A smart heating data management platform

Abstract

The present invention belongs to the technical field of heating data management, and specifically is a smart heating data management platform, which first uses the degree of hydraulic imbalance as the basis for judging whether there is a need for renovation of each building in the target area, reduces dependence on user behavior data to avoid complex and uncertain calculations, and accurately locates each building to be renovated. Then, by configuring an adaptive temperature balancing valve for each building to be renovated, the valve opening and closing degree and fluid flow speed of the adaptive temperature balancing valve are determined to formulate a personalized renovation plan for each building to be renovated, which can not only effectively solve the hydraulic imbalance problem existing in the secondary heating network of the building, but also improve the overall heating performance and user comfort, while reducing energy waste, and then uses the renovation effectiveness coefficient of each building to be renovated in the target area to feedback the effectiveness of the formulation of the heating renovation plan, thereby helping to form a closed-loop feedback mechanism and promoting the long-term optimization of the heating system.

Description

Technical Field

[0001] The present invention belongs to the technical field of heating data management, and specifically relates to an intelligent heating data management platform. Background Art

[0002] With the global energy crisis and the increasing awareness of environmental protection, improving energy efficiency has become a focus of attention for countries around the world. Heating systems account for a considerable proportion of building energy consumption. Traditional heating systems often have problems such as low efficiency, high energy consumption, and difficulty in refined management. Therefore, it is particularly important to explore a solution that can effectively optimize the operating efficiency of the heating system, reduce energy consumption, and improve user satisfaction.

[0003] In the prior art, there are also some solutions related to heating optimization management, such as the invention patent application of a method for optimizing the supply and demand of a heating system based on user behavior analysis with patent publication number CN115841188A. The method constructs a first target model by collecting the user behavior of each heating user in the heating area, obtains the heating output and heating mechanism of the heating system to construct a second target model, and determines the supply and demand plan of each user through correlation analysis based on the two models. The supply and demand adjustment factors are determined according to the user's initial plan and supply and demand plan. The supply and demand optimization factors of the heating system are determined based on all supply and demand adjustment factors and supply and demand optimization is performed, which can effectively meet the user's thermal load requirements.

[0004] Although the above scheme proposes relevant solutions for heating optimization management, the existing technology still has the following limitations, specifically: 1. The existing technology relies on the user's heating supply and demand balance to explore the heating optimization needs and optimization space. Although it can effectively meet the user's thermal load needs, it requires a large amount of user behavior data to be collected, and user behavior has certain uncertainty and complexity. The implementation and monitoring are relatively difficult. In addition, it may not be able to directly solve the specific problems caused by the hydraulic imbalance that is prevalent and has a large impact in the heating system, such as overheating of some users, overcooling of some users, and energy waste.

[0005] 2. Existing technologies lack the ability to test-run heating optimization and transformation plans, making it impossible to verify the heating effect in advance. This may result in the discovery of deficiencies in the plan only when it is officially implemented, such as uneven heating, large fluctuations in indoor temperature, abnormal energy consumption, and other issues, which affect user comfort.

[0006] 3. The existing technology lacks effectiveness evaluation of the formulation of heating optimization transformation plans, making it impossible to further accurately understand the actual effects of the transformation plans, and unable to discover problems and make adjustments in a timely manner, which may cause problems to persist and affect users' heating experience and energy efficiency. Summary of the invention

[0007] In order to overcome the shortcomings of the background technology, an embodiment of the present invention provides a smart heating data management platform that can effectively solve the problems involved in the above-mentioned background technology.

[0008] The purpose of the present invention can be achieved through the following technical solutions: a smart heating data management platform, including: a hydraulic imbalance assessment module, a temperature balancing valve configuration module, a heating transformation plan formulation module, a plan effectiveness assessment module and a cloud database.

[0009] The hydraulic imbalance assessment module is connected to the temperature balancing valve configuration module, the temperature balancing valve configuration module is connected to the heating transformation plan formulation module, the heating transformation plan formulation module is connected to the plan effectiveness assessment module, and the cloud database is connected to the temperature balancing valve configuration module.

[0010] The hydraulic imbalance assessment module is used to collect the historical heating operation data of each building in the target area, evaluate the hydraulic imbalance degree of each building in the target area, and determine whether there is a need for renovation for each building in the target area whose hydraulic imbalance degree is greater than or equal to the preset warning threshold, and record them as the buildings to be renovated.

[0011] The temperature balancing valve configuration module is used to configure an adaptive temperature balancing valve for each building to be renovated, including determining the main valve port diameter of the temperature balancing valve and the valve port diameter of each branch pipe.

[0012] The heating renovation plan formulation module is used to refer to the preset heating renovation goals and use the platform heating simulation software to formulate heating renovation plans for each building to be renovated, including determining the valve opening and closing degree of the adaptive temperature balancing valve and the fluid flow rate.

[0013] The scheme effectiveness evaluation module is used to obtain the renovation effectiveness coefficient of each building to be renovated in the target area after the corresponding heating renovation scheme is actually implemented in each building to be renovated in the target area, so as to evaluate and provide feedback on the effectiveness of the formulation of the heating renovation scheme.

[0014] The cloud database is used to store the preset indoor heating standard temperature values ​​in the target area and the heating area of ​​each household in each building to be renovated in the target area.

[0015] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: (1) The present invention uses the degree of hydraulic imbalance as the basis for judging whether there is a need for renovation of each building in the target area, thereby reducing the reliance on user behavior data, thereby avoiding the implementation and monitoring difficulties caused by the uncertainty of user behavior, and locating the problem more accurately, so that more targeted measures can be taken to make improvements.

[0016] (2) The present invention configures an adaptive temperature balancing valve for each building to be renovated, determines the valve opening and closing degree and fluid flow speed of the adaptive temperature balancing valve, and formulates a personalized renovation plan for each building to be renovated. This can not only effectively solve the hydraulic imbalance problem existing in the heating system, but also improve the overall performance of the system and the comfort of users, while reducing energy waste. Compared with the existing technical solutions, it is more practical and efficient.

[0017] (3) The present invention obtains the renovation effectiveness coefficient of each building to be renovated in the target area after actual renovation, evaluates the effectiveness of the formulation of the heating renovation plan, and provides accurate data support for subsequent decision-making, thereby helping to form a closed-loop feedback mechanism and promote the long-term optimization of the heating system. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0019] Figure 1 It is a schematic diagram of module connection of the present invention.

[0020] Figure 2 It is a reference schematic diagram of the water supply flow change curve of a certain household in a certain building in the target area of ​​the present invention on a certain day in the current season.

[0021] Figure 3 A logical schematic diagram is developed for the heating transformation scheme of the present invention. DETAILED DESCRIPTION

[0022] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0023] Reference Figure 1 As shown, the present invention provides a smart heating data management platform, including: a hydraulic imbalance assessment module, a temperature balancing valve configuration module, a heating transformation plan formulation module, a plan effectiveness assessment module and a cloud database.

[0024] The hydraulic imbalance assessment module is connected to the temperature balancing valve configuration module, the temperature balancing valve configuration module is connected to the heating transformation plan formulation module, the heating transformation plan formulation module is connected to the plan effectiveness assessment module, and the cloud database is connected to the temperature balancing valve configuration module.

[0025] The hydraulic imbalance assessment module is used to collect historical heating operation data of each building in the target area, assess the hydraulic imbalance degree of each building in the target area, and determine whether each building in the target area whose hydraulic imbalance degree is greater than or equal to a preset warning threshold has renovation needs and record them as the buildings to be renovated.

[0026] Specifically, the historical heating operation data include the water supply flow change curve of each household on each day of the season, and the maximum temperature difference and maximum pressure difference of the supply and return water pipes per unit time of each household on each day of the season.

[0027] It should be noted that the historical heating operation data of each building in the above-mentioned target area is collected through the heating network monitoring system historically deployed in the target area.

[0028] Reference Figure 2 Specifically, the evaluation of the hydraulic imbalance degree of each building in the target area includes: extracting the water supply flow change curve of each building in the target area on each day of the season and each household and importing it into Matlab software to obtain the corresponding best fitting function, which is recorded as ,in is the number of each building in the target area, , is the number of each historical day in the season, , The serial number of each household. , obtain the first-order derivative standard deviation of the water supply flow change curve of each building in the target area for each day of the season and each household and the absolute sum of the second derivative , according to the formula Obtain the smoothness of the water supply flow change curve for each household in each building in the target area on each day of the season. is a natural constant.

[0029] It should be noted that the above The first-order derivative of the water supply flow change curve of each building in the target area on each day of the season and each household corresponds to the best fitting function, and the first-order derivative of the water supply flow change curve of each building in the target area on each day of the season and each household corresponds to the best fitting function is expressed as , using the standard deviation calculation formula The first-order derivative standard deviation of the water supply flow change curve of each building in the target area on each day of the season is obtained, where It is expressed as the target area after the first-order derivative Buildings in this season Tiandi The water supply flow change curve of each household corresponds to the best fitting function. The corresponding value of each unit time point is is the number of each unit time point in a single day, , It is the cumulative number of unit time points in a single day.

[0030] Above The water supply flow change curve of each building in the target area on each day of the season and each household is expressed by taking the second-order derivative of the best fitting function corresponding to the water supply flow change curve of each building in the target area on each day of the season and each household. ,like If it is a constant, then the absolute sum of the second-order derivatives of the water supply flow change curves of each building in the target area on each day of the season and each household is directly set to the constant value after the corresponding second-order derivative. is not a constant, then the formula The absolute sum of the second-order derivatives of the water supply flow change curves of each building in the target area on each day of the season is obtained, where It is expressed as the target area after the second-order derivative Buildings in this season Tiandi The water supply flow change curve of each household corresponds to the best fitting function. The value corresponding to each unit time point.

[0031] The water supply flow change curves of each household in each building in the target area on each day of the season are overlapped and compared at the same time to obtain the extreme value of the water supply flow deviation between households in each building in the target area at each unit time point on each day of the season. After calculating the mean value of each unit time point, the ratio analysis is further performed with the preset reference water supply flow deviation value to obtain the water supply flow deviation degree between households in each building in the target area on each day of the season. .

[0032] By formula The heating flow non-uniformity coefficient of each building in the target area is obtained, where For the target area Buildings in this season The minimum smoothness of the water supply flow change curve of each household, is the historical number of days in the season, is a preset constant.

[0033] Extract the maximum temperature difference and maximum pressure difference of the supply and return pipes of each household in the target area in each day of the season. Obtain the temperature difference fluctuation and pressure difference fluctuation of the supply and return pipes of each household in the target area in the season by standard deviation calculation. Obtain the heating temperature non-uniformity coefficient of each building in the target area by mean calculation. and heating pressure unevenness coefficient .

[0034] Will , , The products of the corresponding preset weights are accumulated respectively, and the accumulated value is used as the hydraulic imbalance degree of each building in the target area.

[0035] The embodiment of the present invention uses the degree of hydraulic imbalance as the basis for judging whether there is a need for renovation of each building in the target area, reduces the reliance on user behavior data, thereby avoiding the implementation and monitoring difficulties caused by the uncertainty of user behavior, and locates the problem more accurately, so as to take more targeted measures to make improvements.

[0036] The temperature balancing valve configuration module is used to configure an adaptive temperature balancing valve for each building to be renovated, including determining the main valve port diameter of the temperature balancing valve and the valve port diameters of each branch pipe.

[0037] Specifically, configuring an adaptive temperature balancing valve for each building to be renovated includes: extracting the maximum temperature difference of the supply and return water pipes of each household in the target area for each day of the current season, calculating the average value, and obtaining the reference supply and return water temperature difference of each household in the target area for each building to be renovated in the current season. , is the number of each building to be renovated in the target area, .

[0038] The indoor temperature collectors installed in each building and each household in the target area are used to obtain the lowest indoor temperature values ​​of each household in each building to be renovated in the target area on each day of the season. Combined with the preset indoor heating standard temperature values ​​of the target area stored in the cloud database and the heating area of ​​each household in each building to be renovated in the target area , calculate the reference heating load corresponding to the unit heating area of ​​each household in the target area for each building to be renovated in the current season .

[0039] It should be noted that the above The calculation process is as follows: subtract the preset indoor heating standard temperature value of the target area from the lowest indoor temperature value of each household in each building to be renovated in the target area on each historical day of the season, and obtain the maximum heating demand temperature value of each household in each building to be renovated in the target area on each historical day of the season; multiply it by the preset air specific heat capacity and the preset unit household air mass to obtain the heating demand of each household in each building to be renovated in the target area on each historical day of the season; obtain the reference heating demand of each household in each building to be renovated in the target area on the historical day of the season through mean calculation; then perform ratio analysis with the heating area of ​​the corresponding household in the corresponding building to be renovated in the target area to obtain the reference heating load corresponding to the unit heating area of ​​each household in the target area to be renovated in the historical day of the season.

[0040] According to the temperature balancing valve supplier's plan, its brand type corresponds to the preset fluid flow speed allowance threshold , calculate the main valve port diameter of the temperature balancing valve of each building to be renovated , ,in is the circumference of a circle, For the The total demand flow of the buildings to be renovated, , are the preset specific heat capacity and preset density of water, is the number of households in the building, For the target area The maximum reference supply and return water temperature difference for each household in the building to be renovated in the current season.

[0041] Calculate the demand flow of each household in each building to be renovated The calculation method of the main valve port diameter of the temperature balancing valve of each building to be renovated is consistent with that of the main valve port diameter of the temperature balancing valve of each building to be renovated. The valve port diameter of each household pipe of the temperature balancing valve of each building to be renovated is obtained. .

[0042] It should be noted that the above The calculation formula is: .

[0043] The heating renovation plan formulation module is used to refer to the preset heating renovation goals and use the platform heating simulation software to formulate heating renovation plans for each building to be renovated, including determining the valve opening and closing degree of the adaptive temperature balancing valve and the fluid flow rate.

[0044] Specifically, the preset heating transformation goals include: the supply and return water temperature difference of any household in the building is less than the preset value The overall heat consumption and overall power consumption of the building are reduced by the corresponding preset percentages, which can be further specified as the supply and return water temperature difference of any household in the building is less than 1 , the overall heat consumption of the building is reduced , the overall power consumption of the building is reduced .

[0045] Reference Figure 3 As shown, specifically, the formulation of the heating renovation plan for each building to be renovated includes: using the platform heating simulation software to simulate the secondary network heating operation of each building to be renovated, and monitoring the electricity consumption and heat consumption of each building to be renovated during the initial operation preset time.

[0046] It should be noted that the above-mentioned electricity consumption and heat consumption are obtained by setting up virtual electricity consumption sensors and heat consumption sensors through the platform heating simulation software, and associating them with the models of each building to be renovated.

[0047] Use the platform heating simulation software to configure the temperature balancing valve for each building to be renovated, and set the initial opening and closing degree of each household pipe valve port of the temperature balancing valve to the preset value. , set the initial fluid flow rate of each branch pipe valve port of the adaptive temperature balancing valve to be After configuration is completed, the temperature difference between supply and return water of each household in each building to be renovated in the current heating process is monitored. .

[0048] The opening and closing degree of each household pipe valve port of each temperature balancing valve of each building to be renovated is gradually increased through preset iterations by adjusting the opening and closing degree of the preset benchmark, and the supply and return water temperature difference of each household in each building to be renovated after each gradual increase is collected, thereby calculating the correlation coefficient between the opening and closing degree of the valve port of each household temperature balancing valve of each building to be renovated and the supply and return water temperature difference .

[0049] It should be noted that the correlation coefficients between the valve opening degree of each household temperature balancing valve in the above-mentioned buildings to be renovated and the supply and return water temperature difference, as well as the correlation coefficients between the fluid flow rate of the subsequent temperature balancing valves in each speed-controlled building and the electricity consumption and heat consumption were all calculated by the Spearman rank correlation coefficient method.

[0050] By formula Obtain the reasonable opening and closing degree of the temperature balancing valve of each building to be renovated under the target supply and return water temperature difference state.

[0051] Specifically, the formulation of the heating renovation plan for each building to be renovated also includes: adjusting the household pipe valve openings of the temperature balancing valve of each building to be renovated in the platform heating simulation software according to a reasonable opening and closing degree, and then monitoring the electricity consumption and heat consumption of each building to be renovated during the preset operation time.

[0052] The power consumption reduction rate and heat consumption reduction rate under the action of the temperature balancing valve of each building to be renovated are obtained. If the power consumption reduction rate or heat consumption reduction rate under the action of the temperature balancing valve of a building to be renovated is less than the corresponding preset percentage, it is judged that the temperature balancing valve of the building to be renovated has the need to regulate the fluid passage speed. Otherwise, it is judged that the temperature balancing valve of the building to be renovated does not have the need to regulate the fluid passage speed, and the initial fluid passage speed of the temperature balancing valve is maintained. In this way, the buildings to be renovated for which the temperature balancing valve has the need to regulate the fluid passage speed are screened, and recorded as speed-controlled buildings. The reasonable fluid passage speed of the temperature balancing valve of each speed-controlled building is analyzed, so as to realize the formulation of heating renovation plans for each building to be renovated.

[0053] Specifically, the analysis of the reasonable fluid flow rate of the temperature balancing valve of each speed-controlled building includes: gradually reducing the fluid flow rate of each speed-controlled building temperature balancing valve through a preset benchmark through preset iterations, collecting the heat consumption and electricity consumption of the heating process of each speed-controlled building after each gradual reduction, thereby calculating the correlation coefficients of the fluid flow rate of the temperature balancing valve of each speed-controlled building with the electricity consumption and the heat consumption, and extracting the minimum value as the reference correlation coefficient between the fluid flow rate of the temperature balancing valve of each speed-controlled building and the energy consumption.

[0054] The reasonable opening and closing degree analysis method of the temperature balancing valve of each building to be renovated under the target supply and return water temperature difference state is consistent, and the fluid flow rate of the temperature balancing valve of each speed-controlled building under the target energy consumption reduction state is obtained.

[0055] It should be noted that the above-mentioned fluid flow rate control for the temperature balancing valve is actually a control for the water pump of the secondary network of the building, and the fluid flow rate of each branch pipe in the temperature balancing valve is the same.

[0056] The embodiment of the present invention configures an adaptive temperature balancing valve for each building to be renovated, determines the valve opening and closing degree and fluid flow speed of the adaptive temperature balancing valve to formulate a personalized renovation plan for each building to be renovated, which can not only effectively solve the hydraulic imbalance problem existing in the heating system, but also improve the overall performance of the system and the comfort of users, while reducing energy waste. Compared with the existing technical solutions, it is more practical and efficient.

[0057] The scheme effectiveness evaluation module is used to obtain the renovation effectiveness coefficient of each building to be renovated in the target area after the corresponding heating renovation scheme is actually implemented in each building to be renovated in the target area, so as to evaluate and provide feedback on the effectiveness of the formulation of the heating renovation scheme.

[0058] Specifically, the step of obtaining the renovation effectiveness coefficient of each building to be renovated in the target area includes: evaluating the actual hydraulic imbalance degree of each building to be renovated in the target area after the corresponding heating renovation plan is actually implemented. , Actual power consumption reduction rate and actual heat rate reduction , extract the hydraulic imbalance degree of each building to be renovated in the target area , according to the formula , Calculate the imbalance improvement degree and energy consumption improvement degree of each building to be renovated in the target area respectively, where The overall heat consumption and overall electricity consumption of the building are reduced by the corresponding preset percentages respectively, and the imbalance improvement degree and energy consumption improvement degree are accumulated to obtain the renovation effectiveness coefficient of each building to be renovated in the target area.

[0059] Specifically, the evaluation and feedback of the effectiveness of the formulation of the heating renovation plan include: comparing the renovation effectiveness coefficient of each building to be renovated in the target area with a preset reasonable renovation effectiveness coefficient, counting the number of buildings to be renovated in the target area whose renovation effectiveness coefficient is greater than or equal to the preset reasonable renovation effectiveness coefficient, and using the ratio of the coefficient to the total number of buildings to be renovated in the target area as an evaluation indicator for the effectiveness of the formulation of the heating renovation plan.

[0060] The embodiment of the present invention obtains the renovation effectiveness coefficient of each building to be renovated in the target area after actual renovation, evaluates the effectiveness of the formulation of the heating renovation plan, and provides accurate data support for subsequent decision-making, thereby helping to form a closed-loop feedback mechanism and promote long-term optimization of the heating system.

[0061] The cloud database is used to store the preset indoor heating standard temperature value of the target area and the heating area of ​​each household in each building to be renovated in the target area.

[0062] The data sources in the cloud database of this embodiment are shown in Table 1 below.

[0063] Table 1 Detailed description of data sources in cloud database

[0064]

[0065] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the present invention, they should all fall within the protection scope of the present invention.

Claims

1. A smart heating data management platform, characterized in that: include: The hydraulic imbalance assessment module is used to collect the historical heating operation data of each building in the target area, assess the hydraulic imbalance degree of each building in the target area, and determine whether each building in the target area with a hydraulic imbalance degree greater than or equal to a preset warning threshold has a need for renovation, and record it as each building to be renovated; The temperature balancing valve configuration module is used to configure the temperature balancing valve for each building to be renovated, including determining the main valve port diameter of the temperature balancing valve and the valve port diameter of each branch pipe; The heating renovation plan formulation module is used to formulate heating renovation plans for each building to be renovated by referring to the preset heating renovation goals and using the platform heating simulation software, including determining the valve opening and closing degree of the adaptive temperature balancing valve and the fluid flow rate; The scheme effectiveness evaluation module is used to obtain the renovation effectiveness coefficient of each building to be renovated in the target area after the corresponding heating renovation scheme is actually implemented in each building to be renovated in the target area, so as to evaluate and provide feedback on the effectiveness of the formulation of the heating renovation scheme; The cloud database is used to store the preset indoor heating standard temperature values ​​of the target area and the heating area of ​​each household in each building to be renovated in the target area; The historical heating operation data includes the water supply flow rate change curve of each household on each day of the season, the maximum temperature difference and the maximum pressure difference of the water supply and return pipes per unit time of each household on each day of the season; The evaluation of the hydraulic imbalance degree of each building in the target area includes: extracting the water supply flow change curve of each building in the target area for each day of the season and each household, and importing it into Matlab software to obtain the corresponding best fitting function, which is recorded as ,in is the number of each building in the target area, , is the number of each historical day in the season, , The serial number of each household. , obtain the first-order derivative standard deviation of the water supply flow change curve of each building in the target area for each day of the season and each household and the absolute sum of the second derivative , according to the formula Obtain the smoothness of the water supply flow change curve for each household in each building in the target area on each day of the season. is a natural constant; The water supply flow change curves of each household in each building in the target area on each day of the season are overlapped and compared at the same time to obtain the extreme value of the water supply flow deviation between households in each building in the target area at each unit time point on each day of the season. After calculating the mean value of each unit time point, the ratio analysis is further performed with the preset reference water supply flow deviation value to obtain the water supply flow deviation degree between households in each building in the target area on each day of the season. ; By formula The heating flow non-uniformity coefficient of each building in the target area is obtained, where For the target area Buildings in this season The minimum smoothness of the water supply flow change curve of each household, is the historical number of days in the season, is a preset constant; Extract the maximum temperature difference and maximum pressure difference of the supply and return pipes of each household in the target area in each day of the season. Obtain the temperature difference fluctuation and pressure difference fluctuation of the supply and return pipes of each household in the target area in the season by standard deviation calculation. Obtain the heating temperature non-uniformity coefficient of each building in the target area by mean calculation. and heating pressure unevenness coefficient ; Will , , The products of the corresponding preset weights are accumulated respectively, and the accumulated value is used as the hydraulic imbalance degree of each building in the target area.

2. According to claim 1, a smart heating data management platform is characterized in that: The configuration of an adaptive temperature balancing valve for each building to be renovated includes: extracting the maximum temperature difference of the supply and return water pipes of each household in the target area for each day of the current season, calculating the average value, and obtaining the reference supply and return water temperature difference of each household in the target area for each building to be renovated in the current season. , is the number of each building to be renovated in the target area, ; The indoor temperature collectors installed in each building and each household in the target area are used to obtain the lowest indoor temperature values ​​of each household in each building to be renovated in the target area on each day of the season. Combined with the preset indoor heating standard temperature values ​​of the target area stored in the cloud database and the heating area of ​​each household in each building to be renovated in the target area , calculate the reference heating load corresponding to the unit heating area of ​​each household in the target area for each building to be renovated in the current season ; According to the temperature balancing valve supplier's plan, its brand type corresponds to the preset fluid flow speed allowance threshold , calculate the main valve port diameter of the temperature balancing valve of each building to be renovated , ,in is the circumference of a circle, For the The total demand flow of the buildings to be renovated, , are the preset specific heat capacity and preset density of water, is the number of households in the building, For the target area The maximum reference supply and return water temperature difference of each household in the current season in the building to be renovated; Calculate the demand flow of each household in each building to be renovated The calculation method of the main valve port diameter of the temperature balancing valve of each building to be renovated is consistent with that of the main valve port diameter of the temperature balancing valve of each building to be renovated. The valve port diameter of each household pipe of the temperature balancing valve of each building to be renovated is obtained. .

3. According to claim 2, a smart heating data management platform is characterized in that: The preset heating transformation goals include: the temperature difference between the supply and return water of any household in the building is less than the preset value The overall heat consumption and overall electricity consumption of the building are reduced by corresponding preset percentages respectively.

4. According to claim 3, a smart heating data management platform is characterized in that: The formulating of the heating renovation plan for each building to be renovated includes: using the platform heating simulation software to simulate the secondary network heating operation of each building to be renovated, and monitoring the power consumption and heat consumption of each building to be renovated during the initial operation preset time; Use the platform heating simulation software to configure the temperature balancing valve for each building to be renovated, and set the initial opening and closing degree of each household pipe valve port of the temperature balancing valve to the preset value. , the initial fluid flow rate of each branch pipe valve port of the adaptive temperature balancing valve is set to After configuration is completed, the temperature difference between supply and return water of each household in each building to be renovated in the current heating process is monitored. ; The opening and closing degree of each household pipe valve port of each temperature balancing valve of each building to be renovated is gradually increased through preset iterations by adjusting the opening and closing degree of the preset benchmark, and the supply and return water temperature difference of each household in each building to be renovated after each gradual increase is collected, thereby calculating the correlation coefficient between the opening and closing degree of the valve port of each household temperature balancing valve of each building to be renovated and the supply and return water temperature difference ; By formula Obtain the reasonable opening and closing degree of the temperature balancing valve of each building to be renovated under the target supply and return water temperature difference state.

5. According to claim 4, a smart heating data management platform is characterized in that: The formulating of the heating renovation plan for each building to be renovated also includes: adjusting the valve openings of each household pipe of the temperature balancing valve of each building to be renovated in the platform heating simulation software according to a reasonable opening and closing degree, and then monitoring the power consumption and heat consumption of each building to be renovated during the operation of a preset time; The power consumption reduction rate and heat consumption reduction rate under the action of the temperature balancing valve of each building to be renovated are obtained. If the power consumption reduction rate or heat consumption reduction rate under the action of the temperature balancing valve of a building to be renovated is less than the corresponding preset percentage, it is judged that the temperature balancing valve of the building to be renovated has the need to regulate the fluid passage speed. Otherwise, it is judged that the temperature balancing valve of the building to be renovated does not have the need to regulate the fluid passage speed, and the initial fluid passage speed of the temperature balancing valve is maintained. In this way, the buildings to be renovated for which the temperature balancing valve has the need to regulate the fluid passage speed are screened, and recorded as speed-controlled buildings. The reasonable fluid passage speed of the temperature balancing valve of each speed-controlled building is analyzed, so as to realize the formulation of heating renovation plans for each building to be renovated.

6. According to claim 5, a smart heating data management platform is characterized in that: The analysis of the reasonable fluid flow rate of the temperature balancing valve of each speed-controlled building includes: gradually reducing the fluid flow rate of each speed-controlled building temperature balancing valve through preset iterations by adjusting the flow rate according to a preset benchmark, collecting the heat consumption and power consumption of the heating process of each speed-controlled building after each gradual reduction, thereby calculating the correlation coefficients of the fluid flow rate of each speed-controlled building temperature balancing valve with the power consumption and the heat consumption, and extracting the minimum value as the reference correlation coefficient of the fluid flow rate of each speed-controlled building temperature balancing valve and the energy consumption; The reasonable opening and closing degree analysis method of the temperature balancing valve of each building to be renovated under the target supply and return water temperature difference state is consistent, and the fluid flow rate of the temperature balancing valve of each speed-controlled building under the target energy consumption reduction state is obtained.

7. The intelligent heating data management platform according to claim 5 is characterized by: The step of obtaining the transformation effectiveness coefficient of each building to be transformed in the target area includes: evaluating the actual hydraulic imbalance degree of each building to be transformed in the target area after the corresponding heating transformation plan is actually implemented. , Actual power consumption reduction rate and actual heat rate reduction , extract the hydraulic imbalance degree of each building to be renovated in the target area , according to the formula , Calculate the imbalance improvement degree and energy consumption improvement degree of each building to be renovated in the target area respectively, where The overall heat consumption and overall electricity consumption of the building are reduced by the corresponding preset percentages respectively, and the imbalance improvement degree and energy consumption improvement degree are accumulated to obtain the renovation effectiveness coefficient of each building to be renovated in the target area.

8. The intelligent heating data management platform according to claim 1 is characterized by: The evaluation and feedback of the effectiveness of the formulation of the heating renovation plan include: comparing the renovation effectiveness coefficient of each building to be renovated in the target area with a preset reasonable renovation effectiveness coefficient, counting the number of buildings to be renovated in the target area whose renovation effectiveness coefficient is greater than or equal to the preset reasonable renovation effectiveness coefficient, and using the ratio of the coefficient to the total number of buildings to be renovated in the target area as an evaluation indicator for the effectiveness of the formulation of the heating renovation plan.

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