A method, system, device, and storage medium for intelligent ventilation control in residential buildings based on health needs and natural ventilation potential.

Abstract

This invention discloses a method, system, device, and storage medium for intelligent ventilation control of residential buildings based on health needs and natural ventilation potential, relating to the fields of building environment and energy conservation technology. The method includes determining the minimum health-demand ventilation volume for a target control area based on the dose-response relationship between ventilation volume and the health of the local population; collecting real-time natural ventilation volume in the target control area; determining whether to activate the mechanical ventilation system based on the minimum health-demand ventilation volume and the real-time natural ventilation volume; and controlling the operation of the mechanical ventilation system according to an optimal intermittent operation control strategy. The method of this invention sets health-demand ventilation targets based on the dose-response relationship between ventilation volume and human health, which more comprehensively reflects human health needs compared to control based on a single pollutant concentration. By determining the optimal intermittent operation strategy of the mechanical ventilation system through a multi-objective optimization algorithm, it balances health risks and energy consumption, achieving energy-efficient ventilation control.

Description

Technical Field

[0001] This invention relates to the field of building environment and energy conservation technology, specifically to a method, system, device, and storage medium for intelligent ventilation control of residential buildings based on health needs and natural ventilation potential. Background Technology

[0002] Ventilation is crucial for ensuring indoor air quality and protecting the health of residents. Especially in residential buildings, due to the complexity and uncertainty of resident behavior (such as window-opening habits) and external climate conditions (such as wind speed, direction, temperature, and humidity), natural ventilation fluctuates significantly and is often insufficient to meet the body's need for fresh air, particularly during enclosed periods like nighttime sleep. Prolonged exposure to poorly ventilated environments increases health risks for residents.

[0003] To compensate for insufficient natural ventilation, residential buildings are often equipped with mechanical ventilation systems. Traditional mechanical ventilation control strategies mainly include timed control and demand-controlled ventilation (DCV) based on the concentration of a single pollutant (such as CO2). However, timed control cannot adapt to dynamic changes in the indoor and outdoor environment and occupant behavior, easily leading to unnecessary energy consumption or insufficient ventilation. While DCV based on the concentration of a single pollutant considers indoor air quality, it does not fully consider the interaction between different pollutants and the complex relationship between ventilation volume and human health, making it difficult to achieve truly "healthy" control.

[0004] More importantly, existing control strategies often fail to fully utilize natural ventilation, leading to excessively long operating times for mechanical ventilation systems and unnecessary energy consumption. How to comprehensively consider the health needs of residents, fully utilize natural ventilation, and achieve energy-efficient operation of mechanical ventilation systems is a current challenge in the field of residential building ventilation control. Summary of the Invention

[0005] In view of the above-mentioned problems, the present invention is proposed.

[0006] Therefore, the technical problem solved by the present invention is that existing intelligent ventilation control methods for residential buildings fail to make full use of natural ventilation, resulting in excessively long operating times of mechanical ventilation systems and unnecessary energy consumption.

[0007] To address the aforementioned technical problems, this invention provides the following technical solution: a smart ventilation control method for residential buildings based on health needs and natural ventilation potential, comprising: determining the minimum health-requirement ventilation volume for a target control area based on the dose-response relationship between ventilation volume and the health of the local population; collecting real-time natural ventilation volume in the target control area; determining whether a mechanical ventilation system needs to be activated based on the minimum health-requirement ventilation volume and the real-time natural ventilation volume; controlling the operation of the mechanical ventilation system according to an optimal intermittent operation control strategy; activating the mechanical ventilation system includes, if it is determined that the mechanical ventilation system needs to be activated, using a multi-objective optimization algorithm to determine the optimal intermittent operation control strategy for the mechanical ventilation system within a preset control period.

[0008] As a preferred embodiment of the intelligent ventilation control method for residential buildings based on health needs and natural ventilation potential described in this invention, the minimum ventilation volume for health needs includes a ventilation-health dose-response relationship curve determined according to the specific population and regional climate characteristics, and set to ensure that the population's health risk is at the minimum ventilation volume.

[0009] As a preferred embodiment of the intelligent ventilation control method for residential buildings based on health needs and natural ventilation potential described in this invention, the method for collecting real-time natural ventilation volume of the target control area includes using an SSA-Stacking machine learning prediction model to predict the natural ventilation volume of the area based on real-time indoor and outdoor environmental parameters, resident behavior habits, and basic building characteristics as input data.

[0010] As a preferred embodiment of the intelligent ventilation control method for residential buildings based on health needs and natural ventilation potential described in this invention, the method for determining whether to activate the mechanical ventilation system includes: comparing the acquired real-time natural ventilation volume with the set minimum ventilation volume for health needs; when the natural ventilation volume is greater than or equal to the minimum ventilation volume for health needs, it indicates that the current natural ventilation volume is sufficient to meet health needs, and there is no need to activate or maintain the mechanical ventilation system; when the natural ventilation volume is less than the minimum ventilation volume for health needs, it indicates that the current natural ventilation volume is insufficient to meet health needs, and the mechanical ventilation system needs to be activated for supplementary air; when it is determined that the mechanical ventilation system needs to be activated, a multi-objective optimization algorithm is used to determine the optimal intermittent operation control strategy of the mechanical ventilation system within a preset control period; when the mechanical ventilation system is on, the total ventilation volume is the sum of the rated ventilation volume of the mechanical ventilator and the natural ventilation volume; when the mechanical ventilation system is off, the total ventilation volume is the natural ventilation volume; the mechanical ventilation system is intermittently started and stopped by controlling the equivalent pollutant concentration to be maintained between the set lower and upper concentration limits; the optimal intermittent operation control strategy outputs the optimal lower and upper concentration limits as parameters; the optimal lower and upper concentration limits are determined by the multi-objective optimization algorithm.

[0011] As a preferred embodiment of the intelligent ventilation control method for residential buildings based on health needs and natural ventilation potential described in this invention, the optimal lower and upper concentration limits are determined by a multi-objective optimization algorithm, including minimizing the health risk cost; the health risk cost is output based on the deviation of the equivalent pollutant concentration from the target stable concentration determined by the minimum ventilation volume for health needs and the time; a graded penalty factor is set to express the difference in health impact of the same degree of deviation, and minimizing the health risk cost is the integral of the accumulated health risk cost over the entire control period; when When the reward / penalty factor is 1, the equivalent instantaneous concentration of pollutants is expressed as: , when When the reward / penalty factor is 5, the equivalent instantaneous concentration of pollutants is expressed as: , When 1.25 When the reward / penalty factor is 10, the equivalent instantaneous concentration of pollutants is expressed as: , When 1.5 When the reward / penalty factor is set to 100, the equivalent instantaneous concentration of pollutants is expressed as: , When 0.5 When the reward / penalty factor is -5, the equivalent instantaneous concentration of pollutants is expressed as: , when When the reward / penalty factor is -10, the equivalent instantaneous concentration of pollutants is expressed as: , The integral over the entire ventilation time is expressed as: , in, To ensure the stable concentration of equivalent pollutants under ventilation conditions for health purposes, This represents the equivalent instantaneous concentration of pollutants. Indicates time, The instantaneous concentration of the equivalent pollutant carrying reward and punishment factors.

[0012] As a preferred embodiment of the intelligent ventilation control method for residential buildings based on health needs and natural ventilation potential described in this invention, the determination of whether to activate the mechanical ventilation system includes, when the optimization objective is to minimize the operating time of the mechanical ventilation system; minimizing the operating time of the mechanical ventilation system means minimizing energy consumption, specifically the operating time of the ventilator representing the energy consumption level. , represented as: , Among them, the cumulative operating time of the ventilators was recorded. The ventilator opening time interval is divided into the initial concentration opening time interval. Periodic ventilator start-stop interval and the final control section Composition; the optimization objective is minimized as follows: , , Among them, the independent variable The upper and lower limits of equivalent pollutant concentration for ventilation control systems and The lower and upper concentration limits are used as optimization variables, and the optimization objectives are to minimize the health risk cost and minimize the mechanical ventilation system operating time. A multi-objective optimization algorithm is used to output the results.

[0013] As a preferred embodiment of the intelligent ventilation control method for residential buildings based on health needs and natural ventilation potential described in this invention, the step of controlling the operation of the mechanical ventilation system according to the optimal intermittent operation control strategy includes: after determining the optimal lower and upper concentration limits, monitoring the equivalent pollutant concentration in real time within a preset control period, and controlling the start and stop of the constant air volume ventilator: when the equivalent pollutant concentration reaches or exceeds the upper concentration limit, the ventilator is started; when the equivalent pollutant concentration drops to or below the lower concentration limit, the ventilator is turned off.

[0014] Another objective of this invention is to provide an intelligent ventilation control system for residential buildings based on health needs and natural ventilation potential. This system can determine whether a mechanical ventilation system needs to be activated based on the minimum ventilation volume required for health needs and the real-time natural ventilation volume. This solves the problem in current intelligent ventilation control methods for residential buildings that fail to fully utilize natural ventilation, resulting in excessively long operating times of mechanical ventilation systems and unnecessary energy consumption.

[0015] To address the aforementioned technical problems, this invention provides the following technical solution: a health requirement assessment and ventilation volume acquisition module, a ventilation strategy triggering judgment module, and a mechanical ventilation optimization control module. The health requirement assessment and ventilation volume acquisition module is used to determine the minimum health requirement ventilation volume for the target control area and acquire the real-time natural ventilation volume of the target control area. The ventilation strategy triggering judgment module is used to compare the minimum health requirement ventilation volume with the real-time natural ventilation volume to determine whether the mechanical ventilation system needs to be activated. The mechanical ventilation optimization control module is used to employ a multi-objective optimization algorithm to formulate an optimal intermittent operation control strategy and control the mechanical ventilation system to operate according to the optimal intermittent operation control strategy.

[0016] Another object of the present invention is to provide an intelligent ventilation control device for residential buildings based on health needs and natural ventilation potential, comprising a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of an intelligent ventilation control method for residential buildings based on health needs and natural ventilation potential.

[0017] Another object of the present invention is to provide a storage medium for intelligent ventilation control of residential buildings based on health needs and natural ventilation potential, wherein a computer program is stored thereon, and when the computer program is executed by a processor, the steps of the intelligent ventilation control method for residential buildings based on health needs and natural ventilation potential are implemented.

[0018] The beneficial effects of this invention are as follows: The intelligent ventilation control method for residential buildings based on health needs and natural ventilation potential provides by setting health-demand ventilation targets based on the dose-response relationship between ventilation volume and human health. Compared to control based on a single pollutant concentration, this method more comprehensively reflects human health needs. Utilizing natural ventilation volume as the basis for control decisions allows for more flexible responses to changes in indoor and outdoor environments and occupant behavior, fully utilizing natural ventilation and reducing unnecessary mechanical ventilation operation time. A multi-objective optimization algorithm determines the optimal intermittent operation strategy for the mechanical ventilation system, balancing health risks and energy consumption to achieve energy-efficient ventilation control. The method proposed in this invention has high computational efficiency and is easily integrated into smart home and building automation systems, providing technical support for achieving on-demand health ventilation control. Attached Figure Description

[0019] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 The above is an overall flowchart of a smart ventilation control method for residential buildings based on health needs and natural ventilation potential, provided in Embodiment 1 of the present invention.

[0021] Figure 2 This is a schematic diagram of the equivalent pollutant intermittent control principle of an intelligent ventilation control method for residential buildings based on health needs and natural ventilation potential, provided in Embodiment 1 of the present invention.

[0022] Figure 3The flowchart of a multi-objective optimized ventilation control strategy based on the SSA-Stacking natural ventilation volume prediction model, which is provided in Embodiment 1 of the present invention, is a smart ventilation control method for residential buildings based on health needs and natural ventilation potential. Detailed Implementation

[0023] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail 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 skilled in the art without creative effort should fall within the protection scope of the present invention.

[0024] Example 1, referring to Figures 1-3 As one embodiment of the present invention, a smart ventilation control method for residential buildings based on health needs and natural ventilation potential is provided, comprising: S1: Determine the minimum ventilation volume required for health in the target control area based on the dose-response relationship between ventilation volume and the health of the population in the area, and collect the real-time natural ventilation volume of the target control area.

[0025] Furthermore, the minimum ventilation required for health needs in the target control area is first determined. This ventilation volume is not based on simple standards or empirical values, but rather on a dose-response curve between ventilation volume and the health status of a specific population in the area (e.g., children or adults in residential buildings in cold regions). Studies have shown that lower ventilation volumes are associated with higher prevalence of respiratory illnesses or symptoms of sick building syndrome (SBS). Therefore, a minimum ventilation volume is set to be sufficient to reduce the health risk to an acceptable level for the population in the area. For example, for residential buildings in cold regions, based on relevant studies, a minimum ventilation volume of 6.5 h can be set when children reside there. -1 When no children reside in the premises, the time can be set to 2.5 hours. -1 This target ventilation volume forms the basis of the entire control strategy.

[0026] It should be noted that, to achieve dynamic control, this method requires obtaining the real-time natural ventilation volume of the target control area. Since natural ventilation is influenced by various complex factors and exhibits significant fluctuations, accurate real-time measurement is difficult. This invention preferably utilizes a stacking generalization model (SSA-Stacking) optimized by the Sparrow Search algorithm to obtain this value. This prediction model takes real-time indoor and outdoor environmental parameters (such as indoor temperature, outdoor temperature, indoor humidity, outdoor humidity, outdoor wind speed, and outdoor wind direction), occupant behavior habits (such as the opening and closing status of doors and windows), and basic building characteristics as input, and outputs a predicted value of natural ventilation volume for the current moment or a period in the future. This predicted value reflects the current potential for natural ventilation.

[0027] S2: Determine whether the mechanical ventilation system needs to be activated based on the minimum ventilation volume required for health and the real-time natural ventilation volume.

[0028] Furthermore, the real-time natural ventilation volume is compared with the set minimum ventilation volume required for health.

[0029] If the natural ventilation volume is greater than or equal to the minimum ventilation volume required for health, it means that the current natural ventilation volume is sufficient to meet health needs. In this case, there is no need to start or keep the mechanical ventilation system running, and the mechanical ventilation system can be turned off to save energy to the maximum extent.

[0030] If the natural ventilation volume is less than the minimum ventilation volume required for health, it means that the current natural ventilation volume is insufficient to meet health needs. In this case, it is necessary to start the mechanical ventilation system to supplement the air to ensure indoor air quality and the health of the residents.

[0031] It should be noted that when it is determined that the mechanical ventilation system needs to be started, this method will use a multi-objective optimization algorithm to determine the optimal intermittent operation control strategy of the mechanical ventilation system during the preset control period (e.g., the nighttime sleep period, 0:00-7:00).

[0032] To achieve intermittent control and balance health and energy consumption, the concept of "equivalent pollutants" is introduced. This equivalent pollutant represents various health-related pollutants (including CO2 and VOCs) in indoor air that need to be removed through ventilation. It is assumed that this equivalent pollutant has a constant emission rate indoors, and its concentration varies with ventilation volume, room volume, initial concentration, and outdoor concentration. When the mechanical ventilation system is on, the total ventilation volume is the sum of the rated ventilation volume of the mechanical ventilator and the natural ventilation volume; when the mechanical ventilation system is off, the total ventilation volume is the natural ventilation volume. By controlling the concentration of this equivalent pollutant between a set lower and upper limit, the intermittent start and stop of the mechanical ventilation system can be achieved.

[0033] The optimal intermittent operation control strategy involves finding the optimal lower and upper concentration limits. These parameters are determined by a multi-objective optimization algorithm, with the optimization objective being: Objective 1: Minimize Health Risk Costs (F1): Health risk costs are calculated based on the magnitude and duration of deviations of the equivalent pollutant concentration from the target stable concentration determined by the minimum ventilation volume required for health. Prolonged deviations of the equivalent pollutant concentration from the stable concentration corresponding to the minimum ventilation volume required for health increase health risk. To reflect the differences in health impacts due to varying degrees of deviation, tiered penalty factors can be set. For example, the greater the concentration exceeds the target stable concentration, the larger the penalty factor, and the higher the accumulated health risk cost. A reward factor (negative penalty) can also be set for concentrations below the target stable concentration. F1 is the integral of the accumulated health risk costs over the entire control period.

[0034] when At this time, the reward / penalty factor is 1. The equivalent instantaneous pollutant concentration at this time is expressed as: , when At this time, the reward / penalty factor is 5. The equivalent instantaneous concentration of the pollutant at this time is expressed as: , When 1.25 At this time, the reward / penalty factor is 10. The equivalent instantaneous concentration of the pollutant at this time is expressed as: , When 1.5 At this time, we do not want the pollutant concentration to be too high, so the reward / penalty factor is set to 100. The equivalent instantaneous pollutant concentration at this time is expressed as: , When 0.5 At this time, the reward / penalty factor is -5. The equivalent instantaneous pollutant concentration at this time is expressed as: , when At this time, the reward / penalty factor is -10. The equivalent instantaneous pollutant concentration at this time is expressed as: , The total integral over the entire ventilation time is: , in, Equivalent stable concentration of pollutants under ventilation conditions for health needs, in ppm; The equivalent instantaneous concentration of pollutants is expressed in ppm. Indicates time, in hours (h). The instantaneous concentration of the equivalent pollutant carrying reward and punishment factors is expressed in ppm.

[0035] Objective 2: Minimize the mechanical ventilation system operating time (F2): The operating time of the mechanical ventilation system is directly related to energy consumption. F2 is the cumulative operating time of the mechanical ventilation system within the entire preset control period. Minimizing F2 means minimizing energy consumption.

[0036] Ventilator running time, representing energy consumption level , represented as: , Among them, the cumulative operating time of the ventilators was recorded. The ventilator opening time interval is divided into the initial concentration opening time interval. Periodic ventilator start-stop interval and the final control section (Possible) composition.

[0037] The goal is to minimize both objective functions, which can be expressed mathematically as follows: , , Among them, the independent variable The upper and lower limits of equivalent pollutant concentration for ventilation control systems and .

[0038] Using the lower and upper concentration limits as optimization variables, and minimizing F1 and F2 as optimization objectives, a multi-objective optimization algorithm (e.g., the third-generation non-dominated genetic algorithm NSGA-III) is employed to solve the problem. NSGA-III can find the Pareto front solution set between these two conflicting objectives, i.e., a series of solutions that cannot improve either objective without sacrificing the other. From this Pareto front solution set, an optimal combination of the lower and upper concentration limits can be selected as the final control parameters based on actual needs (e.g., prioritizing health or energy conservation) or through a decision-making method (e.g., the ideal point method TOPSIS).

[0039] During the NSGA-III optimization process, it is necessary to simulate the equivalent pollutant concentration change curve for each potential combination during the control period and calculate the corresponding F1 and F2 values ​​as optimization targets. During the simulation, the initial concentration of the equivalent pollutant can be set as the stable concentration at the start of the control period under natural ventilation. The emission rate of the equivalent pollutant can be determined based on the health requirement ventilation rate and its corresponding target stable concentration (or by analogy with the human emission rate of specific pollutants such as CO2 and the outdoor background concentration), ensuring that it reaches the health requirement concentration under the health requirement natural ventilation rate.

[0040] S3: Control the operation of the mechanical ventilation system according to the optimal intermittent operation control strategy.

[0041] Furthermore, once the optimal lower and upper concentration limits are determined through multi-objective optimization, this method will monitor the equivalent pollutant concentration in real time (or predict its changes through a model) within a preset control period based on these parameters, and control the start and stop of the constant air volume ventilator. When the equivalent pollutant concentration reaches or exceeds the upper limit, the ventilator is activated.

[0042] When the equivalent pollutant concentration drops to or below the lower limit of concentration, turn off the ventilator.

[0043] This process continues until the preset control period ends. Because the predicted natural ventilation volume is dynamically changing, the rate of change of the equivalent pollutant concentration is also dynamically adjusted, allowing the start and stop times of mechanical ventilation to flexibly adapt to the actual situation.

[0044] Through the above steps, the method of the present invention can intelligently decide whether mechanical ventilation is needed based on the predicted natural ventilation volume, and achieve optimal balance control between health and energy consumption through multi-objective optimization when needed, effectively solving the problem of achieving healthy and energy-saving ventilation in complex environments using traditional methods.

[0045] Example 2, one embodiment of the present invention, provides an intelligent ventilation control system for residential buildings based on health needs and natural ventilation potential, including a health needs assessment and ventilation volume acquisition module, a ventilation strategy trigger judgment module, and a mechanical ventilation optimization control module.

[0046] The health needs assessment and ventilation volume acquisition module is used to determine the minimum ventilation volume required for the health needs of the target control area and to acquire the real-time natural ventilation volume of the target control area; the ventilation strategy trigger judgment module is used to compare the minimum ventilation volume required for health needs with the real-time natural ventilation volume to determine whether the mechanical ventilation system needs to be activated; the mechanical ventilation optimization control module is used to formulate the optimal intermittent operation control strategy using a multi-objective optimization algorithm and to control the operation of the mechanical ventilation system according to the optimal intermittent operation control strategy.

[0047] This embodiment also provides a computer device, including a memory and a processor. The memory stores a computer program, and when the processor executes the computer program, it implements the intelligent ventilation control method for residential buildings based on health needs and natural ventilation potential as proposed in the above embodiments.

[0048] This embodiment also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the intelligent ventilation control method for residential buildings based on health needs and natural ventilation potential as proposed in the above embodiments.

[0049] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, essentially, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0050] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-including system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device.

[0051] More specific examples of computer-readable media (a non-exhaustive list) include: electrical connections (electronic devices) having one or more wires, portable computer disk drives (magnetic devices), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Furthermore, computer-readable media can even be paper or other suitable media on which the program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in computer memory.

[0052] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0053] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for intelligent ventilation control in residential buildings based on health needs and natural ventilation potential, characterized in that, include: The minimum ventilation volume required for health in the target control area is determined based on the dose-response relationship between ventilation volume and the health of the regional population, and the real-time natural ventilation volume of the target control area is collected. Determine whether the mechanical ventilation system needs to be activated based on the minimum ventilation volume required for health and the real-time natural ventilation volume. Control the operation of the mechanical ventilation system according to the optimal intermittent operation control strategy; Starting the mechanical ventilation system includes, if it is determined that the mechanical ventilation system needs to be started, using a multi-objective optimization algorithm to determine the optimal intermittent operation control strategy of the mechanical ventilation system within a preset control period; The determination of whether the mechanical ventilation system needs to be activated includes, The real-time natural ventilation volume is compared with the set minimum ventilation volume for health requirements; When the natural ventilation volume is greater than or equal to the minimum ventilation volume required for health, it means that the current natural ventilation volume is sufficient to meet health requirements, and there is no need to start or keep the mechanical ventilation system running. When the natural ventilation volume is less than the minimum ventilation volume required for health, it means that the current natural ventilation volume is insufficient to meet health requirements, and the mechanical ventilation system needs to be activated to make up the air. When it is determined that the mechanical ventilation system needs to be activated, a multi-objective optimization algorithm is used to determine the optimal intermittent operation control strategy of the mechanical ventilation system within a preset control period. When the mechanical ventilation system is turned on, the total ventilation volume is the sum of the rated ventilation volume of the mechanical ventilator and the natural ventilation volume; When the mechanical ventilation system is turned off, the total ventilation volume is equal to the natural ventilation volume; The mechanical ventilation system is intermittently started and stopped by controlling the equivalent pollutant concentration to be maintained between the set lower and upper limits. The optimal intermittent operation control strategy outputs the optimal lower and upper limits of concentration parameters. The optimal lower and upper concentration limits are determined by a multi-objective optimization algorithm; The optimal lower and upper concentration limits are determined by a multi-objective optimization algorithm, including: When the optimization objective is to minimize the health risk cost; The health risk cost is based on the deviation of the equivalent pollutant concentration from the target stable concentration and time determined by the minimum ventilation volume for health requirements. A graded penalty factor is set to express the difference in health impacts of the same degree of deviation, and the health risk cost is minimized as the integral of the accumulated health risk cost over the entire control period; when When the reward / penalty factor is 1, the equivalent instantaneous concentration of pollutants is expressed as: ， When the reward / penalty factor is 5, the equivalent instantaneous concentration of pollutants is expressed as: ， When 1.25 When the reward / penalty factor is 10, the equivalent instantaneous concentration of pollutants is expressed as: ， When 1.5 When the reward / penalty factor is set to 100, the equivalent instantaneous concentration of pollutants is expressed as: ， When 0.5 When the reward / penalty factor is -5, the equivalent instantaneous concentration of pollutants is expressed as: ， when When the reward / penalty factor is -10, the equivalent instantaneous concentration of pollutants is expressed as: ， The integral over the entire ventilation time is expressed as: ， To ensure the stable concentration of equivalent pollutants under ventilation conditions for health purposes, This represents the equivalent instantaneous concentration of pollutants. Indicates time, The instantaneous concentration of the equivalent pollutant carrying reward and punishment factors.

2. The intelligent ventilation control method for residential buildings based on health needs and natural ventilation potential as described in claim 1, characterized in that: The minimum ventilation volume required for health needs includes, The ventilation and health dose-response relationship curves were determined based on specific population groups and regional climate characteristics, and set to ensure that the health risk to the population is at the lowest possible ventilation level. The specific population refers to children or adults living in residential buildings in cold regions.

3. The intelligent ventilation control method for residential buildings based on health needs and natural ventilation potential as described in claim 1, characterized in that: The real-time natural ventilation volume of the target control area includes... Using the SSA-Stacking machine learning prediction model, the natural ventilation volume of a region is predicted based on real-time indoor and outdoor environmental parameters, resident behavior habits, and basic building characteristics.

4. The intelligent ventilation control method for residential buildings based on health needs and natural ventilation potential as described in claim 3, characterized in that: The determination of whether the mechanical ventilation system needs to be activated includes, When the optimization objective is to minimize the uptime of the mechanical ventilation system; Minimizing the operating time of the mechanical ventilation system is equivalent to minimizing energy consumption; the operating time of the ventilator represents the energy consumption level. , is represented as: ， Among them, the cumulative operating time of the ventilators was recorded. The ventilator opening time interval is divided into the initial concentration opening time interval. Periodic ventilator start-stop interval and the final control section constitute; The optimization objective is minimized as follows: ， ， Among them, the independent variable The upper and lower limits of equivalent pollutant concentration for ventilation control systems and ; The lower and upper concentration limits are used as optimization variables, and the optimization objectives are to minimize the health risk cost and minimize the mechanical ventilation system operation time. A multi-objective optimization algorithm is used to output the results.

5. The intelligent ventilation control method for residential buildings based on health needs and natural ventilation potential as described in claim 4, characterized in that: The control of the mechanical ventilation system based on the optimal intermittent operation control strategy includes... After determining the optimal lower and upper concentration limits, the equivalent pollutant concentration is monitored in real time during the preset control period, and the start and stop of the constant air volume ventilator are controlled accordingly. When the equivalent pollutant concentration reaches or exceeds the upper limit, activate the ventilator. When the equivalent pollutant concentration drops to or below the lower limit of concentration, turn off the ventilator.

6. A residential building intelligent ventilation control system based on health needs and natural ventilation potential, employing the residential building intelligent ventilation control method based on health needs and natural ventilation potential as described in any one of claims 1 to 5, characterized in that: It includes a health needs assessment and ventilation volume acquisition module, a ventilation strategy trigger judgment module, and a mechanical ventilation optimization control module; The health demand assessment and ventilation volume acquisition module is used to determine the minimum ventilation volume required for the health demand of the target control area and to acquire the real-time natural ventilation volume of the target control area. The ventilation strategy triggering judgment module is used to compare the minimum ventilation volume required for health with the real-time natural ventilation volume to determine whether the mechanical ventilation system needs to be activated. The mechanical ventilation optimization control module is used to formulate the optimal intermittent operation control strategy using a multi-objective optimization algorithm, and control the operation of the mechanical ventilation system according to the optimal intermittent operation control strategy.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the intelligent ventilation control method for residential buildings based on health needs and natural ventilation potential, as described in any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the intelligent ventilation control method for residential buildings based on health needs and natural ventilation potential, as described in any one of claims 1 to 5.

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