Energy-saving optimization method and system based on building upgrading and reconstruction

Abstract

The invention relates to the technical field of energy saving, and particularly discloses an energy-saving optimization method and system based on building upgrading and reconstruction. According to the method, building structure layout features and building internal environment features are obtained firstly, then the area of a connected scattering region is obtained according to the building structure layout features, and then adjustment energy parameters and natural energy parameters are obtained according to the building internal environment features. Obtaining a radiant heating influence coefficient according to the scattering region area, the adjustment energy parameters and the natural energy parameters, then obtaining the people flow density, then obtaining the edge vertical distance from the position of the current user to the scattering region area, and then obtaining the basic heating temperature of the position of the current user; and according to the basic heating temperature, the radiant heating influence coefficient, the edge vertical distance and the people flow density, the heating adjusting temperature is obtained, energy-saving optimization adjustment is conducted on the position where the current user is located, and the problem of energy waste in a traditional fixed heating mode can be avoided through dynamic adjustment.

Description

Technical Field

[0001] The present invention relates to the field of energy-saving technology, and in particular to an energy-saving optimization method and system based on building upgrading and reconstruction. Background Art

[0002] As the world pays more and more attention to sustainable development and energy conservation and emission reduction, energy management and energy efficiency improvement of buildings, as major energy consumers, have become key issues that need to be addressed. Existing buildings usually use fixed modes for heating, which cannot be flexibly adjusted according to real-time environmental changes and user needs, resulting in a large amount of energy waste. Therefore, an energy-saving optimization method and system based on building upgrades and renovations is needed to solve the problem of a large amount of electricity waste. Summary of the invention

[0003] The purpose of the present invention is to provide an energy-saving optimization method and system based on building upgrade and reconstruction to solve the technical problems raised in the above background technology.

[0004] To achieve the above object, the present invention provides the following technical solutions: An energy-saving optimization method based on building upgrading and reconstruction, comprising: Acquire building structural features based on building upgrading and reconstruction, wherein the building structural features include building structural layout features and building internal environment features; Acquire the office area area and the non-office area area according to the building structure layout characteristics, and acquire the intersecting scattering area area according to the office area area and the non-office area area; Acquiring regulated energy parameters and natural energy parameters according to the internal environmental characteristics of the building; Obtaining a radiation heating influence coefficient according to the scattering region area, the adjustment energy parameter and the natural energy parameter; Obtaining the user's historical activity trajectory, and obtaining the crowd density according to the user's historical activity trajectory; Acquire the current user's position, and acquire the vertical distance from the previous user's position to the edge of the scattering area according to the current user's position and the scattering area; Obtaining the basic heating temperature at the current user's location, and obtaining the heating adjustment temperature according to the basic heating temperature, the radiation heating influence coefficient, the edge vertical distance and the crowd density; Energy-saving optimization adjustment is performed on the current user's location according to the heating adjustment temperature.

[0005] Preferably, the step of acquiring the area of ​​the intersecting scattering area according to the area of ​​the office area and the area of ​​the non-office area comprises: Acquire a first edge line of the office area according to the area of ​​the office area; Acquire a second edge line of the non-office area according to the area of ​​the non-office area; Acquire an edge distance between the first edge line and the second edge line according to the first edge line and the second edge line; Acquiring a first edge temperature of the first edge line based on a temperature sensor; Acquire a second edge temperature of the second edge line based on a temperature sensor, and calculate an edge temperature difference according to the second edge temperature and the first edge temperature; Connecting two ends of the first edge line and the second edge line to obtain an edge area; Get the thermal conductivity of the preset wall material; The heat conduction flow is calculated according to the edge spacing, the edge temperature difference, the edge area and the thermal conductivity of the preset wall material, wherein the calculation formula is: ; Wherein, Q(W) represents the heat conduction flow, K(w) represents the thermal conductivity of the preset wall material, A(m) represents the edge area, ΔT represents the edge temperature difference, and d(m) represents the edge spacing; The flow area through which the heat conduction flow passes within a preset time is obtained, and the flow area is used as the area of ​​the intersecting scattering region.

[0006] Preferably, the step of obtaining the radiation heating influence coefficient according to the scattering area, the adjustment energy parameter and the natural energy parameter comprises: Obtaining heating output power according to the adjustment energy parameter; Obtaining the building height at the current user's location, and calculating the scattering area volume according to the building height and the scattering area area; Obtaining solar radiation temperature according to the natural energy parameter; Get the specific heat capacity and density of preset air; The indoor temperature within a preset time is calculated according to the heating output power, the scattering area volume, the solar radiation temperature, the specific heat capacity and the density, wherein the calculation formula is: ; Among them, T ROOM Indicates the indoor temperature, T OUT represents the solar radiation temperature, Q(L) represents the heating output power, ΔT(y) represents the preset time, V represents the scattering area volume, C p represents specific heat capacity, ρ represents density; The radiation heating influence coefficient is calculated according to the ratio of the indoor temperature to the area of ​​the scattering region.

[0007] Preferably, the step of obtaining the crowd density according to the user's historical activity trajectory comprises: Obtaining the area of ​​the user's stay area, and dividing the user's stay area into grids according to unit areas to obtain multiple grid area areas; Obtaining the number of users in each grid within the area of ​​the plurality of grid regions; Calculate multiple crowd flow densities based on the ratio of the number of users in each grid to the corresponding grid area; An average crowd flow density is calculated according to the multiple crowd flow densities, and the average crowd flow density is used as the crowd flow density.

[0008] Preferably, the step of obtaining the heating adjustment temperature according to the basic heating temperature, the radiation heating influence coefficient, the edge vertical distance and the crowd density comprises: Obtaining the location of a heating heat source, and obtaining a temperature loss factor according to the location of the heating heat source and a vertical distance from the edge; Obtaining a crowd temperature increment factor according to the basic heating temperature and crowd density; The heating adjustment temperature is calculated according to the basic heating temperature, the radiation heating influence coefficient, the edge vertical distance, the crowd density, the temperature loss factor and the crowd temperature increment factor, wherein the calculation formula is: ; Among them, T adjusted Indicates the heating adjustment temperature, T base represents the basic heating temperature, D(c) represents the vertical distance to the edge, S(s) represents the temperature loss factor, M(D) represents the crowd density, Z(L) represents the crowd temperature increment factor, and FS represents the radiation heating influence coefficient.

[0009] Preferably, the step of performing energy-saving optimization adjustment on the current user's location according to the heating adjustment temperature comprises: Get the current actual temperature of the current user's location; Acquire the corresponding current heating output power according to the current actual temperature; Acquire a temperature deviation value according to the heating adjustment temperature and the current actual temperature; Obtain the heating adjustment temperature and the current actual temperature to obtain a temperature difference steady-state error coefficient; Obtain the power steady-state error coefficient of historical power regulation; Obtaining the heating adjustment temperature to obtain the corresponding temperature steady-state error coefficient; Calculate and adjust the heating output power according to the current heating output power, temperature deviation value, temperature difference steady-state error coefficient, power steady-state error coefficient and temperature steady-state error coefficient; The heating output power at the current user's location is adjusted for energy saving and optimization according to the adjustment of the heating output power.

[0010] The present application also provides an energy-saving optimization system based on building upgrading and transformation, including: A first acquisition module is used to acquire building structural features based on building upgrade and reconstruction, wherein the building structural features include building structural layout features and building internal environment features; A second acquisition module is used to acquire the office area area and the non-office area area according to the building structure layout characteristics, and acquire the intersection scattering area area according to the office area area and the non-office area area; A third acquisition module is used to acquire adjustment energy parameters and natural energy parameters according to the internal environment characteristics of the building; A fourth acquisition module, used for acquiring a radiation heating influence coefficient according to the scattering area, the adjustment energy parameter and the natural energy parameter; A fifth acquisition module, used to acquire a user's historical activity trajectory, and acquire a crowd density according to the user's historical activity trajectory; A sixth acquisition module, used to acquire the current user's position, and acquire the vertical distance from the previous user's position to the edge of the scattering area according to the current user's position and the scattering area; The seventh acquisition module is used to acquire the basic heating temperature at the current user's location, and acquire the heating adjustment temperature according to the basic heating temperature, the radiation heating influence coefficient, the edge vertical distance and the crowd density; The first adjustment module is used to perform energy-saving optimization adjustment on the current user's location according to the heating adjustment temperature.

[0011] Preferably, the second acquisition module includes: A first acquisition unit, configured to acquire a first edge line of the office area according to the area of ​​the office area; A second acquiring unit, configured to acquire a second edge line of the non-office area according to the area of ​​the non-office area; A third acquiring unit, configured to acquire an edge distance between the first edge line and the second edge line according to the first edge line and the second edge line; A fourth acquisition unit, configured to acquire a first edge temperature of the first edge line based on a temperature sensor; a fifth acquiring unit, configured to acquire a second edge temperature of the second edge line based on a temperature sensor, and calculate an edge temperature difference according to the second edge temperature and the first edge temperature; A first connection unit, used to connect two ends of the first edge line and the second edge line in a closed manner to obtain an edge area; A sixth acquisition unit, used to acquire the thermal conductivity of a preset wall material; The first calculation unit is used to calculate the heat conduction flow rate according to the edge spacing, the edge temperature difference, the edge area and the thermal conductivity of the preset wall material, wherein the calculation formula is: ; Wherein, Q(W) represents the heat conduction flow, K(w) represents the thermal conductivity of the preset wall material, A(m) represents the edge area, ΔT represents the edge temperature difference, and d(m) represents the edge spacing; The seventh acquisition unit is used to acquire the flow area through which the heat conduction flow passes within a preset time, and use the flow area as the area of ​​the intersecting scattering region.

[0012] The present application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above method when executing the computer program.

[0013] The present application also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps of the above method are implemented.

[0014] The beneficial effects of the present application are as follows: the present invention first obtains building structure layout characteristics and building internal environment characteristics based on building upgrade and reconstruction, then obtains office area area and non-office area area according to the building structure layout characteristics, and obtains the intersecting scattered area area according to the office area and the non-office area, then obtains adjustment energy parameters and natural energy parameters according to the building internal environment characteristics, and then obtains the radiation heating influence coefficient according to the scattered area area, adjustment energy parameters and natural energy parameters, then obtains the user's historical activity trajectory, and obtains the crowd density according to the user's historical activity trajectory, then obtains the current user's location, and obtains the vertical distance from the previous user's location to the edge of the scattered area area according to the current user's location and the scattered area area, then obtains the basic heating temperature of the current user's location, and obtains the heating adjustment temperature according to the basic heating temperature, the radiation heating influence coefficient, the edge vertical distance and the crowd density, and finally, performs energy-saving optimization adjustment on the current user's location according to the heating adjustment temperature. Such dynamic adjustment can avoid the problem of energy waste in the traditional fixed heating mode. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 The figure is a schematic diagram of a method flow of an embodiment of the present application.

[0016] Figure 2 A schematic diagram of the system structure of an embodiment of the present application.

[0017] Figure 3 A schematic diagram of the internal structure of a computer device according to an embodiment of the present application.

[0018] The purpose, features and advantages of this application will be further described in conjunction with the embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0019] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0020] like Figure 1-3 As shown, the present application provides an energy-saving optimization method based on building upgrading and reconstruction, comprising: S1. Obtaining building structural characteristics based on building upgrading and reconstruction, wherein the building structural characteristics include building structural layout characteristics and building internal environment characteristics; S2. Acquire the office area area and the non-office area area according to the building structure layout characteristics, and acquire the intersecting scattering area area according to the office area area and the non-office area area; S3. Acquire adjustment energy parameters and natural energy parameters according to the internal environment characteristics of the building; S4. Obtaining a radiation heating influence coefficient according to the scattering region area, the adjustment energy parameter and the natural energy parameter; S5. Obtain the user's historical activity trajectory, and obtain the crowd density according to the user's historical activity trajectory; S6, obtaining the current user's position, and obtaining the vertical distance from the previous user's position to the edge of the scattering area according to the current user's position and the scattering area; S7, obtaining the basic heating temperature at the current user's location, and obtaining the heating adjustment temperature according to the basic heating temperature, the radiation heating influence coefficient, the edge vertical distance and the crowd density; S8. Perform energy-saving optimization adjustment for the current user's location according to the heating adjustment temperature.

[0021] As described in the above steps S1-S8, since existing buildings usually use a fixed mode for heating, and the fixed mode heating cannot be flexibly adjusted according to real-time environmental changes and user needs, resulting in a large amount of energy waste, the present invention first obtains the building structure characteristics based on the building upgrade and transformation, wherein the building structure characteristics include the building structure layout characteristics and the building internal environment characteristics, and provides basic data for subsequent precise energy-saving optimization analysis by fully understanding the building structure layout (such as room distribution, corridor location, etc.) and internal environment (such as thermal insulation performance, lighting conditions, etc.), and then obtains the office area area and non-office area area according to the building structure layout characteristics, and obtains the intersection scattering area area according to the office area area and the non-office area area, so as to clarify the scope of the office area and the non-office area, which is helpful to analyze the difference between the concentrated area and the non-concentrated area of ​​personnel activities, and provides a basis for targeted heating adjustment. And obtaining the intersection scattering area area can further understand the key areas of heat conduction and distribution between different areas. For example, the office area has frequent personnel activities and has high requirements for temperature comfort, so it is necessary to pay special attention to its heating situation; non-office areas such as storage rooms may have relatively low temperature requirements, and the heating strategy can be appropriately adjusted to save energy. The area of ​​the scattering region is crucial for calculating the exchange and influence of heat between different areas. It can help determine the degree of heat transfer between different areas, thereby providing a basis for accurate regulation of heating and avoiding energy waste on unnecessary heat loss or overcompensation. Then, according to the internal environmental characteristics of the building, the adjustment energy parameters and natural energy parameters are obtained. In this way, the adjustment energy parameters (such as the power of the heating equipment, the type of energy, etc.) determine the ability and consumption of artificial active temperature regulation, and the natural energy parameters (such as solar radiation intensity, outdoor temperature, etc.) reflect the available free natural energy resources and the impact of the external environment on the internal temperature of the building. For example, knowing the output power of the heating equipment can calculate the heat that can be provided within a certain period of time. Combined with the natural energy parameters (such as solar radiation temperature), it can be reasonably arranged to reduce the use of adjustment energy when the solar radiation is strong to achieve energy saving. At the same time, understanding the natural energy parameters is also helpful in evaluating the thermal insulation performance of the building. If the outdoor temperature is low and natural energy cannot effectively supplement the indoor heat, it is necessary to rely more on the regulated energy, which also provides a reference for subsequent optimization and adjustment. Then, the radiant heating influence coefficient is obtained according to the scattering area, the regulated energy parameters and the natural energy parameters. In this way, the radiant heating influence coefficient comprehensively reflects the comprehensive influence of the regulated energy and natural energy on the indoor temperature through the scattering area. It quantifies the relationship between energy input and indoor temperature change under specific scattering area conditions, and then obtains the user's historical activity trajectory, and obtains the crowd density based on the user's historical activity trajectory. The crowd density reflects the distribution of people in different areas of the building. Areas with frequent human activities will generate more human body heat, which has a certain effect on improving the indoor temperature.For example, in a crowded conference room, the human body emits more heat. When adjusting the heating, the heating output power can be appropriately reduced to avoid energy waste caused by excessive temperature; while in areas with fewer people, it may be necessary to rely more on heating equipment to maintain a comfortable temperature. By analyzing the historical activity trajectory of users to obtain the density of human traffic, the distribution of people in different areas can be predicted in advance, so that the heating system can be dynamically adjusted according to the activities of people, improve energy utilization efficiency, avoid continuous heating in unmanned areas or insufficient heating in crowded areas, and then obtain the current user's location, and obtain the vertical distance from the previous user's location to the edge of the scattering area area according to the current user's location and the scattering area area, so that the edge vertical distance affects the loss of heat during the transfer to the user's location. The farther away from the edge of the scattering area, the greater the possibility of heat loss through the wall, air and other media during the transmission process. For example, the user position close to the outer wall is more likely to lose heat to the outdoors than the position close to the center of the scattering area, and more heating energy is required to maintain a comfortable temperature. Accurately obtaining this distance can more accurately calculate the heat loss, so that this difference can be taken into account when determining the heating adjustment temperature, making the heating adjustment more accurate. By performing personalized heating adjustment according to the heat loss at different locations, it is possible to avoid overheating or overcooling of some areas due to unified heating, realize the reasonable allocation and efficient use of energy, and then obtain the basic heating temperature at the current user's location, and obtain the heating adjustment temperature according to the basic heating temperature, the influence coefficient of radiation heating, the vertical distance from the edge and the density of human traffic. In this way, the basic heating temperature is an initial reference temperature, but the actual required heating temperature will be affected by many factors. The introduction of factors such as the influence coefficient of radiation heating, the vertical distance from the edge and the density of human traffic enables the heating adjustment temperature to more accurately reflect the actual comfort temperature required by the user. For example, after considering the influence coefficient of radiation heating, if the combined effect of natural energy and regulating energy in this area is strong, the heating adjustment temperature can be appropriately reduced; considering the heat loss at the vertical distance from the edge, if the distance from the edge is far, the heating adjustment temperature needs to be increased accordingly; according to the density of human traffic, the heating adjustment temperature can be appropriately reduced in areas with more people to rely on human body heat dissipation. The heating adjustment temperature calculated in this way can be dynamically adjusted according to the actual situation, ensuring that energy consumption is minimized and the energy efficiency of the heating system is improved while meeting the comfort level. Finally, the current user's location is optimized for energy saving according to the heating adjustment temperature. This step applies the heating adjustment temperature calculated previously to the actual heating system to achieve precise heating control of the user's location. By real-time monitoring and adjusting the heating output power, the indoor temperature is always maintained at a state that can both meet the user's comfort needs and maximize energy conservation.For example, if the calculated heating adjustment temperature is lower than the current actual temperature, the system can reduce the output power of the heating equipment and reduce energy consumption; if it is higher than the current actual temperature, the power output will be increased appropriately. Such dynamic adjustment can avoid the problem of energy waste in the traditional fixed heating mode.

[0022] In one embodiment, the step S2 of acquiring the area of ​​the intersecting scattering area according to the area of ​​the office area and the area of ​​the non-office area includes: S201, acquiring a first edge line of the office area according to the area of ​​the office area; S202, acquiring a second edge line of the non-office area according to the area of ​​the non-office area; S203, acquiring an edge distance between the first edge line and the second edge line according to the first edge line and the second edge line; S204, acquiring a first edge temperature of the first edge line based on a temperature sensor; S205, acquiring a second edge temperature of the second edge line based on a temperature sensor, and calculating an edge temperature difference according to the second edge temperature and the first edge temperature; S206, connecting two ends of the first edge line and the second edge line to obtain an edge area; S207, obtaining the thermal conductivity of a preset wall material; S208, calculating the heat conduction flow rate according to the edge spacing, the edge temperature difference, the edge area and the thermal conductivity of the preset wall material, wherein the calculation formula is: ; Wherein, Q(W) represents the heat conduction flow, K(w) represents the thermal conductivity of the preset wall material, A(m) represents the edge area, ΔT represents the edge temperature difference, and d(m) represents the edge spacing; S209, obtaining a flow area through which the heat conduction flow passes within a preset time, and using the flow area as an area of ​​a scattering region of intersection.

[0023] As described in the above steps S201-S209, the present invention first obtains the first edge line of the office area according to the area of ​​the office area, and then obtains the second edge line of the non-office area according to the area of ​​the non-office area, determines the boundary range of the office area in space, and provides a basic framework for the subsequent calculation of the relationship between the office area and the non-office area. The edge line clarifies the outline of the office area, which helps to intuitively understand its shape, size and relative position relationship with the surrounding area, which is of great significance for analyzing the heat transfer path, distribution law and mutual influence between different areas between the areas. Then, the edge distance between the office area and the non-office area is obtained according to the first edge line and the second edge line. The edge distance directly reflects the degree of spatial proximity between the office area and the non-office area, and is one of the key indicators for measuring the difficulty of heat conduction between the two areas. Then, the first edge temperature of the first edge line is obtained based on the temperature sensor, and the second edge temperature of the second edge line is obtained based on the temperature sensor. The edge temperature difference is calculated based on the second edge temperature and the first edge temperature. The edge temperature difference is the driving force for heat conduction from the high temperature area (usually the office area) to the low temperature area (non-office area), and its size determines the rate and intensity of heat conduction. A larger edge temperature difference means that the heat conduction speed is faster, and we need to focus on how to reduce heat loss or make rational use of the conducted heat in this case; a smaller edge temperature difference may mean that the heat exchange is relatively slow, but it is also necessary to determine whether energy regulation is needed to maintain a stable thermal environment based on the specific situation. The calculation of the edge temperature difference provides key temperature gradient information for further analysis of the heat conduction process and optimization of the heating strategy. Then, the two ends of the first edge line and the second edge line are closed and connected to obtain the edge area. In the analysis of the heat conduction process, the area of ​​the intersection area is a factor that cannot be ignored. It is the key interface for heat transfer between different areas, which is directly related to the total amount and spatial distribution of heat conduction. By calculating the edge area, the heat conduction process can be linked to the specific spatial range, making the energy-saving optimization calculation more accurate and comprehensive, and then the thermal conductivity of the preset wall material is obtained. Then, the heat conduction flow is calculated according to the edge spacing, the edge temperature difference, the edge area and the thermal conductivity of the preset wall material. The heat conduction flow is the core physical quantity in the heat transfer process, which comprehensively considers the edge spacing (affecting the length of the heat conduction path), the edge temperature difference (the driving force of heat conduction), the edge area (the cross-sectional area of ​​heat conduction) and the thermal conductivity of the wall material (determining the thermal conductivity of the material) and other key factors. Through this precise calculation formula, the heat conduction flow between regions can be accurately calculated based on the actual building structure and thermal environment parameters, so that energy-saving optimization measures can be formulated based on scientific heat conduction theory, ensuring that a comfortable indoor thermal environment is maintained while reducing energy consumption. At the same time, the calculation of the heat conduction flow accurately quantifies the amount of heat conducted through the wall at the junction of the office area and the non-office area.This value directly reflects the heat exchange rate between the two areas due to the temperature difference and the characteristics of the wall materials. It is an important basis for evaluating energy loss and formulating energy-saving measures. Finally, the flow area through which the heat conduction flow passes within the preset time is obtained, and the flow area is used as the area of ​​the intersecting scattering area. The area of ​​the intersecting scattering area determines the spatial range of the main impact of heat conduction within a certain period of time. This area is the key area for heat exchange and mixing between office areas and non-office areas, and has an important impact on the thermal environment distribution and energy utilization efficiency of the entire building. For example, in the scattering area, heat may diffuse and transfer in a complex way, affecting the temperature of the surrounding area. Accurately determining the area of ​​the scattering area helps to further analyze the distribution law of heat in the area, and provides an important basis for the subsequent calculation of the influence coefficient of radiant heating and the optimization of heating regulation on the range of heat exchange space.

[0024] In one embodiment, the step S4 of obtaining the radiation heating influence coefficient according to the scattering area, the adjustment energy parameter and the natural energy parameter includes: S401, obtaining heating output power according to the adjustment energy parameter; S402, obtaining the building height at the current user's location, and calculating the scattering region volume according to the building height and the scattering region area; S403, obtaining solar radiation temperature according to the natural energy parameter; S404, obtaining the specific heat capacity and density of preset air; S405, calculating the indoor temperature within a preset time according to the heating output power, the volume of the scattering area, the solar radiation temperature, the specific heat capacity and the density, wherein the calculation formula is: ; Among them, T ROOM Indicates the indoor temperature, T OUT represents the solar radiation temperature, Q(L) represents the heating output power, ΔT(y) represents the preset time, V represents the scattering area volume, C p represents specific heat capacity, ρ represents density; S406: Calculate the radiation heating influence coefficient according to the ratio of the indoor temperature to the scattering area.

[0025] As described in the above steps S401-S406, the present invention first obtains the heating output power according to the adjustment energy parameters. In the energy-saving and optimized heating system, the output capacity of the heating equipment must be clearly known, which is the energy source basis of the entire heating process. Only by mastering the heating output power can other factors (such as the volume of the scattering area, the impact of natural energy, etc.) be combined in subsequent calculations to comprehensively evaluate the change trend of the indoor temperature, so as to formulate a reasonable energy-saving strategy. Without this parameter, it is impossible to accurately calculate the temperature that can be reached indoors under different conditions, and it is impossible to determine how to optimize the operation of the heating equipment to achieve the energy-saving goal. Then, the building floor height at the current user's location is obtained, and the scattering area volume is calculated according to the building floor height and the scattering area area. The calculation of the scattering area volume provides a three-dimensional quantitative index for a comprehensive analysis of the thermal environment in the area. The building floor height determines the distribution range of heat in the vertical direction. Combined with the scattering area area, the total volume of air in the area can be accurately evaluated. This is of great significance for studying the diffusion and distribution of heat in space and heat exchange with the surrounding environment. For example, a larger scattering area volume means that heat has more space to mix and transfer in the area, and more energy is required to maintain or change its temperature. When calculating the radiant heating impact coefficient, the scattering area volume is a key factor, which can reflect the effect of natural energy and regulated energy in this three-dimensional space, and help to more accurately determine the relationship between energy input and indoor temperature changes, thereby providing a more accurate basis for energy-saving optimization. Then, the solar radiation temperature is obtained based on the natural energy parameters. As an important natural energy source, the temperature change of solar radiation has a significant impact on the indoor thermal environment. Obtaining the solar radiation temperature can incorporate natural energy factors into the analysis of the entire heating system, so that the energy-saving optimization method can fully consider the utilization potential of natural energy, dynamically adjust the heating strategy according to the actual situation of solar radiation, and achieve efficient utilization of energy. Then, the specific heat capacity and density of the preset air are obtained. Then, the indoor temperature within the preset time is calculated according to the heating output power, the scattering area volume, the solar radiation temperature, the specific heat capacity and the density. This step uses an accurate calculation formula to comprehensively consider the adjustment energy (heating output power), natural energy (solar radiation temperature) and the thermophysical properties of air (specific heat capacity, density) and spatial characteristics (scattering area volume) and other factors to calculate the indoor temperature after the preset time, where the preset time is a pre-set time, for example, the preset time is 30 minutes. This calculation result can accurately reflect the actual changes in indoor temperature under various energy inputs and environmental conditions, and provides a direct basis for evaluating the effect of the current heating system. For example, if the calculated indoor temperature is significantly different from the expected comfort temperature, it can be judged whether the current heating strategy is reasonable and whether it is necessary to adjust the heating output power or make better use of natural energy.At the same time, the accurate calculation of indoor temperature is also the basis for the subsequent calculation of the influence coefficient of radiation heating. It quantitatively integrates the influence of different energy factors on indoor temperature, and provides key temperature data support for further analysis of energy utilization efficiency and optimization of heating regulation. At the same time, the above formula is based on the law of conservation of energy and the principle of heat transfer, and multiple key factors are included in the calculation, which can truly simulate the change process of indoor temperature over time. By comprehensively considering the interaction of various energy inputs and environmental factors, the calculated indoor temperature has high accuracy and reliability. Finally, the radiation heating influence coefficient is calculated according to the ratio of the indoor temperature to the area of ​​the scattering area. The radiation heating influence coefficient comprehensively quantifies the relationship between the influence of energy input (including regulating energy and natural energy) on indoor temperature and the area of ​​the scattering area under specific scattering area conditions. It is a normalized indicator that can intuitively reflect the temperature change of the scattering area per unit area under the action of various energy sources. Among them, the indoor temperature will decrease with the increase of the scattering area area, and the larger the area of ​​the scattering area, the faster the temperature decreases. The ratio of the two can provide an important reference basis for heating regulation, which is helpful to achieve refined management and energy-saving optimization of the entire building heating system.

[0026] In one embodiment, the step S5 of obtaining the crowd density according to the user's historical activity trajectory includes: S501, obtaining the area of ​​the user's stay area, and dividing the user's stay area into grids according to unit areas to obtain multiple grid area areas; S502, obtaining the number of users in each grid within the area of ​​the plurality of grid regions; S503, calculating multiple crowd flow densities according to the ratio of the number of users in each grid to the corresponding grid area; S504: Calculate an average crowd flow density according to the multiple crowd flow densities, and use the average crowd flow density as the crowd flow density.

[0027] As described in the above steps S501-S504, the present invention first obtains the area of ​​the user's stay area, and divides the area of ​​the user's stay area into a grid according to the unit area to obtain multiple grid area areas, and then obtains the area of ​​the user's stay area, and divides the area of ​​the user's stay area into a grid according to the unit area to obtain multiple grid area areas, and determines the main area range of the user's activities in the building, and divides it into a grid, which can convert the continuous space into discrete units that are easy to analyze. This method helps to understand the distribution possibility of users in different small areas in more detail, and provides a basic framework for the subsequent accurate calculation of the density of human flow. For example, in a large office area, through gridding, the potential situation of people staying in each small area (such as each grid) can be clarified, and areas where people may gather or be sparse can be found, so as to better analyze the hot spots and cold spots of human activities, and provide a spatial distribution basis for optimizing the allocation of resources such as heating, and then obtain the number of users in each grid in the area of ​​the multiple grid areas. The number of users in each grid directly reflects the actual distribution of people in different small areas. This data is the key information for calculating the density of human flow, and it can accurately show the difference in the degree of aggregation of people in space. For example, if there are a large number of users in some grids, it means that these areas are hot spots with frequent human activities, which may generate more human body heat and affect the heating demand; while grids with a small number of users may be relatively deserted areas with low heating demand. By accurately obtaining the number of users in each grid, the impact of human activities on the temperature of different areas can be more accurately evaluated, providing a basis for personalized heating regulation, avoiding overheating in unmanned areas or insufficient heating in densely populated areas, thereby achieving energy saving. Then, multiple crowd densities are calculated based on the ratio of the number of users in each grid to the corresponding grid area. In this way, the calculation of multiple crowd densities can quantify the density of people in each grid area. Crowd density is a comprehensive indicator that combines the number of people with the spatial area and reflects the distribution of people per unit area. Different crowd density values ​​can intuitively show the differences in human activities between different areas. For example, a high crowd density area means that there are more human activities in a relatively small space, and the heat dissipation of human bodies is relatively concentrated, which has a greater effect on improving the indoor temperature; the opposite is true for low crowd density areas. By calculating multiple crowd densities, we can fully understand the density of personnel distribution in the entire user stay area, provide an important basis for the subsequent analysis of heating demand in different areas and optimize energy allocation, ensure that the heating system can be accurately adjusted according to the actual situation of personnel activities, and improve energy utilization efficiency. Finally, the average crowd density is calculated based on the multiple crowd densities, and the average crowd density is used as the crowd density. Calculating the average crowd density in this way can provide an overall indicator of the density of personnel activities, which is used to represent the general situation of the entire user stay area.Although the crowd density in each grid area is different, the average crowd density can reflect the overall distribution level of people in the area at a macro level. This indicator plays an important role in the subsequent calculation of heating adjustment temperature and other processes.

[0028] In one embodiment, the step S7 of obtaining the heating adjustment temperature according to the basic heating temperature, the radiation heating influence coefficient, the edge vertical distance and the crowd density includes: S701, obtaining a heating heat source position, and obtaining a temperature loss factor according to the heating heat source position and a vertical distance from an edge; S702, obtaining a crowd temperature increment factor according to the basic heating temperature and crowd density; S703, calculating the heating adjustment temperature according to the basic heating temperature, the radiation heating influence coefficient, the edge vertical distance, the crowd density, the temperature loss factor and the crowd temperature increment factor, wherein the calculation formula is: ; Among them, T adjusted Indicates the heating adjustment temperature, T base represents the basic heating temperature, D(c) represents the vertical distance to the edge, S(s) represents the temperature loss factor, M(D) represents the crowd density, Z(L) represents the crowd temperature increment factor, and FS represents the radiation heating influence coefficient.

[0029] As described in the above steps S701-S703, in an actual heating system, heat will inevitably be lost when it is transferred from the heat source to the user's position, and distance is one of the key factors affecting heat loss. In order to achieve accurate heating regulation, this temperature change caused by distance must be considered. The present invention first obtains the position of the heating heat source, and obtains the temperature loss factor based on the position of the heating heat source and the vertical distance to the edge. After determining the relationship between the position of the heating heat source and the vertical distance from the user's position to the edge of the scattering area, the temperature loss factor is obtained by calculation. This factor can quantify the degree of loss caused by the distance factor during the process of heat transfer from the heat source to the user's position. For example, the farther away from the heat source, the more heat is lost through walls, air and other media during the transmission process, and the greater the temperature loss factor. This helps to accurately consider the loss of heat during the transmission process when calculating the heating adjustment temperature in the subsequent calculation, so that the calculated heating adjustment temperature is more in line with actual needs. By understanding the temperature loss factor, the heating output power can be reasonably adjusted for users in different locations to avoid local overheating or overcooling caused by different distances from the heat source, improve the overall energy efficiency of the heating system, and achieve energy-saving optimization. In the energy-saving optimized heating system, human activity is an important factor that cannot be ignored, and the heat generated by it will affect the indoor temperature. The basic heating temperature is combined with the crowd density to calculate the crowd temperature increment factor, which can comprehensively consider the initial heating temperature and the additional heat contribution brought by human activities. This factor can accurately reflect the degree of influence of human activities on the indoor temperature under different densities. Therefore, the crowd temperature increment factor can be obtained according to the basic heating temperature and crowd density. In this way, the crowd density reflects the density of human distribution in the space, and the human itself will emit a certain amount of heat. The crowd temperature increment factor can quantify the effect of the heat generated by human activities on the indoor temperature by considering the basic heating temperature and crowd density. In densely populated areas, the human body emits more heat, and the human temperature increment factor is large, which means that the output power of the heating equipment can be appropriately reduced, and the human body's own heat dissipation can be relied on to maintain a comfortable indoor temperature, thereby achieving energy saving. On the contrary, in areas with low density of people flow, it may be necessary to rely more on heating equipment to provide heat, the temperature increment factor of people flow is small, and heating regulation should focus more on adjusting the output power of equipment. The temperature increment factor of people flow provides an important basis for dynamically adjusting the heating strategy according to the activities of people, which helps to improve energy efficiency and avoid energy waste caused by excessive heating in areas with frequent activities. In actual building heating scenarios, indoor temperature is affected by the interaction of multiple complex factors.In order to achieve accurate and energy-saving heating regulation, a calculation that can comprehensively consider these factors is needed. On this basis, the heating regulation temperature is calculated according to the basic heating temperature, radiation heating influence coefficient, edge vertical distance, crowd density, temperature loss factor and crowd temperature increment factor. This calculation formula integrates multiple key factors, comprehensively considers the basic heating temperature (initial temperature reference), radiation heating influence coefficient (relationship between energy input and indoor temperature change), edge vertical distance (heat transmission loss), crowd density (heat generated by human activities), temperature loss factor (heat loss caused by distance) and crowd temperature increment factor (temperature increase caused by human activities), and accurately calculates the heating regulation temperature. This temperature can be dynamically adjusted according to actual conditions to ensure efficient use of energy while meeting user comfort requirements. For example, when the radiant heating influence coefficient is large, it may mean that the natural energy or regulating energy has a strong effect in this area, and the heating regulating temperature can be appropriately reduced; when the vertical distance to the edge is long, resulting in a large temperature loss factor, the heating regulating temperature needs to be increased to compensate for the heat loss; when the crowd density is large and the crowd temperature increment factor is obvious, the heating regulating temperature can be reduced to rely on human body heat dissipation. Through this comprehensive calculation, the heating regulating temperature can adapt to different environments and personnel activity conditions, avoiding energy waste in fixed heating modes and improving the energy saving effect and adaptability of the entire heating system.

[0030] In one embodiment, the step S8 of performing energy-saving optimization adjustment on the current user's location according to the heating adjustment temperature includes: S801, obtaining the current actual temperature of the current user's location; S802, obtaining the corresponding current heating output power according to the current actual temperature; S803, obtaining a temperature deviation value according to the heating adjustment temperature and the current actual temperature; S804, obtaining the heating adjustment temperature and the current actual temperature to obtain a temperature difference steady-state error coefficient; S805, obtaining a power steady-state error coefficient of historical power regulation; S806, obtaining the heating adjustment temperature and obtaining the corresponding temperature steady-state error coefficient; S807, calculating and adjusting the heating output power according to the current heating output power, the temperature deviation value, the temperature difference steady-state error coefficient, the power steady-state error coefficient and the temperature steady-state error coefficient, wherein: ; Among them, P adj Indicates the regulated heating output power, P current represents the current heating output power, e(t) represents the temperature deviation value, K 1 Represents the temperature difference steady-state error coefficient, K2 Represents the power steady-state error coefficient, K 3 Indicates the temperature steady-state error coefficient S808: Perform energy-saving optimization adjustment on the heating output power at the current user's location according to the adjustment of the heating output power.

[0031] As described in the above steps S801-S808, the present invention first obtains the current actual temperature of the current user's location. The current actual temperature is the key feedback information of the entire energy-saving optimization and adjustment process. It directly reflects the real thermal environment of the current user's location. Since the energy-saving optimization and adjustment are realized, it is necessary to clarify the degree of deviation between the current temperature and the target temperature. The temperature deviation value, as the difference between the two, can intuitively reflect the problems existing in the heating system or the direction that needs to be improved. Therefore, the temperature deviation value can be obtained according to the heating adjustment temperature and the current actual temperature, and then the temperature deviation value clarifies the difference between the current actual temperature and the desired heating adjustment temperature. This deviation value is an important basis for judging whether the heating system needs to be adjusted and the adjustment range. In actual heating applications, not only the current temperature deviation should be paid attention to, but also the ability of the system to maintain temperature stability during long-term operation should be considered. The temperature difference steady-state error coefficient can quantify this long-term stability and provide an important indicator for comprehensively evaluating the performance of the heating system. Then, the heating adjustment temperature and the current actual temperature are obtained to obtain the temperature difference steady-state error coefficient, and the temperature difference steady-state error coefficient reflects the long-term stable control ability of the system for temperature deviation during the heating adjustment process. It takes into account the relationship between the heating adjustment temperature and the current actual temperature, as well as the system's performance in maintaining temperature stability during long-term operation. For example, a smaller temperature difference steady-state error coefficient means that the system can more effectively stabilize the actual temperature within a range close to the heating adjustment temperature, reduce temperature fluctuations, and improve the user's comfort experience; while a larger coefficient may indicate that the system has certain instability in temperature control and needs to further optimize the adjustment strategy. The temperature difference steady-state error coefficient provides an important basis for evaluating the stability and reliability of the heating system, helps to discover potential problems in the system, and takes into account the long-term performance of the system when calculating and adjusting the heating output power, making the heating regulation more scientific and reasonable, ensuring that a stable indoor temperature environment is maintained while saving energy, and then obtaining the power steady-state error coefficient of the historical power regulation. In this way, the power steady-state error coefficient of the historical power regulation records the stability performance of the heating system in the past power regulation process. It reflects the long-term stable deviation between the actual power output and the expected power output when the system adjusts the heating power according to different demands. At the same time, this coefficient provides a historical experience reference for the current adjustment of the heating output power, helping the system to consider factors such as the current temperature deviation while combining past adjustment conditions to formulate a more reasonable and stable power adjustment plan, thereby improving the overall energy efficiency and stability of the heating system. The heating adjustment temperature is then obtained to obtain the corresponding temperature steady-state error coefficient, which is related to the heating adjustment temperature. It reflects the system's ability to maintain a stable temperature under a specific heating adjustment temperature setting.Different heating adjustment temperatures may correspond to different system operating characteristics and stability requirements. By obtaining the corresponding temperature steady-state error coefficient, it is possible to evaluate the difficulty of the system to maintain temperature stability at the current desired heating adjustment temperature. For example, for certain specific heating adjustment temperatures, the system may be easier to achieve stable control, and the temperature steady-state error coefficient is small; while for other temperature settings, it may be difficult to maintain a stable temperature due to system characteristics or external environmental factors, and the coefficient is large. This coefficient provides a stability reference for the current heating adjustment temperature when calculating the heating output power. The operating characteristics and stability performance of the building heating system will be different for different heating adjustment temperatures. For example, at a lower heating adjustment temperature, the system may require a smaller power output to maintain stability, but at a higher heating adjustment temperature, the system may be more difficult to maintain stability due to factors such as increased heat load and changes in equipment operating conditions. The temperature steady-state error coefficient can quantify the stability characteristics of the system under a specific temperature setting. It obtains a coefficient value related to the current set temperature by analyzing and processing the historical operating data of the system at different heating adjustment temperatures. This value reflects the inherent ability of the system to remain stable at that temperature, that is, the degree of stability exhibited by the interaction of various internal factors (such as equipment performance, heat transfer characteristics, control logic, etc.) when the system reaches and maintains the heating regulation temperature. For example, a larger temperature steady-state error coefficient may mean that at the currently set heating adjustment temperature, the system is susceptible to external interference or changes in internal parameters, resulting in large temperature fluctuations and difficulty in maintaining stability; a smaller coefficient means that the system has better stability at this temperature setting and can relatively easily maintain the temperature within a stable range, so that the adjustment strategy can be optimized according to the characteristics of the temperature setting, ensuring that the indoor temperature is stable and comfortable while achieving the energy-saving goal. Finally, the heating output power is calculated based on the current heating output power, temperature deviation value, temperature difference steady-state error coefficient, power steady-state error coefficient and temperature steady-state error coefficient. The formula in this case is based on feedback regulation, which calculates the actual required temperature to infer the required regulated heating output power. At the same time, the temperature deviation value between the current actual temperature and the heating adjustment temperature is the key signal of feedback control, which intuitively reflects the difference between the current heating state and the expected state, and is the main basis for the system to adjust. Among them, K. 1: quantifies the ability of the heating system to control temperature deviation during long-term operation. It takes into account the relationship between the heating adjustment temperature and the current actual temperature, as well as the system's ability to maintain temperature stability. A smaller value means that the system can more effectively stabilize the actual temperature within a range close to the heating adjustment temperature and reduce temperature fluctuations; a larger value means that the system has a certain degree of instability in temperature control and requires more adjustments to correct temperature deviations. e(t): clarifies the gap between the current actual temperature and the desired heating adjustment temperature, and is an important basis for judging whether the heating system needs to be adjusted and the magnitude of the adjustment. If e(t) is a positive value, it means that the current actual temperature is lower than the heating adjustment temperature and the heating power needs to be increased; if e(t) is a negative value, it means that the current actual temperature is higher than the heating adjustment temperature and the heating power needs to be reduced. K 1 *e(t) is used to determine the initial adjustment of the current heating power according to the size of the temperature deviation and the stability of the system's temperature control, so as to adjust the power in the direction of reducing the temperature deviation. For example, when the temperature deviation is large and the system's temperature control is relatively stable (K 1 When K 1 *e(t) will be larger, so that the power is adjusted quickly to approach the target temperature, K 2 :The stability performance of the heating system in the past power adjustment process reflects the long-term stable deviation between the actual power output and the expected power output when the system adjusts the heating power according to different needs. It provides a historical experience reference for the current adjustment of heating output power, helping the system to formulate a more reasonable and stable power adjustment plan while considering factors such as the current temperature deviation and combining the past adjustment situation. 3 :Associated with the heating adjustment temperature, it reflects the system's ability to maintain a stable temperature under a specific heating adjustment temperature setting. Different heating adjustment temperatures may correspond to different system operating characteristics and stability requirements, providing a stability reference for the current heating adjustment temperature when calculating the heating output power. :Integral calculation, :Differential calculation, this calculation formula integrates multiple key factors, comprehensively considers the current actual temperature (reflecting the current thermal environment conditions), temperature deviation value (determines the adjustment direction and amplitude), temperature difference steady-state error coefficient (evaluates temperature control stability), power steady-state error coefficient (draws on historical power adjustment experience) and temperature steady-state error coefficient (for the stability of the current temperature setting), and accurately calculates the regulated heating output power. Through this comprehensive calculation, the heating power can be dynamically adjusted according to the actual situation, so that the heating system can respond to temperature changes quickly and accurately while maintaining stable operating performance. Finally, according to the regulated heating output power, the heating output power at the current user's location is optimized for energy saving. In this way, the calculated regulated heating output power is applied to the actual heating system to achieve accurate heating control at the user's location, so that the indoor temperature is always maintained in a state that can meet the user's comfort needs and maximize energy conservation, solving the problem of energy waste in the existing fixed heating mode.

[0032] The present application also provides an energy-saving optimization system based on building upgrading and transformation, including: A first acquisition module 1 is used to acquire building structural features based on building upgrade and reconstruction, wherein the building structural features include building structural layout features and building internal environment features; A second acquisition module 2 is used to acquire the office area area and the non-office area area according to the building structure layout characteristics, and acquire the intersecting scattering area area according to the office area area and the non-office area area; A third acquisition module 3 is used to acquire adjustment energy parameters and natural energy parameters according to the internal environment characteristics of the building; A fourth acquisition module 4 is used to obtain a radiation heating influence coefficient according to the scattering area, the adjustment energy parameter and the natural energy parameter; The fifth acquisition module 5 is used to acquire the user's historical activity trajectory and acquire the crowd density according to the user's historical activity trajectory; A sixth acquisition module 6 is used to acquire the current user's position, and acquire the vertical distance from the previous user's position to the edge of the scattering area according to the current user's position and the scattering area; The seventh acquisition module 7 is used to obtain the basic heating temperature at the current user's location, and obtain the heating adjustment temperature according to the basic heating temperature, the radiation heating influence coefficient, the edge vertical distance and the crowd density; The first adjustment module 8 is used to perform energy-saving optimization adjustment on the current user's location according to the heating adjustment temperature.

[0033] In one embodiment, the second acquisition module includes: A first acquisition unit, configured to acquire a first edge line of the office area according to the area of ​​the office area; A second acquiring unit, configured to acquire a second edge line of the non-office area according to the area of ​​the non-office area; A third acquisition unit, configured to acquire an edge distance between the first edge line and the second edge line according to the first edge line and the second edge line; A fourth acquisition unit, configured to acquire a first edge temperature of the first edge line based on a temperature sensor; a fifth acquiring unit, configured to acquire a second edge temperature of the second edge line based on a temperature sensor, and calculate an edge temperature difference according to the second edge temperature and the first edge temperature; A first connection unit, used to connect two ends of the first edge line and the second edge line in a closed manner to obtain an edge area; A sixth acquisition unit, used to acquire the thermal conductivity of a preset wall material; The first calculation unit is used to calculate the heat conduction flow rate according to the edge spacing, the edge temperature difference, the edge area and the thermal conductivity of the preset wall material, wherein the calculation formula is: ; Wherein, Q(W) represents the heat conduction flow, K(w) represents the thermal conductivity of the preset wall material, A(m) represents the edge area, ΔT represents the edge temperature difference, and d(m) represents the edge spacing; The seventh acquisition unit is used to acquire the flow area through which the heat conduction flow passes within a preset time, and use the flow area as the area of ​​the intersecting scattering region.

[0034] The present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above-mentioned energy-saving optimization method based on building upgrade and reconstruction when executing the computer program.

[0035] The present invention also provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the energy-saving optimization method based on building upgrade and reconstruction are implemented.

[0036] Those of ordinary skill in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media provided in this application and used in the embodiments may include non-volatile and / or volatile memory. Non-volatile memory may include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory may include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0037] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, device, article or method including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, device, article or method. In the absence of further restrictions, an element defined by the sentence "includes a ..." does not exclude the presence of other identical elements in the process, device, article or method including the element.

[0038] The above description is only a preferred embodiment of the present invention, and does not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made by using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the protection scope of this application.

Claims

1. An energy-saving optimization method based on building upgrading and reconstruction, characterized in that: include: Acquire building structural features based on building upgrading and reconstruction, wherein the building structural features include building structural layout features and building internal environment features; Acquire the office area area and the non-office area area according to the building structure layout characteristics, and acquire the intersecting scattering area area according to the office area area and the non-office area area; Acquiring regulated energy parameters and natural energy parameters according to the internal environmental characteristics of the building; Obtaining a radiation heating influence coefficient according to the scattering region area, the adjustment energy parameter and the natural energy parameter; Obtaining the user's historical activity trajectory, and obtaining the crowd density according to the user's historical activity trajectory; Acquire the current user's position, and acquire the vertical distance from the previous user's position to the edge of the scattering area according to the current user's position and the scattering area; Obtaining the basic heating temperature at the current user's location, and obtaining the heating adjustment temperature according to the basic heating temperature, the radiation heating influence coefficient, the edge vertical distance and the crowd density; Energy-saving optimization adjustment is performed on the current user's location according to the heating adjustment temperature.

2. The energy-saving optimization method based on building upgrading and reconstruction according to claim 1 is characterized in that: The step of acquiring the area of ​​the intersecting scattering area according to the area of ​​the office area and the area of ​​the non-office area comprises: Acquire a first edge line of the office area according to the area of ​​the office area; Acquire a second edge line of the non-office area according to the area of ​​the non-office area; Acquire an edge distance between the first edge line and the second edge line according to the first edge line and the second edge line; Acquiring a first edge temperature of the first edge line based on a temperature sensor; Acquire a second edge temperature of the second edge line based on a temperature sensor, and calculate an edge temperature difference according to the second edge temperature and the first edge temperature; Connecting two ends of the first edge line and the second edge line to obtain an edge area; Get the thermal conductivity of the preset wall material; The heat conduction flow is calculated according to the edge spacing, the edge temperature difference, the edge area and the thermal conductivity of the preset wall material, wherein the calculation formula is: ； Wherein, Q(W) represents the heat conduction flow, K(w) represents the thermal conductivity of the preset wall material, A(m) represents the edge area, ΔT represents the edge temperature difference, and d(m) represents the edge spacing; The flow area through which the heat conduction flow passes within a preset time is obtained, and the flow area is used as the area of ​​the intersecting scattering region.

3. The energy-saving optimization method based on building upgrading and reconstruction according to claim 1 is characterized in that: The step of obtaining the radiation heating influence coefficient according to the scattering area, the adjustment energy parameter and the natural energy parameter comprises: Obtaining heating output power according to the adjustment energy parameter; Obtaining the building height at the current user's location, and calculating the scattering area volume according to the building height and the scattering area area; Obtaining solar radiation temperature according to the natural energy parameter; Get the specific heat capacity and density of preset air; The indoor temperature within a preset time is calculated according to the heating output power, the scattering area volume, the solar radiation temperature, the specific heat capacity and the density, wherein the calculation formula is: ； Among them, T ROOM Indicates the indoor temperature, T OUT represents the solar radiation temperature, Q(L) represents the heating output power, ΔT(y) represents the preset time, V represents the scattering area volume, C p represents specific heat capacity, ρ represents density; The radiation heating influence coefficient is calculated according to the ratio of the indoor temperature to the area of ​​the scattering region.

4. The energy-saving optimization method based on building upgrading and reconstruction according to claim 1 is characterized in that: The step of obtaining the crowd density according to the user's historical activity trajectory includes: Acquire the area of ​​the user's stay area, and divide the user's stay area into grids according to unit areas to obtain multiple grid area areas; Obtaining the number of users in each grid within the area of ​​the plurality of grid regions; Calculate multiple crowd flow densities based on the ratio of the number of users in each grid to the corresponding grid area; An average crowd flow density is calculated according to the multiple crowd flow densities, and the average crowd flow density is used as the crowd flow density.

5. The energy-saving optimization method based on building upgrading and reconstruction according to claim 1 is characterized in that: The step of obtaining the heating adjustment temperature according to the basic heating temperature, the radiation heating influence coefficient, the edge vertical distance and the crowd density includes: Obtaining the location of a heating heat source, and obtaining a temperature loss factor according to the location of the heating heat source and a vertical distance from the edge; Obtaining a crowd temperature increment factor according to the basic heating temperature and crowd density; The heating adjustment temperature is calculated according to the basic heating temperature, the radiation heating influence coefficient, the edge vertical distance, the crowd density, the temperature loss factor and the crowd temperature increment factor, wherein the calculation formula is: ； Among them, T adjusted Indicates the heating adjustment temperature, T base represents the basic heating temperature, D(c) represents the vertical distance to the edge, S(s) represents the temperature loss factor, M(D) represents the crowd density, Z(L) represents the crowd temperature increment factor, and FS represents the radiation heating influence coefficient.

6. The energy-saving optimization method based on building upgrading and reconstruction according to claim 1 is characterized in that: The step of performing energy-saving optimization adjustment on the current user's location according to the heating adjustment temperature comprises: Get the current actual temperature of the current user's location; Acquire the corresponding current heating output power according to the current actual temperature; Acquire a temperature deviation value according to the heating adjustment temperature and the current actual temperature; Obtain the heating adjustment temperature and the current actual temperature to obtain a temperature difference steady-state error coefficient; Obtain the power steady-state error coefficient of historical power regulation; Obtain the heating adjustment temperature and obtain the corresponding temperature steady-state error coefficient; Calculate and adjust the heating output power according to the current heating output power, temperature deviation value, temperature difference steady-state error coefficient, power steady-state error coefficient and temperature steady-state error coefficient; The heating output power at the current user's location is adjusted for energy saving and optimization according to the adjustment of the heating output power.

7. An energy-saving optimization system based on building upgrading and reconstruction, characterized in that: include: A first acquisition module is used to acquire building structural features based on building upgrade and reconstruction, wherein the building structural features include building structural layout features and building internal environment features; A second acquisition module is used to acquire the office area area and the non-office area area according to the building structure layout characteristics, and acquire the intersection scattering area area according to the office area area and the non-office area area; A third acquisition module is used to acquire adjustment energy parameters and natural energy parameters according to the internal environment characteristics of the building; A fourth acquisition module, used for acquiring a radiation heating influence coefficient according to the scattering area, the adjustment energy parameter and the natural energy parameter; A fifth acquisition module, used to acquire a user's historical activity trajectory, and acquire a crowd density according to the user's historical activity trajectory; A sixth acquisition module, used to acquire the current user's position, and acquire the vertical distance from the previous user's position to the edge of the scattering area according to the current user's position and the scattering area; The seventh acquisition module is used to acquire the basic heating temperature at the current user's location, and acquire the heating adjustment temperature according to the basic heating temperature, the radiation heating influence coefficient, the edge vertical distance and the crowd density; The first adjustment module is used to perform energy-saving optimization adjustment on the current user's location according to the heating adjustment temperature.

8. The energy-saving optimization system based on building upgrading and reconstruction according to claim 7 is characterized in that: The second acquisition module includes: A first acquisition unit, configured to acquire a first edge line of the office area according to the area of ​​the office area; A second acquiring unit, configured to acquire a second edge line of the non-office area according to the area of ​​the non-office area; A third acquiring unit, configured to acquire an edge distance between the first edge line and the second edge line according to the first edge line and the second edge line; A fourth acquisition unit, configured to acquire a first edge temperature of the first edge line based on a temperature sensor; a fifth acquiring unit, configured to acquire a second edge temperature of the second edge line based on a temperature sensor, and calculate an edge temperature difference according to the second edge temperature and the first edge temperature; A first connection unit, used to connect two ends of the first edge line and the second edge line in a closed manner to obtain an edge area; A sixth acquisition unit, used to acquire the thermal conductivity of a preset wall material; The first calculation unit is used to calculate the heat conduction flow rate according to the edge spacing, the edge temperature difference, the edge area and the thermal conductivity of the preset wall material, wherein the calculation formula is: ； Wherein, Q(W) represents the heat conduction flow, K(w) represents the thermal conductivity of the preset wall material, A(m) represents the edge area, ΔT represents the edge temperature difference, and d(m) represents the edge spacing; The seventh acquisition unit is used to acquire the flow area through which the heat conduction flow passes within a preset time, and use the flow area as the area of ​​the intersecting scattering region.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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