Method and system for coordinating optimal control of indoor pollution by constant air volume system in public place

Abstract

The application discloses a method and system for optimizing and controlling indoor pollution in a constant air volume system in public places, which monitors the indoor TVOC concentration and outdoor TVOC concentration, the airflow velocity and TVOC concentration at the air supply outlet of a ventilation device, and the TVOC concentration at the air exhaust outlet in real time, combines the room volume and the cross-sectional area of the air supply outlet of the ventilation device, takes the total ventilation volume of the ventilation device and the minimum time interval for limiting the switch action as the optimization target, and optimizes the upper limit value and the lower limit value of the indoor TVOC concentration by using a non-dominated genetic algorithm NSGA-II, so that the ventilation adjusting module is controlled to perform intermittent constant air volume ventilation, which is helpful to control the indoor VOCs concentration level, meet the durability requirement of the equipment, and minimize energy consumption.

Description

Technical Field

[0001] This invention belongs to the field of indoor air quality and building energy conservation and emission reduction, and in particular to the method and system for the coordinated optimization and control of indoor pollution by constant air volume systems in public places. Background Technology

[0002] People spend approximately 90% of their time indoors. Studies have found that indoor air pollutants, such as volatile organic compounds (VOCs), originate from complex sources and are diverse in public places like airplane cabins, cinemas, classrooms, auditoriums, and conference rooms. Exposure to VOCs in the indoor environment can cause symptoms such as drowsiness, fatigue, headaches, and difficulty concentrating, increasing comfort and health risks and leading to reduced work efficiency. Ventilation dilution is an effective, environmentally friendly, and economical method for removing indoor air pollution.

[0003] Currently, most ventilation optimization control strategies focus on real-time monitoring and control of indoor CO2 concentration, with less emphasis on the synergistic optimization of multiple parameters such as indoor VOCs pollution concentration, equipment energy efficiency, and lifespan. Most existing building ventilation systems operate in a traditional constant air volume (CAV) mode, which, while effectively reducing indoor VOCs concentration, consumes a significant amount of energy. Furthermore, prolonged operation or frequent start-ups and shutdowns negatively impact equipment lifespan. Adopting variable air volume (VAV) ventilation control strategies presents challenges in terms of modification difficulty and cost. Some scholars have proposed using software simulation to achieve demand-driven ventilation; however, simulation methods are limited by model accuracy, computer processing power, and precision. In recent years, model predictive control algorithms have been introduced into demand-driven ventilation control strategies to control indoor VOCs concentration in a more energy-efficient manner. However, this method requires establishing accurate dynamic models, involves substantial computation, and lacks a comprehensive ventilation optimization control method that addresses multiple objectives simultaneously. Summary of the Invention

[0004] The purpose of this invention is to provide a method and system for the collaborative optimization and control of indoor pollution in public places using a constant air volume system. The method uses a non-dominated genetic algorithm NSGA-II to optimize the upper and lower limits of indoor TVOC concentration and controls the ventilation adjustment module to perform intermittent constant air volume ventilation. This helps to control the indoor VOC concentration level while meeting the durability requirements of the equipment and minimizing energy consumption.

[0005] The technical solution to achieve the purpose of this invention is as follows:

[0006] Systems for coordinating and optimizing indoor pollution control using constant air volume systems in public places include:

[0007] The environmental parameter monitoring module is used to monitor the indoor TVOC concentration in real time. inoutdoor TVOC concentration C out Airflow velocity v and TVOC concentration C at the air outlet of the ventilation equipment S The TVOC concentration C at the indoor exhaust vent is monitored in real time. e ;

[0008] The data storage and display module is used to store and display the input room volume V, the cross-sectional area A of the ventilation equipment air outlet, and the monitoring data collected in real time by the environmental parameter monitoring module;

[0009] The optimized computing and control module is used to issue on / off action commands to the ventilation regulation module;

[0010] The ventilation control module controls the opening and closing of ventilation equipment based on the action commands issued by the optimization calculation and control module.

[0011] Methods for the coordinated optimization and control of indoor pollution using constant air volume systems in public places include:

[0012] Real-time acquisition of indoor environmental parameters, including indoor TVOC concentration (C). in outdoor TVOC concentration C out Airflow velocity v and TVOC concentration C at the air outlet of the ventilation equipment S The TVOC concentration C at the indoor exhaust vent is monitored in real time. e Obtain the room volume V and the cross-sectional area A of the air supply outlet of the ventilation equipment;

[0013] The ventilation equipment designed in this invention is constrained by the upper and lower limits of indoor TVOC concentration. The basic control logic is as follows: when the real-time indoor TVOC concentration reaches the upper limit, the ventilation equipment is turned on, and then the indoor TVOC concentration begins to decrease; when the real-time indoor TVOC concentration reaches the lower limit, the ventilation equipment is turned off, and then the indoor TVOC concentration begins to rise. An optimization model is built using the total ventilation volume and equipment durability of the ventilation equipment as optimization objectives.

[0014] The non-dominated genetic algorithm NSGA-II is used to optimize the upper and lower limits of indoor TVOC concentration based on the established optimization model, and obtain the optimal solutions for the upper and lower limits. The indoor real-time monitored TVOC concentration value is compared with the optimal solutions for the upper and lower limits, and the start and stop status of the ventilation equipment is determined based on the above basic control logic.

[0015] The significant advantages of this invention compared to existing technologies are:

[0016] Addressing the limitations of traditional constant airflow ventilation systems, such as poor flexibility in airflow adjustment and outdated multi-parameter collaborative ventilation control methods, this paper utilizes sensors to monitor indoor and outdoor environmental parameters in real time and use these parameters as optimization inputs. A non-dominated genetic algorithm (NSGA-II) is employed to optimize and obtain upper and lower limits for indoor TVOC concentration. These limits are then compared with the real-time monitored indoor TVOC concentration to control the automatic on / off operation of ventilation equipment, ultimately finding the optimal intermittent constant airflow ventilation strategy. This achieves synergistic optimization of indoor air quality, energy efficiency, and equipment durability. This method can improve energy efficiency while meeting the requirements for indoor air quality and equipment durability. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of the system for collaborative optimization and control of indoor pollution in public places as described in this invention.

[0018] Figure 2 This is a flowchart of the method for collaborative optimization control of indoor pollution using a constant air volume system in public places, as described in this invention.

[0019] Figure 3 This is a diagram illustrating the optimized scheme of the method for collaborative optimization control of indoor pollution using a constant air volume system in public places, as described in this invention.

[0020] Figure 4 This is a population distribution diagram after iteration using a genetic algorithm in an embodiment of the present invention.

[0021] Figure 5 This is a diagram illustrating the ventilation effect of constant airflow optimization control according to an embodiment of the present invention. Detailed Implementation

[0022] The present invention will be further described below with reference to the accompanying drawings and specific embodiments.

[0023] Combination Figure 1 This embodiment provides a method and system for the collaborative optimization and control of indoor pollution using a constant air volume system in public places, including an environmental parameter monitoring module 1, a data storage and display module 2, an optimization calculation and control module 3, and a ventilation adjustment module 4.

[0024] The environmental parameter monitoring module includes several sensors arranged indoors and outdoors for real-time monitoring of indoor TVOC concentration (C). in outdoor TVOC concentration C out Airflow velocity v and TVOC concentration C at the air outlet of the ventilation equipment S The TVOC concentration C at the indoor exhaust vent is monitored in real time. e It then sends the real-time monitoring data to the data storage and display module and the optimization calculation and control module.

[0025] The data storage and display module is used to store and display the input room volume V, the cross-sectional area A of the ventilation equipment air outlet, and the monitoring data collected in real time by the environmental parameter monitoring module, and send them to the optimization calculation and control module.

[0026] The optimization calculation and control module is used to issue on / off action commands to the ventilation adjustment module, and its control process includes:

[0027] The upper and lower limits of indoor TVOC concentration are optimized based on the established optimization model to obtain the optimal solutions for the upper and lower limits. The indoor real-time monitored TVOC concentration value is then compared with the optimal solutions for the upper and lower limits to determine the start and stop status of the ventilation equipment. Specifically, when the indoor real-time monitored TVOC concentration reaches the upper limit of indoor TVOC concentration, a ventilation start command is sent to the ventilation control module; when the indoor real-time monitored TVOC concentration reaches the lower limit of indoor TVOC concentration, a ventilation stop command is sent to the ventilation control module.

[0028] During the optimization process, the lower limit of indoor TVOC concentration is required to be higher than the stable indoor TVOC concentration to ensure that the air conditioning system can perform intermittent ventilation within a reasonable range, thereby reducing energy consumption.

[0029] The definition of stable indoor TVOC concentration is as follows:

[0030]

[0031] In the formula, C W To maintain a stable indoor TVOC concentration, C in For real-time indoor TVOC concentration, C out For the TVOC concentration monitored in real time outdoors, C S The TVOC concentration at the air outlet of the ventilation equipment is monitored in real time. e This refers to the TVOC concentration monitored in real time at the exhaust vent.

[0032] When the indoor and outdoor TVOC concentrations, as well as the TVOC concentrations at the air supply and exhaust vents of ventilation equipment, change, the steady-state concentration of indoor TVOC must be recalculated and determined according to the above formula.

[0033] The ventilation regulation module (controller controls the switching of ventilation equipment) controls the opening and closing of ventilation equipment based on the action commands issued by the optimization calculation and control module.

[0034] The method of using constant air volume systems in public places to collaboratively optimize the control of indoor pollution mainly includes the following steps:

[0035] Step 1: Install a constant air volume system in the indoor public space to coordinate and optimize the control of indoor pollution, and use sensors to obtain the indoor TVOC concentration in real time.in outdoor TVOC concentration C out Airflow velocity v and TVOC concentration C at the air outlet of the ventilation equipment S The TVOC concentration C at the indoor exhaust vent is monitored in real time. e ; Obtain the input values ​​for room volume V and cross-sectional area A of the ventilation equipment's air outlet;

[0036] Step 2: Construct an optimization model;

[0037] The ventilation equipment designed in this invention is constrained by the upper and lower limits of indoor TVOC concentration during startup and shutdown. The optimization objectives and constraints are described as follows: Energy-efficiency-related ventilation performance is represented by the total ventilation volume. A smaller total ventilation volume results in lower energy consumption during the entire ventilation process, but relatively worse indoor air quality. Equipment durability-related indicators are represented by the minimum time interval between switching actions. A smaller value indicates a shorter minimum time interval between switching actions, better indoor air quality, but also worse durability. Based on this, the total ventilation volume and equipment durability are used as optimization objectives. During the optimization process, to avoid excessively frequent switching operations, the minimum time interval between switching actions should be limited to a self-defined time threshold H, serving as a constraint. Both the total ventilation volume and the minimum time interval between switching actions can be expressed as functions incorporating the upper and lower limits of indoor TVOC concentration.

[0038] The corresponding objective function F(x) is shown below:

[0039] F(x)=[minf1(x1,x2),minf2(x1,x2)]

[0040] In the formula, f1(x1,x2) and f2(x1,x2) are the functions of the total ventilation volume and the minimum time interval of the switching action during the operation of the ventilation system, respectively, and x1 and x2 are the upper limit and lower limit of the indoor TVOC concentration, respectively.

[0041] Where, f1(x1,x2)=Avt

[0042] f2(x1,x2)=min{ATI1,ATI2}

[0043]

[0044]

[0045]

[0046]

[0047] In the formula, A is the cross-sectional area of ​​the air outlet of the ventilation equipment (m²). 2v is the airflow velocity of the ventilation equipment (s); V is the room volume (m³). 3 ); C out The concentration of TVOC in outdoor air in real time (μg / m³) 3 ); C S The TVOC concentration (μg / m³) is monitored in real time at the air outlet of the ventilation equipment. 3 h represents the daily operating time of the ventilation system (h); t represents the cumulative time (s) during which the ventilation system was turned on; θ represents the TVOC concentration threshold (μg / m³) specified in the relevant indoor air quality standard (such as GB / T18883). 3 T represents the time (s) it takes for the indoor TVOC concentration to rise to the concentration threshold when the ventilation system just starts operating; ATI1 and ATI2 represent the duration (s) of a single decrease / rise of the indoor TVOC concentration.

[0048] The corresponding constraint functions are shown below:

[0049] minf2(x1,x2)≥H

[0050] H is the time threshold set by the manufacturer or relevant literature to meet the equipment durability requirements; in this embodiment, it is set to 600s.

[0051] Step 3: Call the non-dominated genetic algorithm NSGA-II to optimize the upper and lower limits of indoor TVOC concentration based on the established optimization model, and obtain the optimal solutions for the upper and lower limits. The specific process is as follows:

[0052] 3.1: Input the environmental parameters measured by the sensor in step 1; set the initial optimization parameters, including the initial population size N, the maximum number of iterations, crossover probability, mutation probability, etc.; set the range of the decision variable (indoor TVOC upper and lower limit concentrations): the upper limit should not exceed the TVOC concentration threshold specified in the relevant indoor air quality standards. Meanwhile, to save operating energy through intermittent operation of the ventilation system, the upper and lower limits should be higher than the stable indoor TVOC concentration C. W And the upper limit is higher than the lower limit; set the "Energy Consumption-Equipment Durability" preference value (enter any value between 0 and 1, closer to 0 indicates more emphasis on energy consumption, closer to 1 indicates more emphasis on equipment durability).

[0053] 3.2: Obtain the initial parent population P through a random function. Each individual in the population needs to satisfy the constraint function in step 2.

[0054] 3.3: Calculate the objective function value (total ventilation volume and minimum time interval) for each individual in population P and perform fast non-dominated sorting to divide individuals into different dominance levels; calculate the crowding distance of individuals within each dominance level by comparing their relative positions in the objective function space.

[0055] 3.4: Using the tournament selection method, individuals with lower dominance levels and larger crowding distances are selected, and then crossover and mutation are used to obtain the first generation offspring population Q.

[0056] 3.5: Adopting an elite retention strategy, the offspring population Q is merged with the parent population P to form a population R of size 2N. Then, R is sorted by fast non-dominated sorting. At the same time, crowding distance is calculated for individuals in each non-dominated layer. Individuals with lower ranking and larger crowding distance are selected to form a new parent population.

[0057] 3.6: Determine if the maximum number of iterations has been reached. If so, output the optimal solution set for the upper and lower limits of indoor TVOC concentration, and then proceed to 3.7; otherwise, return to 3.3 and repeat the iterative calculation.

[0058] 3.7: Select and output the optimal solution from the optimal solution set according to the "energy consumption-equipment durability" preference value set in 3.1; the algorithm terminates.

[0059] During the operation of the ventilation system, if there are changes in the number of people in the room or other sudden sources of pollution, the time it takes for the indoor TVOC concentration to reach the upper limit will change accordingly, that is, the duration of the rising period of indoor TVOC concentration will change accordingly. At this time, the upper and lower limits of indoor TVOC concentration need to be re-optimized and determined according to the aforementioned optimization model.

[0060] Combination Figure 2 Another embodiment of the present invention also provides a method for the coordinated optimization and control of indoor pollution using a constant air volume system in public places, specifically including:

[0061] A system for coordinating and optimizing indoor pollution control using a constant air volume system (CVV) in a public space is installed in a room. The ventilation system is set to operate for 8 hours, and the TVOC concentration threshold θ specified in the Indoor Air Quality Standard (GB / T18883-2022) is 600 μg / m³. 3 .

[0062] The airflow velocity v of the ventilation equipment was measured to be 0.2 m / s at a certain moment by a sensor, and the outdoor TVOC concentration C was... out 172 μg / m 3 Indoor TVOC concentration C in 526 μg / m 3 TVOC concentration C at the air outlet of ventilation equipment S 226 μg / m 3In this embodiment, since there are no factors indoors that would cause uneven pollution, the TVOC concentration C at the indoor exhaust vent can be assumed to be... e With indoor TVOC concentration C in The same principle applies, thus the stable indoor TVOC concentration C can be calculated. W 472 μg / m 3 The room volume V is obtained as 33.4m³. 2 The cross-sectional area A of the air outlet of the ventilation equipment is 0.11m². 2 .

[0063] The optimization model is constructed, and the objective function F(x) is shown below:

[0064] F(x)=[minf1(x1,x2),minf2(x1,x2)]

[0065] In the formula, f1(x1,x2) and f2(x1,x2) are the functions of the total ventilation volume and the minimum time interval of the switching action during the operation of the ventilation system, respectively, and x1 and x2 are the upper limit and lower limit of the indoor TVOC concentration, respectively.

[0066] Where, f1(x1,x2)=Avt

[0067] f2(x1,x2)=min{ATI1,ATI2}

[0068]

[0069]

[0070]

[0071]

[0072] In the formula, A is the cross-sectional area of ​​the air outlet of the ventilation equipment (m²). 2 v is the airflow velocity of the ventilation equipment (s); V is the room volume (m³). 3 ); C out The concentration of TVOC in outdoor air in real time (μg / m³) 3 ); C S The TVOC concentration (μg / m³) is monitored in real time at the air outlet of the ventilation equipment. 3 h represents the daily operating time of the ventilation system (h); t represents the cumulative time (s) during which the ventilation system was turned on; θ represents the TVOC concentration threshold (μg / m³) specified in the relevant indoor air quality standard (such as GB / T18883). 3T represents the time (s) it takes for the indoor TVOC concentration to rise to the concentration threshold when the ventilation system first starts running; ATI1 and ATI2 represent the duration (s) of a single decrease / rise of the indoor TVOC concentration.

[0073] The constraint functions are as follows:

[0074] minf2(x1,x2)≥600s

[0075] The non-dominated genetic algorithm NSGA-II was used to optimize the upper and lower limits of indoor TVOC concentration based on the established optimization model. The optimization scheme is as follows: Figure 3 As shown; the optimal solution for the upper and lower limits is finally obtained, and the specific process is as follows:

[0076] S1: Input environmental parameters measured by the sensor; set the initial population size N = 1500, the maximum number of iterations to 200, the crossover probability to 0.7, and the mutation probability to 0.05; to ensure the ventilation system operates intermittently to maximize energy savings, set the search range for indoor TVOC upper and lower limit concentrations to: upper and lower limits within 472 μg / m³. 3 and 600μg / m 3 Between, and the upper limit is higher than the lower limit; set the "Energy Consumption - Equipment Durability" preference value to 0.5.

[0077] S2: Obtain the initial parent population P through a random function. Each individual in the population needs to satisfy the constraint function described above.

[0078] S3: Calculate the objective function value (total ventilation and minimum time interval) for each individual in population P and perform a fast non-dominated sort to divide individuals into different dominance levels; calculate the crowding distance of individuals within each dominance level by comparing their relative positions in the objective function space.

[0079] S4: Using the tournament selection method, individuals with lower dominance levels and larger crowding distances are selected, and then crossover and mutation are used to obtain the first generation offspring population Q.

[0080] S5: Adopt the elite retention strategy, merge the offspring population Q with the parent population P to form a population R of size 3000, then perform fast non-dominated sorting on R, and calculate the crowding distance for individuals in each non-dominated layer, and prioritize the selection of individuals with lower ranking and larger crowding distance to form a new parent population.

[0081] S6: Determine if the number of iterations has reached 200. If so, output the optimal solution set for the upper and lower limits of indoor TVOC concentrations (e.g., ...). Figure 4 (as shown), then proceed to S7; if not satisfied, return to S3 and repeat the iterative calculation;

[0082] S7: Select and output the optimal solution from the optimal solution set according to the "energy consumption-equipment durability" preference value set in S6 (the optimal solution obtained in this example is the upper and lower limits of indoor TVOC concentration, which are 596 μg / m³). 3 and 472 μg / m 3 (Points); the algorithm terminates.

[0083] The constant air volume ventilation optimization control process in this embodiment is as follows: Figure 5 As shown;

[0084] During the initial startup phase of the ventilation system, the indoor TVOC concentration increased from 172 μg / m³. 3 Increase to the concentration threshold of 600 μg / m 3 At this point, the ventilation equipment is off, so the ventilation volume is zero. Then, a cycle begins, comparing the real-time indoor TVOC concentration with the corresponding upper and lower limits from the optimized solution: when the indoor TVOC concentration rises to 596 μg / m³... 3 When the indoor TVOC concentration drops to 472 μg / m³, turn on the ventilation equipment; when the indoor TVOC concentration drops to 472 μg / m³, turn on the ventilation equipment. 3 When necessary, turn off the ventilation equipment.

[0085] While the present invention has been disclosed above, it is not limited thereto. Any person skilled in the art can make various modifications and alterations without departing from the spirit and scope of the invention; therefore, the scope of protection of the present invention should be determined by the scope defined in the claims.

Claims

1. A system for the coordinated optimization and control of indoor pollution using a constant air volume system in public places, characterized in that: include: The environmental parameter monitoring module is used to monitor indoor TVOC concentration in real time. outdoor TVOC concentration Airflow velocity at the air outlet of the ventilation equipment and TVOC concentration TVOC concentration monitored in real time at the exhaust vent ; Data storage and display module, used to store and display the input room volume. The cross-sectional area A of the air outlet of the ventilation equipment and the monitoring data collected in real time by the environmental parameter monitoring module; The optimization calculation and control module is used to build an optimization model, call the non-dominated genetic algorithm NSGA-II to obtain the optimal solution of the upper and lower limits of indoor TVOC concentration, and issue on / off action commands to the ventilation regulation module accordingly. The ventilation control module controls the opening and closing of ventilation equipment based on the action commands issued by the optimization calculation and control module. The control process of the optimization calculation and control module includes: The non-dominated genetic algorithm NSGA-II is invoked to optimize the upper and lower limits of indoor TVOC concentration. Based on the optimized upper and lower limits and the real-time monitored indoor TVOC concentration, ventilation control modules are issued commands to turn on / off ventilation. Specifically, when the real-time monitored indoor TVOC concentration reaches the upper limit, a ventilation control module is issued a command to turn on ventilation; when the real-time monitored indoor TVOC concentration reaches the lower limit, a ventilation control module is issued a command to turn off ventilation. During the optimization process, the lower limit of indoor TVOC concentration is required to be higher than the stable indoor TVOC concentration; The objective function F(x) for optimizing the model is: In the formula, and These are functions representing the total ventilation volume and the minimum time interval between on / off actions during the operation of the ventilation system, respectively. and These are the upper and lower limits for indoor TVOC concentration, respectively. in, In the formula, The cross-sectional area of ​​the air outlet of the ventilation equipment; The airflow velocity of the ventilation equipment; Room volume; This represents the daily operating time of the ventilation system; t represents the cumulative time the ventilation system has been running throughout the day. The TVOC concentration threshold is specified in the relevant indoor environmental standards; T is the time it takes for the indoor TVOC concentration to rise to the concentration threshold when the ventilation system first starts operating. , These represent the duration of a single decrease / increase in indoor TVOC concentration, respectively. The corresponding constraint functions are shown below: H represents the time threshold for meeting equipment durability requirements.

2. The system for collaborative optimization and control of indoor pollution using a constant air volume system in public places according to claim 1, characterized in that, The definition of the stable concentration of indoor TVOC is as follows: In the formula, To stabilize the indoor TVOC concentration; When the indoor and outdoor TVOC concentrations, as well as the TVOC concentrations at the air supply and exhaust vents of ventilation equipment, change, the steady-state concentration of indoor TVOC must be recalculated and determined according to the above formula.

3. A method for the coordinated optimization and control of indoor pollution using a constant air volume system in public places, characterized in that, include: Real-time acquisition of indoor environmental parameters, including indoor TVOC concentration. outdoor TVOC concentration Airflow velocity at the air outlet of the ventilation equipment and TVOC concentration TVOC concentration monitored in real time at the exhaust vent Get room volume The cross-sectional area A of the air outlet of the ventilation equipment; Optimization model construction: The total ventilation volume and equipment durability of the ventilation equipment are used as optimization objectives; The non-dominated genetic algorithm NSGA-II was used to optimize the upper and lower limits of indoor TVOC concentration based on the established optimization model, and the optimal solutions for the upper and lower limits were obtained. The system compares the real-time indoor TVOC concentration with the optimal solutions for the upper and lower limits to determine the start and stop status of the ventilation equipment. Specifically, it sends a command to the ventilation control module to start ventilation when the real-time indoor TVOC concentration reaches the upper limit; and sends a command to the ventilation control module to stop ventilation when the real-time indoor TVOC concentration reaches the lower limit. During the optimization process, the lower limit of indoor TVOC concentration is required to be higher than the stable indoor TVOC concentration; The objective function F(x) corresponding to the optimization objective is: In the formula, and These are functions representing the total ventilation volume and the minimum time interval between on / off actions during the operation of the ventilation system, respectively. and These are the upper and lower limits for indoor TVOC concentration, respectively. in, In the formula, The cross-sectional area of ​​the air outlet of the ventilation equipment; The airflow velocity of the ventilation equipment; Room volume; This represents the daily operating time of the ventilation system; t represents the cumulative time the ventilation system has been running throughout the day. The TVOC concentration threshold is specified in the relevant indoor environmental standards; T is the time it takes for the indoor TVOC concentration to rise to the concentration threshold when the ventilation system first starts operating. , These represent the duration of a single decrease / increase in indoor TVOC concentration, respectively. The corresponding constraint functions are shown below: H represents the time threshold for meeting equipment durability requirements.

4. The method for collaborative optimization control of indoor pollution using a constant air volume system in public places according to claim 3, characterized in that, The non-dominated genetic algorithm NSGA-II was used to optimize the upper and lower limits of indoor TVOC concentration. The specific process is as follows: 6.1 Set initial optimization parameters; set the value range of decision variables, including the upper and lower limits of indoor TVOC concentration: the upper limit should not exceed the TVOC concentration threshold specified in the relevant indoor air quality standards, and the upper and lower limits should be higher than the stable indoor TVOC concentration. And the upper limit is higher than the lower limit; Set the energy consumption-equipment durability preference value; 6.

2. Obtain the initial parent population P through a random function. Each individual in the population needs to satisfy the constraint function. 6.3 Calculate the objective function value for each individual in population P and perform non-dominated sorting to divide individuals into different dominance levels; calculate the crowding distance of individuals within each dominance level by comparing their relative positions in the objective function space. 6.

4. Using the tournament selection method, individuals with lower dominance levels and larger crowding distances are selected, and then crossover and mutation are used to obtain the first generation offspring population Q; 6.

5. Adopt the elite retention strategy, merge the offspring population Q with the parent population P to form population R, then perform non-dominated sorting on R, and calculate the crowding distance for individuals in each non-dominated layer, and prioritize the selection of individuals with lower ranking and larger crowding distance to form a new parent population. 6.6 Determine if the maximum number of iterations has been reached. If so, output the optimal solution set for the upper and lower limits of indoor TVOC concentration, and then proceed to 6.

7. If not, return to 6.3 and repeat the iterative calculation. 6.

7. Select and output the optimal solution from the optimal solution set according to the energy consumption-equipment durability preference value set in 6.1; the algorithm terminates.

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