Intelligent humidity and temperature deviation energy-saving control method and system for central air conditioner and readable medium

Abstract

According to the intelligent humidity and temperature deviation energy-saving control method and system for the central air conditioner and the readable medium, the PID algorithm is combined with the dynamic real-time enthalpy humidity diagram, air conditioner control parameters float in a range under the condition that the technological requirements are met, the control precision is improved, and therefore the energy consumption of the air conditioner is remarkably reduced. Comprising an energy-saving server and a plurality of air conditioner energy-saving control devices in communication connection with the energy-saving server, and each air conditioner energy-saving control device controls one or more air conditioner units. The air conditioner energy-saving control device is internally provided with a multi-working-condition enthalpy and humidity diagram partitioning module and a region target control optimization calculation module, and the multi-working-condition enthalpy and humidity diagram partitioning module and the region target control optimization calculation module optimize control parameters through a PID algorithm in combination with a dynamic real-time enthalpy and humidity diagram optimization algorithm.

Description

Technical Field

[0001] The present invention relates to the field of air-conditioning temperature and humidity regulation, and in particular to a central air-conditioning intelligent humidity and temperature deviation energy-saving control method and system, and a readable medium. Background Art

[0002] Central air-conditioning equipment is suitable for various industrial environments, such as production workshops, storage and logistics centers, commercial complexes, etc., and is used to provide precise temperature and humidity adjustment to ensure the smooth progress of the production process and the stability of product quality.

[0003] Traditional central air conditioning equipment uses PID algorithm to adjust the parameters of air conditioning, which controls the temperature / humidity value within the deviation range allowed by the process, relying on basic automatic control logic supplemented by simple manual adjustment to achieve the control of the target value, and has been widely used. However, the PID algorithm is suitable for adjusting a single control parameter, such as a single temperature or humidity. When the PID algorithm is used for multi-objective control (such as simultaneous control of temperature and humidity), it cannot effectively handle the coupling relationship between variables, resulting in large control errors.

[0004] Moreover, under the control of PID algorithm, the response speed and temperature and humidity control accuracy are poor, and frequent temperature and humidity fluctuations are prone to occur. For example, when there are large fluctuations in indoor humidity, the compressor needs to run more frequently at a higher speed, and the compressor running at a high speed will reduce the overall energy efficiency of the air conditioner.

[0005] At the same time, the PID algorithm often leads to excessive dehumidification, resulting in the actual output cooling capacity being greater than the room load required, causing waste of cooling capacity, electricity and other energy. Summary of the invention

[0006] The purpose of the present invention is to provide a central air-conditioning intelligent humidity and temperature deviation energy-saving control method and system, and a readable medium. By combining a PID algorithm with a dynamic real-time enthalpy-humidity diagram, the air-conditioning control parameters can float within a range while meeting the process requirements, thereby improving the control accuracy and significantly reducing the energy consumption of the air-conditioning.

[0007] The embodiment of the present invention is achieved as follows:

[0008] On the one hand, a central air-conditioning intelligent humidity and temperature deviation energy-saving control method is proposed, comprising an energy-saving server and a plurality of air-conditioning energy-saving control devices communicating with the energy-saving server, each of which controls one or more air-conditioning units; the air-conditioning energy-saving control device is built with a multi-condition enthalpy-humidity diagram partition module and a regional target control optimization calculation module, the multi-condition enthalpy-humidity diagram partition module and the regional target control optimization calculation module optimize the control parameters through a PID algorithm combined with a dynamic real-time enthalpy-humidity diagram optimization algorithm, and the calculation steps of the PID algorithm combined with the dynamic real-time enthalpy-humidity diagram optimization algorithm include:

[0009] Obtain dynamic real-time enthalpy-humidity diagrams under different working conditions, and divide the dynamic real-time enthalpy-humidity diagrams into different target areas;

[0010] Calculate states a and b in the target area using the PID algorithm, and use the midpoint state c of the line connecting states a and b as the mixed state point;

[0011] Obtain the isohumidities of states a, b, and c, as well as the iso-dry-bulb temperature lines and iso-enthalpy lines of states a and c, and take the intersection of the isohumidities and the iso-dry-bulb temperature lines of state a as the center, and the center passes through the iso-relative temperature lines of states a, b, and c; draw a quadrilateral interval surface perpendicular to the iso-enthalpy line space, where the length of the first pair of sides of the quadrilateral is the difference between the iso-dry-bulb temperature lines of states a and c, and the length of the second pair of sides of the quadrilateral is twice the difference between the iso-enthalpy lines of states a and c;

[0012] Obtain the difference between the iso-dry-bulb temperature lines of states a and c and the ratio of the iso-enthalpy lines of states a and c, perform isothermal dehumidification processing on the center to construct a new floating value center, and based on the floating value center, reduce the lengths of two pairs of sides of the quadrilateral interval surface by equal ratio, and use the further optimized quadrilateral interval surface as the control range floating interval of the target area.

[0013] As a preferred technical solution, the air conditioning energy-saving control device further includes a surface cooler temperature and humidity control calculation module 129, which is configured to select one or more groups of surface coolers to complete heat exchange according to different working conditions.

[0014] As a preferred technical solution, the above-mentioned air-conditioning energy-saving control device also includes a boundary state control optimization calculation module, a wet balance state control optimization calculation module, a compound humidification state optimization calculation module, a dehumidification out of control state optimization calculation module and a process path optimization calculation module. Based on the PID algorithm combined with the dynamic real-time enthalpy-humidity diagram optimization algorithm, one or more algorithms among the boundary state control optimization calculation module, the wet balance state control optimization calculation module, the compound humidification state optimization calculation module and the dehumidification out of control state optimization calculation module are further selected, and the optimal control strategy is selected through the process path optimization calculation module fitting optimization.

[0015] As a preferred technical solution, the above-mentioned boundary state control optimization calculation module obtains at least two target points A and B in the regional target, takes the historical boundary states of the target points A and B as the boundary state detection results, and comprehensively quantifies and confirms multiple historical boundary state detection results to obtain the boundary state floating range. When the air-conditioning system is in the boundary state, the temperature and humidity set values ​​are automatically adjusted within the boundary state floating range so that the air-conditioning operation meets the control requirements.

[0016] As a preferred technical solution, the above-mentioned wet balance state control optimization calculation module, composite humidification state optimization calculation module, and dehumidification out-of-control state optimization calculation module are configured to adopt a temperature and humidity deviation operation strategy, and by selecting the point with the minimum energy consumption within the deviation value as the set value, the control error is kept within 1 / 2 of the process allowable deviation.

[0017] As a preferred technical solution, the fitting optimization method of the above process path optimization calculation module includes:

[0018] Generate forecasts through a variety of optimization algorithms;

[0019] Execute the verification algorithm to calculate the accuracy of the calculated prediction value under the current working conditions;

[0020] A checker that compares multiple validation results and confirms consistency, weighting the contribution of each algorithm based on the accuracy of the validation.

[0021] As a preferred technical solution, the above-mentioned air-conditioning energy-saving control device is also provided with a real-time control enthalpy-humidity diagram interaction module, and the real-time control enthalpy-humidity diagram interaction module is configured to provide a central air-conditioning intelligent monitoring system operation and optimal control strategy monitoring interface.

[0022] As a preferred technical solution, the above-mentioned multi-condition enthalpy-humidity diagram partitioning module and regional target control optimization calculation module, surface cooler temperature and humidity control calculation module, boundary state control optimization calculation module, moisture balance state control optimization calculation module, compound humidification state optimization calculation module, dehumidification out of control state optimization calculation module and process path optimization calculation module are integrated in the air conditioning energy-saving control device.

[0023] Secondly, a central air-conditioning intelligent humidity and temperature deviation energy-saving control system is proposed, including:

[0024] Energy-saving servers,

[0025] A plurality of air-conditioning energy-saving control devices are connected to the energy-saving server in communication. The multi-condition enthalpy-humidity diagram partition module and the regional target control optimization calculation module in the air-conditioning energy-saving control device optimize the control parameters by combining the PID algorithm with the dynamic real-time enthalpy-humidity diagram optimization algorithm. The multi-condition enthalpy-humidity diagram partition module and the regional target control optimization calculation module are configured as follows:

[0026] Obtain dynamic real-time enthalpy-humidity diagrams under different working conditions, and divide the dynamic real-time enthalpy-humidity diagrams into different target areas;

[0027] Calculate states a and b in the target area using the PID algorithm, and use the midpoint state c of the line connecting states a and b as the mixed state point;

[0028] Obtain the isohumidities of states a, b, and c, as well as the iso-dry-bulb temperature lines and iso-enthalpy lines of states a and c, and take the intersection of the isohumidities and the iso-dry-bulb temperature lines of state a as the center, and the center passes through the iso-relative temperature lines of states a, b, and c; draw a quadrilateral interval surface perpendicular to the iso-enthalpy line space, where the length of the first pair of sides of the quadrilateral is the difference between the iso-dry-bulb temperature lines of states a and c, and the length of the second pair of sides of the quadrilateral is twice the difference between the iso-enthalpy lines of states a and c;

[0029] Obtain the difference between the iso-dry-bulb temperature lines of states a and c and the ratio of the iso-enthalpy lines of states a and c, perform isothermal dehumidification processing on the center to construct a new floating value center, and based on the floating value center, reduce the lengths of two pairs of sides of the quadrilateral interval surface by equal ratio, and use the further optimized quadrilateral interval surface as the control range floating interval of the target area.

[0030] As an optimal technical solution, the air-conditioning energy-saving control device controls a group of air-conditioning units, which include a new return air mixing section, a self-cleaning high-efficiency filter section, a surface cooling water retaining section, a heating section, a dry steam humidification section, and a blower section arranged in sequence.

[0031] In a third aspect, a computer-readable storage medium is proposed, on which instructions are stored. When the instructions are loaded by a computer, the computer executes the central air-conditioning intelligent humidity and temperature deviation energy-saving control method as described in any one of the above items.

[0032] The beneficial effects of the present invention are:

[0033] 1. This central air-conditioning intelligent humidity and temperature deviation energy-saving control method adjusts the PID parameters to adapt to the special needs of the central air-conditioning control system. At the same time, it uses the dynamic real-time enthalpy-humidity diagram on the basis of the PID algorithm, and further optimizes the control range floating interval of the target area through the optimization algorithm on the dynamic real-time enthalpy-humidity diagram, improves the temperature and humidity control accuracy, and facilitates the best control strategy in the later stage;

[0034] 2. This technical solution uses a dynamic real-time enthalpy-humidity diagram based on the PID algorithm to better handle nonlinear problems, so that the indoor temperature and humidity have a relatively gentle change trend, improving the stability of the energy-saving control system. In addition, under a continuously changing composite environment, the new optimization algorithm can still stably control the indoor temperature at the set point, further verifying the algorithm's ability to handle nonlinear problems;

[0035] 3. The new optimization algorithm recalculates the control range floating interval of the target area to avoid excessive dehumidification and frequent high-speed operation of the compressor, thereby reducing energy consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0037] Figure 1 A schematic diagram of the connection structure of the energy-saving server and the air-conditioning control network in the central air-conditioning intelligent humidity and temperature deviation energy-saving control method according to an embodiment of the present invention;

[0038] Figure 2 A method flow chart of combining a PID algorithm with a dynamic real-time enthalpy-humidity diagram optimization algorithm in an intelligent humidity-temperature deviation energy-saving control method for a central air conditioner according to an embodiment of the present invention;

[0039] Figure 3 This is a functional module connection diagram of an air conditioning energy-saving control device in a central air-conditioning intelligent humidity-temperature deviation energy-saving control method according to an embodiment of the present invention;

[0040] Figure 4 It is a schematic diagram of the control range floating interval after dynamically optimizing the control parameters by using the PID algorithm combined with the dynamic real-time enthalpy-humidity diagram optimization algorithm in the intelligent humidity-temperature deviation energy-saving control method for central air conditioning in an embodiment of the present invention;

[0041] Figure 5 It is the control path expression form of the enthalpy-humidity diagram of the traditional control method and the schematic diagram of the operating energy consumption;

[0042] Figure 6 It is a control path expression form of the enthalpy-humidity diagram and a schematic diagram of operating energy consumption in the intelligent humidity-temperature deviation energy-saving control method for central air conditioning in an embodiment of the present invention combined with an auxiliary optimization algorithm;

[0043] Figure 7 It is a structural schematic diagram of an air-conditioning unit of a central air-conditioning intelligent humidity-temperature deviation energy-saving control system according to an embodiment of the present invention;

[0044] Figure 8 This is a schematic diagram of the improved structure of the surface cooler of the central air-conditioning intelligent humidity and temperature deviation energy-saving control system according to an embodiment of the present invention.

[0045] Icons: energy-saving server 110; air-conditioning energy-saving control device 120; air-conditioning unit 130; data acquisition and monitoring control device 140; operator station 150;

[0046] Multi-condition enthalpy-humidity diagram partition module 121; regional target control optimization calculation module 122; boundary state control optimization calculation module 123; wet balance state control optimization calculation module 124; compound humidification state optimization calculation module 125; dehumidification out-of-control state optimization calculation module 126; process path optimization calculation module 127; surface cooler temperature and humidity control calculation module 129; real-time control enthalpy-humidity diagram interaction module 128;

[0047] Fresh return air mixing section 131; self-cleaning high efficiency filtering section 132; surface cooling water retaining section 133; heating section 134; dry steam humidifying section 135; blower section 136. DETAILED DESCRIPTION

[0048] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings here can be arranged and designed in various different configurations.

[0049] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention claimed for protection, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0050] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, further definition and explanation thereof is not required in subsequent drawings.

[0051] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in a variety of forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this application will be more comprehensive and complete and fully convey the concept of the example embodiments to those skilled in the art.

[0052] In addition, described feature, structure or characteristic can be combined in one or more embodiments in any suitable manner. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present application. However, those skilled in the art will appreciate that the technical scheme of the present application can be put into practice without one or more of the specific details, or other methods, components, devices, steps, etc. can be adopted. In other cases, known methods, devices, realizations or operations are not shown or described in detail to avoid blurring the various aspects of the application.

[0053] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities may be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0054] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined, so the actual execution order may change according to actual conditions.

[0055] The central air-conditioning intelligent humidity and temperature deviation energy-saving control method in this scheme can be widely used in the following fields.

[0056] For example, production environment control in the tobacco industry: In the workshop at the tobacco factory production site, this system is used to finely control the temperature and humidity, improving product quality while achieving energy conservation and emission reduction.

[0057] Industrial Manufacturing: In industrial manufacturing environments where temperature and humidity control is required, especially in the precision machining industry, intelligent temperature and humidity deviation control technology is used to ensure product production quality.

[0058] Commercial buildings and public places: This system can optimize energy use and reduce operating costs.

[0059] Agricultural greenhouse: Use temperature and humidity deviation control technology to optimize the plant growth environment and improve crop yield and quality.

[0060] Cold chain logistics, food processing and storage: Use temperature and humidity deviation control technology to ensure that the quality of goods is not affected during transportation and reduce losses.

[0061] Smart Home: Improve living comfort and save energy by integrating temperature and humidity deviation control technology.

[0062] etc.

[0063] First embodiment

[0064] This embodiment provides an intelligent humidity and temperature deviation energy-saving control method for a central air conditioner. By combining a dynamic real-time enthalpy-humidity diagram on the basis of a PID algorithm, the air conditioning control parameters are allowed to float within a range while meeting the process requirements, thereby significantly reducing the energy consumption of the air conditioner.

[0065] See also Figure 1-3The central air-conditioning intelligent humidity and temperature deviation energy-saving control method constructs an optimized intelligent humidity and temperature deviation energy-saving control system, which includes an energy-saving server 110 and multiple air-conditioning energy-saving control devices 120 that are communicatively connected to the energy-saving server 110, and each air-conditioning energy-saving control device 120 controls one or more air-conditioning units 130.

[0066] Among them, a multi-condition enthalpy-humidity diagram partitioning module 121 and a regional target control optimization calculation module 122 are built into the air-conditioning energy-saving control device 120. The multi-condition enthalpy-humidity diagram partitioning module 121 and the regional target control optimization calculation module 122 dynamically optimize the control parameters through the PID algorithm combined with the dynamic real-time enthalpy-humidity diagram optimization algorithm, thereby improving the accuracy of the intelligent humidity and temperature deviation energy-saving control system and reducing energy consumption.

[0067] For details, see Figure 2 The calculation steps of the PID algorithm combined with the dynamic real-time enthalpy-humidity diagram optimization algorithm include:

[0068] S1: Obtain the dynamic real-time enthalpy-humidity diagram under different working conditions, and divide the dynamic real-time enthalpy-humidity diagram into different target areas;

[0069] S2: Calculate states a and b in the target area using the PID algorithm, and use the midpoint state c of the line connecting states a and b as the mixed state point;

[0070] S3: Obtain the isohumidities of states a, b, and c, as well as the iso-dry-bulb temperature lines and iso-enthalpy lines of states a and c, and take the intersection of the isohumidities and the iso-dry-bulb temperature lines of state a as the center, and the center passes through the iso-relative temperature lines of states a, b, and c; draw a quadrilateral interval surface perpendicular to the iso-enthalpy line space, wherein the length of the first pair of sides of the quadrilateral is the difference between the iso-dry-bulb temperature lines of states a and c, and the length of the second pair of sides of the quadrilateral is twice the difference between the iso-enthalpy lines of states a and c;

[0071] S4: Obtain the difference between the iso-dry-bulb temperature lines of states a and c and the ratio of the iso-enthalpy lines of states a and c, perform isothermal dehumidification processing on the center to construct a new floating value center, and based on the floating value center, reduce the lengths of two pairs of sides of the quadrilateral interval surface by equal ratio, and use the further optimized quadrilateral interval surface as the control range floating interval of the target area.

[0072] See also Figure 4 The black rectangular box in the figure is the calculated control range floating interval of the target area. Compared with the traditional PID control using a fixed set value, the control range floating interval has higher flexibility and at the same time meets the high-precision temperature and humidity deviation range allowed by the process.

[0073] To further improve the accuracy of the algorithm, see Figure 3The air conditioning energy-saving control device 120 in this embodiment also includes a boundary state control optimization calculation module 123, a wet balance state control optimization calculation module 124, a composite humidification state optimization calculation module 125, a dehumidification out of control state optimization calculation module 126 and a process path optimization calculation module 127 or other auxiliary optimization algorithms, wherein the boundary state control optimization calculation module 123 is used to obtain the compressor boundary state, the wet balance state control optimization calculation module 124, the composite humidification state optimization calculation module 125, and the dehumidification out of control state optimization calculation module 126 are used to calculate the indoor humidity state, so as to avoid the introduction of fresh air to bring additional heat and humidity load, and adopt effective strategies to control the heat and humidity load problem.

[0074] Based on the PID algorithm combined with the dynamic real-time enthalpy-humidity diagram optimization algorithm, one or more algorithms among the boundary state control optimization calculation module 123, the wet balance state control optimization calculation module 124, the compound humidification state optimization calculation module 125, and the dehumidification out-of-control state optimization calculation module 126 are further selected, and the optimal control strategy is selected through the fitting optimization of the process path optimization calculation module 127. By real-time monitoring of the operating status of the air-conditioning system and combining the optimization algorithm on the enthalpy-humidity diagram to analyze the influencing factors of the compressor boundary state and the additional heat and humidity load brought about by the introduction of fresh air, the control range floating interval of the target area is optimized.

[0075] from Figure 5 and Figure 6 It can be seen that by further selecting one or more algorithms in the boundary state control optimization calculation module 123, the wet balance state control optimization calculation module 124, the composite humidification state optimization calculation module 125, and the dehumidification out-of-control state optimization calculation module 126, the energy consumption used is greatly reduced compared to the operating energy consumption of the enthalpy-humidity diagram control path of the traditional control method. For example, the energy consumption of state ab is reduced from the original 345.2643 to the current 236.6258, and the energy consumption of other state points is reduced to varying degrees.

[0076] The wet balance state control optimization calculation module 124, the composite humidification state optimization calculation module 125, and the dehumidification out-of-control state optimization calculation module 126 can adopt the temperature and humidity deviation operation strategy, and by selecting the point with the minimum energy consumption within the deviation value as the set value, the control error is kept within 1 / 2 of the process allowable deviation. In particular, by adopting the temperature and humidity deviation operation strategy in the dehumidification season, the goal of reducing energy consumption while ensuring process requirements is achieved, the dehumidification decision is optimized, and the energy consumption of the air conditioning system is reduced.

[0077] The moisture balance state control optimization calculation module 124 may also calculate the heat and moisture balance by using the sensible heat and latent heat balance, wherein the heat and moisture balance formula is:

[0078]

[0079] Among them, P sen (τ) and M(τ) are the sensible heat part and wet load of the indoor cooling load, cp and ρ are the specific heat capacity and density at constant pressure, V is the indoor volume, v S is the return air volume flow rate, are the indoor air temperature and the supply air temperature, They are the indoor air humidity content and the supply air humidity content (humidity content is defined as the ratio of the mass of water vapor contained in a unit mass of dry air to the mass of dry air), the heat and moisture balance equation, and the indoor hourly cooling load considering sensible heat and latent heat is obtained.

[0080]

[0081] Among them, h is the specific enthalpy of wet air, which is determined by the temperature θ and moisture content d obtained by the heat and moisture balance equation, and the correlation formula is h=1.01θ+0.001d×(2500+1.84θ). Compared with the traditional method that only considers the cooling load caused by temperature changes, this calculation method considers the cooling load caused by temperature and humidity changes at the same time. The formula shows that the cooling load at time τ is determined by the supply air specific enthalpy after participating in the response at this moment and the return air specific enthalpy at the previous moment. The indoor hourly heat load model form of sensible heat and latent heat is consistent with this formula. Only by replacing the equipment power related to heat flow on the right side of the equal sign in the previous formula, the corresponding specific enthalpy change and indoor hourly heat load can be obtained.

[0082] The composite humidification state optimization calculation module 125 can achieve the purpose of cooling the air to a temperature close to its dew point without increasing the humidity by diverting the external hot air to the wet channel and the dry channel, allowing the air in the wet channel to cool down through evaporative cooling and exchange heat with the air in the dry channel, thereby effectively providing an energy-saving and environmentally friendly cooling solution. However, in high-humidity climates, the water vapor content in the air is close to saturation, and the cooling efficiency of evaporative cooling air conditioners is significantly limited. In order to meet the requirements of indoor comfort, it is often used in conjunction with a dehumidification system. Dehumidify the high-humidity air before evaporative cooling to reduce the latent heat load in the air, so that the supply air temperature is lower than the inlet air wet-bulb temperature.

[0083] The dehumidification out-of-control state optimization calculation module 126 is used to calculate the working states of the refrigeration system, humidity transmitter, and circulating fan, fit the working states of the above equipment to the floating range value calculation, and further optimize the real-time floating range value.

[0084] The boundary state control optimization calculation module 123 obtains at least two target points A and B in the regional target, takes the historical boundary states of the target points A and B as the boundary state detection results, performs comprehensive quantitative confirmation on multiple historical boundary state detection results, and obtains the boundary state floating range. When the air-conditioning system is in the boundary state, the temperature and humidity set values ​​are automatically adjusted within the boundary state floating range so that the air-conditioning operation meets the control requirements.

[0085] The boundary state control optimization calculation module 123 uses multiple historical detection results in the dynamic collection process as data support, providing sufficient data analysis while also meeting the optimized boundary state floating range obtained in a similar time under the same working conditions, which is used to improve the intelligent accuracy and output efficiency of the system. It reduces the increase in energy consumption caused by the boundary state, and has a certain energy-saving effect while ensuring the control effect.

[0086] The air conditioning energy-saving control device 120 also includes a surface cooler temperature and humidity control calculation module 129, which is configured to select one or more groups of surface coolers to complete heat exchange work according to different working conditions.

[0087] The process path optimization calculation module 127 is used to fully fit the actual operation path with the optimal path for energy saving, and its fitting optimization method includes:

[0088] Generate forecasts through a variety of optimization algorithms;

[0089] Execute the verification algorithm to calculate the accuracy of the calculated prediction value under the current working conditions;

[0090] A checker that compares multiple validation results and confirms consistency, weighting the contribution of each algorithm based on the accuracy of the validation.

[0091] In order to avoid repeated calculations, the process path optimization calculation module 127 also introduces a method for avoiding repeated verifications, which is used to prevent the same prediction algorithm from being verified multiple times in the same geographical area and time period, thereby improving the calculation speed.

[0092] The air conditioning energy-saving control device 120 is also provided with a real-time control enthalpy-humidity diagram interaction module 128, which is configured to provide a central air conditioning intelligent monitoring system operation and optimal control strategy monitoring interface. Through the user interface and visual operation, a central air conditioning intelligent monitoring system operation interface is provided, which is convenient for operators to monitor the system operation status.

[0093] In this embodiment, the above optimization method is integrated into a software to reduce the number of devices, simplify the system structure, and strengthen the direct integration of the various components of the system to ensure the reliability of operation. The multi-condition enthalpy-humidity diagram partition module 121 and the regional target control optimization calculation module 122, the surface cooler temperature and humidity control calculation module 129, the boundary state control optimization calculation module 123, the wet balance state control optimization calculation module 124, the composite humidification state optimization calculation module 125, the dehumidification out-of-control state optimization calculation module 126 and the process path optimization calculation module 127 can be integrated in the air conditioning energy-saving control device 120, or can be stored in a computer-readable storage medium, which stores instructions. When the instructions are loaded by the computer, the computer executes the central air-conditioning intelligent humidity and temperature deviation energy-saving control method.

[0094] In summary, the central air-conditioning intelligent humidity and temperature deviation energy-saving control method in this embodiment adjusts the PID parameters to adapt to the special needs of the central air-conditioning control system. At the same time, the dynamic real-time enthalpy-humidity diagram is used on the basis of the PID algorithm, and the optimization algorithm on the dynamic real-time enthalpy-humidity diagram is used to further optimize the control range floating interval of the target area, improve the temperature and humidity control accuracy, and facilitate the best control strategy in the later stage;

[0095] This technical solution uses a dynamic real-time enthalpy-humidity diagram based on the PID algorithm to better handle nonlinear problems, making the indoor temperature and humidity have a relatively gentle change trend, improving the stability of the energy-saving control system, and in a continuously changing composite environment, the new optimization algorithm can still stably control the indoor temperature at the set point, further verifying the algorithm's ability to handle nonlinear problems;

[0096] The new optimization algorithm recalculates the control range fluctuation interval of the target area to avoid excessive dehumidification and frequent high-speed operation of the compressor, thereby reducing energy consumption.

[0097] Second embodiment

[0098] This embodiment provides a central air-conditioning intelligent humidity and temperature deviation energy-saving control system based on the first embodiment. Figure 1 and Figure 2 , which includes: an energy-saving server 110, a plurality of air-conditioning energy-saving control devices 120, and the plurality of air-conditioning energy-saving control devices 120 are communicatively connected with the energy-saving server 110.

[0099] In this embodiment, the air conditioning energy-saving control device 120 is provided with two groups, namely the first air conditioning energy-saving control device 120 and the second air conditioning energy-saving control device 120, the first port of the first air conditioning energy-saving control device 120 is connected to the first air conditioning unit 130, the second air conditioning unit 130, the third air conditioning unit 130, and the Nth air conditioning unit 130 are connected in series in sequence, each air conditioning unit 130 is configured with an air conditioning body controller, the Nth air conditioning unit 130 is connected to the second port of the second air conditioning energy-saving control device 120, the second port of the first air conditioning energy-saving control device 120 is connected to the first port of the second air conditioning energy-saving control device 120, the upper energy-saving server 110 and the lower air conditioning body controller energy-saving control software, the energy-saving server 110 and the air conditioning body controller use polling to interact with the air conditioning body controller for operation data, and at the same time, on the basis of the optimization of the air conditioning energy-saving control device 120, it is also necessary to synchronously update the PLC control program of the air conditioning body controller to support the new control strategy. Upgrade the software function of the upper computer monitoring system to cooperate with the intelligent energy-saving monitoring system.

[0100] In this embodiment, each air conditioning unit 130 is equipped with an air conditioning body controller. The structure of each air conditioning unit 130 is shown in FIG. Figure 7 It includes a new return air mixing section 131, a self-cleaning high-efficiency filter section 132, a surface cooling water retaining section 133, a heating section 134, a dry steam humidification section 135, and a blower section 136. Figure 5 The figure shows the entire air conditioning chassis structure. The air flows from left to right in the unit. The new return air mixing section 131 includes a fresh air door and a return air door. The self-cleaning high-efficiency filtration section 132 is composed of components such as the casing, filter assembly, sewage suction device, rotary motor, sewage discharge device, and control system. The surface cooling water retaining section 133 is equipped with three sets of surface coolers and equipped with cold water electric valves. The heating section 134 is equipped with a heating electric valve. The dry steam humidification section 135 is equipped with a humidification electric valve. The blower power of the blower section 136 is 75KW, and the return air fan air volume is 120000m 3 / h.

[0101] The energy-saving server 110 is communicatively connected to any air-conditioning energy-saving control device 120. In order to further improve the system stability of the central air-conditioning intelligent humidity and temperature deviation energy-saving control system, the system can also replace traditional temperature and humidity sensors with intelligent sensors, preferably with remote calibration function to reduce maintenance workload.

[0102] The central air-conditioning intelligent humidity and temperature deviation energy-saving control system also includes a data acquisition and monitoring control device 140 (SCADA). In this embodiment, two data acquisition and monitoring control devices 140 are also provided, namely, a first data acquisition and monitoring control device 140 and a second data acquisition and monitoring control device 140, wherein the two groups of data acquisition and monitoring control devices 140 are cross-fed into two groups of air-conditioning energy-saving control devices 120, that is, the first data acquisition and monitoring control device 140 is respectively connected to the first air-conditioning energy-saving control device 120 and the second air-conditioning energy-saving control device 120, and the second data acquisition and monitoring control device 140 is also respectively connected to the first air-conditioning energy-saving control device 120 and the second air-conditioning energy-saving control device 120. The first data acquisition and monitoring control device 140 is connected to the first operator station 150 for communication, and the second data acquisition and monitoring control device 140 is connected to the second operator station 150 for communication, and is used to present the real-time control enthalpy-humidity diagram interactive module 128 to the operator for display or control.

[0103] The air conditioning energy-saving control device 120 improves control accuracy and reduces energy consumption of air conditioning through optimization algorithms. It does so by setting a multi-condition enthalpy-humidity diagram partitioning module 121 and a regional target control optimization calculation module 122 in the air conditioning energy-saving control device 120. These two optimization calculation modules optimize control parameters through a PID algorithm combined with a dynamic real-time enthalpy-humidity diagram optimization algorithm.

[0104] Specifically, the multi-condition enthalpy-humidity diagram partitioning module 121 and the regional target control optimization calculation module 122 are configured as follows:

[0105] Obtain dynamic real-time enthalpy-humidity diagrams under different working conditions, and divide the dynamic real-time enthalpy-humidity diagrams into different target areas;

[0106] Calculate states a and b in the target area using the PID algorithm, and use the midpoint state c of the line connecting states a and b as the mixed state point;

[0107] Obtain the isohumidities of states a, b, and c, as well as the iso-dry-bulb temperature lines and iso-enthalpy lines of states a and c, and take the intersection of the isohumidities and the iso-dry-bulb temperature lines of state a as the center, and the center passes through the iso-relative temperature lines of states a, b, and c; draw a quadrilateral interval surface perpendicular to the iso-enthalpy line space, where the length of the first pair of sides of the quadrilateral is the difference between the iso-dry-bulb temperature lines of states a and c, and the length of the second pair of sides of the quadrilateral is twice the difference between the iso-enthalpy lines of states a and c;

[0108] Obtain the difference between the iso-dry-bulb temperature lines of states a and c and the ratio of the iso-enthalpy lines of states a and c, perform isothermal dehumidification processing on the center to construct a new floating value center, and based on the floating value center, reduce the lengths of two pairs of sides of the quadrilateral interval surface by equal ratio, and use the further optimized quadrilateral interval surface as the control range floating interval of the target area.

[0109] This embodiment also makes improvements to the surface cooler, see Figure 8 In view of the defect that a more sophisticated control strategy cannot be achieved by using one cooling valve to control the opening of multiple cooling units at the same time in the prior art, a new valve is installed on the cooling unit in this embodiment, so that it can control different cooling units separately by dividing the valves into multiple groups. When the required load is not large, energy-saving control can be performed by opening only one group of cooling units. At the same time, a new control algorithm is developed to support the separate opening or closing of multiple groups of valves, thereby improving the energy efficiency ratio of the system and reducing the operating cost.

[0110] In terms of hardware, the system is upgraded and necessary hardware is installed, such as communication slave stations, I / O modules and communication modules, so as to increase the number of I / O points and communication modules to meet higher control requirements. The surface cooler is also simply modified to make it suitable for the new control system.

[0111] The cooler material can also be improved, such as using materials with higher thermal conductivity or composite materials, to improve the heat exchange efficiency of the cooler itself and reduce energy consumption.

[0112] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0113] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, or it can be an electrical, mechanical or other form of connection.

[0114] The units described as separate components may or may not be physically separated. As a unit, it can be appreciated by those skilled in the art that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0115] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0116] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a grid device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0117] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A central air-conditioning intelligent humidity and temperature deviation energy-saving control method, characterized in that: The invention comprises an energy-saving server and a plurality of air-conditioning energy-saving control devices which are connected to the energy-saving server in communication, each of which controls one or more air-conditioning units; the air-conditioning energy-saving control device has a built-in multi-condition enthalpy-humidity diagram partition module and a regional target control optimization calculation module, the multi-condition enthalpy-humidity diagram partition module and the regional target control optimization calculation module optimize the control parameters by combining the PID algorithm with the dynamic real-time enthalpy-humidity diagram optimization algorithm, and the calculation steps of the PID algorithm combined with the dynamic real-time enthalpy-humidity diagram optimization algorithm include: Acquire dynamic real-time enthalpy-humidity diagrams under different working conditions, and divide the dynamic real-time enthalpy-humidity diagrams into different target areas; Calculate states a and b in the target area by using a PID algorithm, and use state c, the midpoint of the line connecting states a and b, as a mixed state point; Obtain isohumidities of states a, b, and c, as well as iso-dry-bulb temperature lines and isoenthalpy lines of states a and c, take the intersection of the isohumidities and iso-dry-bulb temperature lines of state a as the center, and the center passes through the iso-relative temperature lines of states a, b, and c; draw a quadrilateral interval surface perpendicular to the isoenthalpy line space, wherein the length of the first pair of sides of the quadrilateral is the difference between the iso-dry-bulb temperature lines of states a and c, and the length of the second pair of sides of the quadrilateral is twice the difference between the isoenthalpy lines of states a and c; Obtain the difference between the iso-dry-bulb temperature lines of states a and c and the ratio of the iso-enthalpy lines of states a and c, perform isothermal dehumidification processing of the ratio on the center to construct a new floating value center, based on the floating value center, reduce the lengths of two pairs of sides of the quadrilateral interval surface by the ratio, and use the further optimized quadrilateral interval surface as the control range floating interval of the target area.

2. The central air-conditioning intelligent humidity and temperature deviation energy-saving control method according to claim 1 is characterized in that: The air conditioner energy-saving control device also includes a surface cooler temperature and humidity control calculation module, which is configured to select one or more groups of surface coolers to complete heat exchange work according to different working conditions.

3. The central air-conditioning intelligent humidity and temperature deviation energy-saving control method according to claim 1 is characterized in that: The air conditioning energy-saving control device also includes a boundary state control optimization calculation module, a wet balance state control optimization calculation module, a compound humidification state optimization calculation module, a dehumidification out of control state optimization calculation module and a process path optimization calculation module. Based on the PID algorithm combined with the dynamic real-time enthalpy-humidity diagram optimization algorithm, one or more algorithms among the boundary state control optimization calculation module, the wet balance state control optimization calculation module, the compound humidification state optimization calculation module and the dehumidification out of control state optimization calculation module are further selected, and the optimal control strategy is selected through the process path optimization calculation module fitting optimization.

4. The central air-conditioning intelligent humidity and temperature deviation energy-saving control method according to claim 3 is characterized in that: The boundary state control optimization calculation module obtains at least two target points A and B in the regional target, takes the historical boundary states of the target points A and B as the boundary state detection results, and comprehensively quantifies and confirms multiple historical boundary state detection results to obtain the boundary state floating range. When the air-conditioning system is in the boundary state, the temperature and humidity set values ​​are automatically adjusted within the boundary state floating range so that the air-conditioning operation meets the control requirements.

5. The central air-conditioning intelligent humidity and temperature deviation energy-saving control method according to claim 3 is characterized in that: The wet balance state control optimization calculation module, the composite humidification state optimization calculation module, and the dehumidification out-of-control state optimization calculation module are configured to adopt a temperature and humidity deviation operation strategy, and by selecting the point with the minimum energy consumption within the deviation value as the set value, the control error is kept within 1 / 2 of the process allowable deviation.

6. The central air-conditioning intelligent humidity and temperature deviation energy-saving control method according to claim 3 is characterized in that: The fitting optimization method of the process path optimization calculation module includes: Generate forecasts through a variety of optimization algorithms; Execute the verification algorithm to calculate the accuracy of the calculated prediction value under the current working conditions; A checker that compares multiple validation results and confirms consistency, weighting the contribution of each algorithm based on the accuracy of the validation.

7. The central air-conditioning intelligent humidity and temperature deviation energy-saving control method according to claim 1 is characterized in that: The air conditioning energy-saving control device is also provided with a real-time control enthalpy-humidity diagram interaction module, and the real-time control enthalpy-humidity diagram interaction module is configured to provide a central air conditioning intelligent monitoring system operation and optimal control strategy monitoring interface.

8. The central air-conditioning intelligent humidity and temperature deviation energy-saving control method according to claim 1 is characterized in that: The multi-condition enthalpy-humidity diagram partitioning module and regional target control optimization calculation module, surface cooler temperature and humidity control calculation module, boundary state control optimization calculation module, moisture balance state control optimization calculation module, composite humidification state optimization calculation module, dehumidification out-of-control state optimization calculation module and process path optimization calculation module are integrated in the air conditioning energy-saving control device.

9. A central air-conditioning intelligent humidity and temperature deviation energy-saving control system, characterized in that: include: Energy-saving servers, An air conditioning energy-saving control device, wherein a plurality of air conditioning energy-saving control devices are communicatively connected to an energy-saving server, wherein a multi-operating-condition enthalpy-humidity diagram partition module and a regional target control optimization calculation module in the air conditioning energy-saving control device optimize control parameters by combining a PID algorithm with a dynamic real-time enthalpy-humidity diagram optimization algorithm, and wherein the multi-operating-condition enthalpy-humidity diagram partition module and the regional target control optimization calculation module are configured as follows: Acquire dynamic real-time enthalpy-humidity diagrams under different working conditions, and divide the dynamic real-time enthalpy-humidity diagrams into different target areas; Calculate states a and b in the target area by using a PID algorithm, and use state c, the midpoint of the line connecting states a and b, as a mixed state point; Obtain isohumidities of states a, b, and c, as well as iso-dry-bulb temperature lines and isoenthalpy lines of states a and c, take the intersection of the isohumidities and iso-dry-bulb temperature lines of state a as the center, and the center passes through the iso-relative temperature lines of states a, b, and c; draw a quadrilateral interval surface perpendicular to the isoenthalpy line space, wherein the length of the first pair of sides of the quadrilateral is the difference between the iso-dry-bulb temperature lines of states a and c, and the length of the second pair of sides of the quadrilateral is twice the difference between the isoenthalpy lines of states a and c; Obtain the difference between the iso-dry-bulb temperature lines of states a and c and the ratio of the iso-enthalpy lines of states a and c, perform isothermal dehumidification processing of the ratio on the center to construct a new floating value center, based on the floating value center, reduce the lengths of two pairs of sides of the quadrilateral interval surface by the ratio, and use the further optimized quadrilateral interval surface as the control range floating interval of the target area.

10. The central air-conditioning intelligent humidity and temperature deviation energy-saving control system according to claim 9 is characterized in that: The air conditioning energy-saving control device controls a group of air conditioning units, which include a new return air mixing section, a self-cleaning high-efficiency filter section, a surface cooling water retaining section, a heating section, a dry steam humidification section, and a blower section which are arranged in sequence.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are loaded by the computer, the computer executes the central air-conditioning intelligent humidity and temperature deviation energy-saving control method as described in any one of claims 1 to 8.

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