Method, device and equipment for determining thermal insulation performance of house and storage medium
By acquiring temperature drop data from the heating system, calculating the temperature drop rate, and fitting the insulation performance curve, the accuracy problem of existing methods for determining building insulation performance is solved, achieving higher accuracy and energy efficiency.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-09
- Publication Date
- 2026-04-10
AI Technical Summary
Existing methods for determining the thermal insulation performance of buildings have low accuracy and cannot fully consider all factors that affect the thermal insulation performance of buildings, resulting in high computational complexity and low precision.
By acquiring temperature drop data of the heating system over a historical period, calculating the rate of temperature drop, and fitting the thermal insulation performance curve of the house based on a linear regression algorithm, the set temperature of the heating system is dynamically adjusted to improve accuracy.
It improves the accuracy of determining the thermal insulation performance of buildings, optimizes the operating efficiency and user comfort of heating systems, and reduces energy consumption.
Smart Images
Figure CN121834112A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application belongs to the technical field of intelligent household appliances, and particularly relates to a method and device for determining the thermal insulation performance of a house, equipment and a storage medium. BACKGROUND
[0002] A heating system is a system for providing heat to a house in cold seasons to maintain indoor comfortable temperature, such as a heating stove, a heat pump, a solar heating system, etc. The outdoor temperature has a significant impact on the heating system. In cold weather conditions, the indoor-outdoor temperature difference increases, the heat loss of the house increases, and the heat load demand of the heating system also increases, which means that the heating system needs to provide more heat to maintain the indoor temperature. At this time, the better the thermal insulation performance of the house, the smaller the heat loss, and vice versa. Therefore, the thermal insulation performance of the house is a key factor affecting the operation efficiency, energy consumption and user comfort of the heating system.
[0003] The existing method for determining the thermal insulation performance of a house is to calculate the thermal insulation performance of the house based on various parameters such as the structure and materials of the house, which has low accuracy. SUMMARY
[0004] The present application provides a method and device for determining the thermal insulation performance of a house, equipment and a storage medium to solve the problem of low accuracy of the existing method for determining the thermal insulation performance of a house.
[0005] In a first aspect, the present application provides a method for determining the thermal insulation performance of a house, which comprises:
[0006] Obtaining a plurality of sets of temperature drop data of a heating system of the house in a first historical time period, each set of temperature drop data comprising a historical outlet water temperature, a historical return water temperature, a first time, a second time and a historical outdoor temperature at the first time, wherein the first time is the time when the outlet water temperature of the heating system reaches the historical outlet water temperature and stops heating, and the second time is the time after the first time when the return water temperature of the heating system reaches the historical return water temperature and resumes heating;
[0007] Determining a historical temperature drop rate corresponding to each set of temperature drop data based on the historical outlet water temperature, the historical return water temperature, the first time and the second time in each set of temperature drop data;
[0008] Fitting to obtain a thermal insulation performance curve of the house based on a plurality of sets of historical temperature drop rates and corresponding historical outdoor temperatures, wherein the thermal insulation performance curve of the house represents the corresponding relationship between the outdoor temperature and the temperature drop rate.
[0009] In some embodiments, the determining, based on the historical outlet water temperature, the historical return water temperature, the first time and the second time in each of the groups of the temperature drop data, a historical temperature drop rate corresponding to each of the groups of the temperature drop data, comprises:
[0010] determining a first difference between the historical outlet water temperature and the historical return water temperature, and a second difference between the second time and the first time;
[0011] determining a ratio of the first difference and the second difference as the historical temperature drop rate.
[0012] In some embodiments, the fitting, based on the groups of the historical temperature drop rates and the corresponding historical outdoor temperatures, the thermal performance curve of the house, comprises:
[0013] clustering the groups of the historical temperature drop rates and the corresponding historical outdoor temperatures, and removing the historical temperature drop rates and the corresponding historical outdoor temperatures that are not clustered into a cluster;
[0014] fitting, by using a linear regression algorithm, the groups of the historical temperature drop rates and the corresponding historical outdoor temperatures in the cluster obtained by clustering, to obtain the thermal performance curve of the house.
[0015] In some embodiments, the method further comprises:
[0016] obtaining a first outdoor temperature of the house at present;
[0017] determining a first temperature drop rate based on the first outdoor temperature and the thermal performance curve of the house;
[0018] adjusting a set temperature of the heating system based on the first temperature drop rate.
[0019] In some embodiments, the clusters obtained by clustering are multiple, the historical outdoor temperatures in different clusters correspond to different temperature intervals, and different temperature intervals do not overlap.
[0020] The fitting, by using a linear regression algorithm, the groups of the historical temperature drop rates and the corresponding historical outdoor temperatures in the cluster obtained by clustering, to obtain the thermal performance curve of the house, comprises:
[0021] for each of the clusters, fitting, by using a linear regression algorithm, the groups of the historical temperature drop rates and the corresponding historical outdoor temperatures in the cluster to obtain a thermal performance curve corresponding to a temperature interval of the cluster, and the thermal performance curve of the house comprises multiple thermal performance curves corresponding to multiple temperature intervals.
[0022] In some embodiments, the method further comprises:
[0023] obtaining a second outdoor temperature of the house currently;
[0024] based on the second outdoor temperature, determining a first heat preservation performance curve corresponding to a temperature interval in which the second outdoor temperature is located, from the heat preservation performance curves corresponding to the plurality of temperature intervals;
[0025] based on the second outdoor temperature and the first heat preservation performance curve, determining a second temperature drop rate;
[0026] based on the second temperature drop rate, adjusting a set temperature of the heating system.
[0027] In some embodiments, the method further comprises:
[0028] obtaining a plurality of sets of temperature drop data of the heating system of the house in a second historical time period, the second historical time period being a time period after the first historical time period;
[0029] based on the plurality of sets of temperature drop data in the second historical time period, correcting the heat preservation performance curve of the house.
[0030] In a second aspect, the present application provides a device for determining heat preservation performance of a house, the device comprising:
[0031] an obtaining module, configured to obtain a plurality of sets of temperature drop data of a heating system of the house in a first historical time period, each set of the temperature drop data comprising a historical outlet water temperature, a historical return water temperature, a first time, a second time and a historical outdoor temperature at the first time, wherein the first time is a time when the outlet water temperature of the heating system reaches the historical outlet water temperature and heating stops, and the second time is a time after the first time when the return water temperature of the heating system reaches the historical return water temperature and heating resumes;
[0032] a processing module, configured to determine a historical temperature drop rate corresponding to each set of the temperature drop data based on the historical outlet water temperature, the historical return water temperature, the first time and the second time in each set of the temperature drop data;
[0033] The processing module is further configured to fit a heat preservation performance curve of the house based on the plurality of sets of historical temperature drop rates and corresponding historical outdoor temperatures, the heat preservation performance curve of the house representing a corresponding relationship between an outdoor temperature and a temperature drop rate.
[0034] In some embodiments, the processing module is further configured to determine a first difference between the historical outlet water temperature and the historical return water temperature, and a second difference between the second time and the first time.
[0035] The processing module is further configured to determine the ratio of the first difference to the second difference as the historical temperature drop rate.
[0036] In some embodiments, the processing module is further configured to cluster the multiple sets of historical temperature drop rates and corresponding historical outdoor temperatures, and remove the historical temperature drop rates and corresponding historical outdoor temperatures that are not clustered into clusters.
[0037] The processing module is further configured to use a linear regression algorithm to fit the thermal insulation performance curve of the house to multiple sets of historical temperature drop rates and corresponding historical outdoor temperatures in the clusters obtained by clustering.
[0038] In some embodiments, the device further includes: a control module;
[0039] The acquisition module is also used to acquire the current first outdoor temperature of the house;
[0040] The processing module is further configured to determine a first temperature drop rate based on the first outdoor temperature and the thermal insulation performance curve of the house;
[0041] The control module is used to adjust the set temperature of the heating system based on the first temperature drop rate.
[0042] In some embodiments, the clusters obtained by clustering are multiple, and the historical outdoor temperatures in different clusters correspond to different temperature ranges, and the different temperature ranges do not overlap;
[0043] The processing module is further configured to, for each cluster, use a linear regression algorithm to fit multiple sets of historical temperature drop rates and corresponding historical outdoor temperatures in the cluster to obtain the thermal insulation performance curve corresponding to the temperature range of the cluster, wherein the thermal insulation performance curve of the house includes thermal insulation performance curves corresponding to multiple temperature ranges.
[0044] In some embodiments, the acquisition module is further configured to acquire the current second outdoor temperature of the house;
[0045] The processing module is further configured to determine, based on the second outdoor temperature, the first thermal insulation performance curve corresponding to the temperature range in which the second outdoor temperature is located from the thermal insulation performance curves corresponding to each of the plurality of temperature ranges.
[0046] The processing module is further configured to determine a second temperature drop rate based on the second outdoor temperature and the first thermal insulation performance curve;
[0047] The control module is also used to adjust the set temperature of the heating system based on the second temperature drop rate.
[0048] In some embodiments, the acquisition module is further configured to acquire multiple sets of temperature drop data of the heating system of the house within a second historical time period, wherein the second historical time period is the time after the first historical time period;
[0049] The processing module is also used to correct the thermal insulation performance curve of the house based on multiple sets of temperature drop data within the second historical time period.
[0050] Thirdly, this application provides a device for determining the thermal insulation performance of a building, comprising:
[0051] Memory;
[0052] processor;
[0053] The memory stores computer-executed instructions;
[0054] The processor executes computer execution instructions stored in the memory to implement the method for determining the thermal insulation performance of a building as described in the first aspect and various possible implementations thereof.
[0055] Fourthly, this application provides a computer storage medium storing computer execution instructions thereon, which are executed by a processor to implement the method for determining the thermal insulation performance of a building as described in the first aspect and various possible implementations thereof.
[0056] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the method for determining the thermal insulation performance of a building as described in the first aspect and various possible implementations of the first aspect.
[0057] The method for determining the thermal insulation performance of a building provided in this application acquires multiple sets of temperature drop data for the building's heating system within a first historical time period. Each set of temperature drop data includes historical outlet water temperature, historical return water temperature, a first moment, a second moment, and the historical outdoor temperature at the first moment. The first moment is the time when the heating system's outlet water temperature reaches the historical outlet water temperature and heating stops. The second moment is the time after the first moment when the heating system's return water temperature reaches the historical return water temperature and heating resumes. Based on the historical outlet water temperature, historical return water temperature, the first moment, and the second moment in each set of temperature drop data, the historical temperature drop rate corresponding to each set of temperature drop data is determined. Based on multiple sets of historical temperature drop rates and the corresponding historical outdoor temperatures, a thermal insulation performance curve of the building is fitted. This method enables the determination of the thermal insulation performance of different buildings under different outdoor temperatures, improving the accuracy of determining the building's thermal insulation performance. Attached Figure Description
[0058] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.
[0059] Figure 1 This application outlines the process for determining the thermal insulation performance of a building. Figure One ;
[0060] Figure 2 This application outlines the process for determining the thermal insulation performance of a building. Figure Two ;
[0061] Figure 3 This is a schematic diagram of the structure of the device for determining the thermal insulation performance of a building provided in this application;
[0062] Figure 4 This is a structural schematic diagram of the device for determining the thermal insulation performance of a building provided in this application.
[0063] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation
[0064] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.
[0065] The terms "first," "second," "third," "fourth," etc. (if present) in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein.
[0066] In this application, the terms "exemplary" or "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design described as "exemplary" or "for example" in this application should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of terms such as "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.
[0067] Determining a building's thermal insulation performance plays a crucial role in the operating efficiency, energy consumption, and user comfort of heating systems. Existing methods for determining building thermal insulation performance are based on calculations of various parameters such as the building's structure and materials to evaluate its thermal insulation capabilities.
[0068] However, the factors affecting the thermal insulation performance of different houses vary, and existing methods for determining the thermal insulation performance of houses cannot fully consider the influence of various building factors on the thermal insulation performance of houses. Therefore, direct calculation is highly complex and it is not easy to obtain various parameters, resulting in low calculation accuracy.
[0069] To address the aforementioned issues, this application provides a method for determining the thermal insulation performance of a building. This method acquires multiple sets of temperature drop data over a historical period, including historical outlet water temperature, historical return water temperature, the moment when the heating system's outlet water temperature reaches the historical outlet water temperature and heating stops (temperature drop start time), the moment when the heating system's return water temperature reaches the historical return water temperature and heating resumes (temperature drop end time), and historical outdoor temperature. Based on the temperature drop start time, temperature drop end time, historical outlet water temperature, and historical return water temperature, a historical temperature drop rate is obtained, with each set of temperature drop data corresponding to a historical temperature drop rate. Finally, based on multiple sets of historical temperature drop rates and corresponding historical outdoor temperatures, a linear regression algorithm is used to fit and obtain the building's thermal insulation performance curve. This method uses the temperature drop process of the heating system to represent the building's thermal insulation performance, which is more accurate than existing technologies that calculate thermal insulation performance based on building parameters.
[0070] The technical solutions of this application and how they solve the aforementioned technical problems are described in detail below with specific embodiments. These specific embodiments can be implemented independently or in combination with each other. Identical or similar concepts or processes may not be repeated in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.
[0071] Figure 1 The flowchart of the method for determining the thermal insulation performance of a building provided in the embodiments of this application Figure One .like Figure 1 As shown, the method for determining the thermal insulation performance of a building provided in this embodiment includes:
[0072] S101. Obtain multiple sets of temperature drop data for the heating system of the house within the first historical time period. Each set of temperature drop data includes the historical outlet water temperature, the historical return water temperature, the first moment, the second moment, and the historical outdoor temperature at the first moment.
[0073] The first moment is the moment when the outlet water temperature of the heating system reaches the historical outlet water temperature and heating stops. The second moment is the moment after the first moment when the return water temperature of the heating system reaches the historical return water temperature and heating resumes. The first historical time period is, for example, 7 days.
[0074] Understandably, when the heating system is a boiler, the historical outlet water temperature can be the outlet water temperature at which the boiler heats the water to the user's set temperature and provides it to terminal devices such as underfloor heating or radiators. The first moment refers to the moment when the boiler stops heating from ignition until the outlet water temperature reaches the user's set temperature. The second moment refers to the moment when, after the boiler outlet water is released, the hot water transfers heat to the indoor air through heat exchange, raising the indoor temperature, and then returns to the boiler through the return water pipe, causing the return water temperature to drop to the historical return water temperature so that the boiler can resume heating.
[0075] In one possible implementation, historical outlet water temperature can be detected by a temperature sensor installed at the outlet pipe of the heating boiler, historical return water temperature can be detected by a temperature sensor installed at the return pipe of the heating boiler, and historical outdoor temperature can be obtained by an outdoor temperature sensor, or by querying historical weather information for the area where the heating boiler is located. A data logger connected to these temperature sensors is used, and the sampling frequency of the data logger is set, for example, to record data once per minute, to ensure that the data logger automatically records the outlet water temperature, return water temperature, and corresponding timestamp every minute within a first historical period, for example, 7 days. After the heating boiler collects this historical data, it can extract all the data within the first historical period from the data logger and filter this data to obtain multiple sets of temperature drop data that meet certain conditions. For example, at 14:00, the historical outlet water temperature is 65℃; at 14:05, the historical return water temperature is 45℃; and the corresponding outdoor temperature at 14:00 is 2℃.
[0076] S102. Based on the historical outlet water temperature, historical return water temperature, first moment and second moment in each set of temperature drop data, determine the historical temperature drop rate corresponding to each set of temperature drop data.
[0077] In this case, the first and second moments corresponding to each set of temperature drop data are different. Therefore, multiple historical temperature drop rates can be calculated, which is the rate of temperature drop during the process of the heating system's water temperature dropping from the outlet temperature to the return temperature after heat exchange, so that the heating system can reheat. The historical temperature drop rate can be used to indicate the efficiency and performance of the heating system.
[0078] In some embodiments, the historical temperature drop rate can be determined by determining a first difference between the historical outlet water temperature and the historical return water temperature, and a second difference between the second time point and the first time point, and then the ratio of the first difference to the second difference.
[0079] The first moment refers to the start time of the temperature drop, and the second moment refers to the end time of the temperature drop. Therefore, the difference between the first moment and the second moment, i.e., the second difference, can be understood as the time it takes for the heating system to go from not heating to heating, which is the time it takes for the historical return water temperature to drop from the historical outlet water temperature to the point where it needs to be reheated to the user-set temperature. The first difference between the historical outlet water temperature and the historical return water temperature refers to the magnitude of the temperature drop in the heating system, i.e., the heat loss of the heating system between the first moment and the second moment.
[0080] For example, given a set of temperature drop data: the first time is 14:00, the historical outlet water temperature is 65℃, and the second time is 14:05, the historical return water temperature is 45℃, the first difference is 65℃-45℃=20℃, the second difference is 14:05-14:00=5min, and the corresponding historical temperature drop rate is 20℃ / 5min=4℃ / min.
[0081] Understandably, historical temperature drop rates are used to indicate a building's insulation performance, as they directly reflect how quickly the water temperature in the heating system drops after heating is stopped. A faster temperature drop rate indicates poorer insulation, while a slower rate indicates better insulation.
[0082] S103. Based on multiple sets of historical temperature drop rates and corresponding historical outdoor temperatures, the thermal insulation performance curve of the house is obtained by fitting.
[0083] The thermal insulation performance curve of a building represents the relationship between outdoor temperature and the rate of temperature drop. A building's thermal insulation performance refers to its ability to maintain a stable indoor temperature when outdoor temperature changes. Historical temperature drop rates can be used to represent this performance. By using multiple sets of historical temperature drop rates and corresponding historical outdoor temperatures, a linear relationship between historical outdoor temperature and building insulation performance can be determined, such as a straight line.
[0084] For example, multiple historical temperature drop rates and corresponding historical outdoor temperatures can be clustered, and historical temperature drop rates and corresponding historical outdoor temperatures that are not clustered into clusters can be removed.
[0085] For multiple historical temperature drop rates and corresponding historical outdoor temperatures in the clusters obtained from clustering, a linear regression algorithm is used to fit the thermal insulation performance curve of the building.
[0086] Before fitting the thermal insulation performance curve using a linear regression algorithm, multiple historical temperature drop rates and corresponding historical outdoor temperatures are clustered to remove outliers. Outliers are data points that are significantly different from other data points, which may be caused by measurement errors, equipment failures, or other external factors. Through cluster analysis, these outliers can be identified and removed, thereby improving the accuracy and reliability of the linear regression model. The linear regression algorithm can be, for example, a multiple linear regression equation.
[0087] For example, the formula for the thermal insulation performance curve obtained by linear regression fitting can be expressed as: y = ax + b
[0088] Where y is the rate of temperature drop, x is the outdoor temperature, and a and b are constant parameters, with different values for a and b for different houses.
[0089] Understandably, in the above formula, 'a' indicates the degree of influence of outdoor temperature on the rate of temperature drop. The smaller the slope, the smaller the influence of outdoor temperature on the rate of temperature drop, and the better the thermal insulation performance of the house. 'b' represents the rate of temperature drop when the outdoor temperature is 0℃, which can be used as a benchmark reference.
[0090] For example, when a is 2.5, it means that for every 1°C increase in outdoor temperature, the corresponding temperature drop rate of the house increases by 2.5°C / hour. When b is 15, it means that when the outdoor temperature is 0°C, the historical temperature drop rate is 15°C / hour.
[0091] Optionally, after obtaining the thermal insulation performance curve of the house, the heating system can be automatically adjusted to set the outlet water temperature based on the thermal insulation performance curve, so as to achieve automatic adjustment of the heating temperature according to the thermal insulation performance of the house.
[0092] In some embodiments, the current outdoor temperature of the house can be obtained, a first temperature drop rate can be determined based on the first outdoor temperature and the thermal insulation performance curve of the house, and the set temperature of the heating system can be adjusted based on the first temperature drop rate.
[0093] If the thermal insulation performance curve obtained by linear regression is y = 2.5x + b, and the current first outdoor temperature is 5℃, then the first temperature drop rate is y = 2.5 × 5 + 15 = 27.5℃ / hour. At this time, the target outlet water temperature of the heating system can be calculated based on the mapping relationship between the first temperature drop rate, the current indoor temperature and the current outdoor temperature.
[0094] In some embodiments, the thermal insulation performance of a house is also affected by a variety of factors, such as the condition of doors and windows, the number of people active indoors, the heat emitted by various equipment operating indoors, and the aging of the house's insulation materials and flooring materials over time. As a result, the thermal insulation performance changes accordingly. Therefore, the thermal insulation performance curve of a house can be dynamically corrected and adjusted based on multiple sets of temperature drop data to ensure the accuracy of the house's thermal insulation performance curve.
[0095] For example, multiple sets of temperature drop data of the house's heating system can be obtained within a second historical time period, where the second historical time period is the time after the first historical time period;
[0096] The thermal insulation performance curve of the house was corrected based on multiple sets of temperature drop data within the second historical time period.
[0097] Among them, based on multiple sets of temperature drop data in the second historical time period, new thermal insulation performance curves can be obtained by re-clustering and linear regression fitting. The newly fitted thermal insulation performance curves are then compared with the thermal insulation performance curves corresponding to the first historical time period, and necessary corrections are made to improve the accuracy and reliability of the thermal insulation performance curves.
[0098] The method for determining the thermal insulation performance of a building provided in this embodiment acquires multiple sets of temperature drop data of the building's heating system within a first historical time period. Each set of temperature drop data includes historical outlet water temperature, historical return water temperature, a first moment, a second moment, and the historical outdoor temperature at the first moment. The first moment is the time when the heating system stops heating when the outlet water temperature reaches the historical outlet water temperature, and the second moment is the time when heating resumes after the first moment when the return water temperature reaches the historical return water temperature. Based on the historical outlet water temperature, historical return water temperature, first moment, and second moment in each set of temperature drop data, the historical temperature drop rate corresponding to each set of temperature drop data is determined. Based on multiple sets of historical temperature drop rates and corresponding historical outdoor temperatures, a thermal insulation performance curve of the building is fitted. This method enables the determination of the thermal insulation performance of different buildings under different outdoor temperatures, improving the accuracy of determining the thermal insulation performance of a building.
[0099] Figure 2 The flowchart of the method for determining the thermal insulation performance of a building provided in the embodiments of this application Figure Two This embodiment is... Figure 1 Based on the embodiments, a method for adjusting the set temperature of a heating system based on the building's thermal insulation performance will be described in detail. For example... Figure 2 As shown, the method for determining the thermal insulation performance of a building provided in this embodiment includes:
[0100] S201. Obtain multiple sets of temperature drop data for the heating system of the house within the first historical time period. Each set of temperature drop data includes the historical outlet water temperature, the historical return water temperature, the first moment, the second moment, and the historical outdoor temperature at the first moment.
[0101] Step S201 is similar to step S101 above, and will not be repeated here.
[0102] S202. Based on the historical outlet water temperature, historical return water temperature, first moment and second moment in each set of temperature drop data, determine the historical temperature drop rate corresponding to each set of temperature drop data.
[0103] Step S202 is similar to step S102 above, and will not be described again here.
[0104] S203. Cluster the historical temperature drop rates and corresponding historical outdoor temperatures of multiple groups, and remove the historical temperature drop rates and corresponding historical outdoor temperatures that are not clustered into a cluster.
[0105] In this step, multiple clusters are obtained through clustering. The historical outdoor temperatures in different clusters correspond to different temperature ranges, and the different temperature ranges do not overlap.
[0106] Understandably, clustering multiple sets of historical cooling rates and corresponding historical outdoor temperatures can yield one or more clusters. This refers to the case where multiple clusters are obtained. First, the historical outdoor temperatures can be divided into multiple preset temperature ranges, and the maximum and minimum outdoor temperature values corresponding to each preset temperature range can be obtained to ensure that these ranges do not overlap. Based on the non-overlapping temperature ranges, data points are redistributed to the corresponding clusters to obtain multiple clusters. Then, those historical cooling rates and corresponding historical outdoor temperature data points that have not been assigned to any cluster are removed to ensure the accuracy of the insulation performance curves subsequently fitted by all clusters.
[0107] S204. For each cluster, the thermal insulation performance curve corresponding to the temperature range of the cluster is obtained by fitting multiple sets of historical temperature drop rates and corresponding historical outdoor temperatures in the cluster using a linear regression algorithm.
[0108] The building's thermal insulation performance curves include multiple temperature ranges, each with its own corresponding curve. Therefore, the number of thermal insulation performance curves matches the number of temperature ranges. Each cluster has a linear regression equation describing its thermal insulation performance curve. For example, cluster 1 corresponds to the temperature range [0℃, 4℃], and cluster 2 corresponds to the temperature range [5℃, 8℃]. The slopes of the thermal insulation performance curves for different temperature ranges may differ, reflecting the changes in the building's thermal insulation performance under different outdoor temperature conditions. For instance, for the low-temperature range [0℃, 4℃] corresponding to cluster 1, the slope of its thermal insulation performance curve is relatively large, indicating that when the outdoor temperature is low, the indoor heating system experiences a faster temperature drop. In this case, the thermal insulation performance curve for cluster 1 could be, for example, y = 3x + 10. For the low-temperature range [5℃, 8℃] corresponding to cluster 2, the slope of its thermal insulation performance curve is relatively small, indicating that when the outdoor temperature is high, the indoor heating system experiences a slower temperature drop. In this case, the thermal insulation performance curve for cluster 2 could be, for example, y = 2x + 20.
[0109] S205. Obtain the current second outdoor temperature of the house.
[0110] For example, the current outdoor temperature of the house can be obtained through an outdoor temperature sensor, or when the heating system is connected to a cloud server, the heating system can query the current outdoor temperature from the cloud server.
[0111] S206. Based on the second outdoor temperature, determine the first thermal insulation performance curve corresponding to the temperature range where the second outdoor temperature is located from the thermal insulation performance curves corresponding to multiple temperature ranges.
[0112] Specifically, based on the current outdoor temperature, the temperature range to which the current outdoor temperature belongs is determined, and the thermal insulation performance curve corresponding to this temperature range is used as the first thermal insulation performance curve.
[0113] S207. Based on the second outdoor temperature and the first thermal insulation performance curve, determine the second temperature drop rate.
[0114] Since the first thermal insulation performance curve is used to indicate the linear relationship between the second temperature drop rate and the second outdoor temperature, the first thermal insulation performance curve can be used to calculate the temperature drop rate at the current outdoor temperature, i.e., the second temperature drop rate.
[0115] S208. Adjust the set temperature of the heating system based on the second temperature drop rate.
[0116] For example, the set temperature of the heating system can be adjusted according to the second temperature drop rate, the second outdoor temperature and the current indoor temperature, the difference between the second outdoor temperature and the current indoor temperature can be calculated to obtain the indoor-outdoor temperature difference, and then the target outlet temperature of the heating system, i.e. the set temperature, can be determined based on the mapping relationship between the indoor-outdoor temperature difference, the second temperature drop rate and the outlet water temperature, and the heating system can be controlled to adjust the outlet water temperature to the set temperature.
[0117] The method for determining the thermal insulation performance of a building provided in this embodiment determines the historical temperature drop rate corresponding to each set of temperature drop data, clusters multiple sets of historical temperature drop rates and corresponding historical outdoor temperatures to obtain multiple clusters, and uses a linear regression algorithm to fit the thermal insulation performance curve corresponding to the temperature range of each cluster. This achieves the determination of the corresponding thermal insulation performance curve of the building under different outdoor temperature ranges, improving the accuracy of determining the building's thermal insulation performance. By obtaining the current outdoor temperature of the building, based on the current outdoor temperature, a first thermal insulation performance curve corresponding to the temperature range where the current outdoor temperature is located is determined from the thermal insulation performance curves corresponding to each of the multiple temperature ranges. Based on the current outdoor temperature and the first thermal insulation performance curve, the current temperature drop rate is determined, and then the set temperature of the heating system is adjusted based on the current temperature drop rate. In this way, the outlet water temperature of the heating system can be adjusted based on the building's thermal insulation performance under different outdoor temperatures for the same user, improving user comfort and avoiding energy consumption caused by users blindly adjusting the set temperature due to excessively low outdoor temperatures, thereby achieving energy saving.
[0118] Figure 3 A schematic diagram of the structure of the device for determining the thermal insulation performance of a building provided in this application. Figure 3 As shown, this application provides a device for determining the thermal insulation performance of a building. The device 300 for determining the thermal insulation performance of a building includes:
[0119] The acquisition module 301 is used to acquire multiple sets of temperature drop data of the heating system of the house within a first historical time period. Each set of temperature drop data includes historical outlet water temperature, historical return water temperature, first moment, second moment, and historical outdoor temperature at the first moment. The first moment is the moment when the outlet water temperature of the heating system reaches the historical outlet water temperature and heating stops. The second moment is the moment after the first moment when the return water temperature of the heating system reaches the historical return water temperature and heating resumes.
[0120] Processing module 302 is used to determine the historical temperature drop rate corresponding to each set of temperature drop data based on the historical outlet water temperature, the historical return water temperature, the first time moment, and the second time moment in each set of temperature drop data;
[0121] The processing module 302 is further configured to fit the thermal insulation performance curve of the house based on multiple sets of historical temperature drop rates and corresponding historical outdoor temperatures, wherein the thermal insulation performance curve of the house characterizes the correspondence between outdoor temperature and temperature drop rate.
[0122] In some embodiments, the processing module 302 is further configured to determine a first difference between the historical outlet water temperature and the historical return water temperature, and a second difference between the second time point and the first time point;
[0123] The processing module 302 is further configured to determine the ratio of the first difference to the second difference as the historical temperature drop rate.
[0124] In some embodiments, the processing module 302 is further configured to cluster the multiple sets of historical temperature drop rates and corresponding historical outdoor temperatures, and remove the historical temperature drop rates and corresponding historical outdoor temperatures that are not clustered into clusters.
[0125] The processing module 302 is further configured to use a linear regression algorithm to fit the thermal insulation performance curve of the house to multiple sets of historical temperature drop rates and corresponding historical outdoor temperatures in the clusters obtained by clustering.
[0126] In some embodiments, the device further includes: a control module 303;
[0127] The acquisition module 301 is also used to acquire the current first outdoor temperature of the house;
[0128] The processing module 302 is further configured to determine a first temperature drop rate based on the first outdoor temperature and the thermal insulation performance curve of the house;
[0129] The control module 303 is used to adjust the set temperature of the heating system based on the first temperature drop rate.
[0130] In some embodiments, the clusters obtained by clustering are multiple, and the historical outdoor temperatures in different clusters correspond to different temperature ranges, and the different temperature ranges do not overlap;
[0131] The processing module 302 is further configured to, for each cluster, use a linear regression algorithm to fit multiple sets of historical temperature drop rates and corresponding historical outdoor temperatures in the cluster to obtain the thermal insulation performance curve corresponding to the temperature range of the cluster, wherein the thermal insulation performance curve of the house includes thermal insulation performance curves corresponding to multiple temperature ranges.
[0132] In some embodiments, the acquisition module 301 is further configured to acquire the current second outdoor temperature of the house;
[0133] The processing module 302 is further configured to determine, based on the second outdoor temperature, the first thermal insulation performance curve corresponding to the temperature range in which the second outdoor temperature is located from the thermal insulation performance curves corresponding to each of the plurality of temperature ranges.
[0134] The processing module 302 is further configured to determine a second temperature drop rate based on the second outdoor temperature and the first thermal insulation performance curve;
[0135] The control module 303 is also used to adjust the set temperature of the heating system based on the second temperature drop rate.
[0136] In some embodiments, the acquisition module 301 is further configured to acquire multiple sets of temperature drop data of the heating system of the house within a second historical time period, wherein the second historical time period is the time after the first historical time period;
[0137] The processing module 302 is also used to correct the thermal insulation performance curve of the house based on multiple sets of temperature drop data within the second historical time period.
[0138] Figure 4 A structural schematic diagram of the device used to determine the thermal insulation performance of a building, as provided in this application. Figure 4 As shown, this application provides a device for determining the thermal insulation performance of a building. The device 400 for determining the thermal insulation performance of a building includes: a receiver 401, a transmitter 402, a processor 403, and a memory 404.
[0139] Receiver 401 is used to receive instructions and data;
[0140] Transmitter 402 is used to send commands and data;
[0141] Memory 404 is used to store instructions executed by the computer;
[0142] Processor 403 is used to execute computer execution instructions stored in memory 404 to implement the various steps of the method for determining the thermal insulation performance of a building in the above embodiments. For details, please refer to the relevant descriptions in the embodiments of the method for determining the thermal insulation performance of a building.
[0143] Alternatively, the memory 404 can be either standalone or integrated with the processor 403.
[0144] When the memory 404 is set up independently, the device for determining the thermal insulation performance of the house also includes a bus for connecting the memory 404 and the processor 403.
[0145] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the method for determining the thermal insulation performance of a building as described above by the electronic device.
[0146] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method for determining the thermal insulation performance of a building.
[0147] It will be understood by those skilled in the art that all or some of the steps, systems, or apparatuses disclosed above, and their functional modules / units, can be implemented as software, firmware, hardware, or suitable combinations thereof. In hardware implementations, the division between functional modules / units mentioned in the above description does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed collaboratively by several physical components. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit (ASIC). Such software may be distributed on a computer-readable medium, which may include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by a computer. Furthermore, it is well known to those skilled in the art that communication media typically contain computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.
[0148] The technical solutions of this application have been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it is readily understood by those skilled in the art that the scope of protection of this application is obviously not limited to these specific embodiments. The above embodiments are only used to illustrate the technical solutions of this application and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. These modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.
Claims
1. A method for determining the thermal insulation performance of a building, characterized in that, include: The heating system of the house is acquired in multiple sets of temperature drop data within a first historical time period. Each set of temperature drop data includes historical outlet water temperature, historical return water temperature, a first moment, a second moment, and the historical outdoor temperature at the first moment. The first moment is the moment when the outlet water temperature of the heating system reaches the historical outlet water temperature and heating stops. The second moment is the moment after the first moment when the return water temperature of the heating system reaches the historical return water temperature and heating resumes. Based on the historical outlet water temperature, the historical return water temperature, the first moment, and the second moment in each set of temperature drop data, determine the historical temperature drop rate corresponding to each set of temperature drop data; Based on multiple sets of historical temperature drop rates and corresponding historical outdoor temperatures, the thermal insulation performance curve of the house is obtained by fitting. The thermal insulation performance curve of the house represents the correspondence between outdoor temperature and temperature drop rate.
2. The method according to claim 1, characterized in that, The step of determining the historical temperature drop rate corresponding to each set of temperature drop data based on the historical outlet water temperature, the historical return water temperature, the first time moment, and the second time moment in each set of temperature drop data includes: Determine a first difference between the historical outlet water temperature and the historical return water temperature, and a second difference between the second time point and the first time point; The ratio of the first difference to the second difference is determined as the historical temperature drop rate.
3. The method according to claim 1, characterized in that, The process of fitting the thermal insulation performance curve of the house based on multiple sets of historical temperature drop rates and corresponding historical outdoor temperatures includes: The historical temperature drop rates and corresponding historical outdoor temperatures of the multiple sets are clustered, and the historical temperature drop rates and corresponding historical outdoor temperatures that are not clustered into a cluster are removed. The thermal insulation performance curve of the house is obtained by fitting multiple sets of historical temperature drop rates and corresponding historical outdoor temperatures in the clusters obtained by clustering using a linear regression algorithm.
4. The method according to any one of claims 1-3, characterized in that, Also includes: Obtain the current first outdoor temperature of the house; Based on the first outdoor temperature and the thermal insulation performance curve of the house, the first temperature drop rate is determined; The set temperature of the heating system is adjusted based on the first temperature drop rate.
5. The method according to claim 3, characterized in that, The clustering results in multiple clusters, and the historical outdoor temperatures in different clusters correspond to different temperature ranges, and the different temperature ranges do not overlap. The thermal insulation performance curve of the building is obtained by fitting multiple sets of historical temperature drop rates and corresponding historical outdoor temperatures in the clusters obtained from clustering using a linear regression algorithm, including: For each of the aforementioned clusters, the thermal insulation performance curve corresponding to the temperature range of the cluster is obtained by fitting multiple sets of historical temperature drop rates and corresponding historical outdoor temperatures in the cluster using a linear regression algorithm. The thermal insulation performance curve of the house includes thermal insulation performance curves corresponding to multiple temperature ranges.
6. The method according to claim 5, characterized in that, Also includes: Obtain the current second outdoor temperature of the house; Based on the second outdoor temperature, the first thermal insulation performance curve corresponding to the temperature range where the second outdoor temperature is located is determined from the thermal insulation performance curves corresponding to each of the multiple temperature ranges. Based on the second outdoor temperature and the first thermal insulation performance curve, the second temperature drop rate is determined; The set temperature of the heating system is adjusted based on the second temperature drop rate.
7. The method according to claim 4, characterized in that, Also includes: Obtain multiple sets of temperature drop data for the heating system of the house during a second historical time period, where the second historical time period is the time following the first historical time period. The thermal insulation performance curve of the house is corrected based on multiple sets of temperature drop data within the second historical time period.
8. A device for determining the thermal insulation performance of a building, characterized in that, include: The acquisition module is used to acquire multiple sets of temperature drop data of the heating system of the house within a first historical time period. Each set of temperature drop data includes historical outlet water temperature, historical return water temperature, first moment, second moment, and historical outdoor temperature at the first moment. The first moment is the moment when the outlet water temperature of the heating system reaches the historical outlet water temperature and heating stops. The second moment is the moment after the first moment when the return water temperature of the heating system reaches the historical return water temperature and heating resumes. The processing module is used to determine the historical temperature drop rate corresponding to each set of temperature drop data based on the historical outlet water temperature, the historical return water temperature, the first time moment, and the second time moment in each set of temperature drop data. The processing module is further configured to fit the thermal insulation performance curve of the house based on multiple sets of historical temperature drop rates and corresponding historical outdoor temperatures, wherein the thermal insulation performance curve of the house characterizes the correspondence between outdoor temperature and temperature drop rate.
9. A device for determining the thermal insulation performance of a building, characterized in that, include: Memory; processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the method for determining the thermal insulation performance of a building as described in any one of claims 1 to 7.
10. A computer storage medium, characterized in that, The computer storage medium stores computer execution instructions, which, when executed by a processor, are used to implement the method for determining the thermal insulation performance of a building as described in any one of claims 1 to 7.