A building environmental optimization control system and method

Abstract

The application provides a kind of building environment optimization control system and method, system includes the new fan unit and air pipe being arranged in the space area of building, the new fan unit has high-efficiency filter screen, electrostatic precipitator, frequency conversion fan in, the air speed instrument and actuator are installed in the air pipe;Intelligent environment monitoring sensor is arranged in the space area of building, including particulate matter detector, harmful gas concentration sensor, temperature and humidity sensor;With the controller being connected with the intelligent environment monitoring sensor, air speed instrument, actuator and frequency conversion fan electric cabinet, with the switch being connected with the controller, with the upper management device being connected with the switch, including server and management workstation.The particulate matter in the new air and return air sent into the room is removed by the high-efficiency filter screen and electrostatic precipitator.A unique system linkage control method is designed to optimize the indoor air quality and compensate the indoor temperature and humidity.

Description

Technical Field

[0001] This invention relates to the field of building interior environment optimization technology, and in particular to a building environment optimization control system and method. Background Technology

[0002] Modern architecture aims for the harmonious development of people, buildings, and the natural environment. While utilizing natural conditions and artificial means to create a good and healthy living environment, it strives to control and minimize the use and damage to the natural environment, fully reflecting a balance between what we take from and what we give back to nature. Modern architecture emphasizes indoor air quality, and factors affecting air quality include airflow and air cleanliness.

[0003] Currently, the common practice in buildings is to use indoor CO2 concentration as a limit and control the fresh air volume according to changes in CO2 concentration to maintain indoor CO2 balance. This method of indoor environmental control is too simplistic and does not significantly control or improve indoor air cleanliness, air pollutants, or airflow velocity. Summary of the Invention

[0004] This invention provides a building environment optimization control system and method. Based on feedback from various environmental sensors, it improves indoor particulate matter, harmful gases, temperature and humidity by controlling the fresh air system, thereby achieving the goal of optimizing indoor air cleanliness, air quality, and human comfort.

[0005] To address the problem of overly simplistic indoor environment control methods, this invention provides a building environment optimization control system, comprising:

[0006] The fresh air unit and ductwork are installed in the fresh air system of the building space area. The fresh air unit has a high-efficiency filter, an electrostatic dust removal device and a variable frequency fan. The ductwork includes a fresh air duct, a supply air duct, a return air duct and an exhaust air duct. Several anemometers and several actuators are installed in the ductwork.

[0007] Several intelligent environmental monitoring sensors and fan control cabinets are installed in the interior space of the building.

[0008] A controller connected to the intelligent environmental monitoring sensors, actuators, and fan control cabinet;

[0009] The switch connected to the controller;

[0010] The upper-level management device connected to the switch.

[0011] Furthermore, in the above system, the variable frequency fan includes a blower and an exhaust fan, and the fan electrical control cabinet integrates the power supply and control circuits of the fan for power supply and local control of the fan.

[0012] Furthermore, in the above system, several of the anemometers are respectively installed on the fresh air duct, supply air duct, return air duct and exhaust air duct, the actuators include hot and cold water valves, humidification valves and branch end electric regulating valves, and several of the intelligent environmental monitoring sensors are evenly distributed in the building space area, the intelligent environmental monitoring sensors include particulate matter detectors, harmful gas detectors and temperature and humidity detectors.

[0013] Furthermore, in the above system, the controller includes a main controller and sub-controllers, which are interconnected. The sub-controllers are connected to intelligent environmental monitoring sensors, anemometers, actuators, and wind turbine control cabinets. The switches are wired to the controllers and upper-level management devices, which include servers and management workstations and are equipped with professional upper-level management software.

[0014] According to another aspect of the present invention, a method for controlling indoor air quality in buildings is also provided, which employs any of the above-mentioned building environment optimization control systems. The method includes air volume balance control, air quality optimization control, relative humidity optimization control, and temperature compensation control. Each control method can continuously optimize and set control parameters according to the operation of the system.

[0015] Furthermore, the airflow balance control includes:

[0016] Step S1: Based on the wind speed requirements of the building's indoor fresh air system, determine the maximum and minimum air supply velocities of the main air supply duct, and determine the maximum and minimum fan frequency limits of the air supply fan by observing the feedback data from the anemometer in the air supply duct.

[0017] Step S2: Compare the maximum and minimum airflow velocities in the main air supply duct with the data fed back by the air supply anemometer in the air supply duct, and determine the maximum and minimum fan frequency limits of the blower.

[0018] Step S3: Within the specified range, simultaneously turn on the supply fan and exhaust fan. By observing the feedback data from the fresh air anemometer, supply air anemometer, return air anemometer, and exhaust air anemometer, continuously adjust and test the operating frequency of the supply fan and exhaust fan to balance the indoor air volume, and calculate the ratio coefficient of the operating frequency of the supply and exhaust fans to achieve air volume balance.

[0019] Step S4: When the fresh air system is started, the supply fan and exhaust fan operate in conjunction with each other at a frequency according to this proportional coefficient.

[0020] Furthermore, the building indoor air quality optimization and control includes:

[0021] Step S10: Using the minimum airflow velocity in the air supply duct as the initial set value, and based on the real-time feedback wind speed measured by the anemometer on the main air supply duct, the main controller uses PID mode to control the frequency of the air supply fan and adjust the wind speed of the main air supply duct to the initial set value.

[0022] Step S20: By gradually increasing the air supply volume setting value, find the air supply velocity gradient value associated with the standard air quality index (IAQI) (i.e., the air quality index level 1 (excellent 0-50) and level 2 (good 51-100) gradients calculated based on the concentration limits of PM2.5, PM10, CO, etc. set by national standards) in the service area of ​​the fresh air unit, and send the gradient value to the upper management software for statistics and analysis. Through continuous testing and big data analysis and calculation, a suitable air supply velocity gradient table for the service area is formed.

[0023] In step S30, the upper-level management software determines the air supply velocity gradient value based on the weighted average of all real-time feedback data such as PM2.5, PM10, and CO within the overall service area of ​​the fresh air unit. After receiving the air supply velocity set value from the upper-level management software, the main controller uses PID mode to control the frequency of the air supply fan based on the real-time wind speed feedback from the anemometer on the main air supply pipe, so that the air supply velocity is stabilized at the set value, thereby achieving a one-time adjustment of the ambient air quality.

[0024] Step S40: Based on the indicators and requirements for PM2.5, PM10, CO, CO2, and formaldehyde in the building's interior, select the set values ​​for each data point. Compare the real-time feedback data from the PM2.5 detector, PM10 detector, CO concentration sensor, CO2 concentration sensor, and formaldehyde concentration sensor in a single room. The sub-controller calculates and selects the data point with the highest excess ratio from the above feedback data. Based on this set value, the sub-controller uses PID mode to control the opening of the electric regulating valve at the end of the branch pipe, adjusting the air volume delivered to the service unit area, thus completing the secondary adjustment of the ambient air quality by the control system.

[0025] In step S50, if, after a period of adjustment as described above, any one of the environmental data such as PM2.5, PM10, CO, CO2, or formaldehyde in the overall service area of ​​the fresh air unit still exceeds the concentration limit, the main controller will control the frequency of the fresh air unit's air supply fan to be adjusted to the frequency of the maximum allowable air supply velocity, keeping the air continuously circulating until the environmental data meets the requirements. After that, the control system will return to the PID tracking control mode of the air supply velocity gradient value. Finally, the optimized control of the air quality in the overall service area of ​​the fresh air unit is completed.

[0026] Furthermore, the optimized control of indoor relative humidity in the building includes:

[0027] Step S100: The upper-level management software sets the relative humidity standard range (40-80% in summer, 30-60% in winter) for the overall service area of ​​the fresh air unit according to national standards, and sets the relative humidity gradient table for summer and winter in the building interior.

[0028] Step S200: Determine the relative humidity gradient value based on the weighted average of the humidity feedback data of the overall service area of ​​the fresh air system. After receiving the relative humidity set value from the upper management software, the main controller uses PID mode to control the opening of the humidification valve to adjust the air humidity in the air supply duct based on the humidity data feedback from the air supply temperature and humidity detector 301 on the air supply duct, thereby completing the first adjustment of the relative humidity of the air in the air supply duct by the control system.

[0029] In step S300, the upper-level management software determines the relative humidity gradient value of the service unit area based on real-time data feedback of the relative humidity. After receiving the relative humidity setpoint from the upper-level management software, the sub-controller, based on the humidity feedback from the return air temperature and humidity detector within the service unit area, uses PID mode to control the opening of the electric regulating valve at the end of the branch pipe, adjusting the airflow into the service unit area, thus completing the secondary adjustment of the relative humidity of the air in the supply air branch pipe by the control system. The priority of relative humidity control within the service unit area is lower than that of air quality control. Finally, the optimized control of the relative humidity of the entire service area of ​​the fresh air unit is completed.

[0030] Furthermore, the building indoor temperature compensation control includes:

[0031] Step S1000: The upper-level management software sets the temperature standard range (22-28℃ in summer, 16-24℃ in winter) of the overall service area of ​​the fresh air unit according to national standards, and sets the temperature gradient table of the building's indoor temperature in summer and winter.

[0032] Step S2000: Determine the temperature gradient value based on the weighted average of the temperature feedback data of the overall service area of ​​the fresh air system. After receiving the temperature setpoint from the upper management software, the main controller uses PID mode to control the opening of the hot and cold water valves to adjust the air temperature in the air supply duct based on the temperature data feedback from the air supply temperature and humidity detector on the main air supply duct, thereby completing the first compensation adjustment of the air temperature in the main air supply duct by the control system.

[0033] In step S3000, based on the temperature data feedback set on the temperature control panel of the fresh air system service unit area, the sub-controller uses PID mode to control the opening of the electric regulating valve at the end of the branch pipe, adjusting the air volume supplied to the service unit area, and completing the secondary compensation adjustment of the ambient temperature by the control system. Since the fresh air system has a relatively small impact on the ambient temperature of the service unit area within the building, the priority of temperature compensation control in the service unit area is lower than that of relative humidity control. Finally, the optimized control of the overall service area temperature of the fresh air unit is completed.

[0034] Furthermore, in the aforementioned system, the management workstation displays the status of all equipment in the fresh air system and the building's internal environmental data; simultaneously, the upper-level management software accumulates the operating data of the fresh air system, utilizes big data intelligent analysis to generate transitional season fresh air modes, nighttime fresh air modes, and intelligent fresh air schedules, thereby promoting energy conservation in buildings and improving the perceived comfort of the building environment.

[0035] Furthermore, the aforementioned transitional season fresh air mode meets the building energy-saving requirements during the transitional season through reasonable fresh air system control; that is, during the transitional season, the upper-level management software sets an outdoor temperature trigger limit range (human comfort temperature). When the outdoor temperature is within this limit range, it sends a command to the fresh air system to deliver air into the building at maximum wind speed, utilizing natural resources to provide maximum compensation for indoor temperature and reduce the energy consumption of indoor air conditioning.

[0036] Similarly, the nighttime fresh air mode is achieved by controlling the fresh air system in a reasonable way to meet the energy-saving requirements of buildings at night; that is, the upper-level management software sets the nighttime outdoor temperature trigger limit range and sends instructions to the fresh air system to deliver air into the building at a fixed wind speed, thereby reducing the energy consumption of indoor air conditioning.

[0037] Furthermore, the intelligent fresh air schedule is generated by the upper-level management software through intelligent analysis of accumulated big data on the operation of the fresh air system and by utilizing the learning capabilities of artificial intelligence software to form an optimal operating schedule for the fresh air system that takes into account indoor environmental temperature, humidity, air quality, and meets the building's low energy consumption requirements.

[0038] Compared with existing technologies, this invention utilizes a big data platform, controller, fresh air unit, and environmental monitoring within the building to optimize indoor air quality and compensate for indoor temperature and humidity. This invention employs intelligent sensors to monitor the building environment in real time, including PM2.5, PM10, CO, CO2, and formaldehyde, exceeding the construction standards of general buildings and meeting building requirements. The controller, based on real-time feedback data from various environmental monitoring systems, uses PID control to coordinate and control the electromechanical equipment within the fresh air system. Through multiple cycles of adjustment, it achieves airflow balance, air quality optimization, and temperature and humidity compensation control within the building, representing an innovative environmental control method for buildings. The upper-level management software (big data platform) serves as the central brain of the entire control system, capable of real-time display, statistical analysis, and processing of various equipment statuses, environmental parameters, airflow velocity, and other data. It also comprehensively designs intelligent operating modes for the control system, sets system control strategies, and continuously updates and optimizes system operation decisions during operation. This invention utilizes big data, artificial intelligence, intelligent sensors, and automatic control technologies, fully demonstrating its creativity and novelty. Attached Figure Description

[0039] Figure 1 This is a structural diagram of a building environment optimization control system according to an embodiment of the present invention;

[0040] Figure 2 This is a schematic diagram of a building environment optimization control system according to an embodiment of the present invention;

[0041] Figure 3 This is a flowchart of an embodiment of the air volume balance control method of the present invention;

[0042] Figure 4 This is a schematic diagram of a primary adjustment for air quality optimization control according to an embodiment of the present invention;

[0043] Figure 5 This is a schematic diagram of secondary adjustment for air quality optimization control according to an embodiment of the present invention;

[0044] Figure 6 This is a flowchart of an air quality optimization control method according to an embodiment of the present invention;

[0045] Figure 7 This is a schematic diagram of a single adjustment for relative humidity optimization control according to an embodiment of the present invention;

[0046] Figure 8 This is a schematic diagram of secondary adjustment for relative humidity optimization control according to an embodiment of the present invention;

[0047] Figure 9 This is a flowchart of a relative humidity optimization control method according to an embodiment of the present invention;

[0048] Figure 10This is a schematic diagram of a primary adjustment of temperature compensation control according to an embodiment of the present invention;

[0049] Figure 11 This is a schematic diagram of the secondary adjustment of temperature compensation control according to an embodiment of the present invention;

[0050] Figure 12 This is a flowchart of a temperature compensation control method according to an embodiment of the present invention.

[0051] As shown in the figure:

[0052] 10. High-efficiency filter; 11. Electrostatic dust collector; 100. Fan control cabinet; 101. Supply fan control cabinet; 102. Supply fan; 103. Exhaust fan control cabinet; 104. Exhaust fan; 200. Particulate matter detector; 201. PM2.5 detector; 202. PM10 detector; 300. Temperature and humidity detector; 301. Supply air temperature and humidity detector; 302. Return air temperature and humidity detector; 400. Hazardous gas detector; 401. CO concentration sensor; 402. CO2 concentration sensor. Devices, 403, Formaldehyde concentration sensor, 500, Anemometer, 501, Fresh air anemometer, 502, Supply air anemometer, 503, Return air anemometer, 504, Exhaust air anemometer, 600, Actuator, 601, Hot and cold water valve, 602, Humidifier valve, 603, Branch pipe end electric regulating valve, 700, Controller, 701, Main controller, 702, Sub-controller, 800, Switch, 900, Upper management equipment, 901, Server, 902, Management workstation, 903, Upper management software. Detailed Implementation

[0053] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0054] like Figure 1 As shown, the present invention provides a building environment optimization control system, comprising:

[0055] The fresh air unit and ductwork of the fresh air system are installed in the building space area. The fresh air unit has a high-efficiency filter 10, an electrostatic dust removal device 11 and a variable frequency fan. The ductwork includes a fresh air duct, a supply air duct, a return air duct and an exhaust air duct. Several anemometers 500 and several actuators 600 are installed in the ductwork. Several intelligent environmental monitoring sensors and a fan control cabinet 100 are installed in the building space area. The intelligent environmental monitoring sensors include a particulate matter detector 200, a harmful gas detector 400 and a temperature and humidity detector 300. A controller 700 is connected to the intelligent environmental monitoring sensors, actuators 600 and fan control cabinet 100. A switch 800 is connected to the controller 700. A host management device 900 is connected to the switch 800.

[0056] like Figure 2 As shown, in one embodiment of the present invention, the high-efficiency filter 10 and the electrostatic dust removal device 11 in the fresh air unit can effectively filter out dust particles in the outdoor fresh air and indoor return air, ensuring that the supplied air meets the indoor quality standards; the high-efficiency filter 10 and the electrostatic dust removal device 11 have an alarm device for reminding users to clean and replace the filter and dust removal cover.

[0057] like Figure 2 As shown, in one embodiment of the present invention, the variable frequency fan includes a blower 102 and an exhaust fan 104. The fan electrical control cabinet 100 is divided into a blower electrical control cabinet 101 and an exhaust fan electrical control cabinet 103. The electrical control cabinet integrates the power supply and control circuits of the fan, which are used for the power supply and local control of the blower 102 and the exhaust fan 104, respectively.

[0058] like Figure 2 As shown, in one embodiment of the present invention, anemometers 500 are respectively installed in the fresh air duct, supply air duct, return air duct, and exhaust air duct, and are respectively a fresh air anemometer 501, a supply air anemometer 502, a return air anemometer 503, and an exhaust air anemometer 504, used to monitor the wind speed in the ducts; the actuator 600 includes a hot and cold water valve 601, a humidifying valve 602, and a branch pipe end electric regulating valve 603. The hot and cold water valve 601 is used to control the temperature of the air supplied into the building, the humidifying valve 602 is used to control the humidity of the air supplied into the building, and the branch pipe end electric regulating valve 603 is used to control the air volume supplied into the service unit area.

[0059] like Figure 2 As shown, in one embodiment of the present invention, several intelligent environmental monitoring sensors are evenly distributed in the building space area. The particulate matter detector 200 includes a PM2.5 detector 201 and a PM10 detector 202, and the harmful gas detector 400 includes a CO concentration sensor 401, a CO2 concentration sensor 402, and a formaldehyde concentration sensor 403. The above detectors and the temperature and humidity detector 300 can acquire real-time environmental data such as PM2.5, PM10, CO, CO2, formaldehyde, temperature and humidity in the service area of ​​the fresh air unit.

[0060] like Figure 1 With Figure 2As shown, in one embodiment of the present invention, the controller 700 is divided into a main controller 701 and a sub-controller 702, which are connected in a ring network or star topology. The sub-controller 702 is connected to the particulate matter detector 200, temperature and humidity detector 300, harmful gas detector 400, anemometer 500, actuator 600, and fan control cabinet 100 via wired or wireless connection. The main controller 701 is mainly used for switching the control mode of the entire area served by the fresh air unit, controlling the supply fan 102, exhaust fan 104, hot and cold water valve 601, humidification valve 602, and collecting data detected by intelligent environmental monitoring sensors, as well as the status data of actuator 600 and supply fan 102 and exhaust fan 104. The sub-controller is used to collect data detected by intelligent environmental monitoring sensors in the area served by the fresh air unit, the status data of actuator 600 and supply fan 102 and exhaust fan 104, and control the electric regulating valve 603 at the end of the branch pipe.

[0061] In one embodiment of the present invention, the switch 800 is connected to the controller 700 and the upper management device 900 via wired connection, transmitting the data collected by the controller 700 to the upper management device 900; the upper management device 900 includes a server 901 and a management workstation 902, and is equipped with professional upper management software 903 for storing environmental data, performing comprehensive statistical analysis, issuing instructions and displaying data.

[0062] According to another aspect of the present invention, a method for controlling indoor air quality in buildings is provided, utilizing any one of the above-mentioned building environment optimization control systems. The control method includes air volume balance control, air quality optimization control, relative humidity optimization control, and temperature compensation control. Each control method can continuously optimize the set control parameters according to the operation of the system.

[0063] like Figure 3 As shown, in one embodiment of the present invention, the airflow balance control includes:

[0064] Step S1: Determine the maximum and minimum air supply velocities of the main air supply duct based on the wind speed requirements of the building's indoor fresh air system.

[0065] Step S2: Compare the maximum and minimum airflow velocities in the main air supply duct with the data fed back by the air supply anemometer 502 in the air supply duct, and determine the maximum and minimum fan frequency limits of the blower 102.

[0066] Step S3: Within the specified range, simultaneously turn on the supply fan 102 and the exhaust fan 104. By observing the feedback data from the fresh air anemometer 501, the supply air anemometer 502, the return air anemometer 503, and the exhaust air anemometer 504, continuously adjust and test the operating frequency of the supply fan and the exhaust fan to balance the indoor air volume, and calculate the proportional coefficient of the operating frequency of the supply and exhaust fans to achieve air volume balance.

[0067] In step S4, when the fresh air system is started, the supply fan 102 and the exhaust fan 104 operate in conjunction with each other at a frequency proportional to this coefficient.

[0068] Air volume balance control is based on the real-time air velocity detected by the anemometer 500 in the fresh air duct, supply air duct, return air duct and exhaust air duct, while ensuring that the supply air duct meets the minimum and maximum air velocity requirements. It also controls the frequency of the supply fan 102 and exhaust fan 104 to ensure the air volume balance in the building.

[0069] like Figure 4 , 5 As shown in Figures 6 and 7, in one embodiment of the present invention, air quality optimization control includes:

[0070] Step S10: Using the minimum airflow velocity of the air supply duct as the initial set value, and based on the real-time wind speed measured by the air supply anemometer 502 on the main air supply duct as the feedback, the main controller 701 uses PID mode to control the frequency of the blower 102 and adjusts the wind speed of the main air supply duct to the initial set value.

[0071] Step S20: By gradually increasing the set value of the air supply velocity, find the air supply velocity gradient value associated with the standard air quality index (IAQI) (i.e., the air quality index level 1 (excellent 0-50) and level 2 (good 51-100) gradients calculated based on the concentration limits of PM2.5, PM10, CO, etc. set by national standards) in the service area of ​​the fresh air unit, and send the gradient value to the upper management software 903 for statistics and analysis. Through continuous testing and big data analysis, a suitable air supply velocity gradient table for the service area is formed.

[0072] In step S30, the upper management software 903 determines the air supply velocity gradient value based on the weighted average of all real-time feedback data such as PM2.5, PM10, and CO within the overall service area of ​​the fresh air unit. After receiving the air supply velocity set value from the upper management software 903, the main controller 701 uses the real-time wind speed measured by the air supply anemometer 502 on the main air supply pipe as feedback and adopts PID mode to control the frequency of the air supply fan 102 to stabilize the air supply velocity at the set value, thereby achieving one-time adjustment of the ambient air quality.

[0073] Step S40: Select set values ​​for each of the individual indicators and requirements of PM2.5, PM10, CO, CO2, and formaldehyde in the building, and compare the real-time feedback data of PM2.5 detector 201, PM10 detector 202, CO concentration sensor 401, CO2 concentration sensor 402, and formaldehyde concentration sensor 403 in a single room. The sub-controller 702 selects the data with the highest excess ratio from the above feedback data. Based on the set value of this data and the real-time feedback, the opening degree of the electric regulating valve 603 at the end of the branch pipe is controlled using PID mode. By adjusting the air volume delivered to a single room, the control system completes the secondary adjustment of the indoor ambient air quality.

[0074] In step S50, if, after a period of adjustment as described above, any one of the environmental data such as PM2.5, PM10, CO, CO2, or formaldehyde in the overall service area of ​​the fresh air unit still exceeds the concentration limit, the main controller 701 will adjust the frequency of the air supply fan 102 to the frequency of the maximum allowable air supply velocity, keeping the air continuously circulating until the environmental data meets the requirements. Then, the control system will return to the PID tracking air supply velocity gradient control mode. Finally, the optimized control of the air quality in the overall service area of ​​the fresh air unit is completed.

[0075] Air quality optimization control is based on testing and identifying the correlation of supply air velocity gradient values ​​according to the standard air quality index level. The upper-level management software generates a supply air velocity gradient table for the service area. Based on the real-time feedback data of PM2.5, PM10, CO, CO2, formaldehyde, etc. in the overall service area, the main controller 701 uses PID mode to control the frequency of the supply fan 102 to track the set supply air velocity, completing the first adjustment of the air quality in the overall service area. Based on the standard set values ​​and real-time feedback of PM2.5, PM10, CO, CO2, formaldehyde in the service unit area, the sub-controller 702 uses PID mode to control the opening of the electric regulating valve 603 at the end of the branch pipe to track the set value of any of the above indicators, completing the second adjustment of the air quality in the service unit area.

[0076] like Figure 7 , 8 As shown in Figures 9 and 1, in one embodiment of the present invention, relative humidity optimization control includes:

[0077] Step S100: Set the relative humidity standard range for the entire service area of ​​the fresh air unit according to national standards (40-80% in summer and 30-60% in winter), and set the relative humidity gradient table for summer and winter in the building's indoor environment in the upper management software 903.

[0078] Step S200: The relative humidity gradient value is determined based on the weighted average value of the humidity feedback data of the overall service area of ​​the fresh air system. After receiving the relative humidity setpoint from the upper management software 903, the main controller 701 uses the real-time humidity data of the air supply temperature and humidity detector 301 on the air supply duct as feedback and adopts PID mode to control the opening of the humidification valve 602 to adjust the air humidity in the air supply duct, thus completing the first adjustment of the relative humidity of the air in the air supply duct by the control system.

[0079] In step S300, based on real-time data feedback of relative humidity in the fresh air system service unit area, the upper-level management software 903 determines the relative humidity gradient value for that area. After receiving the relative humidity setpoint from the upper-level management software 903, the sub-controller 702, based on real-time humidity feedback from the return air temperature and humidity detector 302 in a single room, uses PID mode to control the opening of the electric regulating valve 603 at the end of the branch pipe, adjusting the airflow into the single room, thus completing the secondary adjustment of the relative humidity of the air in the supply air branch pipe by the control system. The relative humidity control in a single room has a lower priority than air quality control. Finally, the optimized control of the relative humidity of the entire service area of ​​the fresh air unit is completed.

[0080] The relative humidity optimization control is based on setting the relative humidity gradient value of the overall service area according to national standards. Based on the primary setpoint of relative humidity in the overall service area and the real-time humidity feedback from the temperature and humidity detector 300 on the main air supply duct, the main controller 701 uses PID mode to control the opening of the humidification valve 602 to track the primary setpoint of relative humidity and complete the primary adjustment of relative humidity in the overall service area. Based on the real-time humidity feedback from the temperature and humidity detector 300 in the service unit area and the secondary setpoint of relative humidity, the sub-controller 702 uses PID mode to control the opening of the electric regulating valve 603 at the end of the branch pipe to track the secondary setpoint of relative humidity and complete the secondary adjustment of relative humidity in the service unit area. The relative humidity control in the service unit area has a lower priority than air quality control.

[0081] like Figure 10 , 11 As shown in Figures 1 and 12, in one embodiment of the present invention, temperature compensation control includes:

[0082] Step S1000: Set the temperature standard range for the entire service area of ​​the fresh air unit according to national standards (22-28℃ in summer, 16-24℃ in winter), and set the temperature gradient table for the building's indoor temperature in summer and winter according to the upper management software 903.

[0083] Step S2000: Determine the temperature gradient value based on the weighted average of the temperature feedback data of the overall service area of ​​the fresh air system. After receiving the temperature setpoint from the upper management software 903, the main controller 701 uses PID mode to control the opening of the hot and cold water valve 601 to adjust the air temperature in the air supply duct based on the temperature data feedback from the air supply temperature and humidity detector on the main air supply duct, thereby completing the first compensation adjustment of the air temperature in the main air supply duct by the control system.

[0084] In step S3000, based on the temperature data feedback set on the individual room temperature control panel of the fresh air system, the sub-controller 702 uses PID mode to control the opening of the electric regulating valve 603 at the end of the branch pipe, adjusting the air volume supplied to the individual room, and completing the secondary compensation adjustment of the ambient temperature by the control system. Since the fresh air system has a relatively small impact on the ambient temperature of the service unit area within the building, the compensation control of the individual room temperature has a lower priority than the relative humidity control. Finally, the optimized control of the temperature of the entire service area of ​​the fresh air unit is completed.

[0085] Temperature compensation control is based on setting the overall service area temperature gradient value according to national standards. Based on the primary setpoint of the overall service area temperature and the real-time temperature feedback from the temperature and humidity detector 300 on the main air supply duct, the main controller 701 uses PID mode to control the opening of the hot and cold water valves 601 to track the primary setpoint of the temperature and complete the primary compensation adjustment of the air supply temperature by the control system. Based on the temperature value set on the temperature control panel of the service unit area and the real-time temperature feedback from the temperature and humidity detector 300, the sub-controller 702 uses PID mode to control the opening of the electric regulating valve 603 at the end of the branch pipe to track the setpoint of the temperature control panel and complete the secondary compensation adjustment of the temperature of the service unit area.

[0086] In one embodiment of the present invention, the management workstation 902 displays the status of all equipment in the fresh air system and the building's internal environmental data; at the same time, the upper-level management software 903 accumulates the operating data of the fresh air system, uses big data intelligent analysis to form transitional season fresh air mode, nighttime fresh air mode and intelligent fresh air schedule, etc., to promote energy conservation in the building and improve the physical comfort of the building environment.

[0087] The transitional season fresh air mode is designed to meet the building energy-saving requirements during the transitional season through reasonable control of the fresh air system. Specifically, during the transitional season, the upper-level management software 903 sets an outdoor temperature trigger limit range (human comfort temperature). When the outdoor temperature is within this limit range, it sends a command to the fresh air system to deliver air into the building at maximum wind speed, making full use of natural resources to compensate for indoor temperature to the greatest extent and reduce the energy consumption of indoor air conditioning.

[0088] Similarly, the nighttime fresh air mode meets the building's energy-saving requirements at night through reasonable control of the fresh air system; that is, the upper-level management software 903 sets the nighttime outdoor temperature trigger limit range and sends instructions to the fresh air system to deliver air into the building at a fixed wind speed, thereby reducing the energy consumption of indoor air conditioning.

[0089] The intelligent fresh air schedule is generated by the 903 upper-level management software using big data analysis of the accumulated fresh air system operation and artificial intelligence software learning capabilities to form an optimal operating schedule for the fresh air system that takes into account indoor temperature, humidity, air quality and meets the building's low energy consumption requirements.

[0090] In summary, this invention utilizes a big data platform, controller, fresh air unit, and environmental monitoring within the building to optimize indoor air quality and compensate for indoor temperature and humidity. The invention employs intelligent sensors to monitor the building's internal environment in real time, including PM2.5, PM10, CO, CO2, and formaldehyde, exceeding general building construction standards and meeting building requirements. The controller, based on real-time feedback data from various environmental monitoring systems, uses a PID control method to coordinate and control the electromechanical equipment within the fresh air system. Through multiple cyclic adjustments, it achieves airflow balance, air quality optimization, and temperature and humidity compensation control within the building, representing an innovative environmental control method for buildings. The upper-level management software (big data platform) serves as the central brain of the entire control system, capable of real-time display, statistical analysis, and processing of various equipment statuses, environmental parameters, airflow velocity, and other data. It also comprehensively designs intelligent operating modes for the control system, sets system control strategies, and continuously updates and optimizes system operation decisions during operation. This invention utilizes big data, artificial intelligence, intelligent sensors, and automatic control technologies, fully demonstrating its creativity and novelty.

[0091] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0092] Obviously, those skilled in the art can make various modifications and variations to the invention without departing from the spirit and scope of the invention. Therefore, if these modifications and variations fall within the scope of the claims of the invention and their equivalents, the invention is also intended to include these modifications and variations.

Claims

1. A method for optimizing and controlling the building environment, characterized in that, A building environment optimization control system is adopted, the control system comprising: The fresh air unit and duct are installed in the fresh air system of the building space area. The fresh air unit has a high-efficiency filter (10), an electrostatic dust removal device (11) and a variable frequency fan. The duct includes a fresh air duct, a supply air duct, a return air duct and an exhaust air duct. Several anemometers (500) and several actuators (600) are installed in the duct. Several intelligent environmental monitoring sensors and fan control cabinets (100) are installed in the interior space of the building. A controller (700) connected to the intelligent environmental monitoring sensor, actuator (600) and fan control cabinet (100); A switch (800) connected to the controller (700); A host management device (900) connected to the switch (800). The variable frequency fan includes a blower (102) and an exhaust fan (104). Several anemometers (500) are respectively installed on the fresh air duct, supply air duct, return air duct and exhaust air duct, namely fresh air anemometer (501), supply air anemometer (502), return air anemometer (503) and exhaust air anemometer (504), for monitoring the wind speed in the duct; the actuator (600) includes a hot and cold water valve (601), a humidification valve (602) and a branch pipe end electric regulating valve (603); several intelligent environmental monitoring sensors are evenly distributed in the building space area, including a particulate matter detector (200), a harmful gas detector (400) and a temperature and humidity detector (300). The controller (700) includes a main controller (701) and a sub-controller (702). The main controller (701) and the sub-controller (702) are interconnected. The sub-controller (702) is connected to the intelligent environmental monitoring sensor, the anemometer (500), the actuator (600), and the wind turbine electrical control cabinet (100). The switch (800) is connected to the controller (700) and the upper management device (900) via wired connections. The upper management device (900) includes a server (901) and a management workstation (902), and is equipped with professional upper management software (903). The building environment optimization control method using the aforementioned building environment optimization control system includes air volume balance control, air quality optimization control, relative humidity optimization control, and temperature compensation control. The airflow balance control includes the following steps: Step S1: Determine the maximum and minimum supply air velocity of the main air duct based on the wind speed requirements of the building's indoor fresh air system. Step S2: Compare the maximum and minimum airflow velocities in the main air supply pipe with the data fed back by the air supply anemometer (502) in the air supply pipe, and determine the maximum and minimum fan frequency limits of the blower (102); Step S3: Within a limited range, simultaneously turn on the supply fan (102) and the exhaust fan (104). By observing the feedback data from the fresh air anemometer (501), supply air anemometer (502), return air anemometer (503), and exhaust air anemometer (504), continuously adjust and test the operating frequency of the supply fan (102) and the exhaust fan (104) to balance the indoor air volume, and calculate the proportional coefficient of the operating frequency of the supply and exhaust fans to achieve air volume balance. Step S4: When the fresh air system is started, the supply fan (102) and exhaust fan (104) operate in conjunction with each other at a frequency according to this proportional coefficient. The air quality optimization and control includes the following steps: Step S10: Using the minimum airflow velocity of the air supply duct as the initial set value, and based on the real-time wind speed measured by the air supply anemometer (502) on the main air supply duct as the feedback quantity, the main controller (701) uses PID mode to control the frequency of the blower (102) and adjust the wind speed of the main air supply duct to the initial set value. Step S20: By gradually increasing the set value of the air supply velocity, find the air supply velocity gradient value associated with the standard air quality index in the service area of ​​the fresh air unit, and send the gradient value to the upper management software (903) for statistics and analysis. Through continuous testing and big data analysis, form an air supply velocity gradient table suitable for the service area. In step S30, the upper management software (903) determines the air supply velocity gradient value based on the weighted average of all real-time feedback data of PM2.5, PM10, and CO in the overall service area of ​​the fresh air unit. After receiving the air supply velocity set value issued by the upper management software (903), the main controller (701) uses the real-time wind speed measured by the air supply anemometer (502) on the air supply main pipe as feedback and adopts PID mode to control the frequency of the air supply fan (102) so that the air supply velocity is stabilized at the set value, thereby realizing the one-time adjustment of the ambient air quality. Step S40: Select set values ​​according to the individual indicators and requirements of PM2.5, PM10, CO, CO2, and formaldehyde in the building, and compare the real-time feedback data of PM2.5, PM10, CO, CO2, and formaldehyde in a single room. The sub-controller (702) selects the data with the highest excess ratio from the above feedback data. Based on the set value of the data and the real-time feedback, the PID mode is used to control the opening of the electric regulating valve (603) at the end of the branch pipe. By adjusting the air volume sent into a single room, the control system completes the secondary adjustment of the indoor air quality. In step S50, if, after a period of adjustment as described above, any one of the environmental data for PM2.5, PM10, CO, CO2, or formaldehyde in the overall service area of ​​the fresh air unit still exceeds the concentration limit, the main controller (701) will adjust the frequency of the blower (102) to the frequency of the maximum allowable airflow rate, keeping the air circulating continuously until the environmental data meets the requirements. Then, the control system will return to the PID tracking airflow rate gradient control mode. Finally, the optimized control of the air quality in the overall service area of ​​the fresh air unit is completed. The relative humidity optimization control includes the following steps: Step S100: Set the relative humidity standard range for the overall service area of ​​the fresh air unit according to national standards, and set the relative humidity gradient table for summer and winter in the building's indoor environment using the upper management software (903). Step S200: The relative humidity gradient value is determined based on the weighted average value of the humidity feedback data of the overall service area of ​​the fresh air system. After receiving the relative humidity set value issued by the upper management software (903), the main controller (701) uses the real-time humidity data of the temperature and humidity detector on the air supply duct as feedback quantity and adopts PID mode to control the opening of the humidification valve (602) to adjust the air humidity in the air supply duct, thereby completing the control system's adjustment of the relative humidity of the air in the air supply duct. In step S300, based on the real-time data feedback of the relative humidity of the fresh air system service unit area, the upper-level management software (903) determines the relative humidity gradient value of the area; after receiving the relative humidity setpoint from the upper-level management software (903), the sub-controller (702) uses PID mode to control the opening of the electric regulating valve (603) at the end of the branch pipe based on the real-time humidity feedback of the temperature and humidity detector in a single room, thereby adjusting the air volume supplied to a single room and completing the secondary adjustment of the relative humidity of the air in the supply branch pipe by the control system; the priority of the relative humidity control in a single room is lower than that of air quality control, and finally, the optimization control of the relative humidity of the overall service area of ​​the fresh air unit is completed; The temperature compensation control includes the following steps: Step S1000: Set the temperature standard range of the overall service area of ​​the fresh air unit according to the national standard, and set the temperature gradient table of the building's indoor summer and winter standards in the upper management software (903). Step S2000: Determine the temperature gradient value based on the weighted average of the temperature feedback data of the overall service area of ​​the fresh air system. After receiving the temperature set value issued by the upper management software (903), the main controller (701) uses PID mode to control the opening of the hot and cold water valve (601) to adjust the air temperature in the air supply pipe based on the temperature data feedback from the temperature and humidity detector on the air supply pipe, thereby completing the first compensation adjustment of the air temperature in the air supply pipe by the control system. In step S3000, based on the temperature data feedback set by the temperature control panel of a single room in the fresh air system, the sub-controller (702) uses PID mode to control the opening of the electric regulating valve (603) at the end of the branch pipe, adjusts the air volume supplied to the single room, and completes the secondary compensation adjustment of the ambient temperature by the control system. Since the fresh air system has a relatively small impact on the ambient temperature of the service unit area in the building, the priority of temperature compensation control of a single room is lower than that of relative humidity control. Finally, the optimization control of the temperature of the entire service area of ​​the fresh air unit is completed.

2. The building environment optimization and control method as described in claim 1, characterized in that, The fan electrical control cabinet (100) integrates the power supply and control circuits of the fan, and is used for the power supply and local control of the fan.

3. The building environment optimization and control method as described in claim 1, characterized in that, The management workstation (902) displays the status of all equipment in the fresh air system and the building's internal environmental data. At the same time, through the accumulation and intelligent analysis of fresh air system operation data, it sets the transitional season fresh air mode, the nighttime fresh air mode, and the intelligent fresh air schedule to promote energy conservation in the building and improve the physical comfort of the building environment. The aforementioned transitional season fresh air mode involves the upper-level management software setting a trigger limit range for outdoor temperature during the transitional season. This temperature range is the temperature that feels comfortable to the human body. When the outdoor temperature is within this limit range, a command is sent to the fresh air system to deliver air into the building at maximum wind speed. This utilizes natural resources to compensate for indoor temperature to the maximum extent, reducing the energy consumption of indoor air conditioning and meeting the building energy conservation requirements during the transitional season. The aforementioned nighttime fresh air mode involves the upper-level management software setting a nighttime outdoor temperature trigger limit range and issuing instructions to the fresh air system to deliver air into the building at a fixed wind speed, thereby reducing the energy consumption of indoor air conditioning and meeting the nighttime building energy-saving requirements. The aforementioned intelligent fresh air schedule is generated by the upper-level management software through intelligent analysis of accumulated big data on the operation of the fresh air system and by utilizing the learning capabilities of artificial intelligence software to form an optimal operating schedule for the fresh air system that takes into account indoor environmental temperature, humidity, air quality, and meets the building's low energy consumption requirements.

Images