Green building outer wall passive energy-saving effect evaluation method and system and medium

Abstract

The invention discloses a green building outer wall passive energy-saving effect evaluation method and system and a medium, and relates to the technical field of energy-saving effect evaluation. The method comprises the following steps: querying an information collector with permission in a building, and establishing a connection channel with the information collector; the information collector comprises an intelligent instrument and a plurality of sensors arranged in a wall body; regularly generating a data acquisition instruction, randomly selecting a target sensor from the plurality of sensors, and acquiring acquisition data of the target sensor based on the connection channel; counting and inserting the collected data into a preset BIM model of a building to obtain a building state; comparing the building state with a preset standard state, and determining standard instrument data; and acquiring actual data acquired by the intelligent instrument, and comparing the standard instrument data with the actual data acquired by the intelligent instrument to generate an energy-saving evaluation result. According to the method, the energy-saving effect is quantified by collecting data in real time through the sensor and comparing the data with the standard state in combination with the BIM model.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of energy-saving effect evaluation, in particular to a green building external wall passive energy-saving effect evaluation method, system and medium. BACKGROUND

[0002] The existing green building external wall material is still in the development stage, and is put into use after the preliminary test, but the preliminary test itself is an advanced test, which is a theoretical test behavior, and the actual energy-saving effect can be determined only in the actual use stage. In the prior art, once the building is put into use, the subsequent use condition is almost not obtained. In fact, the subsequent use condition is very valuable data, how to obtain these data and evaluate the energy-saving effect to optimize the development of green buildings has become a technical problem to be solved. SUMMARY

[0003] In order to overcome the above problems or at least partially solve the above problems, the embodiments of the present application provide a green building external wall passive energy-saving effect evaluation method, system and medium, which quantifies the energy-saving effect by real-time data collection by sensors and comparison with BIM model and standard state, excavates the data value in the building use stage, and optimizes the development of green buildings.

[0004] To solve the above technical problems, the technical scheme adopted by the present application is:

[0005] In a first aspect, the present application provides a green building external wall passive energy-saving effect evaluation method, comprising the following steps:

[0006] In the building, an information collector with authority is queried, and a connection channel with the information collector is established; the information collector includes an intelligent instrument and a plurality of sensors built-in the wall;

[0007] A data acquisition instruction is generated at a regular time, a target sensor is randomly selected from the plurality of sensors, and the collection data of the target sensor is acquired based on the connection channel;

[0008] The collection data is inserted into the pre-set BIM model of the building, and the building state is obtained;

[0009] The building state is compared with the pre-set standard state, and the standard instrument data is determined;

[0010] The actual data collected by the intelligent instrument is obtained, and the standard instrument data is compared with the actual data collected by the intelligent instrument, and the energy-saving evaluation result is generated.

[0011] The method obtains building state data in real time through sensors and intelligent instruments built in the wall, alleviates data transmission pressure by combining with a random sampling mechanism, uses a BIM model to visually present the building state, compares with a preset standard state library to realize quantitative evaluation of energy saving effect, and provides a basis for green building outer wall material optimization and energy saving design based on differences between actual data and standard data.

[0012] Based on the first aspect, further, the timing data acquisition instruction is generated, and the method of randomly selecting a target sensor in the sensor includes the following steps:

[0013] Generate data acquisition instructions at a preset time interval;

[0014] Determine the data upload probability of each sensor every time a data acquisition instruction is generated;

[0015] Determine whether each sensor uploads collected data based on the data upload probability, and when the determination result is upload, the sensor is used as the target sensor.

[0016] Based on the first aspect, further, the method of determining the data upload probability of each sensor every time a data acquisition instruction is generated includes the following steps:

[0017] For any sensor, query the latest data acquisition time of another sensor, and calculate the non-acquisition time interval;

[0018] Calculate the influence degree according to the non-acquisition time interval of another sensor and the correlation degree between another sensor and the current sensor;

[0019] Add the influence degree of all other sensors on the current sensor, and determine the data upload probability of the current sensor according to the influence degree.

[0020] Based on the first aspect, further, the data upload probability formula is In the formula, P is the data upload probability, N is the total number of sensors, S i is the correlation degree between the i-th sensor in other sensors and the current sensor, and T i is the non-acquisition time interval of the i-th sensor in other sensors.

[0021] Based on the first aspect, further, the determination process of S i is as follows: obtain the historical data of the i-th sensor in other sensors, obtain the historical data of the current sensor, calculate the correlation degree of the historical data, and use it as S i .

[0022] Based on the first aspect, further, the method of determining whether each sensor uploads collected data based on the data upload probability includes the following steps:

[0023] generating a random number in a range of zero to one, when the random number belongs to a range of zero to the data uploading probability, determining the result as uploading data; when the random number does not belong to the range of zero to the data uploading probability, determining the result as not uploading data.

[0024] According to the first aspect, further, the method for generating the building state by counting and inserting the collected data into the preset BIM model of the building comprises the following steps:

[0025] obtaining the BIM model of the building;

[0026] counting the collected data, and eliminating invalid data according to the time of the collected data;

[0027] converting the collected data after eliminating the invalid data into color values;

[0028] inserting the color values into the BIM model according to the positions to obtain the building state.

[0029] According to the first aspect, further, the method for determining the standard instrument data by comparing the building state with the preset standard state comprises the following steps:

[0030] reading the preset standard state library; the standard state library comprises state items and instrument data items of different external conditions; the external conditions include temperature, humidity and wind speed;

[0031] comparing the building state with each data of the state items in the standard state library in sequence to calculate the similarity;

[0032] selecting the data with the largest similarity as the matched standard state;

[0033] querying the external conditions of the time corresponding to the building state, and selecting the matched instrument data in the instrument data corresponding to the standard state as the standard instrument data.

[0034] According to the second aspect, the present application provides a passive energy-saving effect evaluation system for the green building outer wall, which comprises a connection channel establishing module, a data collection module, a building state generating module, a state comparing module and an energy-saving calculation module, wherein:

[0035] The connection channel establishing module is used for querying the information collector with the authority in the building, and establishing the connection channel with the information collector; the information collector comprises the intelligent instrument and the plurality of sensors built in the wall;

[0036] The data collection module is used for generating the data acquisition instruction in a regular manner, randomly selecting the target sensor from the plurality of sensors, and acquiring the collected data of the target sensor based on the connection channel;

[0037] The building state generation module is configured to count and insert the collected data into the preset BIM model of the building to obtain the building state.

[0038] The state comparison module is configured to compare the building state with the preset standard state to determine the standard instrument data.

[0039] The energy-saving score calculation module is configured to obtain the actual data collected by the intelligent instrument, compare the standard instrument data with the actual data collected by the intelligent instrument, and generate an energy-saving evaluation result.

[0040] The system can obtain the building state data in real time through the connection channel establishment module, the data collection module, the building state generation module, the state comparison module, and the energy-saving score calculation module, and can relieve the data transmission pressure by combining the random sampling mechanism; the building state can be visually presented by using the BIM model, the quantitative evaluation of the energy-saving effect can be realized by comparing with the preset standard state library, and the basis for the optimization of the green building outer wall material and the energy-saving design can be provided based on the difference between the actual data and the standard data.

[0041] In a third aspect, the embodiments of the present application provide a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the method of any one of the above first aspect.

[0042] The embodiments of the present application have at least the following advantages or beneficial effects:

[0043] 1. Data collection innovation: the building state data can be obtained in real time through the sensors and intelligent instruments built in the wall, and the data transmission pressure can be relieved by combining the random sampling mechanism (data uploading probability model).

[0044] 2. Evaluation method innovation: the building state can be visually presented by using the BIM model, the standard instrument data can be matched by combining the external conditions (temperature, humidity, etc.) by comparing with the preset standard state library, and the quantitative evaluation of the energy-saving effect can be realized.

[0045] 3. Dynamic optimization: the basis for the optimization of the green building outer wall material and the energy-saving design can be provided based on the difference between the actual data and the standard data. BRIEF DESCRIPTION OF DRAWINGS

[0046] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiments. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as a limitation on the scope, and other related drawings can also be obtained by those skilled in the art without creative labor on the premise of not paying.

[0047] Figure 1A flow chart of a whole process of a green building outer wall passive energy-saving effect evaluation method according to an embodiment of the present application;

[0048] Figure 2 A flow chart of determining a target sensor in a green building outer wall passive energy-saving effect evaluation method according to an embodiment of the present application;

[0049] Figure 3 A flow chart of obtaining a building state in a green building outer wall passive energy-saving effect evaluation method according to an embodiment of the present application;

[0050] Figure 4 A flow chart of obtaining standard instrument data in a green building outer wall passive energy-saving effect evaluation method according to an embodiment of the present application;

[0051] Figure 5 A principle block diagram of a green building outer wall passive energy-saving effect evaluation system according to an embodiment of the present application.

[0052] Icon: 11, connection channel establishment module; 12, data acquisition module; 13, building state generation module; 14, state comparison module; 15, energy-saving calculation module. DETAILED DESCRIPTION

[0053] In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described below in connection with the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. The components of the embodiments of the present application described and shown in the drawings can be arranged and designed in various different configurations.

[0054] Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor are within the scope of protection of the present application.

[0055] It should be noted that: similar reference numerals and letters represent similar items in the following drawings, therefore, once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings.

[0056] It should be noted that, in the present document, relational terms such as first and second and the like can be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises", "comprising", or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element proceeded by "comprises... a" does not, without more constraints, exclude the presence of additional identical elements in the process, method, article, or apparatus that comprises the element.

[0057] In the description of the embodiments of the present application, "a plurality of" represents at least 2.

[0058] In the description of the embodiments of the present application, it should be further noted that, unless explicitly defined and limited otherwise, if the terms "set", "mounted", "connected", "linked" and "connected" appear, they should be understood in a broad sense, for example, they can be fixedly connected, or detachably connected, or integrally connected, or mechanically connected, or electrically connected, or directly connected, or indirectly connected through an intermediate medium, or the communication inside two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0059] Embodiments

[0060] As shown in the first aspect, the embodiments of the present application provide a green building outer wall passive energy-saving effect evaluation method, comprising the following steps: Figure 1

[0061] S100, querying an information collector with authority in the building, establishing a connection channel with the information collector; the information collector comprises a smart meter and a plurality of sensors built-in the wall;

[0062] S200, generating data acquisition instructions at regular intervals, randomly selecting a target sensor in the plurality of sensors, and acquiring the collection data of the target sensor based on the connection channel; the data acquisition instructions are generated at regular intervals, a target sensor is randomly selected through a data uploading probability model (based on sensor correlation and unacquired time length), and collection data with time and position are acquired.

[0063] S300, statistics and inserting the collection data into the preset BIM model of the building, obtaining the building state;

[0064] S400, comparing the building state with the preset standard state, and determining the standard instrument data; ​

[0065] S500, acquiring actual data collected by the smart meter, and comparing the standard meter data with the actual data collected by the smart meter to generate an energy-saving evaluation result. The energy-saving score is determined by comparing the standard meter data with the actual data collected by the smart meter, and is used as the evaluation result.

[0066] The method acquires building state data in real time through sensors and smart meters built in the wall, alleviates data transmission pressure by using a random sampling mechanism, visualizes the building state by using a BIM model, compares the building state with a preset standard state library to realize quantitative evaluation of the energy-saving effect, and provides a basis for optimization of green building outer wall materials and energy-saving design based on differences between actual data and standard data.

[0067] Based on the first aspect, further, Figure 2 As shown in the above method of randomly selecting a target sensor in the sensor each time the data acquisition instruction is generated, the method comprises the following steps:

[0068] S201, generating a data acquisition instruction at a preset time interval;

[0069] S202, determining a data upload probability of each sensor each time the data acquisition instruction is generated;

[0070] Further, the method of determining the data upload probability of each sensor each time the data acquisition instruction is generated comprises the following steps:

[0071] For any sensor, the latest data acquisition time of another sensor is queried, and the non-acquisition time interval is calculated; the influence degree is calculated according to the non-acquisition time interval of another sensor and the correlation degree between another sensor and the current sensor; the influence degrees of all other sensors on the current sensor are accumulated, and the data upload probability of the current sensor is determined according to the influence degrees.

[0072] Further, the data upload probability formula is In the formula, P is the data upload probability, N is the total number of sensors, S i is the correlation degree between the i-th sensor in the other sensors and the current sensor, and T i is the non-acquisition time interval of the i-th sensor in the other sensors.

[0073] Further, the determination process of S i is as follows: the historical data of the i-th sensor in the other sensors is acquired, the historical data of the current sensor is acquired, the correlation degree of the historical data is calculated, and the correlation degree is taken as S i .

[0074] Further, the method of determining whether each sensor uploads the collected data based on the data upload probability comprises the following steps:

[0075] generating a random number in a range of zero to one, when the random number belongs to a range of zero to the data uploading probability, determining the result as uploading data; when the random number does not belong to the range of zero to the data uploading probability, determining the result as not uploading data.

[0076] S203, determining whether each sensor uploads the collected data based on the data uploading probability,

[0077] S204, when the determination result is uploading, taking the sensor as a target sensor; obtaining the collected data containing time and position of the target sensor based on the connection channel; the time is a collection time, and the position is a position of the target sensor.

[0078] In some embodiments of the present application, the data acquisition instruction is generated in a timing manner, the target sensor is randomly selected through a data uploading probability model (based on sensor correlation and non-acquisition duration), and the collected data containing time and position is obtained.

[0079] Based on the first aspect, further, Figure 3 As shown in the figure, the above-mentioned method for obtaining the building state by statistically inserting the collected data into the preset BIM model of the building comprises the following steps:

[0080] S301, obtaining the BIM model of the building;

[0081] S302, statistically obtaining the collected data, and eliminating invalid data according to the time of the collected data;

[0082] S303, converting the collected data after the invalid data is eliminated into a color value; the color value adopts a three-channel color value;

[0083] S304, inserting the color value into the BIM model according to the position to obtain the building state.

[0084] In some embodiments of the present application, after the invalid data is eliminated, the collected data is converted into a three-channel color value, and is inserted into the BIM model to generate a visualized “building state”.

[0085] Based on the first aspect, further, Figure 4 As shown in the figure, the above-mentioned method for obtaining the building state by statistically inserting the collected data into the preset BIM model of the building comprises the following steps:

[0086] S401, reading a preset standard state library; the standard state library comprises state items and instrument data items under different external conditions; the external conditions include temperature, humidity and wind speed;

[0087] S402, comparing the building state with each data of the state items in the standard state library in sequence to calculate the similarity;

[0088] S403, select the data with the largest similarity as the matched standard state;

[0089] S404, query the external condition of the building state corresponding time, select the matched instrument data in the standard state corresponding instrument data as the standard instrument data.

[0090] In some embodiments of the present application, the building state is compared with the standard state library (containing instrument data under different external conditions), the standard state with the highest similarity is matched, and the corresponding standard instrument data is extracted.

[0091] As shown in Figure 5 The second aspect, the embodiment of the present application provides a kind of green building outer wall passive energy-saving effect evaluation system, including connection channel establishment module 11, data acquisition module 12, building state generation module 13, state comparison module 14 and energy-saving fraction calculation module 15, wherein:

[0092] Connection channel establishment module 11 is used to query information collector with authority in building, establishes connection channel with information collector;The information collector includes intelligent instrument and multiple sensors built-in wall;

[0093] Data acquisition module 12 is used to generate data acquisition instruction in time, randomly selects target sensor in multiple sensors, and obtains the acquisition data of target sensor based on connection channel;

[0094] Building state generation module 13 is used to insert acquisition data into the BIM model of pre-set building and obtain building state;

[0095] State comparison module 14 is used to compare building state with pre-set standard state, and determine standard instrument data;

[0096] Energy-saving fraction calculation module 15 is used to obtain actual data collected by intelligent instrument, compare standard instrument data with actual data collected by intelligent instrument, and generate energy-saving evaluation result.

[0097] Further, in another embodiment of the present application, the above-mentioned data acquisition module 12 includes: instruction generation unit, used to generate data acquisition instruction according to pre-set time length;Frequency determination unit, used to determine the data upload probability of each sensor every time data acquisition instruction is generated;Upload determination unit, used to determine whether each sensor uploads acquisition data based on the data upload probability;Acquisition execution unit, used to take the sensor as target sensor when the determination result is upload, and obtain the acquisition data of target sensor containing time and position based on connection channel;The time is acquisition time, and the position is the position of target sensor.

[0098] Further, in some embodiments of the present application, the building state generation module 13 comprises: a BIM model acquisition unit, configured to acquire a BIM model of the building; an invalid data elimination unit, configured to count the acquired collection data and eliminate invalid data according to the time of the collection data; a data conversion unit, configured to convert the collection data after elimination of invalid data into color values; the color values adopt three-channel color values; the color values are inserted into the BIM model according to positions to obtain the building state.

[0099] The system, through cooperation of the connection channel establishment module 11, the data acquisition module 12, the building state generation module 13, the state comparison module 14 and the energy-saving calculation module 15 and other modules, acquires building state data in real time through sensors and intelligent meters of the built-in wall, alleviates data transmission pressure in combination with a random sampling mechanism; utilizes the BIM model to visually present the building state, compares with a preset standard state library, realizes quantitative evaluation of the energy-saving effect; and provides a basis for optimization of green building outer wall materials and energy-saving design based on differences between actual data and standard data.

[0100] In a third aspect, an embodiment of the present application provides a computer readable storage medium, which stores a computer program. The computer program is executed by a processor to implement the method of any one of the above first aspect. The functions can be stored in a computer readable storage medium if the functions are implemented in the form of software function modules and sold or used as independent products. Based on this understanding, the technical solutions of the present application essentially or the parts that make contributions to the prior art or parts of the technical solutions can be embodied in the form of software products. The computer software product is stored in a storage medium and includes a plurality of instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in the embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0101] In a fourth aspect, an embodiment of the present application provides an electronic device, which includes a memory for storing one or more programs; and a processor. When the one or more programs are executed by the processor, the method of any one of the above first aspect is implemented.

[0102] The memory, the processor and the communication interface are electrically connected with each other directly or indirectly to realize the transmission or interaction of data. For example, the elements can be electrically connected with each other through one or more communication buses or signal lines. The memory can be used to store software programs and modules, and the processor can execute various function applications and data processing by executing the software programs and modules stored in the memory. The communication interface can be used for signaling or data communication with other node devices.

[0103] The memory can be, but is not limited to, a random access memory (RAM), a read only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM) and the like.

[0104] The processor can be an integrated circuit chip with signal processing capability. The processor can be a general purpose processor, including a central processing unit (CPU), a network processor (NP) and the like; or can be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component.

[0105] In the embodiments of the present disclosure, it should be understood that the disclosed methods and systems and methods can also be implemented in other manners. The above described method and system embodiments are merely exemplary but are not intended to limit the present disclosure. For example, the flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation modes of the methods and systems, methods and computer program products according to the embodiments of the present disclosure. In this regard, each block in the flowcharts or block diagrams can represent a module, a program segment or a part of code, which includes one or more executable instructions for implementing the specified logic function. It should also be noted that in some alternative implementation modes, the functions noted in the blocks can occur in different orders from those noted in the accompanying drawings. For example, two consecutive blocks can actually be executed substantially in parallel, and sometimes they can be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and the combination of blocks in the block diagrams and / or flowcharts, can be implemented by a dedicated hardware-based system that performs the specified functions or actions, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0106] In addition, the various functional modules in the embodiments of the present disclosure can be integrated together to form a separate part, or each module can exist independently, or two or more modules can be integrated to form a separate part.

[0107] The above merely provides preferred embodiments of the present disclosure but should not be used to limit the present disclosure. For those skilled in the art, the present disclosure can have various modifications and changes. Any modified, equivalent replaced, improved, etc. within the spirit and principles of the present disclosure shall be included in the protection scope of the present disclosure.

[0108] It is obvious for those skilled in the art that the present disclosure is not limited to the details of the above exemplary embodiments, and the present disclosure can be implemented in other specific forms without departing from the spirit or essential characteristics of the present disclosure. Therefore, the embodiments should be considered as exemplary and non-limiting, and the scope of the present disclosure is defined by the appended claims rather than the above description, and all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be included in the present disclosure. Any reference signs in the claims should not be considered as limiting the involved claims.

Claims

1. A method for evaluating passive energy-saving effect of a green building outer wall, characterized in that, The method comprises the following steps: In the building, an information collector with authority is queried, and a connection channel with the information collector is established; the information collector comprises intelligent meters and a plurality of sensors built into a wall; Data acquisition instructions are generated at regular time intervals, a target sensor is randomly selected from the plurality of sensors, and the collected data of the target sensor is acquired based on the connection channel; The collected data is counted and inserted into a preset BIM model of the building, and a building state is obtained; The building state is compared with a preset standard state, and standard meter data is determined; Actual data collected by the intelligent meters is acquired, the standard meter data is compared with the actual data collected by the intelligent meters, and an energy-saving evaluation result is generated.

2. The method according to claim 1, wherein, The method of randomly selecting a target sensor from the sensors based on the data acquisition instructions generated at regular time intervals comprises the following steps: Data acquisition instructions are generated at regular time intervals according to a preset time length; The data upload probability of each sensor is determined each time a data acquisition instruction is generated; Based on the data upload probability, it is determined whether each sensor uploads the collected data, and when the determination result is upload, the sensor is taken as the target sensor.

3. The method according to claim 2, wherein, The method of determining the data upload probability of each sensor each time a data acquisition instruction is generated comprises the following steps: For any sensor, the latest data acquisition time of another sensor is queried, and the non-acquisition time length is calculated; The influence degree is calculated according to the non-acquisition time length of the other sensor and the correlation degree between the other sensor and the current sensor; The influence degrees of all other sensors on the current sensor are accumulated, and the data upload probability of the current sensor is determined according to the influence degrees.

4. The method according to claim 3, wherein, The data uploading probability formula is In the formula, P is the data uploading probability, N is the total number of sensors, S i is the correlation degree of the i th sensor in other sensors and the current sensor, T i is the unacquired time length of the i th sensor in other sensors.

5. The method for evaluating passive energy-saving effect of a green building outer wall according to claim 4, characterized in that, The S i The determination process is: obtaining the historical data of the i-th sensor in other sensors, obtaining the historical data of the current sensor, calculating the correlation degree of the historical data as S i .

6. The method for evaluating passive energy-saving effect of a green building outer wall according to claim 2, characterized in that, The method of determining whether each sensor uploads the collected data based on the data upload probability comprises the following steps: A random number in the range of zero to one is generated, when the random number belongs to the range of zero to the data upload probability, the determination result is to upload data; when the random number does not belong to the range of zero to the data upload probability, the determination result is not to upload data.

7. The method for evaluating passive energy-saving effect of a green building outer wall according to claim 1, characterized in that, The method of counting and inserting the collected data into the preset BIM model of the building to obtain the building state comprises the following steps: The BIM model of the building is acquired; The acquired collected data is counted, and invalid data is removed according to the time of the collected data; The collected data after the invalid data is removed is converted into a color value; The color value is inserted into the BIM model according to the position, and the building state is obtained. 8.The method of claim 1, wherein, The method of comparing the building state with the preset standard state to determine the standard meter data comprises the following steps: A preset standard state library is read; the standard state library comprises state items and meter data items of different external conditions; the external conditions include temperature, humidity and wind speed; The building state is compared with each item of data of the state items in the standard state library in sequence, and the similarity is calculated; The data with the largest similarity is selected as the matched standard state; The external conditions of the time corresponding to the building state are queried, the matched meter data in the meter data corresponding to the standard state is selected as the standard meter data.

9. A green building outer wall passive energy saving effect evaluation system, characterized in that, The method comprises a connection channel establishment module, a data acquisition module, a building state generation module, a state comparison module and an energy-saving calculation module, wherein: The connection channel establishment module is configured to query an information collector with authority in the building and establish a connection channel with the information collector; the information collector includes a smart meter and a plurality of sensors built in a wall; The data collection module is configured to generate a data acquisition instruction at a regular time, randomly select a target sensor from the plurality of sensors, and acquire collected data of the target sensor based on the connection channel; The building state generation module is configured to count and insert the collected data into a preset BIM model of the building to obtain a building state; The state comparison module is configured to compare the building state with a preset standard state to determine standard meter data; The energy-saving calculation module is configured to acquire actual data collected by the smart meter, compare the standard meter data with the actual data collected by the smart meter, and generate an energy-saving evaluation result.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the method in any one of claims 1-8.

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