Intelligent calculation method for indoor energy consumption of mongolian yurt building under zero-carbon condition

Abstract

An intelligent calculation method for indoor energy consumption of a Mongolian yurt building under a zero-carbon condition, comprising the following steps: constructing a database of a monitored Mongolian yurt building; performing three-dimensional simulation modeling on said Mongolian yurt building and acquiring micro-environment sample parameters of said Mongolian yurt building; constructing an intelligent training database of the indoor energy consumption of said Mongolian yurt building; intelligently calculating the indoor energy consumption of said Mongolian yurt building; constructing and automatically adjusting intelligent grids for the indoor energy consumption of said Mongolian yurt building; and visually displaying the indoor energy consumption of said Mongolian yurt building. The present invention has the advantages that: the three-dimensional simulation model of the Mongolian yurt building and the surrounding environment of the Mongolian yurt building is constructed, so that the high-precision and high-accuracy micro-environment parameters of the Mongolian yurt building are acquired, and the accuracy of energy consumption calculation of the building is improved; the intelligent training database of the indoor energy consumption of the Mongolian yurt building is constructed, so that the reliability of a calculation result is improved; an intelligent calculation model for the indoor energy consumption of the Mongolian yurt building is constructed, and a convolutional neural network algorithm is used, so that the accuracy of indoor energy consumption calculation of the Mongolian yurt building is improved.

Description

Intelligent Calculation Method for Indoor Energy Consumption of Mongolian Yurt Buildings under Zero-Carbon Conditions Technical Field

[0001] This invention belongs to the technical field of building energy consumption, specifically relating to an intelligent method for calculating indoor energy consumption of a yurt building under zero-carbon conditions. Background Technology

[0002] Most of Inner Mongolia is a cold region with a climate characterized by long, harsh winters and short, warm summers with large diurnal temperature variations, necessitating energy consumption calculation and regulation for yurt buildings. On the other hand, the emergence of digital technology and artificial intelligence provides a more scientific and efficient means of energy consumption calculation and regulation. By constructing an intelligent calculation model for indoor energy consumption in yurt buildings, indoor energy consumption can be intelligently calculated and adjusted, thereby effectively saving energy and reducing emissions.

[0003] Currently, common methods for calculating building energy consumption fall into two categories. One is based on the simulation and evaluation of individual building energy consumption according to building thermal performance. However, existing research rarely considers the impact of the surrounding microenvironment on building energy consumption, leading to inaccurate simulation results. Furthermore, existing research often focuses on calculating energy consumption for single-type buildings such as urban residential or commercial buildings, leaving a gap in the intelligent energy consumption calculation and regulation of unique architectural forms like yurts. The other method is based on real-time building energy consumption monitoring. This method is time-consuming and labor-intensive, faces difficulties in acquiring targeted data, suffers from inconsistent data quality, and fails to provide intuitive, dynamic, and effective monitoring and control of building space zoning. Technical issues

[0004] To address the shortcomings mentioned in the background art, the present invention aims to provide an intelligent method for calculating indoor energy consumption of yurt buildings under zero-carbon conditions. This invention can intelligently calculate indoor energy consumption of yurt buildings and automatically adjust energy consumption for high-energy-consumption scenarios. Technical solutions

[0005] A smart method for calculating indoor energy consumption of yurt buildings under zero-carbon conditions, the method includes the following steps:

[0006] Step S1: Construction of the database of the tested Mongolian yurt buildings;

[0007] Obtain meteorological data from the meteorological department for the city where the yurt is located, obtain indoor air design standard text data from the local planning department, obtain design scheme data for the yurt from the design unit, and obtain historical hourly electricity consumption data and coal consumption data for the yurt through the energy consumption monitoring system; upload and store the above data to the cloud SQL database management system.

[0008] Step S2: 3D simulation modeling of the tested yurt building and acquisition of microenvironment sample parameters;

[0009] The design data from step S1 is retrieved and entered into the architectural modeling software to perform a 3D physical model of the yurt under test, resulting in a 3D physical model. Simultaneously, a rotary-wing drone equipped with five tilting cameras is used to collect data at a flight altitude of 30m and automatically model the yurt and its surrounding urban environment within a 1km radius. This model is then integrated with the 3D physical model to construct a 3D simulation model of the yurt and its surrounding environment. An intelligent anemometer made of aluminum alloy with an accuracy of 0.02% FS is then attached to... At the junction of the tornado and uni in the tested yurt building, wind speed and direction were measured at fixed points every hour. Using an intelligent humidity and heat sensor with a measurement accuracy of ±0.5℃ and a measurement range of -30~60℃, temperature and humidity values ​​were measured at three locations in the tested yurt building every hour: the gap between the furnace and the tornado, the gap between the bottom of the felt and the ground, and 1.5m above the hana wall. The measurements were taken for the first 8 days of the heating season in January, the transition season in April, and the cooling season in July, for a total of 24 days, to obtain microenvironmental sample parameters of the tested yurt building.

[0010] Step S3: Construction of an intelligent training database for the indoor energy consumption of the yurt being measured.

[0011] Import the micro-environmental sample parameters of the tested yurt building obtained in step S2 as physical environment influence characteristics X1, including wind speed characteristics, wind direction characteristics, temperature characteristics, and humidity characteristics; calculate the yurt building morphological parameters as morphological influence characteristics X2, including overall air tightness characteristics, envelope thickness characteristics, and overall height-to-width ratio characteristics; import the electricity and coal consumption of the case yurt building every hour as historical energy consumption information Y, and construct an intelligent training database for indoor energy consumption of yurt buildings in the cloud SQL database management system;

[0012] Step S4: Intelligent calculation of indoor energy consumption in yurt buildings.

[0013] Import the physical environment impact characteristics, morphological impact characteristics, and historical energy consumption information from the intelligent training database for indoor energy consumption of yurt buildings in step S3. Standardize the data, then reorganize the input data, train it using a convolutional neural network algorithm, and construct an intelligent calculation model for indoor energy consumption of yurt buildings using the mean absolute percentage error method. Finally, place the target building into the three-dimensional simulation model in step S2, calculate its physical environment impact characteristic value based on the micro-environment sample parameters, input the characteristic value into the intelligent calculation model for indoor energy consumption of yurt buildings, intelligently generate hourly electricity consumption data and coal consumption data for indoor energy consumption of yurt buildings, and upload them to the cloud-based Mongolian Zero Carbon Building Data Platform.

[0014] Step S5: Intelligent grid construction and automatic adjustment of indoor energy consumption in yurt buildings.

[0015] Construct a 1m×1m×1m smart grid to divide the target building and ensure that the smart grid completely covers the three-dimensional shape of the target building. Number each smart grid and enter it into the zero-carbon building data platform. Set energy consumption thresholds based on the building's indoor lighting standard data and indoor space design text data. Monitor the indoor energy consumption of the yurt building in real time and compare it with the threshold. If the monitored energy consumption value is greater than the energy consumption threshold, the smart grid will be automatically adjusted through the zero-carbon building data platform until the monitored energy consumption value is less than or equal to the energy consumption threshold.

[0016] Step S6: Visual display of indoor energy consumption in the yurt building.

[0017] The cloud-based Mongolian zero-carbon building data platform is linked to a large visualization screen to display in real time a 3D simulation model of the yurt building, as well as intelligent grids, indoor personnel status, physical environment conditions, and real-time monitoring of building energy consumption.

[0018] Preferably, the meteorological data in step S1 refers to the outdoor meteorological data of the city where the yurt is located, including geographical location latitude and longitude, date, surface temperature, all-sky ground shortwave downward irradiance, all-sky surface photosynthetically active radiation, and relative humidity at two meters, and the data is stored in CSV format; the standard text data refers to indoor air design standard data, including the indoor design temperature for heating in main rooms in cold and frigid regions, the air conditioning design parameters for heating conditions in areas where people stay for a long time, and the air conditioning design parameters for cooling conditions in areas where people stay for a long time, and the data is stored in TXT format; the design scheme data refers to the plan and elevation drawings of the yurt, including the bottom diameter of the yurt, the height of the khana wall, the number of uni poles, the diameter of the uni poles, the length of the uni poles, the diameter of the toon, the door height, the door width, the number of columns, the column diameter, the column height (height of the bottom edge of the toon), and the total height of the yurt, and the data is stored in DXF format.

[0019] Preferably, the process of embedding with the three-dimensional physical model in step S2 is as follows: extending the outer contour of the building outward by 3m to 5m as the boundary of the three-dimensional physical model, flattening the oblique photogrammetry data within the defined boundary, and superimposing the three-dimensional physical model onto the three-dimensional simulation model.

[0020] Preferably, the morphological parameters affecting the indoor energy consumption of the yurt building in step S3 include: building air tightness, measured by air change rate (ACH), which refers to the number of times the air inside the building is replaced in one hour, ACH = (Q / V) * 60, where Q represents the rate of air inflow or outflow inside the building (in m³ / h), V represents the volume of the building (in m³), ​​and 60 is a coefficient for converting the result to per hour; envelope thickness, measured by d, specifically d = felt thickness * quantity + air film thickness, where the air film thickness is a variable value; and height-to-width ratio, measured by D / H, where D = number of felt sheets * folded length / Π (in m), and H = vertical height of the felt sheet from the ground (in m).

[0021] Preferably, the standardization process in step S4 refers to using the 90th percentile of energy consumption as a baseline value, defining twice the baseline value as a reasonable energy consumption range, identifying data outside the range as outliers, deleting outliers, completing the data through linear interpolation, and then standardizing the data using the Min-Max method; wherein, the formula for standardizing the data using the Min-Max method is: .

[0022] Preferably, the intelligent energy consumption calculation model for yurt buildings in step S4 refers to reorganizing the input data into a two-dimensional matrix, using 80% of the data as the training set and 20% as the test set, and extracting and training features using a convolutional neural network (CNN) algorithm. When the mean absolute percentage error... When the minimum value is reached, an intelligent calculation model for indoor energy consumption of yurt buildings is constructed.

[0023] Preferably, in step S4, the hourly electricity consumption data and coal consumption data are converted and summed using one standard coal unit to obtain the hourly indoor energy consumption value and the total building energy consumption value of the yurt building over 24 hours.

[0024] Preferably, in step S5, the automatic adjustment of the smart grid is achieved by monitoring various energy consumption values ​​through a zero-carbon building data platform. When the energy consumption value exceeds the upper threshold or is less than the lower threshold, the data platform sends a command to adjust the corresponding rods within the grid, which are connected to the corresponding yurt building structure. When the coal energy consumption value is greater than the set upper threshold, the data platform sends a command to inflate the air film structure in the middle layer of the felt, increasing the overall thickness of the felt, and monitoring whether there are significant fluctuations in temperature, humidity, and light within the grid of the yurt building, thereby adjusting the rods within the corresponding grid.

[0025] Preferably, the visualization screen in step S6 includes: a 3D model module of the actual building, which visually displays the yurt building, the human-computer interaction visualization platform, and the presence of people inside; an intelligent sensing device module, which visually monitors the intelligent sensing devices and detects their operating status and functions; an energy consumption monitoring module, which monitors and statistically analyzes the fluctuations in electricity consumption, coal consumption, ventilation, and humidity data of each functional area inside the yurt building 24 hours a day; an intelligent grid real-time monitoring and early warning module, which alerts users by highlighting the grid when significant fluctuations in temperature, humidity, or light occur within it; and a human-computer interaction module, which allows users to customize monitoring and early warning thresholds and the adjustment range of the automatic adjustment device as needed. Beneficial effects

[0026] By acquiring yurt architectural design data from design firms and creating 3D physical models, and utilizing a rotary-wing drone equipped with five tilting cameras to automatically model the yurt and its surrounding urban environment at a 30m flight altitude, a 3D simulation model of the yurt and its surrounding environment was constructed. This model, taking into account the unique characteristics of the yurt—its mobility, detachability, special environment, and strong interaction with its surroundings—models both the building itself and its micro-environment, significantly enhancing the reliability and practicality of the 3D simulation model.

[0027] By installing aluminum alloy materials, an intelligent wind speed sensor with an accuracy of FS0.02%, and an intelligent humidity and heat sensor with a measurement accuracy of ±0.5℃ and a measurement range of -30~60℃ at the connection between the tornado and uni in the yurt building, at the interval between the furnace cylinder and the tornado, and at the gap between the bottom of the felt and the ground, high-precision and high-accuracy micro-environmental parameters of the yurt building can be obtained, which greatly improves the accuracy of energy consumption calculation of the yurt building.

[0028] By acquiring microenvironmental data X1 of the yurt building, analyzing the building's own form that affects energy consumption and quantifying it to obtain data X2, the specific quantification includes building air tightness, measured by air change rate (ACH), envelope thickness, measured by d, and height-to-width ratio, measured by D / H. The electricity and coal consumption of the case yurt building every hour is used as historical energy consumption data Y. The X1, X2, and Y data are imported into the cloud-based SQL database management system to construct an intelligent training database for indoor energy consumption of the yurt building. The database gathers comprehensive data affecting the energy consumption calculation of the yurt building, greatly improving the reliability of the calculation results.

[0029] By reorganizing the input data into a two-dimensional matrix, training and testing sets for intelligent energy consumption measurement are constructed. Features are extracted and trained using a convolutional neural network (CNN) algorithm, thus building an intelligent energy consumption measurement model for yurt buildings. This model innovatively utilizes a clipping neural network algorithm, and through error elimination and continuous feature extraction and training using the CNN algorithm, it can significantly improve the accuracy of indoor energy consumption measurement for yurt buildings. Attached Figure Description

[0030] Figure 1 is a flowchart of the present invention.

[0031] Figure 2 shows the installation location of the equipment for measuring the microenvironment of a yurt building.

[0032] Figure 3 shows the intelligent grid display for energy consumption regulation in Mongolian yurt buildings.

[0033] Figure 4 shows a large screen displaying the indoor energy consumption of a yurt building. The best embodiment of the present invention

[0034] As shown in Figures 1 to 4, the intelligent calculation method for indoor energy consumption of a Mongolian yurt building under zero-carbon conditions according to the present invention specifically includes the following steps:

[0035] Step S1: Constructing the database of the tested yurt buildings.

[0036] Obtain meteorological data from the meteorological department for the city where the yurt is located, obtain indoor air design standard text data from the local planning department, obtain design scheme data for the yurt from the design unit, and obtain historical hourly electricity consumption data and coal consumption data for the yurt through the energy consumption monitoring system; upload and store the above data to the cloud SQL database management system.

[0037] The meteorological data refers to the outdoor meteorological data of the city where the yurt is located, including geographical location (latitude and longitude), date, surface temperature, total sky surface shortwave downward irradiance, total sky surface photosynthetically active radiation, and relative humidity at two meters. The data is stored in CSV format. The standard text data refers to indoor air design standard data, including the indoor design temperature for heating in main rooms in cold and frigid regions, air conditioning design parameters for heating and cooling in areas where people stay for extended periods, and air conditioning design parameters for cooling in areas where people stay for extended periods. The data is stored in TXT format. The design scheme data refers to the floor plan and elevation drawings of the yurt, including the bottom diameter of the yurt, the height of the khana wall, the number of uni poles, the diameter of the uni poles, the length of the uni poles, the diameter of the toon, the door height, the door width, the number of columns, the column diameter, the column height (height of the bottom edge of the toon), and the total height of the yurt. The data is stored in DXF format.

[0038] Step S2: 3D simulation modeling of the tested yurt and acquisition of microenvironment sample parameters.

[0039] The design data from step S1 was retrieved and entered into the architectural modeling software to create a 3D physical model of the yurt. Simultaneously, a rotary-wing drone equipped with five tilting cameras was used to collect data at a flight altitude of 30m and automatically model the yurt and its surrounding urban environment within a 1km radius. This model was then integrated with the 3D physical model to construct a 3D simulation model of the yurt and its surrounding environment. An aluminum alloy smart anemometer with an accuracy of FS0.02% was attached to the connection between the furnace and the uni (heater tube) of the yurt, measuring wind speed and direction at fixed points every hour. A smart humidity sensor with a measurement accuracy of ±0.5℃ and a measurement range of -30~60℃ was used to measure temperature and humidity at three locations on the yurt every hour: the gap between the furnace and the furnace, the gap between the bottom of the felt and the ground, and a height of 1.5m above the hana wall. Measurements were taken for the first eight days of the heating season (January), the transition season (April), and the cooling season (July), totaling 24 days, to obtain microenvironmental sample parameters for the yurt.

[0040] The process of embedding the three-dimensional physical model includes defining the boundary of the three-dimensional physical model as the building's outer contour extending outward by 3m, then flattening the oblique photogrammetry data within the defined boundary, and then overlaying the three-dimensional physical model onto the three-dimensional simulation model.

[0041] Step S3: Construction of an intelligent training database for the indoor energy consumption of the yurt being measured.

[0042] Import the micro-environmental sample parameters of the yurt building obtained in step S2 as physical environment influence feature X1, including wind speed, wind direction, temperature and humidity features; calculate the morphological parameters of the yurt building as morphological influence feature X2, including overall air tightness, envelope thickness and overall height-to-width ratio; import the electricity and coal consumption of the case yurt building every hour as historical energy consumption information Y, and construct the intelligent training database of indoor energy consumption of the yurt building in the cloud SQL database management system.

[0043] The calculation of morphological parameters affecting indoor energy consumption in yurt buildings specifically includes:

[0044] Building airtightness is measured by the air change rate (ACH), which refers to the number of times the air inside a building is replaced in one hour. ACH = (Q / V) * 60, where Q represents the rate of air inflow or outflow (in m³ / h), V represents the building volume (in m³), ​​and 60 is a coefficient to convert the result to per hour. Envelope thickness is measured by d, specifically d = felt thickness * number of sheets + air film thickness, where the air film thickness is a variable value. Aspect ratio is measured by D / H, where D = number of Hanna sheets * folded length / Π (in meters), and H = vertical height of the felt from the ground (in meters).

[0045] Step S4: Intelligent calculation of indoor energy consumption in yurt buildings.

[0046] Import the physical environment impact characteristics, morphological impact characteristics, and historical energy consumption information from the intelligent training database for indoor energy consumption of yurt buildings in step S3. Standardize the data, then reorganize the input data, train it using a convolutional neural network (CNN) algorithm, and construct an intelligent calculation model for indoor energy consumption of yurt buildings using the mean absolute percentage error (MAPE) method. Finally, place the target building into the three-dimensional simulation model in step S2, calculate its physical environment impact characteristic value based on micro-environment sample parameters, input the characteristic value into the intelligent calculation model for indoor energy consumption of yurt buildings, intelligently generate hourly electricity consumption data and coal consumption data for indoor energy consumption of yurt buildings, and upload them to the cloud-based Mongolian zero-carbon building data platform.

[0047] The standardization process involves using the 90th percentile of energy consumption as a baseline, defining a reasonable energy consumption range as twice the baseline, identifying data outside this range as outliers, deleting outliers, performing linear interpolation to complete the data, and then standardizing the data using the Min-Max method. The formula for Min-Max data standardization is as follows: ;

[0048] The intelligent energy consumption calculation model for yurt buildings is implemented as follows:

[0049] The input data was reorganized into a two-dimensional matrix as shown in Table 1. 80% of the data was used as the training set, and 20% as the test set. Features were extracted and trained using a convolutional neural network algorithm, with the mean absolute percentage error (MAE) used as the benchmark. As a model evaluation index, an intelligent calculation model for indoor energy consumption of yurt buildings is constructed, where y represents the actual energy consumption value. This is a predicted energy consumption value;

[0050] Table 1 Two-dimensional matrix table

[0051]

[0052] The hourly electricity consumption data and coal consumption data are converted and summed using one standard coal unit to obtain the hourly indoor energy consumption value and the total building energy consumption value of the yurt building over 24 hours, respectively.

[0053] Step S5: Intelligent grid construction and automatic adjustment of indoor energy consumption in yurt buildings.

[0054] Construct a 1m×1m×1m smart grid to divide the target building and ensure that the smart grid completely covers the three-dimensional shape of the target building. Number each smart grid and enter it into the zero-carbon building data platform. Set energy consumption thresholds based on the building's indoor lighting standard data and indoor space design text data. Monitor the indoor energy consumption of the yurt building in real time and compare it with the threshold. If the monitored energy consumption value is greater than the energy consumption threshold, the smart grid will be automatically adjusted through the zero-carbon building data platform until the monitored energy consumption value is less than or equal to the energy consumption threshold.

[0055] The intelligent grid automatic adjustment system monitors various energy consumption values ​​through a zero-carbon building data platform. When the energy consumption value exceeds the upper threshold or falls below the lower threshold, the data platform sends a command to adjust the corresponding rods within the grid, which are connected to the corresponding yurt building structure. When the coal energy consumption value exceeds the set upper threshold, the data platform sends a command to inflate the air-supported membrane structure in the middle layer of the yurt, increasing the overall thickness of the yurt. It also monitors whether there are significant fluctuations in temperature, humidity, and light within the grids of the yurt building and adjusts the rods within the corresponding grids accordingly.

[0056] Step S6: Visual display of indoor energy consumption in the yurt building.

[0057] Link the cloud-based Mongolian zero-carbon building data platform to a large visualization screen to display the 3D simulation model of the Mongolian yurt building, as well as the intelligent grid, the status of people inside, the physical environment, and the real-time monitoring of building energy consumption in real time.

[0058] The visualization screen includes: a 3D model module of the actual building, which visually displays the yurt architecture, the human-computer interaction visualization platform, and the presence of people inside; an intelligent sensing device module, which visually monitors intelligent sensing devices and detects their operating status and functions; an energy consumption monitoring module, which monitors and statistically analyzes the fluctuations in electricity consumption, coal consumption, ventilation, and humidity data of each functional area inside the yurt 24 hours a day; an intelligent grid real-time monitoring and early warning module, which alerts users when significant fluctuations in temperature, humidity, or light occur within a grid by highlighting that grid; and a human-computer interaction module, which allows users to customize monitoring and early warning thresholds and the adjustment range of the automatic adjustment device as needed.

Claims

1. A method for intelligently calculating indoor energy consumption of yurt buildings under zero-carbon conditions, characterized in that, The method includes the following steps: Step S1: Construction of the database of the tested Mongolian yurt buildings; Obtain meteorological data from the meteorological department for the city where the yurt is located, obtain indoor air design standard text data from the local planning department, obtain design scheme data for the yurt from the design unit, and obtain historical hourly electricity consumption data and coal consumption data for the yurt through the energy consumption monitoring system; upload and store the above data to the cloud SQL database management system. Step S2: 3D simulation modeling of the tested yurt building and acquisition of microenvironment sample parameters; The design data from step S1 is retrieved and entered into the architectural modeling software to perform a 3D physical model of the yurt under test, resulting in a 3D physical model. Simultaneously, a rotary-wing drone equipped with five tilting cameras is used to collect data at a flight altitude of 30m and automatically model the yurt and its surrounding urban environment within a 1km radius. This model is then integrated with the 3D physical model to construct a 3D simulation model of the yurt and its surrounding environment. An intelligent anemometer made of aluminum alloy with an accuracy of 0.02% FS is then attached to... At the junction of the tornado and uni in the tested yurt building, wind speed and direction were measured at fixed points every hour. Using an intelligent humidity and heat sensor with a measurement accuracy of ±0.5℃ and a measurement range of -30 to 60℃, temperature and humidity values ​​were measured at three locations in the tested yurt building every hour: the gap between the furnace and the tornado, the gap between the bottom of the felt and the ground, and 1.5m above the hana wall. The measurements were taken for the first 8 days of the heating season in January, the transition season in April, and the cooling season in July, for a total of 24 days, to obtain microenvironmental sample parameters of the tested yurt building. Step S3: Construction of an intelligent training database for the indoor energy consumption of the yurt being measured. Import the micro-environmental sample parameters of the tested yurt building obtained in step S2 as physical environment influence characteristics X1, including wind speed characteristics, wind direction characteristics, temperature characteristics, and humidity characteristics; calculate the yurt building morphological parameters as morphological influence characteristics X2, including overall air tightness characteristics, envelope thickness characteristics, and overall height-to-width ratio characteristics; import the electricity and coal consumption of the case yurt building every hour as historical energy consumption information Y, and construct an intelligent training database for indoor energy consumption of yurt buildings in the cloud SQL database management system; Step S4: Intelligent calculation of indoor energy consumption in yurt buildings. Import the physical environment impact characteristics, morphological impact characteristics, and historical energy consumption information from the intelligent training database for indoor energy consumption of yurt buildings in step S3. Standardize the data, then reorganize the input data, train it using a convolutional neural network algorithm, and construct an intelligent calculation model for indoor energy consumption of yurt buildings using the mean absolute percentage error method. Finally, place the target building into the three-dimensional simulation model in step S2, calculate its physical environment impact characteristic value based on the micro-environment sample parameters, input the characteristic value into the intelligent calculation model for indoor energy consumption of yurt buildings, intelligently generate hourly electricity consumption data and coal consumption data for indoor energy consumption of yurt buildings, and upload them to the cloud-based Mongolian Zero Carbon Building Data Platform. Step S5: Intelligent grid construction and automatic adjustment of indoor energy consumption in yurt buildings. A 1m×1m×1m smart grid is constructed to divide the target building, ensuring the grid completely covers its three-dimensional shape. Each smart grid is labeled and entered into the zero-carbon building data platform. Energy consumption thresholds are set based on building interior lighting standards and interior space design data. The indoor energy consumption of the yurt building is monitored in real time and compared against the threshold. If the monitored energy consumption value exceeds the threshold, the smart grid is automatically adjusted via the zero-carbon building data platform until the monitored energy consumption value is less than or equal to the threshold. In step S5, the automatic... The intelligent grid adjustment system monitors various energy consumption values ​​through a zero-carbon building data platform. When the energy consumption value exceeds the upper threshold or falls below the lower threshold, the data platform sends a command to adjust the corresponding rods within the grid, which are connected to the corresponding yurt building structure. When the coal energy consumption value exceeds the set upper threshold, the data platform sends a command to inflate the air-film structure in the middle layer of the felt, increasing the overall thickness of the felt, and monitors whether there are significant fluctuations in temperature, humidity, and light within the grids of the yurt building, adjusting the rods within the corresponding grids accordingly. Step S6: Visual display of indoor energy consumption in the yurt building. The cloud-based Mongolian zero-carbon building data platform is linked to a large visualization screen to display in real time a 3D simulation model of the yurt building, as well as intelligent grids, indoor personnel status, physical environment conditions, and real-time monitoring of building energy consumption.

2. The intelligent calculation method for indoor energy consumption of yurt buildings under zero-carbon conditions according to claim 1, characterized in that, The meteorological data in step S1 refers to the outdoor meteorological data of the city where the yurt is located, including geographical location latitude and longitude, date, surface temperature, total sky surface shortwave downward irradiance, total sky surface photosynthetically active radiation, and relative humidity at two meters. The data is stored in CSV format. The standard text data refers to indoor air design standard data, including the indoor design temperature for heating in main rooms in severely cold and cold regions, air conditioning design parameters for heating and cooling in areas where people stay for extended periods, and air conditioning design parameters for cooling in areas where people stay for extended periods. The data is stored in TXT format. The design scheme data refers to the floor plan and elevation drawings of the yurt, including the bottom diameter of the yurt, the height of the khana wall, the number of uni poles, the diameter of the uni poles, the length of the uni poles, the diameter of the tornado, the door height, the door width, the number of columns, the diameter of the columns, the height of the columns, and the total height of the yurt. The data is stored in DXF format.

3. The intelligent calculation method for indoor energy consumption of yurt buildings under zero-carbon conditions according to claim 1, characterized in that, The process of embedding the three-dimensional physical model in step S2 is as follows: extending the outer contour of the building outward by 3m to 5m as the boundary of the three-dimensional physical model, flattening the oblique photogrammetry data within the defined boundary, and superimposing the three-dimensional physical model onto the three-dimensional simulation model.

4. The intelligent calculation method for indoor energy consumption of yurt buildings under zero-carbon conditions according to claim 1, characterized in that, Step S3 calculates the morphological parameters affecting the indoor energy consumption of the yurt building, including: building airtightness, measured by the air change rate (ACH), which refers to the number of times the air inside the building is replaced in one hour, ACH = (Q / V) * 60, where Q represents the rate of air inflow or outflow inside the building in m³ / h; V represents the volume of the building in m³; and 60 is a coefficient for converting the result to per hour; envelope thickness, measured by d, specifically d = felt thickness * quantity + air film thickness, where the air film thickness is a variable value; and aspect ratio, measured by D / H, where D = number of felt sheets * folded length / Π in meters; and H = vertical height of the felt sheet from the ground in meters.

5. The intelligent calculation method for indoor energy consumption of yurt buildings under zero-carbon conditions according to claim 1, characterized in that, The standardization process in step S4 involves using the 90th percentile of energy consumption as a baseline value, defining twice the baseline value as a reasonable energy consumption range, identifying data outside this range as outliers, deleting outliers, performing linear interpolation to complete the data, and then standardizing the data using the Min-Max method. The formula for standardizing the data using the Min-Max method is as follows: .

6. The intelligent calculation method for indoor energy consumption of yurt buildings under zero-carbon conditions according to claim 1, characterized in that, The intelligent energy consumption calculation model for yurt buildings in step S4 refers to reorganizing the input data into a two-dimensional matrix, using 80% of the data as the training set and 20% as the test set, and extracting and training features using a convolutional neural network (CNN) algorithm. When the mean absolute percentage error... When the minimum value is reached, an intelligent calculation model for indoor energy consumption of yurt buildings is constructed.

7. The intelligent calculation method for indoor energy consumption of yurt buildings under zero-carbon conditions according to claim 1, characterized in that, In step S4, the hourly electricity consumption data and coal consumption data are converted and summed using one standard coal unit to obtain the hourly indoor energy consumption value and the total building energy consumption value of the yurt building over 24 hours.

8. The intelligent calculation method for indoor energy consumption of yurt buildings under zero-carbon conditions according to claim 1, characterized in that, The visualization screen in step S6 includes: a 3D model module of the actual building, which visually displays the yurt building, the human-computer interaction visualization platform, and the situation of people inside; an intelligent sensing device module, which visually monitors the intelligent sensing devices and detects their operating status and functions; and an energy consumption monitoring module, which monitors and statistically analyzes the fluctuations of electricity consumption, coal consumption, ventilation data, and humidity data in each functional area inside the yurt building 24 hours a day. The intelligent grid real-time monitoring and early warning module is designed to alert a grid by highlighting it when there are significant fluctuations in temperature, humidity, or light intensity within the grid. The human-computer interaction module allows users to customize monitoring and early warning thresholds and adjust the range of automatic adjustment devices as needed.

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