific activities, and is not limited to the above model that is analyzed from the whole.
Example 2: a system for predicting and analyzing carbon emissions of a building, which is used for implementing the analysis method described in embodiment 1, includes a model building module, a balance calculation module, a balance prediction module, a prediction analysis module, and a prediction calculation module, as shown in fig. 2.
The model building module is used for building a data balance model related to each item of carbon emission data according to the type of consumed energy and the type of an energy utilization system; the balance calculation module is used for inputting the carbon emission data in the plurality of historical periods into the data balance model to obtain balance coefficients between each energy consumption system type and each energy consumption type in the corresponding historical period; the balance predicting module is used for establishing a balance change curve changing along with time according to the same type of balance coefficients in a plurality of historical periods and intercepting the predicted balance coefficients of a future period from the balance change curve; the prediction analysis module is used for selecting type data with minimum volatility from each consumed energy type and energy utilization system type as a reference value and analyzing by combining each predicted balance coefficient to obtain predicted values of each consumed energy type and energy utilization system type; and the prediction calculation module is used for inputting the predicted values of the various consumed energy types and the energy system types into the carbon emission calculation model to obtain the predicted value of the carbon emission.
The working principle is as follows: according to the method, the balance coefficients between each energy consumption system type and each energy consumption type are analyzed through the data balance model, the predicted balance coefficients of the future period are obtained according to a nonlinear fitting mode, and the carbon emission prediction result under the influence of factors such as artificial activities can be accurately and reliably analyzed according to at least one relatively stable data and the determined predicted balance coefficients, so that the method is suitable for the carbon emission analysis of target objects under different space and time environments; in addition, the invention corrects the predicted balance coefficient from two dimensions of the energy consumption system type and the energy consumption type, thereby effectively reducing the prediction error.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The above embodiments are provided to further explain the objects, technical solutions and advantages of the present invention in detail, it should be understood that the above embodiments are merely exemplary embodiments of the present invention and are not intended to limit the scope of the present invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. The method for predicting and analyzing the carbon emission of the building is characterized by comprising the following steps of:
establishing a data balance model associated with each carbon emission data according to the type of the consumed energy and the type of the energy utilization system;
inputting carbon emission data in a plurality of historical periods into a data balance model to obtain balance coefficients between each energy consumption system type and each energy consumption type in the corresponding historical period;
establishing a balance change curve changing along with time according to the same type of balance coefficients in a plurality of historical periods, and intercepting the predicted balance coefficients of a future period from the balance change curve;
selecting type data with minimum volatility from each consumed energy type and each energy utilization system type as a reference value, and analyzing by combining with each predicted balance coefficient to obtain predicted values of each consumed energy type and each energy utilization system type;
and inputting the predicted values of the various energy consumption types and the energy utilization system types into the carbon emission calculation model to obtain the predicted value of the carbon emission.
2. The method for predicting and analyzing the carbon emission of the building as claimed in claim 1, wherein the calculation formula of the data balance model is specifically as follows:
wherein, P (b, a) represents a balance coefficient between the energy consumption system type b and the energy consumption type a; e a Representing the consumption corresponding to the consumed energy type a; e b Energy for representationConsumption corresponding to system type b; e i Represents the consumption amount of the ith consumed energy type; n represents the number of types of consumed energy; e j Represents the consumption of the jth energy usage system type; m represents the number of energy usage system types.
3. The method for predicting and analyzing the carbon emission of the building as claimed in claim 1, wherein the analysis process of the predicted value is specifically as follows:
establishing a check matrix according to all predicted balance coefficients;
correcting and analyzing the predicted balance coefficients of the corresponding rows according to the fluctuation conditions of all the predicted balance coefficients in the check matrix to obtain first correction coefficients of the predicted balance coefficients of the corresponding rows;
correcting and analyzing the predicted balance coefficients of the corresponding columns according to the fluctuation conditions of all the predicted balance coefficients in the check matrix to obtain second correction coefficients of the predicted balance coefficients of the corresponding columns;
comprehensively correcting the corresponding predicted balance coefficient according to the first correction coefficient and the second correction coefficient to obtain a final balance coefficient;
and solving according to the reference value and the final balance coefficient to obtain predicted values of various energy consumption system types and energy consumption types.
4. The method for predicting and analyzing the carbon emission of the building as claimed in claim 3, wherein the calculation formula of the first correction coefficient is specifically as follows:
wherein, P k,g Representing the balance coefficient of the kth prediction in the g row in the check matrix; x is the number of k,g A first correction coefficient corresponding to a balance coefficient representing a kth prediction in a g-th row; q represents the number of columns in the check matrix; h denotes the number of rows in the check matrix.
5. The method for predicting and analyzing the carbon emission of the building as claimed in claim 3, wherein the calculation formula of the final balance coefficient is specifically as follows:
P Z ＝P 0 (1+0.5X 1 +0.5X 2 )
wherein, P Z Representing the final equilibrium coefficient; p 0 Representing the predicted balance coefficients; x 1 Represents a first correction coefficient; x 2 Indicating the second correction factor.
6. The method for predicting and analyzing carbon emission of buildings according to claim 1, wherein the balance change curve is constructed by a least square method.
7. The method for predicting and analyzing the carbon emission of the building as recited in claim 1, wherein the calculation formula of the carbon emission calculation model is specifically as follows:
wherein the content of the first and second substances,
representing the actual carbon emissions of the target building over a fixed period; e i Represents the consumption amount of the ith consumed energy type; f i A carbon emission factor representing an ith type of energy consumed; n represents the number of types of consumed energy; c p Representing greening carbon reduction amount; e i(j) A category i energy consumption representing a jth energy usage system type; r i(j) Representing that the jth energy consumption system type consumes the ith type of energy provided by the renewable energy system; m represents the number of energy usage system types.
8. Building carbon emission prediction analysis system, characterized by includes:
the model building module is used for building a data balance model related to each item of carbon emission data according to the type of the consumed energy and the type of the energy utilization system;
the balance calculation module is used for inputting the carbon emission data in the plurality of historical periods into the data balance model to obtain balance coefficients between each energy consumption system type and each energy consumption type in the corresponding historical period;
the balance predicting module is used for establishing a balance change curve changing along with time according to the same type of balance coefficients in a plurality of historical periods and intercepting the predicted balance coefficients of a future period from the balance change curve;
the prediction analysis module is used for selecting type data with minimum volatility from each consumed energy type and each energy consumption system type as a reference value and analyzing by combining each predicted balance coefficient to obtain predicted values of each consumed energy type and each energy consumption system type;
and the prediction calculation module is used for inputting the predicted values of the various consumed energy types and the energy system types into the carbon emission calculation model to obtain the predicted value of the carbon emission.
9. A computer terminal comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for predictive analysis of carbon emissions from buildings as claimed in any one of claims 1 to 7.
10. A computer-readable medium, on which a computer program is stored, the computer program being executable by a processor to implement the method for predictive analysis of carbon emissions from buildings according to any of claims 1 to 7.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115630434A (en) * | 2022-12-25 | 2023-01-20 | 国网上海能源互联网研究院有限公司 | Building carbon emission prediction method and device based on multi-agent simulation |
| CN115689253A (en) * | 2022-12-30 | 2023-02-03 | 北京智能建筑科技有限公司 | Comprehensive energy scheduling optimization method taking total carbon emission of building as target |
| CN115759346A (en) * | 2022-10-21 | 2023-03-07 | 中山大学 | AO algorithm based carbon emission prediction method, device and equipment |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115759346A (en) * | 2022-10-21 | 2023-03-07 | 中山大学 | AO algorithm based carbon emission prediction method, device and equipment |
| CN115759346B (en) * | 2022-10-21 | 2023-12-22 | 中山大学 | Carbon emission prediction method, device and equipment based on AO algorithm |
| CN115630434A (en) * | 2022-12-25 | 2023-01-20 | 国网上海能源互联网研究院有限公司 | Building carbon emission prediction method and device based on multi-agent simulation |
| CN115630434B (en) * | 2022-12-25 | 2023-04-07 | 国网上海能源互联网研究院有限公司 | Building carbon emission prediction method and device based on multi-agent simulation |
| CN115689253A (en) * | 2022-12-30 | 2023-02-03 | 北京智能建筑科技有限公司 | Comprehensive energy scheduling optimization method taking total carbon emission of building as target |
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