Low-carbon building energy carbon statistical index management method and device and cloud platform

Abstract

The invention discloses a low-carbon building energy carbon statistical index management method and device and a cloud platform, and the method is applied to the cloud platform, and comprises the steps: determining a building energy consumption intensity index constraint value corresponding to a target building according to a thermotechnical partition of a region where the target building is located, and the function type and ventilation mode of the target building; energy-carbon data of the target building are obtained, and energy-carbon statistical indexes of the target building are determined according to the energy-carbon data; and determining overall evaluation grade information and optimization suggestions of the target building according to the energy-carbon statistical index and the building energy consumption intensity index constraint value. According to the technical scheme disclosed by the invention, the energy-carbon statistical indexes of the building operation stage are automatically determined through the cloud platform, so that the energy-carbon statistical indexes of the building are obtained efficiently, accurately and scientifically at low cost, and the overall evaluation grade information and optimization suggestions are determined, so that more comprehensive information is provided, and the user experience is improved. Therefore, a clear management and control scheme can be provided for building managers, and different building environments and requirements can be flexibly adapted.

Description

Technical Field

[0001] The present application relates to the field of low-carbon building technology, and in particular to a method, device and cloud platform for managing energy and carbon statistical indicators of low-carbon buildings. Background Art

[0002] In today's world, global climate change and environmental degradation are becoming increasingly serious. Therefore, developing a low-carbon economy and achieving sustainable development have gradually become a broad consensus of the international community. Among many fields, the construction industry is one of the main sources of energy consumption and carbon emissions. Its low-carbon transformation plays an indispensable role in achieving the ambitious goal of global carbon reduction.

[0003] At present, there are still many challenges in the management and control of building energy and carbon statistical indicators within the construction industry. Generally, relevant personnel conduct personalized measurements of buildings on site, specifically measuring relevant parameters such as building physical materials, building structure, ventilation, and equipment used in buildings. Then, the measured relevant parameters are calculated to obtain indicators such as carbon emissions. However, this method is not only arduous and inefficient in statistical work, but also may result in incomplete or unreliable data collection, resulting in errors. At the same time, the above method can only obtain indicators such as carbon emissions and cannot provide more information.

[0004] In summary, how to efficiently and accurately obtain building energy carbon indicators and provide more comprehensive information is a technical problem that needs to be urgently solved by technical personnel in this field. Summary of the invention

[0005] In view of this, the purpose of this application is to provide a low-carbon building energy carbon statistical indicator management method, device and cloud platform for efficiently and accurately obtaining building energy carbon indicators and providing more comprehensive information.

[0006] In order to achieve the above objectives, this application provides the following technical solutions:

[0007] A low-carbon building energy carbon statistical index management method is applied to a cloud platform, comprising: determining the thermal zoning of the area where a target building is located, the functional type and ventilation mode of the target building, and determining the building energy consumption intensity index constraint value corresponding to the target building according to the thermal zoning of the area where the target building is located, the functional type and ventilation mode of the target building; acquiring the energy carbon data of the target building, and determining the energy carbon statistical index of the target building according to the energy carbon data of the target building; and determining the overall evaluation grade information and optimization suggestions of the target building according to the energy carbon statistical index of the target building and the building energy consumption intensity index constraint value corresponding to the target building.

[0008] Optionally, the energy-carbon statistical indicators of the target building are determined according to the energy-carbon data of the target building, including: determining the energy consumption indicators and carbon emission indicators of the target building according to the energy-carbon data of the target building; wherein the energy consumption indicators include energy consumption indicators per unit area and renewable energy power substitution rate indicators, and the carbon emission indicators include carbon emission indicators per unit area, renewable energy emission reduction rate indicators and carbon emission offset rate indicators.

[0009] Optionally, the overall evaluation grade information of the target building is determined according to the energy-carbon statistical index of the target building and the constraint value of the building energy consumption intensity index corresponding to the target building, including: determining the ratio of the target building's unit area energy consumption reduction compared with the benchmark according to the unit area energy consumption index and the constraint value of the building energy consumption intensity index corresponding to the target building; determining the overall evaluation grade information of the target building according to the ratio of the unit area energy consumption reduction compared with the benchmark, the renewable energy power substitution rate index and the renewable energy emission reduction rate index.

[0010] Optionally, determining the overall evaluation grade information of the target building according to the benchmark reduction ratio of the energy consumption per unit area, the renewable energy power substitution rate index, and the renewable energy emission reduction rate index includes: determining the overall evaluation grade of the target building according to the benchmark reduction ratio of the energy consumption per unit area, the renewable energy power substitution rate index, the renewable energy emission reduction rate index, and a pre-established first corresponding relationship;

[0011] Among them, the first corresponding relationship is the corresponding relationship between the benchmark reduction ratio of energy consumption per unit area, the renewable energy power substitution rate index, the renewable energy emission reduction rate index and the overall evaluation level, and the overall evaluation levels include: no rating, bronze, gold and platinum; the benchmark reduction ratio of energy consumption per unit area < the first preset value, the renewable energy power substitution rate index < the second preset value, the renewable energy emission reduction rate index < the third preset value, the overall evaluation level is no rating; the first preset value ≤ the benchmark reduction ratio of energy consumption per unit area < the fourth preset value, the second preset value ≤ the renewable energy power substitution rate index < the fifth preset value, the third preset value ≤ the renewable energy emission reduction rate index < the sixth preset value, the overall evaluation level is bronze ; The fourth preset value ≤ the ratio of energy consumption per unit area to the benchmark reduction < the seventh preset value, the fifth preset value ≤ renewable energy power substitution rate index < the eighth preset value, the sixth preset value ≤ renewable energy emission reduction rate index < the ninth preset value, and the overall evaluation level is silver; the seventh preset value ≤ the ratio of energy consumption per unit area to the benchmark reduction < the tenth preset value, the eighth preset value ≤ renewable energy power substitution rate index < the eleventh preset value, the ninth preset value ≤ renewable energy emission reduction rate index < the twelfth preset value, and the overall evaluation level is gold; the tenth preset value ≤ the ratio of energy consumption per unit area to the benchmark reduction, the eleventh preset value ≤ renewable energy power substitution rate index, the twelfth preset value ≤ renewable energy emission reduction rate index, and the overall evaluation level is platinum.

[0012] Optionally, the overall evaluation grade of the target building is determined according to the ratio of the reduction in energy consumption per unit area, the renewable energy power substitution rate index, the renewable energy emission reduction rate index and a pre-established first corresponding relationship, including: when the ratio of the reduction in energy consumption per unit area, the renewable energy power substitution rate index and the renewable energy emission reduction rate index are determined according to the first corresponding relationship to correspond to the same overall evaluation grade, the overall evaluation grade is determined as the overall evaluation grade of the target building; when the ratio of the reduction in energy consumption per unit area, the renewable energy power substitution rate index and the renewable energy emission reduction rate index are determined according to the first corresponding relationship to not correspond to the same overall evaluation grade, the lower overall evaluation grade among the overall evaluation grades corresponding to the ratio of the reduction in energy consumption per unit area, the renewable energy power substitution rate index and the renewable energy emission reduction rate index respectively is determined as the overall evaluation grade of the target building.

[0013] Optionally, determining the optimization suggestion for the target building according to the energy-carbon statistical index of the target building and the constraint value of the building energy consumption intensity index corresponding to the target building includes: determining the energy consumption reduction ratio per unit area according to the energy consumption index per unit area and the constraint value of the building energy consumption intensity index; determining the optimization suggestion information according to the energy consumption reduction ratio per unit area, the renewable energy power substitution rate index, the carbon emission index per unit area, the renewable energy emission reduction rate index, the carbon emission offset rate index and a pre-established second corresponding relationship; wherein the second corresponding relationship is the corresponding relationship between the optimization suggestion triggering conditions corresponding to the energy consumption reduction ratio per unit area, the renewable energy power substitution rate index, the carbon emission index per unit area, the renewable energy emission reduction rate index and the carbon emission offset rate index and the corresponding optimization suggestion information, and the optimization suggestion information includes a title prompt and description details;

[0014] The optimization suggestion triggering condition corresponding to the energy consumption reduction ratio per unit area is: the energy consumption reduction ratio per unit area is less than the thirteenth preset value; the title prompt in the corresponding optimization suggestion information is: the energy consumption per unit area is high; the description details in the corresponding optimization suggestion information are: there may be a waste of electricity, and the electrical equipment can be upgraded to energy-saving equipment or an intelligent control system can be added;

[0015] The optimization suggestion triggering condition corresponding to the renewable energy power substitution rate indicator is: the renewable energy power substitution rate is less than the fourteenth preset value; the title prompt in the corresponding optimization suggestion information is: the renewable energy power substitution rate is low; the description details in the corresponding optimization suggestion information are: it is recommended to install renewable energy equipment to provide more renewable energy for the building, improve the utilization rate of renewable energy, and reduce the energy consumption of building operation;

[0016] The optimization suggestion triggering condition corresponding to the renewable energy emission reduction rate indicator is: the renewable energy emission reduction rate is equal to 0; the title prompt in the corresponding optimization suggestion information is: the renewable energy emission reduction rate is low; the description details in the corresponding optimization suggestion information are: it is recommended to install renewable energy equipment to provide more renewable energy for the building, improve the utilization rate of renewable energy, or implement emission reduction projects to increase emission reduction and reduce carbon emissions;

[0017] The optimization suggestion triggering condition corresponding to the carbon emission offset rate indicator is: the carbon emission offset rate is equal to 0; the title prompt in the corresponding optimization suggestion information is: the carbon emission trading offset rate is low; the description details in the corresponding optimization suggestion information are: you can consider purchasing carbon indicators to offset the actual carbon emissions that can no longer be reduced, so as to achieve the goal of carbon neutrality;

[0018] The optimization suggestion triggering conditions corresponding to the carbon emission per unit area index are: any one of the carbon emission per unit area index in winter and the carbon emission per unit area index in summer is higher than any one of the carbon emission per unit area index in spring and the carbon emission per unit area index in autumn by fifteen preset values; the title prompt in the corresponding optimization suggestion information is: seasonal carbon emission per unit area fluctuates too much; the description details in the corresponding optimization suggestion information are: it is recommended to carry out insulation renovation of the building's exterior walls and roof to reduce energy loss, adjust the indoor temperature settings according to seasonal changes, and optimize the operation of the heating and cooling systems.

[0019] Optionally, before determining the energy-carbon statistical index of the target building according to the energy-carbon data of the target building, the method further includes: preprocessing the energy-carbon data of the target building.

[0020] Optionally, obtaining the energy carbon data of the target building includes: periodically obtaining the energy carbon data of the target building.

[0021] A low-carbon building energy carbon statistical index management device, applied to a cloud platform, comprises: a first determination module, used to determine the thermal zoning of the area where a target building is located, the functional type and ventilation mode of the target building, and determine the building energy consumption intensity index constraint value corresponding to the target building according to the thermal zoning of the area where the target building is located, the functional type and ventilation mode of the target building; a second determination module, used to obtain the energy carbon data of the target building, and determine the energy carbon statistical index of the target building according to the energy carbon data of the target building; a third determination module, used to determine the overall evaluation grade information and optimization suggestions of the target building according to the energy carbon statistical index of the target building and the building energy consumption intensity index constraint value corresponding to the target building.

[0022] A cloud platform comprises: a memory for storing a computer program; and a processor for implementing the steps of the low-carbon building energy and carbon statistical indicator management method as described in any one of the above items when executing the computer program.

[0023] The present application provides a method, device and cloud platform for managing energy carbon statistical indicators of low-carbon buildings, wherein the method is applied to the cloud platform, including: determining the thermal zoning of the area where the target building is located, the functional type and ventilation method of the target building, and determining the building energy consumption intensity indicator constraint value corresponding to the target building according to the thermal zoning of the area where the target building is located, the functional type and ventilation method of the target building; obtaining the energy carbon data of the target building, and determining the energy carbon statistical indicators of the target building according to the energy carbon data of the target building; determining the overall evaluation grade information and optimization suggestions of the target building according to the energy carbon statistical indicators of the target building and the building energy consumption intensity indicator constraint value corresponding to the target building.

[0024] In the above technical solution disclosed in the present application, the cloud platform determines the thermal zoning of the area where the target building is located, the functional type and ventilation method of the target building, and determines the building energy intensity index constraint value corresponding to the target building based on this information. In addition, the cloud platform also automatically obtains the energy carbon data of the target building, and automatically determines the energy carbon statistical indicators of the target building based on the energy carbon data of the target building. Then, the overall evaluation grade information and optimization suggestions of the target building are determined based on the determined energy carbon statistical indicators and the building energy intensity index constraint values, so as to realize the conversion of the collected data into operational evaluation indicators, thereby providing building managers with clear management goals and decision-making basis, and helping building managers to formulate and implement specific management and control plans according to actual conditions, thereby effectively improving the energy efficiency of buildings and reducing carbon emissions. It can be seen that this application not only automatically determines the energy and carbon statistical indicators of the building operation stage through the cloud platform to achieve efficient, accurate, low-cost and scientific acquisition of building energy and carbon statistical indicators, but also determines the overall evaluation level information and optimization suggestions of the target building to provide more comprehensive information, thereby providing building managers with clear management and control plans to improve the energy efficiency of buildings and reduce carbon emissions, and can flexibly adapt to different building environments and needs, providing the construction industry with an efficient and customizable energy and carbon management plan.

[0025] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 A flowchart of a low-carbon building energy and carbon statistical index management method provided in an embodiment of the present application;

[0027] Figure 2 A corresponding relationship diagram of thermal zones, building function types and building energy intensity index constraint values ​​under Class A natural ventilation when gas-based heating for severe cold weather / regional centralized heating is provided in the embodiment of the present application;

[0028] Figure 3 A corresponding relationship diagram of thermal zoning, building function type and building energy intensity index constraint value under Class B mechanical ventilation when gas-based heating in severe cold weather / regional centralized heating is provided in the embodiment of the present application;

[0029] Figure 4 A flowchart of another low-carbon building energy and carbon statistical index management method provided in an embodiment of the present application;

[0030] Figure 5 A schematic diagram of a page for entering information when managing energy and carbon statistical indicators provided in an embodiment of the present application;

[0031] Figure 6A schematic diagram of a page displaying energy and carbon statistical indicators and optimization suggestions for a target building provided in an embodiment of the present application;

[0032] Figure 7 A schematic diagram of the structure of a low-carbon building energy and carbon statistical index management device provided in an embodiment of the present application;

[0033] Figure 8 A schematic diagram of the structure of a cloud platform provided in an embodiment of the present application. DETAILED DESCRIPTION

[0034] In today's world, global climate change and environmental degradation are becoming increasingly serious. Therefore, developing a low-carbon economy and achieving sustainable development have gradually become a broad consensus of the international community. Among many fields, the construction industry is one of the main sources of energy consumption and carbon emissions. Its low-carbon transformation plays an indispensable role in achieving the ambitious goal of global carbon reduction.

[0035] At present, there are still many challenges in the management and control of building energy carbon statistical indicators within the construction industry. The current management method of building energy carbon statistical indicators is that relevant personnel conduct personalized measurements of buildings on site, and then calculate the characteristics of the measured related parameters to obtain indicators such as carbon emissions. On the one hand, the current statistical indicator system is complicated, involving data from multiple dimensions including building materials, structures, equipment, etc., which not only makes the statistical work arduous, but also prone to errors; on the other hand, the current method is too simple, lacks the necessary pertinence and effectiveness, and is difficult to meet the actual needs of low-carbon building development.

[0036] In addition, although a series of tools (such as LEED and BREEAM) have been widely adopted in the field of energy efficiency assessment in the construction industry, which provide standards and methods for building energy efficiency assessment, these tools are effective in the design and construction stages of buildings and cannot achieve energy and carbon management in the operation stage of buildings, which leads to a significant gap in the control of energy and carbon statistics such as energy efficiency and carbon emissions during the life cycle of buildings. Although the existing building management system plays an important role in monitoring the internal environment and energy use of buildings, its functions are often limited to data collection and display, and it fails to establish a comprehensive data evaluation system. This means that although the building management system can provide data, it lacks in-depth analysis and effective application of energy and carbon data, and thus cannot provide data-based decision support for building managers. In addition, there are some carbon footprint calculation tools on the market that are designed to help estimate the carbon emissions of buildings. However, these tools usually require users to manually input a large amount of data, and the accuracy of the calculation results depends largely on the quality of the input data. Therefore, these tools have certain limitations in practical applications, especially when the data entered by users is incomplete or unreliable.

[0037] To this end, the present application provides a low-carbon building energy carbon statistical indicator management method, device and cloud platform for efficiently and accurately obtaining building energy carbon indicators and providing more comprehensive information.

[0038] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0039] See also Figure 1 , which shows a flow chart of a low-carbon building energy carbon statistical index management method provided by an embodiment of the present application. A low-carbon building energy carbon statistical index management method provided by an embodiment of the present application is applied to a cloud platform and may include:

[0040] S11: Determine the thermal zoning of the area where the target building is located, the functional type and ventilation method of the target building, and determine the building energy intensity index constraint value corresponding to the target building based on the thermal zoning of the area where the target building is located, the functional type and ventilation method of the target building.

[0041] The low-carbon building energy carbon statistical index management method provided in the embodiment of the present application can be applied to a cloud platform, and the cloud platform is used to automatically manage the building energy carbon statistical index. It should be noted that the low-carbon building mentioned in the embodiment of the present application refers to a building that can generate energy by itself, or use very few external resources, while reducing pollution to the environment, such as using solar panels to generate electricity, or designing the house to be naturally versatile and reduce the use of air conditioning. In addition, the target building mentioned in the embodiment of the present application is specifically a low-carbon building that needs to be managed for energy carbon statistical indicators.

[0042] When managing low-carbon building energy and carbon statistical indicators, the cloud platform can first determine the thermal zoning of the target building. This step includes detailed confirmation of the administrative divisions of the area where the building is located to obtain the specific geographical location of the target building, including cities, counties, streets and other geographical locations and longitude and latitude coordinates, so as to determine the thermal zoning of the target building based on the specific geographical location of the target building. Among them, thermal zoning is usually based on factors such as climate conditions and geographical location, which has an important impact on the energy consumption and carbon emission characteristics of the building. The design of thermal zoning is adapted to the regional climate, including severe cold areas, cold areas, hot summer and cold winter areas, hot summer and warm winter areas and mild areas. According to the thermal zoning, the energy consumption and carbon emission baseline value or standard of the building can be determined (that is, the constraint value of the building energy consumption intensity index), and the building energy consumption and carbon emission indicators within the regional scope can be compared. It should be noted that, specifically, relevant personnel can enter at least one of the area where the target building is located, the geographical location of the target building, and the thermal zone of the area where the target building is located on the cloud platform or on a terminal device (after entering through the terminal device, the information can be sent to the cloud platform by the terminal device through the Internet of Things communication method), so that the cloud platform can determine the thermal zone of the area where the target building is located based on the entered information.

[0043] In addition, the cloud platform can also determine the functional type of the target building, for example: the functional type of the building can be a government office building, an office building, a shopping mall building, a hotel building, a cultural and educational building, a medical and health building or other buildings, wherein the functional type of the target building can be specifically entered into the cloud platform by relevant personnel, or entered into a terminal device, and sent to the cloud platform by the terminal device. By determining the functional type of the target building, it is convenient to determine the project type category for comparing its energy consumption and carbon emission indicators according to the specific function of the target building. Among them, different types of buildings have different energy consumption and carbon emission characteristics, so it is necessary to design statistical indicators in a targeted manner. Specific refinements include functional classification, energy consumption characteristic analysis, carbon emission characteristic analysis, setting statistical indicators and comparing project type categories. Through these steps, the embodiment of the present application can more accurately determine the functional type of the target building.

[0044] In addition, the cloud platform can also determine the ventilation mode of the target building. This information can be entered into the cloud platform by relevant personnel, or can be entered into the terminal device and sent to the cloud platform by the terminal device. Of course, the cloud platform can also obtain the model of the target building and determine it based on the model of the target building. Among them, the ventilation mode of the building can be divided into two categories: Class A natural ventilation, which is suitable for buildings that can use natural wind to adjust the indoor temperature by opening windows, thereby reducing the use of air conditioning and reducing energy consumption; Class B mechanical ventilation, which is suitable for buildings that cannot rely on natural ventilation due to functional, scale or environmental limitations, and need to rely on mechanical ventilation and air conditioning systems to maintain a comfortable indoor environment. By distinguishing ventilation modes, a basis is provided for the subsequent energy-carbon statistical indicator control to achieve effective management of building energy efficiency and carbon emissions.

[0045] After determining the thermal zoning of the target building, the functional type of the target building, and the ventilation method, the cloud platform can determine the building energy intensity index constraint value corresponding to the target building by looking up the table, etc. For example, the cloud platform can query Figure 2 and Figure 3 Determine the building energy intensity index constraint value corresponding to the target building, where: Figure 2 This is a corresponding relationship diagram of thermal zoning, building function type and building energy intensity index constraint value under Class A natural ventilation when gas-based heating in severe cold weather / regional centralized heating provided in the embodiment of the present application, Figure 3 This is a corresponding relationship diagram of thermal zoning, building function type and building energy intensity index constraint value under Class B mechanical ventilation when gas-based heating in severe cold weather / regional centralized heating provided in the embodiment of this application. Figure 2 and Figure 3 It can be seen that in order to improve the accuracy of determining the constraint value of the building energy intensity index corresponding to the target building, the cloud platform can also obtain the heating method of the target building when determining the thermal zoning of the area where the target building is located, the functional type of the target building and the ventilation method, and determine the constraint value of the building energy intensity index corresponding to the target building according to the thermal zoning of the area where the target building is located, the functional type of the target building, the ventilation method and the heating method.

[0046] S12: Obtain energy carbon data of the target building, and determine energy carbon statistical indicators of the target building according to the energy carbon data of the target building.

[0047] In addition, during the operation phase of the target building, the sensors, monitoring equipment and other data collection equipment on the target building side can comprehensively collect the energy carbon data of the target building, where the energy carbon data mentioned here covers data on energy consumption, carbon emissions and other aspects. After collecting the energy carbon data of the target building, the data collection equipment on the target building side can transmit the collected energy carbon data of the target building to the cloud platform through the Internet of Things communication method. Then, the cloud platform can determine the energy carbon statistical indicators of the target building based on the acquired energy carbon data of the target building (energy carbon statistical indicators specifically include energy consumption indicators and carbon emission indicators).

[0048] This process can realize automatic collection, acquisition and processing of the target building's energy and carbon data, automatic determination of the target building's energy and carbon statistical indicators, reduce dependence on user input, improve data accuracy and reliability, and thus enhance the practicality and accuracy of the low-carbon building statistical indicator management solution provided in the embodiment of the present application during the building operation stage.

[0049] It should be noted that there is no restriction on the execution order between step S11 and step S12.

[0050] See also Figure 4 , which shows a flow chart of another low-carbon building energy carbon statistical index management method provided by an embodiment of the present application. In one embodiment, determining the energy carbon statistical index of a target building according to the energy carbon data of the target building may include: determining the energy consumption index and carbon emission index of the target building according to the energy carbon data of the target building; wherein the energy consumption index may include an energy consumption index per unit area and a renewable energy power substitution rate index, and the carbon emission index may include a carbon emission index per unit area, a renewable energy emission reduction rate index, and a carbon emission offset rate index.

[0051] In an embodiment of the present application, determining the energy-carbon statistical indicators of the target building based on the energy-carbon data of the target building can specifically include determining the energy consumption indicators and carbon emission indicators of the target building based on the energy-carbon data of the target building, wherein the energy consumption indicators of the target building can specifically include two key energy consumption indicators, namely, the energy consumption indicator per unit area and the renewable energy substitution rate indicator; and the carbon emission indicators of the target building can include three key carbon emission indicators, namely, the carbon emission indicator per unit area, the renewable energy emission reduction rate indicator and the carbon emission offset rate indicator.

[0052] Specifically, the energy consumption per unit area index = annual comprehensive total energy consumption / area of ​​the target building. For the annual comprehensive total energy consumption, if the natural year is one full year, the total energy consumption of the target building in the current year is used as the annual comprehensive total energy consumption; if the natural year is less than one year, the formula: annual comprehensive total energy consumption = (actual cumulative comprehensive energy consumption of the target building in the current year / number of days that have passed in the current year) * 365 is used to convert the comprehensive estimated total energy consumption and use it as the annual comprehensive total energy consumption, where the number of days that have passed in the current year can include the current day. This calculation rule ensures that the energy consumption per unit area index can more accurately reflect the energy consumption level of the target building within a year, providing a quantitative basis for building energy efficiency evaluation.

[0053] Renewable energy power substitution rate index = (renewable energy power generation discounted energy consumption / target building's current annual cumulative comprehensive energy consumption value) * 100%, thus obtaining the proportion of renewable energy power in total energy consumption. Taking photovoltaic power generation as an example, the renewable energy power substitution rate index = (photovoltaic power generation discounted energy consumption / target building's current annual cumulative comprehensive energy consumption value) * 100%, where photovoltaic power generation discounted value = photovoltaic power generation * electricity discounted coefficient (specifically 0.1229kgce / kwh). This calculation rule enables the renewable energy power substitution rate index to intuitively reflect the target building's performance in the use of renewable energy and the degree of reduction in the target building's dependence on traditional energy, thereby providing important reference data for the sustainable development of the construction industry.

[0054] Carbon emission index per unit area = annual comprehensive total carbon emission / area of ​​target building. For annual comprehensive total carbon emission, if the natural year is one year, the total carbon emission of the target building in the current year will be taken as the annual comprehensive total carbon emission; if the natural year is less than one year, the formula: annual comprehensive total carbon emission = (the actual accumulated total carbon emission of the current building in the current year / the number of days that have passed in the current year) * 365 is used to convert the comprehensive total carbon emission and use it as the annual comprehensive total carbon emission, where the number of days that have passed in the current year mentioned above can include the current day. This calculation rule ensures that the carbon emission index per unit area can more accurately reflect the carbon emission level of the target building within a year, and provides a quantitative basis for the assessment of the building's carbon footprint. It should be noted that the above-mentioned carbon emission index per unit area is actually the calculated annual carbon emission index per unit area. Of course, the quarterly carbon emission index per unit area can also be calculated (the specific calculation process is similar to the calculation process of the annual carbon emission index per unit area, except that the quarterly carbon emission index per unit area uses the quarterly comprehensive total carbon emission), so that relevant personnel can not only know the annual carbon emission index per unit area, but also the quarterly carbon emission index per unit area.

[0055] Renewable energy emission reduction rate index = [current annual renewable energy emission reduction / (current annual actual cumulative carbon emissions + current annual renewable energy emission reduction)] * 100%, to obtain the reduction ratio of renewable energy to carbon emissions. This calculation formula enables the renewable energy emission reduction rate index to intuitively reflect the performance of the target building in renewable energy and the degree of reduction of the target building's dependence on traditional energy, thereby providing important reference data for the sustainable development of the construction industry. Among them, the current annual renewable energy emission reduction = renewable energy power generation carbon emission reduction + ground source heat pump emission reduction + solar water heating emission reduction. Specifically, renewable energy power generation carbon emission reduction (tCO2) = renewable energy power generation (kWh) * regional power grid emission factor, where the regional power emission factor can be obtained by looking up the table, as shown in Table 1, which shows a schematic table of regional power grid emission factors; ground source heat pump emission reduction (tCO2) = ground source heat pump corresponding hot water supply (tons) * carbon emission factor (for example, it can be 0.0153); solar water heating emission reduction (tCO2) = solar corresponding hot water supply (tons) * carbon emission factor (for example, it can be 0.0153). Taking photovoltaic power generation as an example of renewable energy generation, the current annual renewable energy emission reduction = photovoltaic power generation carbon emission reduction + ground source heat pump emission reduction + solar water heating emission reduction, photovoltaic power generation carbon emission reduction (tCO2) = photovoltaic power generation (kWh) * regional power grid emission factor.

[0056] Table 1 Schematic table of regional power grid emission factors

[0057]

[0058]

[0059] Carbon emission offset rate index = (the current year's cumulative carbon emission offset / the current year's cumulative carbon emissions) * 100%, thus obtaining the proportion of carbon emission offset measures in the total carbon emissions. This calculation formula enables the carbon emission offset rate index to intuitively reflect the amount of carbon emissions reduced by the target building through offset measures, thus providing important reference data for the sustainable development of the construction industry.

[0060] After calculating the target building's energy consumption per unit area, renewable energy power substitution rate, carbon emission per unit area, renewable energy emission reduction rate and carbon emission offset rate, these indicators can be displayed on the cloud platform page, or the calculated indicators can be sent to the target building or the building manager's terminal device through the Internet of Things communication method, so that relevant personnel can obtain these indicators.

[0061] For example, please refer to Figure 5 and Figure 6 ,in, Figure 5A schematic diagram of a page for entering information during energy and carbon statistical index management provided in an embodiment of the present application is shown. Figure 6 A schematic diagram of a page display of energy and carbon statistical indicators and optimization suggestions for a target building provided in an embodiment of the present application is shown.

[0062] It should be noted that in the calculation of the above five energy-carbon statistical indicators, except for the carbon emission offset amount accumulated in the current year which can be entered by relevant personnel, the remaining input amounts can be collected by the data collection equipment on the target building side and sent to the cloud platform to participate in the calculation of the energy-carbon statistical indicators.

[0063] The energy carbon statistical index of the target building can be accurately calculated through the above method, so as to improve the accuracy of the management of the energy carbon statistical index of the target building. Moreover, through the above process, the embodiment of the present application establishes a comprehensive and scientific statistical index system according to the characteristics and needs of the building, and specifically establishes a statistical system including multiple key energy carbon indicators, which can comprehensively reflect the energy carbon status of the building during the operation stage.

[0064] S13: Determine the overall evaluation grade information and optimization suggestions of the target building according to the energy carbon statistical indicators of the target building and the building energy intensity indicator constraint value corresponding to the target building.

[0065] After determining the building energy intensity index constraint value corresponding to the target building based on step S11 and determining the energy carbon statistical index of the target building based on step S12, the overall evaluation grade information and optimization suggestions of the target building can be determined according to the energy carbon statistical index of the target building and the building energy intensity index constraint value corresponding to the target building, so as to build a scientific evaluation index system, convert the collected data into operational evaluation indicators, thereby providing clear management goals and decision-making basis for building managers, and providing suggestions through evaluation results to help building managers formulate and implement specific control plans according to optimization suggestions and actual conditions. The evaluation mechanism of the embodiment of the present application can flexibly adapt to different building environments and needs, and provide an efficient and customizable energy carbon management tool for the construction industry.

[0066] In one embodiment, the overall evaluation grade information of the target building is determined based on the energy-carbon statistical indicators of the target building and the constraint value of the building energy consumption intensity indicator corresponding to the target building, which can include: determining the ratio of the target building's unit area energy consumption reduction compared with the benchmark based on the unit area energy consumption indicator and the constraint value of the building energy consumption intensity indicator corresponding to the target building; determining the overall evaluation grade information of the target building based on the ratio of the unit area energy consumption reduction compared with the benchmark, the renewable energy power substitution rate indicator and the renewable energy emission reduction rate indicator.

[0067] In an embodiment of the present application, when determining the overall evaluation grade information of the target building based on the energy carbon statistical indicators of the target building and the building energy consumption intensity indicator constraint value corresponding to the target building, first, based on the unit area energy consumption indicator and the building energy consumption intensity indicator constraint value corresponding to the target building, the following method can be used: the ratio of unit area energy consumption reduction compared with the benchmark = [(unit area energy consumption - building energy consumption intensity indicator constraint value) / building energy consumption intensity indicator constraint value] * 100% to obtain the ratio of unit area energy consumption reduction compared with the benchmark. This calculation rule enables building managers to intuitively understand the degree of reduction in energy consumption of the target building relative to the standard value, thereby providing a quantitative basis for energy carbon management.

[0068] On the basis of the above, the overall evaluation grade information of the target building can be determined according to the three indicators of the reduction ratio of energy consumption per unit area, the renewable energy power substitution rate index and the renewable energy emission reduction rate index, so as to quantify the overall evaluation grade of the target building by using these three indicators, so that relevant personnel can obtain the overall evaluation grade information of the target building, so as to provide building managers with clear management goals and decision-making basis.

[0069] In one embodiment, determining the overall evaluation grade information of the target building according to the benchmark reduction ratio of energy consumption per unit area, the renewable energy power substitution rate index, and the renewable energy emission reduction rate index may include: determining the overall evaluation grade of the target building according to the benchmark reduction ratio of energy consumption per unit area, the renewable energy power substitution rate index, the renewable energy emission reduction rate index, and a pre-established first corresponding relationship;

[0070] The first correspondence is the correspondence between the ratio of energy consumption per unit area to benchmark reduction, renewable energy power substitution rate index, renewable energy emission reduction rate index and the overall evaluation level. The overall evaluation levels include: no rating, bronze, gold and platinum;

[0071] The first corresponding relationship can be specifically:

[0072] If the ratio of energy consumption per unit area to benchmark reduction is less than the first preset value, the renewable energy power substitution rate index is less than the second preset value, and the renewable energy emission reduction rate index is less than the third preset value, the overall evaluation level is no rating;

[0073] The first preset value ≤ the ratio of energy consumption per unit area to benchmark reduction < the fourth preset value, the second preset value ≤ the renewable energy power substitution rate index < the fifth preset value, the third preset value ≤ the renewable energy emission reduction rate index < the sixth preset value, and the overall evaluation level is bronze;

[0074] The fourth preset value ≤ the ratio of energy consumption per unit area to benchmark reduction < the seventh preset value, the fifth preset value ≤ the renewable energy power substitution rate index < the eighth preset value, the sixth preset value ≤ the renewable energy emission reduction rate index < the ninth preset value, and the overall evaluation level is silver;

[0075] The seventh preset value ≤ the ratio of energy consumption per unit area to benchmark reduction < the tenth preset value, the eighth preset value ≤ the renewable energy power substitution rate index < the eleventh preset value, the ninth preset value ≤ the renewable energy emission reduction rate index < the twelfth preset value, the overall evaluation level is gold;

[0076] The tenth preset value is ≤ the ratio of energy consumption per unit area to the benchmark reduction, the eleventh preset value is ≤ the renewable energy power substitution rate index, and the twelfth preset value is ≤ the renewable energy emission reduction rate index. The overall evaluation level is platinum.

[0077] In an embodiment of the present application, a first corresponding relationship can be established in advance, and the first corresponding relationship is the corresponding relationship between the ratio of energy consumption per unit area to benchmark reduction, renewable energy power substitution rate index, renewable energy emission reduction rate index and overall evaluation level. Specifically, the ratio of energy consumption per unit area to benchmark reduction, renewable energy power substitution rate index, and renewable energy emission reduction rate index can be divided into different numerical ranges, and the corresponding relationship between the numerical ranges of these three indicators and the overall evaluation level can be constructed. The sizes of the first preset value to the twelfth preset value mentioned above can be set by relevant personnel according to needs or experience, among which, the larger the numerical range of these three indicators, the higher the overall evaluation level, indicating that the low-carbon effect of the target building is better. Among them, the overall evaluation level can be divided into five levels: no rating (0 star), bronze (1 star), silver (2 stars), gold (3 stars) and platinum (4 stars), and these five levels increase in sequence, and the first preset value mentioned above can be 0%, the second preset value can be 2%, the third preset value can be 1%, the fourth preset value can be 20%, the fifth preset value can be 4%, the sixth preset value can be 3%, the seventh preset value can be 25%, the eighth preset value can be 8%, the ninth preset value can be 6%, the tenth preset value can be 30%, the eleventh preset value can be 15%, and the twelfth preset value can be 10%, which can be specifically shown in Table 2, which shows a first corresponding relationship schematic table:

[0078] Table 2 Schematic diagram of the first correspondence

[0079]

[0080] Through the above method, a low-carbon building energy efficiency overall evaluation index system is constructed, so as to determine the overall evaluation level of the target building based on the low-carbon building energy efficiency overall evaluation index system and realize the overall evaluation of the target building.

[0081] On the above basis, the overall evaluation grade information of the target building can be determined according to the calculated reduction ratio of the target building's unit area energy consumption, the renewable energy power substitution rate index, the renewable energy emission reduction rate index and the pre-established first corresponding relationship, so as to quantify the overall evaluation grade of the target building based on the target building's unit area energy consumption reduction ratio, the renewable energy power substitution rate index and the renewable energy emission reduction rate index, thereby realizing the conversion of the collected data into operational evaluation indicators, thereby providing building managers with clear management goals and decision-making basis.

[0082] In one embodiment, determining the overall evaluation level of the target building based on the ratio of unit area energy consumption reduction, the renewable energy power substitution rate index, the renewable energy emission reduction rate index and a pre-established first correspondence may include: when it is determined according to the first correspondence that the ratio of unit area energy consumption reduction, the renewable energy power substitution rate index and the renewable energy emission reduction rate index correspond to the same overall evaluation level, then determining the overall evaluation level as the overall evaluation level of the target building; when it is determined according to the first correspondence that the ratio of unit area energy consumption reduction, the renewable energy power substitution rate index and the renewable energy emission reduction rate index do not correspond to the same overall evaluation level, then determining the lower overall evaluation level among the overall evaluation levels corresponding to the ratio of unit area energy consumption reduction, the renewable energy power substitution rate index and the renewable energy emission reduction rate index respectively as the overall evaluation level of the target building.

[0083] In the embodiment of the present application, in order to ensure the objectivity and accuracy of the evaluation system, an overall evaluation grade of the target building is determined only when the three indicators of the target building's unit area energy consumption reduction ratio, renewable energy power substitution rate index and renewable energy emission reduction rate index are met at the same time. If the overall evaluation grades determined by the three indicators are inconsistent, the one with the lower overall evaluation grade is used as the low-carbon grade of the target building. This evaluation system aims to encourage the construction industry to achieve better results in energy carbon management and provides building managers with a clear reference framework to guide building managers towards higher energy carbon efficiency and sustainability goals.

[0084] Specifically, if it is determined according to the pre-established first correspondence that the target building's unit area energy consumption reduction ratio, renewable energy power substitution rate index, and renewable energy emission reduction rate index correspond to the same overall evaluation level, then the overall evaluation level is determined as the target building's overall evaluation level. If it is determined according to the pre-established first correspondence that the target building's unit area energy consumption reduction ratio, renewable energy power substitution rate index, and renewable energy emission reduction rate index do not correspond to the same overall evaluation level, then the lower overall evaluation level among the overall evaluation levels corresponding to the target building's unit area energy consumption reduction ratio, renewable energy power substitution rate index, and renewable energy emission reduction rate index is determined as the target building's overall evaluation level.

[0085] Exemplarily, the target building's energy consumption per unit area is reduced by 24% (determined as silver level), the renewable energy power substitution rate is 5% (determined as silver level), and the renewable energy emission reduction rate index is 2% (determined as bronze level). These three indicators determine different overall evaluation levels, and bronze is the lowest overall evaluation level among them. In this case, bronze can be determined as the overall evaluation level of the target building.

[0086] The above method can ensure the objectivity and accuracy of the overall evaluation level of the target building, so that building managers can improve the energy efficiency of the target building and reduce carbon emissions.

[0087] In one embodiment, determining the optimization suggestion for the target building according to the energy-carbon statistical index of the target building and the constraint value of the building energy consumption intensity index corresponding to the target building may include: determining the energy consumption reduction ratio per unit area according to the energy consumption index per unit area and the constraint value of the building energy consumption intensity index; determining the optimization suggestion information according to the energy consumption reduction ratio per unit area, the renewable energy power substitution rate index, the carbon emission index per unit area, the renewable energy emission reduction rate index, the carbon emission offset rate index and the pre-established second corresponding relationship;

[0088] The second correspondence is the correspondence between the optimization suggestion trigger conditions corresponding to the energy consumption reduction ratio per unit area, renewable energy power substitution rate index, unit area carbon emission index, renewable energy emission reduction rate index and carbon emission offset rate index and the corresponding optimization suggestion information, and the optimization suggestion information includes title prompts and description details;

[0089] The second corresponding relationship may specifically be:

[0090] The optimization suggestion triggering condition corresponding to the energy consumption reduction ratio per unit area is: the energy consumption reduction ratio per unit area is less than the thirteenth preset value; the title prompt in the corresponding optimization suggestion information is: the energy consumption per unit area is high; the description details in the corresponding optimization suggestion information are: there may be a waste of electricity, and the electrical equipment can be upgraded to energy-saving equipment or an intelligent control system can be added;

[0091] The optimization suggestion triggering condition corresponding to the renewable energy power substitution rate indicator is: the renewable energy power substitution rate is less than the fourteenth preset value; the title prompt in the corresponding optimization suggestion information is: the renewable energy power substitution rate is low; the description details in the corresponding optimization suggestion information are: it is recommended to install renewable energy equipment to provide more renewable energy for the building, improve the utilization rate of renewable energy, and reduce the energy consumption of building operation;

[0092] The optimization suggestion triggering condition corresponding to the renewable energy emission reduction rate indicator is: the renewable energy emission reduction rate is equal to 0; the title prompt in the corresponding optimization suggestion information is: the renewable energy emission reduction rate is low; the description details in the corresponding optimization suggestion information are: it is recommended to install renewable energy equipment to provide more renewable energy for the building, improve the utilization rate of renewable energy, or implement emission reduction projects to increase emission reduction and reduce carbon emissions;

[0093] The optimization suggestion triggering condition corresponding to the carbon emission offset rate indicator is: the carbon emission offset rate is equal to 0; the title prompt in the corresponding optimization suggestion information is: the carbon emission trading offset rate is low; the description details in the corresponding optimization suggestion information are: you can consider purchasing carbon indicators to offset the actual carbon emissions that can no longer be reduced, so as to achieve the goal of carbon neutrality;

[0094] The optimization suggestion triggering conditions corresponding to the carbon emission per unit area index are: any one of the carbon emission per unit area index in winter and the carbon emission per unit area index in summer is higher than any one of the carbon emission per unit area index in spring and the carbon emission per unit area index in autumn by fifteen preset values; the title prompt in the corresponding optimization suggestion information is: seasonal carbon emission per unit area fluctuates too much; the description details in the corresponding optimization suggestion information can be: it is recommended to carry out insulation renovation of the building's exterior walls and roof to reduce energy loss, adjust the indoor temperature settings according to seasonal changes, and optimize the operation of the heating and cooling systems.

[0095] In an embodiment of the present application, a second corresponding relationship can be established in advance, and the second corresponding relationship is the correspondence between the optimization suggestion trigger conditions corresponding to the unit area energy consumption reduction ratio (wherein, the unit area energy consumption reduction ratio = [(building energy consumption intensity index constraint value - unit area energy consumption index) / building energy consumption intensity index constraint value] * 100%), the renewable energy power substitution rate index, the unit area carbon emission index, the renewable energy emission reduction rate index and the carbon emission offset rate index and the corresponding optimization suggestion information, wherein the above five indicators can respectively correspond to an optimization suggestion trigger condition, and the optimization suggestion trigger condition and the optimization suggestion information correspond one-to-one, and the optimization suggestion information can include description details and title prompts (specifically, prompts for problems existing in the corresponding indicators), so that relevant personnel can not only obtain the optimization suggestion details, but also know what problems currently exist in the target building.

[0096] Specifically, the optimization suggestion trigger condition corresponding to the energy consumption reduction ratio per unit area may be: the energy consumption reduction ratio per unit area is less than the thirteenth preset value, wherein the thirteenth preset value may be 0. The title prompt in the corresponding optimization suggestion information may be: the energy consumption per unit area is relatively high. The description details in the corresponding optimization suggestion information may be: there may be a waste of electricity, and the electrical equipment may be upgraded to energy-saving equipment or an intelligent control system may be added. Specifically, the description details may be: there may be a waste of electricity in HVAC equipment, lighting equipment, etc., and it may be considered to upgrade the HVAC and lighting equipment to energy-saving equipment or add an intelligent control system.

[0097] The optimization suggestion triggering condition corresponding to the renewable energy power substitution rate indicator may be: the renewable energy power substitution rate is less than the fourteenth preset value, wherein the fourteenth preset value may be 2%. The title prompt in the corresponding optimization suggestion information may be: the renewable energy power substitution rate is low. The description details in the corresponding optimization suggestion information may be: it is recommended to install renewable energy equipment to provide more renewable energy for the building, improve the utilization rate of renewable energy, and reduce the energy consumption of building operation. Specifically, the description details may be: it is recommended to provide more renewable energy for the building by installing photovoltaic power generation facilities, photovoltaic heating facilities, heat pumps and other equipment, improve the utilization rate of renewable energy, and reduce the energy consumption of building operation.

[0098] The optimization suggestion trigger condition corresponding to the renewable energy emission reduction rate indicator may be: the renewable energy emission reduction rate is equal to 0. The title prompt in the corresponding optimization suggestion information may be: the renewable energy emission reduction rate is low. The description details in the corresponding optimization suggestion information may be: it is recommended to install renewable energy equipment to provide more renewable energy for buildings, improve the utilization rate of renewable energy, or implement emission reduction projects to increase emission reduction and reduce carbon emissions. Specifically, the description details may be: it is recommended to install more photovoltaic power generation facilities, photovoltaic heating facilities, heat pumps and other equipment to provide more renewable energy for buildings, improve the utilization rate of renewable energy, or implement other feasible energy-saving and other emission reduction projects to increase emission reduction, reduce carbon emissions, and gradually reduce the cost of achieving carbon neutrality in the later stage.

[0099] The optimization suggestion trigger condition corresponding to the carbon emission offset rate indicator may be: the carbon emission offset rate is equal to 0. The title prompt in the corresponding optimization suggestion information may be: the carbon emission trading offset rate is low. The description details in the corresponding optimization suggestion information may be: you may consider purchasing carbon indicators to offset the actual carbon emissions that cannot be reduced any further, so as to achieve the goal of carbon neutrality.

[0100] For the carbon emission index per unit area, the quarterly carbon emission index per unit area can be used to participate in the establishment of the second corresponding relationship and the determination of the optimization suggestion information. Specifically, the optimization suggestion triggering condition corresponding to the carbon emission index per unit area can be: any one of the carbon emission index per unit area in winter and the carbon emission index per unit area in summer is higher than any one of the carbon emission index per unit area in spring and the carbon emission index per unit area in autumn by the fifteenth preset value, wherein the fifteenth preset value can be 30%. The title prompt in the corresponding optimization suggestion information can be: Seasonal carbon emission per unit area fluctuates too much. The description details in the corresponding optimization suggestion information can be: It is recommended to carry out insulation renovation of the exterior walls and roofs of the building to reduce energy loss, and adjust the indoor temperature settings according to seasonal changes to optimize the operation of the heating and cooling systems.

[0101] Specifically, see Table 3, which shows the correspondence between the optimization suggestion triggering conditions and the optimization suggestion information:

[0102] Table 3. Correspondence between optimization suggestion trigger conditions and optimization suggestion information

[0103]

[0104] On the basis of the above, when determining the optimization suggestion of the target building according to the energy-carbon statistical index of the target building and the constraint value of the building energy intensity index corresponding to the target building, the energy consumption per unit area of ​​the target building can be determined according to the energy consumption per unit area of ​​the target building and the constraint value of the building energy intensity index corresponding to the target building, using: energy consumption per unit area reduction ratio = [(building energy intensity index constraint value - energy consumption per unit area) / building energy intensity index constraint value] * 100%. Then, the optimization suggestion information can be determined according to the energy consumption per unit area reduction ratio of the target building, the renewable energy power substitution rate index, the carbon emission per unit area index, the renewable energy emission reduction rate index, the carbon emission offset rate index and the pre-established second corresponding relationship, and the optimization suggestion information can be displayed or output.

[0105] The above steps are based on the above data analysis and evaluation results, and put forward specific optimization measures and suggestions for the energy-carbon performance and potential improvement points of the target building. Among them, the optimization suggestions can guide building managers to take practical measures to improve the energy efficiency of buildings and reduce carbon emissions.

[0106] Through the above process, a comprehensive energy carbon statistical indicator system for the building operation stage can be provided to ensure that energy carbon can be effectively monitored and managed during the building operation process. That is, through the above process, the embodiment of the present application provides the construction industry with a more comprehensive, scientific and systematic low-carbon building operation stage energy carbon statistical indicator control method and logic, thereby effectively improving the energy efficiency of buildings and reducing carbon emissions, and promoting the construction industry to develop in a low-carbon and sustainable direction. The above determination of the energy carbon statistical indicators of the target building based on the energy carbon data of the target building is like giving the target building a "physical examination". By measuring how much energy the target building consumes during use, such as electricity, water, gas, etc., and how much carbon dioxide is generated during these energy consumption processes, these indicators are like the "health report" of the target building, telling us the energy efficiency and environmental impact of the building. With the "health report", some methods are needed to improve the "health status" of the building. The control method is like a series of "fitness plans" and "dietary recommendations", telling us how to reduce energy consumption and carbon emissions by improving building design, using energy-saving materials, and optimizing energy use. The above logic refers to a set of principles or steps that need to be followed when implementing management and control methods. For example, first determine the current energy consumption status of the building, then set goals to reduce energy consumption and carbon emissions, then select appropriate energy-saving technologies and measures, and finally implement and monitor the results to ensure that the goals are achieved.

[0107] As can be seen from the above, the embodiment of the present application provides a basic framework for subsequent data collection and analysis by confirming thermal zoning, determining building function types and ventilation methods. Then, through data collection and preparation, establishing energy carbon statistical indicators and constructing a statistical indicator system, the energy carbon status of the building can be fully reflected. The low-carbon building energy carbon statistical indicator management method provided by the embodiment of the present application can realize efficient and accurate energy carbon data collection and statistics, formulate a unified energy carbon statistical standard, and facilitate data comparison and integration between different buildings and regions.

[0108] In the technical solution provided by the embodiment of the present application, the cloud platform determines the thermal zoning of the area where the target building is located, the functional type and ventilation method of the target building, and determines the building energy intensity index constraint value corresponding to the target building based on this information. In addition, the cloud platform also automatically obtains the energy carbon data of the target building, and automatically determines the energy carbon statistical indicators of the target building based on the energy carbon data of the target building. Then, the overall evaluation grade information and optimization suggestions of the target building are determined based on the determined energy carbon statistical indicators and the building energy intensity index constraint values, so as to realize the conversion of the collected data into operational evaluation indicators, thereby providing building managers with clear management goals and decision-making basis, and helping building managers to formulate and implement specific management and control plans according to actual conditions, thereby effectively improving the energy efficiency of buildings and reducing carbon emissions. It can be seen that the embodiment of the present application not only automatically determines the energy and carbon statistical indicators of the building operation stage through the cloud platform to achieve efficient, accurate, low-cost and scientific acquisition of building energy and carbon statistical indicators, but also determines the overall evaluation level information and optimization suggestions of the target building to provide more comprehensive information, thereby providing building managers with clear management and control plans to improve the energy efficiency of buildings and reduce carbon emissions, and can flexibly adapt to different building environments and needs, providing the construction industry with an efficient and customizable energy and carbon management plan.

[0109] A low-carbon building energy carbon statistical index management method provided in an embodiment of the present application may further include, before determining the energy carbon statistical index of a target building according to the energy carbon data of the target building:

[0110] Preprocess the energy and carbon data of the target building.

[0111] In an embodiment of the present application, after obtaining the energy carbon data of the target building and before determining the energy carbon statistical indicators of the target building based on the energy carbon data of the target building, the cloud platform may pre-process the acquired energy carbon data of the target building. Specifically, the pre-processing may include steps such as cleaning and formatting, so that the energy carbon data of the target building undergoes careful pre-processing, thereby ensuring the accuracy and reliability of the energy carbon data of the target building, so as to improve the accuracy of the calculation of the energy carbon statistical indicators of the target building, thereby facilitating the accurate determination of the overall evaluation grade information and optimization suggestions of the target building.

[0112] The above process not only ensures the quality of the data, but also lays a solid foundation for subsequent data analysis and management strategy formulation.

[0113] The embodiment of the present application provides a low-carbon building energy carbon statistical index management method, which obtains the energy carbon data of the target building and may include:

[0114] Obtain energy and carbon data of target buildings regularly.

[0115] In the embodiment of the present application, the cloud platform can specifically obtain the energy carbon data of the target building on a regular basis (the timing can be obtained by relevant personnel based on the target building and / or experience, etc.) to achieve regular and dynamic determination of the target building's energy carbon statistical indicators, overall evaluation level information and optimization suggestions, thereby achieving continuous attention and optimization of the target building's energy carbon management, that is, continuous improvement can be achieved through the aforementioned process, specifically including adjustments to the energy carbon statistical indicator system and optimization of control measures to better reflect the actual situation of the building and industry best practices. This step can further achieve real-time monitoring and dynamic analysis of building energy carbon use, while enhancing users' awareness of low-carbon buildings, thereby facilitating the enhancement of their participation and driving force, and contributing to the green transformation of the construction industry.

[0116] By regularly collecting new data, updating the statistical indicator system and control measures, we can ensure that the building's energy and carbon management is always kept at the latest and most effective level. Through continuous improvement, we can adapt to changes in the building environment, technological advances, and updates to industry standards.

[0117] From the above, it can be seen that when managing the energy-carbon statistical indicators of low-carbon buildings, the thermal zoning, building function type and ventilation method are first confirmed to provide a basic framework for subsequent data collection and analysis. Then, through data collection and preparation, the establishment of energy consumption indicators and carbon emission indicators, and the construction of a statistical indicator system, this application can comprehensively reflect the energy-carbon status of the building. Data processing and analysis, formulation of management and control strategies (i.e. formulation of optimization suggestions), implementation of management and control measures (specifically, it can be implemented by building managers based on the optimization suggestions for the target buildings determined), monitoring and evaluation, and continuous improvement steps ensure the effectiveness and sustainability of management and control measures, thereby achieving the goal of low-carbon buildings.

[0118] This application also provides a low-carbon building energy carbon statistical index management device, which is applied to the cloud platform. Figure 7 , which shows a structural schematic diagram of a low-carbon building energy and carbon statistical index management device provided in an embodiment of the present application, which may include:

[0119] The first determination module 71 is used to determine the thermal zone of the area where the target building is located, the functional type and ventilation mode of the target building, and determine the building energy intensity index constraint value corresponding to the target building according to the thermal zone of the area where the target building is located, the functional type and ventilation mode of the target building;

[0120] The second determination module 72 is used to obtain the energy carbon data of the target building and determine the energy carbon statistical index of the target building according to the energy carbon data of the target building;

[0121] The third determination module 73 is used to determine the overall evaluation level information and optimization suggestions of the target building according to the energy carbon statistical index of the target building and the building energy intensity index constraint value corresponding to the target building.

[0122] In a low-carbon building energy and carbon statistical index management device provided in an embodiment of the present application, the second determination module 72 may include:

[0123] The first determination submodule is used to determine the energy consumption index and carbon emission index of the target building according to the energy and carbon data of the target building;

[0124] Among them, energy consumption indicators may include energy consumption per unit area indicators and renewable energy power substitution rate indicators; carbon emission indicators may include carbon emission per unit area indicators, renewable energy emission reduction rate indicators and carbon emission offset rate indicators.

[0125] In a low-carbon building energy and carbon statistical index management device provided in an embodiment of the present application, the third determination module 73 may include:

[0126] The second determination submodule is used to determine the reduction ratio of the target building's energy consumption per unit area to the benchmark according to the energy consumption per unit area index and the building energy consumption intensity index constraint value corresponding to the target building;

[0127] The third determination submodule is used to determine the overall evaluation grade information of the target building according to the ratio of energy consumption per unit area to the benchmark, the renewable energy power substitution rate index and the renewable energy emission reduction rate index.

[0128] In a low-carbon building energy and carbon statistical index management device provided in an embodiment of the present application, the third determination submodule may include:

[0129] A first determination unit is used to determine the overall evaluation level of the target building according to the ratio of energy consumption per unit area to the benchmark, the renewable energy power substitution rate index, the renewable energy emission reduction rate index and a pre-established first corresponding relationship;

[0130] Among them, the first correspondence is the correspondence between the ratio of energy consumption per unit area to benchmark reduction, renewable energy power substitution rate index, renewable energy emission reduction rate index and the overall evaluation level. The overall evaluation levels include: no rating, bronze, gold and platinum;

[0131] If the ratio of energy consumption per unit area to benchmark reduction is less than the first preset value, the renewable energy power substitution rate index is less than the second preset value, and the renewable energy emission reduction rate index is less than the third preset value, the overall evaluation level is no rating;

[0132] The first preset value ≤ the ratio of energy consumption per unit area to benchmark reduction < the fourth preset value, the second preset value ≤ the renewable energy power substitution rate index < the fifth preset value, the third preset value ≤ the renewable energy emission reduction rate index < the sixth preset value, and the overall evaluation level is bronze;

[0133] The fourth preset value ≤ the ratio of energy consumption per unit area to benchmark reduction < the seventh preset value, the fifth preset value ≤ the renewable energy power substitution rate index < the eighth preset value, the sixth preset value ≤ the renewable energy emission reduction rate index < the ninth preset value, and the overall evaluation level is silver;

[0134] The seventh preset value ≤ the ratio of energy consumption per unit area to benchmark reduction < the tenth preset value, the eighth preset value ≤ the renewable energy power substitution rate index < the eleventh preset value, the ninth preset value ≤ the renewable energy emission reduction rate index < the twelfth preset value, the overall evaluation level is gold;

[0135] The tenth preset value is ≤ the ratio of energy consumption per unit area to the benchmark reduction, the eleventh preset value is ≤ the renewable energy power substitution rate index, and the twelfth preset value is ≤ the renewable energy emission reduction rate index. The overall evaluation level is platinum.

[0136] An embodiment of the present application provides a low-carbon building energy and carbon statistical index management device, wherein the first determination unit may include:

[0137] A first determining subunit is used to determine the overall evaluation level as the overall evaluation level of the target building when the ratio of the energy consumption per unit area to the benchmark reduction, the renewable energy power substitution rate index and the renewable energy emission reduction rate index correspond to the same overall evaluation level according to the first corresponding relationship;

[0138] The second determination subunit is used to determine the lower overall evaluation level among the overall evaluation levels corresponding to the ratio of reduction in energy consumption per unit area, the renewable energy power substitution rate index and the renewable energy emission reduction rate index as the overall evaluation level of the target building when the ratio of reduction in energy consumption per unit area, the renewable energy power substitution rate index and the renewable energy emission reduction rate index determined according to the first corresponding relationship do not correspond to the same overall evaluation level.

[0139] In a low-carbon building energy and carbon statistical index management device provided in an embodiment of the present application, the third determination module 73 may include:

[0140] The fourth determination submodule is used to determine the energy consumption reduction ratio per unit area according to the energy consumption index per unit area and the constraint value of the building energy consumption intensity index;

[0141] The fifth determination submodule is used to determine the optimization suggestion information according to the energy consumption reduction ratio per unit area, the renewable energy power substitution rate index, the carbon emission index per unit area, the renewable energy emission reduction rate index, the carbon emission offset rate index and the pre-established second corresponding relationship;

[0142] Among them, the second corresponding relationship is the corresponding relationship between the optimization suggestion trigger conditions corresponding to the energy consumption reduction ratio per unit area, the renewable energy power substitution rate index, the carbon emission index per unit area, the renewable energy emission reduction rate index and the carbon emission offset rate index and the corresponding optimization suggestion information, and the optimization suggestion information includes a title prompt and description details;

[0143] The optimization suggestion triggering condition corresponding to the energy consumption reduction ratio per unit area is: the energy consumption reduction ratio per unit area is less than the thirteenth preset value; the title prompt in the corresponding optimization suggestion information is: the energy consumption per unit area is high; the description details in the corresponding optimization suggestion information are: there may be a waste of electricity, and the electrical equipment can be upgraded to energy-saving equipment or an intelligent control system can be added;

[0144] The optimization suggestion triggering condition corresponding to the renewable energy power substitution rate indicator is: the renewable energy power substitution rate is less than the fourteenth preset value; the title prompt in the corresponding optimization suggestion information is: the renewable energy power substitution rate is low; the description details in the corresponding optimization suggestion information are: it is recommended to install renewable energy equipment to provide more renewable energy for the building, improve the utilization rate of renewable energy, and reduce the energy consumption of building operation;

[0145] The optimization suggestion triggering condition corresponding to the renewable energy emission reduction rate indicator is: the renewable energy emission reduction rate is equal to 0; the title prompt in the corresponding optimization suggestion information is: the renewable energy emission reduction rate is low; the description details in the corresponding optimization suggestion information are: it is recommended to install renewable energy equipment to provide more renewable energy for the building, improve the utilization rate of renewable energy, or implement emission reduction projects to increase emission reduction and reduce carbon emissions;

[0146] The optimization suggestion triggering condition corresponding to the carbon emission offset rate indicator is: the carbon emission offset rate is equal to 0; the title prompt in the corresponding optimization suggestion information is: the carbon emission trading offset rate is low; the description details in the corresponding optimization suggestion information are: you can consider purchasing carbon indicators to offset the actual carbon emissions that can no longer be reduced, so as to achieve the goal of carbon neutrality;

[0147] The optimization suggestion triggering conditions corresponding to the carbon emission per unit area index are: any one of the carbon emission per unit area index in winter and the carbon emission per unit area index in summer is higher than any one of the carbon emission per unit area index in spring and the carbon emission per unit area index in autumn by fifteen preset values; the title prompt in the corresponding optimization suggestion information is: seasonal carbon emission per unit area fluctuates too much; the description details in the corresponding optimization suggestion information can be: it is recommended to carry out insulation renovation of the building's exterior walls and roof to reduce energy loss, adjust the indoor temperature settings according to seasonal changes, and optimize the operation of the heating and cooling systems.

[0148] A low-carbon building energy and carbon statistical index management device provided in an embodiment of the present application may also include:

[0149] The preprocessing module is used to preprocess the energy carbon data of the target building before determining the energy carbon statistical index of the target building according to the energy carbon data of the target building.

[0150] In a low-carbon building energy and carbon statistical index management device provided in an embodiment of the present application, the second determination module 72 may include:

[0151] The timed acquisition submodule is used to obtain the energy and carbon data of the target building at a regular time.

[0152] The present application also provides a cloud platform. Figure 8 , which shows a schematic diagram of the structure of a cloud platform provided in an embodiment of the present application, which may include:

[0153] A memory 81, used for storing computer programs;

[0154] The processor 82, when used to execute the computer program stored in the memory 81, can implement the following steps:

[0155] Determine the thermal zoning of the area where the target building is located, the functional type and ventilation method of the target building, and determine the constraint value of the building energy intensity index corresponding to the target building based on the thermal zoning of the area where the target building is located, the functional type and ventilation method of the target building; obtain the energy carbon data of the target building, and determine the energy carbon statistical indicators of the target building based on the energy carbon data of the target building; determine the overall evaluation grade information and optimization suggestions of the target building based on the energy carbon statistical indicators of the target building and the constraint value of the building energy intensity index corresponding to the target building.

[0156] For the description of the relevant parts of a low-carbon building energy carbon statistical indicator management device and a cloud platform provided in the embodiment of the present application, please refer to the detailed description of the corresponding parts of a low-carbon building energy carbon statistical indicator management method provided in the embodiment of the present application, which will not be repeated here.

[0157] It should be noted that the logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection portion with one or more wirings (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0158] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0159] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0160] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0161] In this application, unless otherwise clearly specified and limited, the terms "installed", "connected", "connected", "fixed" and the like should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, it can be the internal connection of two elements or the interaction relationship between two elements, unless otherwise clearly defined. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0162] Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limitations on the present application. Ordinary technicians in this field can change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for managing carbon statistical indicators of low-carbon buildings, characterized in that: Applied to cloud platforms, including: Determine the thermal zoning of the area where the target building is located, the functional type and ventilation mode of the target building, and determine the building energy intensity index constraint value corresponding to the target building according to the thermal zoning of the area where the target building is located, the functional type and ventilation mode of the target building; Acquiring energy carbon data of the target building, and determining energy carbon statistical indicators of the target building according to the energy carbon data of the target building; The overall evaluation grade information and optimization suggestions of the target building are determined according to the energy carbon statistical index of the target building and the building energy intensity index constraint value corresponding to the target building.

2. The low-carbon building energy and carbon statistical index management method according to claim 1 is characterized in that: Determining the energy carbon statistical index of the target building according to the energy carbon data of the target building includes: Determine the energy consumption index and carbon emission index of the target building according to the energy and carbon data of the target building; Among them, the energy consumption indicators include energy consumption per unit area indicators and renewable energy power substitution rate indicators, and the carbon emission indicators include carbon emission per unit area indicators, renewable energy emission reduction rate indicators and carbon emission offset rate indicators.

3. The low-carbon building energy and carbon statistical index management method according to claim 2 is characterized in that: Determining the overall evaluation grade information of the target building according to the energy carbon statistical index of the target building and the building energy intensity index constraint value corresponding to the target building includes: Determining the reduction ratio of the target building's energy consumption per unit area according to the energy consumption per unit area index and the building energy consumption intensity index constraint value corresponding to the target building; The overall evaluation grade information of the target building is determined according to the ratio of the energy consumption per unit area to the benchmark, the renewable energy power substitution rate index and the renewable energy emission reduction rate index.

4. The low-carbon building energy and carbon statistical index management method according to claim 2 is characterized in that: The overall evaluation grade information of the target building is determined according to the ratio of the energy consumption per unit area to the benchmark, the renewable energy power substitution rate index and the renewable energy emission reduction rate index, including: Determining the overall evaluation grade of the target building according to the ratio of the energy consumption per unit area to the benchmark, the renewable energy power substitution rate index, the renewable energy emission reduction rate index and the pre-established first corresponding relationship; The first corresponding relationship is the corresponding relationship between the ratio of energy consumption per unit area to benchmark reduction, renewable energy power substitution rate index, renewable energy emission reduction rate index and the overall evaluation level, and the overall evaluation level includes: no rating, bronze, gold and platinum; If the ratio of energy consumption per unit area to benchmark reduction is less than the first preset value, the renewable energy power substitution rate index is less than the second preset value, and the renewable energy emission reduction rate index is less than the third preset value, the overall evaluation level is no rating; The first preset value ≤ the ratio of energy consumption per unit area to benchmark reduction < the fourth preset value, the second preset value ≤ the renewable energy power substitution rate index < the fifth preset value, the third preset value ≤ the renewable energy emission reduction rate index < the sixth preset value, and the overall evaluation level is bronze; The fourth preset value ≤ the ratio of energy consumption per unit area to benchmark reduction < the seventh preset value, the fifth preset value ≤ the renewable energy power substitution rate index < the eighth preset value, the sixth preset value ≤ the renewable energy emission reduction rate index < the ninth preset value, and the overall evaluation level is silver; The seventh preset value ≤ the ratio of energy consumption per unit area to benchmark reduction < the tenth preset value, the eighth preset value ≤ the renewable energy power substitution rate index < the eleventh preset value, the ninth preset value ≤ the renewable energy emission reduction rate index < the twelfth preset value, the overall evaluation level is gold; The tenth preset value is ≤ the ratio of energy consumption per unit area to the benchmark reduction, the eleventh preset value is ≤ the renewable energy power substitution rate index, and the twelfth preset value is ≤ the renewable energy emission reduction rate index. The overall evaluation level is platinum.

5. The low-carbon building energy and carbon statistical index management method according to claim 4 is characterized in that: According to the ratio of the energy consumption per unit area to the benchmark reduction, the renewable energy power substitution rate index, the renewable energy emission reduction rate index and the pre-established first corresponding relationship, the overall evaluation grade of the target building is determined, including: When it is determined according to the first corresponding relationship that the ratio of the energy consumption per unit area to the benchmark reduction, the renewable energy power substitution rate index and the renewable energy emission reduction rate index correspond to the same overall evaluation level, the overall evaluation level is determined as the overall evaluation level of the target building; When it is determined according to the first corresponding relationship that the ratio of the reduction in energy consumption per unit area, the renewable energy power substitution rate index and the renewable energy emission reduction rate index do not correspond to the same overall evaluation level, the lower overall evaluation level among the overall evaluation levels respectively corresponding to the ratio of the reduction in energy consumption per unit area, the renewable energy power substitution rate index and the renewable energy emission reduction rate index shall be determined as the overall evaluation level of the target building.

6. The low-carbon building energy and carbon statistical index management method according to claim 2 is characterized in that: Determining optimization suggestions for the target building according to the energy carbon statistical index of the target building and the building energy intensity index constraint value corresponding to the target building includes: Determine the energy consumption reduction ratio per unit area according to the energy consumption index per unit area and the constraint value of the building energy consumption intensity index; Determine optimization suggestion information according to the energy consumption reduction ratio per unit area, the renewable energy power substitution rate index, the carbon emission index per unit area, the renewable energy emission reduction rate index, the carbon emission offset rate index and the pre-established second corresponding relationship; The second corresponding relationship is the corresponding relationship between the optimization suggestion triggering conditions corresponding to the energy consumption reduction ratio per unit area, the renewable energy power substitution rate index, the carbon emission index per unit area, the renewable energy emission reduction rate index and the carbon emission offset rate index, and the corresponding optimization suggestion information, wherein the optimization suggestion information includes a title prompt and description details; The optimization suggestion triggering condition corresponding to the energy consumption reduction ratio per unit area is: the energy consumption reduction ratio per unit area is less than the thirteenth preset value; the title prompt in the corresponding optimization suggestion information is: the energy consumption per unit area is high; the description details in the corresponding optimization suggestion information are: there may be a waste of electricity, and the electrical equipment can be upgraded to energy-saving equipment or an intelligent control system can be added; The optimization suggestion triggering condition corresponding to the renewable energy power substitution rate indicator is: the renewable energy power substitution rate is less than the fourteenth preset value; the title prompt in the corresponding optimization suggestion information is: the renewable energy power substitution rate is low; the description details in the corresponding optimization suggestion information are: it is recommended to install renewable energy equipment to provide more renewable energy for the building, improve the utilization rate of renewable energy, and reduce the energy consumption of building operation; The optimization suggestion triggering condition corresponding to the renewable energy emission reduction rate indicator is: the renewable energy emission reduction rate is equal to 0; the title prompt in the corresponding optimization suggestion information is: the renewable energy emission reduction rate is low; the description details in the corresponding optimization suggestion information are: it is recommended to install renewable energy equipment to provide more renewable energy for the building, improve the utilization rate of renewable energy, or implement emission reduction projects to increase emission reduction and reduce carbon emissions; The optimization suggestion triggering condition corresponding to the carbon emission offset rate indicator is: the carbon emission offset rate is equal to 0; the title prompt in the corresponding optimization suggestion information is: the carbon emission trading offset rate is low; the description details in the corresponding optimization suggestion information are: you can consider purchasing carbon indicators to offset the actual carbon emissions that can no longer be reduced, so as to achieve the goal of carbon neutrality; The optimization suggestion triggering conditions corresponding to the carbon emission per unit area index are: any one of the carbon emission per unit area index in winter and the carbon emission per unit area index in summer is higher than any one of the carbon emission per unit area index in spring and the carbon emission per unit area index in autumn by fifteen preset values; the title prompt in the corresponding optimization suggestion information is: seasonal carbon emission per unit area fluctuates too much; the description details in the corresponding optimization suggestion information are: it is recommended to carry out insulation renovation of the building's exterior walls and roof to reduce energy loss, adjust the indoor temperature settings according to seasonal changes, and optimize the operation of the heating and cooling systems.

7. The low-carbon building energy and carbon statistical index management method according to claim 1 is characterized in that: Before determining the energy carbon statistical index of the target building according to the energy carbon data of the target building, it also includes: The energy and carbon data of the target building are preprocessed.

8. The low-carbon building energy and carbon statistical index management method according to any one of claims 1 to 7, characterized in that: Obtain energy and carbon data for target buildings, including: The energy and carbon data of the target building are obtained regularly.

9. A low-carbon building energy and carbon statistical index management device, characterized in that: Applied to cloud platforms, including: The first determination module is used to determine the thermal zone of the area where the target building is located, the functional type and ventilation mode of the target building, and determine the building energy intensity index constraint value corresponding to the target building according to the thermal zone of the area where the target building is located, the functional type and ventilation mode of the target building; A second determination module is used to obtain the energy carbon data of the target building, and determine the energy carbon statistical index of the target building according to the energy carbon data of the target building; The third determination module is used to determine the overall evaluation level information and optimization suggestions of the target building according to the energy carbon statistical index of the target building and the building energy intensity index constraint value corresponding to the target building.

10. A cloud platform, characterized in that: include: Memory for storing computer programs; A processor is used to implement the steps of the low-carbon building energy and carbon statistical indicator management method as described in any one of claims 1 to 8 when executing the computer program.

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