Carbon emission monitoring method and system for integrated energy house

Abstract

The invention relates to the technical field of carbon emission monitoring, in particular to a carbon emission monitoring method and system for an integrated energy house. The method comprises the following steps: periodically monitoring a real-time supply and return water temperature difference in a normal heating state of a heating system in the integrated energy house so as to evaluate the loop flow unbalance degree of each heating loop; respectively calculating overheat loss caused by user behaviors and heat source degradation energy consumption caused by system compensation operation according to the loop flow unbalance degree so as to obtain carbon emission incremental data of the heating system through conversion; and carrying out flow regulation processing on the overflowing loop and the underflow loop to generate water dividing and collecting device valve regulation instruction data. By monitoring the flow of the distributed heating pipe network in the integrated energy house, extra carbon emission caused by uneven flow distribution is accurately quantified.

Description

Technical Field

[0001] This invention relates to the field of carbon emission monitoring technology, and in particular to a method and system for monitoring carbon emissions from an integrated energy house. Background Technology

[0002] As a major component of energy consumption in integrated energy homes, the heating system's operational efficiency directly determines the low-carbon performance of these homes. In these homes, the centralized heating system, using a gas-fired boiler or air-source heat pump as the heat source, is the primary energy consumer in winter. This system uses circulating water as the heat transfer medium, distributing it through a manifold to the terminal radiators (such as underfloor heating coils or radiators) in each room to maintain a comfortable indoor temperature. Theoretically, an efficient heating system should be able to accurately deliver the required heat according to the actual heat load of each room, thereby minimizing energy waste. However, most residential distributed heating networks suffer from severe hydraulic imbalance, namely "overflow at the near end and underflow at the far end." In the near-end overflow loop, excessive hot water flow causes the room temperature to remain higher than the user's set value, resulting in an "overheating" state. In the far-end underflow loop, due to insufficient flow, the room temperature fails to reach the set standard for a long time. To solve the "not hot enough" problem, users usually compensate by increasing the total supply water temperature of the heat source or extending the operating time of the entire heating system. Therefore, it is impossible to accurately monitor the hidden carbon emission increase caused by the extra power consumption waste. Summary of the Invention

[0003] Based on this, the present invention provides a carbon emission monitoring method and system for integrated energy houses to solve at least one of the above-mentioned technical problems.

[0004] To achieve the above objectives, a method for monitoring carbon emissions from an integrated energy house includes the following steps: Step S1: Apply heat input tests to each heating loop of the heating system in the integrated energy house in turn, and collect loop reference thermal characteristic data of each heating loop to construct a loop thermal response dataset. Step S2: Under normal heating conditions in the integrated energy house heating system, periodically monitor the real-time supply and return water temperature difference, and conduct comparative analysis based on the loop reference thermal characteristic data to assess the loop flow imbalance of each heating loop; mark the loop flow direction status according to the positive and negative values ​​of the loop flow imbalance; wherein, the loop flow direction status includes overflow loops and underflow loops, with positive values ​​marked as overflow loops and negative values ​​marked as underflow loops; Step S3: Calculate the overheating loss caused by user behavior and the heat source deterioration energy consumption caused by system compensation operation according to the loop flow state, so as to calculate the carbon emission increment data of the heating system. Step S4: Perform flow regulation processing on the overcurrent loop and undercurrent loop to generate manifold valve regulation command data.

[0005] Preferably, the present invention also provides a carbon emission monitoring system for an integrated energy house, which performs the carbon emission monitoring method for an integrated energy house as described above. The carbon emission monitoring system for the integrated energy house includes: The heating loop feature module is used to sequentially apply heat input tests to each heating loop of the heating system in the integrated energy house, and collect loop reference thermal feature data of each heating loop to construct a loop thermal response dataset. The flow imbalance analysis module is used to periodically monitor the real-time supply and return water temperature difference under normal heating conditions in the heating system of the integrated energy house, and to perform comparative analysis based on the loop reference thermal characteristic data to assess the loop flow imbalance of each heating loop; the loop flow direction status is marked according to the positive and negative values ​​of the loop flow imbalance; the loop flow direction status includes overflow loops and underflow loops, with positive values ​​marked as overflow loops and negative values ​​marked as underflow loops; The carbon emission increment calculation module is used to calculate the overheating loss caused by user behavior and the heat source deterioration energy consumption caused by system compensation operation according to the loop flow status, so as to calculate the carbon emission increment data of the heating system. The system optimization and control module is used to regulate the flow of the overflow loop and underflow loop, and generate valve adjustment command data for the manifold.

[0006] The beneficial effects of this invention are as follows: On the one hand, this invention achieves precise quantification of the additional carbon emissions caused by uneven flow distribution in distributed heating networks. Through a pioneering single-loop thermal characteristic identification method, a unique baseline thermodynamic model is established for each heating loop. Based on this, by dynamically differentiating real-time operating data with this baseline model, it can accurately identify and quantify two types of "hidden" energy consumption directly caused by the hydraulic imbalance state of "overflow at the near end and underflow at the far end": one is the direct heat loss caused by users opening windows to dissipate heat due to overheating in near-end rooms; the other is the systemic efficiency degradation energy consumption caused by the heat source increasing its operating load due to insufficient heat in far-end rooms. This invention accurately extracts these two additional energy consumptions, which traditional monitoring methods cannot capture, from the total energy consumption and converts them into specific incremental carbon emission data. This allows managers to clearly see the real carbon emission costs caused by the hydraulic imbalance problem in the network, solving the technical problem that traditional monitoring methods can only "package" estimates and cannot trace the source.

[0007] On the other hand, this invention provides an intelligent valve adjustment mechanism for manifolds based on quantitative diagnostic results, realizing closed-loop control from passive monitoring to active optimization. Unlike extensive adjustments relying on human experience, this method automatically generates optimal valve opening adjustment commands based on real-time calculated flow imbalances in each loop. These commands precisely reduce redundant flow in overflow loops and compensate underflow loops as needed, thereby actively and dynamically approaching the hydraulic balance of the pipe network. This data-driven intelligent adjustment method not only fundamentally eliminates energy waste caused by uneven flow and directly reduces the aforementioned quantified carbon emission increments, but also ensures that all rooms achieve the user's comfort settings with minimal energy consumption. By closely integrating diagnosis and control, this invention transforms the heating system from a passively operating energy-consuming unit into an intelligent, low-carbon system capable of self-optimization and continuous high-efficiency operation, significantly improving the overall energy-saving level and intelligence of integrated energy homes. Attached Figure Description

[0008] Figure 1 This is a schematic diagram of the steps of the carbon emission monitoring method for the integrated energy house of the present invention; Figure 2 This is a schematic diagram of the building heating pipe network topology in this invention; Figure 3 This is a schematic diagram of the carbon emission monitoring process in this invention; The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0009] The technical method of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0010] Furthermore, the accompanying drawings are merely illustrative of the invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor methods and / or microcontroller methods.

[0011] It should be understood that although the terms "first," "second," etc., may be used herein to describe various units, these units should not be limited by these terms. These terms are used merely to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, a first unit may be referred to as a second unit, and similarly, a second unit may be referred to as a first unit. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0012] To achieve the above objectives, please refer to Figures 1 to 3 This invention provides a method for monitoring carbon emissions from integrated energy homes, comprising the following steps: Step S1: Apply heat input tests to each heating loop of the heating system in the integrated energy house in turn, and collect loop reference thermal characteristic data of each heating loop to construct a loop thermal response dataset. In this embodiment of the invention, this step involves executing an automated test program through a central controller. The controller first connects to the manifold control terminal and iterates through all registered heating loops (e.g., living room loop, master bedroom loop, secondary bedroom loop, etc.). For each loop under test, the controller issues a command to fully close the electric valves of all other loops, thereby physically isolating an independent test path. Subsequently, the controller sends a high-intensity heating command to the heat source (e.g., a gas boiler), causing it to continuously heat the loop under test at a fixed temperature (e.g., 60°C) higher than the normal supply water temperature (e.g., normally 50°C) for a preset time (e.g., 8 minutes), completing the active heat input. During this period and the subsequent natural decay period (e.g., 30 minutes), the temperature sensor arrays deployed at the water supply inlet, water return inlet, and the corresponding room center point synchronously collect three temperature data at a frequency of once every 15 seconds. These data are then timestamped to form three sets of temperature time-series data, including the water supply inlet temperature sequence, the water return inlet temperature sequence, and the room center point temperature sequence, and stored in the local database.

[0013] Step S2: Under normal heating conditions in the integrated energy house heating system, periodically monitor the real-time supply and return water temperature difference, and conduct comparative analysis based on the loop reference thermal characteristic data to assess the loop flow imbalance of each heating loop; mark the loop flow direction status according to the positive and negative values ​​of the loop flow imbalance; wherein, the loop flow direction status includes overflow loops and underflow loops, with positive values ​​marked as overflow loops and negative values ​​marked as underflow loops; In this embodiment of the invention, after the heating system enters the normal operating mode, the monitoring system collects real-time data from the supply and return water temperature sensors of each loop at a relatively short interval (e.g., every 5 minutes). For each loop, the system first calculates its real-time supply and return water temperature difference. Simultaneously, it retrieves the loop reference thermal characteristic data for that loop from the loop thermal response dataset constructed in step S1, particularly the reference supply and return water temperature difference and the fixed heat source temperature during single-loop testing. Based on the difference between the current real-time supply water temperature and the fixed temperature during testing, the system calculates a temperature correction factor to calibrate the reference supply and return water temperature difference, thus obtaining the corrected supply and return water temperature difference. Finally, the loop flow imbalance is calculated using a specific formula: (corrected supply and return water temperature difference - real-time supply and return water temperature difference) / corrected supply and return water temperature difference. The sign of this value directly reflects the state of flow deviation from the reference: a positive value indicates that the real-time temperature difference is less than the reference temperature difference, i.e., the flow is too large, and it is marked as an overflow loop; a negative value indicates that the real-time temperature difference is greater than the reference temperature difference, i.e., the flow is insufficient, and it is marked as an underflow loop.

[0014] Step S3: Calculate the overheating loss caused by user behavior and the heat source deterioration energy consumption caused by system compensation operation according to the loop flow state, so as to calculate the carbon emission increment data of the heating system. In this embodiment of the invention, different energy consumption calculation logics are activated for two states: overcurrent loop and undercurrent loop. For the overcurrent loop, the real-time temperature of its corresponding room is continuously monitored. When the room temperature remains above a user-set temperature threshold (e.g., 2°C) for an extended period (e.g., more than 30 minutes), it is determined to be "overheating." In this state, if an abnormally large increase in the room temperature change rate is detected (exceeding the natural heat dissipation rate calculated based on the room temperature response gain characteristics), it is determined that the user is opening windows to dissipate heat, and overheating losses begin to accumulate. For the undercurrent loop, when the temperature of its corresponding room remains below the set value, the additional increase in water supply temperature or extended operating time by the heat source to compensate for this deficiency is recorded, and the system's heat source degradation energy consumption is calculated based on this. Finally, the overheating losses and heat source degradation energy consumption of all loops are added together to obtain the total incremental energy consumption, which is then multiplied by the unit heat carbon emission factor corresponding to the integrated energy house heat source type (e.g., 0.202 kgCO2 / kWh for natural gas) to obtain real-time incremental carbon emission data.

[0015] Step S4: Perform flow regulation processing on the overcurrent loop and undercurrent loop to generate manifold valve regulation command data.

[0016] In this embodiment of the invention, when the calculated carbon emission increment exceeds a preset alarm threshold, or when a fixed control cycle (e.g., every 2 hours) is reached, a flow regulation process is automatically triggered. The pipe network topology data of the heating system is read to identify which overflow and underflow loops are connected to the same manifold node. For each such node, the loop flow imbalance of all overflow loops under that node is summarized, and a total flow regulation amount for a region is calculated, i.e., the total excess flow that needs to be reduced in that region. Then, based on the imbalance of each underflow loop under that node, the total flow regulation amount for the region is allocated proportionally to them, and a specific target flow compensation amount is calculated for each underflow loop. Finally, these flow reduction and compensation amounts are converted into specific valve opening percentage increments or reduction amounts according to the valve flow characteristic curves, and combined with the current opening of each valve, a set of manifold valve regulation command data containing loop IDs and target openings is generated and sent to the manifold controller for execution.

[0017] Preferably, in step S1, heat input tests are applied to each heating loop of the heating system in the integrated energy house sequentially, and loop reference thermal characteristic data of each heating loop are collected to construct a loop thermal response dataset, including: By closing all loop valves except the loop under test through the manifold control terminal, the single-loop test procedure can be initiated. The heat source is controlled to supply heat to the loop under test at a fixed temperature 5-15 degrees Celsius higher than the preset normal water supply temperature for 5-10 minutes to apply heat input. During the heat input and subsequent 30-minute natural decay period, the water supply temperature, return temperature, and center point temperature of the corresponding room in the test loop are synchronously collected at a frequency of no less than 15 seconds to form three sets of temperature time series data.

[0018] In one implementation of this invention, the test process is automatically initiated by the central controller. The controller first sends a control command to the electric actuator array of the manifold via the communication bus. The data frame of this command explicitly specifies that the valve actuators corresponding to the "living room loop," "secondary bedroom loop," and "study loop" should be driven to the fully closed position (valve position value 0%), while ensuring that the valve actuator of the "master bedroom loop" is in the fully open position (valve position value 100%). This physically confines the hydraulic flow path of the heating system temporarily between the heat source and the "master bedroom loop," thus constituting the valve controller sending the test command. Specifically, assuming an integrated energy house has five heating loops distributed inside: the living room loop, master bedroom loop, secondary bedroom loop, study loop, and dining room loop, when the controller selects to test the "living room loop," it generates a command frame containing the target loop identifier and the target valve status. After receiving this command, the valve controller drives a closed single-loop test environment for the remaining loops, excluding the "living room loop."

[0019] In one implementation of this invention, the conventional water supply temperature is preset to 50 degrees Celsius. This value is a baseline parameter pre-written into the controller's memory during the initial system commissioning phase, based on the climate conditions of the integrated energy house's location and the thermal insulation performance of the building envelope. It should be noted that, in order to obtain a significant temperature response in a short time for feature extraction, the controller selects 60 degrees Celsius, which is 10 degrees Celsius higher than the conventional water supply temperature, as the fixed heating temperature for this test, and sets the continuous heating duration to 8 minutes. Specifically, the controller activates the electric actuators of the four standard communication loops (master bedroom, secondary bedroom, study, and dining room) to adjust their valves from their current opening to a fully closed state, while ensuring that the valve in the "living room loop" is fully open.

[0020] It should be noted that, in order to ensure the uniqueness and purity of the test flow path, the controller will wait for a preset confirmation time, such as 5 seconds, after issuing the shutdown command, and read the status feedback signals of the valve actuators in each loop. Only after confirming that the valves in the non-test loops have been closed in place will the test process proceed to the next step.

[0021] In one implementation of this invention, once the single-loop test process is confirmed to be established, the central controller sends a command containing the target outlet water temperature (60 degrees Celsius) and operating mode (forced fixed-temperature output) to the heat source device (e.g., a gas wall-mounted boiler). After receiving the command, the boiler adjusts its combustion power to precisely maintain the outlet water temperature at 60 degrees Celsius and continues to run for 8 minutes, thereby applying a stable and quantifiable heat input to the "main bedroom loop".

[0022] Specifically, the controller first reads the standard water supply temperature set for the heating system during normal winter operation from the system configuration parameter table. This data is preset during the initial system commissioning based on the building envelope insulation performance and local climate conditions, for example, 50 degrees Celsius. Subsequently, during this and the following 30-minute natural decay period, the controller synchronously collects data from the loop under test at a frequency of no less than 15 seconds, adding a fixed temperature rise value. This temperature rise value aims to create a sufficiently strong heat pulse to generate three sets of temperature time-series data: the supply water temperature, the return water temperature, and the corresponding room center point temperature.

[0023] Preferably, step S1, which involves sequentially applying heat input tests to each heating loop of the integrated energy house's heating system and collecting loop reference thermal characteristic data for each heating loop to construct a loop thermal response dataset, further includes: The time difference between the return water inlet temperature reaching its peak value and the supply water inlet temperature reaching its peak value is calculated as the temperature peak conduction delay. The rate of temperature drop at the return water inlet after the heat input stops is calculated as the reference temperature drop rate. The baseline supply and return water temperature difference is analyzed based on the supply and return water temperatures. The room temperature rise data was calculated based on the initial and final center point temperatures of the room from three sets of temperature time series data. The ratio of total heat input to room temperature rise data is calculated as a characteristic of room temperature response gain. The temperature peak conduction delay, reference temperature drop rate, reference supply and return water temperature difference, and room temperature response gain characteristics are encapsulated as loop reference thermal characteristic data for the loop under test.

[0024] In one implementation of this invention, the supply water temperature sequence and the return water temperature sequence are retrieved from the three sets of temperature time-series data generated in the previous step. Specifically, the supply water temperature sequence is traversed to locate the data point with the highest temperature value, and its corresponding timestamp is recorded as the peak supply water time. Similarly, the return water temperature sequence is traversed to locate its peak temperature point and the return water peak time is recorded. The temperature peak conduction delay is the difference between these two timestamps.

[0025] In one implementation of this invention, assuming that in the test of the "living room loop," the supply water temperature sequence reaches a peak of 60.1 degrees Celsius at 480 seconds (8 minutes), while the return water temperature sequence reaches a peak of 57.5 degrees Celsius at 660 seconds (11 minutes), then the calculated temperature peak conduction delay is: Temperature peak conduction delay = Return water peak time - Supply water peak time = 660 seconds - 480 seconds = 180 seconds. This 180-second data represents the time required for the heat wavefront to travel through the entire living room underfloor heating coil, reflecting a comprehensive physical characteristic of the loop length and water flow velocity.

[0026] In one implementation of this invention, the analysis window focuses on the time-series data of the return water inlet temperature during the natural decay period after the heat input stops (i.e., at the 8th minute). It is important to note that, to avoid the influence of initial temperature fluctuations, the calculation starts from a stable point after the return water inlet temperature reaches its peak. Specifically, the moment when the return water inlet temperature drops by 1 degree Celsius from its peak is selected as the starting point for the calculation, and a data segment of a fixed duration (e.g., 10 minutes, or 600 seconds) is extracted from this segment. Then, a linear regression fitting is performed on this data segment using the least squares method to obtain a straight line representing the temperature decrease trend. The absolute value of the slope of this line is defined as the baseline temperature drop rate.

[0027] In one implementation of this invention, assuming the peak temperature of the return water inlet of the "living room loop" is 57.5 degrees Celsius, data is captured from the moment the temperature drops to 56.5 degrees Celsius (assumed to be the 720th second) up to the 1320th second. Through linear regression analysis, the fitted linear equation for this data segment is obtained as follows: ; in, for Temperature at any moment Time (seconds) Since is a constant, the slope of the straight line is -0.015 degrees Celsius per second, and its absolute value is the reference temperature drop rate of 0.015 degrees Celsius per second (or 0.9 degrees Celsius per minute).

[0028] In one implementation of this invention, to obtain a temperature difference value that represents the characteristics of the loop under stable heat transfer conditions, the supply and return water temperature data of the latter half of the heat input phase (e.g., from the 4th to the 8th minute) are selected for calculation. Specifically, the arithmetic mean of all supply water temperature data points within this time period is calculated to obtain the average supply water temperature; similarly, the arithmetic mean of all return water temperature data points is calculated to obtain the average return water temperature. The difference between the two is the baseline supply and return water temperature difference.

[0029] In one implementation of this invention, two key state point temperatures are extracted from the time-series data of the room center point temperature. The initial room center point temperature is the temperature reading before the test begins (timestamp 0 seconds), representing the room's background temperature. The final room center point temperature is the stable value when the temperature curve tends to flatten after the entire test cycle (38 minutes), typically taken as the average of the temperature readings from the last 5 minutes to increase stability. The room temperature rise data is the difference between these two temperatures.

[0030] In one implementation of this invention, the total heat input is calculated based on the performance parameters and operating data of the heat source. It should be noted that this calculation requires the specific heat capacity of water, the average flow rate during the test, and the supply and return water temperature difference. The specific mathematical expression is: Total Heat Input ;in, It is the specific heat capacity of water (approximately 4200 joules / kg·degree Celsius). The average mass flow rate (kg / s) measured by the flow meter during the single-loop test. This refers to the average supply and return water temperature difference (degrees Celsius) during this period. The duration (in seconds) of heat input is given. After calculating the total heat, divide it by the room temperature rise data obtained in the previous step to obtain the room temperature response gain characteristics.

[0031] In one implementation of this invention, after completing all the above calculations, the five key feature values ​​obtained are associated with the identifier of the loop under test and combined into a structured data record. Specifically, for the test of the "living room loop", the final generated loop reference thermal characteristic data record is as follows: {Loop ID: "living room loop", peak temperature conduction delay: 180 seconds, reference temperature drop rate: 0.9 degrees Celsius / minute, reference supply and return water temperature difference: 7.5 degrees Celsius, room temperature rise data: 2.47 degrees Celsius, room temperature response gain characteristic: 0.204 kWh / degree Celsius}.

[0032] Preferably, in step S2, the real-time supply and return water temperature difference is periodically monitored under normal heating conditions in the integrated energy house heating system, and a comparative analysis is performed based on loop reference thermal characteristic data to assess the loop flow imbalance of each heating loop, including: Periodically monitor the real-time supply and return water temperatures of each heating loop; The real-time supply and return water temperature difference of each heating loop is calculated based on the real-time supply water temperature and return water temperature, and the reference supply and return water temperature difference and reference temperature drop rate of the heating loop are read from the loop thermal response dataset. The terminal heat dissipation characteristic coefficient is set based on the reference temperature drop rate, and the temperature correction factor is calculated based on the difference between the real-time water supply temperature and the fixed temperature during the single-loop test of the heating loop. The corrected supply and return water temperature difference is obtained by multiplying the baseline supply and return water temperature difference by a temperature correction factor. Divide the reference supply and return water temperature difference by the real-time supply and return water temperature difference to obtain the loop flow imbalance.

[0033] In one implementation of this invention, temperature sensors deployed on the branch pipes of each heating loop manifold are polled at a fixed time period (e.g., 3 minutes). Specifically, when polling reaches the "master bedroom loop," the controller reads the current temperature values ​​from its supply pipe sensor and return pipe sensor, and records these two values ​​along with the loop identifier and the current system timestamp as a real-time operating data entry. For example, in a certain monitoring period, the real-time supply water temperature of the "master bedroom loop" is collected as 50.2 degrees Celsius, and the real-time return water temperature is 45.8 degrees Celsius.

[0034] In one implementation of this invention, after receiving the real-time data collected in the previous sub-step, the data processing unit immediately performs calculations. Specifically, the real-time supply water temperature is subtracted from the real-time return water temperature to obtain the current real-time supply and return water temperature difference for the loop. Simultaneously, the processing unit uses the loop identifier "main bedroom loop" as an index to query the loop thermal response dataset established in step S1 and extracts the pre-stored reference supply and return water temperature difference and reference temperature drop rate for the loop.

[0035] In one implementation of this invention, based on the principles of heat transfer, it is assumed that the heat dissipation at the terminal is proportional to the difference between the water temperature and the room temperature. Therefore, a temperature correction factor is needed to calibrate the heat dissipation performance under different operating conditions. It should be noted that the calculation formula for this correction factor is as follows: Temperature Correction Factor = (Real-time Average Water Temperature - Real-time Room Temperature) / (Average Water Temperature at Test Time - Initial Room Temperature at Test Time); where "Real-time Average Water Temperature" is the average of the current real-time supply and return water temperatures; "Real-time Room Temperature" is provided by the temperature sensor of the corresponding room; and both "Average Water Temperature at Test Time" and "Initial Room Temperature at Test Time" are historical baseline values ​​read from the loop thermal response dataset.

[0036] In one implementation of this invention, the reference supply and return water temperature difference is corrected to the current actual operating temperature difference to make it comparable. Specifically, the controller multiplies the reference supply and return water temperature difference read from the database with the temperature correction factor calculated in the previous step. Based on the data from the "master bedroom loop," the calculation is as follows: Corrected supply and return water temperature difference = Reference supply and return water temperature difference × Temperature correction factor = 7.5 degrees Celsius × 0.737 ≈ 5.53 degrees Celsius. This 5.53 degrees Celsius is theoretically the supply and return water temperature difference that the "master bedroom loop" should exhibit under the current conditions of a 50.2-degree Celsius water supply and a 20-degree Celsius room temperature, if it maintains the same "reference flow rate" as during the test.

[0037] In one implementation of this invention, a normalized difference calculation formula is used to assess the degree of flow deviation. It should be noted that this calculation method is used because the result can intuitively represent whether the flow is "excessive" or "insufficient" through a positive or negative sign, which perfectly matches the final marking target of step S2. Its mathematical expression is: Loop flow imbalance = (Corrected supply and return water temperature difference - Real-time supply and return water temperature difference) / Corrected supply and return water temperature difference.

[0038] Preferably, in step S3, the overheating loss caused by user behavior and the energy consumption due to heat source degradation caused by system compensation operation are calculated separately according to the loop flow state, so as to calculate the carbon emission increment data of the heating system, including: The room heat dissipation judgment threshold is dynamically determined based on the room temperature response gain characteristics in the loop reference thermal characteristic data. Monitor the real-time temperature of the room corresponding to the overcurrent loop, calculate the deviation between the real-time temperature and the user-set temperature, and mark the room as potentially overheated and the heating loop as an overheating loop when the deviation exceeds the preset overheating temperature threshold and the duration exceeds the preset overheating duration. Calculate the room temperature change rate under potential overheating conditions, and mark the room as having heat dissipation status when the temperature change rate is less than the room heat dissipation judgment threshold. For each room's heat dissipation status, the overheat loss of a single loop is analyzed, and the overheat loss is accumulated to obtain the total overheat loss.

[0039] In one implementation of this invention, a dynamic heat dissipation threshold is established for each room to distinguish between normal temperature fluctuations and rapid heat loss caused by users opening windows. Specifically, the room temperature response gain feature of the corresponding room is read from the loop thermal response dataset. It should be noted that the physical meaning of this feature is "the increase in room temperature caused by a unit of input heat energy," and its reciprocal approximately represents the "thermal resistance" of the room in a closed state, i.e., the slowness of natural heat dissipation. The reciprocal of this feature is multiplied by a preset empirical coefficient (e.g., 0.15, which represents the drastic change in heat exchange efficiency when windows are opened for ventilation) to calculate the room window opening threshold.

[0040] In another implementation of this invention, taking the "master bedroom loop" as an example, the room temperature response gain characteristic is found to be 0.2 kWh / °C in the database. The calculation process for the room heat dissipation judgment threshold is as follows: Room natural heat dissipation rate ≈ 1 / Room temperature response gain characteristic = 1 / 0.2 = 5°C / kWh. Room heat dissipation judgment threshold = Room natural heat dissipation rate × Empirical coefficient = 5 × (-0.15) = -0.75°C / kWh (the negative sign here indicates a temperature drop). This -0.75°C / kWh threshold means that when the rate of decrease in room temperature is detected, after conversion to equivalent heat loss, if it exceeds a certain level of the natural heat dissipation rate, it can be judged as heat dissipation.

[0041] In one implementation of this invention, all room temperature sensors marked as "overcurrent loops" are continuously polled. Specifically, two preset parameters for determining overheating are built-in: an overheating temperature threshold, such as 2.0 degrees Celsius; and an overheating duration, such as 30 minutes. In each monitoring cycle, the deviation between the real-time temperature and the user-set temperature for that room is calculated. If this deviation is greater than 2.0 degrees Celsius for multiple consecutive cycles (cumulative duration exceeding 30 minutes), the room is marked as "potentially overheated," and the heating loop is marked as an "overheating loop."

[0042] In one implementation of this invention, once a room enters a "potentially overheated state," a higher-frequency temperature change rate monitoring logic is initiated. Specifically, the temperature difference between the two most recent monitoring periods (e.g., the most recent 5 minutes) is calculated and then divided by the time interval to obtain the real-time room temperature change rate. Subsequently, this real-time change rate is compared with the "room window opening judgment threshold" calculated in the first step. It should be noted that opening a window causes a rapid drop in temperature, so the temperature change rate will be a large negative number. If the calculated real-time temperature change rate is less than (i.e., more negative) the room window opening judgment threshold, it is determined that the user has performed window ventilation, and the room state is marked as "window-opening heat dissipation state."

[0043] In another implementation of this invention, after the "master bedroom" enters a potentially overheated state, its temperature is monitored to rapidly drop from 22.5 degrees Celsius to 21.5 degrees Celsius within 5 minutes from 2:35 PM to 2:40 PM. The real-time room temperature change rate = (21.5 - 22.5) degrees Celsius / (5 × 60) seconds = -1 / 300 ≈ -0.0033 degrees Celsius / second. To compare with the threshold, the units need to be standardized. Assuming the net heat power supplied to the loop during this period is approximately 0.4 kilowatts, the converted temperature change rate is -0.0033 / 0.4 ≈ -0.00825 degrees Celsius / kilowatt-second, or approximately -2.97 degrees Celsius / kilowatt-hour. Because -2.97 is much smaller than the previously calculated room window opening threshold of -0.75, a window opening event is determined to have occurred, and the "master bedroom" is marked as being in a "window-opening heat dissipation state."

[0044] In one implementation of this invention, once a room is marked as being in "window-open heat dissipation state," the resulting overheat loss is measured. Specifically, it is assumed that all heat transferred by the loop is wasted in this state. The overheat loss is calculated as follows: Overheat loss of a single loop = Real-time flow rate of the loop × Specific heat capacity of water × Real-time supply and return water temperature difference × Duration of window-open heat dissipation state; where "real-time flow rate" is the flow rate exceeding the design value, calculated based on the loop flow imbalance and the loop reference flow rate. The overheat loss for each monitoring cycle is calculated once and accumulated into a global variable named "Total Overheat Loss Heat".

[0045] Preferably, the overheating loss of a single loop is analyzed for the room's heat dissipation status, and the overheating loss is accumulated to obtain the total overheating loss, which includes: The actual water flow transit time of each heating loop under normal operation is estimated based on the temperature peak conduction delay in the loop reference thermal characteristic data. The loop reference flow rate of the pipeline network is assessed based on the actual water flow transit time of each heating loop. Determine the overcurrent flow rate based on the loop reference flow rate. For rooms with high heat dissipation, the loop flow imbalance of the heating loop is read, and the redundant heat per unit time is calculated based on the overflow rate and the real-time supply and return water temperature difference. Obtain the duration of heat dissipation status in the rooms corresponding to each heating loop, and calculate the overheat loss of a single loop based on the redundant heat per unit time.

[0046] In one implementation of this invention, when calculating overheat loss, the system first needs to determine the flow rate baseline of the loop under design or ideal operating conditions. Specifically, using the loop identifier marked as "window-open heat dissipation state" (e.g., "living room loop") as an index, the system directly queries the constructed loop thermal response dataset. It should be noted that this key parameter, the loop baseline flow rate, is directly measured and recorded by a flow meter installed on the main pipeline during the single-loop feature identification test phase, representing an inherent hydraulic characteristic of the loop under a specific test pressure. Therefore, this step is a direct data reading process, not an estimation.

[0047] In one implementation of this invention, the current flow rate exceeding design requirements is accurately calculated using a known baseline flow rate and a measured flow rate deviation. Specifically, the loop baseline flow rate read in the previous step is multiplied by the loop flow imbalance degree calculated in step S2, which characterizes the current operating state of the loop. The mathematical expression is: Real-time overflow flow rate = Loop baseline flow rate × Loop flow imbalance degree. It should be noted that this calculation is only meaningful when the loop flow imbalance degree is positive (i.e., overflow state), and the result is also positive, representing the additional mass of heat medium flowing per second.

[0048] In one implementation of this invention, this step aims to convert redundant "water flow" into redundant "heat." Specifically, the real-time overflow rate calculated in the previous step is multiplied by the real-time supply and return water temperature difference of the loop during the current monitoring period, and the specific heat capacity of water (a physical constant, preset to 4200 joules / kg·°C). The physical meaning of the calculation result is the heat waste per unit time caused by overflow, i.e., redundant heat power. The calculation formula is: Redundant heat power per unit time = Real-time overflow rate × Specific heat capacity of water × Real-time supply and return water temperature difference.

[0049] In one implementation of this invention, a timer is started for each room marked as being in "window-opening heat dissipation state". The timer begins counting from the moment the state is marked until the window-opening behavior is detected to have ended (e.g., the room temperature change rate returns to normal). The total recorded duration is the duration of the window-opening heat dissipation state. Finally, multiplying the redundant heat power per unit time calculated in the previous step by this duration yields the total overheating loss caused by the loop in this window-opening event.

[0050] In one implementation of this invention, the window-opening heat dissipation state of the "living room loop" was monitored from 3:10 PM to 3:25 PM, a total of 15 minutes. The duration of the window-opening heat dissipation state = 15 minutes × 60 seconds / minute = 900 seconds. The overheating loss of a single loop in the "living room loop" is calculated as follows: Overheating loss of a single loop = redundant heat power per unit time × duration = 630 watts × 900 seconds = 567,000 joules. For ease of energy consumption statistics, this is usually converted to a more commonly used unit, such as kilowatt-hour: Overheating loss of a single loop = 567,000 joules / 3,600,000 joules / kilowatt-hour ≈ 0.1575 kilowatt-hours. This calculation result is then added to the total overheating loss.

[0051] Most importantly, analyzing the heat loss of a single loop in a room based on its heat dissipation status, and summing up the heat loss, the total heat loss can also be obtained as follows: When the heating loop is marked as room heat dissipation status, the room reference heat dissipation power required to maintain the set temperature is calculated based on the terminal heat dissipation characteristic coefficient and the user-set temperature. The real-time total heat dissipation power of the room is calculated based on the rate of temperature change and the room temperature response gain characteristics under the heat dissipation conditions of the room. Subtract the room's baseline heat dissipation power from the room's real-time total heat dissipation power to obtain the redundant heat dissipation power caused by heat dissipation behavior. The redundant heat of the overheating loop is obtained by accumulating redundant heat dissipation power in a preset monitoring time period.

[0052] In one implementation of this invention, it is first necessary to calculate the heating power required to maintain the set room temperature under ideal conditions without opening windows. Specifically, the end-of-loop heat dissipation characteristic coefficient is retrieved from the loop thermal response dataset. This coefficient is obtained by analyzing parameters such as the reference temperature drop rate and room heat capacity during the single-loop test in step S1. Physically, it represents the additional heat dissipation power required at the end for every 1 degree Celsius increase in the temperature difference between the inside and outside of the room. Simultaneously, the user-set room temperature and the outdoor ambient temperature are read. The room's reference heat dissipation power is the product of the temperature difference between these two temperatures and the end-of-loop heat dissipation characteristic coefficient.

[0053] In one implementation of this invention, it is assumed that the "master bedroom loop" is marked as being in a window-opening heat dissipation state. The terminal heat dissipation characteristic coefficient is found to be 15 watts / degree Celsius. Simultaneously, the user-set temperature for the "master bedroom" is read as 20 degrees Celsius, and the current outdoor temperature is obtained from an external meteorological data interface as 5 degrees Celsius. Therefore, the baseline heat dissipation power of the room is calculated as follows: Room baseline heat dissipation power = (User-set temperature - Outdoor ambient temperature) × Terminal heat dissipation characteristic coefficient = (20 - 5) degrees Celsius × 15 watts / degree Celsius = 225 watts. It should be noted that this 225 watts represents the minimum heat power that the heating system needs to continuously deliver to the room to offset natural heat loss through the walls and windows, assuming no windows are open and the wall insulation performance is normal.

[0054] In one implementation of this invention, the total heat dissipation power of the room is inferred from the actual rate of temperature decrease. Specifically, after detecting heat dissipation through open windows, the real-time temperature change rate (in degrees Celsius per second) of the room is continuously calculated. Simultaneously, the room temperature response gain characteristic (in kilowatt-hours per degree Celsius) is retrieved from the database. It should be noted that the reciprocal of the room temperature response gain characteristic can be approximated as the room's heat capacity (in degrees Celsius per kilowatt-hour), i.e., the energy required to change the room temperature by 1 degree Celsius. Dividing the real-time temperature change rate by the reciprocal of the room temperature response gain characteristic (i.e., multiplying by the room temperature response gain characteristic) yields the current real-time total heat dissipation power of the room.

[0055] In another implementation of this invention, the temperature change rate of the "master bedroom" remained stable at -0.003 degrees Celsius per second during window opening. The room temperature response gain characteristic was found to be 0.2 kWh / degree Celsius from the database. This was first converted to Joules / degree Celsius for calculation: 0.2 × 3,600,000 = 720,000 Joules / degree Celsius. The reciprocal of this value is an approximation of the room's heat capacity. The room's real-time total heat dissipation power = |real-time temperature change rate| × room heat capacity = |-0.003 degrees Celsius / second| × (1 / (0.2 kWh / degree Celsius)) = 0.003 × (1 / (0.2 × 3,600,000 Joules / kWh))^(-1)... The room temperature response gain characteristic = energy / temperature rise, so energy = temperature rise × room temperature response gain characteristic. Power is the rate of change of energy over time, so power = (temperature rise / time) × room temperature response gain characteristic. The room's real-time total heat dissipation power = |real-time temperature change rate| × (1 / room temperature response gain characteristic) = |-0.003 degrees Celsius / second| × (1 / (0.2 kWh / degree Celsius))... The units are mismatched; use the energy concept. Room heat capacity. ≈1 / Room temperature response gain characteristic; Real-time total heat dissipation power ;in, Represents temperature. Represents time, It is the differential symbol in calculus, representing "an extremely small change". Therefore... It precisely describes whether the temperature is rising rapidly, rising slowly, falling rapidly, or falling slowly. If the temperature is constant, The value is 0. The reciprocal of the room temperature response gain characteristic is the room heat capacity, with units of energy / temperature. The room temperature response gain characteristic = 0.2 kWh / °C, and its reciprocal 1 / 0.2 = 5°C / kWh, which is the thermal resistance, calculated using heat capacity. Assume the room heat capacity is 1.5 MJ / °C (this is a preset or calibrated value). The room's real-time total heat dissipation power = room heat capacity × |real-time temperature change rate| = 1,500,000 joules / °C × |-0.003°C / second| = 4500 joules / second = 4500 watts. This 4500 watts represents the total equivalent heat dissipation power of the room due to open windows, heating input, and natural heat dissipation.

[0056] In one implementation of this invention, the extra heat generated by the user's specific action of opening a window is precisely extracted from the total heat dissipation. Specifically, the total real-time heat dissipation power of the room, calculated in the previous step and representing the current actual situation, is subtracted from the baseline heat dissipation power of the room, calculated in the first step and representing the ideal situation. The difference is the redundant heat dissipation power caused entirely by the act of opening the window. Based on the data of the "master bedroom," the calculation is as follows: Redundant heat dissipation power = Total real-time heat dissipation power of the room - Baseline heat dissipation power of the room = 4500 watts - 225 watts = 4275 watts. This result shows that at the moment the window is opened, as much as 4275 watts of heat power is wasted.

[0057] In one implementation of this invention, during a complete "window-opening heat dissipation state," heat accumulation is performed using its inherent monitoring time period (e.g., 3 minutes) as the basic time unit. At the end of each period, the redundant heat dissipation power calculated in the previous step is multiplied by the duration of the monitoring period to obtain the redundant heat generated in that period, and this is added to a temporary variable in the loop. When the window-opening state ends, the total value of this temporary variable is the total redundant heat caused by this event.

[0058] In one implementation of this invention, it is assumed that the window in the "master bedroom" was open for 15 minutes, for a total of 5 monitoring cycles. The average redundant heat dissipation power calculated in each cycle is 4275 watts. The redundant heat per cycle = 4275 watts × (3 × 60 seconds) = 769,500 joules. The total redundant heat of this overheating loop = 769,500 joules / cycle × 5 cycles = 3,847,500 joules ≈ 1.069 kilowatt-hours. This 1.069 kilowatt-hour is the precisely quantified overheating loss caused by this window opening event, which will then be added to the total overheating loss of the system.

[0059] Preferably, step S3, which calculates the overheating loss caused by user behavior and the heat source deterioration energy consumption caused by system compensation operation based on the loop flow state, in order to convert the carbon emission increment data of the heating system, further includes: Monitor the real-time temperature of the room corresponding to the undercurrent loop. When the real-time temperature is continuously lower than the user-set temperature and exceeds the preset undercurrent duration, the loop is determined to enter the remote undercurrent state. For loops in a state of undercurrent at the far end, read the real-time water supply temperature of the heat source and obtain the reference operating temperature of the heating system design, and calculate the difference between the two as the heat source compensation temperature rise value. Based on the heat source compensation temperature rise value and the total baseline flow rate of all heating loops, assess the heat source compensation power generated by increasing the supply water temperature to compensate for the underflow at the far end. By integrating the heat source compensation power over time with the duration of the remote undercurrent state, the energy consumption of heat source degradation caused by the undercurrent loop can be determined.

[0060] In one implementation of this invention, all rooms marked as "undercurrent loops" in step S2 are continuously monitored. Specifically, a preset "undercurrent duration" is read from their configuration parameters. This parameter is typically set based on the user's tolerance for temperature fluctuations or the building's thermal inertia, for example, 1 hour. In each monitoring cycle, the real-time temperature of the room is compared with the user-set desired temperature. If the real-time temperature remains below the set temperature, an internal timer is activated; once the accumulated duration of this timer exceeds the preset 1 hour, the heating loop is officially classified as "remote undercurrent state".

[0061] In one implementation of this invention, the "study room loop" is marked as an undercurrent loop, with a user-set temperature of 21 degrees Celsius. Starting at 9:00 AM, the room temperature was monitored to fluctuate between 19.5 and 20 degrees Celsius, never reaching 21 degrees Celsius. By 10:00 AM, the low temperature had persisted for one hour, meeting the criteria. Therefore, at 10:00 AM, the "study room loop" is marked as "remote undercurrent state," triggering subsequent energy consumption analysis logic.

[0062] In one implementation of this invention, once a loop is determined to be in a "remote undercurrent state," the real-time water supply temperature at the outlet of the heat source equipment is immediately collected. Simultaneously, a key design parameter—the "baseline operating temperature"—is read from its core configuration file. It should be noted that this baseline operating temperature is the ideal water supply temperature set during the initial design of the heating system to meet the heat load of all rooms under standard operating conditions. Subtracting the real-time water supply temperature, which has been manually or automatically increased, from this ideal baseline temperature yields the additional temperature rise compensated for the remote undercurrent.

[0063] In one implementation of this invention, after the "study room loop" enters a remote undercurrent state, the current real-time water supply temperature of the heat source is read as 55 degrees Celsius. A query reveals that the baseline operating temperature of the heating system is designed to be 50 degrees Celsius. Therefore, the heat source compensation temperature rise is calculated as follows: Heat source compensation temperature rise = Real-time water supply temperature - Baseline operating temperature = 55 degrees Celsius - 50 degrees Celsius = 5 degrees Celsius. This 5-degree Celsius difference clearly quantifies the "overheating" drive caused to the entire system in order to solve the "study room not being hot" problem.

[0064] In one implementation of this invention, the "temperature increase" is transformed into an "increase in power." Specifically, the system first iterates through the loop reference flow rates measured for all heating loops in step S1 and sums them to obtain the total reference flow rate of the entire pipe network system. Subsequently, the heat source compensation power is evaluated according to the basic thermodynamic formula. Its mathematical expression is: Heat source compensation power = Total reference flow rate × Specific heat capacity of water × Heat source compensation temperature rise value; where "specific heat capacity of water" is a physical constant, preset to 4200 joules / kg·degree Celsius.

[0065] In one implementation of this invention, the system times the duration of the "remote undercurrent state". In each monitoring cycle, the heat source compensation power calculated in the previous step is multiplied by the duration of the monitoring cycle to obtain the degraded energy consumption generated within that cycle, and this is accumulated into an energy consumption accumulator associated with the undercurrent loop. It should be noted that this "time integration" in the digital system is represented by periodic summation. When the remote undercurrent state is resolved (e.g., the room temperature reaches the target), timing and accumulation stop, and the final value in the accumulator is the total heat source degraded energy consumption caused by this event.

[0066] In one implementation of this invention, it is assumed that the undercurrent state at the far end of the "study room loop" lasts from 10:00 AM to 12:00 PM, a total of 2 hours. The duration of the undercurrent state at the far end = 2 hours × 3600 seconds / hour = 7200 seconds; then the energy consumption due to heat source degradation caused by this undercurrent loop is calculated as follows: Heat source degradation energy consumption = heat source compensation power × duration = 10500 watts × 7200 seconds = 75,600,000 joules; for ease of statistics, the system converts it to kilowatt-hours: Heat source degradation energy consumption = 75,600,000 joules / 3,600,000 joules / kilowatt-hour = 21 kilowatt-hours; this 21 kilowatt-hour of additional energy consumption is the "hidden" energy consumption that can be accurately quantified due to the inefficient operation of the system caused by the hydraulic imbalance of the pipeline network.

[0067] Preferably, step S3, which calculates the overheating loss caused by user behavior and the heat source deterioration energy consumption caused by system compensation operation based on the loop flow state, in order to convert the carbon emission increment data of the heating system, further includes: The total heat loss due to overheating is summed with the energy consumption caused by the deterioration of heat sources due to all undercurrent loops, and this sum is taken as the total incremental energy consumption of the heating system. Based on the type of heat source configured in the integrated energy housing, query and match its corresponding carbon emission factor per unit of heat. The total incremental energy consumption of the heating system is multiplied by the carbon emission factor per unit heat, thereby calculating and updating the incremental carbon emission data of the heating system.

[0068] In one implementation of this invention, the two types of "hidden" energy consumption previously calculated separately and caused by different reasons (wasteful user behavior and system compensation operation) are combined to obtain a total energy waste caused by the hydraulic imbalance problem. Specifically, the system reads two globally accumulated variables from its memory: one is the "total overheating loss heat" caused by the continuous accumulation of all overcurrent loop opening and heat dissipation behaviors, and the other is the "heat source degradation energy consumption" accumulated by all undercurrent loops causing inefficient system operation. The system directly adds these two values ​​together.

[0069] In one implementation of this invention, to convert energy consumption into carbon emissions, it is necessary to know the carbon footprint of the energy type that generates this heat. Specifically, the system accesses the device configuration file set during initialization to read the core heat source type configured in the integrated energy house. Subsequently, the system uses this heat source type as a keyword to perform a query and match in a built-in, standardized "energy carbon emission coefficient database." It should be noted that this coefficient database is pre-established based on official energy consumption and carbon emission accounting standards published by the state or industry.

[0070] In one implementation of this invention, this is a crucial step in quantifying total energy waste into environmental impact. The "total incremental energy consumption of the heating system" calculated in the first step is multiplied by the "carbon emission factor per unit heat" matched to the heat source type obtained in the second step. The result is the precisely measurable increase in carbon emissions caused by hydraulic imbalance. This data is recorded and stored for generating energy efficiency reports, triggering energy-saving optimization recommendations, or serving as a basis for carbon asset management.

[0071] Preferably, step S4 includes the following steps: Step S41: Obtain the pipe network topology data of the heating system; Step S42: Identify the common manifold node that contains both overcurrent loops and undercurrent loops based on the pipeline topology data; Step S43: Summarize the loop flow imbalance of all flow loops in the area based on the common manifold node to calculate the total flow regulation of the area; Step S44: Based on the total regional flow adjustment amount, the flow imbalance of the undercurrent loops is weighted and allocated, and the target flow compensation amount is calculated for each undercurrent loop. Step S45: Calculate the valve opening increment or reduction based on the total regional flow adjustment and the target flow compensation. Step S46: Obtain the current valve opening of the common manifold node, and construct the manifold valve adjustment command data according to the valve opening increment or reduction.

[0072] In one implementation of this invention, when the system initiates the flow regulation process, it first loads a preset pipeline topology data from its system configuration file. It should be noted that this data was entered by technicians during the system installation and commissioning phase, based on the actual pipeline layout of the building, and describes the physical connection relationships between each heating loop and the manifold nodes in a structured format (e.g., JSON or XML).

[0073] In one implementation of this invention, each manifold node in the topology data obtained in the previous sub-step is traversed. Specifically, for each node, the algorithm checks whether its subordinate loop list contains members simultaneously marked as "overflow loop" and "underflow loop" in step S2. If a node satisfies both conditions, then the node is identified as a "common manifold node" requiring internal flow rebalancing and added to the pending list.

[0074] In one implementation of this invention, the current system state is assumed to be: "Living room loop" (overcurrent), "Dining room loop" (normal), "Study room loop" (undercurrent), "Master bedroom loop" (overcurrent), and "Secondary bedroom loop" (normal). The algorithm analyzes "Manifold Node 1" and finds that its subordinate "Living room loop" is in an overcurrent state, and its "Study room loop" is in an undercurrent state. Therefore, "Manifold Node 1" is identified as a common manifold node. "Manifold Node 2" has only one overcurrent loop and no undercurrent loop, therefore it is not selected.

[0075] In one implementation of this invention, for each identified common manifold node, the total redundant flow that needs to be reallocated within it is calculated. Specifically, the algorithm iterates through all members marked as "flow loops" under that node, reads their respective loop flow imbalance (a dimensionless percentage), multiplies it by their respective loop reference flow, and then sums the results. The mathematical expression is: Total flow regulation of the area = Σ(loop flow imbalance of a single flow loop × loop reference flow of that loop).

[0076] In one implementation of this invention, the calculated total adjustment amount is allocated to undercurrent loops under the same node according to the principle of "allocation on demand". Specifically, the algorithm first summarizes the sum of the absolute values ​​of the loop flow imbalance of all undercurrent loops under the node as the allocation weight. Then, the absolute value of the imbalance of each undercurrent loop is divided by this sum to obtain the respective allocation ratio. Finally, the total flow adjustment amount of the region is multiplied by this ratio to obtain the target flow compensation amount that the undercurrent loop should receive.

[0077] In one implementation of this invention, a preset "flow valve opening" characteristic curve model is invoked. This model, calibrated experimentally during the system debugging phase, describes the nonlinear relationship between valve opening and through flow. For an overflow loop, the required flow reduction (equal to its contribution to regulation) is input, and the model inversely solves for the percentage of valve opening reduction needed. For an underflow loop, the target flow compensation amount is input, and the model inversely solves for the percentage of valve opening increase needed.

[0078] In one implementation of this invention, before generating the final instruction, the current real-time opening degree of the relevant loop valves is read. Then, the current opening degree is added to or subtracted from the opening change calculated in the previous step to obtain the final target opening degree. It should be noted that the calculation result is limited to a valid range of 0% to 100%. Finally, the identifier of each loop and its corresponding target opening degree are encapsulated into an instruction, forming a set of manifold valve adjustment instruction data.

[0079] Of particular importance is obtaining the current valve opening of the common manifold node and constructing manifold valve regulation command data based on the valve opening increment or reduction, including: The absolute value of the flow imbalance of all flow loops is extracted from the flow imbalance of the loops as a weighting coefficient. The carbon emission increment data is allocated to each flow loop according to the weighting coefficient ratio to obtain the carbon responsibility value of each loop. The carbon responsibility values ​​of each loop are sorted from largest to smallest, and the loops with the highest carbon responsibility values ​​are selected as priority adjustment targets. Read the current valve opening of each priority adjustment object from the manifold control system, and calculate the target valve opening based on the corresponding flow correction coefficient and flow imbalance degree; Extract the flow deficit of all undercurrent loops from the flow imbalance dataset and sum them up. Allocate the total flow deficit as additional transfer flow according to the carbon responsibility value of each flow loop. Convert the additional transfer flow into additional shutdown amount for each flow loop. The final valve regulation is calculated by combining the target valve opening and additional closing amount of each loop. The expected emission reduction is calculated based on the final valve regulation and carbon responsibility value. The loop number, distance characteristics, current opening, target opening, regulation amount and expected emission reduction are summarized to generate manifold valve regulation command data.

[0080] In one implementation of this invention, the total increase in carbon emissions caused by hydraulic imbalance is fairly attributed to the individual flow loops that caused the problem. Specifically, all members marked as "flow loops" are traversed, and their respective loop flow imbalance degrees are read. This imbalance degree (a positive percentage) is directly used as the basis for weight allocation. The imbalance degrees of all flow loops are summed to obtain the total weight, and then the imbalance degree of each loop is divided by the total weight to obtain the proportion of carbon emission responsibility that loop should bear. Finally, the total increase in carbon emissions calculated in step S3 is multiplied by this proportion to obtain the specific carbon responsibility value for each flow loop.

[0081] In one implementation of this invention, to maximize regulation efficiency, loops that cause the most carbon emissions are prioritized. Specifically, the carbon responsibility values ​​of all flow loops calculated in the previous step are sorted in descending order. Then, according to a preset regulation strategy, such as selecting the top 50% of loops or fixing the top 3 loops, these selected loops are marked as "priority regulation targets".

[0082] In one implementation of this invention, the current real-time valve opening of each priority adjustment object (e.g., the "living room loop") is queried and obtained from the manifold controller. Simultaneously, a built-in valve adjustment model is invoked. The core of this model is a flow correction coefficient, which is preset based on the valve type and pipeline characteristics to quantify the impact of opening changes on flow rate. The formula for calculating the target valve opening is: Target valve opening = Current valve opening × (1 - Flow correction coefficient × Flow imbalance).

[0083] In one implementation of this invention, the total flow required by all undercurrent loops (total flow deficit) is calculated. Then, this total deficit is allocated to each priority regulation object (current loop) according to their respective carbon responsibility values, yielding the additional transfer flow required from each current loop. Finally, the valve characteristic curve model is used again to convert this additional transfer flow into a percentage reduction in valve opening, i.e., an additional closing amount.

[0084] Specifically, the final target valve opening is obtained by subtracting the additional closure amount calculated in the fourth step from the target valve opening calculated in the third step. The expected emission reduction is directly taken from the carbon liability value undertaken by this loop in this round of calculation, as it represents the amount of carbon emissions that this adjustment aims to eliminate. Finally, the loop's unique number, pipeline distance, and other static characteristics, as well as the dynamic calculation results such as the current opening, the final target opening, the total adjustment amount (the difference between the current opening and the target opening), and the expected emission reduction, are encapsulated into a structured data frame.

[0085] Please see Figure 2 , Figure 2 The core object of this application's embodiments is a schematic diagram of the topology of a typical residential heating system based on a "heat source-loop" design. Starting from the "heat source," the diagram shows six parallel or series-connected terminal loops formed by supply pipes (solid lines) and return pipes (dashed lines), supplying heat to rooms such as bedrooms, kitchens, and bathrooms. "Overflow / Underflow" indicators are used to visually diagnose the hydraulic characteristics of each loop. The elements in the diagram and their logical meanings are as follows: Nodes and Legend: Heat Source: Located at the top of the topology, a circular node, representing a gas-fired wall-hung boiler or a central heating system's heat exchange station, which is the heat and circulation power source for the entire system.

[0086] End room: Rectangular node, labeled "Bedroom 1, Bedroom 2, Kitchen, Bathroom", representing the heat load demand side, and also the connection point for loop numbering and commissioning results.

[0087] Loop numbers: L1 to L6, six horizontally arranged line segments, corresponding to six independently distributed pipelines, numbered from left to right, matching the room load one by one.

[0088] Legend: Solid line represents water supply pipe (direction of high-temperature water flow); dashed line represents return pipe (direction of low-temperature water return); blue line represents overflow loop (actual flow rate > 120% of design value); red line represents underflow loop (actual flow rate < 80% of design value).

[0089] The system adopts a "bottom-up supply and bottom-up return, same-path" layout to ensure that the theoretical length of each loop is consistent. However, in actual operation, flow deviations may occur due to differences in pipe resistance, valve opening drift, or unauthorized adjustments by users. The diagram uses three line types to represent the "design path" and "anomaly diagnosis" in layers: Solid line (thick): Supply main pipe and normal loop branches, representing the design flow range of 80%–120%. Dashed line (thin): Return main pipe, used only for flow direction identification and not for anomaly marking. Red / blue line: Superimposed on the center of the loop, used for qualitative judgment of "overflow" and "underflow," allowing maintenance personnel to easily identify unbalanced loops at a glance.

[0090] Taking "Loop 3" as a typical example, assuming that after the system starts, the heat source outlet water temperature is set to 60℃ and the circulating pump runs at a constant speed. At this time: the high-temperature water flows downward along the water supply main and first flows to Loop 3 (Bedroom 2). If the radiator valve in this bedroom was closed or the branch pipe is partially blocked, the local resistance increases, and the measured flow rate drops to 65% of the design value. Loop 3 is immediately marked as underflow in red. The room temperature in Bedroom 2 is insufficient, and the user is forced to increase the main thermostat, causing the other rooms to become overheated. To maintain the overall temperature, the heat source continues to increase its load, increasing gas consumption by about 6%, and carbon emissions increase simultaneously. According to the red circle in the diagram, the user can directly lock Loop 3, close the balancing valve of this branch, and reduce the flow rate back to 100%±5%. The system restores thermal balance, and the overall energy consumption of the household decreases. For individual variable flow systems, wireless flow meters and electric heating regulating valves can be added to each loop, and the node colors can be changed from "red / blue" to a continuous color spectrum to achieve 0-100% stepless visualization. At the same time, the "overflow / underflow" criterion is written into the edge algorithm to automatically issue valve opening commands and complete closed-loop adaptive balancing. Figure 2 The static marker shown is upgraded to a real-time digital twin interface, but the core topology and diagnostic logic remain unchanged.

[0091] Please see Figure 3 The flowchart below illustrates the carbon emission monitoring process for an integrated energy house according to an embodiment of this application. First, the loop thermal response of each heating loop is tested—standard heat is applied to each branch to establish zero-carbon benchmarks such as peak temperature delay and reference temperature difference. Next, the loop flow imbalance is assessed—the supply and return water temperature difference is monitored in real time, compared to the benchmark, the imbalance is quantified, and overflow / underflow loops are marked for treatment. Then, carbon emission increment is calculated—overflow and overheat losses and underflow compensation energy consumption are uniformly converted into real-time carbon increments and dynamically displayed on the monitoring terminal. Finally, flow regulation and optimization—based on the real-time carbon increment ranking, valve adjustment commands are automatically generated to close the loop and reduce imbalance until the carbon increment approaches zero, achieving visibility, calculation, and controllability of household-level heating's implicit carbon emissions.

[0092] Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of the equivalents of the application are intended to be included within the invention.

[0093] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features of the invention herein.

Claims

1. A method for monitoring carbon emissions from an integrated energy house, characterized in that, Includes the following steps: Step S1: Apply heat input tests to each heating loop of the heating system in the integrated energy house in turn, and collect loop reference thermal characteristic data of each heating loop to construct a loop thermal response dataset. Step S2: Under normal heating conditions in the integrated energy house heating system, periodically monitor the real-time supply and return water temperature difference, and conduct comparative analysis based on the loop reference thermal characteristic data to assess the loop flow imbalance of each heating loop; mark the loop flow direction status according to the positive and negative values ​​of the loop flow imbalance; wherein, the loop flow direction status includes overflow loops and underflow loops, with positive values ​​marked as overflow loops and negative values ​​marked as underflow loops; Step S3: Calculate the overheating loss caused by user behavior and the heat source deterioration energy consumption caused by system compensation operation according to the loop flow state, so as to calculate the carbon emission increment data of the heating system. Step S4: Perform flow regulation processing on the overcurrent loop and undercurrent loop to generate manifold valve regulation command data.

2. The carbon emission monitoring method for integrated energy houses according to claim 1, characterized in that, In step S1, heat input tests are applied to each heating loop of the integrated energy house heating system individually, and loop reference thermal characteristic data of each heating loop are collected to construct a loop thermal response dataset, including: By closing all loop valves except the loop under test through the manifold control terminal, the single-loop test procedure can be initiated. The heat source is controlled to supply heat to the loop under test at a fixed temperature 5-15 degrees Celsius higher than the preset normal water supply temperature for 5-10 minutes to apply heat input. During the heat input and subsequent 30-minute natural decay period, the water supply temperature, return temperature, and center point temperature of the corresponding room in the test loop are synchronously collected at a frequency of no less than 15 seconds to form three sets of temperature time series data.

3. The carbon emission monitoring method for integrated energy houses according to claim 2, characterized in that, Step S1, which involves sequentially applying heat input tests to each heating loop of the integrated energy house's heating system and collecting loop baseline thermal characteristic data for each loop to construct a loop thermal response dataset, also includes: The time difference between the return water inlet temperature reaching its peak value and the supply water inlet temperature reaching its peak value is calculated as the temperature peak conduction delay. The rate of temperature drop at the return water inlet after the heat input stops is calculated as the reference temperature drop rate. The baseline supply and return water temperature difference is analyzed based on the supply and return water temperatures. The room temperature rise data was calculated based on the initial and final center point temperatures of the room from three sets of temperature time series data. The ratio of total heat input to room temperature rise data is calculated as a characteristic of room temperature response gain. The temperature peak conduction delay, reference temperature drop rate, reference supply and return water temperature difference, and room temperature response gain characteristics are encapsulated as loop reference thermal characteristic data for the loop under test.

4. The carbon emission monitoring method for integrated energy houses according to claim 2, characterized in that, In step S2, under normal heating conditions in the integrated energy house heating system, the real-time supply and return water temperature difference is periodically monitored, and a comparative analysis is performed based on loop reference thermal characteristic data to assess the loop flow imbalance of each heating loop, including: Periodically monitor the real-time supply and return water temperatures of each heating loop; The real-time supply and return water temperature difference of each heating loop is calculated based on the real-time supply water temperature and return water temperature, and the reference supply and return water temperature difference and reference temperature drop rate of the heating loop are read from the loop thermal response dataset. The terminal heat dissipation characteristic coefficient is set based on the reference temperature drop rate, and the temperature correction factor is calculated based on the difference between the real-time water supply temperature and the fixed temperature during the single-loop test of the heating loop. The corrected supply and return water temperature difference is obtained by multiplying the baseline supply and return water temperature difference by a temperature correction factor. Divide the reference supply and return water temperature difference by the real-time supply and return water temperature difference to obtain the loop flow imbalance.

5. The carbon emission monitoring method for integrated energy houses according to claim 1, characterized in that, In step S3, the overheating loss caused by user behavior and the energy consumption due to heat source degradation caused by system compensation operation are calculated separately according to the loop flow state, so as to calculate the carbon emission increment data of the heating system, including: The room heat dissipation judgment threshold is dynamically determined based on the room temperature response gain characteristics in the loop reference thermal characteristic data. Monitor the real-time temperature of the room corresponding to the overcurrent loop, calculate the deviation between the real-time temperature and the user-set temperature, and mark the room as potentially overheated and the heating loop as an overheating loop when the deviation exceeds the preset overheating temperature threshold and the duration exceeds the preset overheating duration. Calculate the room temperature change rate under potential overheating conditions, and mark the room as having heat dissipation status when the temperature change rate is less than the room heat dissipation judgment threshold. For each room's heat dissipation status, the overheat loss of a single loop is analyzed, and the overheat loss is accumulated to obtain the total overheat loss.

6. The carbon emission monitoring method for integrated energy houses according to claim 5, characterized in that, For a given room's heat dissipation status, the overheating loss of a single loop is analyzed, and the total overheating loss is accumulated to obtain the total overheating loss, including: The actual water flow transit time of each heating loop under normal operation is estimated based on the temperature peak conduction delay in the loop reference thermal characteristic data. The loop reference flow rate of the pipeline network is assessed based on the actual water flow transit time of each heating loop. Determine the overcurrent flow rate based on the loop reference flow rate. For rooms with high heat dissipation, the loop flow imbalance of the heating loop is read, and the redundant heat per unit time is calculated based on the overflow rate and the real-time supply and return water temperature difference. Obtain the duration of heat dissipation status in the rooms corresponding to each heating loop, and calculate the overheat loss of a single loop based on the redundant heat per unit time.

7. The carbon emission monitoring method for integrated energy houses according to claim 1, characterized in that, Step S3, which calculates the overheating loss caused by user behavior and the energy consumption due to heat source degradation caused by system compensation operation based on the loop flow state, to convert the incremental carbon emission data of the heating system, also includes: Monitor the real-time temperature of the room corresponding to the undercurrent loop. When the real-time temperature is continuously lower than the user-set temperature and exceeds the preset undercurrent duration, the loop is determined to enter the remote undercurrent state. For loops in a state of undercurrent at the far end, read the real-time water supply temperature of the heat source and obtain the reference operating temperature of the heating system design, and calculate the difference between the two as the heat source compensation temperature rise value. Based on the heat source compensation temperature rise value and the total baseline flow rate of all heating loops, assess the heat source compensation power generated by increasing the supply water temperature to compensate for the underflow at the far end. By integrating the heat source compensation power over time with the duration of the remote undercurrent state, the energy consumption of heat source degradation caused by the undercurrent loop can be determined.

8. The carbon emission monitoring method for integrated energy houses according to claim 1, characterized in that, Step S3, which calculates the overheating loss caused by user behavior and the energy consumption due to heat source degradation caused by system compensation operation based on the loop flow state, to convert the incremental carbon emission data of the heating system, also includes: The total heat loss due to overheating is summed with the energy consumption caused by the deterioration of heat sources due to all undercurrent loops, and this sum is taken as the total incremental energy consumption of the heating system. Based on the type of heat source configured in the integrated energy housing, query and match its corresponding carbon emission factor per unit of heat. The total incremental energy consumption of the heating system is multiplied by the carbon emission factor per unit heat, thereby calculating and updating the incremental carbon emission data of the heating system.

9. The carbon emission monitoring method for integrated energy houses according to claim 1, characterized in that, Step S4 includes the following steps: Step S41: Obtain the pipe network topology data of the heating system; Step S42: Identify the common manifold node that contains both overcurrent loops and undercurrent loops based on the pipeline topology data; Step S43: Summarize the loop flow imbalance of all flow loops in the area based on the common manifold node to calculate the total flow regulation of the area; Step S44: Based on the total regional flow adjustment amount, the flow imbalance of the undercurrent loops is weighted and allocated, and the target flow compensation amount is calculated for each undercurrent loop. Step S45: Calculate the valve opening increment or reduction based on the total regional flow adjustment and the target flow compensation. Step S46: Obtain the current valve opening of the common manifold node, and construct the manifold valve adjustment command data according to the valve opening increment or reduction.

10. A carbon emission monitoring system for an integrated energy house, characterized in that, For performing the carbon emission monitoring method for an integrated energy house as described in claim 1, the carbon emission monitoring system for the integrated energy house includes: The heating loop feature module is used to sequentially apply heat input tests to each heating loop of the heating system in the integrated energy house, and collect loop reference thermal feature data of each heating loop to construct a loop thermal response dataset. The flow imbalance analysis module is used to periodically monitor the real-time supply and return water temperature difference under normal heating conditions in the heating system of the integrated energy house, and to perform comparative analysis based on the loop reference thermal characteristic data to assess the loop flow imbalance of each heating loop; the loop flow direction status is marked according to the positive and negative values ​​of the loop flow imbalance; the loop flow direction status includes overflow loops and underflow loops, with positive values ​​marked as overflow loops and negative values ​​marked as underflow loops; The carbon emission increment calculation module is used to calculate the overheating loss caused by user behavior and the heat source deterioration energy consumption caused by system compensation operation according to the loop flow status, so as to calculate the carbon emission increment data of the heating system. The system optimization and control module is used to regulate the flow of the overflow loop and underflow loop, and generate valve adjustment command data for the manifold.

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