Dynamic matching control method and system for temperature and humidity load oriented to low-carbon building scene

Abstract

This invention discloses a dynamic temperature and humidity load matching control method and system for low-carbon building scenarios, belonging to the field of building environment control and energy-saving technology. It collects building space temperature and humidity, envelope surface temperature, and air conditioning operating parameters to determine sensible and latent heat demands and corresponding processing capacities, and calculates sensible and latent heat mismatch coefficients and dynamic condensation margins. Based on these, a two-dimensional state domain for temperature and humidity load is constructed, and the direction of state change is determined by combining the historical displacement of state points. Accordingly, the thermal-humidity coupling control state is determined, and candidate adjustment combinations are generated. Under the conditions of satisfying condensation safety constraints and sensible and latent heat convergence constraints, the combination with the lowest energy consumption per unit target load is selected for adjustment, and the system is continuously updated based on the adjusted state points. This invention can balance sensible and latent heat matching, condensation safety, and low-energy operation, reducing excessive cooling, repeated dehumidification, and heat-cold offsetting.

Description

Technical Field

[0001] This invention relates to the field of building environment control and energy conservation technology, specifically to a dynamic temperature and humidity load matching control method and system for low-carbon building scenarios. Background Technology

[0002] With the widespread application of low-carbon buildings, near-zero energy buildings, and high-performance building envelopes, heat transfer losses in building envelopes are gradually decreasing, and the proportion of sensible heat load indoors is relatively smaller. Meanwhile, latent heat load, formed by occupant activity, fresh air intake, and the infiltration of humid outdoor air, exhibits strong time-varying characteristics, causing the sensible heat demand and latent heat demand in building spaces to show significant asynchronous changes. Existing air conditioning systems typically detect indoor temperature and relative humidity, compare the detected values ​​with preset temperature and humidity thresholds, and determine control states such as cooling, heating, dehumidification, or humidification based on the comparison results. Then, they adjust the cooling capacity, air supply volume, fresh air volume, or dehumidification equipment accordingly.

[0003] However, the aforementioned control methods primarily focus on whether indoor temperature and humidity exceed set ranges, with less consideration given to the dynamic matching relationship between the building's sensible and latent heat demands and the sensible and latent heat handling capabilities of the air conditioning equipment. When a building is operating under conditions of low sensible heat and high latent heat, the equipment typically needs to further reduce the heat exchanger or supply air temperature to meet dehumidification requirements. This can easily lead to overcooling when the indoor temperature is already close to the target value, resulting in reheat compensation, frequent equipment switching, and additional energy consumption. Furthermore, relative humidity is a temperature-dependent state parameter. Controlling it solely based on the overall relative humidity of the space makes it difficult to reflect the proximity between the air dew point temperature and the surface temperatures of the building envelope, ducts, or air supply components. Therefore, there is a risk of localized condensation even when the indoor temperature and humidity are still within acceptable ranges.

[0004] Furthermore, existing technologies typically use fixed thresholds or discrete control intervals to determine the temperature and humidity control state, mainly reflecting the static state at the current moment. This makes it difficult to combine the continuous trend of temperature and humidity changes to determine whether the system is converging towards a safe zone or deteriorating towards load mismatch or condensation boundaries, thus easily leading to control lag, control oscillations, or repeated adjustments. For the same temperature and humidity control requirement, there are often multiple feasible equipment operation combinations for refrigeration, dehumidification, fresh air conditioning, and supply air temperature regulation. However, existing control methods usually adjust according to a fixed control sequence or preset equipment priority, lacking a comprehensive comparison of the sensible and latent heat matching effect, condensation safety level, and unit load adjustment energy consumption of different adjustment combinations. This results in unnecessary energy consumption even while the system achieves the temperature and humidity control target.

[0005] Therefore, existing technologies cannot simultaneously solve the problems of dynamic mismatch between sensible heat demand and latent heat demand, difficulty in timely identification of local condensation risk, insufficient utilization of thermal and humidity state change trends, and difficulty in effectively coordinating the energy consumption differences of different equipment adjustment combinations. This limits the refined and low-energy operation of low-carbon building air conditioning systems under the condition of meeting indoor temperature and humidity requirements. Summary of the Invention

[0006] The purpose of this invention is to provide a dynamic temperature and humidity load matching control method and system for low-carbon building scenarios, so as to solve the shortcomings of the prior art.

[0007] To achieve the above objectives, the present invention provides the following technical solution: a dynamic temperature and humidity load matching control method for low-carbon building scenarios, comprising: The indoor temperature, relative humidity, surface temperature of the building envelope, and operating parameters of the air conditioning equipment in the target building space are collected. Based on the indoor temperature and relative humidity, the air moisture content, dew point temperature, sensible heat demand, and latent heat demand are determined. Based on the operating parameters of the air conditioning equipment, the sensible heat treatment capacity and latent heat treatment capacity are determined. The sensible and latent heat mismatch coefficients are calculated based on the sensible heat demand, latent heat demand, sensible heat treatment capacity, and latent heat treatment capacity, and the dynamic condensation margin is determined based on the difference between the surface temperature of the building envelope and the dew point temperature. A two-dimensional state domain of temperature and humidity load is constructed using the apparent latent heat mismatch coefficient and dynamic condensation margin. The target state region to which the current state point belongs is determined, and the direction of state change relative to the boundary of the target state region is determined based on the displacement relationship between the current state point and continuous historical state points. The thermal-humidity coupling control state is determined based on the target state region and the direction of state change, and at least two candidate adjustment combinations including cooling capacity, dehumidification capacity, fresh air volume and supply air temperature are generated based on the thermal-humidity coupling control state. Calculate the unit target load regulation energy consumption corresponding to each candidate regulation combination. Among the candidate regulation combinations that meet the dynamic condensation margin safety constraints and the convergence direction constraints of sensible and latent heat mismatch, select the target regulation combination with the lowest unit target load regulation energy consumption, and control the operation of the air conditioning equipment according to the target regulation combination. The adjusted latent heat mismatch coefficient and dynamic condensation margin are obtained. The state points in the two-dimensional state domain are updated according to the adjusted latent heat mismatch coefficient and dynamic condensation margin. When the state point does not enter the preset matching safety area, the thermal-humidity coupling control state and target adjustment combination are re-determined until the state point enters the preset matching safety area.

[0008] Preferably, the determination of the apparent latent heat mismatch coefficient includes: Sensible heat demand and latent heat demand are combined into demand-side data pairs, and sensible heat processing capacity and latent heat processing capacity are combined into equipment-side data pairs. The sensible heat and latent heat in each data pair are compared to determine the normalized ratio value. Based on the heat type of the larger quantity, a directional indicator is assigned: sensible heat dominance, latent heat dominance, or sensible and latent heat balance. The demand-side position value and equipment-side position value are determined according to the directional indicator and the normalized ratio value, so that sensible heat dominance corresponds to a positive position and latent heat dominance corresponds to a negative position. The difference between the equipment-side position value and the demand-side position value is calculated to obtain the sensible and latent heat mismatch coefficient.

[0009] Preferably, the determination of dynamic condensation margin includes: When multiple building envelope surface temperatures exist at the same sampling time, the lowest value is selected as the effective building envelope surface temperature, and the condensation temperature difference between the effective building envelope surface temperature and the corresponding dew point temperature is calculated. The condensation temperature difference at the current sampling time and the previous two sampling times is obtained. When the condensation temperature difference in two consecutive sampling intervals decreases, the approach intensity is determined based on the average of the actual decrease in the two sampling intervals, and the approach intensity is subtracted from the current condensation temperature difference to obtain the corrected condensation temperature difference. The minimum condensation temperature difference is obtained from the condensation temperature differences at three consecutive sampling times, and the smaller of the corrected condensation temperature difference and the minimum condensation temperature difference is selected as the dynamic condensation margin when the continuous approaching condensation state is not present. When there is no continuous approaching state, the current condensation temperature difference is used as the dynamic condensation margin.

[0010] Preferably, the determination of the two-dimensional state domain and the direction of state change of temperature and humidity load includes: Using the latent heat mismatch coefficient as the first state dimension and the dynamic condensation margin as the second state dimension, the two-dimensional state domain is divided into multiple state regions formed by the intersection of load matching, strong sensible heat treatment, strong latent heat treatment and condensation safety, condensation approach, and condensation risk, respectively, based on the sensible heat matching boundary, condensation safety boundary, and condensation occurrence boundary. The current state point and its unique target state region are determined according to the current sensible heat mismatch coefficient and dynamic condensation margin. Two consecutive historical state points before the current state point are obtained, and the change direction of the absolute value of sensible heat mismatch and dynamic condensation margin in the continuous sampling interval are determined. When the change directions of the two state dimensions are inconsistent, the ratio of the distance from the current state point to the boundary of the approaching region to the corresponding average displacement is calculated, and the boundary with the smallest expected sampling steps is determined as the main approaching boundary, and the state change direction is determined accordingly.

[0011] Preferably, the determination of the thermal-humidity coupling control state and candidate adjustment combinations includes: Based on the target state region, determine the basic adjustment direction of sensible heat treatment reduction, latent heat treatment reduction, matching maintenance, or condensation priority, and determine whether the current state is approaching the load mismatch boundary or condensation risk boundary based on the state change direction; when the state point moves towards the unfavorable boundary, the adjustment target corresponding to the main approach boundary is promoted to the priority adjustment target, thereby determining the heat and humidity coupling control state; using the current cooling capacity, dehumidification capacity, fresh air volume, and supply air temperature as reference parameters, define the increase, decrease, or maintenance direction of each parameter according to the heat and humidity coupling control state, forming at least two different parameter adjustment paths, and making the sensible and latent heat composition on the equipment side corresponding to each adjustment path move closer to the sensible and latent heat composition on the demand side or make the dynamic condensation margin change in the direction of increasing, thereby obtaining candidate adjustment combinations.

[0012] Preferably, the determination of the sensible heat demand, latent heat demand, sensible heat treatment capacity, and latent heat treatment capacity includes: determining the sensible heat demand and latent heat demand based on the indoor temperature, relative humidity, and target temperature and humidity conditions, combined with the heat transfer of the building envelope, heat dissipation and moisture dissipation of personnel and equipment, and the introduction of fresh air; and determining the sensible heat treatment capacity and latent heat treatment capacity based on the supply and return air temperature difference, humidity difference, and air mass flow rate.

[0013] Preferably, the latent heat matching boundary is determined based on the maximum absolute value of the latent heat mismatch coefficient collected when the indoor temperature and humidity are within the design allowable range and there is no condensation. The condensation safety boundary is determined based on the sum of the maximum error in the surface temperature measurement of the building envelope, the maximum error in the dew point temperature calculation, and the maximum sampling fluctuation of the surface temperature during stable operation.

[0014] Preferably, the determination of the target regulation combination includes: obtaining candidate latent heat mismatch coefficients and candidate dynamic condensation margins for each candidate regulation combination; eliminating candidate regulation combinations that cannot bring the latent heat mismatch to the matching region or cannot maintain or improve the condensation safety margin; determining the unit target load regulation energy consumption among the remaining candidate regulation combinations based on the ratio of the total energy consumption of one control cycle to the effective target load regulation amount; and selecting the candidate regulation combination with the lowest unit target load regulation energy consumption as the target regulation combination.

[0015] Preferably, the state point update in the two-dimensional state domain includes: after the target adjustment combination executes a control cycle, the apparent latent heat mismatch coefficient and dynamic condensation margin are re-obtained to form an updated state point; the displacement of the state point before and after adjustment is used to determine whether it has migrated along the safe matching direction; and when the updated state point does not simultaneously satisfy the apparent latent heat matching boundary and the condensation safety boundary, the updated state point is used as the current state point of the next control cycle to redetermine the thermal-humidity coupling control state and the target adjustment combination.

[0016] This invention also provides a dynamic temperature and humidity load matching control system for low-carbon building scenarios, including: a parameter acquisition module, a heat and humidity mismatch and condensation margin determination module, a two-dimensional state domain construction module, a heat and humidity coupling state determination module, a low-energy-consumption adjustment combination screening module, and a dynamic iteration module.

[0017] The technical effects and advantages provided by the present invention in the above technical solution are as follows: This invention differs from existing technologies that rely solely on independent adjustments based on indoor temperature and humidity thresholds. It compares the sensible and latent heat demands of the building with the sensible and latent heat handling capabilities of the equipment, forming a sensible and latent heat mismatch coefficient that simultaneously reflects the direction and degree of mismatch. Furthermore, by combining the changes in the building envelope surface temperature, dew point temperature, and continuous condensation temperature difference, a dynamic condensation margin with trend characterization capabilities is obtained, and both are mapped onto a two-dimensional state domain of temperature and humidity load. This not only identifies whether the current sensible and latent heat handling is matched but also whether the thermal and humidity state is approaching the condensation boundary, thus solving the problems of untimely identification of low sensible heat and high latent heat conditions and difficulty in timely detection of localized condensation risks in traditional control systems.

[0018] Building upon this foundation, the present invention further utilizes the target state region to which the current state point belongs and the displacement direction of continuous historical state points to determine the thermal-humidity coupling control state, and accordingly generates multiple candidate adjustment combinations of cooling capacity, dehumidification capacity, fresh air volume, and supply air temperature. Each candidate combination is first subject to dynamic condensation margin safety constraints and sensible-latent heat mismatch convergence direction constraints, and then screened based on the energy consumption of adjusting per unit target load, and continuously updated based on feedback from the actual state point after adjustment. This invention ensures that each adjustment simultaneously considers whether the sensible-latent heat converges towards the matching direction, whether it is far from the risk of condensation, and the energy consumption required to achieve the adjustment. This reduces excessive cooling, repeated dehumidification, heat-cold offsetting, and ineffective adjustment, improving the stability, safety, and energy efficiency of temperature and humidity control in low-carbon buildings. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0020] Figure 1 This is a flowchart of the method of the present invention.

[0021] Figure 2 This is a flowchart of the system modules of the present invention.

[0022] Figure 3 This is a schematic diagram illustrating the determination of building space heat and humidity load and air conditioning equipment processing capacity according to the present invention. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] Example 1, please refer to Figure 1 and Figure 3 As shown in this embodiment, the dynamic temperature and humidity load matching control method for low-carbon building scenarios includes: The indoor temperature, relative humidity, surface temperature of the building envelope, and operating parameters of the air conditioning equipment in the target building space are collected. Based on the indoor temperature and relative humidity, the air moisture content, dew point temperature, sensible heat demand, and latent heat demand are determined. Based on the operating parameters of the air conditioning equipment, the sensible heat treatment capacity and latent heat treatment capacity are determined.

[0025] In this embodiment, information on the thermal and humidity environment of the target building space and the operating status of the air conditioning equipment is first collected. Specifically, temperature and humidity sensors are installed in the target building space to obtain indoor temperature and relative humidity according to a preset sampling period. Surface temperature sensors are installed in the building envelope at locations prone to low surface temperatures, such as walls, windows, beam-column connections, or other locations with thermal bridges, to obtain the surface temperature of the building envelope. Simultaneously, the operating parameters of the air conditioning equipment are read from the air conditioning control system. These operating parameters include one or more of the following: supply air temperature, return air temperature, supply air volume, fresh air volume, chilled water supply and return water temperature, chilled water flow rate, compressor operating frequency, and the operating status of the dehumidifier.

[0026] The collected indoor temperature and relative humidity data are validated and filtered. Based on preset atmospheric pressure parameters and the thermodynamic relationship of moist air, the moisture content and dew point temperature of the air within the target building space are calculated. Moisture content characterizes the actual water vapor content in the air, and dew point temperature characterizes the critical temperature at which condensation occurs. Furthermore, the current indoor temperature and humidity state is compared with the preset target temperature and humidity state. Considering the heat transfer of the building envelope, heat dissipation from personnel and equipment, and the introduction of fresh air, the sensible heat requirement to maintain the target temperature and the latent heat requirement to maintain the target humidity are determined.

[0027] Further, based on the obtained operating parameters of the air conditioning equipment, the air handling status under the current operating conditions of the equipment is determined. By analyzing the temperature difference, humidity difference, and corresponding air mass flow rate between the supply and return air, the sensible heat handling capacity and latent heat handling capacity that the air conditioning equipment can handle per unit time are determined. This provides the current sensible heat demand and latent heat demand of the target building space, as well as the corresponding sensible heat handling capacity and latent heat handling capacity of the air conditioning equipment, providing fundamental data for subsequent calculations of the degree of sensible and latent heat mismatch and assessment of the dynamic matching status of temperature and humidity loads.

[0028] The sensible and latent heat mismatch coefficients are calculated based on the sensible heat demand, latent heat demand, sensible heat treatment capacity, and latent heat treatment capacity, and the dynamic condensation margin is determined based on the difference between the surface temperature of the building envelope and the dew point temperature.

[0029] After obtaining the sensible heat demand, latent heat demand, sensible heat handling capacity, and latent heat handling capacity of the target building space, the sensible and latent heat composition on the demand side and equipment side are determined respectively, and the sensible and latent heat mismatch coefficient is obtained accordingly. Among these, the sensible heat demand... Latent heat demand Sensible heat treatment capability and latent heat treatment capability All values ​​are non-negative values ​​corresponding to the current adjustment direction, so that the demand side and the equipment side can be compared on the same scale of sensible and latent heat composition.

[0030] Specifically, the sensible heat demand With latent heat demand Combining demand-side data pairs, the apparent heat treatment capacity will be considered. With latent heat treatment capability Composition of equipment-side data pairs. For any data pair consisting of sensible heat... and latent heat The data pairs are formed according to... and The ratios are examined in both directions, and the ratio of the smaller quantity to the larger quantity is used as the normalized ratio. .when At that time, if the data pair is determined to be dominated by sensible heat, then the direction indicator is set. and order ;when At that time, it was determined that latent heat was dominant, so that and order ;when When both are greater than zero, it is determined to be in sensible latent heat equilibrium. When one of them is zero and the other is greater than zero, let And according to whether the non-zero quantity belongs to sensible heat or latent heat, let or When both are zero, let By employing the above methods, it is not necessary to use the near-zero heat and moisture content as a divisor, thus avoiding a sudden increase in the unidirectional sensible and latent heat ratio when the sensible or latent heat is close to zero.

[0031] According to the direction signs and normalized ratio Further determine the position values ​​of the corresponding data pairs on the apparent latent heat composition axis: ;in, This indicates that sensible heat and latent heat are in equilibrium or that neither exists. A value approaching 1 indicates that the proportion of sensible heat gradually increases. A value approaching -1 indicates a gradually increasing proportion of latent heat. The demand-side location value is calculated from the demand-side directional indicator and the normalized proportion. The equipment-side position value is calculated from the equipment-side orientation indicator and the normalized scaling value. .

[0032] Compare the equipment-side location values ​​with the demand-side location values, and obtain the sensible latent heat mismatch coefficient according to the following formula: ;in, is the latent heat mismatch coefficient. When... When this occurs, it indicates that the composition of the equipment's current latent heat treatment capacity is consistent with the composition of the building's current latent heat demand; when When, it indicates that the equipment's processing capacity is biased towards sensible heat treatment relative to the building's needs; when When this occurs, it indicates that the equipment's processing capacity is biased towards latent heat treatment relative to the building's needs; This represents the distance between the two components on the axis of sensible and latent heat composition; a larger value indicates a greater degree of mismatch in sensible and latent heat composition. Therefore, the same sensible and latent heat mismatch coefficient can simultaneously characterize the direction and degree of mismatch, and can directly and continuously compare cases where sensible heat dominance and latent heat dominance are on different sides.

[0033] Furthermore, the dynamic condensation margin is determined based on the surface temperature and dew point temperature of the building envelope. When multiple surface temperature collection points exist at the same sampling time, the lowest surface temperature is taken as the effective surface temperature of the building envelope at that time, corresponding to the location with a higher risk of condensation in the current building space. Let the first... The effective surface temperature of the enclosure structure at each sampling time is The corresponding air dew point temperature is Then calculate the condensation temperature difference at that moment: ; in, This indicates the temperature margin between the surface temperature of the building envelope and the current air dew point temperature. This indicates that the surface temperature is higher than the dew point temperature. This indicates that the surface temperature has reached the dew point temperature. This indicates that the surface temperature is below the dew point temperature.

[0034] The condensation temperature difference between the current sampling time and the two previous sampling times is continuously obtained using the same sampling period. and And calculate: ; ; when and If the temperature difference decreases within two consecutive sampling intervals, it indicates that the current state is continuously approaching condensation; otherwise, it indicates that there is no continuous approaching state. Using two consecutive sampling intervals as the basis for judgment can eliminate the possibility of a single sampling fluctuation directly forming a trend judgment, and it also eliminates the need to set an additional manual threshold for the rate of change.

[0035] When continuously approaching a condensation state, the approach intensity is determined based on the actual decrease in the condensation temperature difference between two consecutive sampling intervals: ; The current condensation temperature difference is then asymmetrically compressed toward the condensation risk side to obtain the corrected condensation temperature difference: ; When there is no continuous approximation state, let and order Therefore, the approaching amount formed by the actual rate of decrease is deducted in advance only when the condensation temperature difference decreases continuously, and no reverse expansion is carried out when the condensation temperature difference is stable or increases, so that the margin shrinks faster during the risk deterioration process than during the risk mitigation process.

[0036] Further from and The minimum value is selected as the most unfavorable temperature difference for condensation in the near term. When the current state is continuously approaching condensation, the condensation temperature difference will be corrected. The temperature difference with the most unfavorable condensation recently The smaller value in the range is determined as the dynamic condensation margin. .

[0037] When there is no continuous approach to condensation, the current condensation temperature difference will be... Directly determined as dynamic condensation margin Therefore, the dynamic condensation margin retains the actual distance between the current surface temperature and the dew point temperature, the most unfavorable recent condition, and the rate of temperature difference reduction when the condensation risk continues to worsen. When the condensation risk does not worsen continuously, it restores the current actual condensation safety distance, thus avoiding the long-term participation of historical low temperature differences in the calculation, which would cause the condensation risk to be continuously overestimated.

[0038] The latent heat mismatch coefficient obtained by this invention Dynamic condensation margin is used to characterize the direction and degree of deviation between the composition of building sensible latent heat demand and the composition of equipment sensible latent heat treatment capacity. Used to characterize the current condensation safety distance of the building envelope and its continuous deterioration trend, the two parameters describe the thermal and humidity operation state of the target building space from the load matching direction and the condensation safety direction, respectively, and serve as two input parameters for the subsequent construction of the two-dimensional state domain of temperature and humidity load.

[0039] A two-dimensional state domain of temperature and humidity load is constructed using the apparent latent heat mismatch coefficient and dynamic condensation margin. The target state region to which the current state point belongs is determined, and the direction of state change relative to the boundary of the target state region is determined based on the displacement relationship between the current state point and continuous historical state points.

[0040] Obtain the latent heat mismatch coefficient at the current sampling time. and dynamic condensation margin Subsequently, a two-dimensional state domain for temperature and humidity load was established, using the sensible latent heat mismatch coefficient as the first state dimension and the dynamic condensation margin as the second state dimension. The first state dimension represents the deviation between the building's sensible latent heat demand and the air conditioning equipment's sensible latent heat handling capacity, while the second state dimension represents the condensation safety state of the building envelope surface temperature relative to the air dew point temperature. The state point corresponding to the current sampling time is represented as follows: ; The apparent and latent heat mismatch coefficients and dynamic condensation margins used at each state point correspond to the same sampling time to ensure the consistency of the two state dimensions over time.

[0041] Set latent heat matching boundary along the first state dimension The latent heat matching boundary is determined through normal operating data of the target building. Specifically, during the operating period when indoor temperature and humidity are within the building's design limits and condensation is absent, the latent heat mismatch coefficient is continuously acquired, and the maximum absolute value of the latent heat mismatch coefficient within this operating period is determined as follows: Therefore, when When, the state point is determined to belong to the load matching region in the first state dimension; when At that time, it belongs to the region with a relatively strong sensible heat treatment; when At this point, the load falls within the region of excessive latent heat treatment. By employing the aforementioned inequality, the state points located on both matching boundaries are uniquely assigned to the load matching region.

[0042] Set condensation safety boundaries along the second state dimension Condensation boundary 0. Condensation safety boundary. The value is determined based on the maximum measurement error of the building envelope surface temperature, the maximum calculation error of the dew point temperature, and the maximum sampling fluctuation of the building envelope surface temperature under normal stable operating conditions. Specifically, the three values ​​are added together to obtain the result. The maximum error in surface temperature measurement is determined by the maximum permissible error given by the temperature measuring device within the current measurement range; the maximum error in dew point temperature calculation is determined by the maximum deviation after the temperature and relative humidity measurement errors are passed to the dew point temperature calculation result; the maximum sampling fluctuation of surface temperature is determined by the maximum absolute value of the temperature difference between adjacent surfaces obtained through continuous sampling during stable building operation. Therefore, This indicates the minimum safe distance for condensation that needs to be maintained after excluding measurement errors and normal temperature fluctuations.

[0043] when When, the state point is determined to belong to the condensation safety zone in the second state dimension; when When, it is determined to be the area where condensation is approaching; when When a certain condition is met, it is identified as a condensation risk area. State points on the condensation safety boundary are assigned to the condensation approaching area, while state points on the condensation occurrence boundary are assigned to the condensation risk area, thus ensuring that any dynamic condensation margin corresponds to only one area.

[0044] The load matching region, sensible heat treatment overload region, and latent heat treatment overload region of the first state dimension are cross-combined with the condensation safety region, condensation approach region, and condensation risk region of the second state dimension to form nine non-overlapping state regions. Based on the current state point... of and Based on the aforementioned interval conditions, the unique state region to which the current state point belongs is determined, and this region is designated as the target state region for the current state point. For example, when... and At that time, the target state area is the load-matched and condensation-safe area; when and At that time, the target state area is the area where the sensible heat treatment is strong and condensation is close to occurring.

[0045] Furthermore, to determine the direction of motion of the current state point relative to the boundary of the target state region, historical state points from two consecutive sampling moments preceding the current state point are obtained: as well as ; The changes in the apparent and latent heat mismatch coefficient and the dynamic condensation margin were calculated for two consecutive sampling intervals. ; ; ; ; For the first state dimension, the absolute value of the latent heat mismatch coefficient represents the degree of deviation of the state point from the position where the latent heat is perfectly matched. When two consecutive sampling intervals satisfy... When the first state dimension is determined to move in the load matching direction; when the conditions are continuously met... In the case of a certain condition, the first state dimension is determined to move in the direction of increased load mismatch; in other cases, the first state dimension is determined not to have formed a continuous direction of change.

[0046] For the second state dimension, when and When, the state point is continuously moved away from the condensation risk boundary; when and In the first case, the state point is determined to be continuously oriented towards the condensation risk boundary; in the other cases, the second state dimension is determined not to have formed a continuous direction of change. This avoids instantaneous fluctuations in a single sampling interval from directly changing the direction of state change.

[0047] When both the first and second state dimensions show improvement, the current state point is determined to move towards load matching and condensation safety; when both show deterioration, the current state point is determined to move towards load mismatch and condensation risk. When one state dimension shows improvement and the other shows deterioration, the regional boundary that the current state point preferentially approaches is further determined.

[0048] Specifically, for each approaching boundary, the coordinate distance from the current state point to that boundary is calculated, and the average displacement towards that boundary within the two most recent sampling intervals is also calculated. Dividing the coordinate distance by the average displacement yields the estimated number of sampling steps required to reach the corresponding boundary at the current rate of change. For example, when the dynamic condensation margin continuously decreases, if the current state point is located within the condensation safety zone, then... As the distance to the safe boundary of condensation; if located in the condensation approach area, then... This serves as the distance to the boundary where condensation occurs. For the apparent latent heat mismatch dimension, its distance to the boundary is calculated based on the side where the current state point is located. or The distance.

[0049] When a dimension does not move towards the corresponding boundary or the average displacement of two consecutive sampling intervals in that dimension is 0, the finite expected sampling steps for that boundary are not calculated, and it is considered a boundary that will not be reached first. When there are two or more approaching boundaries, the boundary with the smallest expected sampling steps is determined as the primary approaching boundary of the current state point, and the direction of state change is determined accordingly. Since the boundary distance and the displacement of the corresponding coordinate in each sampling period have the same dimensions, and their ratio represents the expected sampling steps, the boundary arrival results of the apparent latent heat mismatch direction and the condensation margin direction can be directly compared.

[0050] In this invention, each current state point is first uniquely mapped to a target state region in the two-dimensional state domain of temperature and humidity load based on the sensible and latent heat mismatch coefficient and dynamic condensation margin. Then, the changing trends of the sensible and latent heat matching state and the condensation safety state are determined using continuous historical state points. When the changing directions of the two state dimensions are inconsistent, the main state change direction is determined by comparing the number of sampling steps required to reach the boundaries of different regions. The target state region and the state change direction obtained in this way serve as inputs for subsequent determination of the temperature and humidity coupling control state, so that subsequent adjustments not only consider the current temperature and humidity state, but also whether the state is trending towards improvement or approaching the boundary of an unfavorable region.

[0051] The thermal-humidity coupling control state is determined based on the target state region and the direction of state change, and at least two candidate adjustment combinations including cooling capacity, dehumidification capacity, fresh air volume and supply air temperature are generated based on the thermal-humidity coupling control state.

[0052] After determining the target state region and the direction of state change corresponding to the current state point, the thermo-humidity coupling control state is determined based on the combination relationship between the two. The thermo-humidity coupling control state is used to characterize whether, during the current adjustment process, priority should be given to reducing sensible heat treatment deviation, reducing latent heat treatment deviation, increasing condensation safety margin, or maintaining the existing thermo-humidity treatment relationship. The determination result is directly used to generate subsequent candidate adjustment combinations.

[0053] Specifically, when the target state region is located in the load matching region and the condensation safety region, and the direction of state change is not towards the load mismatch boundary or the condensation risk boundary, it is determined to be a matching maintenance state; when the target state region is located in the sensible heat treatment overload region, it is determined to be a sensible heat treatment reduction state; when the target state region is located in the latent heat treatment overload region, it is determined to be a latent heat treatment reduction state. When the current state point is located in the condensation approach region or the condensation risk region, regardless of whether it belongs to the load matching, sensible heat treatment overload, or latent heat treatment overload in the first state dimension, improving the dynamic condensation margin will be the priority adjustment target, and on this basis, the corresponding sensible and latent heat mismatch correction direction will be retained, thereby forming a condensation priority-sensible heat correction state, a condensation priority-latent heat correction state, or a condensation priority-match maintenance state, respectively.

[0054] For cases where the target state region is the same but the direction of state change differs, the direction of state change is further used to correct the thermo-humidity coupling control state. When the state point moves towards the load matching and condensation safety direction, the current thermo-humidity coupling control state determined by the target state region is maintained; when the state point moves towards the main unfavorable boundary, the adjustment target corresponding to the main unfavorable boundary is elevated to the priority target. For example, if the current state point is located in the region with strong sensible heat treatment and condensation safety, but its main approach boundary is the condensation safety boundary, the thermo-humidity coupling control state is adjusted from a simple sensible heat treatment reduction state to a condensation priority-sensible heat correction state; if the current state point is located in the load matching region, but the dynamic condensation margin continuously decreases and approaches the condensation occurrence boundary with the minimum expected sampling steps, it is determined to be a condensation priority-matching maintenance state. Thus, the target state region is used to characterize the current thermo-humidity state, while the direction of state change is used to correct the current adjustment priority relationship.

[0055] After obtaining the thermo-humidity coupling control state, the cooling capacity, dehumidification capacity, fresh air volume, and supply air temperature at the current sampling time are used as the baseline operating parameters, and candidate adjustment combinations are generated around the adjustment target corresponding to the thermo-humidity coupling control state. Each candidate adjustment combination includes a set of determined cooling capacity, dehumidification capacity, fresh air volume, and supply air temperature, and each parameter is unidirectionally increased, unidirectionally decreased, or kept unchanged starting from the current operating value, so that the candidate adjustment combination is consistent with the adjustment direction corresponding to the current thermo-humidity coupling control state.

[0056] When the sensible heat treatment is reduced, the candidate adjustment combinations include at least: a first candidate adjustment combination, which reduces the cooling capacity while maintaining the dehumidification capacity, and correspondingly increases the supply air temperature; and a second candidate adjustment combination, which adjusts the fresh air volume and dehumidification capacity while maintaining the cooling capacity, thereby increasing the latent heat treatment capacity relative to the sensible heat treatment capacity. These two candidate adjustment combinations alter the sensible and latent heat composition on the equipment side by weakening the sensible heat treatment intensity and increasing the latent heat treatment proportion, respectively, to bring the equipment-side position value closer to the demand-side position value.

[0057] When the latent heat treatment is reduced, the candidate adjustment combinations include at least: a first candidate adjustment combination, which reduces the dehumidification capacity while maintaining the cooling capacity; and a second candidate adjustment combination, which adjusts the fresh air volume and reduces the supply air temperature without increasing the dehumidification capacity, thereby increasing the sensible heat treatment capacity relative to the latent heat treatment capacity. This shifts the sensible latent heat composition on the equipment side towards the sensible latent heat composition on the building demand side.

[0058] When condensation is prioritized, the generation of candidate adjustment combinations first satisfies the adjustment direction of increasing the safe distance between the surface temperature of the building envelope and the dew point temperature. At least one set of candidate adjustment combinations is generated that reduces the surface temperature drop by increasing the supply air temperature and limiting the cooling capacity, and another set of candidate adjustment combinations is generated that reduces the air humidity by adjusting the dehumidification and fresh air volume, thereby lowering the dew point temperature. If there is currently an imbalance between sensible heat treatment and latent heat treatment, the parameter change direction is further restricted in the above two types of candidate adjustment combinations, so that the adjusted sensible and latent heat composition on the equipment side simultaneously approaches the sensible and latent heat composition on the demand side, rather than adopting a parameter change direction that would further amplify the absolute value of the sensible and latent heat mismatch coefficient.

[0059] The parameter variation range in each candidate adjustment combination is based on the minimum adjustable step size allowed by the equipment within the current sampling period, and at least one candidate result with different adjustment paths is generated for each combination. When a parameter has reached the upper or lower limit of the equipment's allowed operating range, no further candidate values ​​are generated in directions exceeding that range. This results in at least two sets of candidate adjustment combinations that meet the current thermal-humidity coupling control requirements and have different parameter combination relationships.

[0060] Calculate the unit target load regulation energy consumption corresponding to each candidate regulation combination. Among the candidate regulation combinations that meet the dynamic condensation margin safety constraints and the convergence direction constraints of sensible and latent heat mismatch, select the target regulation combination with the lowest unit target load regulation energy consumption, and control the operation of the air conditioning equipment according to the target regulation combination.

[0061] In this embodiment, after obtaining at least two candidate control combinations, each candidate control combination is evaluated for condensation safety, sensible and latent heat matching convergence, and load control energy consumption. The target control combination is then determined from the candidate control combinations that meet the constraints. The evaluation of each candidate control combination uses the same control cycle as the time reference to ensure the comparability of energy consumption and load control effects between different combinations.

[0062] Specifically, for the first For each candidate control combination, based on the determined cooling capacity, dehumidification capacity, fresh air volume, and supply air temperature, combined with the current return air temperature, return air humidity, and current airflow, the candidate sensible heat treatment capacity that the candidate control combination can achieve in the next control cycle is determined. and candidate latent heat treatment capabilities The candidate sensible heat treatment capacity is determined based on the temperature difference between the candidate supply air temperature and the current indoor temperature, and the corresponding air mass flow rate. The candidate latent heat treatment capacity is determined based on the difference between the candidate supply air humidity and the current indoor air humidity, and the corresponding air mass flow rate. The candidate supply air humidity is determined based on the air treatment results corresponding to the candidate dehumidification capacity and the candidate fresh air volume. This allows each candidate adjustment combination to be converted into sensible heat treatment capacity and latent heat treatment capacity with the same dimensions as the aforementioned sensible heat demand and latent heat demand.

[0063] Subsequently, the candidate's heat treatment capability was assessed. and candidate latent heat treatment capabilities Following the same calculation process as the aforementioned latent heat mismatch coefficient, the first... Candidate latent heat mismatch coefficients corresponding to the candidate adjustment combinations When the current state point is located in the region of strong sensible heat treatment or strong latent heat treatment, if the following conditions are met... Then the candidate adjustment combination is determined to satisfy the convergence direction constraint of apparent and latent heat mismatch; when the current state point is already in the load matching region, i.e. If the candidate latent heat mismatch coefficient still satisfies If the latent heat mismatch convergence direction constraint is satisfied, then the candidate adjustment result is required to move towards the latent heat matching position when there is a significant mismatch. If the allowable matching range has been reached, the latent heat mismatch caused by energy-saving adjustment is avoided.

[0064] Furthermore, dynamic condensation margin safety constraints are determined for each candidate control combination. The direction of change in the building envelope surface temperature within the next control cycle is determined based on the candidate supply air temperature, candidate cooling capacity, and candidate fresh air volume. The change in indoor air humidity is determined based on the candidate dehumidification capacity and candidate fresh air volume. The candidate dew point temperature is then determined from the changed air temperature and humidity state. Finally, following the aforementioned dynamic condensation margin calculation method, the [number of cycles] is obtained. Candidate dynamic condensation margin corresponding to the candidate adjustment combination .

[0065] When the current dynamic condensation margin meets That is, when the current condensation safety zone is reached, the candidate dynamic condensation margin is required to meet the following conditions. ; to prevent candidate adjustment actions from causing the state point to cross into the condensation approach region; when the current dynamic condensation margin meets When the area is already in the condensation approach zone or condensation risk zone, then it is required that... ; In other words, the candidate adjustment combination should be able to increase the dynamic condensation margin at least once. By adopting two types of constraints corresponding to the current condensation state, it is possible to avoid the situation where there are no alternative adjustment combinations when the current situation is already in an unfavorable region, as a single control cycle is required to immediately return to the condensation safety region. At the same time, it is ensured that the selected adjustment direction will not further aggravate the condensation risk.

[0066] After applying dynamic condensation margin safety constraints and sensible-latent heat mismatch convergence direction constraints, the unit target load regulation energy consumption of the candidate regulation combinations is further calculated. First, the total energy consumption of the candidate regulation combination is determined based on the input power of each device within one control cycle: ;in, Indicates the first Energy consumption of a candidate control combination within one control cycle. This represents the total input power related to cooling, dehumidification, and air supply when operating according to this candidate control combination. This indicates the duration of the current control cycle.

[0067] Then, the target load adjustment amount is determined based on the current thermal-humidity coupling control state. When the sensible heat treatment reduction state or the latent heat treatment reduction state is in effect, the improvement of the candidate sensible and latent heat mismatch coefficient relative to the current sensible and latent heat mismatch coefficient is used to characterize the effective target adjustment degree, and the candidate target load adjustment amount is obtained by combining the total current sensible heat demand and latent heat demand: ; in, This indicates that the candidate control combination is the effective target load control amount used to correct the mismatch between sensible and latent heat, and is only applicable to loads that meet the following conditions. The above calculations are performed on the candidate combinations.

[0068] When the thermal-humidity coupling control state is in the condensation-priority state, the improvement in the candidate dynamic condensation margin relative to the current dynamic condensation margin is used as the condensation safety improvement amount, and the improvement amount of sensible and latent heat mismatch is used as an additional contribution. In this case, priority is given to candidate combinations that satisfy... The effective target load adjustment amount is determined by the latent heat reduction or surface cooling reduction amount that can be achieved under the conditions, so that the target load adjustment amount corresponds to the load direction that actually needs to be addressed first in the current heat and humidity coupling control state, without including the cooling or dehumidification output that is unrelated to the current adjustment target in the effective adjustment amount.

[0069] The energy consumption per unit target load is calculated by comparing the total energy consumption of the candidate regulation combination with its effective target load regulation amount. ; in, This represents the energy consumed to achieve a unit effective target load adjustment; under the same security and convergence constraints, The smaller the value, the lower the energy consumption required for the current temperature and humidity load correction among the candidate control combinations. Candidate combinations with zero effective target load control are not included in the comparison of energy consumption per unit target load control, in order to avoid selecting operating modes with no actual control contribution.

[0070] Finally, from the candidate regulation combinations that simultaneously satisfy the dynamic condensation margin safety constraint and the convergence direction constraint of sensible and latent heat mismatch, and whose effective target load adjustment is greater than zero, their unit target load adjustment energy consumption is compared, and the candidate regulation combination with the minimum unit target load adjustment energy consumption is determined as the target regulation combination. When there are two or more candidate regulation combinations with the same unit target load adjustment energy consumption, the combination with the larger candidate dynamic condensation margin is selected first; if the candidate dynamic condensation margins are still the same, the combination with the smaller absolute value of the candidate sensible and latent heat mismatch coefficient is selected to ensure that the target regulation combination can be uniquely determined.

[0071] After determining the target control combination, the current operating parameters of the air conditioning equipment are adjusted according to the corresponding cooling capacity, dehumidification capacity, fresh air volume, and supply air temperature in the target control combination. The indoor temperature and humidity status and equipment operating status are then re-acquired in the next control cycle. This process ensures that candidate control combinations are first screened for condensation safety and sensible latent heat convergence, and then the energy consumption per unit target load is used as the basis for low-carbon operation evaluation. Thus, while ensuring that the thermal and humidity conditions change towards a safe matching direction, the actual control scheme with lower energy consumption is selected.

[0072] The adjusted latent heat mismatch coefficient and dynamic condensation margin are obtained. The state points in the two-dimensional state domain are updated according to the adjusted latent heat mismatch coefficient and dynamic condensation margin. When the state point does not enter the preset matching safety area, the thermal-humidity coupling control state and target adjustment combination are re-determined until the state point enters the preset matching safety area.

[0073] After the target control combination has completed one control cycle according to the corresponding cooling capacity, dehumidification capacity, fresh air volume, and supply air temperature, the indoor temperature, relative humidity, building envelope surface temperature, and air conditioning equipment operating parameters are re-acquired using the same sampling method as before the control. Then, following the aforementioned calculation process for the sensible latent heat mismatch coefficient and dynamic condensation margin, the controlled sensible latent heat mismatch coefficient is obtained. and dynamic condensation margin The parameters before and after adjustment use the same sampling period, the same parameter definition, and the same calculation rules, so that the state parameters obtained from different control cycles can be directly compared.

[0074] Using the adjusted latent heat mismatch coefficient as the first coordinate and the adjusted dynamic condensation margin as the second coordinate, candidate update state points are formed: ; The candidate updated state point represents the actual thermal and humidity state of the target building space after one control cycle of the target adjustment combination. This is based on the state point before adjustment. The coordinate difference between the candidate updated state point and the apparent latent heat dimension displacement and the condensation dimension displacement are calculated: ; ; in, This indicates the change in the composition of the equipment's latent heat treatment relative to the composition of the building's latent heat demand within a control cycle. This indicates the change in condensation safety margin within the same control cycle.

[0075] To eliminate the influence of the different numerical ranges of the latent heat mismatch coefficient and the dynamic condensation margin on the determination of the migration direction, the two displacements are normalized according to the distance from the state point before adjustment to the boundary corresponding to the current adjustment target.

[0076] For the apparent and latent heat dimensions, when At this point, the current state is in the region of excessive sensible heat treatment, and its goal is to enter the load matching region. Therefore, the following is taken: ; when At that time, the current state is in the region of strong latent heat treatment, so we take: ; when At this point, the current latent heat state is already within the allowable matching range, and entering the matching region is no longer the migration goal; instead, a different approach is adopted. This serves as the normalization baseline for that dimension.

[0077] Regarding the condensation dimension, when At that time, the current state is within the safe condensation zone. This indicates the distance of the state point from the condensation safety boundary; when At that time, the current adjustment objective is to increase the dynamic condensation margin until it re-enters the condensation safety zone, in order to This indicates the distance of the state point from the condensation safety boundary. If the state point is exactly located at... Then adopt As a normalization benchmark value.

[0078] The and The boundary values ​​of the aforementioned two-dimensional state domain of temperature and humidity load are all adopted, where , Therefore, no new judgment threshold is introduced. When the boundary distance obtained in the above manner is zero, the following methods are used respectively: or This serves as the corresponding normalization benchmark to avoid division by zero.

[0079] Based on the obtained normalized benchmark, calculate: ; ; And by and Construct the state transition vector: ; The two components of the state transition vector represent the relative migration amounts generated by the target regulation combination for the apparent latent heat matching state and the condensation safety state within a control cycle.

[0080] Further, the expected safety matching direction is determined based on the target state region before adjustment and the direction of state change. Specifically, when At that time, the expected directional quantity of the apparent and latent heat dimensions is denoted as This indicates a need to reduce the deviation on the sensible heat side; when When, the directional quantity is denoted as This indicates a need to reduce the latent heat side deviation; when When this is the case, the directional quantity is recorded as 0, indicating that the dimension is constrained to remain within the load matching region.

[0081] when At that time, the expected direction quantity of the condensation dimension is denoted as This indicates a need to increase dynamic condensation margin; when When this direction variable is set to 0, it indicates that the dimension is constrained to remain within the condensation safety zone. The two desired direction variables are then combined to form the expected safety matching direction vector. When both direction variables are non-zero, the direction vector is normalized; when only one direction variable is non-zero, that non-zero direction is directly used as the expected safe matching direction.

[0082] Since the aforementioned thermo-humidity coupling control state has been determined based on the target state region and the direction of state change before adjustment, the expected safety matching direction corresponds to the migration direction that should be achieved after correcting the original state change trend. For example, when the original state continuously moves towards the condensation risk boundary, the expected direction after the target adjustment combination is executed is an increase in dynamic condensation margin, rather than continuing to move along the original deterioration direction.

[0083] Calculate the projection decision value of the state transition vector onto the expected safe-matching direction: ; when When, it indicates that the candidate update state points migrate as a whole along the safe matching direction of the current thermal and humidity control requirements; when When this occurs, it indicates that the target adjustment combination has not produced an effective migration consistent with the expected safety matching direction.

[0084] for The candidate update state points are further evaluated to determine whether a state dimension that already met the requirements has crossed the corresponding safe zone due to this adjustment. If the requirements were met before the adjustment... At that time, the following requirements must still be met after adjustment: ; When the condition before adjustment is satisfied At that time, the following requirements must still be met after adjustment: ; Only when Furthermore, if the state dimension that already meets the requirements does not exceed the corresponding region, the migration is determined to be a valid and safe migration. This judgment is used to prevent sacrificing another state dimension that already meets the requirements by significantly improving one state dimension.

[0085] Regardless of whether the migration results meet expectations, the state points in the two-dimensional state domain are all obtained from actual data collection and calculation. Update the data, but do not use predicted values ​​or pre-adjustment state points to replace actual results. When the migration meets the above-mentioned valid safe migration conditions, [the data will be updated]. This is recorded as a normal update state point; when , or although However, when this causes the state dimension that originally met the requirements to exceed the corresponding region, it will... This is denoted as the reverse migration state point. The reverse migration state point only indicates that the previous target adjustment combination failed to improve the actual thermal and humidity conditions as required, and its coordinates are still the actual state parameters after the end of this control cycle.

[0086] After the status point update is completed, it is determined whether the updated status point enters the preset matching safety region. The preset matching safety region is directly determined by the aforementioned load matching boundary and condensation safety boundary, i.e., it simultaneously satisfies: as well as At that time, the updated status point is determined to enter the preset matching safe zone. Because... This is derived from the allowable range of sensible and latent heat mismatch fluctuations under normal building conditions. The safe distance required to be maintained is due to errors in surface temperature measurement, dew point temperature calculation, and normal surface temperature fluctuations.

[0087] When the updated status point does not enter the preset matching safe area, As the current state point for the next control cycle, together with the two previous actual state points, the target state region and the direction of state change are redefined. Then, based on the redefined target state region and the direction of state change, a new thermo-humidity coupling control state is determined, candidate adjustment combinations are generated, and the target adjustment combination is re-screened.

[0088] When the updated state point is determined to be a reverse migration state point, the thermal-humidity coupling control state and target adjustment combination corresponding to the previous control cycle are not continued to be used. Instead, the above state judgment and adjustment combination determination process is directly re-executed based on the reverse migration state point and its historical state points, thereby avoiding the continuous use of parameter combinations that have been proven by actual operation results to have unfavorable migration directions.

[0089] When the updated state point enters the preset matching safety zone, the current round of continuous adjustment aimed at correcting sensible and latent heat mismatch and condensation risk is stopped, and the current operating parameters are maintained; thereafter, the sensible and latent heat mismatch coefficient and dynamic condensation margin are obtained according to the original sampling cycle. When any subsequent state point no longer simultaneously meets the requirements... and When that point is reached, the target state region determination and subsequent adjustment process restarts from that state point.

[0090] This invention no longer uses indoor temperature and humidity exceeding limits as the basis for air conditioning adjustment. Instead, it constructs joint evaluation parameters from two aspects: whether the building's sensible latent heat demand matches the equipment's sensible latent heat handling capacity, and whether the building envelope is close to the risk of condensation. It maps the sensible latent heat mismatch coefficient and dynamic condensation margin into a two-dimensional state domain, and judges whether the current thermal and humidity state tends to improve or deteriorate by combining the historical migration direction of the state points. Based on this, it determines the thermal and humidity coupling control state, generates multiple sets of cooling, dehumidification, fresh air and supply air temperature adjustment schemes, and then selects target schemes with condensation safety, sensible latent heat convergence and unit target load adjustment energy consumption as constraints. It updates and iterates again according to the actual adjusted state, thereby achieving dynamic coordination and matching between temperature and humidity load, condensation safety and low energy consumption operation.

[0091] Example 2, please refer to Figure 2 As shown in this embodiment, the dynamic temperature and humidity load matching control system for low-carbon building scenarios includes: The parameter acquisition module collects indoor temperature, relative humidity, building envelope surface temperature, and air conditioning equipment operating parameters of the target building space. Based on the indoor temperature and relative humidity, it determines the air moisture content, dew point temperature, sensible heat demand, and latent heat demand. Based on the air conditioning equipment operating parameters, it determines the sensible heat treatment capacity and latent heat treatment capacity. The heat and moisture mismatch and condensation margin determination module calculates the sensible and latent heat mismatch coefficients based on the sensible heat demand, latent heat demand, sensible heat treatment capacity, and latent heat treatment capacity, and determines the dynamic condensation margin based on the difference between the surface temperature of the building envelope and the dew point temperature. The two-dimensional state domain construction module constructs a two-dimensional state domain of temperature and humidity load using the apparent latent heat mismatch coefficient and dynamic condensation margin, determines the target state region to which the current state point belongs, and determines the state change direction relative to the boundary of the target state region based on the displacement relationship between the current state point and continuous historical state points. The thermal-humidity coupling state determination module determines the thermal-humidity coupling control state based on the target state region and the direction of state change, and generates at least two sets of candidate adjustment combinations including cooling capacity, dehumidification capacity, fresh air volume and supply air temperature based on the thermal-humidity coupling control state. The low-energy-consumption regulation combination screening module calculates the unit target load regulation energy consumption corresponding to each candidate regulation combination. Among the candidate regulation combinations that meet the dynamic condensation margin safety constraints and the convergence direction constraints of sensible and latent heat mismatch, the target regulation combination with the lowest unit target load regulation energy consumption is selected, and the air conditioning equipment is controlled to operate according to the target regulation combination. The dynamic iteration module obtains the adjusted latent heat mismatch coefficient and dynamic condensation margin, updates the state point in the two-dimensional state domain according to the adjusted latent heat mismatch coefficient and dynamic condensation margin, and re-determines the thermal-humidity coupling control state and target adjustment combination when the state point does not enter the preset matching safety area, until the state point enters the preset matching safety area.

[0092] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A dynamic temperature and humidity load matching control method for low-carbon building scenarios, characterized in that, include: The indoor temperature, relative humidity, surface temperature of the building envelope, and operating parameters of the air conditioning equipment in the target building space are collected. Based on the indoor temperature and relative humidity, the air moisture content, dew point temperature, sensible heat demand, and latent heat demand are determined. Based on the operating parameters of the air conditioning equipment, the sensible heat treatment capacity and latent heat treatment capacity are determined. The sensible and latent heat mismatch coefficients are calculated based on the sensible heat demand, latent heat demand, sensible heat treatment capacity, and latent heat treatment capacity, and the dynamic condensation margin is determined based on the difference between the surface temperature of the building envelope and the dew point temperature. A two-dimensional state domain of temperature and humidity load is constructed using the apparent latent heat mismatch coefficient and dynamic condensation margin. The target state region to which the current state point belongs is determined, and the direction of state change relative to the boundary of the target state region is determined based on the displacement relationship between the current state point and continuous historical state points. The thermal-humidity coupling control state is determined based on the target state region and the direction of state change, and at least two candidate adjustment combinations including cooling capacity, dehumidification capacity, fresh air volume and supply air temperature are generated based on the thermal-humidity coupling control state. Calculate the unit target load regulation energy consumption corresponding to each candidate regulation combination. Among the candidate regulation combinations that meet the dynamic condensation margin safety constraints and the convergence direction constraints of sensible and latent heat mismatch, select the target regulation combination with the lowest unit target load regulation energy consumption, and control the operation of the air conditioning equipment according to the target regulation combination. The adjusted latent heat mismatch coefficient and dynamic condensation margin are obtained. The state points in the two-dimensional state domain are updated according to the adjusted latent heat mismatch coefficient and dynamic condensation margin. When the state point does not enter the preset matching safety area, the thermal-humidity coupling control state and target adjustment combination are re-determined until the state point enters the preset matching safety area.

2. The dynamic temperature and humidity load matching control method for low-carbon building scenarios according to claim 1, characterized in that, The determination of the apparent latent heat mismatch coefficient includes: Sensible heat demand and latent heat demand are combined into demand-side data pairs, and sensible heat processing capacity and latent heat processing capacity are combined into equipment-side data pairs. The sensible heat and latent heat in each data pair are compared to determine the normalized ratio value. Based on the heat type of the larger quantity, a directional indicator is assigned: sensible heat dominance, latent heat dominance, or sensible and latent heat balance. The demand-side position value and equipment-side position value are determined according to the directional indicator and the normalized ratio value, so that sensible heat dominance corresponds to a positive position and latent heat dominance corresponds to a negative position. The difference between the equipment-side position value and the demand-side position value is calculated to obtain the sensible and latent heat mismatch coefficient.

3. The method according to claim 2, characterized in that, Determining dynamic condensation margin includes: When multiple building envelope surface temperatures exist at the same sampling time, the lowest value is selected as the effective building envelope surface temperature, and the condensation temperature difference between the effective building envelope surface temperature and the corresponding dew point temperature is calculated. The condensation temperature difference at the current sampling time and the previous two sampling times is obtained. When the condensation temperature difference in two consecutive sampling intervals decreases, the approach intensity is determined based on the average of the actual decrease in the two sampling intervals, and the approach intensity is subtracted from the current condensation temperature difference to obtain the corrected condensation temperature difference. The minimum condensation temperature difference is obtained from the condensation temperature differences at three consecutive sampling times, and the smaller of the corrected condensation temperature difference and the minimum condensation temperature difference is selected as the dynamic condensation margin when the continuous approaching condensation state is not present. When there is no continuous approaching state, the current condensation temperature difference is used as the dynamic condensation margin.

4. The method according to claim 3, characterized in that, The determination of the two-dimensional state domain and the direction of state change under temperature and humidity load includes: Using the latent heat mismatch coefficient as the first state dimension and the dynamic condensation margin as the second state dimension, the two-dimensional state domain is divided into multiple state regions formed by the intersection of load matching, strong sensible heat treatment, strong latent heat treatment and condensation safety, condensation approach, and condensation risk, respectively, based on the sensible heat matching boundary, condensation safety boundary, and condensation occurrence boundary. The current state point and its unique target state region are determined according to the current sensible heat mismatch coefficient and dynamic condensation margin. Two consecutive historical state points before the current state point are obtained, and the change direction of the absolute value of sensible heat mismatch and dynamic condensation margin in the continuous sampling interval are determined. When the change directions of the two state dimensions are inconsistent, the ratio of the distance from the current state point to the boundary of the approaching region to the corresponding average displacement is calculated, and the boundary with the smallest expected sampling steps is determined as the main approaching boundary, and the state change direction is determined accordingly.

5. The method according to claim 4, characterized in that, The determination of the thermal-humidity coupling control state and candidate adjustment combinations includes: Based on the target state region, determine the basic adjustment direction of sensible heat treatment reduction, latent heat treatment reduction, matching maintenance, or condensation priority, and determine whether the current state is approaching the load mismatch boundary or condensation risk boundary based on the state change direction; when the state point moves towards the unfavorable boundary, the adjustment target corresponding to the main approach boundary is promoted to the priority adjustment target, thereby determining the heat and humidity coupling control state; using the current cooling capacity, dehumidification capacity, fresh air volume, and supply air temperature as reference parameters, define the increase, decrease, or maintenance direction of each parameter according to the heat and humidity coupling control state, forming at least two different parameter adjustment paths, and making the sensible and latent heat composition on the equipment side corresponding to each adjustment path move closer to the sensible and latent heat composition on the demand side or make the dynamic condensation margin change in the direction of increasing, thereby obtaining candidate adjustment combinations.

6. The method according to claim 1, characterized in that, The determination of sensible heat demand, latent heat demand, sensible heat treatment capacity, and latent heat treatment capacity includes: determining sensible heat demand and latent heat demand based on indoor temperature, relative humidity, and target temperature and humidity conditions, combined with heat transfer of the building envelope, heat dissipation and moisture dissipation of personnel and equipment, and fresh air introduction; and determining sensible heat treatment capacity and latent heat treatment capacity based on the supply and return air temperature difference, humidity difference, and air mass flow rate.

7. The method according to claim 4, characterized in that, The latent heat matching boundary is determined based on the maximum absolute value of the latent heat mismatch coefficient collected when the indoor temperature and humidity are within the design allowable range and there is no condensation. The condensation safety boundary is determined based on the sum of the maximum error in the surface temperature measurement of the building envelope, the maximum error in the dew point temperature calculation, and the maximum sampling fluctuation of the surface temperature during stable operation.

8. The method according to claim 5, characterized in that, The determination of the target regulation combination includes: obtaining the candidate latent heat mismatch coefficient and candidate dynamic condensation margin for each candidate regulation combination; eliminating candidate regulation combinations that cannot bring the latent heat mismatch to the matching region or cannot maintain or improve the condensation safety margin; determining the unit target load regulation energy consumption among the remaining candidate regulation combinations based on the ratio of the total energy consumption of one control cycle to the effective target load regulation amount; and selecting the candidate regulation combination with the lowest unit target load regulation energy consumption as the target regulation combination.

9. The method according to claim 8, characterized in that, The state point update in the two-dimensional state domain includes: after the target adjustment combination executes a control cycle, the apparent latent heat mismatch coefficient and dynamic condensation margin are re-obtained to form an updated state point; the displacement of the state point before and after adjustment is used to determine whether it has migrated along the safe matching direction; and when the updated state point does not simultaneously satisfy the apparent latent heat matching boundary and the condensation safety boundary, the updated state point is used as the current state point of the next control cycle to redetermine the thermal-humidity coupling control state and the target adjustment combination.

10. A dynamic temperature and humidity load matching control system for low-carbon building scenarios, used to implement the dynamic temperature and humidity load matching control method for low-carbon building scenarios as described in any one of claims 1-9, characterized in that, include: The system includes a parameter acquisition module, a heat and humidity mismatch and condensation margin determination module, a two-dimensional state domain construction module, a heat and humidity coupling state determination module, a low-energy-consumption regulation combination screening module, and a dynamic iteration module.

Images