3D visual energy consumption management method

Abstract

The invention discloses a 3D visual energy consumption management method. The method comprises the following steps: (1) constructing an Internet of Things platform and installing a sensor; (2) creating a 3D model; (3) data integration and processing: according to actual display requirements of the 3D model, associating the acquired energy consumption data and environmental data with the 3D model by adopting a color coding method, a height change method, a label and chart method, an animation display method and a symbol and icon method; corresponding energy consumption data and environment data are matched with corresponding areas, floors, rooms and devices in the 3D model, integration processing is carried out, energy consumption conditions of different areas, floors, rooms and devices are represented by color codes, height changes, charts, animations, symbols and icons, and the energy consumption conditions of the areas, floors, rooms and devices are stored on an Internet of Things platform; (4) a user requests visual display of a corresponding area according to needs; (5) data analysis and optimization; and (6) real-time monitoring and reporting.

Description

Technical Field

[0001] The present invention relates to the technical field of energy consumption management, and in particular to a 3D visualized energy consumption management method. Background Art

[0002] The energy consumption management system is based on the traditional IoT management platform. It connects water meters, electricity meters, gas meters and other meters to the IoT platform through gateway devices. It collects energy consumption data through water meters, electricity meters and gas meters. After the data is processed by the IoT platform, it is connected and processed with the energy consumption management system through the API interface. However, the current energy consumption management system has the following defects: (1) Insufficient visualization: Energy consumption management systems usually present energy consumption data in the form of tables, charts or reports, and the visualization effect is relatively weak; (2) User experience limitations: The energy consumption management system is intended for professionals and may require certain professional knowledge and training to use; (3) Lack of intuitive spatial perception: The energy management system cannot intuitively display the relationship between building space and energy consumption data. Summary of the invention

[0003] The problem to be solved by the present invention is to provide a 3D visualized energy consumption management method, which can improve the visualization effect, intuitively understand the energy consumption distribution, and identify energy consumption anomalies and high-energy consumption equipment.

[0004] In order to solve the above technical problems, the technical solution adopted by the present invention is as follows: A 3D visualized energy consumption management method, characterized by comprising the following steps: (1) Construction of the IoT platform and installation of sensors: Build various connected devices into an IoT platform, and then install corresponding sensors in each area, floor, room, and equipment of the building where data needs to be collected. Use various sensors to collect energy consumption data and environmental data related to energy consumption; (2) 3D model creation: According to the layout of each area, floor, room, and equipment of the building, measure the dimensions of each area, floor, room, and equipment of the actual building, and use 3D modeling technology to create a 3D model on a 3D visualization platform in proportion; (3) Data integration and processing: According to the actual display requirements of the 3D model, the collected energy consumption data and environmental data are associated with the 3D model using color coding, height change, label and chart, animation display, symbol and icon methods. The corresponding energy consumption data and environmental data are matched with the corresponding areas, floors, rooms and equipment in the 3D model, and integrated. The energy consumption of different areas, floors, rooms and equipment is represented by color coding, height change, chart, animation, symbol and icon, and the energy consumption of each area, floor, room and equipment is stored on the IoT platform; (4) The user requests a visualization display of the corresponding area as needed: the user installs the application of the 3D visualization platform on the user terminal. The user selects the corresponding area through the application of the user terminal according to the area actually needed to be viewed and sends a request to the IoT platform. The IoT platform sends the data requested by the user to the application of the user terminal. The 3D visualization platform can obtain the energy consumption of the corresponding area, floor, room, and equipment of the building from the material network platform, and use three-dimensional visualization technology to display the energy consumption data and environmental data in an intuitive way on the 3D model. The user can view and analyze the energy consumption data through interactive operations on the user terminal: rotate, zoom, select a certain area, floor, room or equipment; (5) Data analysis and optimization: By analyzing and comparing energy consumption data, integrating and analyzing energy consumption data of different dimensions, identifying information such as energy consumption anomalies, energy consumption peaks, and energy consumption trends from the time dimension, and identifying information such as energy consumption distribution, energy consumption anomaly locations, and high energy consumption locations from the spatial dimension, corresponding energy consumption optimization strategies are formulated based on this information, providing a more comprehensive energy consumption analysis to reduce energy consumption and improve energy efficiency; (6) Real-time monitoring and reporting: Real-time monitoring of energy consumption data and generation of energy consumption visualization reports so that users can understand energy consumption and optimization effects at any time, thereby helping users make decisions and adjust energy consumption management strategies.

[0005] In the above step (1), the energy consumption data includes electricity, gas, water, etc., and the environmental data includes temperature, humidity, light, etc.

[0006] In the above step (3), by using three-dimensional graphics, animation and simulation effects, the energy consumption data can be visualized, so that users can intuitively understand the energy consumption pattern, change trend and spatial distribution.

[0007] In the above step (5), the above energy consumption optimization strategy includes adjusting the equipment operation mode, improving energy utilization efficiency, etc.

[0008] In the above step (6), the above energy consumption visualization report includes energy consumption report, energy consumption statistical chart, etc. The energy consumption report includes information such as energy consumption trend, energy consumption proportion, energy consumption difference, etc. The above energy consumption statistical chart identifies when the data recorded by various sensors is generated from the time dimension, and then performs energy consumption statistics in the form of charts.

[0009] In the preferred solution, in step (3), the steps of matching the corresponding energy consumption data and environmental data with the corresponding areas, floors, rooms, and equipment in the 3D model and integrating them are as follows: (3-1) Steps of data cleaning: (3-1.1) Data collection: obtain raw data; (3-1.2) Data review: Check the completeness and accuracy of the data; (3-1.3) Handling missing values: Determine whether to delete, fill or retain missing values; (3-1.4) Deduplication: Delete duplicate data records; (3-1.5) Format standardization: unify data formats (such as date, time and unit); (3-1.6) Outlier detection: Identify and handle outliers in the data; (3-2) Steps of data format conversion processing: (3-2.1) Identify fields that need to be converted: determine which data needs to be formatted; (3-2.2) Select the target format: Determine the target format of the data (such as date, number, or string); (3-2.3) Apply transformation rules: Use appropriate functions or scripts to perform the transformation (e.g., using programming languages ​​or data processing tools); (3-2.4) Verify conversion results: Check whether the converted data meets expectations; (3-2.5) Handling exceptions: If there are errors or abnormal values ​​in the data, further processing of the errors or abnormal values ​​is performed; (3-2.6) Preservation and Recording: Preserve the converted data and record the conversion process for future reference; (3-3) Data verification process steps: (3-3.1) Define validation rules: determine the standards that the data should follow, such as data type, range, and format; (3-3.2) Implement verification: Use automated tools or scripts to verify data and check whether it complies with the rules; (3-3.3) Record errors: record data that does not conform to the rules for subsequent processing; (3-3.4) Correct data: Correct or clean data that does not conform to the rules to ensure that it meets the requirements; (3-3.5) Recalibration: Recalibrate to confirm that all data meet the standards; (3-3.6) Documentation: Record the verification process and results for future reference; (3-4) Steps of data association processing: (3-4.1) Identify association requirements: Identify the data sets that need to be associated and the purpose of the association; (3-4.2) Select key fields: Determine the key fields used for association (such as ID, name, etc.); (3-4.3) Data preprocessing: clean the data to ensure the format of key fields is consistent; (3-4.4) Select the join method: select inner join method, outer join method or cross join method; (3-4.5) Perform association operations: Use database query or data processing tools to associate data; (3-4.6) Verify results: Check whether the associated data is consistent with expectations and ensure there are no errors or omissions; (3-4.7) Record and save: Save the associated data and record the processing process and methods.

[0010] The above processing steps such as data cleaning, data format conversion, data verification and data association can ensure the accuracy and consistency of energy consumption data.

[0011] In a further preferred embodiment, in the steps (3-4.4), the inner join method: only retains records that exist in both data sets; the outer join method: retains all records, including records without matches; and the cross join method: generates all possible combinations of records.

[0012] In the above steps (3-4.5), SQL database can be used for database query and Pandas can be used as data processing tool.

[0013] In the preferred embodiment, the color coding method in step (3) is to configure the relationship between the colors and data values ​​of various models in the 3D visualization platform, and map the energy consumption data to the 3D model. For example, a heat map is used to display high energy consumption areas in red or orange, and low energy consumption areas in green or blue. Users can quickly understand which devices' energy consumption exceeds their expectations through color changes.

[0014] In the preferred embodiment, the height change method in step (3) is to configure the relationship between the height of various models and the size of data values ​​in the 3D visualization platform, and map the energy consumption data to the 3D model. For example, in some containers that store energy internally, the energy in the container will gradually decrease as the energy is consumed, and the change reflected in the 3D model can be the height of the energy material in the 3D model: when the height of the energy material in the 3D model is the same as the height of the container, it means that the energy is full; when the height of the energy material in the 3D model is zero, it means that the energy is exhausted; in this way, the user can understand the distribution of energy consumption by observing the shape of the model.

[0015] In the preferred embodiment, the label and chart method in step (3) is to configure additional labels and charts for various models in the 3D visualization platform, and users can view these label information and chart information by clicking on the labels and charts hovering on the models. These label information and chart information can be energy consumption values, energy consumption trends, etc. For example, a numerical value of energy consumption for the day can be displayed on the electric meter model. If the energy consumption for the day is higher than that for yesterday, an upward icon can also be displayed to indicate that the energy consumption has increased relative to yesterday. At this time, users who pay attention will notice the increase in energy consumption and intervene in time.

[0016] In the preferred embodiment, the animation display method in step (3) is to configure animation effects for various models in the 3D visualization platform, and map the real-time changes of energy consumption values ​​on various model animations. For example, the parts with higher energy consumption can flash or glow at different speeds to attract the user's attention, so that the user can intuitively feel the real-time changes of energy consumption.

[0017] In the preferred embodiment, the symbol and icon method in step (3) is to configure the relationship between various model states and various symbols and icons in the 3D visualization platform to indicate the location and status of different energy-consuming devices. Users can select different symbols or icons according to the status of the device (such as on, off, fault) and energy consumption level, to help users quickly identify, filter and locate devices with abnormal energy consumption.

[0018] In the preferred embodiment, in step (4), the collected energy consumption data is read through the 3D visualization platform, and a container is created on the 3D model. The amount of energy consumption is reflected by the filling amount inside the container; when the energy consumption data is always in an increasing state, the energy consumption data on the 3D model is slowly increasing in the container to indicate a slow increase; similarly, when the energy consumption data is always in a decreasing state, the energy consumption data on the 3D model is slowly decreasing in the container to indicate a slow decrease, so that the energy consumption data is visualized in a three-dimensional form. The above energy consumption data should be presented on the 3D model as much as possible, and try not to open up an area for display, so that the energy consumption data looks more intuitive.

[0019] In a further preferred embodiment, in step (4), a UI slider that can freely select a time point is set in the 3D visualization platform; the collected energy consumption data is recorded in a database in chronological order, and when it is necessary to view the energy consumption status at a certain time, the time is selected by sliding the position of the UI slider, and then the data at the time point is queried, and the data is updated to the 3D model, so that the historical status of the 3D model can be displayed.

[0020] In the preferred embodiment, in step (4), the application of the user terminal is provided with an interactive interface and a user participation function, so that the user can be immersed in the application of the user terminal, and the user can interact, operate and explore the 3D model, thereby enhancing the user's sense of participation and initiative.

[0021] In a further preferred embodiment, in step (4), the user can freely browse the building model, view the energy consumption of any area, floor, room or equipment, perform data query and filtering, and participate in the decision-making process of energy optimization.

[0022] Compared with the prior art, the present invention has the following advantages: (1) Visual display: The present invention displays energy consumption data in three dimensions on a 3D model, allowing users to intuitively understand energy consumption distribution, identify energy consumption anomalies and high-energy-consuming equipment, and formulate corresponding energy consumption optimization strategies based on data analysis results, providing users with a more intuitive and interactive energy management experience, allowing users to understand and analyze energy consumption data in a visual way, improve the efficiency and accuracy of energy management, and achieve the goals of sustainable energy use and energy conservation and emission reduction; (2) The IoT platform of the present invention can store the energy consumption of each area, floor, room, and equipment. It is not necessary to store all energy consumption data in the application of the user terminal. The user terminal does not need to store and receive data in real time, which reduces the memory usage of the user terminal and can greatly improve the speed of data transmission, ensuring the smoothness of users viewing energy consumption status on the user terminal. (3) User participation and decision support: The present invention can better encourage users to participate in energy consumption management. Through visual display and interactive functions, users can understand energy consumption more intuitively and make corresponding decisions and optimization measures based on the display results. (4) Effect evaluation and optimization: The present invention can intuitively display the spatial distribution and change trend of energy consumption data, helping users to identify energy consumption peaks, energy consumption anomalies, and potential energy-saving opportunities. Through visual display, users can simulate and optimize energy consumption, evaluate the effects of different measures, and make corresponding adjustments and decisions. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a schematic diagram of a flow chart of a specific embodiment of the present invention; Figure 2 is a schematic diagram of data visualization of a specific embodiment of the present invention; Figure 3 is a schematic diagram of different dimensional analysis in a specific embodiment of the present invention; Figure 4 It is a schematic diagram of user interaction and participation in a specific embodiment of the present invention. DETAILED DESCRIPTION

[0024] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments.

[0025] like Figure 1-4 As shown, the 3D visualization energy consumption management method in this embodiment includes the following steps: (1) Construction of the IoT platform and installation of sensors: Build various connected devices into an IoT platform, and then install corresponding sensors in each area, floor, room, and equipment of the building where data needs to be collected. Use various sensors to collect energy consumption data and environmental data related to energy consumption; (2) 3D model creation: According to the layout of each area, floor, room, and equipment of the building, measure the dimensions of each area, floor, room, and equipment of the actual building, and use 3D modeling technology to create a 3D model on a 3D visualization platform in proportion; (3) Data integration and processing: According to the actual display requirements of the 3D model, the collected energy consumption data and environmental data are associated with the 3D model using color coding, height change, label and chart, animation display, symbol and icon methods. The corresponding energy consumption data and environmental data are matched with the corresponding areas, floors, rooms and equipment in the 3D model, and integrated. The energy consumption of different areas, floors, rooms and equipment is represented by color coding, height change, chart, animation, symbol and icon, and the energy consumption of each area, floor, room and equipment is stored on the IoT platform; (4) The user requests a visualization display of the corresponding area as needed: the user installs the application of the 3D visualization platform on the user terminal. The user selects the corresponding area through the application of the user terminal according to the area actually needed to be viewed and sends a request to the IoT platform. The IoT platform sends the data requested by the user to the application of the user terminal. The 3D visualization platform can obtain the energy consumption of the corresponding area, floor, room, and equipment of the building from the material network platform, and use three-dimensional visualization technology to display the energy consumption data and environmental data in an intuitive way on the 3D model. The user can view and analyze the energy consumption data through interactive operations on the user terminal: rotate, zoom, select a certain area, floor, room or equipment; (5) Data analysis and optimization: By analyzing and comparing energy consumption data, integrating and analyzing energy consumption data of different dimensions, identifying information such as energy consumption anomalies, energy consumption peaks, and energy consumption trends from the time dimension, and identifying information such as energy consumption distribution, energy consumption anomaly locations, and high energy consumption locations from the spatial dimension, corresponding energy consumption optimization strategies are formulated based on this information, providing a more comprehensive energy consumption analysis to reduce energy consumption and improve energy efficiency; (6) Real-time monitoring and reporting: Real-time monitoring of energy consumption data and generation of energy consumption visualization reports so that users can understand energy consumption and optimization effects at any time, thereby helping users make decisions and adjust energy consumption management strategies.

[0026] In the above step (1), the energy consumption data includes electricity, gas, water, etc., and the environmental data includes temperature, humidity, light, etc.

[0027] In the above step (3), by using three-dimensional graphics, animation and simulation effects, the energy consumption data can be visualized, so that users can intuitively understand the energy consumption pattern, change trend and spatial distribution.

[0028] In the above step (5), the above energy consumption optimization strategy includes adjusting the equipment operation mode, improving energy utilization efficiency, etc.

[0029] In the above step (6), the above energy consumption visualization report includes energy consumption report, energy consumption statistical chart, etc. The energy consumption report includes information such as energy consumption trend, energy consumption proportion, energy consumption difference, etc. The above energy consumption statistical chart identifies when the data recorded by various sensors is generated from the time dimension, and then performs energy consumption statistics in the form of charts.

[0030] In the above step (3), the corresponding energy consumption data and environmental data are matched with the corresponding areas, floors, rooms, and equipment in the 3D model, and the steps of integration processing are as follows: (3-1) Steps of data cleaning: (3-1.1) Data collection: obtain raw data; (3-1.2) Data review: Check the completeness and accuracy of the data; (3-1.3) Handling missing values: Determine whether to delete, fill or retain missing values; (3-1.4) Deduplication: Delete duplicate data records; (3-1.5) Format standardization: unify data formats (such as date, time and unit); (3-1.6) Outlier detection: Identify and handle outliers in the data; (3-2) Steps of data format conversion processing: (3-2.1) Identify fields that need to be converted: determine which data needs to be formatted; (3-2.2) Select the target format: Determine the target format of the data (such as date, number, or string); (3-2.3) Apply transformation rules: Use appropriate functions or scripts to perform the transformation (e.g., using programming languages ​​or data processing tools); (3-2.4) Verify conversion results: Check whether the converted data meets expectations; (3-2.5) Handling exceptions: If there are errors or abnormal values ​​in the data, further processing of the errors or abnormal values ​​is performed; (3-2.6) Preservation and Recording: Preserve the converted data and record the conversion process for future reference; (3-3) Data verification process steps: (3-3.1) Define validation rules: determine the standards that the data should follow, such as data type, range, and format; (3-3.2) Implement verification: Use automated tools or scripts to verify data and check whether it complies with the rules; (3-3.3) Record errors: record data that does not conform to the rules for subsequent processing; (3-3.4) Correct data: Correct or clean data that does not conform to the rules to ensure that it meets the requirements; (3-3.5) Recalibration: Recalibrate to confirm that all data meet the standards; (3-3.6) Documentation: Record the verification process and results for future reference; (3-4) Steps of data association processing: (3-4.1) Identify association requirements: Identify the data sets that need to be associated and the purpose of the association; (3-4.2) Select key fields: Determine the key fields used for association (such as ID, name, etc.); (3-4.3) Data preprocessing: clean the data to ensure the format of key fields is consistent; (3-4.4) Select the join method: select inner join method, outer join method or cross join method; (3-4.5) Perform association operations: Use database query or data processing tools to associate data; (3-4.6) Verify results: Check whether the associated data is consistent with expectations and ensure there are no errors or omissions; (3-4.7) Record and save: Save the associated data and record the processing process and methods.

[0031] The above processing steps such as data cleaning, data format conversion, data verification and data association can ensure the accuracy and consistency of energy consumption data.

[0032] In the steps (3-4.4), the inner join method: only retains the records in both data sets; the outer join method: retains all records, including those without matches; the cross join method: generates all possible record combinations.

[0033] In the above steps (3-4.5), SQL database can be used for database query and Pandas can be used as data processing tool.

[0034] The color coding method in step (3) is to configure the relationship between the colors and data values ​​of various models in the 3D visualization platform, and map the energy consumption data to the 3D model. For example, a heat map is used to display high energy consumption areas in red or orange, and low energy consumption areas in green or blue. Users can quickly understand which devices' energy consumption exceeds their expectations through color changes.

[0035] The height change method in step (3) is to configure the relationship between the height of various models and the size of data values ​​in the 3D visualization platform, and map the energy consumption data to the 3D model. For example, in some containers that store energy internally, the energy in the container will gradually decrease as the energy is consumed, and the change reflected in the 3D model can be the height of the energy material in the 3D model: when the height of the energy material in the 3D model is the same as the height of the container, it means that the energy is full; when the height of the energy material in the 3D model is zero, it means that the energy is exhausted; in this way, the user can understand the distribution of energy consumption by observing the shape of the model.

[0036] The label and chart method in step (3) is to configure additional labels and charts for various models in the 3D visualization platform. Users can view these label information and chart information by clicking on the labels and charts hovering on the models. These label information and chart information can be energy consumption values, energy consumption trends, etc. For example, a numerical value of energy consumption for the day can be displayed on the electric meter model. If the energy consumption for the day is higher than that for yesterday, an upward icon can also be displayed to indicate that the energy consumption has increased relative to yesterday. At this time, users who pay attention will notice the increase in energy consumption and make timely interventions.

[0037] The animation display method in step (3) is to configure animation effects for various models in the 3D visualization platform, and map the real-time changes of energy consumption values ​​on various model animations. For example, the parts with higher energy consumption can flash or glow at different speeds to attract the user's attention, so that the user can intuitively feel the real-time changes of energy consumption.

[0038] The symbol and icon method in step (3) is to configure the relationship between various model states and various symbols and icons in the 3D visualization platform to indicate the location and status of different energy-consuming devices. Users can select different symbols or icons according to the status of the device (such as on, off, fault) and energy consumption level, to help users quickly identify, filter and locate devices with abnormal energy consumption.

[0039] In step (4), the collected energy consumption data is read through the 3D visualization platform, and a container is created on the 3D model. The amount of energy consumption is reflected by the filling amount inside the container; when the energy consumption data is always in an increasing state, the energy consumption data on the 3D model is slowly increasing in the container to indicate a slow increase; similarly, when the energy consumption data is always in a decreasing state, the energy consumption data on the 3D model is slowly decreasing in the container to indicate a slow decrease, so that the energy consumption data is visualized in a three-dimensional form. The above energy consumption data should be presented on the 3D model as much as possible, and try not to open up an area for display, so that the energy consumption data looks more intuitive.

[0040] In the step (4), a UI slider that can freely select a time point is set in the 3D visualization platform; the collected energy consumption data is recorded in the database in chronological order. When it is necessary to view the energy consumption status at a certain time, the time is selected by sliding the position of the UI slider, and then the data at the time point is queried, and the data is updated to the 3D model, so that the historical status of the 3D model can be displayed.

[0041] In the step (4), the application of the user terminal is provided with an interactive interface and a user participation function, so that the user can be immersed in the application of the user terminal, and the user can interact, operate and explore the 3D model, thereby enhancing the user's sense of participation and initiative.

[0042] In step (4), the user can freely browse the building model, view the energy consumption of any area, floor, room or equipment, perform data query and filtering, and participate in the decision-making process of energy optimization.

[0043] In addition, it should be noted that the names of the various parts of the specific embodiments described in this specification may be different, and any equivalent or simple changes made based on the structure, features and principles described in the patent concept of the present invention are included in the protection scope of the patent of the present invention. The technicians in the technical field of the present invention can make various modifications or supplements to the specific embodiments described or replace them in a similar manner, as long as they do not deviate from the structure of the present invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. A 3D visual energy consumption management method, characterized in that The steps include: (1) Construction of the IoT platform and installation of sensors: Build various connected devices into an IoT platform, and then install corresponding sensors in each area, floor, room, and equipment of the building where data needs to be collected. Use various sensors to collect energy consumption data and environmental data related to energy consumption; (2) 3D model creation: According to the layout of each area, floor, room, and equipment of the building, measure the dimensions of each area, floor, room, and equipment of the actual building, and use 3D modeling technology to create a 3D model on a 3D visualization platform in proportion; (3) Data integration and processing: According to the actual display requirements of the 3D model, the collected energy consumption data and environmental data are associated with the 3D model using color coding, height change, label and chart, animation display, symbol and icon methods. The corresponding energy consumption data and environmental data are matched with the corresponding areas, floors, rooms and equipment in the 3D model, and integrated. The energy consumption of different areas, floors, rooms and equipment is represented by color coding, height change, chart, animation, symbol and icon, and the energy consumption of each area, floor, room and equipment is stored on the IoT platform; (4) The user requests a visualization display of the corresponding area as needed: the user installs the application of the 3D visualization platform on the user terminal. The user selects the corresponding area through the application of the user terminal according to the area actually needed to be viewed and sends a request to the IoT platform. The IoT platform sends the data requested by the user to the application of the user terminal. The 3D visualization platform can obtain the energy consumption of the corresponding area, floor, room, and equipment of the building from the material network platform, and use three-dimensional visualization technology to display the energy consumption data and environmental data in an intuitive way on the 3D model. The user can view and analyze the energy consumption data through interactive operations on the user terminal: rotate, zoom, select a certain area, floor, room or equipment; (5) Data analysis and optimization: By analyzing and comparing energy consumption data, integrating and analyzing energy consumption data of different dimensions, identifying information such as energy consumption anomalies, energy consumption peaks, and energy consumption trends from the time dimension, and identifying information such as energy consumption distribution, energy consumption anomaly locations, and high energy consumption locations from the spatial dimension, corresponding energy consumption optimization strategies are formulated based on this information, providing a more comprehensive energy consumption analysis to reduce energy consumption and improve energy efficiency; (6) Real-time monitoring and reporting: Real-time monitoring of energy consumption data and generation of energy consumption visualization reports so that users can understand energy consumption and optimization effects at any time, thereby helping users make decisions and adjust energy consumption management strategies.

2. The 3D visualization energy consumption management method according to claim 1, characterized in that: In step (3), the corresponding energy consumption data and environmental data are matched with the corresponding areas, floors, rooms, and equipment in the 3D model, and the steps of integration processing are as follows: (3-1) Steps of data cleaning: (3-1.1) Data collection: obtain raw data; (3-1.2) Data review: Check the completeness and accuracy of the data; (3-1.3) Handling missing values: Determine whether to delete, fill or retain missing values; (3-1.4) Deduplication: Delete duplicate data records; (3-1.5) Format standardization: unify data formats; (3-1.6) Outlier detection: Identify and handle outliers in the data; (3-2) Steps of data format conversion processing: (3-2.1) Identify fields that need to be converted: determine which data needs to be formatted; (3-2.2) Select the target format: determine the target format of the data; (3-2.3) Apply transformation rules: use appropriate functions or scripts to perform the transformation; (3-2.4) Verify conversion results: Check whether the converted data meets expectations; (3-2.5) Handling exceptions: If there are errors or abnormal values ​​in the data, further processing of the errors or abnormal values ​​is performed; (3-2.6) Preservation and Recording: Preserve the converted data and record the conversion process for future reference; (3-3) Data verification process steps: (3-3.1) Define validation rules: determine the standards that the data should follow, such as data type, range, and format; (3-3.2) Implement verification: Use automated tools or scripts to verify data and check whether it complies with the rules; (3-3.3) Record errors: record data that does not conform to the rules for subsequent processing; (3-3.4) Correct data: Correct or clean data that does not conform to the rules to ensure that it meets the requirements; (3-3.5) Recalibration: Recalibrate to confirm that all data meet the standards; (3-3.6) Documentation: Record the verification process and results for future reference; (3-4) Steps of data association processing: (3-4.1) Identify association requirements: Identify the data sets that need to be associated and the purpose of the association; (3-4.2) Select key fields: Determine the key fields used for association; (3-4.3) Data preprocessing: clean the data to ensure the format of key fields is consistent; (3-4.4) Select the join method: select inner join method, outer join method or cross join method; Inner join method: only keep the records in both data sets; Outer join method: retain all records, including those without matching records; Cross-join method: Generate all possible record combinations; (3-4.5) Perform association operations: Use database query or data processing tools to associate data; (3-4.6) Verify results: Check whether the associated data is consistent with expectations and ensure there are no errors or omissions; (3-4.7) Record and save: Save the associated data and record the processing process and methods.

3. The 3D visualization energy consumption management method according to claim 1, characterized in that: The color coding method in step (3) is to configure the relationship between the colors and data values ​​of various models in the 3D visualization platform, and map the energy consumption data to the 3D model.

4. The 3D visualization energy consumption management method according to claim 1, characterized in that: The height change method in step (3) is to configure the relationship between the height of various models and the size of data values ​​in the 3D visualization platform, and map the energy consumption data to the 3D model.

5. The 3D visualized energy consumption management method according to claim 1, characterized in that: The label and chart method in step (3) is to configure additional labels and charts for various models in the 3D visualization platform, and the user can view the label information and chart information by clicking on the label or chart hovering on the model.

6. The 3D visualized energy consumption management method according to claim 1, characterized in that: The animation display method in step (3) is to configure animation effects for various models in the 3D visualization platform, and map the real-time changes of energy consumption values ​​on various model animations.

7. The 3D visualization energy consumption management method according to claim 1, characterized in that: The symbol and icon method in step (3) is to configure the relationship between various model states and various symbols and icons in the 3D visualization platform to indicate the location and state of different energy-consuming devices.

8. The 3D visualized energy consumption management method according to claim 1, characterized in that: In the step (4), the collected energy consumption data is read through the 3D visualization platform, and a container is created on the 3D model. The amount of energy consumption is reflected by the filling amount inside the container. When the energy consumption data is always in an increasing state, the energy consumption data on the 3D model is represented by a slowly rising manner in the container to indicate a slow increase. Similarly, when the energy consumption data is always in a decreasing state, the energy consumption data on the 3D model is represented by a slowly falling manner in the container to indicate a slow decrease, so that the energy consumption data is visualized in a three-dimensional form.

9. The 3D visualized energy consumption management method according to claim 8, characterized in that: In the step (4), a UI slider that can freely select a time point is set in the 3D visualization platform; the collected energy consumption data is recorded in the database in chronological order. When it is necessary to view the energy consumption status at a certain time, the time is selected by sliding the position of the UI slider, and then the data at the time point is queried, and the data is updated to the 3D model, so that the historical status of the 3D model can be displayed.

10. The 3D visualized energy consumption management method according to claim 1, characterized in that: In the step (4), an interactive interface and a user participation function are provided in the application of the user terminal, so that the user can be immersed in the application of the user terminal, and the user can interact, operate and explore the 3D model, thereby enhancing the user's sense of participation and initiative; In step (4), the user can freely browse the building model, view the energy consumption of any area, floor, room or equipment, perform data query and filtering, and participate in the decision-making process of energy optimization.

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