A dual variable energy saving control system and method for constant temperature and humidity environment

Abstract

The application discloses a kind of dual-variable energy-saving control system and method for constant temperature and humidity environment, it is related to environmental regulation technical field, by the temperature influence priority score value Tsc and humidity influence priority score value Hsc contained in the dual-variable influence score set Sco, control priority can be judged based on actual state, generate control order mark Tag, make control order no longer rely on fixed logic, but have real-time and response adaptability, control response data set Crs is constructed by collecting control action feedback parameter Fbk, and control stability score value Sta and control adjustment energy consumption score value Pow are calculated accordingly, compared with the last cycle result to form optimization path, realize the continuous learning and precision evolution of control behavior in the energy saving and stability two dimensions, significantly improve the secondary disturbance problem caused by variable independent control, realize the systematic optimization of control energy saving, response efficiency and system stability.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of environmental regulation, in particular to a dual-variable energy-saving control system and method for constant temperature and humidity environment. BACKGROUND

[0002] Constant temperature and humidity environment control systems are widely used in places such as museums, cultural relic storage rooms, biological laboratories, electronic component production workshops, and dried fruit cold storage rooms, etc. These scenarios have strict requirements for temperature and humidity fluctuations of air. In such occasions, any slight temperature and humidity changes may cause problems such as deterioration of goods, device failure, and data distortion. Therefore, in order to reduce energy consumption and improve control stability and precision, it is urgent to propose an energy-saving control mechanism that integrates multiple parameters for constant temperature and humidity environment.

[0003] In the traditional implementation of the constant temperature and humidity control system, the control process of temperature and humidity often adopts separate sequential control logic, that is, the system sets a main control variable, such as temperature, first, and then adjusts the humidity after it is stable. Although this control strategy is simple in structure and easy to implement, it cannot adapt to the coupling characteristics between temperature and humidity variables. In fact, temperature control actions, such as refrigeration and heating, will directly or indirectly affect the humidity level of indoor air, while humidity control actions, such as dehumidification or humidification, may also change the enthalpy of air, thereby affecting the temperature in turn.

[0004] Since the existing system usually does not consider the real-time offset degree between temperature and humidity variables and their cross-response influence, the following situations frequently occur during system operation: temperature is controlled first and then humidity, resulting in that temperature adjustment is just completed, and humidity adjustment causes temperature rebound; or humidity is just controlled stable, and temperature control deviates humidity, forming control reciprocation, adjustment redundancy, and frequent start-stop of devices, etc. This not only increases energy consumption, but also affects the stability of environmental parameters and reduces system efficiency. SUMMARY

[0005] In view of the deficiencies of the prior art, the present application provides a dual-variable energy-saving control system and method for constant temperature and humidity environment, which solves the problems mentioned in the background art.

[0006] To achieve the above purpose, the present application is implemented by the following technical scheme: a dual-variable energy-saving control method for constant temperature and humidity environment, comprising the following steps:

[0007] S1, collecting temperature and humidity change information of a target control space in real time through an environmental sensing unit, and analyzing and obtaining temperature variation influence trend parameter Thi and humidity variation influence trend parameter Hti to form an environmental change parameter set Env;

[0008] S2, constructing a temperature and humidity coupling cross-influence scoring model based on the environmental change parameter set Env, calculating a temperature influence priority scoring value Tsc and a humidity influence priority scoring value Hsc, and forming a bivariate influence scoring set Sco;

[0009] S3, comparing the relative strength of the temperature influence priority scoring value Tsc and the humidity influence priority scoring value Hsc based on the bivariate influence scoring set Sco, and generating a control sorting tag Tag;

[0010] S4, according to the control sorting tag Tag, starting the corresponding priority regulation channel, and recording the feedback parameter Fbk of the current regulation channel control action impact to form a control response data set Crs;

[0011] S5, based on the control response data set Crs, calculating a control stability scoring value Sta and a control adjustment energy consumption scoring value Pow, and comparing with the previous cycle scoring value for optimization.

[0012] Preferably, the S1 includes S11 and S12;

[0013] S11, continuously monitoring the temperature and humidity changes of the space environment by a composite temperature and humidity sensor device arranged in the target control space, and obtaining the temperature and humidity change information of the target control space;

[0014] The composite temperature and humidity sensor device includes a temperature detection module for detecting temperature changes in the ambient air, and a humidity detection module for detecting relative humidity changes in the ambient air.

[0015] The temperature and humidity change information includes a temperature change rate parameter Temp, a humidity change rate parameter Hum, a current temperature offset rate parameter Tof, and a current humidity offset rate parameter Hof.

[0016] The temperature change rate parameter Temp and the humidity change rate parameter Hum are respectively calculated from the change amount between the current detection value and the detection value at the last time combined with the time interval.

[0017] The current temperature offset rate parameter Tof and the current humidity offset rate parameter Hof respectively represent the relative deviation percentage of the current temperature and humidity value relative to the preset target value.

[0018] The temperature and humidity change information is transmitted and communicated through a bus type local area connection structure or a wireless low power consumption communication protocol.

[0019] Preferably, S12 analyzes and processes the interaction between the temperature and humidity changes based on the acquired temperature and humidity change information, obtains a temperature variation influence on humidity trend parameter Thi and a humidity variation influence on temperature trend parameter Hti, and integrates the temperature and humidity change information to form an environment change parameter set Env;

[0020] The analysis and processing includes steps S121 and S122.

[0021] S121, calls the cached temperature and humidity change information record data in the historical running period, extracts the temperature and humidity change trajectories of consecutive multiple periods, and constructs the temperature and humidity response sequence in the adjacent period based on the sliding window method to form a historical variable sample set for coupling analysis.

[0022] S122, uses the temperature change value sequence and the humidity response change value sequence in the historical variable sample set to perform trend modeling calculation through a linear fitting model to generate the temperature variation influence on humidity trend parameter Thi and the humidity variation influence on temperature trend parameter Hti, respectively.

[0023] The temperature variation influence on humidity trend parameter Thi is used to represent the humidity response direction, rate and sensitivity caused by temperature change, and reflects the typical influence mode of temperature behavior on humidity in the current environment.

[0024] The humidity variation influence on temperature trend parameter Hti is used to represent the disturbance ability of humidity change on temperature, and identifies the possible related effects of humidification and dehumidification actions on the current environment on the heat load.

[0025] Preferably, S2 includes S21 and S22.

[0026] S21, after normalizing the environment change parameter set Env, extracts the temperature change rate parameter Temp, the current temperature offset rate parameter Tof, the humidity change rate parameter Hum, the current humidity offset rate parameter Hof, the temperature variation influence on humidity trend parameter Thi and the humidity variation influence on temperature trend parameter Hti, respectively constructs a temperature influence scoring function and a humidity influence scoring function, and uses them to form a temperature and humidity coupling cross-influence scoring model.

[0027] The temperature influence scoring function and the humidity influence scoring function are constructed by using a linear weighted combination function structure constructed by an entropy weight method.

[0028] Preferably, S22, using the acquired temperature and humidity coupling cross-influence scoring model, substitutes the acquired environment change parameter set Env in the current period into the two component functions in sequence to perform quantitative calculation and processing of the scoring values, and obtains a temperature influence priority scoring value Tsc and a humidity influence priority scoring value Hsc.

[0029] The temperature influence priority score value Tsc is outputted by inputting the temperature change rate parameter Temp, the current temperature offset rate parameter Tof and the humidity variation temperature influence trend parameter Hti into the temperature influence score function in sequence, and is used to represent the temperature control priority weight in the current control period;

[0030] The humidity influence priority score value Hsc is outputted by inputting the humidity change rate parameter Hum, the current humidity offset rate parameter Hof and the temperature variation humidity influence trend parameter Thi into the humidity influence score function in sequence, and is used to represent the humidity control priority weight in the current control period;

[0031] The temperature influence priority score value Tsc and the humidity influence priority score value Hsc are integrated to form the bivariate influence score set Sco used for sorting and judging.

[0032] Preferably, the S3 comprises S31.

[0033] The S31 reads the temperature influence priority score value Tsc and the humidity influence priority score value Hsc in sequence based on the bivariate influence score set Sco, compares the relative strengths, judges the control variable to be executed preferentially in the current control period, and obtains the control sorting tag Tag.

[0034] The control sorting tag Tag is obtained by the following comparison method:

[0035] The first judging method: when the temperature influence priority score value Tsc is greater than the humidity influence priority score value Hsc, it is judged that the temperature control is preferentially executed in the current period, and the control sorting tag Tag is obtained as the priority temperature control.

[0036] The second judging method: when the temperature influence priority score value Tsc is less than the humidity influence priority score value Hsc, it is judged that the humidity control is preferentially executed in the current period, and the control sorting tag Tag is obtained as the priority humidity control.

[0037] The third judging method: when neither the first judging method nor the second judging method meets the condition, it is indicated that the temperature influence priority score value Tsc and the humidity influence priority score value Hsc are close in strength, and the control sorting tag Tag is generated as the temperature and humidity control unchanged.

[0038] Preferably, the S4 comprises S41.

[0039] The S41 judges the control path to be activated in the current control period based on the obtained control sorting tag Tag, and calls the corresponding control instruction set according to the corresponding control target in the control execution module.

[0040] The control instruction set comprises:

[0041] When the control sequence marker Tag is marked as priority temperature control, the preset temperature control execution instruction set Cmdt is called, including starting the refrigeration unit, adjusting the supply air temperature, and adjusting the fan speed action;

[0042] When the control sequence marker Tag is marked as priority humidity control, the corresponding humidity control execution instruction set Cmdh is called, including starting the dehumidification unit, adjusting the humidifier output, and switching the supply air mode instruction;

[0043] When the control sequence marker Tag is marked as temperature and humidity control unchanged, no model instruction is executed;

[0044] The control execution module triggers the control feedback collection process during the issuance of the temperature control execution instruction set Cmdt or the humidity control execution instruction set Cmdh under the regulation instruction.

[0045] Preferably, S42, after the issuance of the regulation instruction is completed, the control feedback collection process is entered, the influence result of the executed regulation instruction on the environmental variable in the current period is monitored in real time, including environmental state response collection and regulation execution feedback information collection;

[0046] The environmental state response collection collects the following environmental change information within a preset response period after the control action is executed by calling the environmental sensing unit:

[0047] The difference between the actual temperature value after the control action is executed and the temperature value before the action is executed is marked as the regulation after temperature change difference parameter Tdf; the difference between the actual humidity value after the control action is executed and the humidity value before the action is executed is marked as the regulation after humidity change difference parameter Hdf; the rate of convergence of the current environmental parameter value to the set target value is marked as the environmental target deviation correction rate parameter Dcv;

[0048] The regulation execution feedback information collection collects the execution state of the regulation device, including the time interval between the sending of the control instruction and the actual entering of the stable working state of the executed device, which is marked as the regulation response delay time parameter Ltg; the device power consumption change before and after the regulation action is executed, which is marked as the regulation load current change parameter Iex;

[0049] The regulation after temperature change difference parameter Tdf, the regulation after humidity change difference parameter Hdf, the environmental target deviation correction rate parameter Dcv, the regulation response delay time parameter Ltg, and the regulation load current change parameter Iex are integrated to form the feedback parameter Fbk, which is combined with the called temperature control execution instruction set Cmdt or humidity control execution instruction set Cmdh for processing to form the control response data set Crs.

[0050] Preferably, the S5 includes S51;

[0051] S51, based on the control response data set Crs, performing normalization processing, calculating the normalized control response data set Crs, obtaining the control stability score value Sta and the control adjustment energy consumption score value Pow, and integrating into the control optimization factor set Opt, then extracting the control optimization factor set Opt of the last period as the historical control optimization factor set Optp, and comparing with the control optimization factor set Opt, and performing iterative optimization according to the comparison result;

[0052] The control stability score value Sta is obtained by linearly weighting and summing the normalized temperature change difference value parameter Tdf, the normalized humidity change difference value parameter Hdf and the environmental target deviation correction rate parameter Dcv.

[0053] The control adjustment energy consumption score value Pow is linearly weighted and combined to calculate the normalized control response delay time parameter Ltg and the normalized load current change parameter Iex.

[0054] The iterative optimization is triggered by the following comparison results:

[0055] When the control stability score value Sta of the current period is greater than the corresponding value in the historical control optimization factor set Optp, and the control adjustment energy consumption score value Pow is less than the corresponding value in the historical control optimization factor set Optp, it is determined that the current generated control instruction has improved effect on control precision and energy consumption efficiency, and it is determined that the control strategy of the current period is effective, and optimization is not performed.

[0056] When the control stability score value Sta of the current period is less than the corresponding value in the historical control optimization factor set Optp, or the control adjustment energy consumption score value Pow is greater than the corresponding value in the historical control optimization factor set Optp, it is determined that the control precision is decreased or the energy consumption is increased, and there are response delay, excessive control amplitude and poor execution energy efficiency, and the iterative optimization is triggered, including adjusting the weight coefficients in the temperature influence score function and the humidity influence score function.

[0057] A double-variable energy-saving control system for constant temperature and humidity environment, comprising an environment data acquisition module, a model function establishment module, an ordering analysis module, a control execution module and an effect evaluation module.

[0058] The environment data acquisition module acquires the temperature and humidity change information of the target control space in real time through the environment sensing unit, and analyzes and obtains the temperature change influence trend parameter Thi and the humidity change influence trend parameter Hti, to form the environment change parameter set Env.

[0059] The model function establishing module establishes a temperature and humidity coupling cross-influence scoring model based on the environment change parameter set Env, calculates a temperature influence priority scoring value Tsc and a humidity influence priority scoring value Hsc, and forms a bivariate influence scoring set Sco;

[0060] The sorting analysis module compares the relative strength of the temperature influence priority scoring value Tsc and the humidity influence priority scoring value Hsc based on the bivariate influence scoring set Sco, and generates a control sorting mark Tag;

[0061] The control execution module starts a corresponding priority regulation channel according to the control sorting mark Tag, and records a feedback parameter Fbk of a current regulation channel control action impact to form a control response data set Crs;

[0062] The effect evaluation module calculates a control stability scoring value Sta and a control adjustment energy consumption scoring value Pow based on the control response data set Crs, and compares them with the last period scoring value for optimization.

[0063] The application provides a bivariate energy-saving control system and method for a constant temperature and humidity environment, which has the following beneficial effects:

[0064] (1) By constructing the environment change parameter set Env, not only the temperature and humidity change data are comprehensively collected, but also the temperature variation influence trend parameter Thi and the humidity variation influence trend parameter Hti are introduced, so that the variable cross-disturbance trend is quantitatively modeled, and the pre-knowledge ability of the control system to the coupling disturbance is enhanced; the temperature influence priority scoring value Tsc and the humidity influence priority scoring value Hsc contained in the bivariate influence scoring set Sco can determine the regulation priority based on the actual state, generate the control sorting mark Tag, and make the control sequence no longer depend on the fixed logic, but have real-time and response adaptability; at the same time, the control response data set Crs is constructed by collecting the control action feedback parameter Fbk, and the control stability scoring value Sta and the control adjustment energy consumption scoring value Pow are calculated, and then compared with the last period result to form an optimization path, so that the control behavior continuously learns and the precision evolves in the two dimensions of energy-saving and stability, the secondary disturbance problem caused by variable independent control is significantly improved, and finally the systematic optimization of control energy-saving, response efficiency and system stability is realized without changing the hardware structure.

[0065] (2) By generating the humidity influence priority score value Hsc; and then in the construction of the bivariate influence score set Sco, the control order tag Tag can be generated based on the score intensity difference in each control cycle, so that the control order determination has a clear quantitative basis and fault tolerance adjustment logic. The introduction of this score-order linkage mechanism not only improves the accuracy and stability of the priority judgment, but also introduces a neutral decision state of "constant temperature and humidity control" when the variable score is close, avoiding system oscillation or misjudgment caused by frequent control switching. Therefore, the unique technical value of this step in the method is to realize the structured modeling and executable landing of the variable control order dynamic decision mechanism for constant temperature and humidity control objects.

[0066] (3) The control response data set Crs assembled based on the feedback parameter Fbk and the instruction execution record is used to calculate the control stability score value Sta and the control adjustment energy consumption score value Pow after normalization. The two are integrated into the control optimization factor set Opt, and compared with the historical control optimization factor set Optp reserved in the last period. This comparison not only realizes the period evolution judgment of control performance, but also automatically updates and corrects the weight coefficients in the temperature influence score function and the humidity influence score function through a clear iteration trigger mechanism, thereby giving the control model self-learning ability and adaptive environmental evolution ability in long-period operation. Therefore, the outstanding technical advantage of this step is to realize the dynamic performance feedback iteration closed-loop mechanism of score-comparison-correction with the control response data set Crs as the core, which significantly improves the energy saving sustainability, control stability and strategy optimization plasticity of the system under multi-variable control conditions. BRIEF DESCRIPTION OF DRAWINGS

[0067] Figure 1 A schematic diagram of a double-variable energy-saving control method for a constant temperature and humidity environment according to the present application;

[0068] Figure 2 A block diagram schematic diagram of a double-variable energy-saving control system for a constant temperature and humidity environment according to the present application. DETAILED DESCRIPTION

[0069] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.

[0070] Embodiment 1

[0071] The present application provides a double-variable energy-saving control method for a constant temperature and humidity environment, please refer to Figure 1, comprising the following steps:

[0072] S1, collecting temperature and humidity change information of a target control space in real time through an environment sensing unit, and analyzing and obtaining a humidity influence trend parameter Thi of temperature variation and a temperature influence trend parameter Hti of humidity variation to form an environment change parameter set Env;

[0073] S2, constructing a temperature and humidity coupling cross-influence scoring model based on the environment change parameter set Env, calculating a temperature influence priority score value Tsc and a humidity influence priority score value Hsc to form a bivariate influence score set Sco;

[0074] S3, comparing the relative strength of the temperature influence priority score value Tsc and the humidity influence priority score value Hsc based on the bivariate influence score set Sco, and generating a control sorting tag Tag;

[0075] S4, starting a corresponding priority regulation channel according to the control sorting tag Tag, and recording a feedback parameter Fbk of a current regulation channel control action to form a control response data set Crs;

[0076] S5, calculating a control stability score value Sta and a control adjustment energy consumption score value Pow based on the control response data set Crs, and comparing them with the score values of the previous period to optimize.

[0077] In this embodiment, by constructing the environment change parameter set Env, not only the temperature and humidity change data is comprehensively collected, but also the temperature variation influence trend parameter Thi and the humidity variation influence trend parameter Hti are introduced to realize the quantitative modeling of the variable cross-disturbance trend and enhance the pre-knowledge ability of the control system to the coupling disturbance. Through the temperature influence priority score value Tsc and the humidity influence priority score value Hsc contained in the bivariate influence score set Sco, the regulation priority can be judged based on the actual state, the control sorting tag Tag is generated, and the control order is no longer dependent on fixed logic, but has real-time and response adaptability. At the same time, by collecting the control action feedback parameter Fbk to construct the control response data set Crs, and calculating the control stability score value Sta and the control adjustment energy consumption score value Pow based on it, and comparing them with the results of the previous period to form an optimization path, the continuous learning and precision evolution of the control behavior in the energy saving and stability dimensions are realized. Overall, this method not only improves the precision and flexibility of the control strategy, but also significantly improves the secondary disturbance problem caused by variable independent control, and finally realizes the systematic optimization of control energy saving, response efficiency and system stability without changing the hardware structure.

[0078] Embodiment 2

[0079] This embodiment is an explanation in embodiment 1, please refer to Figure 1 Specifically, the S1 includes S11 and S12;

[0080] S11, through the composite type temperature and humidity sensor device arranged in the target control space, the temperature and humidity changes of the space environment are continuously monitored, and the temperature and humidity change information of the target control space is obtained;

[0081] The composite type temperature and humidity sensor device includes a temperature detection module for detecting temperature changes in the ambient air, and a humidity detection module for detecting relative humidity changes in the ambient air;

[0082] The temperature and humidity change information includes temperature change rate parameter Temp, humidity change rate parameter Hum, current temperature offset rate parameter Tof, and current humidity offset rate parameter Hof;

[0083] The temperature change rate parameter Temp and the humidity change rate parameter Hum are calculated by the change amount between the current detection value and the detection value at the last time combined with the time interval;

[0084] The current temperature offset rate parameter Tof and the current humidity offset rate parameter Hof represent the relative deviation percentage of the current temperature and humidity value relative to the preset target value, respectively;

[0085] The temperature and humidity change information is transmitted and communicated through a bus type local area connection structure or a wireless low power consumption communication protocol (such as ZigBee or LoRa).

[0086] S12, based on the obtained temperature and humidity change information, the interaction between temperature and humidity changes is analyzed and processed, the temperature change influence trend parameter Thi and the humidity change influence trend parameter Hti are obtained, and then the temperature and humidity change information is integrated to form the environment change parameter set Env;

[0087] The analysis and processing includes steps S121 and S122;

[0088] S121, the cached temperature and humidity change information record data in the historical running period is called, the temperature and humidity change trajectory of continuous multiple periods is extracted, and the temperature and humidity response sequence in the adjacent period is constructed based on the sliding window method, and the historical variable sample set for coupling analysis is formed;

[0089] S122, the temperature change value sequence and the humidity response change value sequence in the historical variable sample set are used to calculate the trend model through the linear fitting model, and the temperature change influence trend parameter Thi and the humidity change influence trend parameter Hti are generated, respectively;

[0090] The temperature variation influence on humidity trend parameter Thi is used to represent the humidity response direction, rate and sensitivity caused by temperature change, reflecting the typical influence mode of temperature behavior on humidity in the current environment;

[0091] The humidity variation influence on temperature trend parameter Hti is used to represent the disturbance ability of humidity change on temperature, identifying the possible related effects of humidifying and dehumidifying actions on heat load in the current environment.

[0092] In this embodiment, based on the temperature change rate parameter Temp, the humidity change rate parameter Hum, the current temperature offset rate parameter Tof and the current humidity offset rate parameter Hof obtained by the composite temperature and humidity sensing device, not only a real-time multi-dimensional description of the current state of the target control space is formed, but also the continuity and stability of data transmission are ensured through the bus-type local connection structure or the wireless low-power communication protocol; on this basis, through the temperature and humidity response sequence in the historical variable sample set and the linear fitting analysis, the temperature variation influence on humidity trend parameter Thi and the humidity variation influence on temperature trend parameter Hti are further obtained, which has the ability to identify the coupling direction, coupling strength and response delay characteristics between variables. This process not only realizes the direct monitoring of the variable entity, but also upgrades the control object from "state perception" to "disturbance estimation" through trend parameter modeling, thereby providing more forward-looking and context-related control basis for subsequent control priority sorting and path selection. Therefore, the technical contribution of this step lies in significantly improving the integrity, relevance and prediction orientation of the environmental change parameter set Env.

[0093] Embodiment 3

[0094] This embodiment is an explanation and description in embodiment 1, please refer to Figure 1 , specifically: the S2 includes S21 and S22;

[0095] S21, after normalizing the environmental change parameter set Env, the temperature change rate parameter Temp, the current temperature offset rate parameter Tof, the humidity change rate parameter Hum, the current humidity offset rate parameter Hof, the temperature variation influence on humidity trend parameter Thi and the humidity variation influence on temperature trend parameter Hti are extracted, and the temperature influence score function and the humidity influence score function are respectively constructed, which are used to constitute the temperature and humidity coupling cross-influence score model;

[0096] The temperature influence score function and the humidity influence score function are constructed by using the linear weighted combination function structure constructed by the entropy weight method;

[0097] The temperature influence scoring function is used to identify the current temperature disturbance degree: the intensity of short-time temperature fluctuation is quantified by the temperature change rate parameter Temp as a dynamic indication of temperature instability; the necessity of temperature control is quantified: the current temperature offset rate parameter Tof is used to reflect the degree of current temperature deviation from the target set value, which provides a basis for determining whether temperature regulation should be activated; the potential disturbance influence of humidity control on temperature is perceived: the humidity change influence on temperature trend parameter Hti is used to analyze whether the temperature changes unexpectedly due to humidity adjustment, so as to evaluate whether the temperature control means needs to be intervened preferentially;

[0098] The humidity influence scoring function is used to capture the humidity change trend: the humidity change rate parameter Hum is used to measure the intensity of short-time humidity fluctuation, and identify whether there is potential humidity instability; the humidity deviation degree is evaluated: the current humidity offset rate parameter Hof is used to determine whether the current humidity value is outside the effective control range of the set target; the side effect of temperature behavior on humidity is predicted: the temperature change influence on humidity trend parameter Thi is used to analyze the humidity disturbance that may be caused by temperature behavior, so as to warn the cross-influence risk.

[0099] S22, with the obtained temperature and humidity coupling cross-influence scoring model, the environment change parameter set Env obtained in the current period is used as an input item to be sequentially substituted into the two component functions, and the quantitative calculation processing of the scoring values is performed respectively, to obtain the temperature influence priority scoring value Tsc and the humidity influence priority scoring value Hsc;

[0100] The temperature influence priority scoring value Tsc is obtained by sequentially inputting the temperature change rate parameter Temp, the current temperature offset rate parameter Tof, and the humidity change influence on temperature trend parameter Hti into the temperature influence scoring function, and outputting the temperature influence priority scoring value Tsc for representing the current temperature control priority weight;

[0101] The humidity influence priority scoring value Hsc is obtained by sequentially inputting the humidity change rate parameter Hum, the current humidity offset rate parameter Hof, and the temperature change influence on humidity trend parameter Thi into the humidity influence scoring function, and outputting the humidity influence priority scoring value Hsc for representing the current humidity control priority weight;

[0102] The obtained temperature influence priority scoring value Tsc and humidity influence priority scoring value Hsc are integrated to form a two-variable influence scoring set Sco for sorting and judging.

[0103] The S3 includes S31;

[0104] S31, based on the double variable influence score set Sco, read the temperature influence priority score value Tsc and the humidity influence priority score value Hsc in turn, compare the relative intensity, determine the priority control variable in the current control period, and obtain the control order mark Tag;

[0105] The control order mark Tag is determined by the following comparison method:

[0106] Determination method one: when the temperature influence priority score value Tsc is greater than the humidity influence priority score value Hsc, it is determined that the temperature control is executed in the current period, and the control order mark Tag is obtained as priority temperature control;

[0107] Determination method two: when the temperature influence priority score value Tsc is less than the humidity influence priority score value Hsc, it is determined that the humidity control is executed in the current period, and the control order mark Tag is obtained as priority humidity control;

[0108] Determination method three: when neither the determination method one nor the determination method two meets the condition, it means that the temperature influence priority score value Tsc and the humidity influence priority score value Hsc are close in intensity, and the control order mark Tag is generated as temperature and humidity control unchanged.

[0109] In this embodiment, after the normalization processing of each type of parameter in the environmental change parameter set Env, the temperature influence score function and the humidity influence score function constructed by using the entropy weight method not only make the score model have the self-adaptive weight distribution ability, but also ensure the objectivity and dynamic response of the score calculation result, and significantly improve the analysis ability of the control system to the temperature and humidity fluctuation behavior. On this basis, by inputting the temperature change rate parameter Temp, the current temperature offset rate parameter Tof and the humidity change trend parameter Hti to the temperature influence score function, the temperature influence priority score value Tsc is generated; and by inputting the humidity change rate parameter Hum, the current humidity offset rate parameter Hof and the temperature change trend parameter Thi to the humidity influence score function, the humidity influence priority score value Hsc is generated; and then after the construction of the double variable influence score set Sco, the control order mark Tag can be generated based on the score intensity difference in each control period, so that the control order determination has a clear quantitative basis and fault tolerance adjustment logic. The introduction of the score-order linkage mechanism not only improves the accuracy and stability of the priority judgment, but also introduces the neutral decision state of "temperature and humidity control unchanged" when the variable score is close, avoiding the system oscillation or misjudgment behavior caused by frequent control switching. Therefore, the unique technical value of this step in the method is that the variable control order dynamic decision mechanism for the constant temperature and humidity control object is structured and executable.

[0110] Embodiment 4

[0111] This embodiment is an explanation in embodiment 1, please refer to Figure 1 Specifically, the S4 comprises an S41.

[0112] The S41, based on the acquired control sequence marker Tag, determines the control path to be activated in the current control period in the control execution module, and calls the corresponding control instruction set according to the corresponding control target;

[0113] The control instruction set comprises:

[0114] When the control sequence marker Tag is marked as priority temperature control, a preset temperature control execution instruction set Cmdt is called, including starting the refrigeration unit, adjusting the supply air temperature and adjusting the fan speed action;

[0115] When the control sequence marker Tag is marked as priority humidity control, the corresponding humidity control execution instruction set Cmdh is called, including starting the dehumidification unit, adjusting the humidifier output and switching the supply air mode instruction;

[0116] When the control sequence marker Tag is marked as constant temperature and humidity control, no model instruction is executed;

[0117] The control execution module triggers the control feedback collection process to be started in the process of issuing the temperature control execution instruction set Cmdt or the humidity control execution instruction set Cmdh under the control instruction.

[0118] S42, after the control instruction is issued, the control feedback collection process is entered, the influence result of the executed control instruction on the environment variable in the current period is monitored in real time, including environment state response collection and control execution feedback information collection;

[0119] The environment state response collection collects the following environment change information in a preset response period after the control action is executed by calling the environment sensing unit:

[0120] The difference between the actual temperature value after the control action is executed and the temperature value before the action is executed is marked as the control post-change temperature difference parameter Tdf; the difference between the actual humidity value after the control action is executed and the humidity value before the action is executed is marked as the control post-change humidity difference parameter Hdf; the rate of convergence of the current environment parameter value to the set target value is marked as the environment target deviation correction rate parameter Dcv, which is used to quantify whether the control action promotes the approximation of the target state;

[0121] The control execution feedback information collection collects the execution state of the control device, including the time interval between the sending of the control instruction and the actual entering of the stable working state of the executed device, which is marked as the control response delay time parameter Ltg; the device power consumption change before and after the control action is executed, which is marked as the control load current change parameter Iex, which is used to identify the actual load reaction strength;

[0122] The feedback parameter Fbk is formed by integrating the temperature change difference parameter Tdf, the humidity change difference parameter Hdf, the environment target deviation correction rate parameter Dcv, the regulation response delay time parameter Ltg, and the regulation load current change parameter Iex, and is combined with the temperature control execution instruction set Cmdt or the humidity control execution instruction set Cmdh to perform merging processing to form the control response data set Crs.

[0123] The S5 comprises an S51;

[0124] The S51 performs normalization processing based on the control response data set Crs, calculates the normalized control response data set Crs to obtain the control stability score Sta and the control adjustment energy consumption score Pow, integrates them into the control optimization factor set Opt, extracts the control optimization factor set Opt of the previous period as the historical control optimization factor set Optp, and compares the control optimization factor set Opt with the historical control optimization factor set Optp to perform iterative optimization according to the comparison result.

[0125] The control stability score Sta is obtained by linearly weighting the normalized temperature change difference parameter Tdf, the normalized humidity change difference parameter Hdf, and the environment target deviation correction rate parameter Dcv.

[0126] The control adjustment energy consumption score Pow is obtained by linearly weighting and combining the normalized regulation response delay time parameter Ltg and the normalized load current change parameter Iex.

[0127] The iterative optimization is triggered by the following comparison results:

[0128] When the control stability score Sta of the current period is greater than the corresponding value in the historical control optimization factor set Optp, and the control adjustment energy consumption score Pow is less than the corresponding value in the historical control optimization factor set Optp, it is determined that the current generated regulation instruction has improved effect on regulation accuracy and energy consumption efficiency, and it is determined that the regulation instruction control strategy of the current period is effective, and optimization is not performed.

[0129] When the control stability score Sta of the current period is less than the corresponding value in the historical control optimization factor set Optp, or the control adjustment energy consumption score Pow is greater than the corresponding value in the historical control optimization factor set Optp, it is determined that the control accuracy decreases or the energy consumption increases, and there is a situation of response delay, excessive regulation amplitude, and poor execution energy efficiency, and the iterative optimization is triggered, including adjusting the weight coefficients in the temperature influence score function and the humidity influence score function.

[0130] In this embodiment, the control channel to be activated in the current period is determined according to the control order mark Tag, the temperature control execution instruction group Cmdt or the humidity control execution instruction group Cmdh is accurately called, and the feedback collection process is triggered synchronously, so that each time the adjustment behavior has corresponding quantitative response data. Subsequently, the feedback parameters Fbk are collected and structured in the response period, covering the temperature change difference parameter Tdf after regulation, the humidity change difference parameter Hdf after regulation, the environmental target deviation correction rate parameter Dcv, the regulation response delay time parameter Ltg and the regulation load current change parameter Iex, ensuring that the regulation effect has complete and traceable data expression from environmental impact to device performance. The control response data set Crs assembled based on the feedback parameters Fbk and the instruction execution record is used to calculate the control stability score Sta and the control adjustment energy consumption score Pow after normalization processing, both of which are integrated into the control optimization factor set Opt, and compared with the historical control optimization factor set Optp reserved in the last period. The comparison not only realizes the period evolution judgment of the control performance, but also automatically updates and corrects the weight coefficients in the temperature influence score function and the humidity influence score function through the explicit iteration trigger mechanism, thereby giving the control model the self-learning ability and the ability to adapt to environmental evolution in long-period operation. Therefore, the prominent technical advantage of this step is to realize the dynamic performance feedback iteration closed loop mechanism of scoring-comparison-correction based on the control response data set Crs, which significantly improves the energy saving sustainability, control stability and strategy optimization plasticity of the system under multi-variable regulation conditions.

[0131] Embodiment 5

[0132] A dual-variable energy-saving control system for a constant temperature and humidity environment, please refer to Figure 2 , specifically: including an environment data acquisition module, a model function establishment module, an order analysis module, a control execution module and an effect evaluation module;

[0133] The environment data acquisition module acquires the temperature and humidity change information of the target control space in real time through the environment sensing unit, and analyzes and obtains the temperature change influence trend parameter Thi and the humidity change influence trend parameter Hti, to form the environment change parameter set Env.

[0134] The model function establishment module constructs a temperature and humidity coupling cross-influence score model based on the environment change parameter set Env, calculates the temperature influence priority score value Tsc and the humidity influence priority score value Hsc, and forms the dual-variable influence score set Sco.

[0135] The order analysis module compares the relative strength of the temperature influence priority score value Tsc and the humidity influence priority score value Hsc based on the dual-variable influence score set Sco, and generates a control order mark Tag.

[0136] The control execution module starts the corresponding priority regulation channel according to the control sequence mark Tag, and records the feedback parameter Fbk affected by the current regulation channel control action to form a control response data set Crs;

[0137] The effect evaluation module calculates the control stability score Sta and the control adjustment energy consumption score Pow based on the control response data set Crs, and compares them with the score of the previous period for optimization.

[0138] Although the embodiments of the present application have been shown and described, it is to be understood that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the present application, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A dual variable energy saving control method for a constant temperature and humidity environment, characterized in that: The method comprises the following steps: S1, collecting temperature and humidity change information of a target control space in real time through an environmental sensing unit, and analyzing and obtaining temperature variation influence trend parameter Thi and humidity variation influence trend parameter Hti to form an environmental change parameter set Env; S1 comprises S11 and S12; S11, continuously monitoring temperature and humidity changes of the space environment through a composite temperature and humidity sensing device arranged in the target control space, and obtaining temperature and humidity change information of the target control space; The composite temperature and humidity sensing device comprises a temperature detection module for detecting temperature changes in the ambient air and a humidity detection module for detecting relative humidity changes in the ambient air; The temperature and humidity change information comprises temperature change rate parameter Temp, humidity change rate parameter Hum, current temperature offset rate parameter Tof, and current humidity offset rate parameter Hof; The temperature change rate parameter Temp and the humidity change rate parameter Hum are respectively calculated from the change amount between the current detection value and the detection value at the last time interval combined with the time interval; The current temperature offset rate parameter Tof and the current humidity offset rate parameter Hof respectively represent the relative deviation percentage of the current temperature and humidity value relative to the preset target value; The temperature and humidity change information is transmitted and communicated through a bus type local area connection structure or a wireless low power consumption communication protocol; S12, analyzing and processing the interaction between temperature and humidity changes based on the obtained temperature and humidity change information, obtaining temperature variation influence trend parameter Thi and humidity variation influence trend parameter Hti, and integrating them with the temperature and humidity change information to form the environmental change parameter set Env; The analysis and processing comprises steps S121 and S122; S121, calling the cached temperature and humidity change information record data in the historical running period, extracting the temperature and humidity change trajectory of multiple consecutive periods, and constructing the temperature and humidity response sequence in adjacent periods based on the sliding window method to form a historical variable sample set for coupling analysis; S122, using the temperature change value sequence and the humidity response change value sequence in the historical variable sample set to calculate the trend model through a linear fitting model to generate temperature variation influence trend parameter Thi and humidity variation influence trend parameter Hti respectively; The temperature variation influence trend parameter Thi is used to represent the humidity response direction, rate and sensitivity caused by temperature change, and reflects the typical influence mode of temperature behavior on humidity in the current environment; The humidity variation influence trend parameter Hti is used to represent the disturbance ability of humidity change on temperature, and identifies the possible related effects of humidification and dehumidification actions on heat load in the current environment; S2, based on the environmental change parameter set Env, constructing a temperature and humidity coupling cross-influence scoring model, calculating temperature influence priority score value Tsc and humidity influence priority score value Hsc, and forming a two-variable influence score set Sco; S2 comprises S21 and S22; S21, after normalizing the set of environmental change parameters Env, extract the temperature change rate parameter Temp, the current temperature offset rate parameter Tof, the humidity change rate parameter Hum, the current humidity offset rate parameter Hof, the temperature change influence on humidity trend parameter Thi and the humidity change influence on temperature trend parameter Hti, respectively construct a temperature influence scoring function and a humidity influence scoring function, and use them to form a temperature and humidity coupling cross-influence scoring model; The temperature influence scoring function and the humidity influence scoring function are constructed by using a linear weighted combination function structure constructed by an entropy weight method; S22, using the obtained temperature and humidity coupling cross-influence scoring model, input the obtained set of environmental change parameters Env in the current period into the two component functions in turn to perform quantitative calculation and processing of the scoring values, and obtain a temperature influence priority score Tsc and a humidity influence priority score Hsc; The temperature influence priority score Tsc is obtained by inputting the temperature change rate parameter Temp, the current temperature offset rate parameter Tof, and the humidity change influence on temperature trend parameter Hti into the temperature influence scoring function in turn, and outputting the temperature influence priority score Tsc representing the current temperature control priority weight; The humidity influence priority score Hsc is obtained by inputting the humidity change rate parameter Hum, the current humidity offset rate parameter Hof, and the temperature change influence on humidity trend parameter Thi into the humidity influence scoring function in turn, and outputting the humidity influence priority score Hsc representing the current humidity control priority weight; The obtained temperature influence priority score Tsc and humidity influence priority score Hsc are integrated to form a bivariate influence scoring set Sco for sorting and judgment; S3, based on the bivariate influence scoring set Sco, compare the relative strengths of the temperature influence priority score Tsc and the humidity influence priority score Hsc, and generate a control sorting tag Tag; S4, according to the control sorting tag Tag, start the corresponding priority control channel, and record the feedback parameter Fbk of the current control channel control action, and form a control response data set Crs; S5, based on the control response data set Crs, calculate a control stability score Sta and a control adjustment energy consumption score Pow, and compare them with the scores of the previous period to optimize.

2. The dual variable energy saving control method for a constant temperature and humidity environment according to claim 1, characterized in that: The S3 includes S31; S31, based on the bivariate influence scoring set Sco, read the temperature influence priority score Tsc and the humidity influence priority score Hsc in turn, compare their relative strengths, determine the control variable to be executed preferentially in the current control period, and obtain the control sorting tag Tag; The control sorting tag Tag is obtained by the following comparison methods: Method one: when the temperature influence priority score Tsc is greater than the humidity influence priority score Hsc, it is determined that temperature control is preferentially executed in the current period, and the control sorting tag Tag is a priority temperature control; The second determination mode is: when the temperature influence priority score Tsc is less than the humidity influence priority score Hsc, it is determined that the current period is preferentially executed humidity control, and the control order mark Tag is marked as priority humidity control; The third determination mode is: when neither the first determination mode nor the second determination mode meets the condition, it is indicated that the temperature influence priority score Tsc and the humidity influence priority score Hsc are close in strength, and the control order mark Tag is generated as temperature and humidity control unchanged.

3. The dual variable energy saving control method for a constant temperature and humidity environment according to claim 1, characterized in that: The S4 comprises S41; In the S41, based on the obtained control order mark Tag, the control execution module determines the control path to be activated in the current control period, and calls the corresponding control instruction set according to the corresponding control target; The control instruction set comprises: When the control order mark Tag is marked as priority temperature control, a preset temperature control execution instruction set Cmdt is called, including starting the refrigeration unit, adjusting the supply air temperature and adjusting the fan speed action; When the control order mark Tag is marked as priority humidity control, the corresponding humidity control execution instruction set Cmdh is called, including starting the dehumidification unit, adjusting the humidifier output and switching the supply air mode instruction; When the control order mark Tag is marked as temperature and humidity control unchanged, no model instruction is executed; In the process of issuing the temperature control execution instruction set Cmdt or the humidity control execution instruction set Cmdh under the control instruction, the control feedback collection process is triggered.

4. The dual variable energy saving control method for a constant temperature and humidity environment according to claim 3, characterized in that: In the S42, after the control instruction is issued, the control feedback collection process is entered, the influence result of the executed control instruction on the environment variable in the current period is monitored in real time, including environment state response collection and control execution feedback information collection; The environment state response collection collects the following environment change information in a preset response period after the control action is executed by calling the environment sensing unit: The difference between the actual temperature value after the control action is executed and the temperature value before the control action is executed is marked as a control-after temperature change difference parameter Tdf; the difference between the actual humidity value after the control action is executed and the humidity value before the control action is executed is marked as a control-after humidity change difference parameter Hdf; and the rate at which the current environment parameter value converges to the set target value is marked as an environment target deviation correction rate parameter Dcv; The control execution feedback information collection monitors the execution state of the control device, including the time interval between the sending of the control instruction and the actual entering of the stable working state of the executed device, which is marked as a control response delay time parameter Ltg; and the device power consumption change before and after the control action is executed, which is marked as a control load current change parameter Iex; The control-after temperature change difference parameter Tdf, the control-after humidity change difference parameter Hdf, the environment target deviation correction rate parameter Dcv, the control response delay time parameter Ltg and the control load current change parameter Iex are integrated to form a feedback parameter Fbk, which is combined with the called temperature control execution instruction set Cmdt or humidity control execution instruction set Cmdh for processing, to form a control response data set Crs.

5. A dual variable energy saving control method for a constant temperature and humidity environment according to claim 4, characterized in that: The S5 comprises S51; S51. Based on the control response dataset Crs, normalize it, calculate the control stability score Sta and control adjustment energy consumption score Pow, and integrate them into the control optimization factor set Opt. Then, extract the control optimization factor set Opt from the previous period and mark it as the historical control optimization factor set Optp. Then, compare it with the control optimization factor set Opt and perform iterative optimization based on the comparison results. The control stability score Sta is obtained by linearly weighting the normalized temperature change difference parameter Tdf, humidity change difference parameter Hdf, and environmental target deviation correction rate parameter Dcv after regulation. The normalized control response delay time parameter Ltg and the control load current change parameter Iex are calculated and obtained by linear weighted combination of the control adjustment energy consumption score value Pow. The iterative optimization is triggered by the following comparison results: If the current cycle's control stability score Sta is greater than the corresponding value in the historical control optimization factor set Optp, and the control adjustment energy consumption score Pow is less than the corresponding value in the historical control optimization factor set Optp, then the currently generated control command is determined to have an improvement effect on control accuracy and energy consumption efficiency. Therefore, the control strategy of the control command for this cycle is determined to be effective and no optimization is performed. When the current cycle's control stability score Sta is less than the corresponding value in the historical control optimization factor set Optp, or when the control adjustment energy consumption score Pow is greater than the corresponding value in the historical control optimization factor set Optp, it is determined that the control accuracy has decreased or the energy consumption has increased, indicating a situation of response hysteresis, excessive adjustment amplitude, and poor execution energy efficiency. This triggers iterative optimization, including adjusting the weight coefficients in the temperature influence scoring function and the humidity influence scoring function.

6. A dual-variable energy-saving control system for a constant temperature and humidity environment, comprising a dual-variable energy-saving control method for a constant temperature and humidity environment according to any one of claims 1-5, characterized in that: It includes an environmental data acquisition module, a model function establishment module, a sorting analysis module, a control execution module, and an effect evaluation module; The environmental data acquisition module collects temperature and humidity change information of the target control space in real time through the environmental sensing unit, and analyzes and obtains the trend parameter Thi of temperature change on humidity and the trend parameter Hti of humidity change on temperature, forming the environmental change parameter set Env. The model function building module constructs a temperature and humidity coupled cross-influence scoring model based on the environmental change parameter set Env, and calculates the temperature influence priority score value Tsc and the humidity influence priority score value Hsc to form a bivariate influence score set Sco. The ranking analysis module compares the relative strengths of the temperature influence priority score value Tsc and the humidity influence priority score value Hsc based on the bivariate influence score set Sco, and generates a control ranking tag Tag. The control execution module starts the corresponding priority control channel according to the control sorting tag, and records the feedback parameter Fbk of the current control channel's control action to form a control response dataset Crs; The effect evaluation module calculates the control stability score Sta and the control adjustment energy consumption score Pow based on the control response dataset Crs, and then compares them with the score values ​​of the previous period for optimization.

Images