Intelligent control method and system for building HVAC system

Abstract

The invention discloses an intelligent control method and system for a building HVAC system, and the system comprises an information monitoring unit, a core processing unit, a scheme design unit, a real-time regulation and control unit and an early warning management unit. Therefore, the building environment quality of the space area is evaluated in a targeted mode, HVAC linkage control over the local regulation and control area range is carried out in combination with the geographic coordinates of the space area, an air regulation and control management scheme and an equipment management signal are output, real-time regulation and control over the building environment are carried out, and air interaction from a key monitoring area as the center to an associated area is achieved. Through local linkage control, the HVAC regulation and control precision is improved, the energy consumption of air conditioning equipment is reduced, the continuous stability of the building environment quality is guaranteed by predicting and evaluating the building environment quality of a space area, and therefore the comfort level of the working and living states of users in a building is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of building environment air control, and in particular to an intelligent control method and system for a building HVAC system. Background Art

[0002] ‌Building HVAC system refers to the related disciplines, technologies and industries of heating, ventilation and air conditioning, including control systems of temperature, humidity and air circulation. HVAC system aims to provide a comfortable working and living environment and is widely used in building design and manufacturing. With the development of Internet of Things technology, HVAC system is gradually being integrated into building management platform. Since modern building designs are mainly high-rise buildings, the degree of external environmental interference to the space area near the building's outer curtain wall and the space area near the center of the building is different, including differences in temperature, humidity, particulate matter and harmful gas accumulation. For example, the space area near the building's outer curtain wall is more affected by temperature, humidity and particulate matter; the space area near the center of the building needs to rely on a narrow patio for gas exchange, which will lead to low gas diffusion efficiency and cause harmful gas accumulation; However, when the building HVAC system adopts a unified management method for air conditioning, there will be defects in inaccurate control, which makes it difficult to meet the comfort level of people in the building; and when the building HVAC system controls the building space in an independent unit, it will lead to high energy consumption of the equipment and increase the operation and management costs; therefore, the existing building HVAC technology has the defect of being difficult to balance the air control accuracy and the energy consumption of the control equipment; In view of the above technical defects, a solution is now proposed. Summary of the invention

[0003] The purpose of the present invention is to solve the defect of the existing technology that it is difficult to balance the air control accuracy and the energy consumption of the control equipment. The present invention controls the building environment in real time through HVAC linkage control in the local control area, and realizes air interaction from the key monitoring area to the related area. The local linkage control improves the HVAC control accuracy and reduces the energy consumption of the air conditioning equipment. Then, the building environment quality of the spatial area is predicted and evaluated to ensure the continuous stability of the building environment quality, thereby improving the comfort of the working and living conditions of the people using the building.

[0004] In order to achieve the above object, the present invention adopts the following technical solutions: An intelligent control method for a building HVAC system comprises the following steps: Step 1: Construct an HVAC monitoring model to collect building environment information: Monitor the building environment through the HVAC monitoring model, construct a three-dimensional building model, divide any building BR into N0 spatial areas, mark any spatial area as a, and collect the building environment information of spatial area a; Step 2: Analyze building environment information to evaluate building environment quality: Preprocess the building environment information of spatial area a and set up a parameter risk assessment model to construct a building risk parameter vector and integrate and evaluate the building environment quality of spatial area a; Step 3: Output the air control management plan and equipment control signal: Analyze and mark the key monitoring areas from N0 spatial areas through the building environment quality of spatial area a and combine the regional geographic coordinates, and obtain the associated areas of the key monitoring areas. Output the corresponding equipment control signal through detailed analysis of the regional building environment quality, and integrate and generate the air control management plan; Step 4: Carry out targeted real-time control of spatial areas: by receiving air control management solutions and equipment control signals, local control area HVAC linkage control is carried out on key monitoring areas and related areas to achieve real-time environmental control of buildings; Step 5: Conduct early warning management for spatial areas: construct a historical parameter matrix and set up a parameter vector prediction model to predict and evaluate the building environment quality of spatial area a, generate corresponding early warning prompt signals, and thus provide early warning for the building HVAC system.

[0005] Furthermore, the specific process of constructing the HVAC monitoring model to monitor the building environment is as follows: Mark any building as BR, and an air conditioning unit is installed in the building BR. The air conditioning unit includes N0 air conditioning equipment. Then construct a three-dimensional building model, divide the building into N0 space areas, mark any space area as a, mark the air conditioning equipment in space area a as Qa, and collect the building environment information and regional geographic coordinates of space area a; Building environment information includes temperature, humidity, wind speed, particulate matter content and harmful gas concentration; set the information collection period Tc to collect building environment information regularly; The temperature, humidity, wind speed, and particulate matter content of space region a are marked as Wa, Sa, Fa, and HKa, respectively; It is preset to collect n0 kinds of harmful gases, mark any harmful gas as φ, and mark the concentration of the harmful gas φ as Cφa; by combining the concentrations Cφa of n0 kinds of harmful gases, the harmful gas risk value FCa of the space area a is comprehensively obtained.

[0006] Furthermore, the specific process of setting the parameter risk assessment model is as follows: Input parameter i and its standard interval [Qa, Qb], and obtain and output the risk value fi of parameter i by combining parameter i and its standard interval [Qa, Qb]: ; in, It refers to the correction coefficient of parameter i, which is a constant value that keeps the risk value fi always greater than 0; By setting the standard intervals of temperature Wa, humidity Sa, and wind speed Fa respectively and substituting them into the parameter risk assessment model for preprocessing, the risk values ​​of temperature Wa, humidity Sa, and wind speed Fa are obtained in turn and marked as Wfa, Sfa, and Ffa respectively; The temperature risk value Wfa, humidity risk value Sfa, wind speed risk value Ffa, particulate matter content HKa and harmful gas risk value FCa are integrated and marked as a building risk parameter vector.

[0007] Furthermore, the specific process of evaluating the building environment quality of space area a is as follows: The building environment quality assessment coefficient HJa of space area a is obtained by combining the temperature risk value Wfa, humidity risk value Sfa, wind speed risk value Ffa, particulate matter content HKa and harmful gas risk value FCa; The building environment quality assessment coefficient HJa is calculated according to the information collection period Tc. By measuring the building environment quality assessment coefficients of N0 spatial areas and sorting them in descending order, the top n1 spatial areas are extracted and marked as key monitoring areas.

[0008] Furthermore, the specific process of generating the air control management plan is as follows: The regional geographic coordinates are calibrated through the three-dimensional model of the building, and any key monitoring area is marked as b, and the regional geographic coordinates of the key monitoring area b are marked as (Xb, Yb, Zb); Taking the key monitoring area b as the reference coordinate, measure the distance between other spatial areas and the key monitoring area b, mark any other spatial area as c, and mark the regional geographic coordinates of spatial area c as (Xc, Yc, Zc), then the distance between spatial area c and key monitoring area b is ; Set the distance between spatial area c and key monitoring area b The threshold G0, when the distance When it is lower than the threshold G0, the spatial area c is extracted as the associated area of ​​the key monitoring area b, and the number of associated areas is marked as m0. The m0 associated areas are integrated and marked as a linkage area group, and the linkage area group centered on the key monitoring area and connected to it is integrated and marked as a local control area. Retrieve the building environment quality assessment coefficients of m0 associated areas, mark the associated areas in descending order of the building environment quality assessment coefficients, and set the corresponding control range, so as to generate a local air control management plan and corresponding equipment control signals, realize the HVAC linkage control of the local control area, and thus comprehensively carry out real-time environmental control of the building BR.

[0009] Furthermore, the specific process of the parameter vector prediction model is: Input vector L to the parameter vector prediction model. Vector L includes m1 sub-vectors. Vector L is marked as: ; By averaging the m1 component vectors, we can obtain the mean coefficient σ1 of the vector L; then by calculating the standard deviation of the m1 component vectors, we can obtain the fluctuation coefficient σ2 of the vector L; by averaging the differences between all adjacent component vectors, we can obtain the increase rate coefficient σ3 of the vector L; The prediction coefficient of vector L is obtained by combining the mean coefficient σ1, fluctuation coefficient σ2 and increase rate coefficient σ3 of vector L ; The parameter vector predicts the prediction coefficients of the model output vector L .

[0010] Furthermore, the specific process of evaluating the predicted state of the building environment in the spatial area a and generating the early warning signal is as follows: The parameter risk assessment model is used to calculate the building risk parameter vector corresponding to m1 information collection cycles Tc, and the historical parameter matrix V is constructed to predict and evaluate the building environment quality in the spatial area a, and the building environment quality prediction index ZLa is obtained: ; Among them, any row vector of the historical parameter matrix V includes the five parameter values ​​of the building risk parameter vector, namely, the temperature risk value Wfa, the humidity risk value Sfa, the wind speed risk value Ffa, the particulate matter content HKa and the harmful gas risk value FCa; any column vector of the historical parameter matrix V represents the building risk parameter vector corresponding to m1 information collection cycles Tc; Set the parameter vector prediction model, integrate the column vector and substitute it into the parameter vector prediction model to obtain the prediction coefficient of the column vector, where: , , , and They are the prediction coefficients of temperature risk value Wfa, humidity risk value Sfa, wind speed risk value Ffa, particulate matter content HKa, and harmful gas risk value FCa; The environmental quality prediction index ZLa is obtained by combining the prediction coefficients of temperature risk value Wfa, humidity risk value Sfa, wind speed risk value Ffa, particulate matter content HKa and harmful gas risk value FCa; Set the evaluation interval of the environmental quality prediction index ZLa, evaluate the predicted state of the building environment in spatial area a through interval comparison, and generate corresponding early warning signals.

[0011] An intelligent control system for a building HVAC system, comprising an information monitoring unit, a core processing unit, a scheme design unit, a real-time control unit and an early warning management unit, wherein the information monitoring unit, the core processing unit, the scheme design unit, the real-time control unit and the early warning management unit are connected in communication, and the system applies the above-mentioned intelligent control method for a building HVAC system; The information monitoring unit is used to construct an HVAC monitoring model to collect building environment information; The core processing unit is used to analyze the building environment information and evaluate the building environment quality; The scheme design unit is used to output air control management schemes and equipment control signals; The real-time control unit is used to receive air control management solutions and equipment control signals, so as to carry out targeted real-time control of the space area; The early warning management unit is used to predict and evaluate the building environment quality of the space area a and generate corresponding early warning prompt signals, so as to carry out early warning management of the space area.

[0012] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: The present invention collects environmental information of the spatial area of ​​the building by constructing an HVAC monitoring model, thereby specifically evaluating the building environment quality of the spatial area, and combines the geographical coordinates of the spatial area to perform HVAC linkage control in the local control area, output air control management plans and equipment management signals to perform real-time control of the building environment, and realize air interaction from the key monitoring area to the associated area. The local linkage control improves the accuracy of HVAC control and reduces the energy consumption of air conditioning equipment. The building environment quality of the spatial area is then predicted and evaluated to ensure the continuous stability of the building environment quality, thereby improving the comfort of the working and living conditions of the people using the building. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 A schematic diagram of the process steps of the present invention is shown; Figure 2 The module connection diagram of the present invention is shown. DETAILED DESCRIPTION

[0014] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0015] Embodiment 1: like Figure 1-Figure 2 As shown, an intelligent control method for a building HVAC system includes the following steps: S1, constructing an HVAC monitoring model to collect building environment information: monitor the building environment through the HVAC monitoring model, construct a three-dimensional building model, divide any building BR into N0 spatial areas, mark any spatial area as a, and collect the building environment information of spatial area a. The specific process is as follows: Mark any building as BR, and an air conditioning unit is installed in the building BR. The air conditioning unit includes N0 air conditioning equipment. Then construct a three-dimensional building model, divide the building into N0 space areas, mark any space area as a, mark the air conditioning equipment in space area a as Qa, and collect the building environment information and regional geographic coordinates of space area a; The air conditioning equipment in space area a is marked as Qa, where the air conditioning equipment includes a combination structure such as an air conditioner and a ventilation fan, so that a single or combined device can control wind speed, temperature, and humidity; Setting an information collection period Tc to collect building environment information regularly; building environment information includes temperature, humidity, wind speed, particulate matter content and harmful gas concentration; temperature, humidity and wind speed are collected by monitoring through sensors; for example, temperature sensors, humidity sensors and wind speed sensors; Measure particulate matter content and harmful gas concentrations through optical technology; Among them, the concentration of harmful gases in space area a is collected through infrared spectroscopy technology; infrared spectroscopy technology is based on the principle of interaction between infrared radiation and matter. Different gas molecules absorb infrared radiation of specific wavelengths, and the gas composition is judged based on this, so as to obtain the concentration of harmful gases; The laser scattering image of the space area a is obtained by the laser particle size analyzer based on the laser scattering technology, so as to collect the particle content of the space area a. The laser scattering technology is to radiate the laser beam to the particles, absorb part of the energy, and emit scattered light in all directions, and then use the difference in the scattered light intensity to analyze the gas in the space area, and take and collect the laser scattering image of the space area a; Evaluate the quality of the built environment in spatial area a through built environment information; The temperature, humidity, wind speed, and particulate matter content of space region a are marked as Wa, Sa, Fa, and HKa, respectively; It is preset to collect n0 kinds of harmful gases, mark any harmful gas as φ, and mark the concentration of harmful gas φ as Cφa; Harmful gases include C0, CO2, H2S, CH4, NO, NO2, etc. Carbon monoxide C0 is a colorless, odorless, non-irritating gas. It can easily combine with hemoglobin that transports oxygen in the human body, causing oxygen to lose the opportunity to combine with hemoglobin, thereby affecting the body's ability to transport and utilize oxygen, and may cause human tissue necrosis due to lack of oxygen; Carbon dioxide CO2 can cause suffocation at high concentrations, especially in a closed environment; Hydrogen sulfide H2S is a toxic gas that often exists in confined spaces, such as basements. Hydrogen sulfide poisoning can cause suffocation and poisoning accidents, especially in poorly ventilated environments. Methane CH4 may mix with air to form explosive gases in some cases, especially in a closed environment; Nitrogen oxides include nitric oxide NO, nitrogen dioxide NO2, etc. These gases are irritating to the respiratory tract, and long-term inhalation may cause pulmonary edema and other respiratory diseases; By combining n0 kinds of harmful gas concentrations Cφa, the harmful gas risk value FCa of space area a is comprehensively obtained: , assess the risk level of harmful gases in space area a; Wherein, e is the conversion coefficient of the harmful gas concentration Cφa and e is greater than 0; the conversion coefficient e is preset and obtained after a large amount of data calculation. When the concentration Cφa of the harmful gas φ is higher, the harmful gas risk value FCa is higher, and the degree of harmful gas risk in the assessment space area a is higher; S2, analyzing building environment information to evaluate building environment quality: by preprocessing the building environment information of spatial area a and setting a parameter risk assessment model, a building risk parameter vector is constructed, and the building environment quality of spatial area a is integrated and evaluated; The specific process of setting up the parameter risk assessment model is: Input parameter i and its standard interval [Qa, Qb]; By combining parameter i and its standard interval [Qa, Qb], the risk value fi of parameter i is obtained and output: ,in, It refers to the correction coefficient of parameter i. The correction coefficient is a constant value that keeps the risk value fi always greater than 0. When parameter i is in the standard interval [Qa, Qb], it is judged that parameter i is normal and the risk value fi of parameter i is less than ; When parameter i is not in the standard interval [Qa, Qb], it is judged that parameter i is abnormal, and the risk value fi of parameter i is greater than ; By setting the standard intervals of temperature Wa, humidity Sa, and wind speed Fa respectively and substituting them into the parameter risk assessment model for preprocessing, the risk values ​​of temperature Wa, humidity Sa, and wind speed Fa are obtained in turn and marked as Wfa, Sfa, and Ffa respectively; When the temperature risk value Wfa, humidity risk value Sfa, and wind speed risk value Ffa are higher, it means that the abnormal degree of temperature Wa, humidity Sa, and wind speed Fa deviating from the corresponding standard interval is higher, indicating that the risk degree of the corresponding parameters is higher; The temperature risk value Wfa, humidity risk value Sfa, wind speed risk value Ffa, particulate matter content HKa and harmful gas risk value FCa are integrated and marked as a building risk parameter vector; The specific process of evaluating the building environment quality of spatial area a is: By combining the temperature risk value Wfa, humidity risk value Sfa, wind speed risk value Ffa, particulate matter content HKa and harmful gas risk value FCa, the building environment quality assessment coefficient HJa of space area a is obtained: ; Among them, ε1, ε2, ε3, ε4 and ε5 are the weight factor coefficients of the temperature risk value Wfa, the humidity risk value Sfa, the wind speed risk value Ffa, the particulate matter content HKa and the harmful gas risk value FCa, respectively, and ε1, ε2, ε3, ε4 and ε5 are all greater than 0. The weight factor coefficients are preset and obtained after calculating a large amount of experimental data, and ; When the temperature risk value Wfa, humidity risk value Sfa, wind speed risk value Ffa, particulate matter content HKa and harmful gas risk value FCa are higher, the building environment quality assessment coefficient HJa is lower, and the building environment quality of the assessment space area a is worse; The building environment quality assessment coefficient HJa is calculated in real time according to the information collection period Tc. By measuring the building environment quality assessment coefficients of N0 spatial areas and sorting them in descending order, the top n1 spatial areas are extracted and marked as key monitoring areas. S3, output air control management plan and equipment control signal: through the building environment quality of spatial area a and combined with the regional geographic coordinates, analyze and mark the key monitoring areas from N0 spatial areas, and obtain the associated areas of the key monitoring areas, output the corresponding equipment control signal by refining the regional building environment quality, and integrate and generate the air control management plan; S4, targeted real-time control of spatial areas: by receiving air control management solutions and equipment control signals, local control area HVAC linkage control is performed on key monitoring areas and related areas to achieve real-time environmental control of buildings. The specific process is as follows: The regional geographic coordinates are calibrated through the three-dimensional model of the building, and any key monitoring area is marked as b, and the regional geographic coordinates of the key monitoring area b are marked as (Xb, Yb, Zb); Taking the key monitoring area b as the reference coordinate, measure the distance between other spatial areas and the key monitoring area b, mark any other spatial area as c, and mark the regional geographic coordinates of spatial area c as (Xc, Yc, Zc), then the distance between spatial area c and key monitoring area b is : ; Set the distance between spatial area c and key monitoring area b The threshold G0, when the distance When it is lower than the threshold G0, the spatial area c is extracted as the associated area of ​​the key monitoring area b, and the number of associated areas is marked as m0. The m0 associated areas are integrated and marked as a linkage area group, and the linkage area group centered on the key monitoring area and connected to it is integrated and marked as a local control area. Retrieve the building environment quality assessment coefficients of m0 associated areas, and sort the associated areas in descending order to mark them, so as to generate a local air control management plan. The local air control management plan refers to setting the control range from small to large for the air conditioning adjustment equipment in the m0 associated areas by combining the air conditioning adjustment equipment in the m0 associated areas and sorting them in descending order according to the building environment quality assessment coefficients. The specific value of the control range is set with reference to the specific conditions of the environment and the equipment. For example, the wind speed of the ventilation fan is divided into N2 gears, and the key monitoring area b applies the highest wind speed gear. The lower the building environment quality assessment coefficient of the m0 associated areas, the higher the wind speed gear. The corresponding setting is made in combination with the actual situation. The control range of air conditioning equipment refers to the fan speed of the vent, the temperature and humidity control setting value, etc. The corresponding equipment control signal is generated by feedback analysis of the building environment information of the space area c. The specific setting process is as follows: By setting the thresholds of temperature risk value Wfa, humidity risk value Sfa, wind speed risk value Ffa, particulate matter content HKa and harmful gas risk value FCa respectively, and making detailed comparisons; The thresholds of the temperature risk value Wfa, humidity risk value Sfa, wind speed risk value Ffa, particulate matter content HKa and harmful gas risk value FCa are marked as temperature threshold Gw, humidity threshold Gs, wind speed threshold Gf, particulate matter threshold Gh and harmful gas threshold Gc respectively; When the temperature risk value Wfa is higher than the temperature threshold Gw, a control signal No. 1 is generated; When the humidity risk value Sfa is higher than the humidity threshold Gs, a second control signal is generated; When the wind speed risk value Ffa is higher than the wind speed threshold Gf, a No. 3 control signal is generated; When the particle content HKa is higher than the particle threshold Gh, a fourth control signal is generated; When the harmful gas risk value FCa is higher than the harmful gas threshold Gc, a No. 5 control signal is generated; The first control signal and the second control signal are integrated and marked as an air conditioning equipment control signal, and the equipment parameters of the air conditioner are controlled by the air conditioning equipment control signal; wherein the temperature parameter is controlled by the first control signal, and the humidity parameter is controlled by the second control signal; The third control signal, the fourth control signal and the fifth control signal are integrated and marked as a fan device control signal, and the device parameters of the ventilation fan are controlled by the fan device control signal; For example, when a No. 5 control signal is received, it means that the risk of harmful gases in the key monitoring area b and its associated areas exceeds the threshold, and the ventilation fan needs to be activated for ventilation control; Taking the key monitoring area b as the starting point, and taking the building quality of m0 associated areas in ascending order as the path, the ventilation fan is enabled and the ventilation ducts of the path are connected, and the air conditioning adjustment equipment of the m0 associated areas is set with the control range from large to small, so as to perform air interaction in the key monitoring area b and the m0 associated areas, so as to realize the air replacement from the relatively closed space of the building to the window area of ​​the building's exterior wall, ensure the ventilation efficiency of the indoor windowless area, and different control ranges are aimed at different degrees of regional environmental quality, so as to reduce the energy consumption of air conditioning equipment and realize targeted wind control; The temperature and humidity are similar to the above operations. After the air temperature is cooled or dried by air conditioning equipment, the air interaction between the key monitoring area and its linkage area group is realized through the ventilation duct, so that the air is transmitted to the local control area with the key monitoring area as the center point and the linkage area group as the connection point, and the HVAC linkage control of the local control area is realized; The local control area generally includes the space area near the outer curtain wall of the building and the space area near the inner center of the building. By making air interaction between the space area near the outer curtain wall of the building and the space area near the inner center, the temperature and humidity transfer from the outside to the inside and the diffusion of harmful gases from the inside to the outside are realized. By transferring the resource energy of different geographical coordinate spaces under the natural state, the actual operation intensity of the air conditioning equipment is reduced to reduce the energy consumption of the equipment. Obtain the corresponding local control area and its air control local management plan through n1 key monitoring areas, and integrate all the air control local management plans as the air control management plan, so as to comprehensively carry out real-time environmental control of the building BR; S5, early warning management of spatial areas: construct a historical parameter matrix and set a parameter vector prediction model to predict and evaluate the building environment quality of spatial area a, generate corresponding early warning prompt signals, and thus provide early warning for the building HVAC system The parameter risk assessment model is used to calculate the building risk parameter vector corresponding to m1 information collection cycles Tc, and the historical parameter matrix V is constructed to predict and evaluate the building environment quality in the spatial area a, and the building environment quality prediction index ZLa is obtained: ; Among them, any row vector of the historical parameter matrix V includes the five parameter values ​​of the building risk parameter vector, namely, the temperature risk value Wfa, the humidity risk value Sfa, the wind speed risk value Ffa, the particulate matter content HKa and the harmful gas risk value FCa; any column vector of the historical parameter matrix V represents the building risk parameter vector corresponding to m1 information collection cycles Tc; for example It refers to the temperature risk value Wfa corresponding to the first information collection cycle Tc; It refers to the humidity risk value Sfa corresponding to the first information collection period Tc; It refers to the temperature risk value Wfa corresponding to the second information collection period Tc; The specific process of the parameter vector prediction model is: Input vector L to the parameter vector prediction model. Vector L includes m1 sub-vectors. Vector L is marked as: ; By averaging the m1 component vectors, we can obtain the mean coefficient σ1 of the vector L; then by calculating the standard deviation of the m1 component vectors, we can obtain the fluctuation coefficient σ2 of the vector L; by averaging the differences between all adjacent component vectors, we can obtain the increase rate coefficient σ3 of the vector L; but, ; ; ; The prediction coefficient of vector L is obtained by combining the mean coefficient σ1, fluctuation coefficient σ2 and increase rate coefficient σ3 of vector L : ; Where ω is the logarithmic base and is preset to be greater than 1; when the mean coefficient σ1, fluctuation coefficient σ2 and increase rate coefficient σ3 of vector L are higher, the prediction coefficient of vector L is The higher it is, the higher the overall level of vector L is, the greater the volatility is, and the more obvious the growth trend is, indicating that the risk level of vector L is higher; The parameter vector predicts the prediction coefficients of the model output vector L ; Set up a parameter vector prediction model, integrate the column vector and substitute it into the parameter vector prediction model to obtain the prediction coefficient of the column vector, and combine the prediction coefficients of the temperature risk value Wfa, humidity risk value Sfa, wind speed risk value Ffa, particulate matter content HKa and harmful gas risk value FCa to obtain the environmental quality prediction index ZLa; The five column vectors of the historical parameter matrix V are sequentially input into the parameter vector prediction model, thereby outputting the corresponding prediction coefficients in sequence and marking them as temperature prediction coefficient Rw, humidity prediction coefficient Rs, wind speed prediction coefficient Rf, particle prediction coefficient Rh and harmful gas prediction coefficient Rc respectively; Then, by combining the temperature prediction coefficient Rw, humidity prediction coefficient Rs, wind speed prediction coefficient Rf, particle prediction coefficient Rh and harmful gas prediction coefficient Rc, the environmental quality prediction index ZLa is obtained: ; Among them, η1, η2, η3, η4 and η5 are weight factor coefficients of temperature prediction coefficient Rw, humidity prediction coefficient Rs, wind speed prediction coefficient Rf, particle prediction coefficient Rh and harmful gas prediction coefficient Rc, and η1, η2, η3, η4 and η5 are all preset to be greater than 0; the weight coefficients are preset and obtained after a large amount of experimental data is measured, and ; When the temperature prediction coefficient Rw, humidity prediction coefficient Rs, wind speed prediction coefficient Rf, particle prediction coefficient Rh and harmful gas prediction coefficient Rc are higher, the environmental quality prediction index ZL is lower, and the predicted state of the building environment quality of the evaluation space area a is worse; Set the evaluation interval of the environmental quality prediction index ZLa, evaluate the predicted state of the building environment in the spatial area a through interval comparison, and generate corresponding early warning signals; There are U evaluation intervals for the preset environmental quality prediction index ZLa. Any evaluation interval is marked as Qu. When the environmental quality prediction index ZLa is in the evaluation interval Qu, a u-level early warning prompt signal is generated, and corresponding early warning prompts are made, so as to give corresponding reminders to the management personnel of the background center and take corresponding management plans to ensure the continuous stability of the building environment quality.

[0016] An intelligent control system for a building HVAC system, comprising an information monitoring unit, a core processing unit, a scheme design unit, a real-time control unit and an early warning management unit, wherein the information monitoring unit, the core processing unit, the scheme design unit, the real-time control unit and the early warning management unit are connected in communication, and the system applies the above-mentioned intelligent control method for a building HVAC system; The information monitoring unit is used to construct an HVAC monitoring model to collect building environment information; The core processing unit is used to analyze the building environment information and evaluate the building environment quality; The scheme design unit is used to output air control management schemes and equipment control signals; The real-time control unit is used to receive air control management solutions and equipment control signals, so as to carry out targeted real-time control of the space area; The early warning management unit is used to predict and evaluate the building environment quality of the space area a and generate corresponding early warning prompt signals, so as to carry out early warning management of the space area.

[0017] In summary, the present invention collects environmental information of the spatial area of ​​the building by constructing an HVAC monitoring model, thereby evaluating the building environment quality of the spatial area in a targeted manner, and performs HVAC linkage control in the local control area in combination with the geographical coordinates of the spatial area, and outputs corresponding air control management plans and equipment management signals to perform real-time control of the building environment, and realize air interaction from the key monitoring area to the associated area. The local linkage control improves the accuracy of HVAC control and reduces the energy consumption of air conditioning equipment. The building environment quality of the spatial area is predicted and evaluated to ensure the continuous stability of the building environment quality, thereby improving the comfort of the working and living conditions of the people using the building.

[0018] The size of the interval and threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by technical personnel in this field for each group of sample data; as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0019] The above formulas are all dimensionless and numerical calculations. The formula is a formula obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formula are set by technicians in this field according to actual conditions. The above description is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can make equivalent replacements or changes according to the technical scheme and inventive concept of the present invention within the technical scope disclosed by the present invention, which should be covered by the protection scope of the present invention.

Claims

1. An intelligent control method for a building HVAC system, characterized in that: The following steps are involved: Step 1: Construct an HVAC monitoring model to collect building environment information: Monitor the building environment through the HVAC monitoring model, construct a three-dimensional building model, divide any building BR into N0 spatial areas, mark any spatial area as a, and collect the building environment information of spatial area a; Step 2: Analyze building environment information to evaluate building environment quality: Preprocess the building environment information of spatial area a and set up a parameter risk assessment model to construct a building risk parameter vector and integrate and evaluate the building environment quality of spatial area a; Step 3: Output the air control management plan and equipment control signal: Analyze and mark the key monitoring areas from N0 spatial areas through the building environment quality of spatial area a and combine the regional geographic coordinates, and obtain the associated areas of the key monitoring areas. Output the corresponding equipment control signal through detailed analysis of the regional building environment quality, and integrate and generate the air control management plan; Step 4: Carry out targeted real-time control of spatial areas: by receiving air control management solutions and equipment control signals, local control area HVAC linkage control is carried out on key monitoring areas and related areas to achieve real-time environmental control of buildings; Step 5: Conduct early warning management for spatial areas: construct a historical parameter matrix and set up a parameter vector prediction model to predict and evaluate the building environment quality of spatial area a, generate corresponding early warning prompt signals, and thus provide early warning for the building HVAC system.

2. The intelligent control method of a building HVAC system according to claim 1, characterized in that: The specific process of building an HVAC monitoring model to monitor the building environment is as follows: Mark any building as BR, and an air conditioning unit is installed in the building BR. The air conditioning unit includes N0 air conditioning equipment. Then construct a three-dimensional building model, divide the building into N0 space areas, mark any space area as a, mark the air conditioning equipment in space area a as Qa, and collect the building environment information and regional geographic coordinates of space area a; Building environment information includes temperature, humidity, wind speed, particulate matter content and harmful gas concentration; set the information collection period Tc to collect building environment information regularly; The temperature, humidity, wind speed, and particulate matter content of space region a are marked as Wa, Sa, Fa, and HKa, respectively; It is preset to collect n0 kinds of harmful gases, mark any harmful gas as φ, and mark the concentration of the harmful gas φ as Cφa; by combining the concentrations Cφa of n0 kinds of harmful gases, the harmful gas risk value FCa of the space area a is comprehensively obtained.

3. The intelligent control method of a building HVAC system according to claim 2, characterized in that: The specific process of setting up the parameter risk assessment model is: Input parameter i and its standard interval [Qa, Qb], and obtain and output the risk value fi of parameter i by combining parameter i and its standard interval [Qa, Qb]: ; in, It refers to the correction coefficient of parameter i, which is a constant value that keeps the risk value fi always greater than 0; By setting the standard intervals of temperature Wa, humidity Sa, and wind speed Fa respectively and substituting them into the parameter risk assessment model for preprocessing, the risk values ​​of temperature Wa, humidity Sa, and wind speed Fa are obtained in turn and marked as Wfa, Sfa, and Ffa respectively; The temperature risk value Wfa, humidity risk value Sfa, wind speed risk value Ffa, particulate matter content HKa and harmful gas risk value FCa are integrated and marked as a building risk parameter vector.

4. The intelligent control method of a building HVAC system according to claim 3, characterized in that: The specific process of evaluating the building environment quality of spatial area a is: The building environment quality assessment coefficient HJa of space area a is obtained by combining the temperature risk value Wfa, humidity risk value Sfa, wind speed risk value Ffa, particulate matter content HKa and harmful gas risk value FCa; The building environment quality assessment coefficient HJa is calculated according to the information collection period Tc. By measuring the building environment quality assessment coefficients of N0 spatial areas and sorting them in descending order, the top n1 spatial areas are extracted and marked as key monitoring areas.

5. The intelligent control method of a building HVAC system according to claim 4, characterized in that: The specific process of generating an air control management plan is as follows: The regional geographic coordinates are calibrated through the three-dimensional model of the building, and any key monitoring area is marked as b, and the regional geographic coordinates of the key monitoring area b are marked as (Xb, Yb, Zb); Taking the key monitoring area b as the reference coordinate, measure the distance between other spatial areas and the key monitoring area b, mark any other spatial area as c, and mark the regional geographic coordinates of spatial area c as (Xc, Yc, Zc), then the distance between spatial area c and key monitoring area b is ; Set the distance between spatial area c and key monitoring area b The threshold G0, when the distance When it is lower than the threshold G0, the spatial area c is extracted as the associated area of ​​the key monitoring area b, and the number of associated areas is marked as m0. The m0 associated areas are integrated and marked as a linkage area group, and the linkage area group centered on the key monitoring area and connected to it is integrated and marked as a local control area. Retrieve the building environment quality assessment coefficients of m0 associated areas, mark the associated areas in descending order of the building environment quality assessment coefficients, and set the corresponding control range, so as to generate a local air control management plan and corresponding equipment control signals, realize the HVAC linkage control of the local control area, and thus comprehensively carry out real-time environmental control of the building BR.

6. The intelligent control method of a building HVAC system according to claim 5, characterized in that: The specific process of the parameter vector prediction model is: Input vector L to the parameter vector prediction model. Vector L includes m1 sub-vectors. Vector L is marked as: ； By averaging the m1 component vectors, we can obtain the mean coefficient σ1 of the vector L; then by calculating the standard deviation of the m1 component vectors, we can obtain the fluctuation coefficient σ2 of the vector L; by averaging the differences between all adjacent component vectors, we can obtain the increase rate coefficient σ3 of the vector L; The prediction coefficient of vector L is obtained by combining the mean coefficient σ1, fluctuation coefficient σ2 and increase rate coefficient σ3 of vector L ; The parameter vector predicts the prediction coefficients of the model output vector L .

7. The intelligent control method of a building HVAC system according to claim 6, characterized in that: The specific process of evaluating the predicted state of the building environment in space area a and generating early warning signals is as follows: The parameter risk assessment model is used to calculate the building risk parameter vector corresponding to m1 information collection cycles Tc, and the historical parameter matrix V is constructed to predict and evaluate the building environment quality in the spatial area a, and the building environment quality prediction index ZLa is obtained: ； Among them, any row vector of the historical parameter matrix V includes the five parameter values ​​of the building risk parameter vector, namely, the temperature risk value Wfa, the humidity risk value Sfa, the wind speed risk value Ffa, the particulate matter content HKa and the harmful gas risk value FCa; any column vector of the historical parameter matrix V represents the building risk parameter vector corresponding to m1 information collection cycles Tc; Set the parameter vector prediction model, integrate the column vector and substitute it into the parameter vector prediction model to obtain the prediction coefficient of the column vector, where: , , , and They are the prediction coefficients of temperature risk value Wfa, humidity risk value Sfa, wind speed risk value Ffa, particulate matter content HKa, and harmful gas risk value FCa; The environmental quality prediction index ZLa is obtained by combining the prediction coefficients of temperature risk value Wfa, humidity risk value Sfa, wind speed risk value Ffa, particulate matter content HKa and harmful gas risk value FCa; Set the evaluation interval of the environmental quality prediction index ZLa, evaluate the predicted state of the building environment in spatial area a through interval comparison, and generate corresponding early warning signals.

8. An intelligent control system for a building HVAC system, characterized in that: The system comprises an information monitoring unit, a core processing unit, a scheme design unit, a real-time control unit and an early warning management unit, wherein the information monitoring unit, the core processing unit, the scheme design unit, the real-time control unit and the early warning management unit are communicatively connected with each other, and the system applies an intelligent control method for a building HVAC system as described in any one of claims 1 to 7 above; The information monitoring unit is used to construct an HVAC monitoring model to collect building environment information; The core processing unit is used to analyze the building environment information and evaluate the building environment quality; The scheme design unit is used to output air control management schemes and equipment control signals; The real-time control unit is used to receive air control management solutions and equipment control signals, so as to carry out targeted real-time control of the space area; The early warning management unit is used to predict and evaluate the building environment quality of the space area a and generate corresponding early warning prompt signals, so as to carry out early warning management of the space area.

Images