An air conditioner temperature and humidity set value control method
By collecting air conditioning system parameters in real time to calculate sensible heat and humidity load, and dynamically optimizing temperature and humidity setpoints, the energy consumption problem of the air conditioning system when the external environment changes is solved, achieving energy saving and intelligent control.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- GUANGZHOU ZHIHANDA ENERGY SAVING TECHNOLOGY CO LTD
- Filing Date
- 2026-04-08
- Publication Date
- 2026-06-09
AI Technical Summary
Existing air conditioning systems cannot adaptively adjust temperature and humidity settings when the external environment changes, resulting in unnecessary increases in energy consumption.
By collecting the fresh air, return air, and supply air parameters of the air conditioning system in real time, calculating the sensible heat load and humidity load, traversing temperature and humidity nodes, and selecting the temperature and humidity setpoints with the lowest total energy consumption or the lowest cost, the operating parameters of the air conditioning system can be dynamically optimized.
While ensuring that the controlled environment meets the requirements of the production process, it effectively reduces the energy consumption and operating costs of the air conditioning system, and improves the energy efficiency ratio and intelligent control.
Smart Images
Figure CN122170502A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of energy-saving control technology for air conditioning systems, specifically a method for controlling the setpoints of air conditioning temperature and humidity. Background Technology
[0002] Existing automatic air conditioning systems typically employ fixed setpoint control, where operators pre-set target temperature and humidity values for the controlled environment based on experience. The system's automatic controller then compares the measured temperature and humidity values with the set values, driving the actuators to adjust and maintain the environment's temperature and humidity within the set range. However, during operation, the temperature and humidity of the external environment (fresh air) fluctuate significantly with sunlight duration, weather changes, and seasonal changes. Especially in regions influenced by subtropical monsoon climates, extreme weather conditions such as heavy rain can cause drastic changes in fresh air temperature and humidity. Because the setpoints are determined manually and remain fixed, they cannot adaptively adjust to real-time changes in external environmental parameters. When external temperature and humidity fluctuate, the fixed setpoints may deviate from the optimal values for the current operating conditions, resulting in unnecessary energy consumption: if the setpoints are too low, cooling or dehumidification will increase unnecessarily; if they are too high, heating or humidification will increase unnecessarily, thus increasing the system's energy consumption. Summary of the Invention
[0003] This invention provides a control method that can automatically and intelligently adjust the setpoints of air conditioning temperature and humidity according to changes in external ambient temperature and humidity and changes in on-site heat and humidity load, so as to achieve energy-saving operation of the air conditioning system.
[0004] The air conditioning temperature and humidity setpoint control method of the present invention includes the following steps:
[0005] Step A: Environmental Data Acquisition: Real-time acquisition of environmental parameters for the fresh air, return air, and supply air of the automatic control air conditioning system. In the case of a 100% fresh air air conditioning system, exhaust air is selected instead of return air. The environmental parameters include temperature and relative humidity. The fresh air represents the external environmental parameters, and the return air represents the controlled environmental parameters.
[0006] Step B: Calculation of heat and humidity load: Based on the environmental parameters collected in Step A, calculate the sensible heat load and humidity load of the controlled environment, wherein the sensible heat load is determined based on the difference between the return air temperature and the supply air temperature, and the humidity load is determined based on the difference between the absolute humidity of the return air and the absolute humidity of the supply air.
[0007] Step C: Determine the optimal temperature and humidity setpoints: Within the preset allowable temperature and humidity range, divide the temperature and relative humidity values into a series of discrete temperature and humidity nodes according to preset intervals, and perform the following calculations for each temperature and humidity node:
[0008] C1: Assume the current temperature and humidity node as the temperature and humidity setpoint. Combine the fresh air environment parameters collected in step A and the sensible heat load, moisture load calculated in step B, as well as the known supply air volume, fresh air ratio, and primary return air ratio. The supply air volume, fresh air ratio, and primary return air ratio are determined during the commissioning of the air conditioning system. Calculate the cooling load, heating load, and humidification energy required for the air conditioning to operate at this temperature and humidity node.
[0009] The fresh air ratio is the ratio of fresh air volume to total supply air volume, the primary return air ratio is the ratio of primary return air volume to total supply air volume, and the secondary return air ratio = 1 - fresh air ratio - primary return air ratio;
[0010] C2: Convert the cooling load, heating load, and humidification energy consumption into corresponding electricity consumption, and sum them up to obtain the total energy consumption of the temperature and humidity node; or, multiply the cooling load, heating load, and humidification energy consumption by the corresponding energy cost unit price, and sum them up to obtain the total energy cost of the temperature and humidity node.
[0011] C3: Traverse all temperature and humidity nodes, compare the total energy consumption or total energy cost of each node, and select the temperature and humidity node with the lowest total energy consumption or the lowest total energy cost as the preferred temperature and humidity setting value.
[0012] The aforementioned air conditioning temperature and humidity setpoint control method collects environmental parameters such as temperature and relative humidity of the fresh air, return air, and supply air of the air conditioning system in real time, and intelligently calculates the heat and humidity load of the controlled environment, as well as known parameters such as supply air volume, fresh air ratio, and primary return air ratio. Within the preset allowable temperature and humidity range, it traverses each discrete temperature and humidity node, calculates the cooling load, heating load, and humidification energy consumption, and converts the cooling load, heating load, and humidification energy consumption into corresponding power consumption, summing them to obtain the total energy consumption of the temperature and humidity node; or, it multiplies the cooling load, heating load, and humidification energy consumption by the corresponding energy cost unit price to obtain the total energy cost of the temperature and humidity node. This automatically selects the temperature and humidity setpoint with the lowest energy consumption or the lowest energy cost, achieving the effect of dynamically optimizing the operating parameters of the air conditioning system according to changes in the external environment and on-site heat and humidity load. While ensuring that the controlled environment meets the production process requirements, it effectively reduces the energy consumption and operating costs of the air conditioning system, improves the energy saving rate, and significantly enhances the energy efficiency ratio and intelligent control of the air conditioning system. Attached Figure Description
[0013] Figure 1 This is a schematic diagram of the air conditioning system and a table of air handling process parameters for Example 1.
[0014] Figure 2 This is a schematic diagram illustrating four scenarios of the air conditioning energy consumption calculation process in Example 1.
[0015] Figure 3 This is a schematic diagram of the main interface of the program in working condition 1 of Example 1.
[0016] Figure 4 This is a schematic diagram of the operating parameters of the lowest energy consumption node in operating condition 1 of Example 1.
[0017] Figure 5 This is a schematic diagram of the normal setting node operation parameters for working condition 1 of Example 1.
[0018] Figure 6 This is a schematic diagram of the main interface of the program in working condition 2 of Example 1.
[0019] Figure 7 This is a schematic diagram of the operating parameters of the lowest energy consumption node in operating condition 2 of Example 1.
[0020] Figure 8 This is a schematic diagram of the normal setting node operation parameters for working condition 2 in Example 1.
[0021] Figure 9 This is a schematic diagram of the main interface of the program in working condition 3 of Example 1.
[0022] Figure 10 This is a schematic diagram of the operating parameters of the lowest energy consumption node in operating condition 3 of Example 1.
[0023] Figure 11 This is a schematic diagram of the normal setting node operation parameters for working condition 3 in Example 1.
[0024] Figure 12 This is a schematic diagram of the air conditioning system and a table of air handling process parameters for Example 2.
[0025] Figure 13 This is a schematic diagram illustrating four scenarios of the air conditioning energy consumption cost calculation process in Example 2.
[0026] Figure 14 This is a schematic diagram of the main interface of the program in working condition 1 of Example 2.
[0027] Figure 15 This is a schematic diagram of the operating parameters of the lowest energy consumption cost node in operating condition 1 of Example 2.
[0028] Figure 16 This is a schematic diagram of the normal setting node operation parameters for working condition 1 in Example 2.
[0029] Figure 17 This is a schematic diagram of the main interface of the program in working condition 2 of Example 2.
[0030] Figure 18 This is a schematic diagram of the operating parameters of the lowest energy consumption cost node in operating condition 2 of Example 2.
[0031] Figure 19 This is a schematic diagram of the normal setting node operation parameters for working condition 2 in Example 2.
[0032] Figure 20 This is a schematic diagram of the main interface of the program in working condition 3 of Example 2.
[0033] Figure 21 This is a schematic diagram of the operating parameters of the lowest energy consumption cost node in operating condition 3 of Example 2.
[0034] Figure 22 This is a schematic diagram of the normal setting node operation parameters for working condition 3 in Example 2. Detailed Implementation
[0035] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.
[0036] It should be noted that if the embodiments of the present invention involve directional indicators (such as up, down, left, right, front, back, top, bottom, inside, outside, vertical, horizontal, longitudinal, counterclockwise, clockwise, circumferential, radial, axial, etc.), the directional indicators are only used to explain the relative positional relationship and movement of the components in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indicators will also change accordingly.
[0037] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installed," "set," "equipped with," "connected," and "linked" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention based on the specific circumstances.
[0038] If the embodiments of this invention involve descriptions such as "first" or "second," such descriptions are for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined with "first" or "second" may explicitly or implicitly include at least one of those features. In the description of this invention, "several" means one or more, "multiple" means two or more, and "above," "below," and "within" are all understood to include the stated number. Furthermore, the technical features of each embodiment can be arbitrarily combined. For the sake of brevity, not all possible combinations of the technical features in the embodiments are described; however, as long as these combinations of technical features do not contradict each other, they should be considered within the scope of this specification.
[0039] A method for controlling the temperature and humidity setpoint of an air conditioner includes the following steps:
[0040] Step A: Environmental Data Acquisition: Real-time acquisition of environmental parameters for the fresh air, return air, and supply air of the automatic control air conditioning system. In the case of a 100% fresh air air conditioning system, exhaust air is selected instead of return air. The environmental parameters include temperature and relative humidity. The fresh air represents the external environmental parameters, and the return air represents the controlled environmental parameters.
[0041] Step B: Calculation of heat and humidity load: Based on the environmental parameters collected in Step A, calculate the sensible heat load and humidity load of the controlled environment, wherein the sensible heat load is determined based on the difference between the return air temperature and the supply air temperature, and the humidity load is determined based on the difference between the absolute humidity of the return air and the absolute humidity of the supply air.
[0042] Step C: Determine the optimal temperature and humidity setpoints: Within the preset allowable temperature and humidity range, divide the temperature and relative humidity values into a series of discrete temperature and humidity nodes according to preset intervals, and perform the following calculations for each temperature and humidity node:
[0043] C1: Assume the current temperature and humidity node as the temperature and humidity setpoint. Combine the fresh air environment parameters collected in step A and the sensible heat load, moisture load calculated in step B, as well as the known supply air volume, fresh air ratio, and primary return air ratio. The supply air volume, fresh air ratio, and primary return air ratio are determined during the commissioning of the air conditioning system. Calculate the cooling load, heating load, and humidification energy required for the air conditioning to operate at this temperature and humidity node.
[0044] The fresh air ratio is the ratio of fresh air volume to total supply air volume, the primary return air ratio is the ratio of primary return air volume to total supply air volume, and the secondary return air ratio = 1 - fresh air ratio - primary return air ratio;
[0045] C2: Convert the cooling load, heating load, and humidification energy consumption into corresponding electricity consumption, and sum them up to obtain the total energy consumption of the temperature and humidity node; or, multiply the cooling load, heating load, and humidification energy consumption by the corresponding energy cost unit price, and sum them up to obtain the total energy cost of the temperature and humidity node.
[0046] C3: Traverse all temperature and humidity nodes, compare the total energy consumption or total energy cost of each node, and select the temperature and humidity node with the lowest total energy consumption or the lowest total energy cost as the preferred temperature and humidity setting value.
[0047] The aforementioned air conditioning temperature and humidity setpoint control method collects environmental parameters such as temperature and relative humidity of the fresh air, return air, and supply air of the air conditioning system in real time, and intelligently calculates the heat and humidity load of the controlled environment, as well as known parameters such as supply air volume, fresh air ratio, and primary return air ratio. Within the preset allowable temperature and humidity range, it traverses each discrete temperature and humidity node, calculates the cooling load, heating load, and humidification energy consumption, and converts the cooling load, heating load, and humidification energy consumption into corresponding power consumption, summing them to obtain the total energy consumption of the temperature and humidity node; or, it multiplies the cooling load, heating load, and humidification energy consumption by the corresponding energy cost unit price to obtain the total energy cost of the temperature and humidity node. This automatically selects the temperature and humidity setpoint with the lowest energy consumption or the lowest energy cost, achieving the effect of dynamically optimizing the operating parameters of the air conditioning system according to changes in the external environment and on-site heat and humidity load. While ensuring that the controlled environment meets the production process requirements, it effectively reduces the energy consumption and operating costs of the air conditioning system, improves the energy saving rate, and significantly enhances the energy efficiency ratio and intelligent control of the air conditioning system.
[0048] In step B: Sensible heat load = return air temperature - supply air temperature; Humidity load = return air absolute humidity - supply air absolute humidity. Furthermore, a method for determining the applicability of environmental sampling data is established: the controlled environment temperature and humidity values must reach a set range. Only when the return air temperature and humidity samples are taken n consecutively, and both temperature and relative humidity are within the set range, can it be determined that the air conditioning system has reached equilibrium. Only the environmental data from the last sample is used to calculate and derive the optimal temperature and humidity setpoints. By setting a method to determine the applicability of environmental sampling data: a range is set for the controlled environment's temperature and humidity values (where the temperature range can be set to ±0.1℃ and the humidity range can be set to ±0.2% of the set relative humidity). Only when the return air temperature and humidity sampling values are continuously sampled n times (up to 3 times), and both the temperature and relative humidity are within the set range, can it be determined that the air conditioning system has reached a balanced state. Only the environmental data from the last sampling is used to calculate and derive the optimal temperature and humidity setpoints. This provides reliable load data for the subsequent derivation of the optimal temperature and humidity setpoints, thereby ensuring the accuracy of the calculation of cooling capacity, heating capacity, and humidification capacity. This improves the accuracy and reliability of the selection of optimal temperature and humidity setpoints, enabling the air conditioning system to maintain a stable, efficient, and energy-saving operating state under different external environmental conditions and operating conditions.
[0049] The preset intervals mentioned in step C are adjusted according to the CPU's computing power and the air conditioning control precision requirements. The temperature interval is 0.1℃, and the relative humidity interval is 0.1%. By setting the temperature and relative humidity intervals to a fine division of 0.1℃ and 0.1% respectively, a high-density discrete node mesh is formed within the preset temperature and humidity allowable range. This significantly reduces the search step size for the optimal temperature and humidity setpoints, thereby greatly improving the positioning accuracy of the optimal energy consumption solution. This ensures that the selected temperature and humidity setpoints are closer to the actual minimum energy consumption point, maximizing energy savings while ensuring that the controlled environment's temperature and humidity meet the stringent requirements of the production process.
[0050] Step C further includes: C4: Outputting the preferred temperature and humidity setpoints determined in step C3 to the controller of the automatic air conditioning system, replacing the original temperature and relative humidity setpoints, thereby achieving automatic change of the temperature and humidity setpoints. By automatically outputting the preferred temperature and humidity setpoints determined in step C3 to the air conditioning system controller and replacing the original setpoints in real time, closed-loop control of temperature and humidity setpoints from intelligent calculation to automatic execution is achieved, allowing for dynamic adjustment of operating parameters based on changes in the external environment and fluctuations in heat and humidity loads without manual intervention.
[0051] Furthermore, an environmental data acquisition and calculation interval is set. The sampling and calculation interval is set according to the changes in the heat and humidity load of the external environment or the controlled environment. The sampling and calculation interval can be set to 10 minutes to ensure that the air conditioning system is basically in an automatic operation state with optimal energy consumption or lowest cost. This significantly improves the intelligence level and response speed of the control system, effectively avoids energy waste caused by manual setting deviations or delayed adjustments, and further ensures the stability and continuity of energy-saving effects.
[0052] In step C, a loop traversal algorithm is used to calculate and compare all temperature and humidity nodes. The loop traversal algorithm includes: using the boundary value of the allowable temperature and humidity range as the loop boundary value, and using a preset interval as the step size, calculating the total energy consumption or total energy cost of each temperature and humidity node in turn. After the traversal is completed, the optimal temperature and humidity set value is output, so that the air conditioning system can quickly respond to changes in the external environment and switch to the operating condition with the lowest energy consumption or the best cost in a timely manner, thereby enhancing practicality and real-time performance.
[0053] The preset temperature and humidity allowable ranges are determined according to production process requirements, with the temperature allowable range being 20℃~24℃ and the relative humidity allowable range being 50%~60%. By limiting the temperature and humidity allowable ranges to the temperature requirements of 20℃~24℃ and the relative humidity to 50%~60%, the system intelligently optimizes and determines the temperature and humidity setpoints with the lowest energy consumption or optimal cost within this constraint range, while ensuring product quality and production safety. This avoids the risk of exceeding process limits in pursuit of extreme energy saving, achieving an organic unity between process compliance and energy-saving economy, and making the optimized control of the air conditioning system more closely aligned with the needs of actual industrial application scenarios.
[0054] Example 1
[0055] Assuming the regional atmospheric pressure is P0 = 101325 Pa and the total air supply volume is G = 20000 m³ / s 3 / h, air density ρ=1.2Kg / m³ 3 The fresh air ratio α = 15%, the primary return air ratio β = 15%, the required reference temperature range for the production process is 20℃~24℃, and the required reference relative humidity range is 50%~60%. Chilled water is the cold source, steam is the heating and humidifying heat source, the coefficient of performance (COP) is Kl = 3, the coefficient of performance (COP) is Kr = 1, the coefficient of performance (COP) is Kq = 1, and the fan temperature rise is T. d =0.5℃ (can be provided by the manufacturer or measured on-site), relative humidity after dehumidification Y4=93% (determined by the number of coils in the cooling coil, can be provided by the manufacturer or measured on-site), air conditioning system schematic diagram and air handling process parameter table as follows Figure 1 As shown. For example, if the indoor temperature is set to X... 11 The relative humidity is set to Y. 11 When the air conditioning system reaches equilibrium, the energy consumption calculation and the derivation of the optimal temperature and humidity setpoints are as follows:
[0056] 1. Calculate the saturated water vapor partial pressures P11 and P12, moisture contents Z1 and Z2 of the fresh air and return air, and (return air temperature X2 = X 11 The relative humidity of the return air is Y2=Y 11 Supply air moisture content Z 10 =Z 11 -Z0);
[0057] P11=610.69*10^(7.5*X1 / (237.3+X1));
[0058] Z1 = 622 * Y1 * P11 / (P0 - Y1 * P11);
[0059] P12=610.69*10^(7.5*X2 / (237.3+X2));
[0060] Z2 = 622 * Y2 * P12 / (P0 - Y1 * P12);
[0061] 2. Calculate the temperature X3 and moisture content Z3 at the primary mixing point;
[0062] X3=(a*X1+b*X2) / (a+b)=(a*X1+b*X 11 ) / (a+b);
[0063] Z3=(a*Z1+b*Z2) / (a+b)=(a*Z1+b*Z 11 ) / (a+b);
[0064] 3. Compare Z3 and Z 11 -Z0 / (a+b) is the size, when Z3>Z 11 When -Z0 / (a+b), the air conditioning system is in dehumidification mode; when Z3 <Z 11 When -Z0 / (a+b), the air conditioning system is in humidification mode.
[0065] 3.1 Energy consumption calculation under dehumidification conditions:
[0066] 3.1.1. Calculate the moisture content Z4 after dehumidification, the partial pressure of saturated water vapor P14 (pa), the temperature X4, the enthalpy H3 at the primary mixing point, and the enthalpy H4 after dehumidification. Calculate the dehumidification cooling capacity Ql4.
[0067] Z4=Z 11 -Z0 / (a+b);
[0068] P14 = Z4 * P0 / (Y4 * (622 + Z4));
[0069] X4==237.3 / ((7.5 / lg(P14 / 610.7)-1);
[0070] H3=1.01*X3+(2500+1.84*X3)Z3* / 1000;
[0071] H4=1.01*X4+(2500+1.84*X4)Z4* / 1000;
[0072] Ql4=1.2*G*(a+b)*(H3-H4) / 3600;
[0073] 3.1.2. Calculate the temperature X6 and moisture content Z6 at the secondary mixing point, the temperature X7 and moisture content Z7 after the secondary surface cooling, and the temperature X8 and moisture content Z8 after the heater;
[0074] X6 = X4(a+b) + X 11 (1-ab);
[0075] Z6=Z 11 -Z0;
[0076] X7=X 11 -X0-T d ;
[0077] Z7=Z 11 -Z0;
[0078] X8=X 11 -X0-T d ;
[0079] Z8=Z 11 -Z0;
[0080] 3.1.3. When X⁴(a+b)+X 11 (1-ab)>X 11 -X0-T d At this time, cooling is required, and the enthalpy of the secondary mixing point H6, the enthalpy of the secondary surface cooling H7, and the cooling capacity Ql7 are calculated.
[0081] H6=1.01*X6+(2500+1.84*X6)Z6* / 1000;
[0082] H7=1.01*X7+(2500+1.84*X7)Z7* / 1000;
[0083] Ql7 = 1.2 * G * (H6 - H7) / 3600;
[0084] Total energy consumption Q = (Ql4 + Ql7) / Kl;
[0085] 3.1.4. When X⁴(a+b)+X 11 (1-ab) <X 11 -X0-T d When heating is required, the enthalpy H6 at the secondary mixing point, the enthalpy H8 after the heater, and the heating amount Qr8 are calculated.
[0086] H6=1.01*X6+(2500+1.84*X6)Z6* / 1000;
[0087] H8=1.01*X8+(2500+1.84*X8)Z7* / 1000;
[0088] Qr8 = 1.2 * G * (H8 - H6) / 3600;
[0089] Total energy consumption Q = Ql⁴ / Kl + Qr⁸ / Kr;
[0090] 3.2. Energy consumption calculation under humidification conditions:
[0091] 3.2.1. Calculate the temperature X6, moisture content Z6, enthalpy H6 at the secondary mixing point, the temperature X7, moisture content Z7, enthalpy H7 after the second-stage surface cooling, the temperature X8, moisture content Z8, enthalpy H8 after the heater, the temperature X9, moisture content Z9, enthalpy H9 after humidification, and the humidification energy consumption Qq9;
[0092] X6 = a * X1 + (1 - a) * X 11 ;
[0093] Z6 = a * Z1 + (1 - a) * Z 11 ;
[0094] H6=1.01*X6+(2500+1.84*X6)Z6* / 1000;
[0095] X7=X 11 -X0-T d ;
[0096] Z7 = a * Z1 + (1 - a) * Z 11 ;
[0097] H7=1.01*X7+(2500+1.84*X7)Z7* / 1000;
[0098] X8=X 11 -X0-T d ;
[0099] Z8 = a * Z1 + (1 - a) * Z 11 ;
[0100] H8=1.01*X8+(2500+1.84*X8)Z7* / 1000;
[0101] X9=X 11 -X0-T d ;
[0102] Z9=Z 11 -Z0;
[0103] H9=1.01*X9+(2500+1.84*X9)Z9* / 1000;
[0104] Qq9 = 1.2 * G * (H9 - H8) / 3600;
[0105] 3.2.2. When a*Z1+(1-a)*Z 11 >X 11 -X0-T d When cooling is required, the cooling capacity Ql7 should be calculated.
[0106] Ql7 = 1.2 * G * (H6 - H7) / 3600;
[0107] Total energy consumption Q = Ql7 / Kl + Qq9 / Kq;
[0108] 3.2.3.When a*Z1+(1-a)*Z 11 <X 11 -X0-T d When heating is required, the amount of heat required for heating should be calculated as Qr8.
[0109] Qr8 = 1.2 * G * (H8 - H6) / 3600;
[0110] Total energy consumption Q = Qr8 / Kr + Qq9 / Kq;
[0111] The diagrams illustrating four scenarios in the air conditioning energy consumption calculation process are shown below. Figure 2 As shown.
[0112] 4. Within a temperature range of 20℃ to 24℃ and a relative humidity range of 50% to 60%, a grid is formed by pre-setting temperature intervals of 0.1℃ and relative humidity intervals of 0.1%. The temperature and humidity values for each node are then calculated sequentially (i.e., the temperature and humidity of each node are substituted into X). 11 Y 11 The total energy consumption is calculated, and after traversing through the data, the minimum value and its corresponding temperature and humidity nodes are recorded, and the optimal temperature and humidity settings are output.
[0113] 5. Based on the above air handling process logic and calculation formula, write a PLC program to calculate and derive the optimal temperature and humidity setpoints.
[0114] In Example 1, under condition 1, when the fresh air temperature is 12℃ and the fresh air relative humidity is 50%, the system sensible heat load X0 = 1.5℃ (return air temperature - supply air temperature), and the system moisture load Z0 = 0.3g / Kg (return air absolute humidity - supply air absolute humidity). The program calculates that within the temperature range of 20℃~24℃ and the relative humidity range of 50%~60%, the energy consumption at the lowest energy consumption node is 3.3KW, corresponding to a temperature and humidity of 20.0℃ and 50.0%, respectively. Therefore, the preferred setting temperature is 20.0℃ and the preferred setting relative humidity is 50.0%. Compared to the conventional setting temperature of 22℃ and relative humidity of 55%, which consumes 7.2KW, the air conditioning system operating at this preferred temperature and humidity saves 3.9kW, representing an energy saving rate of 54%. The program's main interface and operating parameters are as follows:
[0115] 1. The main interface of the program is as follows: Figure 3 As shown;
[0116] 2. Operating parameters of the lowest energy consumption node are as follows: Figure 4 As shown;
[0117] 3. Standard node operation parameters are set as follows: Figure 5 As shown.
[0118] In Scenario 1, Condition 2, when the fresh air temperature is 20℃ and the fresh air relative humidity is 55%, the system sensible heat load X0 = 1.8℃ (return air temperature - supply air temperature), and the system moisture load Z0 = 0.3g / Kg (return air absolute humidity - supply air absolute humidity). The program calculates that within the temperature range of 20℃ to 24℃ and the relative humidity range of 50% to 60%, the energy consumption at the lowest energy consumption node is 3.9KW, corresponding to a temperature and humidity of 24.0℃ and 55.9%, respectively. Therefore, the preferred setting temperature is 24.0℃, and the preferred setting relative humidity is 55.9%. Compared to the conventional setting temperature of 22℃ and relative humidity of 55%, which consumes 13.4KW, the air conditioning system operating at this preferred temperature and humidity saves 9.6kW, achieving an energy saving rate of 71%. The program's main interface and operating parameters are as follows:
[0119] 1. The main interface of the program is as follows: Figure 6 As shown;
[0120] 2. Operating parameters of the lowest energy consumption node are as follows: Figure 7 As shown;
[0121] 3. Standard node operation parameters are set as follows: Figure 8 As shown.
[0122] In Example 1, under condition 3, when the fresh air temperature is 25℃ and the fresh air relative humidity is 60%, the system sensible heat load X0 = 2.0℃ (return air temperature - supply air temperature), and the system moisture load Z0 = 0.3g / Kg (return air absolute humidity - supply air absolute humidity). The program calculates that within the temperature range of 20℃ to 24℃ and the relative humidity range of 50% to 60%, the energy consumption at the lowest energy consumption node is 9.4KW, corresponding to a temperature and humidity of 24℃ and 60%. Therefore, the preferred setting temperature is 24℃ and the preferred setting relative humidity is 60%. Compared to the energy consumption of 16.2KW when the air conditioning system operates at this preferred temperature and humidity, operating at this optimal temperature and humidity saves 6.8kW, representing an energy saving rate of 42%. The program's main interface and operating parameters are as follows:
[0123] 1. The main interface of the program is as follows: Figure 9 As shown;
[0124] 2. Operating parameters of the lowest energy consumption node are as follows: Figure 10 As shown;
[0125] 3. Standard node operation parameters are set as follows: Figure 11 As shown;
[0126] Example 2
[0127] Similarly, assuming the regional atmospheric pressure is P0 = 101325 Pa and the total air supply volume is G = 20000 m³ / s 3 / h, air density ρ=1.2Kg / m³ 3 The fresh air ratio α = 15%, the primary return air ratio β = 15%, the required reference temperature range for the production process is 20℃~24℃, and the required reference relative humidity range is 50%~60%. Chilled water is the cold source, and steam is the heat source for heating and humidification. The unit cooling cost Ml = 0.3 yuan / kWH, the unit heating cost Mr = 0.6 yuan / kWH, the unit humidification energy cost Mq = 0.6 yuan / kWH, and the fan temperature rise T... d =0.5℃ (can be provided by the manufacturer or measured on-site), relative humidity after dehumidification Y4=93% (determined by the number of coils in the cooling coil, can be provided by the manufacturer or measured on-site), air conditioning system schematic diagram and air handling process parameter table as follows Figure 12 As shown.
[0128] If the indoor temperature is set to X 11 The relative humidity is set to Y. 11 When the air conditioning system reaches equilibrium, the energy consumption cost calculation and the derivation of the optimal temperature and humidity setpoints are as follows:
[0129] 1. Calculate the saturated water vapor partial pressures P11 and P12, moisture contents Z1 and Z2 of the fresh air and return air, and (return air temperature X2 = X 11 The relative humidity of the return air is Y2=Y 11 Supply air moisture content Z 10 =Z 11 -Z0);
[0130] P11=610.69*10^(7.5*X1 / (237.3+X1));
[0131] Z1 = 622 * Y1 * P11 / (P0 - Y1 * P11);
[0132] P12=610.69*10^(7.5*X2 / (237.3+X2));
[0133] Z2 = 622 * Y2 * P12 / (P0 - Y1 * P12);
[0134] 2. Calculate the temperature X3 and moisture content Z3 at the primary mixing point;
[0135] X3=(a*X1+b*X2) / (a+b)=(a*X1+b*X 11 ) / (a+b);
[0136] Z3=(a*Z1+b*Z2) / (a+b)=(a*Z1+b*Z 11 ) / (a+b);
[0137] 3. Compare Z3 and Z 11 -Z0 / (a+b) is the size, when Z3>Z 11 When -Z0 / (a+b), the air conditioning system is in dehumidification mode; when Z3 <Z 11 When -Z0 / (a+b), the air conditioning system is in humidification mode.
[0138] 3.1. Energy cost calculation under dehumidification conditions:
[0139] 3.1.1. Calculate the moisture content Z4 after dehumidification, the partial pressure of saturated water vapor P14 (pa), the temperature X4, the enthalpy H3 at the primary mixing point, and the enthalpy H4 after dehumidification. Calculate the dehumidification cooling capacity Ql4.
[0140] Z4=Z 11 -Z0 / (a+b);
[0141] P14 = Z4 * P0 / (Y4 * (622 + Z4));
[0142] X4=237.3 / ((7.5 / lg(P14 / 610.7)-1);
[0143] H3=1.01*X3+(2500+1.84*X3)Z3* / 1000;
[0144] H4=1.01*X4+(2500+1.84*X4)Z4* / 1000;
[0145] Ql4=1.2*G*(a+b)*(H3-H4) / 3600;
[0146] 3.1.2. Calculate the temperature X6 and moisture content Z6 at the secondary mixing point, the temperature X7 and moisture content Z7 after the secondary surface cooling, and the temperature X8 and moisture content Z8 after the heater;
[0147] X6 = X4(a+b) + X 11 (1-ab);
[0148] Z6=Z 11 -Z0;
[0149] X7=X 11 -X0-T d ;
[0150] Z7=Z 11 -Z0;
[0151] X8=X11 -X0-T d ;
[0152] Z8=Z 11 -Z0;
[0153] 3.1.3. When X⁴(a+b)+X 11 (1-ab)>X 11 -X0-T d At this time, cooling is required, and the enthalpy of the secondary mixing point H6, the enthalpy of the secondary surface cooling H7, and the cooling capacity Ql7 are calculated.
[0154] H6=1.01*X6+(2500+1.84*X6)Z6* / 1000;
[0155] H7=1.01*X7+(2500+1.84*X7)Z7* / 1000;
[0156] Ql7 = 1.2 * G * (H6 - H7) / 3600;
[0157] Total energy cost M = (Ql4 + Ql7) * Ml;
[0158] 3.1.4. When X⁴(a+b)+X 11 (1-ab) <X 11 -X0-T d When heating is required, the enthalpy H6 at the secondary mixing point, the enthalpy H8 after the heater, and the heating amount Qr8 are calculated.
[0159] H6=1.01*X6+(2500+1.84*X6)Z6* / 1000;
[0160] H8=1.01*X8+(2500+1.84*X8)Z7* / 1000;
[0161] Qr8 = 1.2 * G * (H8 - H6) / 3600;
[0162] Total energy cost M = Ql4*Ml + Qr8*Mr;
[0163] 3.2. Energy cost calculation under humidification conditions:
[0164] 3.2.1. Calculate the temperature X6, moisture content Z6, enthalpy H6 at the secondary mixing point, the temperature X7, moisture content Z7, enthalpy H7 after the second-stage surface cooling, the temperature X8, moisture content Z8, enthalpy H8 after the heater, the temperature X9, moisture content Z9, enthalpy H9 after humidification, and the humidification energy consumption Qq9;
[0165] X6 = a * X1 + (1 - a) * X11 ;
[0166] Z6 = a * Z1 + (1 - a) * Z 11 ;
[0167] H6=1.01*X6+(2500+1.84*X6)Z6* / 1000;
[0168] X7=X 11 -X0-T d ;
[0169] Z7 = a * Z1 + (1 - a) * Z 11 ;
[0170] H7=1.01*X7+(2500+1.84*X7)Z7* / 1000;
[0171] X8=X 11 -X0-T d ;
[0172] Z8 = a * Z1 + (1 - a) * Z 11 ;
[0173] H8=1.01*X8+(2500+1.84*X8)Z7* / 1000;
[0174] X9=X 11 -X0-T d ;
[0175] Z9=Z 11 -Z0;
[0176] H9=1.01*X9+(2500+1.84*X9)Z9* / 1000;
[0177] Q q9 =1.2*G*(H9-H8) / 3600;
[0178] 3.2.2. When a*Z1+(1-a)*Z 11 >X 11 -X0-T d When cooling is required, the cooling capacity Ql7 should be calculated.
[0179] Ql7 = 1.2 * G * (H6 - H7) / 3600;
[0180] Total energy cost M = Ql7 * Ml + Q q9 *Mq;
[0181] 3.2.3.When a*Z1+(1-a)*Z 11 <X11 -X0-T d When heating is required, the amount of heat required for heating should be calculated as Qr8.
[0182] Qr8 = 1.2 * G * (H8 - H6) / 3600;
[0183] Total energy cost M = Qr8*Mr + Qq9*Mq;
[0184] The four scenarios for calculating air conditioning energy consumption costs are shown in the flowchart below. Figure 13 As shown;
[0185] 4. Within a temperature range of 20℃ to 24℃ and a relative humidity range of 50% to 60%, a grid is formed by pre-setting temperature intervals of 0.1℃ and relative humidity intervals of 0.1%. The temperature and humidity values for each node are then calculated sequentially (i.e., the temperature and humidity of each node are substituted into X). 11 Y 11 The total energy consumption cost is calculated, and after traversing through the data, the minimum value and its corresponding temperature and humidity nodes are recorded, and the optimal temperature and humidity settings are output.
[0186] 5. Based on the above air handling process logic and calculation formulas, write a PLC program to calculate and derive the optimal temperature and humidity setpoints.
[0187] In Example 2, under condition 1, when the fresh air temperature is 12℃ and the fresh air relative humidity is 50%, the system sensible heat load X0 = 1.5℃ (return air temperature - supply air temperature) and the system moisture load Z0 = 0.3g / Kg (return air absolute humidity - supply air absolute humidity).
[0188] The program calculates that the lowest energy cost node within a temperature range of 20℃ to 24℃ and a relative humidity range of 50% to 60% is 2.5 yuan / hour, corresponding to a temperature of 20.0℃ and a relative humidity of 50.0%. Therefore, the preferred setting temperature is 20.0℃ and the preferred setting relative humidity is 50.0%. Compared to the conventional setting temperature of 22℃ and relative humidity of 55%, which results in an energy cost of 4.7 yuan / hour, the air conditioning system operating at this preferred temperature and humidity saves 2.1 yuan / hour, representing a 45% energy saving. The program's main interface and operating parameters are as follows:
[0189] 1. The main interface of the program is as follows: Figure 14 As shown;
[0190] 2. Operating parameters at the lowest energy cost node are as follows: Figure 15 As shown;
[0191] 3. Standard node operation parameters are set as follows: Figure 16 As shown.
[0192] In Example 2, under condition 2, when the fresh air temperature is 20℃ and the fresh air relative humidity is 55%, the system sensible heat load X0 = 1.8℃ (return air temperature - supply air temperature) and the system moisture load Z0 = 0.3g / Kg (return air absolute humidity - supply air absolute humidity).
[0193] The program calculates that the lowest energy cost node within a temperature range of 20℃ to 24℃ and a relative humidity range of 50% to 60% is 3.5 yuan / hour, corresponding to a temperature of 24.0℃ and a relative humidity of 55.9%. Therefore, the preferred setting temperature is 24.0℃ and the preferred setting relative humidity is 55.9%. Compared to the conventional setting temperature of 22℃ and relative humidity of 55%, which results in an energy cost of 10.3 yuan / hour, the air conditioning system operating at this preferred temperature and humidity saves 6.9 yuan / hour, representing a 66% energy saving. The program's main interface and operating parameters are as follows:
[0194] 1. The main interface of the program is as follows: Figure 17 As shown.
[0195] 2. Operating parameters at the lowest energy cost node are as follows: Figure 18 As shown.
[0196] 3. Standard node operation parameters are set as follows: Figure 19 As shown.
[0197] In Example 2, under condition 3, when the fresh air temperature is 25℃ and the fresh air relative humidity is 60%, the system sensible heat load X0 = 2.0℃ (return air temperature - supply air temperature), and the system moisture load Z0 = 0.3g / Kg (return air absolute humidity - supply air absolute humidity). The program calculates that within the temperature range of 20℃ to 24℃ and the relative humidity range of 50% to 60%, the lowest energy cost node is 8.2 yuan / hour, corresponding to a temperature and humidity of 24.0℃ and 60.0%, respectively. Therefore, the preferred setting temperature is 24.0℃, and the preferred setting relative humidity is 60.0%. Compared to the conventional setting temperature of 22℃ and relative humidity of 55%, which results in an energy cost of 13.4 yuan / hour, the air conditioning system operating at this preferred temperature and humidity saves 5.1 yuan / hour, a saving rate of 38%. The main program interface and operating parameters are as follows:
[0198] 1. The main interface of the program is as follows: Figure 20 As shown;
[0199] 2. Operating parameters at the lowest energy cost node are as follows: Figure 21 As shown;
[0200] 3. Standard node operation parameters are set as follows: Figure 22 As shown.
[0201] The above embodiments illustrate that the present invention can select the optimal temperature and humidity setting value with the least energy consumption or the lowest energy cost, resulting in excellent energy saving or cost saving effects.
[0202] The above description is merely a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural transformations made using the description and drawings of the present invention within the inventive concept of the present invention, or direct / indirect applications in other related technical fields, are included within the patent protection scope of the present invention. In the description of the present invention, the terms "one embodiment," "some embodiments," "embodiment," "illustrative embodiment," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described can be combined in any suitable manner in one or more embodiments or examples. Those skilled in the art will understand, explicitly and implicitly, that, without conflict, the embodiments described herein can be combined with other embodiments, and the embodiments and features within those embodiments can be combined with each other.
Claims
1. A method for controlling the temperature and humidity setpoint of an air conditioner, characterized in that, Includes the following steps: Step A: Environmental Data Acquisition: Real-time acquisition of environmental parameters for the fresh air, return air, and supply air of the automatic control air conditioning system. In the case of a 100% fresh air air conditioning system, exhaust air is selected instead of return air. The environmental parameters include temperature and relative humidity. The fresh air represents the external environmental parameters, and the return air represents the controlled environmental parameters. Step B: Calculation of heat and humidity load: Based on the environmental parameters collected in Step A, calculate the sensible heat load and humidity load of the controlled environment, wherein the sensible heat load is determined based on the difference between the return air temperature and the supply air temperature, and the humidity load is determined based on the difference between the absolute humidity of the return air and the absolute humidity of the supply air. Step C: Determine the optimal temperature and humidity setpoints: Within the preset allowable temperature and humidity range, divide the temperature and relative humidity values into a series of discrete temperature and humidity nodes according to preset intervals, and perform the following calculations for each temperature and humidity node: C1: Assume the current temperature and humidity node as the temperature and humidity setpoint. Combine the fresh air environment parameters collected in step A and the sensible heat load, moisture load calculated in step B, as well as the known supply air volume, fresh air ratio, and primary return air ratio. The supply air volume, fresh air ratio, and primary return air ratio are determined during the commissioning of the air conditioning system. Calculate the cooling load, heating load, and humidification energy required for the air conditioning to operate at this temperature and humidity node. The fresh air ratio is the ratio of fresh air volume to total supply air volume, the primary return air ratio is the ratio of primary return air volume to total supply air volume, and the secondary return air ratio = 1 - fresh air ratio - primary return air ratio; C2: Convert the cooling load, heating load, and humidification energy consumption into corresponding electricity consumption, and sum them up to obtain the total energy consumption of the temperature and humidity node; or, multiply the cooling load, heating load, and humidification energy consumption by the corresponding energy cost unit price, and sum them up to obtain the total energy cost of the temperature and humidity node. C3: Traverse all temperature and humidity nodes, compare the total energy consumption or total energy cost of each node, and select the temperature and humidity node with the lowest total energy consumption or the lowest total energy cost as the preferred temperature and humidity setting value.
2. The air conditioning temperature and humidity setpoint control method according to claim 1, characterized in that, In step B: Sensible heat load = return air temperature - supply air temperature; Moisture load = return air absolute humidity - supply air absolute humidity.
3. The air conditioning temperature and humidity setpoint control method according to claim 1, characterized in that, The preset interval mentioned in step C is set according to the CPU's computing power and the air conditioning control precision requirements.
4. The air conditioning temperature and humidity setpoint control method according to claim 1, characterized in that, Step C also includes: C4: Outputting the preferred temperature and humidity setpoints determined in step C3 to the controller of the automatic air conditioning system to replace the original temperature and relative humidity setpoints, thereby realizing the automatic change of temperature and humidity setpoints.
5. The air conditioning temperature and humidity setpoint control method according to claim 1, characterized in that, In step C, a loop traversal algorithm is used to calculate and compare all temperature and humidity nodes. The loop traversal algorithm includes: using the boundary value of the allowable temperature and humidity range as the loop boundary value, using a preset interval as the step size, calculating the total energy consumption or total energy cost of each temperature and humidity node in turn, and outputting the optimal temperature and humidity setting value after the traversal is completed.
6. The air conditioning temperature and humidity setpoint control method according to claim 1, characterized in that, The preset temperature and humidity allowable range is determined according to the production process requirements.
7. The air conditioning temperature and humidity setpoint control method according to claim 1, characterized in that, The environmental data acquisition and calculation interval is set according to the changes in the heat and humidity load of the external environment or the controlled environment.
8. The air conditioning temperature and humidity setpoint control method according to claim 1, characterized in that, A method for determining the applicability of environmental sampling data is set: the temperature and humidity values of the controlled environment are set to reach the set range. Only when the temperature and relative humidity of the return air are sampled n times consecutively and both the temperature and relative humidity are within the set range can it be determined that the air conditioning system has reached a balanced state. Only the environmental data of the last sample is used to calculate and derive the optimal temperature and humidity set values.