A method and system for real-time optimization and control of building energy consumption based on digital twins

Abstract

This invention belongs to the field of building energy consumption control technology. It provides a method and system for real-time optimization and control of building energy consumption based on digital twins. The method includes: simulating and monitoring the building envelope within a constructed three-dimensional indoor model; monitoring the temperature within the envelope in real time during each simulation monitoring cycle; identifying temperature difference change periods; performing temperature difference change trend and duration stability analysis for each temperature difference change period; and evaluating whether the temperature difference change period within the envelope is stable in each simulation monitoring cycle. The purpose is to: by acquiring information on temperature difference change periods, monitor and predict indoor temperature change trends in real time, and adjust the operating parameters of the air conditioning system in a timely manner to keep the indoor temperature within a comfortable range.

Description

Technical Field

[0001] This invention belongs to the field of building energy consumption control technology, specifically a method and system for real-time optimization and control of building energy consumption based on digital twins. Background Technology

[0002] With the acceleration of urbanization and the booming development of the construction industry, building energy consumption accounts for an increasingly larger proportion of total social energy consumption. Statistics show that building energy consumption already accounts for a significant portion of global energy consumption and continues to rise. This not only puts enormous pressure on energy supply but also triggers serious environmental problems, such as increased greenhouse gas emissions and exacerbated air pollution. Therefore, how to effectively reduce building energy consumption and achieve green and sustainable development of buildings has become a critical issue that urgently needs to be addressed in the construction sector.

[0003] Most existing building energy consumption monitoring systems can only perform simple real-time monitoring of indoor temperature, lacking in-depth analysis of temperature difference changes in the building envelope. Furthermore, they cannot accurately identify the time periods of temperature difference changes, nor can they effectively assess the trend and duration stability of temperature difference changes. This results in the inability to detect abnormal changes in the thermal performance of the building envelope in a timely manner, making it difficult to take targeted energy consumption control measures, thus affecting the effectiveness of building energy consumption control.

[0004] Secondly, due to the uncertainty of the intensity and temporal distribution of solar radiation, the heat storage and release delay time is a key parameter in the process of solar radiation heat storage and release, which directly affects the changes in indoor energy consumption and the formulation of energy consumption control strategies. However, existing technical methods are difficult to accurately obtain the heat storage and release delay time, and cannot carry out precise energy consumption control based on the actual situation of the building envelope.

[0005] To this end, the present invention provides a method and system for real-time optimization and control of building energy consumption based on digital twins. Summary of the Invention

[0006] In order to overcome the shortcomings of the prior art, at least one technical problem raised in the background art is solved.

[0007] The technical solution adopted by this invention to solve its technical problem is:

[0008] The first aspect is a real-time optimization and control method for building energy consumption based on digital twins, including:

[0009] The enclosure area within the constructed indoor 3D model is simulated and monitored. During each simulation monitoring cycle, the temperature within the enclosure area is monitored in real time, and the time periods of temperature difference change are selected.

[0010] For each period of temperature difference change in the enclosure, the trend of temperature difference change and the stability of temperature difference change duration were analyzed to assess whether the temperature difference change period in the enclosure area was stable in each simulated monitoring cycle.

[0011] If the temperature difference changes during a period of instability, the temperature difference changes during each simulation monitoring period of the enclosure area will be analyzed to determine whether the heat load type in the enclosure area is solar radiation heat storage and release.

[0012] If the heat load type within the building envelope is solar radiation heat storage and release, then the heat storage and release delay time is obtained, and the indoor energy consumption is optimized and controlled in real time.

[0013] A further aspect of this invention is the real-time monitoring of the temperature within the enclosure area, as follows:

[0014] The simulation monitoring period is divided into several simulation monitoring points. The temperature of the enclosure material in the enclosure area at each simulation monitoring point during the simulation monitoring period is obtained. If the temperature difference value is positive or zero, the simulation monitoring point is marked as the starting point of the temperature difference change. All the temperature difference values ​​from the starting point of the temperature difference change to the last simulation monitoring point in the simulation monitoring period are extracted to construct the temperature difference change curve.

[0015] Extract the inflection point on the temperature difference change curve, take the local change curve from the starting point coordinates to the inflection point coordinates as the growth analysis curve, and take the local change curve from the inflection point coordinates to the ending point coordinates as the fitting analysis curve.

[0016] Connect the starting point coordinates and the inflection point coordinates of the growth analysis curve with a straight line to obtain the fitted growth analysis line. Use the slope calculation formula to obtain the slope corresponding to the fitted growth analysis line. If it is positive, the overall trend of the fitted growth analysis line is growth. Combine the inflection point coordinates with the coordinates of any simulated monitoring point on the fitted analysis curve multiple times to obtain the local curve of stability analysis.

[0017] As a further aspect of the present invention, the screening process for the temperature difference change period is as follows:

[0018] Extract the monitoring temperature difference value corresponding to each simulated monitoring point on the local curve of stability analysis, calculate the standard deviation, and output the temperature difference standard deviation value. If the temperature difference standard deviation value is less than or equal to the temperature difference standard deviation threshold, the local curve of stability analysis is marked as a temperature difference stable curve.

[0019] The temperature difference standard deviation values ​​corresponding to each temperature difference stability curve are compared, and the temperature difference stability curve corresponding to the smallest temperature difference standard deviation value is selected. The time period between the simulated monitoring points corresponding to the starting point coordinates and the ending point coordinates on the temperature difference stability curve is taken as the temperature difference change period.

[0020] A further aspect of this invention is as follows: Extracting the time periods of temperature difference variation within each simulated monitoring cycle, and performing temperature difference trend analysis, as follows:

[0021] Extract the growth analysis curve and temperature difference stability curve for each period of temperature difference change in the enclosure. Combine the growth analysis curve and temperature difference stability curve for any two simulated monitoring periods to obtain the growth trend comparison group and the temperature difference stability comparison group.

[0022] The slopes of the growth trend comparison group and the temperature difference stability comparison group are subtracted, and the absolute values ​​are taken to obtain the growth trend comparison sub-value and the stability trend comparison sub-value.

[0023] Calculate the standard deviation of the stable trend comparison sub-values ​​corresponding to each group of temperature difference stable comparison groups, and output the stable trend comparison value.

[0024] The temperature difference trend analysis value is obtained by summing the growth trend comparison value and the stable trend comparison value.

[0025] A further aspect of this invention is as follows: Extracting the time periods of temperature difference changes within each simulated monitoring cycle, and performing a stability analysis of the duration of temperature difference changes, as follows:

[0026] The ratio of the duration of each period of temperature difference change in the enclosure to the duration of the simulated monitoring cycle is calculated, and the ratio of the duration of temperature difference in the enclosure is output.

[0027] Input the duration ratio of the enclosure temperature difference corresponding to any simulated monitoring cycle into the Euclidean distance formula, and output the enclosure temperature difference duration difference value.

[0028] A further aspect of this invention is: assessing whether the temperature difference variation in the enclosure area remains stable during each simulated monitoring cycle, the process of which is as follows:

[0029] The temperature difference trend analysis value is summed with the temperature difference duration difference value of the enclosure to obtain the temperature change stability value. If the temperature change stability value is greater than the temperature change stability threshold, it is displayed as a temperature difference change fluctuation signal.

[0030] As a further aspect of the present invention, the process of analyzing the temperature difference changes in the enclosure area during each simulation monitoring cycle is as follows:

[0031] The time periods corresponding to the growth analysis curve and the local curves of the stability analysis are extracted respectively as the heat storage period and the heat release period of the enclosure.

[0032] Within the simulated monitoring period, the simulated solar peak radiation period and solar valley radiation period are obtained. The starting time points of the solar peak radiation period and solar valley radiation period, as well as the starting time points of the enclosure heat storage period and enclosure heat release period, are extracted respectively. The difference between the corresponding starting time points is calculated, and the absolute value is taken to obtain the radiation storage start time difference value and the radiation release start time difference value. The sum is then calculated to obtain the start time difference value. The standard deviation of the start time difference value corresponding to each simulated monitoring period is calculated, and the start time difference value is output.

[0033] The termination times of the solar peak radiation period and the solar peak radiation period, as well as the termination times of the enclosure heat storage period and the enclosure heat release period, are extracted separately. The differences between the termination times are calculated, and the absolute values ​​are taken to obtain the solar peak radiation storage end time difference and the solar peak radiation release end time difference. These are then summed to output the end time difference value. The standard deviation of the end time difference value corresponding to each simulation monitoring cycle is calculated to output the end time difference value.

[0034] A further aspect of this invention is as follows: determining whether the heat load type within the enclosure area is solar radiation heat storage and release, the process is as follows:

[0035] The start time difference value and the end time difference value are summed to obtain the time period overlap value. If the time period overlap value is less than or equal to the time period overlap threshold, it is displayed as a solar power storage and discharge signal.

[0036] A further aspect of the present invention is as follows: the process of obtaining the heat storage release delay time and optimizing and controlling indoor energy consumption in real time is as follows:

[0037] The duration of the heat release period of the enclosure within each simulation monitoring cycle is extracted as the unit heat release delay time. The longest and shortest unit heat release delay times are selected, and the summation and average are calculated to output the heat storage release delay time.

[0038] The inflection point on the temperature difference change curve is taken as the starting point of energy consumption control, and summed with the heat storage release delay time to obtain the real-time energy consumption control period. The monitored temperature difference values ​​within the heat release period of the enclosure are extracted and summed to obtain the average temperature difference of the unit period. The magnitudes are compared, and the average temperature difference of the largest and smallest unit period is taken as the temperature adjustment range.

[0039] Secondly, the building energy consumption real-time optimization and control system based on digital twins includes the following modules:

[0040] Time Period Filtering Module: Simulates and monitors the enclosure area within the constructed indoor 3D model. During each simulation monitoring cycle, the temperature within the enclosure area is monitored in real time, and time periods of temperature difference changes are filtered out.

[0041] Stability assessment module: Performs temperature difference change trend and temperature difference change duration stability analysis for each period of temperature difference change in the enclosure, and assesses whether the temperature difference change period of the enclosure area is stable in each simulated monitoring cycle;

[0042] Storage and release analysis module: If the temperature difference change period is unstable, the temperature difference change period corresponding to each simulation monitoring cycle of the enclosure area will be analyzed to determine whether the heat load type in the enclosure area is solar radiation heat storage and release.

[0043] Real-time optimization control module: If the heat load type in the building envelope is solar radiation heat storage and release, the heat storage and release delay time is obtained, and the indoor energy consumption is optimized and controlled in real time.

[0044] The beneficial effects of this invention are as follows:

[0045] 1. This invention simulates and monitors the building envelope within a constructed 3D indoor model. During each simulation monitoring cycle, the temperature within the envelope is monitored in real time. Temperature difference change periods are selected, and the temperature difference change trend and duration stability analysis are performed for each temperature difference change period. This assesses whether the temperature difference change period within the envelope is stable in each simulation monitoring cycle. The purpose is that during stable temperature difference change periods, the system can accurately predict the building's energy demand at different times, prioritizing energy allocation to critical equipment. Furthermore, since changes in heat transfer within the building envelope can easily lead to indoor temperature fluctuations, the digital twin system, by acquiring information on temperature difference change periods, can monitor and predict indoor temperature trends in real time and adjust the operating parameters of the air conditioning system accordingly, ensuring that the indoor temperature remains within a comfortable range.

[0046] 2. If the temperature difference change period of the enclosed area in each simulated monitoring cycle is unstable, the present invention analyzes the temperature difference change period of the enclosed area in each simulated monitoring cycle to determine whether the heat load type in the enclosed area is solar radiation heat storage and release. If the heat load type in the enclosed area is solar radiation heat storage and release, the heat storage and release delay time is obtained, and the indoor energy consumption is optimized and controlled in real time. Thus, based on the monitored temperature difference value and temperature adjustment range in the current heat release period of the enclosed area, the over-operation or under-operation of the equipment can be avoided, the operating efficiency of the equipment can be improved, and energy waste can be reduced. Attached Figure Description

[0047] The invention will now be further described with reference to the accompanying drawings.

[0048] Figure 1 This is a flowchart of the steps of the real-time optimization and control method for building energy consumption based on digital twins in this invention;

[0049] Figure 2This is a flowchart of the decision-making process in the real-time optimization control of building energy consumption based on digital twins in this invention;

[0050] Figure 3 This is a schematic diagram of the real-time building energy consumption optimization control system based on digital twins according to the present invention. Detailed Implementation

[0051] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments.

[0052] Example 1

[0053] In summer, when solar radiation (or high outdoor temperatures) acts on building envelopes (such as double-glazed windows or concrete columns), these materials do not immediately transfer heat to the interior like a funnel. Instead, they retain heat like a reservoir. For example, between 12 PM and 2 PM in summer, when the sun shines directly on south-facing double-glazed windows: the temperature on the outside (outdoor) side may reach over 35°C, while the inside (indoor) side is maintained at 26°C due to air conditioning. At this time, the sun's heat is first absorbed by the outer layer of the glass, the middle air layer, and the inner glass layer—the glass itself gradually rises from 26°C to 30°C or even higher. However, during this process, only a small amount of heat is immediately transferred to the interior; most of the heat is stored within the glass material itself. When a temperature difference exists (the difference between the temperature of the building envelope material and the temperature of the environment on the other side it contacts—for example, the inner side of the glass contacts indoor air, and the outer side contacts outdoor air, the temperature difference is the glass temperature)... Indoor or outdoor temperature - glass temperature; the temperature difference between a concrete column and indoor air is column temperature - indoor temperature. Therefore, for the real-time building energy consumption optimization and control method based on digital twins described in this invention, please refer to [link to relevant documentation]. Figure 1 - Figure 2 As shown, it includes the following steps:

[0054] Step 1: Based on the 3D drawings of the interior building, use digital twin technology to simulate and construct an interior 3D model, extract the enclosure area within the interior 3D model, set multiple simulation monitoring cycles, and monitor the temperature within the enclosure area in real time during each simulation monitoring cycle to identify periods of temperature difference changes.

[0055] In some embodiments, the process of simulating the construction of an indoor 3D model and extracting the enclosure area is as follows:

[0056] The parameters in the 3D model of the interior building are input into the digital twin technology to convert the 3D model into an interior 3D model and extract the enclosure area within the interior 3D model.

[0057] It should be noted that the enclosure area includes the enclosure material itself, the outdoor enclosure area, and the indoor enclosure area. The indoor enclosure area includes the area near the windows (double glazing) and the area near the columns (concrete columns).

[0058] The selection method for periods of temperature variation is as follows:

[0059] For example, the simulated monitoring period is divided into several simulated monitoring points, wherein the duration between adjacent simulated monitoring points is equal;

[0060] The temperature of the enclosure material (surface temperature of glass or concrete column) and the indoor temperature of the enclosure are obtained at each simulated monitoring point during the simulated monitoring period, and the difference is calculated to obtain the monitored temperature difference value.

[0061] If the monitored temperature difference is negative, it means that at the simulated monitoring point being analyzed, the temperature of the building envelope material does not meet the conditions for releasing heat into the room.

[0062] If the monitored temperature difference is positive or zero, it indicates that at the analyzed simulated monitoring point, the temperature of the building envelope material is capable of releasing heat into the room, and the simulated monitoring point is marked as the starting point of the temperature difference change.

[0063] Extract all monitored temperature difference values ​​from the starting point of the temperature difference change to the last simulated monitoring point within the simulated monitoring period, and input them into a two-dimensional coordinate system, with the X-axis representing time and the Y-axis representing the temperature difference value, to construct a temperature difference change curve;

[0064] Extract the inflection point on the temperature difference change curve, and use the local change curve from the starting point coordinates to the inflection point coordinates as the growth analysis curve;

[0065] The local variation curve from the inflection point coordinate of the temperature difference change curve to the end point coordinate of the temperature difference change curve is used as the fitting analysis curve.

[0066] Connect the starting point coordinates and the ending point coordinates (inflection point coordinates) of the growth analysis curve with a straight line to obtain the fitted growth analysis line;

[0067] The slope of the fitted growth analysis line is obtained by using the slope calculation formula. If it is positive, it means that the overall trend of the fitted growth analysis line from the starting point coordinate on the temperature difference curve to the inflection point on the temperature difference curve is growth. If it is negative, it means that the overall trend of the fitted growth analysis line from the starting point coordinate on the temperature difference curve to the inflection point on the temperature difference curve is decline.

[0068] If the overall trend of the fitted growth analysis line is growth, then the coordinates of the inflection point and the coordinates of any simulated monitoring point on the fitted analysis curve are combined and intercepted multiple times to obtain the local curve of the stability analysis.

[0069] It should be noted that the rule for multiple combination and truncation is as follows: except for the inflection point coordinates, on the fitted analysis curve, the time sequence corresponding to each simulated monitoring point is iteratively combined with the inflection point coordinates in turn, and the corresponding temperature difference standard deviation value is obtained until the temperature difference standard deviation value is greater than the temperature difference standard deviation threshold, then the combination and truncation stops.

[0070] Extract the monitoring temperature difference value corresponding to each simulated monitoring point on the local curve of stability analysis, calculate the standard deviation, and output the standard deviation value of temperature difference;

[0071] If the standard deviation of temperature difference is greater than the standard deviation threshold of temperature difference, it indicates that the monitoring temperature difference value corresponding to each simulated monitoring point is relatively unstable on the local curve of the stability analysis.

[0072] If the standard deviation of temperature difference is less than or equal to the standard deviation threshold of temperature difference, it indicates that the temperature difference change corresponding to each simulated monitoring point is relatively stable on the local curve of stability analysis. In this case, the local curve of stability analysis is marked as the temperature difference stability curve.

[0073] The temperature difference standard deviation values ​​corresponding to each temperature difference stability curve are compared, and the temperature difference stability curve corresponding to the smallest temperature difference standard deviation value is selected. The time period between the simulated monitoring points corresponding to the starting point coordinates and the ending point coordinates on the temperature difference stability curve is taken as the temperature difference change period.

[0074] It should be noted that the purpose of selecting the time periods of temperature difference change is: from the perspective of equipment energy consumption operation, since the rate at which the building envelope transfers heat to the room changes during the time periods of temperature difference change, by obtaining the information of the time periods of temperature difference change, the digital twin system can reduce the operating time of the ventilation system or reduce the ventilation volume during the time periods of large temperature difference, so as to avoid unnecessary heat introduction.

[0075] Secondly, from the perspective of energy management, after obtaining information on temperature difference changes over time, the digital twin system can predict the building's energy demand in the future based on the characteristics of heat transfer in the building envelope at different times, and make reasonable energy allocation by analyzing the heat transfer situation of the building envelope at different times.

[0076] Finally, from the perspective of indoor comfort design, changes in heat transfer of the building envelope during periods of temperature difference can easily lead to fluctuations in indoor temperature. By acquiring information on periods of temperature difference, the digital twin system can monitor and predict the trend of indoor temperature changes in real time and adjust the operating parameters of the air conditioning system in a timely manner to keep the indoor temperature within a comfortable range.

[0077] Step 2: Perform temperature difference trend analysis and temperature difference duration stability analysis for each temperature difference change period of the enclosure to obtain temperature change stability value, and evaluate whether the temperature difference change period of the enclosure area is stable in each simulation monitoring cycle based on the temperature change stability value.

[0078] In some embodiments, the time periods of temperature difference change within the enclosure are extracted during each simulated monitoring cycle, and the trend analysis of temperature difference change is performed as follows:

[0079] Extract the growth analysis curve and temperature difference stability curve for each period of temperature difference change in the enclosure. Combine the growth analysis curve and temperature difference stability curve for any two simulated monitoring periods to obtain the growth trend comparison group and the temperature difference stability comparison group.

[0080] Within the growth trend comparison group, the slopes of the growth analysis curves within the simulated monitoring period are subtracted, and the absolute values ​​are taken to obtain the growth trend comparison sub-values.

[0081] Calculate the standard deviation of the growth trend comparison sub-values ​​corresponding to each group of growth trend comparison groups, and output the growth trend comparison value.

[0082] Similarly, within the temperature difference stability comparison group, the slopes of the temperature difference stability curves within the simulated monitoring period are subtracted, and the absolute value is taken to obtain the stability trend comparison sub-value.

[0083] Calculate the standard deviation of the stable trend comparison sub-values ​​corresponding to each group of temperature difference stable comparison groups, and output the stable trend comparison value.

[0084] The temperature difference trend analysis value is obtained by summing the growth trend comparison value and the stable trend comparison value.

[0085] The time periods of temperature difference variation within the enclosure were extracted during each simulated monitoring cycle, and the stability analysis of the duration of temperature difference variation was performed as follows:

[0086] The ratio of the duration of each period of temperature difference change in the enclosure to the duration of the simulated monitoring cycle is calculated, and the ratio of the duration of temperature difference in the enclosure is output.

[0087] Input the duration ratio of the enclosure temperature difference corresponding to any simulated monitoring cycle into the Euclidean distance formula, and output the enclosure temperature difference duration difference value.

[0088] The temperature change stability value is obtained by summing the temperature difference trend analysis value and the difference value of the temperature difference duration of the enclosure.

[0089] It is understandable that the meaning of the temperature change stability value is: the analysis and calculation of the temperature difference change trend and the stability of the temperature difference change duration during the period of temperature difference change in the building envelope within each simulation monitoring cycle. Specifically, on the one hand, the temperature difference trend analysis value reflects the similarity of the temperature difference change trend of the building envelope within different simulation monitoring cycles; on the other hand, the temperature difference duration difference value reflects the stability of the duration of the temperature difference change period in the building envelope within different simulation monitoring cycles.

[0090] If the temperature change stability value is greater than the temperature change stability threshold, it indicates that the duration of the temperature difference change period in the enclosure is relatively unstable in multiple simulation monitoring cycles, and the consistency of the temperature difference change trend is low, which is displayed as a temperature difference change fluctuation signal.

[0091] If the temperature change stability value is less than or equal to the temperature change stability threshold, it indicates that the duration of the temperature difference change period in the enclosure is relatively stable in multiple simulated monitoring cycles, and the temperature difference change trend is highly consistent, which is displayed as a stable temperature difference change signal.

[0092] The purpose of assessing the stability of temperature difference changes over time is primarily to more accurately grasp the patterns of heat transfer in the building envelope, thereby providing a reliable basis for real-time optimization and control of building energy consumption. Since changes in heat transfer in the building envelope directly affect indoor ambient temperature, which in turn affects the operation of building equipment and energy consumption, only by accurately assessing the stability of temperature difference changes over time can reasonable control strategies be formulated according to different situations to optimize building energy consumption.

[0093] From the perspective of optimizing energy consumption during equipment operation, during periods of stable and increasing temperature difference, the cooling capacity output of the air conditioning system can be adjusted in advance to keep the indoor temperature within a comfortable range, avoiding frequent start-ups and shutdowns of the air conditioning equipment due to excessive temperature fluctuations, thus reducing equipment wear and energy consumption. If the temperature difference is unstable, the system can dynamically adjust the response strategy of the air conditioning system according to the magnitude of the stable temperature change value, strengthening monitoring and control during periods of large changes and appropriately reducing the control frequency during periods of small changes, thereby improving the operating efficiency of the air conditioning system.

[0094] From the perspective of energy management and energy consumption optimization, during periods of stable temperature variation, the system can accurately predict the building's energy demand at different times and prioritize energy allocation to critical equipment. For example, air conditioning systems require more energy to maintain indoor temperature during high-temperature periods. During periods of instability, the system can dynamically adjust the energy allocation ratio based on the magnitude of temperature stability values. Furthermore, through data analysis of historical stable periods, the digital twin system can establish a more accurate energy consumption prediction model to predict the building's energy demand in the future. During periods of instability, the system can conduct risk assessments based on temperature stability values ​​and formulate corresponding emergency plans to ensure the stability of energy supply.

[0095] The specific solution in this embodiment is as follows: Simulation monitoring is performed on the building envelope within the constructed 3D indoor model. During each simulation monitoring cycle, the temperature within the building envelope is monitored in real time. Time periods of temperature difference variation are selected, and the trend and stability of temperature difference variation duration are analyzed for each temperature difference variation period. The stability of the temperature difference variation period within each simulation monitoring cycle is assessed. The purpose is that during stable temperature difference variation periods, the system can accurately predict the building's energy demand at different times and prioritize energy allocation to critical equipment. Furthermore, since changes in heat transfer within the building envelope can easily lead to indoor temperature fluctuations, the digital twin system, by acquiring information on temperature difference variation periods, can monitor and predict indoor temperature trends in real time and adjust the operating parameters of the air conditioning system accordingly, ensuring that the indoor temperature remains within a comfortable range.

[0096] Example 2

[0097] Please see Figure 1 - Figure 2 As shown in the embodiment of the present invention, the method for real-time optimization and control of building energy consumption based on digital twins includes the following steps:

[0098] Step 3: If the temperature difference change period of the enclosed area is unstable in each simulation monitoring cycle, analyze the temperature difference change period of the enclosed area in each simulation monitoring cycle to determine whether the heat load type in the enclosed area is solar radiation heat storage and release.

[0099] In some embodiments, the time periods corresponding to the growth analysis curve and the time periods corresponding to the local curve of the stability analysis are extracted respectively as the heat storage period and the heat release period of the enclosure.

[0100] Within the simulated monitoring period, the simulated solar peak radiation period and solar valley radiation period are extracted;

[0101] It should be noted that the solar peak radiation period refers to the period in previous summers when the outdoor solar radiation temperature reaches its peak, and the heat absorption rate of the building envelope materials within the building envelope is stable and continuous, such as from 12:00 to 14:00 in summer; the solar valley radiation period refers to the period in previous summers when the outdoor solar radiation intensity weakens, the heat absorption rate of the building envelope materials within the building envelope decreases, and the materials then release heat steadily into the interior, such as from 14:00 to 18:00 in summer.

[0102] The starting time points of the solar peak radiation period and the building enclosure heat storage period are extracted separately, and the difference is calculated. The absolute value is taken to obtain the radiation-storage start time difference value.

[0103] The starting time points of the solar valley radiation period and the building enclosure heat release period are extracted separately, and the difference is calculated. The absolute value is taken to obtain the radiation start time difference value.

[0104] The start-up time difference value of the radiative storage is summed with the start-up time difference value of the radiative release to obtain the start-up time difference value. The standard deviation of the start-up time difference value corresponding to each simulated monitoring cycle is calculated and the start-up time difference value is output.

[0105] Similarly, the end time points of the solar peak radiation period and the end time point of the building enclosure heat storage period are extracted respectively, and the difference is calculated. The absolute value is taken to obtain the radiation storage end time difference value.

[0106] The termination time points of the solar valley radiation period and the enclosure heat release period are extracted separately, and the difference is calculated. The absolute value is taken to obtain the radiation end time difference value.

[0107] The final time difference value is obtained by summing the final time difference value of the radiative storage and the final time difference value of the radiative emission. The standard deviation of the final time difference value corresponding to each simulation monitoring cycle is calculated and the final time difference value is obtained.

[0108] The sum of the start time difference and the end time difference is used to output the time period overlap value.

[0109] It is understandable that the time period overlap value means that the heat storage and release period of the building envelope overlaps with the solar peak radiation period and the solar valley radiation period in time during different simulation monitoring cycles. Specifically, solar radiation heat storage and release is an important dynamic factor in building energy consumption. The time period overlap value can distinguish it from other types of heat loads (such as heat generated by human activities, heat generated by equipment operation, etc.).

[0110] From a spatiotemporal perspective, by monitoring the overlap between the heat storage and release periods of the building envelope and the solar radiation periods in real time, the system can predict changes in the heat load of the building envelope in the future, adjust the building's energy supply strategy in advance, and achieve real-time optimization control of energy consumption. Moreover, the building envelope materials, orientations, and solar radiation conditions of different areas may be different, resulting in differences in their heat storage and release periods. By calculating the overlap values ​​of the periods in each area, the digital twin system can achieve differentiated energy consumption control in different areas of the building and can automatically and dynamically adjust the energy consumption of indoor air conditioning and lighting equipment.

[0111] If the overlap value of the time period is greater than the overlap threshold of the time period, it indicates that the heat storage and heat release period of the enclosure area has a low degree of overlap with the solar peak radiation period and the solar valley radiation period in time, which shows a non-solar radiation storage and release signal.

[0112] If the overlap value of the time period is less than or equal to the overlap threshold of the time period, it indicates that the heat storage and heat release period of the enclosure area has a high degree of overlap with the solar peak radiation period and the solar valley radiation period in time, which is displayed as a solar radiation storage and release signal.

[0113] Step 4: If the heat load type in the building envelope is solar radiation heat storage and release, obtain the heat storage and release delay time and optimize and control the indoor energy consumption in real time.

[0114] In some embodiments, the duration of the heat release period of the enclosure within each simulation monitoring cycle is extracted as the unit heat release delay time;

[0115] The unit heat release delay time within each simulation monitoring cycle is compared, the longest and shortest unit heat release delay times are selected, and the summation and average are calculated to output the heat storage release delay time.

[0116] The inflection point on the temperature difference change curve is taken as the starting point of energy consumption control, and summed with the heat storage release delay time to obtain the real-time energy consumption control period.

[0117] Extract the monitored temperature difference values ​​during the heat release period of the enclosure, and sum them to obtain the average temperature difference for each time period;

[0118] Within each simulation monitoring cycle, the average temperature difference of the unit time period corresponding to the heat release period of the enclosure is extracted and compared. The average temperature difference of the largest and smallest unit time periods are used as the temperature adjustment range.

[0119] The purpose of obtaining the temperature adjustment range is that the digital twin system can obtain the monitored temperature difference value during the heat release period of the building envelope in real time according to the temperature adjustment range, and compare it with the range. This can avoid over-operation or under-operation of equipment, improve the operating efficiency of equipment, reduce energy waste, and when the monitored temperature difference value during the heat release period of the building envelope gradually approaches the boundary of the temperature adjustment range, the system can adjust the operating status of equipment such as air conditioners in advance to avoid frequent start-up and shutdown of equipment due to the temperature exceeding the comfort range.

[0120] The specific solution in this embodiment is as follows: If the temperature difference change period of the enclosed area in each simulated monitoring cycle is unstable, the temperature difference change period of the enclosed area in each simulated monitoring cycle is analyzed to determine whether the heat load type in the enclosed area is solar radiation heat storage and release. If the heat load type in the enclosed area is solar radiation heat storage and release, the heat storage and release delay time is obtained, and the indoor energy consumption is optimized and controlled in real time. Thus, based on the monitored temperature difference value and temperature adjustment range in the current heat release period of the enclosed area, the equipment can avoid over-operation or under-operation, improve the operating efficiency of the equipment, and reduce energy waste.

[0121] Example 3

[0122] Please see Figure 3 As shown in the embodiment of the present invention, the building energy consumption real-time optimization control system based on digital twin includes the following modules:

[0123] Time Period Filtering Module: Simulates and monitors the enclosure area within the constructed indoor 3D model. During each simulation monitoring cycle, the temperature within the enclosure area is monitored in real time, and time periods of temperature difference changes are filtered out.

[0124] Stability assessment module: Performs temperature difference change trend and temperature difference change duration stability analysis for each period of temperature difference change in the enclosure, and assesses whether the temperature difference change period of the enclosure area is stable in each simulated monitoring cycle;

[0125] Storage and release analysis module: If the temperature difference change period is unstable, the temperature difference change period corresponding to each simulation monitoring cycle of the enclosure area will be analyzed to determine whether the heat load type in the enclosure area is solar radiation heat storage and release.

[0126] Real-time optimization control module: If the heat load type in the building envelope is solar radiation heat storage and release, the heat storage and release delay time is obtained, and the indoor energy consumption is optimized and controlled in real time.

[0127] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for real-time optimization and control of building energy consumption based on digital twins, characterized in that: include: The enclosure area within the constructed indoor 3D model is simulated and monitored. During each simulation monitoring cycle, the temperature within the enclosure area is monitored in real time, and the time periods of temperature difference change are selected. For each period of temperature difference change in the enclosure, the trend of temperature difference change and the stability of temperature difference change duration were analyzed to assess whether the temperature difference change period in the enclosure area was stable in each simulated monitoring cycle. If the temperature difference changes during a period of instability, the temperature difference changes during each simulation monitoring period of the enclosure area will be analyzed to determine whether the heat load type in the enclosure area is solar radiation heat storage and release. If the heat load type in the building envelope is solar radiation heat storage and release, then obtain the heat storage and release delay time and optimize and control the indoor energy consumption in real time. The temperature within the enclosure area is monitored in real time, as follows: The simulation monitoring period is divided into several simulation monitoring points. The temperature of the enclosure material in the enclosure area at each simulation monitoring point during the simulation monitoring period is obtained. If the temperature difference value is positive or zero, the simulation monitoring point is marked as the starting point of the temperature difference change. All the temperature difference values ​​from the starting point of the temperature difference change to the last simulation monitoring point in the simulation monitoring period are extracted to construct the temperature difference change curve. Extract the inflection point on the temperature difference change curve, take the local change curve from the starting point coordinates to the inflection point coordinates as the growth analysis curve, and take the local change curve from the inflection point coordinates to the ending point coordinates as the fitting analysis curve. Connect the starting point coordinates and the inflection point coordinates of the growth analysis curve with a straight line to obtain the fitted growth analysis line. Use the slope calculation formula to obtain the slope corresponding to the fitted growth analysis line. If it is positive, the overall trend of the fitted growth analysis line is growth. Combine the inflection point coordinates with the coordinates corresponding to any simulated monitoring point on the fitted analysis curve multiple times to obtain the local curve of stability analysis. The process for selecting periods of temperature variation is as follows: Extract the monitoring temperature difference value corresponding to each simulated monitoring point on the local curve of stability analysis, calculate the standard deviation, and output the temperature difference standard deviation value. If the temperature difference standard deviation value is less than or equal to the temperature difference standard deviation threshold, the local curve of stability analysis is marked as a temperature difference stable curve. The temperature difference standard deviation values ​​corresponding to each temperature difference stability curve are compared, and the temperature difference stability curve corresponding to the smallest temperature difference standard deviation value is selected. The time period between the simulated monitoring points corresponding to the starting point coordinates and the ending point coordinates on the temperature difference stability curve is taken as the temperature difference change period.

2. The method for real-time optimization and control of building energy consumption based on digital twins according to claim 1, characterized in that: The time periods of temperature difference variation within the enclosure are extracted during each simulated monitoring cycle, and the trend analysis of temperature difference variation is performed as follows: Extract the growth analysis curve and temperature difference stability curve for each period of temperature difference change in the enclosure. Combine the growth analysis curve and temperature difference stability curve for any two simulated monitoring periods to obtain the growth trend comparison group and the temperature difference stability comparison group. The slopes of the growth trend comparison group and the temperature difference stability comparison group are subtracted, and the absolute values ​​are taken to obtain the growth trend comparison sub-value and the stability trend comparison sub-value. Calculate the standard deviation of the stable trend comparison sub-values ​​corresponding to each group of temperature difference stable comparison groups, and output the stable trend comparison value. The temperature difference trend analysis value is obtained by summing the growth trend comparison value and the stable trend comparison value.

3. The method for real-time optimization and control of building energy consumption based on digital twins according to claim 1, characterized in that: The time periods of temperature difference variation within the enclosure were extracted during each simulated monitoring cycle, and the stability analysis of the duration of temperature difference variation was performed as follows: The ratio of the duration of each period of temperature difference change in the enclosure to the duration of the simulated monitoring cycle is calculated, and the ratio of the duration of temperature difference in the enclosure is output. Input the duration ratio of the enclosure temperature difference corresponding to any simulated monitoring cycle into the Euclidean distance formula, and output the enclosure temperature difference duration difference value.

4. The method for real-time optimization and control of building energy consumption based on digital twins according to claim 1, characterized in that: The process for assessing whether the temperature difference variation in the enclosure area remains stable during each simulated monitoring period is as follows: The temperature difference trend analysis value is summed with the temperature difference duration difference value of the enclosure to obtain the temperature change stability value. If the temperature change stability value is greater than the temperature change stability threshold, it is displayed as a temperature difference change fluctuation signal.

5. The method for real-time optimization and control of building energy consumption based on digital twins according to claim 1, characterized in that: The process of analyzing the temperature difference changes in the enclosure area during each simulation monitoring cycle is as follows: The time periods corresponding to the growth analysis curve and the local curves of the stability analysis are extracted respectively as the heat storage period and the heat release period of the enclosure. Within the simulated monitoring period, the simulated solar peak radiation period and solar valley radiation period are obtained. The starting time points of the solar peak radiation period and solar valley radiation period, as well as the starting time points of the enclosure heat storage period and enclosure heat release period, are extracted respectively. The difference between the corresponding starting time points is calculated, and the absolute value is taken to obtain the radiation storage start time difference value and the radiation release start time difference value. The sum is then calculated to obtain the start time difference value. The standard deviation of the start time difference value corresponding to each simulated monitoring period is calculated, and the start time difference value is output. The termination times of the solar peak radiation period and the solar peak radiation period, as well as the termination times of the enclosure heat storage period and the enclosure heat release period, are extracted separately. The differences between the termination times are calculated, and the absolute values ​​are taken to obtain the solar peak radiation storage end time difference and the solar peak radiation release end time difference. These are then summed to output the end time difference value. The standard deviation of the end time difference value corresponding to each simulation monitoring cycle is calculated to output the end time difference value.

6. The method for real-time optimization and control of building energy consumption based on digital twins according to claim 1, characterized in that: The process for determining whether the heat load type within the building envelope is solar radiation heat storage and release is as follows: The start time difference value and the end time difference value are summed to obtain the time period overlap value. If the time period overlap value is less than or equal to the time period overlap threshold, it is displayed as a solar power storage and discharge signal.

7. The method for real-time optimization and control of building energy consumption based on digital twins according to claim 1, characterized in that: The process of obtaining the heat storage release delay time and optimizing indoor energy consumption in real time is as follows: The duration of the heat release period of the enclosure within each simulation monitoring cycle is extracted as the unit heat release delay time. The longest and shortest unit heat release delay times are selected, and the summation and average are calculated to output the heat storage release delay time. The inflection point on the temperature difference change curve is taken as the starting point of energy consumption control, and summed with the heat storage release delay time to obtain the real-time energy consumption control period. The monitored temperature difference values ​​within the heat release period of the enclosure are extracted and summed to obtain the average temperature difference of the unit period. The magnitudes are compared, and the average temperature difference of the largest and smallest unit period is taken as the temperature adjustment range.

8. A building energy consumption real-time optimization control system based on digital twins, characterized in that: Includes the following steps: Time Period Filtering Module: Simulates and monitors the enclosure area within the constructed indoor 3D model. During each simulation monitoring cycle, the temperature within the enclosure area is monitored in real time, and time periods of temperature difference changes are filtered out. Stability assessment module: Performs temperature difference change trend and temperature difference change duration stability analysis for each period of temperature difference change in the enclosure, and assesses whether the temperature difference change period of the enclosure area is stable in each simulated monitoring cycle; Storage and release analysis module: If the temperature difference change period is unstable, the temperature difference change period corresponding to each simulation monitoring cycle of the enclosure area will be analyzed to determine whether the heat load type in the enclosure area is solar radiation heat storage and release. Real-time optimization control module: If the heat load type in the building envelope is solar radiation heat storage and release, the heat storage and release delay time is obtained, and the indoor energy consumption is optimized and controlled in real time. The temperature within the enclosure area is monitored in real time, as follows: The simulation monitoring period is divided into several simulation monitoring points. The temperature of the enclosure material in the enclosure area at each simulation monitoring point during the simulation monitoring period is obtained. If the temperature difference value is positive or zero, the simulation monitoring point is marked as the starting point of the temperature difference change. All the temperature difference values ​​from the starting point of the temperature difference change to the last simulation monitoring point in the simulation monitoring period are extracted to construct the temperature difference change curve. Extract the inflection point on the temperature difference change curve, take the local change curve from the starting point coordinates to the inflection point coordinates as the growth analysis curve, and take the local change curve from the inflection point coordinates to the ending point coordinates as the fitting analysis curve. Connect the starting point coordinates and the inflection point coordinates of the growth analysis curve with a straight line to obtain the fitted growth analysis line. Use the slope calculation formula to obtain the slope corresponding to the fitted growth analysis line. If it is positive, the overall trend of the fitted growth analysis line is growth. Combine the inflection point coordinates with the coordinates corresponding to any simulated monitoring point on the fitted analysis curve multiple times to obtain the local curve of stability analysis. The process for selecting periods of temperature variation is as follows: Extract the monitoring temperature difference value corresponding to each simulated monitoring point on the local curve of stability analysis, calculate the standard deviation, and output the temperature difference standard deviation value. If the temperature difference standard deviation value is less than or equal to the temperature difference standard deviation threshold, the local curve of stability analysis is marked as a temperature difference stable curve. The temperature difference standard deviation values ​​corresponding to each temperature difference stability curve are compared, and the temperature difference stability curve corresponding to the smallest temperature difference standard deviation value is selected. The time period between the simulated monitoring points corresponding to the starting point coordinates and the ending point coordinates on the temperature difference stability curve is taken as the temperature difference change period.

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