Building energy-saving effect evaluation method and system based on causal reasoning

Abstract

The invention belongs to the technical field of effect evaluation, and particularly relates to a building energy-saving effect evaluation method and system based on causal reasoning, and the method comprises the steps: obtaining data information before and after energy-saving reconstruction; constructing a causal structure diagram based on the acquired data information; calculating a joint distribution estimation function based on the causal relationship according to the constructed causal structure diagram; and according to the obtained joint distribution estimation function based on the causal relationship, carrying out anti-fact analysis based on the causal relationship, calculating an anti-fact estimator and a mathematical expectation of power consumption by taking an energy-saving model as an intervention variable, and calculating an energy-saving rate based on the causal relationship according to the obtained anti-fact estimator and the mathematical expectation of the anti-fact estimator. And building energy-saving effect evaluation based on causal reasoning is completed.

Description

Technical Field

[0001] The present invention belongs to the technical field of effect evaluation, and in particular relates to a method and system for evaluating building energy-saving effects based on causal reasoning. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] In the field of building energy conservation, in order to evaluate the effect of energy-saving renovation, the energy saving rate is usually calculated by the difference between the original energy consumption and the improved energy consumption as a percentage of the original energy consumption (i.e. The original energy consumption and the energy consumption after improvement can be calculated by simulation software for theoretical energy consumption; or the actual energy consumption of the whole year or a single heating season / cooling season before and after the transformation can be used for calculation. The data collected before the energy-saving transformation is used to calculate the original energy consumption, and the data collected after the transformation is used to calculate the improved energy consumption; the theoretical value calculated by simulation software usually has a certain error from the actual measured energy consumption, and cannot reflect the actual equipment and on-site conditions.

[0004] Although the measured energy consumption can reflect the actual conditions of the equipment and the site, the measured energy consumption data before and after the energy-saving transformation are collected from different objective environments. Different objective environments will change the heat demand and equipment operation efficiency of heating, cooling and other equipment. That is, the energy-saving rate calculated in this form is affected by both the energy-saving transformation and the objective environment, and cannot fully and objectively evaluate the effect of the energy-saving transformation. Summary of the invention

[0005] To solve the above problems, the present invention proposes a building energy-saving effect evaluation method and system based on causal reasoning, which combines the causal inference theory, uses the measured energy consumption data collected from different objective environments before and after the energy-saving transformation, and calculates the energy consumption and energy-saving rate before and after the transformation under the same objective conditions, so that the energy-saving effect evaluation is based on the measured data, excluding the influence of the objective environment, and only the effect of the energy-saving transformation is included in the energy-saving rate.

[0006] According to some embodiments, a first solution of the present invention provides a building energy-saving effect evaluation method based on causal reasoning, which adopts the following technical solution: A building energy-saving effect evaluation method based on causal reasoning, comprising: Obtain data information before and after energy-saving transformation; Construct a cause-effect structure diagram based on the acquired data information; According to the constructed causal structure diagram, a joint distribution estimation function based on causal relationship is calculated; According to the obtained joint distribution estimation function based on causal relationship, counterfactual analysis based on causal relationship is carried out, and the counterfactual estimator of power consumption and its mathematical expectation are calculated with the energy-saving model as the intervention variable. According to the obtained counterfactual estimator and its mathematical expectation, the energy saving rate based on causal relationship is calculated, and the building energy-saving effect evaluation based on causal reasoning is completed.

[0007] As a further technical limitation, the data information obtained before and after the energy-saving transformation includes at least the energy-saving model, confusion factors, cooling capacity or heating capacity, power consumption and time.

[0008] Furthermore, the constructed causal structure diagram is a logical relationship between the power consumption and the confusion factor, the cooling capacity or heating capacity and the energy-saving model, and a logical relationship between the confusion factor and the cooling capacity or heating capacity and the energy-saving model.

[0009] As a further technical limitation, the causal relationship-based joint distribution estimation function is ;in, is the energy-saving model, and the energy-saving model before transformation is recorded as , the energy-saving model after transformation is ; as confounding factors; is cooling capacity or heating capacity; For power consumption.

[0010] Furthermore, in the process of counterfactual analysis based on causality, the energy saving model is an intervention variable, then the variable , , The joint distribution of ; ; Energy-saving model is the intervention variable, The counterfactual estimate of ; ; in, For variables , The mathematical expectation of .

[0011] Furthermore, the energy saving rate based on causality is ; in, For variables The mathematical expectation of .

[0012] According to some embodiments, a second solution of the present invention provides a building energy-saving effect evaluation system based on causal reasoning, which adopts the following technical solution: A building energy-saving effect evaluation system based on causal reasoning, comprising: An acquisition module, which is configured to acquire data information before and after energy-saving transformation; A construction module, which is configured to construct a causal structure diagram based on the acquired data information; A calculation module, configured to calculate a joint distribution estimation function based on causal relationships according to the constructed causal structure graph; The evaluation module is configured to perform counterfactual analysis based on causal relationship according to the obtained joint distribution estimation function based on causal relationship, calculate the counterfactual estimator of power consumption and its mathematical expectation with the energy-saving model as the intervention variable, calculate the energy-saving rate based on causal relationship according to the obtained counterfactual estimator and its mathematical expectation, and complete the building energy-saving effect evaluation based on causal reasoning.

[0013] According to some embodiments, a third solution of the present invention provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium stores a program, which, when executed by a processor, implements the steps of the building energy-saving effect evaluation method based on causal reasoning as described in the first solution of the present invention.

[0014] According to some embodiments, a fourth solution of the present invention provides an electronic device, which adopts the following technical solution: An electronic device comprises a memory, a processor and a program stored in the memory and running on the processor. When the processor executes the program, the steps in the building energy-saving effect evaluation method based on causal reasoning as described in the first solution of the present invention are implemented.

[0015] According to some embodiments, a fifth solution of the present invention provides a computer program product, which adopts the following technical solution: A computer program product includes software codes, wherein the program in the software codes executes the steps in the building energy-saving effect evaluation method based on causal reasoning as described in the first solution of the present invention.

[0016] Compared with the prior art, the present invention has the following beneficial effects: The present invention combines the causal inference theory, uses the measured energy consumption data collected from different objective environments before and after the energy-saving transformation, calculates the energy consumption and energy-saving rate before and after the transformation under the same objective conditions, so that the energy-saving effect evaluation is based on the measured data, excluding the influence of the objective environment, and only the effect of the energy-saving transformation is included in the energy-saving rate. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings in the specification that constitute a part of this embodiment are used to provide a further understanding of this embodiment. The schematic embodiments of this embodiment and their descriptions are used to explain this embodiment and do not constitute improper limitations on this embodiment.

[0018] Figure 1 This is a temperature trend chart for a certain area in February in the past three years; Figure 2 This is a flow chart of a building energy-saving effect evaluation method based on causal reasoning in Embodiment 1 of the present invention; Figure 3 The cause-effect structure diagram constructed in the first embodiment of the present invention; Figure 4 This is a structural block diagram of a building energy-saving effect evaluation system based on causal reasoning in Embodiment 2 of the present invention. DETAILED DESCRIPTION

[0019] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0020] It should be noted that the following detailed descriptions are exemplary and are intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present application belongs.

[0021] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0022] In the present invention, terms such as "upper", "lower", "left", "right", "front", "back", "vertical", "horizontal", "side", "bottom", etc. indicate directions or positional relationships based on the directions or positional relationships shown in the accompanying drawings. They are relational words determined only for the convenience of describing the structural relationships of the various parts or elements of the present invention, and do not specifically refer to any part or element in the present invention and should not be understood as limitations on the present invention.

[0023] In the present invention, terms such as "fixed connection", "connected", "connection", etc. should be understood in a broad sense, indicating that it can be fixedly connected, integrally connected or detachably connected; it can be directly connected or indirectly connected through an intermediate medium. For relevant scientific research or technical personnel in this field, the specific meanings of the above terms in the present invention can be determined according to specific circumstances, and they cannot be understood as limitations on the present invention.

[0024] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0025] Embodiment 1 Embodiment 1 of the present invention introduces a building energy-saving effect evaluation method based on causal reasoning.

[0026] like Figure 1 As shown, the temperature in a certain area in February 2024 is lower than the same period in history. The lower temperature in winter will generate higher heating load demand and reduce the operating efficiency of the heating equipment system. Assuming that the same non-energy-saving equipment is used in February 2024 as in February 2023, the energy consumption will also be higher; when the energy consumption of energy-saving equipment in February 2024 and the energy consumption of non-energy-saving equipment in February 2023 are used to calculate the energy saving rate, the energy saving effect is underestimated.

[0027] In order to objectively evaluate the energy-saving effect before and after the transformation, this paper introduces a method such as Figure 2 The building energy-saving effect evaluation method based on causal reasoning shown includes: Obtain data information before and after energy-saving transformation; Construct a cause-effect structure diagram based on the acquired data information; According to the constructed causal structure diagram, a joint distribution estimation function based on causal relationship is calculated; According to the obtained joint distribution estimation function based on causal relationship, counterfactual analysis based on causal relationship is carried out, and the counterfactual estimator of power consumption and its mathematical expectation are calculated with the energy-saving model as the intervention variable. According to the obtained counterfactual estimator and its mathematical expectation, the energy saving rate based on causal relationship is calculated, and the building energy-saving effect evaluation based on causal reasoning is completed.

[0028] This embodiment obtains the following data information before and after the energy-saving transformation: (1) Energy-saving model , the energy-saving model before transformation is recorded as , the energy-saving model after transformation is .

[0029] (2) Confounding factors , that is, a high-dimensional vector, is the observation data of objective conditions, including temperature, humidity, radiation, and flow of people.

[0030] (3) Cooling capacity or heating capacity , which can directly measure the cooling or heating capacity per unit time or indirectly measure it through temperature difference and flow rate.

[0031] (4) Power consumption , which can be measured directly or indirectly through current and voltage, is the system power consumption per unit time.

[0032] (5) Time , that is, the time node at which each observation occurs, with common intervals such as 15 minutes, 1 hour, etc.

[0033] It should be noted that confounding factors Usually a high-dimensional vector, it is the observation data of objective environmental conditions, including but not limited to temperature, humidity, radiation, flow of people, etc. These variables affect the cooling / heating demand of the building and the operating efficiency of the cooling and heating equipment. Although the objective environmental conditions in common sense logic are not whether it is an energy-saving device, that is, the model variables However, the different objective environments before and after the energy-saving transformation caused selection bias at the data level, that is, confusion.

[0034] When some objective environmental variables have little difference before and after the transformation, they are ignored and regarded as approximate calculations in this embodiment.

[0035] In actual application scenarios, if there are variables that affect building energy consumption and have objective differences before and after energy-saving renovation, even if they are not listed above, they should be included as confounding variables. , which is regarded as a natural extension in this embodiment.

[0036] In actual application scenarios, if observation conditions are limited, only confounding variables can be collected. Some or even individual factors in the embodiment are regarded as special cases of this embodiment.

[0037] In this embodiment, the following is constructed based on the acquired data information: Figure 3 The causal structure diagram shown, that is, the logical relationship between the power consumption and the confusion factor, the cooling capacity or heating capacity and the energy-saving model, and the logical relationship between the confusion factor and the cooling capacity or heating capacity and the energy-saving model.

[0038] In this embodiment, the joint distribution estimation function based on causality is ;in, is the energy-saving model, and the energy-saving model before transformation is recorded as , the energy-saving model after transformation is ; as confounding factors; is cooling capacity or heating capacity; For power consumption.

[0039] In this embodiment, in the process of counterfactual analysis based on causal relationship, the energy saving model is an intervention variable, then the variable , , The joint distribution of ; ; Energy-saving model is the intervention variable, The counterfactual estimate of ; ; in, For variables , The mathematical expectation of .

[0040] In this embodiment, in the process of causal relationship counterfactual analysis, power consumption The counterfactual estimate of , The mathematical expectation of the distribution is calculated based on the principle of maximizing the use of data, using variables , The sampling distribution of all observations is calculated.

[0041] Variables can be selected in certain cases , The sample distribution of a particular subset of all observations of , for example: (1) The energy saving rate is calculated based on the most recent period of time after the energy-saving transformation (such as one year or one heating / cooling season, etc.). The time period of all observed variables is used. Subset calculation variables that meet time period requirements , The sample distribution of (2) Based on the local If the energy saving rate is calculated based on the average level of the last three years or the last five years, the variable is corrected according to the required objective environmental conditions. , The sample distribution of .

[0042] In this embodiment, the energy saving rate based on the causal relationship is ; in, For variables The mathematical expectation of .

[0043] This embodiment analyzes and calculates the causal relationship between energy-saving renovation and energy consumption from the existing observable data. By using the data observed and collected at different times and under different objective conditions before and after the energy-saving renovation, the objective energy consumption difference under the same objective conditions is calculated. This embodiment eliminates the impact of objective environmental conditions (such as temperature, humidity, etc.) on energy consumption data when calculating the energy saving rate based on historical data of the same period. After the energy-saving renovation of the building is completed, although only the energy consumption of the current energy-saving equipment can be observed, the "counterfactual" energy consumption if the original (non-energy-saving) equipment is still used in the current period can be calculated, thereby obtaining an objective energy saving rate evaluation.

[0044] Embodiment 2 Embodiment 2 of the present invention introduces a building energy-saving effect evaluation system based on causal reasoning.

[0045] like Figure 4 A building energy-saving effect evaluation system based on causal reasoning is shown, comprising: An acquisition module, which is configured to acquire data information before and after energy-saving transformation; A construction module, which is configured to construct a causal structure diagram based on the acquired data information; A calculation module, configured to calculate a joint distribution estimation function based on causal relationships according to the constructed causal structure graph; The evaluation module is configured to perform counterfactual analysis based on causal relationship according to the obtained joint distribution estimation function based on causal relationship, calculate the counterfactual estimator of power consumption and its mathematical expectation with the energy-saving model as the intervention variable, calculate the energy-saving rate based on causal relationship according to the obtained counterfactual estimator and its mathematical expectation, and complete the building energy-saving effect evaluation based on causal reasoning.

[0046] The detailed steps are the same as those of the building energy-saving effect evaluation method based on causal reasoning provided in Example 1, and will not be repeated here.

[0047] Embodiment 3 Embodiment 3 of the present invention provides a computer-readable storage medium.

[0048] A computer-readable storage medium stores a program, which, when executed by a processor, implements the steps of the building energy-saving effect evaluation method based on causal reasoning as described in Embodiment 1 of the present invention.

[0049] The detailed steps are the same as those of the building energy-saving effect evaluation method based on causal reasoning provided in Example 1, and will not be repeated here.

[0050] Embodiment 4 A fourth embodiment of the present invention provides an electronic device.

[0051] An electronic device comprises a memory, a processor and a program stored in the memory and running on the processor. When the processor executes the program, the steps in the building energy-saving effect evaluation method based on causal reasoning as described in Embodiment 1 of the present invention are implemented.

[0052] The detailed steps are the same as those of the building energy-saving effect evaluation method based on causal reasoning provided in Example 1, and will not be repeated here.

[0053] Embodiment 5 Embodiment 5 of the present invention provides a computer program product.

[0054] A computer program product includes software codes, wherein the program in the software codes executes the steps in the building energy-saving effect evaluation method based on causal reasoning as described in the first embodiment of the present invention.

[0055] The detailed steps are the same as those of the building energy-saving effect evaluation method based on causal reasoning provided in Example 1, and will not be repeated here.

[0056] It should be understood by those skilled in the art that the embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes. The schemes in the embodiments of the present invention may be implemented in various computer languages, for example, object-oriented programming languages ​​Python, R, Java, and literal scripting languages ​​JavaScript, etc.

[0057] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0058] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0059] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0060] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0061] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

[0062] The above description is only a preferred embodiment of the present embodiment and is not intended to limit the present embodiment. For those skilled in the art, the present embodiment may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present embodiment shall be included in the protection scope of the present embodiment.

Claims

1. A building energy-saving effect evaluation method based on causal reasoning, characterized in that: include: Obtain data information before and after energy-saving transformation; Construct a cause-effect structure diagram based on the acquired data information; According to the constructed causal structure diagram, a joint distribution estimation function based on causal relationship is calculated; According to the obtained joint distribution estimation function based on causal relationship, counterfactual analysis based on causal relationship is carried out, and the counterfactual estimator of power consumption and its mathematical expectation are calculated with the energy-saving model as the intervention variable. According to the obtained counterfactual estimator and its mathematical expectation, the energy saving rate based on causal relationship is calculated, and the building energy-saving effect evaluation based on causal reasoning is completed.

2. A building energy-saving effect evaluation method based on causal reasoning as claimed in claim 1, characterized in that: The acquired data information before and after the energy-saving transformation at least includes energy-saving model, confounding factors, cooling capacity or heating capacity, power consumption and time.

3. A building energy-saving effect evaluation method based on causal reasoning as claimed in claim 2, characterized in that: The constructed causal structure diagram is the logical relationship between the power consumption and the confounding factor, the cooling capacity or heating capacity and the energy-saving model, and the logical relationship between the confounding factor and the cooling capacity or heating capacity and the energy-saving model.

4. A building energy-saving effect evaluation method based on causal reasoning as claimed in claim 1, characterized in that: The joint distribution estimation function based on causality is: ;in, is the energy-saving model, and the energy-saving model before transformation is recorded as , the energy-saving model after transformation is ; as confounding factors; is cooling capacity or heating capacity; For power consumption.

5. A building energy-saving effect evaluation method based on causal reasoning as claimed in claim 4, characterized in that: In the process of counterfactual analysis based on causality, the energy saving model is an intervention variable, then the variable , , The joint distribution of ； ； Energy-saving model is the intervention variable, The counterfactual estimate of ； ； in, For variables , The mathematical expectation of .

6. A building energy-saving effect evaluation method based on causal reasoning as claimed in claim 5, characterized in that: The energy saving rate based on causal relationship is ； in, For variables The mathematical expectation of .

7. A building energy-saving effect evaluation system based on causal reasoning, characterized in that: include: An acquisition module, which is configured to acquire data information before and after energy-saving transformation; A construction module, which is configured to construct a causal structure diagram based on the acquired data information; A calculation module, configured to calculate a joint distribution estimation function based on a causal relationship according to the constructed causal structure graph; The evaluation module is configured to perform counterfactual analysis based on causal relationship according to the obtained joint distribution estimation function based on causal relationship, calculate the counterfactual estimator of power consumption and its mathematical expectation with the energy-saving model as the intervention variable, calculate the energy-saving rate based on causal relationship according to the obtained counterfactual estimator and its mathematical expectation, and complete the building energy-saving effect evaluation based on causal reasoning.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the building energy-saving effect evaluation method based on causal reasoning as described in any one of claims 1 to 6 are implemented.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the program, the steps of the building energy-saving effect evaluation method based on causal reasoning as described in any one of claims 1 to 6 are implemented.

10. A computer program product comprising software code, characterized in that The program in the software code executes the steps of the building energy-saving effect evaluation method based on causal reasoning as described in any one of claims 1 to 6.

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