A management system for centralized control of air conditioners

Abstract

The present application relates to air conditioning technology field, specifically to a kind of air conditioning centralized control management system, system includes: environment perception module, obtains carbon dioxide sensor real-time concentration reading, establishes current CO2 concentration value, determines personnel profile, generates area state assessment result.In the present application, the degree of concentration of personnel is determined by real-time acquisition of carbon dioxide concentration reading, and the activity state of personnel in the area is evaluated, and the temperature and fresh air volume benchmark are set reasonably in combination with the particulate matter pollution level, to enhance the pertinence of air quality control.The determination method of air conditioning demand intensity is refined by quantitative calculation of health and comfort gap, so that the adjustment of temperature and fresh air volume is more in line with actual demand.The priority of temperature or fresh air volume is dynamically determined based on air conditioning demand intensity, and the control weight is used as a quantitative benchmark to reasonably improve the flexibility of adjustment strategy and avoid the hysteresis of traditional static control mode.

Description

Technical Field

[0001] This invention relates to the field of air conditioning technology, and more particularly to a centralized control management system for air conditioning. Background Technology

[0002] The field of air conditioning technology mainly involves a series of technical methods and equipment integration for the effective monitoring, control and optimization of indoor air environment temperature, humidity, fresh air volume and air quality.

[0003] Current technologies lack assessments of occupant density, activity levels, and indoor pollution, failing to effectively respond to changes in indoor environmental demands. This makes air conditioning strategies relatively inadequate when dealing with complex and variable human activities. Furthermore, current technologies do not fully utilize outdoor meteorological data, resulting in air conditioning parameter settings often deviating from actual external conditions. This can easily lead to over- or under-adjustment, such as failing to respond promptly to rising outdoor temperatures, increasing energy costs. Therefore, improvements are needed. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of existing technologies and to propose a centralized air conditioning control management system.

[0005] To achieve the above objectives, the present invention adopts the following technical solution: a centralized air conditioning control management system comprising:

[0006] The environmental perception module acquires real-time concentration readings from the carbon dioxide sensor, establishes the current CO2 concentration value, determines personnel profiles, and generates regional status assessment results.

[0007] The demand assessment module reads the current value of the indoor PM2.5 sensor based on the regional status assessment results, obtains the indoor particulate matter pollution level, sets the temperature benchmark and fresh air volume benchmark based on the indoor particulate matter pollution level and with reference to the regional status assessment results, calculates the health and comfort gap, and establishes the air conditioning demand intensity.

[0008] The control decision module determines whether to prioritize adjusting the temperature or the fresh air volume based on the intensity of the air conditioning demand, obtains the control weight corresponding to the priority item, obtains the weight of the core control parameter, formulates the target value of the air conditioning operation parameter based on the weight of the core control parameter and in conjunction with the weather forecast, and establishes the air conditioning parameter adjustment instruction.

[0009] The zone execution module, based on the air conditioning parameter adjustment command, selects the target air conditioning control zone corresponding to the command, determines the zone adjustment range, obtains the specified zone adjustment scheme, and operates the ventilation equipment operating frequency of the target zone based on the specified zone adjustment scheme.

[0010] Preferably, the steps for obtaining the regional state assessment results are as follows:

[0011] Based on the real-time concentration readings of the carbon dioxide sensor, the instantaneous CO2 concentration values ​​at each monitoring point are collected, the instantaneous CO2 concentration values ​​are sorted by time series, and the average and highest CO2 concentration values ​​within the last 30 minutes are calculated to obtain the average and highest CO2 concentration values.

[0012] Calculate the CO2 concentration fluctuation composite factor based on the average CO2 concentration and the highest CO2 concentration.

[0013] Based on the CO2 concentration fluctuation composite factor, the difference is compared with the personnel density benchmark value in the preset regional functional attributes to determine the activity level of personnel in the region and to determine the personnel profile, thereby generating a regional status assessment result.

[0014] Preferably, the step of obtaining the indoor particulate matter pollution level is as follows:

[0015] Based on the regional status assessment results, personnel profiles are extracted from the regional status assessment results, and the corresponding personnel density and activity level are analyzed to determine the current particulate matter pollution sensitivity level of the region, thus forming a particulate matter pollution sensitivity level.

[0016] Based on the particulate matter pollution sensitivity level, read the current value of the indoor PM2.5 sensor, obtain the instantaneous PM2.5 concentration readings collected by all sensors one by one, sort the instantaneous PM2.5 concentration readings, remove abnormal concentration readings, and select the median of the sorted values ​​as the representative value of indoor PM2.5 to obtain the representative value of indoor PM2.5.

[0017] Based on the representative value of indoor PM2.5, and referring to the concentration classification range of the ambient air quality standard, the pollution level of indoor particulate matter pollution is determined, and the pollution level is compared with the particulate matter pollution sensitivity level to obtain the indoor particulate matter pollution level.

[0018] Preferably, the step of obtaining the air conditioning demand intensity is as follows:

[0019] Based on the indoor particulate matter pollution level and regional status assessment results, the pollution level classification standard table and the regional functional attribute mapping table are called to match the combination of pollution level and population density, and the temperature benchmark, fresh air volume benchmark and humidity benchmark corresponding to the matched combination are extracted to form the temperature benchmark, fresh air volume benchmark and humidity benchmark.

[0020] Based on temperature, fresh air volume, and humidity benchmarks, calculate the gap in health and comfort.

[0021] Based on the aforementioned health and comfort gap, the health and comfort gap is compared with the adjustment demand threshold range, and the corresponding air conditioning demand intensity is divided according to the range in which it is located.

[0022] Preferably, the steps for obtaining the weights of the core control parameters are as follows:

[0023] Based on the air conditioning demand intensity, a pre-established mapping table of air conditioning demand intensity and adjustment item priority is invoked, and the temperature adjustment priority and fresh air volume adjustment priority corresponding to the air conditioning demand intensity level are compared one by one to determine the adjustment priority under the current demand intensity and form the adjustment priority.

[0024] Based on the adjustment priority, the corresponding control weight values ​​are extracted from the adjustment priority, and the control weight values ​​of non-priority adjustment items are confirmed based on the control weight values. These are then combined to form the temperature adjustment control weight and the fresh air volume adjustment control weight, generating the core control parameter weights.

[0025] Preferably, the step of obtaining the air conditioner parameter adjustment command is as follows:

[0026] Based on the weights of the core control parameters, the temperature regulation control weight and the fresh air volume regulation control weight are extracted from the core control parameter weights. The difference between the temperature regulation control weight and the fresh air volume regulation control weight is calculated. It is determined whether the absolute value of the difference between the two control weights exceeds the set dominant weight threshold. If the absolute value of the difference exceeds the threshold, the control parameter with the largest weight is selected as the dominant control item for air conditioning. Otherwise, the temperature regulation is the dominant control item by default, and the dominant control item for air conditioning is generated.

[0027] Based on the air conditioning dominant control item, obtain the hourly outdoor temperature forecast data for the next 24 hours, analyze and extract the temperature change rate of adjacent time periods in the hourly temperature forecast data, determine whether each time period belongs to the temperature change period by setting the temperature change rate threshold, and then combine the type of air conditioning dominant control item and the change period to determine the adjustment range of the corresponding air conditioning dominant control item one by one, and accumulate and superimpose the initial operating parameters to generate the target value of the air conditioning operating parameters for 24 hours, thus forming the target value of the air conditioning operating parameters.

[0028] Based on the target values ​​of the air conditioning operating parameters, and in accordance with the interface standard between the target values ​​of the air conditioning operating parameters and the air conditioning control system, the hourly target temperature values ​​and target fresh air volume values ​​are converted into digital parameter adjustment instructions that can be executed by the air conditioning control system. These instructions are then arranged in order of timestamp and encapsulated into data messages to generate air conditioning parameter adjustment instructions.

[0029] Preferably, the step of obtaining the adjustment scheme for the specified area is as follows:

[0030] Based on the air conditioning parameter adjustment instructions, the target air conditioning control area number in each parameter adjustment instruction is extracted, and the area number in the air conditioning control area configuration table is compared one by one to determine the target air conditioning control area that needs to be adjusted. The current temperature, current fresh air volume and current personnel density of each area are recorded to generate a target air conditioning control area information set.

[0031] Based on the target air conditioning control area information set, calculate the standardized adjustment demand index for each area;

[0032] Based on the standardized adjustment demand index of each air conditioning control area, it is compared with the set adjustment threshold value to screen out the air conditioning control areas that exceed the adjustment threshold value, and the temperature adjustment deviation and fresh air volume adjustment deviation are recorded respectively to generate the specified area adjustment plan.

[0033] Preferably, based on the specified area adjustment scheme, the steps for adjusting the operating frequency of the ventilation equipment in the target area are as follows:

[0034] Based on the specified area adjustment scheme, the temperature adjustment deviation and fresh air volume adjustment deviation of each target air conditioning control area are extracted from the specified area adjustment scheme. The fresh air volume adjustment deviation is compared with the preset maximum fresh air volume adjustment range, and the percentage of the fresh air volume adjustment deviation to the maximum adjustment range is calculated to generate the fresh air volume adjustment ratio.

[0035] Based on the fresh air volume adjustment ratio, the rated operating frequency of the ventilation equipment corresponding to the target air conditioning control area is called. The real-time operating frequency of the target ventilation equipment is obtained by multiplying the fresh air volume adjustment ratio by the rated operating frequency, and then rounded down to an integer frequency that can be directly accepted by the equipment to form the real-time frequency of the ventilation equipment in the target area.

[0036] Based on the real-time frequency of the ventilation equipment in the target area, the instructions are sent one by one to the ventilation equipment in the target area, driving the ventilation equipment in the target area to adjust its current operating frequency according to the instructions.

[0037] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0038] This invention uses real-time carbon dioxide concentration readings to determine population density and assess the activity levels of people in the area. Simultaneously, it sets reasonable temperature and fresh air volume benchmarks based on particulate matter pollution levels, enhancing the targeted nature of air quality control. Quantitative calculations of the health and comfort gap refine the determination of air conditioning demand intensity, making temperature and fresh air volume adjustments more aligned with actual needs. Based on the dynamic determination of air conditioning demand intensity, the priority of temperature or fresh air volume is assessed, using control weights as quantitative benchmarks to reasonably improve the flexibility of adjustment strategies and avoid the lag of traditional static control modes. Furthermore, it integrates outdoor meteorological data, enabling proactive responses to outdoor temperature fluctuations and optimizing the setting of target values ​​for air conditioning operating parameters, thus improving the adaptability of operating parameters. Standardized analysis methods for specific parameters in target areas allow for more precise determination of regional adjustment ranges, thereby improving the execution accuracy of air conditioning control commands and enhancing the air conditioning effect and energy efficiency management level in each area. Attached Figure Description

[0039] Figure 1 This is a system flowchart of the present invention. Detailed Implementation

[0040] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0041] Please see Figure 1 The present invention provides a technical solution: a centralized air conditioning control management system comprising:

[0042] The environmental perception module acquires real-time concentration readings from the carbon dioxide sensor, establishes the current CO2 concentration value, determines personnel profiles, and generates regional status assessment results.

[0043] The demand assessment module reads the current value of the indoor PM2.5 sensor based on the regional status assessment results to obtain the indoor particulate matter pollution level. Based on the indoor particulate matter pollution level, it sets the temperature benchmark and fresh air volume benchmark with reference to the regional status assessment results, calculates the health and comfort gap, and establishes the air conditioning demand intensity.

[0044] The control decision module determines whether to prioritize adjusting the temperature or the fresh air volume based on the intensity of air conditioning demand, obtains the control weight corresponding to the priority item, obtains the weight of the core control parameter, formulates the target value of the air conditioning operation parameter based on the weight of the core control parameter and combined with the weather forecast, and establishes the air conditioning parameter adjustment instruction.

[0045] The zone execution module selects the target air conditioning control zone corresponding to the air conditioning parameter adjustment command, determines the zone adjustment range, obtains the specified zone adjustment scheme, and operates the ventilation equipment operating frequency of the target zone based on the specified zone adjustment scheme.

[0046] The steps for obtaining the regional status assessment results are as follows:

[0047] Based on the real-time concentration readings of the carbon dioxide sensor, the instantaneous CO2 concentration values ​​at each monitoring point are collected, the instantaneous CO2 concentration values ​​are sorted by time series, and the average and highest CO2 concentration values ​​within the last 30 minutes are calculated to obtain the average and highest CO2 concentration values.

[0048] The CO2 concentration fluctuation composite factor is calculated based on the average CO2 concentration and the highest CO2 concentration. The calculation formula is as follows:

[0049] in, It is a composite factor for CO2 concentration fluctuations. For the first The instantaneous CO2 concentration value at each moment. This represents the average CO2 concentration. This represents the highest CO2 concentration. This represents the number of samples within the time window.

[0050] Based on the CO2 concentration fluctuation composite factor, the difference is compared with the personnel density benchmark value in the preset regional functional attributes to determine the activity level of personnel in the region and determine the personnel profile, thereby generating the regional status assessment result.

[0051] Specifically, based on real-time concentration readings from carbon dioxide sensors, the system first systematically collects current CO2 concentration data from, for example, three independent carbon dioxide sensors (SenseAir S8 or equivalent precision devices) deployed within a designated monitoring area. This data collection is performed at preset fixed time intervals, such as once per minute. The three sensors report instantaneous readings respectively. , ,and Subsequently, the system fuses these instantaneous readings from multiple sensors within the same area to calculate the value of the monitoring point at that moment. A single representative instantaneous CO2 concentration value The average method is used, that is For the above example, These calculations yielded The values ​​are recorded and stored strictly in chronological order of their collection, forming a time-series database. Then, to obtain the average and highest CO2 concentration values ​​within the most recent 30 minutes, the system extracts the latest 30 consecutive values ​​from this time-series database. Data points (if collected once per minute, corresponding to readings over the past 30 minutes), for example, to obtain a sequence. ,in This is a reading from 30 minutes ago. This is the latest reading, the average CO2 concentration. By calculating these 30 The average of the values ​​is obtained, i.e. The highest CO2 concentration value This is achieved by iterating through these 30... The value is determined by selecting the largest value among the 30 readings. For example, if the sum of the 30 readings is... The average value is If one of the readings is And if it is the maximum, then the highest concentration value is... The average CO2 concentration and the highest CO2 concentration were obtained.

[0052] formula: The advantage of the formula lies in the CO2 concentration fluctuation composite factor. It can comprehensively reflect the fluctuation characteristics and degree of variation of CO2 concentration over time, and also introduces its relationship with the highest concentration value. The relative relationship between these two factors, by averaging the products of their deviations, can more sensitively capture rapid or large fluctuations in CO2 concentration caused by changes in the number of people or their activity status, especially those points that deviate from the average and are significantly lower (or higher) than the peak value. The denominator contains... It serves to normalize and avoid division by zero, making the factors comparable at different concentration levels.

[0053] The steps to obtain the parameters are as follows: Representing the The instantaneous CO2 concentration value at each sampling moment. This value is obtained in real time by CO2 sensors deployed within the monitoring area. Data is read from the sensors at a preset sampling frequency (e.g., once per minute). Each reading is associated with a specific timestamp, representing a particular moment. At any given moment. For example, in region A, the CO2 sensor... The concentration recorded at that time was Then at this time If there are multiple sensors in an area, This could be the average of all sensor readings at that moment, ensuring data representativeness. For example, if three sensors in the area... The time readings are respectively , , ,but .

[0054] The steps to obtain the parameters are as follows: Represents all instantaneous CO2 concentration values ​​within a specific time window (e.g., the most recent 30 minutes). The average value. This value reflects the average level of CO2 concentration within that time period. It is calculated by taking all values ​​within the selected time window. indivual Sum the values ​​and then divide by the sample size. For example, if one sample is collected every minute within the last 30 minutes... Value, then If these 30 The sum of the values ​​is ,but .

[0055] The steps to obtain the parameters are as follows: Represents all instantaneous CO2 concentration values ​​within a target time window (e.g., the most recent 30 minutes). The highest value in the range. It represents the peak level of CO2 concentration reached within that time period. It is obtained by analyzing all values ​​within the selected time window. indivual Among the values, the one with the largest value is selected by comparison. For example, if the values ​​collected within the last 30 minutes... The value sequence is And among them If it is the maximum value in this set of data, then .

[0056] The steps to obtain the parameters are as follows: This represents the number of samples within the time window used for statistical analysis. For example, if the system is set to collect CO2 concentration data once per minute ( And the analysis time window is the most recent 30 minutes, so the sample size... It is equal to .

[0057] Calculation process: Select a relatively short time window and set... These are sample points. These sample points represent the most recently observed instantaneous CO2 concentration values. The obtained average CO2 concentration values... and the highest CO2 concentration value The set instantaneous CO2 concentration value (Unit: ppm) is as follows: , , , , ;

[0058] Number of samples within the time window .

[0059] First, calculate the average CO2 concentration. :

[0060] ;

[0061] Then, determine the highest CO2 concentration value. From sample data In the middle, the maximum value is .

[0062] Next, calculate each term in the summation term. Corresponding part :for ( ):

[0063] ;

[0064] for ( ):

[0065] ;

[0066] for ( ):

[0067] ;

[0068] for ( ):

[0069] ;

[0070] for ( ):

[0071] ;

[0072] Then, sum these values:

[0073] ;

[0074] Finally, the composite factor of CO2 concentration fluctuations was calculated. :

[0075] ;

[0076] The results indicate that the CO2 concentration fluctuation composite factor is approximately 1.7235. This value quantifies the degree of fluctuation and non-uniformity of CO2 concentration within a defined time window of five sample points. A higher... Values ​​typically indicate drastic changes or highly uneven distribution of CO2 concentration in a region, suggesting rapid increases or decreases in the number of people, sudden changes in people's activity patterns (such as from sitting to exercising), or significant changes in ventilation conditions.

[0077] Based on the CO2 concentration fluctuation composite factor calculated in the previous step For example, if its value is 1.7235, the system will then compare and analyze it with the "personnel density benchmark value in the preset area function attributes." Here, the "personnel density benchmark value" is not a single value, but a set of predefined CO2 concentration fluctuation reference indicators for different area functions (e.g., meeting rooms, open office areas, corridors, etc.) and different expected personnel density levels (e.g., low, medium, high density). These indicators include the expected range of CO2 concentration fluctuation composite factors. Their setting is based on long-term monitoring and statistical analysis of CO2 data for various types of areas under different usage scenarios. For example, for an "open office area," by analyzing historical data, under the scenario of "normal medium-density occupancy and regular office activities," its expected... The range is 1.5 to 3.0, corresponding to the low activity threshold. The value is 1.0 (based on historically confirmed periods of moderate density and low activity). The 80th percentile of the value is set, such as 1.0 ppm), and the high activity threshold is used. The value was 4.0 (based on historically confirmed periods of moderate density and high activity). The 20th percentile of the value is set, such as 4.0 ppm. In practice, the corresponding set of baseline values ​​is first retrieved based on the functional attributes of the current area (e.g., "open office area"), and then the currently calculated value is... Compare with the threshold in this set, if (Right now (If this does not apply in this example), then it is judged as low activity; if (Right now If this is true in this example, then it is judged as moderate activity; if (Right now (This does not apply in this example), therefore, it is judged as high activity. Thus, according to... This value indicates that the activity level of people in the area is classified as "moderate," which is combined with the obtained average CO2 concentration value. (For example, 720 ppm may correspond to a moderate population density) and the highest concentration value The overall population size profile reflected by (e.g., 780 ppm) is used to determine the current population profile as "medium population density, medium activity level", and generate an area status assessment result containing this population density and activity information.

[0078] The steps to obtain indoor particulate matter pollution levels are as follows:

[0079] Based on the regional status assessment results, personnel profiles are extracted from the regional status assessment results, and the corresponding personnel density and activity level are analyzed to determine the current particulate matter pollution sensitivity level of the region and form a particulate matter pollution sensitivity level.

[0080] Based on the particulate matter pollution sensitivity level, read the current value of the indoor PM2.5 sensor, obtain the instantaneous PM2.5 concentration readings collected by all sensors one by one, sort the instantaneous PM2.5 concentration readings, remove abnormal concentration readings, and select the median of the sorted values ​​as the representative value of indoor PM2.5 to obtain the representative value of indoor PM2.5.

[0081] Based on the representative value of indoor PM2.5 and referring to the concentration classification range of ambient air quality standards, the pollution level of indoor particulate matter is determined, and the pollution level is compared with the particulate matter pollution sensitivity level to obtain the indoor particulate matter pollution level.

[0082] Specifically, based on the regional status assessment results obtained from previous steps, such as structured data containing "Medium Population Density" and "High Activity Level," the system first accurately extracts these two core population profile indicators: "Medium Population Density" and "High Activity Level." Then, based on these two indicators, the system determines the current area's particulate matter pollution sensitivity level by consulting a predefined "Personnel Profile and Particulate Matter Pollution Sensitivity Level Mapping Table." This mapping table maps different combinations of population density and activity level to preset sensitivity levels, such as "High," "Medium," and "Low." This mapping table is established based on the following logic: the denser the population, the more potential sources of particulate matter (such as clothing fibers and dander), and the greater the air disturbance. Conversely, the more active the activity, the easier it is for dust accumulated on the ground and object surfaces to be stirred up and suspended in the air. Both factors exacerbate the instantaneous concentration of indoor particulate matter or increase the risk of human exposure. Therefore, the mapping rule is set as follows: for example, when both "Personnel Density" and "Activity Level" are "High,"... Either "medium" or when both "population density" and "activity level" are "medium" is "high" is the "particulate matter pollution sensitivity level"; when both "population density" and "activity level" are "low", or both are "medium" and "activity level" is "low", it is determined to be "low"; other intermediate combinations, such as "population density: medium" and "activity level: relatively high" in this example, may be determined according to specific mapping rules (e.g., "high" activity level implies at least "medium" sensitivity, unless the population density is high). If the density is extremely low, it is judged as "medium" or "high". If the rule defines medium density combined with high activity as corresponding to "high" sensitivity level, then the particulate matter pollution sensitivity level of the current area is determined to be "high". The specific entries of this mapping table are formulated by environmental health experts and building management engineers through statistical analysis of historical PM2.5 data and corresponding time period records of personnel activities in specific places (such as offices, schools, shopping malls) based on research results on indoor air quality exposure risk in public health.

[0083] Based on the particulate matter pollution sensitivity level determined in the previous step, for example, if it is determined to be "high", the system then proceeds to read the current values ​​of the indoor PM2.5 sensors. This involves sending data request commands to all PM2.5 sensors deployed in the target monitoring area. The sensors report the instantaneous PM2.5 concentration readings at a preset frequency (e.g., once every 5 minutes). The system acquires these readings one by one. For example, in the current sampling period, the three sensors reported [data missing]. , , The instantaneous PM2.5 concentration readings were obtained. Next, outlier removal was performed on these raw readings. The criteria for outlier determination first included an absolute valid range check; for example, the PM2.5 reading must be within a certain range. to If the readings exceed the specified range, they are considered sensor faults or communication errors and are directly rejected. Secondly, for multi-sensor deployments, consistency checks are performed. For example, the average and standard deviation of all valid readings are calculated. If a reading deviates from the average by more than three times the standard deviation, it is considered an anomaly. Or, more simply, if a value in a set of readings is significantly higher than others, for example… Much higher and A threshold rule can be set, such as "if a reading exceeds twice the average value of other sensors and the absolute difference is greater than..." "Here, the average value of other sensors is..." , , Greater than and Greater than ,but These readings are identified as abnormal and removed. The threshold for this type of reading is set based on statistical analysis of historical sensor data and empirical judgment of environmental disturbance factors, removing outliers (in this example, ). After that, the remaining effective instantaneous PM2.5 concentration reading (i.e. , The values ​​will be sorted in ascending order to obtain the sorted sequence. Finally, the median of this sorted sequence is selected as the representative value of indoor PM2.5 for the area. If the number of elements in the sequence is odd, the median is the middle value; if it is even (as in this example), the median is usually the average of the two middle values. This yields the representative value of indoor PM2.5.

[0084] Based on the indoor PM2.5 values ​​obtained in the previous step, for example... Based on the particulate matter pollution sensitivity level obtained in the first paragraph, such as "high," the system begins to determine the final indoor particulate matter pollution level. First, it refers to the representative indoor PM2.5 value within a set concentration grading range to determine its original air quality level. The specific standards are: 0-35µg / m³ corresponds to "Excellent," 36-75µg / m³ to "Good," 76-115µg / m³ to "Lightly Polluted," 116-150µg / m³ to "Moderately Polluted," 151-250µg / m³ to "Heavily Polluted," and greater than 250µg / m³ to "Severely Polluted." According to this standard... The pollution level is classified as "Excellent". Subsequently, this "Excellent" pollution level is compared and analyzed against the known "High" particulate matter pollution sensitivity level. This comparison is based on a pre-defined "Comprehensive Assessment Matrix of Pollution Level and Sensitivity Level". This matrix defines the final "indoor particulate matter pollution level" under different combinations. For example, the final level is divided into five levels: "Clean", "Good", "Average", "Poor", and "Very Poor". The principle behind this matrix is ​​that, at the same PM2.5 concentration, the higher the sensitivity level, the higher the final assessed indoor particulate matter pollution level will be, reflecting a more prudent consideration of health risks. For example, if the PM2.5 level is "Excellent" and the sensitivity level is "Low" or "Medium", the final level is still "Clean"; however, if the sensitivity level is "High" (as in this example), the final level is adjusted to "Good". Although the current absolute value of PM2.5 is not high, due to dense population or frequent activities, the potential health impact or deterioration trend cannot be ignored. Specifically, in this example, the "Excellent" pollution level (PM2.5 is...) is... The combination of "good" and "high" particulate matter pollution sensitivity levels is used to determine the final indoor particulate matter pollution level as "good" by consulting the comprehensive assessment matrix (for example, the matrix specifies: PM2.5 excellent & high sensitivity -> indoor particulate matter pollution level = good).

[0085] The steps to obtain the air conditioning demand intensity are as follows:

[0086] Based on the indoor particulate matter pollution level and regional status assessment results, the pollution level classification standard table and the regional functional attribute mapping table are called to match the combination of pollution level and population density, and the temperature benchmark, fresh air volume benchmark and humidity benchmark corresponding to the matched combination are extracted to form the temperature benchmark, fresh air volume benchmark and humidity benchmark.

[0087] Based on temperature, fresh air volume, and humidity benchmarks, the health and comfort gap is calculated using the following formula:

[0088] ;

[0089] in, To address the gap in health and comfort, The current indoor temperature. As a temperature reference, For the current fresh air volume, As a benchmark for fresh air volume, The current relative humidity, As a humidity benchmark, The level of particulate matter pollution;

[0090] "Based on temperature, fresh air volume, and humidity benchmarks, the individual contribution of each environmental parameter to the health and comfort gap is calculated:"

[0091] Temperature contribution ,in The current indoor temperature. As a temperature reference, The level of particulate matter pollution;

[0092] Humidity contribution ,in The current relative humidity, Used as a humidity reference.

[0093] Contribution of fresh air volume ,in For the current fresh air volume, As a benchmark for fresh air volume; through comparison The magnitude of the values ​​is used to determine the dominant influencing parameter (the parameter with the largest value is the main factor causing the current gap in health and comfort), and the dominant influencing parameter is recorded together with the intensity of air conditioning demand.

[0094] Based on the health and comfort gap, the health and comfort gap is compared with the threshold range of adjustment demand, and the corresponding air conditioning demand intensity is divided according to the range in which it is located.

[0095] Table 1 Pollution Level Classification Standards

[0096] Indoor particulate matter pollution levels Pollution level coding clean 1 good 2 generally 3 Poor 4 Difference 5

[0097] Table 2 Mapping Table of Regional Functional Attributes and Environmental Benchmarks

[0098] Regional functions population density Pollution level coding Temperature baseline (summer) Fresh air volume standard (m³ / h / person) Humidity Standard Open office area Low 1 (Cleaning) 25.5℃ 25 60% Open office area medium 2 (Good) 24.5℃ 30 55% Open office area high 2 (Good) 24.0℃ 35 55% Open office area medium 4 (Poor) 25.0℃ 40 50% Meeting room high 1 (Cleaning) 24.0℃ 30 50% Meeting room high 3 (General) 24.5℃ 35 50% private office Low 2 (Good) 25.0℃ 25 55% corridor Low 3 (General) 26.0℃ 15 60%

[0099] Specifically, based on the indoor particulate matter pollution level determined in the previous steps, such as "Good," and the regional status assessment results, such as information including "Personnel density: Moderate" and "Regional function: Open office area," the system first calls the internally stored "Pollution Level Classification Standard Table" and "Regional Function Attribute and Environmental Baseline Mapping Table," as shown in Tables 1 and 2. The "Pollution Level Classification Standard Table" maps "Indoor Particulate Matter Pollution Level" (such as "Clean," "Good," "Average," "Poor," "Very Poor") to standardized pollution level codes. For example, "Clean" corresponds to level 1, "Good" to level 2, "Average" to level 3, "Poor" to level 4, and "Very Poor" to level 5. This classification standard is based on the degree of impact of various pollution levels on human health and comfort, and is formulated with reference to relevant environmental health guidelines. For example, level 2 (Good) indicates that the air quality is acceptable, but may have a slight impact on sensitive groups. Based on the input "Good" indoor particulate matter pollution level, the system retrieves its corresponding pollution level code of 2 from the table. At the same time, the system... The regional status assessment results extract "Medium" for "Personnel Density" and "Open Office Area" for "Regional Function". Then, the system uses this information—pollution level code 2, "Medium" for "Personnel Density", and "Open Office Area" for "Regional Function Attributes and Environmental Benchmark Mapping Table"—for multi-dimensional matching queries. This mapping table is a pre-set database storing recommended indoor environmental parameter benchmark values ​​for different combinations of regional functions, personnel densities, and air pollution levels. These benchmark values ​​are comprehensively set based on relevant international and domestic building environmental design standards, combined with the energy-saving goals and usage characteristics of specific buildings. For example, for "Open Office Area", under the conditions of "Medium" personnel density and pollution level 2 (Good), the table might return the following matching results: temperature benchmark of 24.5℃ in summer, fresh air volume benchmark of 30 cubic meters per person per hour (if the area is designed to accommodate 20 people, then the total fresh air volume benchmark is 600 cubic meters per hour), and humidity benchmark of 55% relative humidity. The system extracts these specific values ​​to form the temperature benchmark (…). ), Fresh air volume benchmark ( ) and humidity standard ( ).

[0100] formula: The advantage of the formula lies in the "health and comfort gap". This indicator quantifies the deviation of the current indoor environment from the ideal state of comfort and health through a comprehensive metric. It combines the relative deviations of three core environmental parameters affecting comfort and health—temperature, fresh air volume, and humidity—using a square root of the sum of squares (similar to Euclidean distance), ensuring that a significant deviation in any parameter will lead to… The increase in values ​​thus comprehensively reflects the overall environmental inadequacy. More importantly, it introduces particulate matter pollution level grades. As amplification factor This formula highlights that when air quality is poor, even if the deviations in temperature, humidity, and fresh air volume are the same, their negative impact on human health and comfort will be amplified. This design allows the air conditioning system to prioritize handling situations where air pollution is superimposed on deviations in other environmental parameters when making decisions, reflecting a people-oriented and health-first regulation strategy.

[0101] The steps to obtain the parameters are as follows: This represents the actual average indoor temperature within the current monitoring area. This value is collected in real time by multiple temperature sensors deployed within the area. The system reads the instantaneous temperature values ​​from each sensor at a fixed frequency (e.g., every minute) and calculates the average of these readings as the average temperature of the area at that moment. Value. For example, if the current readings of three temperature sensors in the area are 25.8℃, 26.0℃, and 26.2℃ respectively, then... .

[0102] The steps to obtain the parameters are as follows: This represents the temperature baseline value for the region, retrieved from the "Regional Function Attributes and Environmental Baseline Mapping Table" based on the current regional status (including regional function, population density, season, and indoor particulate matter pollution level). This baseline value is dynamic and aims to provide the optimal or acceptable temperature setting target under current conditions. For example, according to the description, for an "open office area," with a "moderate" population density, summer conditions, and a "good" indoor particulate matter pollution level, the extracted temperature baseline is... .

[0103] The steps to obtain the parameters are as follows: This represents the actual total fresh air supply to the currently monitored area. This data is typically obtained from the building management system (BMS) or directly from the fresh air valve controller, air velocity sensor, or differential pressure sensor within the HVAC system. For example, it can be recorded as the current fresh air supply to the area by reading the real-time airflow data from the fresh air handling unit's supply air volume monitoring instrument or the variable air volume box associated with the area. .

[0104] The steps to obtain the parameters are as follows: This represents the baseline fresh air volume value for the area, obtained based on the current area status. This baseline value is also dynamic, set according to the area's rated or estimated occupancy and pollution levels. For example, for an "open office area" designed to accommodate 20 people, under "medium" occupancy and "good" pollution levels, the extracted baseline fresh air volume would be: .

[0105] The steps to obtain the parameters are as follows: This represents the actual average relative humidity within the current monitoring area. Similar to temperature, this value is obtained by averaging the readings of multiple humidity sensors deployed within the area in real time. For example, if two humidity sensor readings in the area are 63% and 67%, then... .

[0106] The steps to obtain the parameters are as follows: This represents the relative humidity baseline value for the region, retrieved based on the current regional conditions. This baseline value aims to maintain a humidity range that is both comfortable and healthy. For example, the humidity baseline extracted for specific conditions might be... .

[0107] The steps to obtain the parameters are as follows: Representing the level of particulate matter pollution, this is a unitless quantitative value that is converted from the "indoor particulate matter pollution level" (e.g., "clean," "good," "average," "poor," "very poor") determined in previous steps. The conversion rules need to be predefined, mapping qualitative pollution descriptions to incremental numerical values ​​to reflect the weighted impact of pollution levels on comfort level calculations. For example, the following mapping relationship could be set: "clean" corresponds to... "Good" corresponds to "General" corresponds to "Poor" corresponds to "difference" corresponds to These values ​​are based on empirical assessments of the acceptability and health impacts on the population at different air quality levels. The numerical intervals can be non-linear to emphasize the greater negative weighting of poorer air quality. If the aforementioned "indoor particulate matter pollution level" is "good," then... .

[0108] Calculation process: Assume the currently acquired parameter values ​​are as follows: Current indoor temperature Temperature reference Current fresh air volume Fresh air volume benchmark Current relative humidity Humidity standard Particulate matter pollution level (Corresponding to a "good" level of indoor particulate matter pollution);

[0109] Calculate the relative deviation term for each parameter: Square of relative temperature deviation:

[0110] ;

[0111] Square of relative deviation of fresh air volume:

[0112] ;

[0113] Square of relative humidity deviation:

[0114] ;

[0115] Calculate the sum of squares:

[0116] ;

[0117] Calculate the square root of the sum of squares:

[0118] ;

[0119] Calculate the pollution level adjustment factor:

[0120] ;

[0121] Calculate the final health and comfort gap :

[0122] ;

[0123] This result indicates a gap in health and comfort. The value is 0.27955. This unitless value comprehensively reflects the overall deviation of the current indoor environment from the set benchmark in three dimensions: temperature, fresh air volume, and humidity, and is weighted and adjusted by the particulate matter pollution level. The higher the value, the greater the gap between the current environment and the ideal comfortable and healthy state, and the higher the likelihood and intensity of adjustment required by the air conditioning system.

[0124] Based on the health and comfort gap calculated in the previous step For example, a value of 0.27955. The system then compares this difference value with a set of preset "adjustment demand threshold ranges," which define different health and comfort gaps. The corresponding air conditioning demand intensity levels, for example, demand intensity can be divided into four levels: "low", "medium", "high" and "emergency". The threshold range is set as follows: when When the demand intensity is "low", when At that time, the demand intensity was "moderate"; when At that time, the demand intensity was "high"; when At that time, the demand intensity was "urgent." These thresholds (0.10, 0.30, 0.50) were set after comprehensively considering the human body's sensitivity to environmental changes, the potential impact of different deviations on work efficiency and health, and the economy and responsiveness of the air conditioning system. Specifically, these thresholds were determined by analyzing a large amount of historical environmental parameter data, corresponding user comfort feedback (e.g., collected through periodic questionnaires or instant feedback buttons), and air conditioning system operating energy consumption data. Statistical methods (e.g., percentile method to determine the G-value distribution corresponding to different comfort complaint rates) were used, combined with expert experience (building automation engineers and ergonomics experts discussed together). The goal is to avoid excessive adjustment and frequent start-stop of the air conditioning system while ensuring the comfort and health of personnel. This is based on the currently calculated health and comfort gap. In this regard, the system matches it with the aforementioned threshold range: because The value falls within the "medium" demand intensity range. Therefore, based on this comparison result, the system classifies the current air conditioning demand intensity as "medium".

[0125] The steps for obtaining the weights of the core control parameters are as follows:

[0126] Based on the air conditioning demand intensity and dominant influencing parameters, the pre-established "Demand Intensity-Dominant Parameter-Regulation Priority Mapping Table" (see Table 3) is invoked to determine the regulation priority items for different scenarios:

[0127] If the dominant influencing parameter is temperature ( (Maximum): Regardless of the intensity of demand, temperature regulation is the priority.

[0128] If the dominant influencing parameter is humidity ( Maximum): Regardless of the intensity of demand, humidity control is the priority (a new humidity control module has been added, which is executed through the humidifier / dehumidifier).

[0129] If the dominant influencing parameter is the fresh air volume ( Maximum) or particulate matter pollution level (For pollution levels of "poor" or above): Regardless of the intensity of demand, adjusting the fresh air volume should be the priority.

[0130] If two or more parameters have similar contribution levels (difference ≤ 0.05): Prioritize them according to the order of "fresh air volume > humidity > temperature" (based on the industry knowledge that "fresh air volume directly affects air quality and health, humidity second, and temperature last"), and determine the adjustment priority under the current demand intensity to form the adjustment priority.

[0131] Table 3 Demand Intensity - Dominant Parameter - Adjustment Priority Mapping Table

[0132] Air conditioning demand intensity Dominant Influence Parameters Adjustment priority Temperature control weight Humidity control weight Fresh air volume control weight Low temperature temperature 0.7 0.2 0.1 Low humidity humidity 0.2 0.7 0.1 Low Fresh air volume / pollution Fresh air volume 0.1 0.2 0.7 middle temperature temperature 0.6 0.2 0.2 middle humidity humidity 0.2 0.6 0.2 middle Fresh air volume / pollution Fresh air volume 0.1 0.1 0.8 High / Emergency temperature temperature 0.8 0.1 0.1 High / Emergency humidity humidity 0.1 0.8 0.1 High / Emergency Fresh air volume / pollution Fresh air volume 0.1 0.1 0.8

[0133] Based on the adjustment priority, the corresponding control weight values ​​are extracted from the adjustment priority, and the control weight values ​​of non-priority adjustment items are confirmed based on the control weight values. These are then combined to form the temperature adjustment control weight and the fresh air volume adjustment control weight, generating the core control parameter weights.

[0134] Specifically, based on the air conditioning demand intensity determined in the previous step, for example, if the current level is "medium," the system first calls a pre-established "Air Conditioning Demand Intensity and Adjustment Item Priority Mapping Table." This table records in detail the initial priority values ​​of temperature adjustment and fresh air volume adjustment under different air conditioning demand intensity levels (e.g., divided into four levels: "low," "medium," "high," and "emergency"). The construction of this mapping table is based on in-depth analysis of factors affecting human comfort and health, energy efficiency of different environmental parameter adjustments, and expected response speeds. It is also calibrated and optimized by combining the experience and knowledge of HVAC experts with actual building operation data. For example, under a "medium" air conditioning demand intensity, if historical data and comfort models indicate slight temperature discomfort at this stage, the priority of temperature adjustment should be lower than that of fresh air volume adjustment. Slight fluctuations are more easily perceived by occupants, so temperature adjustment may be assigned a higher priority value, such as a priority of 1 (the smaller the number, the higher the priority), while fresh air volume adjustment is set to a priority of 2. Conversely, if maintaining air freshness is more critical for eliminating potential pollutants and improving the overall experience under this demand intensity, then fresh air volume adjustment may have a higher priority. The system looks up the corresponding entry in the mapping table based on the currently input "medium" level air conditioning demand intensity. For example, it reads that the temperature adjustment priority is 1 and the fresh air volume adjustment priority is 2. By comparing these two priority values, the system determines that the one with the smaller priority value (in this case, temperature adjustment, with a priority of 1) is the primary adjustment item under the current demand intensity, that is, it determines that the adjustment priority under the current demand intensity is "temperature adjustment", thus forming the adjustment priority item.

[0135] Based on the established adjustment priority, such as "temperature adjustment," the system then extracts the specific control weight value corresponding to the "temperature adjustment" priority from a preset "adjustment priority and control weight configuration table" or through a fixed weight allocation rule. The setting of this control weight value aims to quantify the importance or resource allocation ratio of different adjustment parameters in subsequent control decisions. The basis for setting this value is typically to assign a significantly higher weight to the priority adjustment item to ensure that its adjustment needs are primarily met. For example, a control weight of 0.7 can be specified for the priority adjustment item. These weight values ​​(such as 0.7) are not arbitrarily set. Instead, it analyzes historical control effects to evaluate the comprehensive impact of different weight allocation schemes on the improvement rate of target parameters, system stability, and energy consumption. The optimal balance between rapidly responding to priority needs and maintaining overall system balance is achieved through expert systems or machine learning methods. After extracting the control weight value of "temperature regulation" as a priority item as 0.7, the system uses this value and a preset weight allocation rule (e.g., the sum of the control weights of temperature and fresh air volume is always 1.0) to determine the control weight value of non-priority adjustment items (in this example, "fresh air volume regulation"). That is, the control weight of fresh air volume regulation is... Subsequently, the system merges the two separately calculated weight values, that is, the weight of temperature regulation control is determined to be 0.7 and the weight of fresh air volume regulation control is determined to be 0.3, which together constitute a set of core control parameter weights and generate core control parameter weights.

[0136] The steps to obtain air conditioner parameter adjustment commands are as follows:

[0137] Based on the weights of the core control parameters, the temperature regulation control weight and the fresh air volume regulation control weight are extracted from the weights of the core control parameters. The difference between the temperature regulation control weight and the fresh air volume regulation control weight is calculated. It is determined whether the absolute value of the difference between the two control weights exceeds the set dominant weight threshold. If the absolute value of the difference exceeds the threshold, the control parameter with the largest weight is selected as the dominant control item for air conditioning. Otherwise, the temperature regulation is the dominant control item by default, and the dominant control item for air conditioning is generated.

[0138] Based on the air conditioning dominant control item, obtain the hourly outdoor temperature forecast data for the next 24 hours, analyze and extract the temperature change rate of adjacent time periods in the hourly temperature forecast data, determine whether each time period belongs to the temperature change period by setting the temperature change rate threshold, and then combine the type of air conditioning dominant control item and the change period to determine the adjustment range of the corresponding air conditioning dominant control item one by one, and accumulate and superimpose the initial operating parameters to generate the target value of the air conditioning operating parameters for 24 hours, thus forming the target value of the air conditioning operating parameters.

[0139] Based on the target values ​​of the air conditioning operating parameters, and in accordance with the interface standard between the target values ​​of the air conditioning operating parameters and the air conditioning control system, the hourly target temperature values ​​and target fresh air volume values ​​are converted into digital parameter adjustment instructions that can be executed by the air conditioning control system. These instructions are then arranged in order of timestamp and encapsulated into data messages to generate air conditioning parameter adjustment instructions.

[0140] Specifically, based on the weights of the core control parameters generated in the preceding steps, such as a temperature regulation control weight of 0.7 and a fresh air volume regulation control weight of 0.3, the system first clearly extracts these two values ​​from this set of weights, namely the temperature regulation control weight. and fresh air volume adjustment control weight Next, the system calculates the absolute value of the difference between the two control weights, i.e. Subsequently, the system compares the absolute value of this difference, 0.4, with a pre-set "dominant weight threshold." This threshold, for example, 0.35, is based on the principle that when the weight difference between two control parameters is sufficiently large, focusing on adjusting the parameter with the higher weight can more significantly and efficiently improve the indoor environment to the target state, avoiding the slow response caused by the dispersion of control resources. This threshold of 0.35 was determined by analyzing the response time and energy efficiency of different weight combinations on the air conditioning system, combined with expert experience (for example, it is generally believed that when the weight of one parameter exceeds that of another by a certain proportion, such as a weight ratio exceeding 2:1, corresponding to a weight difference of approximately 0.33, its dominant role begins to emerge) and a large number of control strategy simulation test results. The aim is to ensure that only when a certain parameter's weight is significantly different does the system achieve its dominant effect. The system only designates a control parameter as the dominant control item when it has a significant advantage, in order to achieve stable and effective control. In this example, the absolute value of the calculated difference (0.4) is greater than the set dominant weight threshold (0.35). Therefore, the system will select the control parameter with the larger weight value as the dominant control item for air conditioning. Since the weight of temperature regulation (0.7) is greater than the weight of fresh air volume regulation (0.3), "temperature regulation" is selected as the dominant control item for air conditioning in the current state. If the absolute value of the calculated difference does not exceed the threshold, for example, 0.2, the system will default to using "temperature regulation" as the dominant control item for air conditioning. This is because when the weight difference is not significant, temperature is usually regarded as the primary factor affecting people's direct thermal comfort. Prioritizing its stability to meet general comfort requirements will generate the dominant control item for air conditioning.

[0141] Based on the air conditioning control item generated in the previous step, such as "temperature regulation", the system first obtains hourly outdoor temperature forecast data for the target area for the next 24 hours by calling the integrated meteorological service interface or internal prediction model. This data includes the expected average temperature value for each hour, for example, obtaining the forecast sequence for the next 24 hours from the current moment. Next, the system analyzes this hourly temperature forecast data, extracting the rate of temperature change between adjacent time periods. The calculation method is to subtract the predicted temperature of the previous hour from the predicted temperature of the next hour, obtaining the hourly temperature change value. For example, the hourly temperature change... The rate of temperature change per hour is Subsequently, the system compares the calculated rate of temperature change for each time period with a preset "rate of temperature change threshold," for example, 1.8°C per hour. This threshold is set with reference to the common daily temperature variation range in local historical meteorological statistics, the thermal performance of buildings (such as external wall insulation and airtightness), and the design load margin of the air conditioning system. The aim is to identify periods of rapid outdoor temperature change that may significantly impact the indoor heat load. A temperature change exceeding 1.8°C per hour is considered to require the air conditioning system to make pre-emptive adjustments. If the absolute value of the rate of temperature change for a given time period is greater than 1.8°C, that time period is marked as a "temperature change period," otherwise it is marked as a "temperature stable period." Then, the system combines the currently determined type of dominant air conditioning control item ("temperature regulation" in this example) with whether each time period belongs to a "temperature change period." The system determines the adjustment range of the dominant control item for the air conditioning system for each corresponding time period. If the dominant control item is "temperature regulation," and the period is marked as a "temperature change period," for example, if the outdoor temperature is predicted to drop by 2.5℃ (exceeding the 1.8℃ threshold) in the third hour, the system decides to pre-adjust and increase the indoor target temperature by 0.3℃ before the start of that period. This adjustment range is determined based on a preset rule base, which comprehensively considers the predicted change intensity, building thermal inertia, and energy-saving strategies. In "temperature stable periods," the adjustment range may be zero or only a small adjustment in response to changes in indoor load. This process will be applied to every hour of the next 24 hours, and the adjustment range determined for each hour (e.g., temperature adjustment range or fresh air volume adjustment range, depending on the dominant item) will be accumulated and superimposed on an initial operating parameter (e.g., the currently effective indoor target temperature of 24.0℃ and the target fresh air volume of 600). The system generates hourly target values ​​for air conditioning operating parameters for the next 24 hours. For example, if the initial target temperature is 24.0℃, and there is no significant change in the first hour, the adjustment range is 0℃, and the target remains 24.0℃. In the second hour, a significant temperature drop is predicted, so the adjustment range is +0.3℃, and the target becomes 24.3℃. In the third hour, the temperature continues to drop, so the adjustment is +0.2℃, and the target becomes 24.5℃, and so on. At the same time, it ensures that the target value is within the set reasonable comfort range. For example, in summer, the target temperature is always kept between 22℃ and 26℃, thus forming the target values ​​for air conditioning operating parameters.

[0142] Based on the target values ​​of the air conditioning operating parameters formed in the previous step, which are time-series data containing hourly target temperature and target fresh air volume values ​​for the next 24 hours, the system begins to convert and encapsulate these target values ​​according to the predefined interface standard of the building air conditioning control system. This interface standard specifies in detail the data exchange format, communication protocol, object attributes, or register addresses. The system processes these 24 sets of hourly target values ​​one by one, converting the target temperature value (e.g., the target temperature of the third hour is 24.5℃) and the target fresh air volume value (e.g., the target fresh air volume of the third hour is 620) for each hour. This process converts floating-point numbers into digital parameter adjustment commands that the air conditioning control system can directly receive and execute. This conversion includes data type matching (e.g., converting floating-point numbers to fixed-point numbers or integers of a specific precision accepted by the controller), unit conversion (if necessary), and converting logical target values ​​(such as fresh air volume) into digital parameter adjustment instructions. ) is mapped to specific device control commands (such as mapping 620) Based on the damper characteristic curve, the command is converted into the corresponding damper opening percentage instruction (78%) or fresh air unit frequency setting value (45Hz). This ensures that the converted instruction meets the input requirements and operating range of the target controller. After conversion, these digital parameter adjustment instructions are arranged strictly according to their corresponding timestamp order and encapsulated into one or more data messages conforming to the interface standard. For example, they are encapsulated into a JSON array containing the instruction sequence. Each JSON object contains a timestamp, region identifier, parameter type (such as "TEMP_SETPOINT", "FRESHAIR_VOLUME_SETPOINT"), parameter value, and possible execution priority. Finally, air conditioning parameter adjustment instructions that can be scheduled and executed by the air conditioning control system are generated.

[0143] The steps to obtain the adjustment plan for a specified area are as follows:

[0144] Based on the air conditioning parameter adjustment instructions, the target air conditioning control area number in each parameter adjustment instruction is extracted, and the area number in the air conditioning control area configuration table is compared one by one to determine the target air conditioning control area that needs to be adjusted. The current temperature, current fresh air volume and current personnel density of each area are recorded to generate a target air conditioning control area information set.

[0145] Based on the target air conditioning control area information set, the standardized regulation demand index of each area is calculated using the following formula:

[0146] ;

[0147] in, For the first Standardized adjustment demand index for each air conditioning control zone For the first The target temperature for each air-conditioned control zone For the first The current temperature of each air-conditioned control zone For the first The target fresh air volume for each air-conditioned control zone For the first The current fresh air volume in each air conditioning control zone For the first Instantaneous population density in each air-conditioned control zone;

[0148] Based on the standardized adjustment demand index of each air conditioning control area, it is compared with the set adjustment threshold value to screen out the air conditioning control areas that exceed the adjustment threshold value, and the temperature adjustment deviation and fresh air volume adjustment deviation are recorded respectively to generate the specified area adjustment plan.

[0149] Specifically, based on the air conditioning parameter adjustment instructions generated in the preceding steps, which contain parameter settings such as target temperature and target fresh air volume for specific air conditioning control areas at various future time periods, the system first parses and extracts the "target air conditioning control area number" from each received parameter adjustment instruction. For example, if the instruction specifies the area number as "ZONE_EAST_01F_OFFICE_A", then the system compares and queries this extracted area number with the internally stored "air conditioning control area configuration table". This configuration table is a database initialized during system deployment, recording detailed information about all independently controllable air conditioning areas within the building, including a unique "area number", corresponding physical location description, area type (such as open office area, meeting room), staff capacity, and associated environmental sensors (temperature, air quality ... The system uses identifiers (such as humidity, CO2, and PM2.5) to identify the target air conditioning control area requiring adjustment under the current command. For each identified target air conditioning control area requiring adjustment, such as "ZONE_EAST_01F_OFFICE_A", the system will immediately collect and record the current real-time environmental status parameters of the area through the building automation system or a directly connected sensor network. Specifically, this includes: obtaining the current temperature by querying the average temperature sensor reading in the area, for example, 25.5℃; obtaining the current fresh air volume by querying the fresh air valve opening feedback or anemometer reading connected to the area, for example, 450 cubic meters per hour; and obtaining the current personnel density, which can be obtained through various means, such as based on the real-time concentration value of the CO2 sensor in the area (as obtained in the aforementioned steps). and The system estimates the real-time number of people in the area by combining the area volume and a preset CO2 production rate per person model. This number is then divided by the area's designed capacity to obtain the density ratio (e.g., between 0.0 and 1.0). Alternatively, if a dedicated personnel counting device (e.g., Wi-Fi sniffing, video analysis, or infrared sensor) is used, the counting results are directly read and normalized. For example, if the area is designed to accommodate 20 people and there are currently 10 people, the personnel density is 0.5. All of this information collected for each target area (area number, current temperature, current fresh air volume, current personnel density, and the corresponding target temperature and target fresh air volume obtained from the air conditioning parameter adjustment command) is integrated to generate a target air conditioning control area information set.

[0150] formula: The advantage of the formula lies in the fact that it constructs a standardized adjustment demand index. Capable of comprehensively and dynamically quantifying specific air conditioning control zones The urgency of adjustment. First, the square root part of the formula calculates the combined effect of the relative deviations between the current values ​​and target values ​​of the two key parameters, temperature and fresh air volume, similar to a normalized Euclidean distance, by using relative deviations (e.g., This results in different physical dimensions (temperature unit °C, fresh air volume unit). The parameter deviations can be dimensionless and compared and integrated on the same scale. The squared term ensures that the deviation, whether positive or negative, contributes to the increase in the demand index, and the impact of larger deviations is more significant. Secondly, the formula is multiplied by a factor based on instantaneous population density. Regulatory factors natural logarithm function The introduction of this makes it possible when there is no one in the area ( When the population density in the area increases, the factor is 1, which does not change the impact of the baseline deviation. However, as the population density in the area increases, the factor increases smoothly but at a decreasing rate. This means that the higher the population density, the higher the adjustment priority (i.e., the greater the adjustment rate) the same deviation in temperature, humidity, or fresh air volume will be assigned. value).

[0151] The steps to obtain the parameters are as follows: Representing the The target temperature for each air conditioning control zone is expressed in degrees Celsius (°C). This value originates from the "Air Conditioning Parameter Adjustment Instruction" generated in the previous steps, specifying the temperature for a particular zone. The target temperature value set in the current or upcoming control cycle. For example, for zone "ZONE_EAST_01F_OFFICE_A" (i.e., the... (For each region), the system reads from the parsed air conditioning parameter adjustment command that the target temperature should be set to [value]. .

[0152] The steps to obtain the parameters are as follows: Representing the The current average temperature of each air conditioning control zone is shown in degrees Celsius (°C). This data was generated during the creation of the "Target Air Conditioning Control Zone Information Set" by querying the data in real time with the regional data. This is obtained by connecting a network of temperature sensors (e.g., multiple PT1000 or NTC temperature sensors deployed in the area) and calculating their average readings. For example, for area "ZONE_EAST_01F_OFFICE_A", the recorded current temperature is... .

[0153] The steps to obtain the parameters are as follows: Representing the The target fresh air volume for each air conditioning control zone is expressed in cubic meters per hour. Similar to the target temperature, this value also originates from the "Air Conditioning Parameter Adjustment Instructions" for the region. The set fresh air supply target. For example, the instruction specifies a target fresh air supply for zone "ZONE_EAST_01F_OFFICE_A". .

[0154] The steps to obtain the parameters are as follows: Representing the The actual fresh air supply to each air conditioning control zone at the current moment, in cubic meters per hour (m³ / h). This data was obtained by querying the building automation system and its relation to the area. The real-time feedback value is obtained from the connected fresh air conditioning unit. For example, the current fresh air volume in zone "ZONE_EAST_01F_OFFICE_A" is... .

[0155] The steps to obtain the parameters are as follows: Representing the The instantaneous occupancy density of each air-conditioned control zone. This value is obtained when generating the "target air-conditioned control zone information set". For example, by analyzing real-time monitoring data of CO2 concentration in this zone, combined with the zone volume, fresh air volume, and a standard human CO2 exhalation rate model (e.g., approximately 0.005 L / s per person), the current number of people in the room can be estimated, and then divided by the zone's maximum designed capacity. If zone "ZONE_EAST_01F_OFFICE_A" is designed to accommodate 20 people, and CO2 analysis estimates that there are currently 12 people, then... Alternatively, if a dedicated personnel counting system is available (such as a system based on Wi-Fi signal analysis or image recognition), the number of people output by that system can be directly used and normalized.

[0156] Calculation process: (The following is a list of steps / processes, likely related to calculations or calculations.) Taking the air conditioning control zone "ZONE_EAST_01F_OFFICE_A" as an example, substitute the specific values: target temperature Current temperature Target fresh air volume Current fresh air volume Instantaneous population density ;

[0157] Calculate the square of the relative temperature deviation:

[0158] ;

[0159] Calculate the square of the relative deviation of fresh air volume:

[0160] ;

[0161] Calculate the logarithmic term in the personnel density adjustment factor:

[0162] ;

[0163] Calculate the overall personnel density adjustment factor:

[0164] ;

[0165] Calculate the square root term:

[0166] ;

[0167] Calculate the final standardized adjustment demand index :

[0168] ;

[0169] The result indicates that the first Standardized adjustment demand index for each air conditioning control zone “ZONE_EAST_01F_OFFICE_A” It is approximately 0.37877. This value takes into account the deviation of the current temperature and fresh air volume from the target value, and also considers the impact of a population density of 0.6 in the area. The higher the value, the more urgent the need for air conditioning system adjustment in that area. For example, if the set adjustment threshold is 0.15, since 0.37877 is much greater than 0.15, this area will be identified as requiring priority adjustment.

[0170] Based on the standardized regulation demand index calculated for each target air conditioning control zone in the previous step. For example, the region "ZONE_EAST_01F_OFFICE_A" The value is 0.37877 for the region "ZONE_WEST_02F_MEETING_B". The system then compares each of these index values, starting with 0.12000, with a pre-set "adjustment threshold." This threshold, for example, is set to 0.15. It is not fixed but is determined based on the building's overall energy-saving strategy, the current season, specific time periods (such as peak or off-peak hours), and users' average sensitivity to environmental changes. The specific value (e.g., 0.15) is determined by analyzing long-term building operation data to identify a critical demand index that effectively balances the timeliness of adjustment response, avoids energy waste caused by over-adjustment, and ensures basic user comfort. For example, the maintenance team might analyze historical data and find that when the standardized adjustment demand index is below 0.15, most users report an acceptable environment, and further adjustments do not significantly improve comfort or increase energy consumption disproportionately. Therefore, 0.15 is used as a criterion for determining whether fine-tuning is necessary. Through this comparison process, the system filters out those standardized adjustment demand indices... Air conditioning control zones exceeding 0.15 are considered to be the areas most in need of air conditioning parameter adjustments. For each selected high-demand zone (e.g., "ZONE_EAST_01F_OFFICE_A"), due to its... The system will record the specific temperature regulation deviation, i.e. (For example, This indicates a need for a 1.5℃ temperature reduction, and also indicates a deviation in the fresh air volume adjustment. (For example, This indicates that an additional 150 is needed. The fresh air), while for areas that do not exceed the adjustment threshold (such as "ZONE_WEST_02F_MEETING_B"), because of its ... If a region is selected as a high-demand region, it will be ignored or only subject to basic maintenance adjustments in this round of adjustments. Finally, all the selected high-demand regions and their corresponding specific adjustment deviation information will be summarized and organized to form a regional adjustment plan.

[0171] Based on the specified area adjustment plan, the steps for adjusting the operating frequency of ventilation equipment in the target area are as follows:

[0172] Based on the specified area adjustment scheme, the temperature adjustment deviation and fresh air volume adjustment deviation of each target air conditioning control area are extracted from the specified area adjustment scheme. The fresh air volume adjustment deviation is compared with the preset maximum fresh air volume adjustment range, and the percentage of the fresh air volume adjustment deviation to the maximum adjustment range is calculated to generate the fresh air volume adjustment ratio.

[0173] Based on the fresh air volume adjustment ratio, the rated operating frequency of the ventilation equipment corresponding to the target air conditioning control area is called. The real-time operating frequency of the target ventilation equipment is obtained by multiplying the fresh air volume adjustment ratio by the rated operating frequency, and then rounded down to an integer frequency that can be directly accepted by the equipment to form the real-time frequency of the ventilation equipment in the target area.

[0174] Based on the real-time frequency of the ventilation equipment in the target area, the command is sent to each ventilation equipment in the target area, driving the ventilation equipment in the target area to adjust its current operating frequency according to the command requirements.

[0175] Specifically, based on the specified area adjustment scheme generated in the previous step, this scheme includes target air conditioning control areas that need to be adjusted, such as "ZONE_EAST_01F_OFFICE_A," along with their corresponding temperature adjustment deviations and fresh air volume adjustment deviations. The system first extracts the specific adjustment requirements for each target air conditioning control area from this scheme. For example, for the area "ZONE_EAST_01F_OFFICE_A," its temperature adjustment deviation is extracted to be -1.5℃ (meaning the current temperature is 1.5℃ higher than the target), and the fresh air volume adjustment deviation is... The value is +150 cubic meters per hour (indicating that the current fresh air volume is 150 cubic meters per hour lower than the target). Next, the system compares this extracted fresh air volume adjustment deviation value (150 cubic meters per hour in this case) with a preset "maximum fresh air volume adjustment range" for the ventilation equipment in this area. This "maximum fresh air volume adjustment range" refers to the total adjustable range of the ventilation equipment in this area from its minimum design air volume to its maximum design air volume. For example, if the design operating range of this VAV box is 200 cubic meters per hour to 1000 cubic meters per hour, then its maximum fresh air volume adjustment range is... The fresh air volume per hour (m³ / h) is a pre-configured value based on the equipment nameplate parameters, design specifications, and calibrated through performance testing during the system installation and commissioning phase. This value is stored in the system parameter library associated with the equipment in each area. The system then calculates the percentage of the current fresh air volume adjustment deviation (absolute value, i.e., 150 m³ / h) relative to the maximum fresh air volume adjustment range (800 m³ / h). The calculation method is: Percentage = (Absolute value of fresh air volume adjustment deviation / Maximum fresh air volume adjustment range) 100%, that is The calculated result, 18.75%, was recorded and used to generate the fresh air volume adjustment ratio.

[0176] Based on the fresh air volume adjustment ratio generated in the previous step, for example, the ratio obtained for the zone "ZONE_EAST_01F_OFFICE_A" is 18.75% (i.e., 0.1875). The system then calls the "rated operating frequency" of the ventilation equipment corresponding to the target air conditioning control zone. This "rated operating frequency" refers to the operating frequency of the inverter when the ventilation equipment reaches its maximum design output capacity (e.g., maximum design fresh air volume), such as 50 Hz or 60 Hz. This rated frequency value is one of the core design parameters of the ventilation equipment, clearly marked by the equipment manufacturer in its technical manual and entered during system configuration. For example, the rated operating frequency of the associated fresh air supply fan for the zone "ZONE_EAST_01F_OFFICE_A" is 50 Hz. The system then calculates the real-time operating frequency of the target ventilation equipment by multiplying the previously calculated fresh air volume adjustment ratio (0.1875) by this rated operating frequency (50 Hz). That is: Target real-time operating frequency = Fresh air volume adjustment ratio Rated operating frequency = Since frequency converters typically only accept integer or specific precision frequency setting values, the system will round down the calculated frequency value (i.e., take the largest integer not greater than the value) to obtain an integer frequency value that can be directly accepted and executed by the equipment. Therefore, 9.375Hz is rounded down to 9Hz, which is the target operating frequency determined by the system for the ventilation equipment in this area, forming the real-time frequency of the ventilation equipment in the target area.

[0177] Based on the real-time frequency of the ventilation equipment in the target area determined in the previous step, for example, calculating and determining the target real-time operating frequency of 9Hz for the ventilation equipment in area "ZONE_EAST_01F_OFFICE_A", the system sends this specific frequency command value, along with the corresponding target air conditioning control area identifier ("ZONE_EAST_01F_OFFICE_A"), one by one to the corresponding ventilation equipment drive unit in that target area through the building automation system or a direct equipment control network interface. This is usually the frequency converter controller connected to the fan motor. This transmission process follows a predefined communication protocol and data format. After receiving the new operating frequency command (9Hz), the inverter's internal control logic will parse the command and adjust the frequency of the AC power output to the fan motor, thereby changing the motor speed and driving the ventilation equipment (such as fresh air fans or supply air fans) in the target area to operate at the 9Hz frequency required by the command, adjusting its current actual operating frequency to the new target value. The execution of this operation will directly affect the fresh air supply in the area, making it tend to meet the previously calculated adjustment requirements. This sending and driving adjustment process will be executed sequentially for all areas in the "specified area adjustment scheme" that need to change the operating frequency of ventilation equipment.

Claims

1. A centralized air conditioning control management system, characterized in that, The system includes: The environmental perception module acquires real-time concentration readings from the carbon dioxide sensor, establishes the current CO2 concentration value, determines personnel profiles, and generates regional status assessment results. The demand assessment module reads the current value of the indoor PM2.5 sensor based on the regional status assessment results, obtains the indoor particulate matter pollution level, sets the temperature benchmark and fresh air volume benchmark based on the indoor particulate matter pollution level and with reference to the regional status assessment results, calculates the health and comfort gap, and establishes the air conditioning demand intensity. The control decision module determines whether to prioritize adjusting the temperature or the fresh air volume based on the intensity of the air conditioning demand, obtains the control weight corresponding to the priority item, obtains the weight of the core control parameter, formulates the target value of the air conditioning operation parameter based on the weight of the core control parameter and in conjunction with the weather forecast, and establishes the air conditioning parameter adjustment instruction. The zone execution module, based on the air conditioning parameter adjustment command, selects the target air conditioning control zone corresponding to the command, determines the zone adjustment range, obtains the specified zone adjustment scheme, and operates the ventilation equipment operating frequency of the target zone based on the specified zone adjustment scheme.

2. The air conditioning centralized control management system according to claim 1, characterized in that, The steps for obtaining the regional status assessment results are as follows: Based on the real-time concentration readings of the carbon dioxide sensor, the instantaneous CO2 concentration values ​​at each monitoring point are collected, the instantaneous CO2 concentration values ​​are sorted by time series, and the average and highest CO2 concentration values ​​within the last 30 minutes are calculated to obtain the average and highest CO2 concentration values. Calculate the CO2 concentration fluctuation composite factor based on the average CO2 concentration and the highest CO2 concentration. Based on the CO2 concentration fluctuation composite factor, the difference is compared with the personnel density benchmark value in the preset regional functional attributes to determine the activity level of personnel in the region and to determine the personnel profile, thereby generating a regional status assessment result.

3. The air conditioning centralized control management system according to claim 1, characterized in that, The steps for obtaining the indoor particulate matter pollution level are as follows: Based on the regional status assessment results, personnel profiles are extracted from the regional status assessment results, and the corresponding personnel density and activity level are analyzed to determine the current particulate matter pollution sensitivity level of the region, thus forming a particulate matter pollution sensitivity level. Based on the particulate matter pollution sensitivity level, read the current value of the indoor PM2.5 sensor, obtain the instantaneous PM2.5 concentration readings collected by all sensors one by one, sort the instantaneous PM2.5 concentration readings, remove abnormal concentration readings, and select the median of the sorted values ​​as the representative value of indoor PM2.5 to obtain the representative value of indoor PM2.

5. Based on the representative value of indoor PM2.5, and referring to the concentration classification range of the ambient air quality standard, the pollution level of indoor particulate matter pollution is determined, and the pollution level is compared with the particulate matter pollution sensitivity level to obtain the indoor particulate matter pollution level.

4. The air conditioning centralized control management system according to claim 1, characterized in that, The steps for obtaining the air conditioning demand intensity are as follows: Based on the indoor particulate matter pollution level and regional status assessment results, the pollution level classification standard table and the regional functional attribute mapping table are called to match the combination of pollution level and population density, and the temperature benchmark, fresh air volume benchmark and humidity benchmark corresponding to the matched combination are extracted to form the temperature benchmark, fresh air volume benchmark and humidity benchmark. Based on temperature, fresh air volume, and humidity benchmarks, calculate the gap in health and comfort. Based on the aforementioned health and comfort gap, the health and comfort gap is compared with the adjustment demand threshold range, and the corresponding air conditioning demand intensity is divided according to the range in which it is located.

5. The air conditioning centralized control management system according to claim 1, characterized in that, The steps for obtaining the weights of the core control parameters are as follows: Based on the air conditioning demand intensity, a pre-established mapping table of air conditioning demand intensity and adjustment item priority is invoked, and the temperature adjustment priority and fresh air volume adjustment priority corresponding to the air conditioning demand intensity level are compared one by one to determine the adjustment priority under the current demand intensity and form the adjustment priority. Based on the adjustment priority, the corresponding control weight values ​​are extracted from the adjustment priority, and the control weight values ​​of non-priority adjustment items are confirmed based on the control weight values. These are then combined to form the temperature adjustment control weight and the fresh air volume adjustment control weight, generating the core control parameter weights.

6. The air conditioning centralized control management system according to claim 1, characterized in that, The steps for obtaining the air conditioner parameter adjustment command are as follows: Based on the weights of the core control parameters, the temperature regulation control weight and the fresh air volume regulation control weight are extracted from the core control parameter weights. The difference between the temperature regulation control weight and the fresh air volume regulation control weight is calculated. It is determined whether the absolute value of the difference between the two control weights exceeds the set dominant weight threshold. If the absolute value of the difference exceeds the threshold, the control parameter with the largest weight is selected as the dominant control item for air conditioning. Otherwise, the temperature regulation is the dominant control item by default, and the dominant control item for air conditioning is generated. Based on the air conditioning dominant control item, obtain the hourly outdoor temperature forecast data for the next 24 hours, analyze and extract the temperature change rate of adjacent time periods in the hourly temperature forecast data, determine whether each time period belongs to the temperature change period by setting the temperature change rate threshold, and then combine the type of air conditioning dominant control item and the change period to determine the adjustment range of the corresponding air conditioning dominant control item one by one, and accumulate and superimpose the initial operating parameters to generate the target value of the air conditioning operating parameters for 24 hours, thus forming the target value of the air conditioning operating parameters. Based on the target values ​​of the air conditioning operating parameters, and in accordance with the interface standard between the target values ​​of the air conditioning operating parameters and the air conditioning control system, the hourly target temperature values ​​and target fresh air volume values ​​are converted into digital parameter adjustment instructions that can be executed by the air conditioning control system. These instructions are then arranged in order of timestamp and encapsulated into data messages to generate air conditioning parameter adjustment instructions.

7. The air conditioning centralized control management system according to claim 1, characterized in that, The steps for obtaining the adjustment scheme for the specified area are as follows: Based on the air conditioning parameter adjustment instructions, the target air conditioning control area number in each parameter adjustment instruction is extracted, and the area number in the air conditioning control area configuration table is compared one by one to determine the target air conditioning control area that needs to be adjusted. The current temperature, current fresh air volume and current personnel density of each area are recorded to generate a target air conditioning control area information set. Based on the target air conditioning control area information set, calculate the standardized adjustment demand index for each area; Based on the standardized adjustment demand index of each air conditioning control area, it is compared with the set adjustment threshold value to screen out the air conditioning control areas that exceed the adjustment threshold value, and the temperature adjustment deviation and fresh air volume adjustment deviation are recorded respectively to generate the specified area adjustment plan.

8. The air conditioning centralized control management system according to claim 1, characterized in that, Based on the specified area adjustment scheme, the steps for adjusting the operating frequency of ventilation equipment in the target area are as follows: Based on the specified area adjustment scheme, the temperature adjustment deviation and fresh air volume adjustment deviation of each target air conditioning control area are extracted from the specified area adjustment scheme. The fresh air volume adjustment deviation is compared with the preset maximum fresh air volume adjustment range, and the percentage of the fresh air volume adjustment deviation to the maximum adjustment range is calculated to generate the fresh air volume adjustment ratio. Based on the fresh air volume adjustment ratio, the rated operating frequency of the ventilation equipment corresponding to the target air conditioning control area is called. The real-time operating frequency of the target ventilation equipment is obtained by multiplying the fresh air volume adjustment ratio by the rated operating frequency, and then rounded down to an integer frequency that can be directly accepted by the equipment to form the real-time frequency of the ventilation equipment in the target area. Based on the real-time frequency of the ventilation equipment in the target area, the instructions are sent one by one to the ventilation equipment in the target area, driving the ventilation equipment in the target area to adjust its current operating frequency according to the instructions.

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