An intelligent control method for a photovoltaic energy storage direct-drive five-constant system

Abstract

This invention relates to the field of intelligent control, and more particularly to an intelligent control method for a photovoltaic energy storage direct-drive five-constant system. The invention monitors environmental data from several spatial areas to extract the environmental state characteristics of each area; combines these environmental state characteristics with fluctuations in fan noise intensity to analyze the environmental quality characterization values ​​of the spatial areas, thus marking them; in response to the presence of marked spatial areas, the invention assesses and analyzes the environment of those areas to determine the environmental quality degradation level of occupied spaces; and based on this degradation level, it adaptively regulates the control equipment within the occupied spaces. This invention improves the accuracy and targeting of environmental control while optimizing human comfort, aligning with the core experience requirements of a five-constant system.

Description

Technical Field

[0001] This invention relates to the field of intelligent control, and in particular to an intelligent control method for a photovoltaic energy storage direct-drive five-constant system. Background Technology

[0002] The five constant systems (temperature, humidity, air cleanliness, noise, and fresh air volume) are an important technical means for indoor environmental control, enabling constant regulation of indoor temperature, humidity, air cleanliness, noise, and fresh air volume. They are widely used in the creation of indoor living environments in civil buildings, becoming a key facility for improving the comfort of residents. Photovoltaic energy storage direct-drive technology relies on photovoltaic modules to convert light energy into electrical energy, and combines this with energy storage equipment to store and release electrical energy on demand. This provides a clean and autonomous energy supply for the five constant systems, aligning with the development trend of energy conservation and environmental protection. The combination of these two technologies represents an important development direction in the field of intelligent indoor environmental control.

[0003] Meanwhile, the application of intelligent control technology in fields such as HVAC and environmental control is becoming increasingly mature. By using various sensors to achieve real-time monitoring of environmental data and combining algorithm models to complete data analysis and processing and precise control of equipment, the automation and intelligence level of environmental control systems can be effectively improved. This provides technical support for the efficient operation of photovoltaic energy storage direct-drive five constant systems and also promotes the development of five constant systems towards scenario-based and refined control.

[0004] Chinese Patent Application Publication No. CN120947157A discloses a multi-objective adaptive optimization method and system for a windless radiant five-constant air conditioning system, belonging to the field of digital monitoring technology. It establishes a population density thermal and humidity load model and a building thermal and humidity response RC network model, combined with long short-term memory neural network training, to output predicted values ​​of the humidity load increment rate and temperature rise rate. It uses a non-dominated sorting genetic algorithm to dynamically adjust the temperature and humidity control weights, generating the optimal parameter combination, and optimizes LSTM parameters through incremental learning. It deploys edge computing nodes, leveraging a tensor inference engine and a field-programmable gate array to accelerate LSTM inference and NSGA-II non-dominated sorting operations. It adopts a dual-timescale strategy: during load fluctuations, the fast response layer directly outputs control quantities; after stabilization, a deep optimization layer is activated to simultaneously optimize energy efficiency and comfort, saving energy. This invention achieves real-time response in scenarios with sudden increases in population, compressing the algorithm time to match the time scale of sudden population increases, and simultaneously improving energy efficiency and comfort.

[0005] However, the following problems still exist in the existing technology. The equipment's operating status is poorly matched with the actual environmental requirements of the space, and its adjustment flexibility and timeliness are lacking, failing to take into account the comfort of human living. Summary of the Invention

[0006] To address this, the present invention provides an intelligent control method for a photovoltaic energy storage direct-drive five-constant system, which overcomes the problems in the prior art where the matching degree between the equipment operating status and the actual environmental requirements of the space is low, the regulation flexibility and timeliness are poor, and the comfort of human living cannot be taken into account.

[0007] To achieve the above objectives, the present invention provides an intelligent control method for a photovoltaic energy storage direct-drive five-constant system, comprising: Environmental data from several spatial regions are monitored to extract environmental state characteristics of each spatial region, including carbon dioxide concentration and thermal humidity deviation value. By combining the environmental characteristics and the fluctuation of the fan noise intensity, the environmental quality characterization value of the spatial area is analyzed to mark the spatial area; In response to the marking of a spatial region, an environmental assessment and analysis of the spatial region is performed, including: The perceived temperature characteristics of human bodies in occupied spaces are used to determine whether the environment meets the comfort benchmark. Based on the air age difference between the occupied space area and the adjacent space area during the sleep time domain, and the change in the location of the air stagnation area in the occupied space area, the environmental circulation characterization value of the occupied space area is analyzed, and the environmental quality weakening level of the occupied space area is marked. Based on the aforementioned environmental quality degradation level, the control equipment in the occupied space area is adjusted, including, Identify the airflow path coverage area and the directional proportion of non-concentrated coverage areas corresponding to the regulating device, calculate environmental coordination characterization parameters, and determine the regulating force for the regulating device. Send an environmental optimization reminder signal; The human body's perceived temperature characteristics include the uniformity of heat distribution and the area of ​​concentrated heat.

[0008] Furthermore, the process of analyzing the environmental quality characterization values ​​of the aforementioned spatial region includes: The sum of the ratio of carbon dioxide concentration to carbon dioxide concentration threshold and the ratio of thermal humidity deviation value to thermal humidity deviation threshold is used as the first environmental quality characteristic. The ratio of the fluctuation of fan noise intensity to the threshold of fan noise intensity is used as the second environmental quality characteristic. The environmental quality characterization value is determined by weighted summation of the first environmental quality characteristic and the second environmental quality characteristic.

[0009] Further, the spatial region is marked, including: If the environmental quality characterization value of a spatial region is greater than or equal to the environmental quality characterization threshold, then the spatial region is marked.

[0010] Further, determining whether environmental comfort standards are met includes: If the heat distribution uniformity is greater than the heat distribution uniformity threshold and the heat concentration area is less than the heat concentration area threshold, then it is determined that the environmental comfort benchmark is met.

[0011] Furthermore, the process of analyzing the environmental circulation characteristics of the occupied space area includes: The ratio of the air age difference threshold to the air age difference of the occupied space area and the adjacent space area is used as the first environmental circulation characteristic. The ratio of the change in the position of the air stagnation area in the occupied space to the threshold value of the change in the position of the air stagnation area is used as the second environmental circulation characteristic. The environmental circulation characteristic value is determined by weighted summation of the first environmental circulation characteristic and the second environmental circulation characteristic.

[0012] Furthermore, the environmental quality degradation level of the aforementioned occupied space area is indicated, including: If the environmental circulation characterization value of a populated space area is greater than or equal to the environmental circulation characterization threshold, then the populated space area will be marked as having a low environmental quality weakening level. If the environmental circulation characterization value of a populated area is less than the environmental circulation characterization threshold, the populated area will be marked as a high-level deterioration of environmental quality.

[0013] Furthermore, based on the aforementioned environmental quality degradation level, the regulating equipment is adjusted, including: If the environmental quality degradation level is low, then identify the spatial area covered by the airflow path in the occupied space area and the directional proportion of the non-concentrated coverage area, calculate the environmental coordination characterization parameters, and determine the adjustment intensity for the adjustment device. If the environmental quality degradation level is high degradation level, an environmental optimization reminder signal will be issued.

[0014] Furthermore, the process of calculating environmental coordination characterization parameters includes: The ratio of the airflow path coverage area to the airflow path coverage area threshold is used as the first environmental coordination feature. The ratio of the azimuth proportion threshold to the azimuth proportion of non-concentrated coverage areas is used as the second environmental coordination feature. The first environmental coordination feature and the second environmental coordination feature are weighted and summed to determine the environmental coordination characterization parameter.

[0015] Further, determining the adjustment force for the adjustment device includes: The regulatory intensity is negatively correlated with the environmental coordination characterization parameters.

[0016] Furthermore, it also includes adjusting the air supply angle of the regulating device, wherein the air supply angle corresponds to the non-concentrated coverage area.

[0017] Compared with existing technologies, this invention monitors environmental data from several spatial areas to extract the environmental state characteristics of each area; combines these environmental state characteristics with fluctuations in fan noise intensity to analyze the environmental quality characterization values ​​of the spatial areas, thus marking them; in response to the presence of marked spatial areas, the invention assesses and analyzes the environment of those areas to determine the environmental quality degradation level of occupied spaces; and based on this degradation level, it adaptively adjusts the control equipment within the occupied spaces. This invention improves the accuracy and targeting of environmental control while optimizing human living comfort, aligning with the core experience requirements of a five-constant system.

[0018] In particular, in practice, nighttime is the period when the five constant systems are used most frequently and when human sensitivity to temperature is highest. Targeted monitoring makes environmental data more closely match actual usage needs. Based on this, this invention constructs a three-in-one quantitative judgment system based on three indicators for indoor environmental quality, human comfort, and equipment operation status. In terms of air quality, carbon dioxide concentration reflects the freshness of the air and ventilation efficiency in the space. Human respiration is the main source of carbon dioxide. The concentration value can quantify whether there is a risk of oxygen deficiency in the space. Generally, a concentration exceeding 1000 ppm is considered to cause drowsiness and is a core parameter for testing the effectiveness of fresh air systems or air conditioning ventilation functions. If the concentration remains high, it indicates that the current ventilation volume cannot meet the needs of the population. In terms of thermal comfort, the interaction between temperature and humidity, i.e., the thermal-humidity deviation value, is calculated to quantify the actual degree of warmth or coldness felt by the human body, more realistically reflecting the actual comfort state of the temperature and humidity environment in the space. In terms of quiet and safe operation, the fluctuation of fan noise intensity quantifies whether the fan is operating stably. Moreover, noise fluctuations, such as sudden increases and decreases in volume, are more disruptive to sleep than continuous background noise. Furthermore, this indicator can quantify the smoothness of the acoustic environment, thereby reflecting the operating conditions of the wind turbine equipment and the stability of the indoor acoustic environment. Further, it analyzes the environmental quality characterization values ​​for specific spatial areas to represent the comprehensive compliance of core indicators of the living environment in those areas, the overall level of human comfort, and the impact of equipment operation on environmental quality, providing data support for subsequent labeling of the spatial areas. This invention improves the targeting and accuracy of environmental monitoring, achieving targeted monitoring, avoiding indiscriminate operation of equipment across the entire area, and reducing the ineffective consumption of photovoltaic energy storage.

[0019] In particular, for nighttime sleep scenarios, this invention conducts a refined and scenario-based assessment from two dimensions: human comfort and air circulation quality. Focusing on actual human sensations, it incorporates human perceived temperature characteristics to quantify the spatial distribution of the thermal environment and the actual thermal sensations experienced by people in occupied spaces. From the perspective of overall thermal distribution uniformity, it measures the overall temperature difference in the space through the uniformity of heat distribution. A higher value indicates a smaller temperature difference between different areas of the space and a more balanced heat distribution; a lower value indicates a significant regional temperature difference, such as a hot head and cold feet, a cold area near the window and a warm center, or a large temperature difference between the head and foot of the bed in the bedroom, indicating an overall imbalance in the thermal environment. In reality, human discomfort with the thermal environment often stems from the change in perceived temperature caused by spatial temperature differences, such as suddenly feeling cold / hot when moving from the living room to the bedroom. This indicator can quantify this "consistency of perceived temperature." Higher uniformity means that the thermal sensations are more similar across any location in the space, resulting in stronger overall comfort, thus reflecting whether the temperature in occupied spaces is in a uniform and stable state. This invention quantifies the actual coverage of local thermal anomalies and their impact on human comfort by relying on the area of ​​concentrated heat. In reality, human activity within a space is confined to a fixed range, such as the bed area during sleep or the sofa area for prolonged sitting. If the concentrated heat area appears in the main activity area, even with relatively good overall uniformity, it will directly lead to localized discomfort. This indicator quantifies the area of ​​the anomaly to determine its impact on the core living area. The larger the area, the wider the impact, and the higher the probability and degree of human discomfort. Therefore, this invention combines these two features to achieve precise quantification of the overall and local thermal environment and human comfort in occupied spaces. This makes the determination of environmental comfort benchmarks more ergonomic, accurately reflecting the matching degree between the spatial thermal environment and human comfort, and significantly improving the human experience in occupied spaces at night, especially in sleeping environments.

[0020] In particular, this invention focuses on designing air circulation assessment indicators for the sleep time domain, precisely adapting to the special environmental needs of nighttime sleep. Addressing the high demand for fresh air and a stuffy environment during sleep, it introduces an air age difference index between the occupied space and adjacent spaces. This quantifies the difference in air freshness between the two areas, assesses the environmental impact of adjacent spaces on the occupied sleep space, identifies whether polluted air from adjacent spaces diffuses into the sleep space, and reduces the risk of air freshness issues in the sleep area. A smaller index value indicates a closer similarity in air residence time and a smaller difference in air freshness between the two areas; a larger value indicates a more significant difference in air freshness. If the air age of the adjacent space is older, there is a gradient dynamic for polluted air from the adjacent space to diffuse into the occupied sleep space, continuously reducing the air freshness of the occupied space. Simultaneously, the dynamic changes in the air stagnation area within the sleep area and the overall activity of air circulation in the occupied space are quantified by the change in the position of the air stagnation area. The larger the value of this indicator, the more frequently the location of the stagnation zone moves and the more significant the area change, indicating that the air in the space is in a state of continuous micro-flow, and the stagnation zone has no fixed landing point. The smaller the value, the more likely the stagnation zone is fixed in a certain location for a long time, such as a corner of the bedroom or next to the bed, forming a fixed ventilation dead corner, where the air cannot be effectively replaced. Furthermore, it can reflect whether there are long-term fixed air stagnation zones in the space, such as those prone to odor growth and stuffiness, making the air circulation assessment more aligned with the specific needs of sleep scenarios for "no stagnation, micro-flow". Therefore, by deeply integrating the above two characteristics, an environmental circulation characterization value is formed to comprehensively assess the environmental quality of occupied spaces, characterizing the ability to maintain air freshness and the effect of cross-contamination prevention within occupied spaces. The environmental circulation characterization value is used as the basis for marking the level of environmental quality degradation, providing a clear quantitative basis for subsequent control and measurement. This invention optimizes the environmental adaptability of sleep scenarios. By relying on the change in the location of air retention areas and the time dimension design of sleep time segments, the environmental assessment is upgraded from static instantaneous data judgment to dynamic process state analysis. It can accurately capture the dynamic changes of the spatial environment during sleep, making the assessment results more consistent with the actual changes in the nighttime environment and enhancing the dynamism and comprehensiveness of the environmental assessment.

[0021] In particular, this invention employs a dual-indicator quantification approach to the airflow effect of regulating equipment within occupied spaces, characterizing the actual distribution of airflow within these spaces. From an overall coverage perspective, the airflow path coverage area quantifies the overall airflow range and effective service capability of the regulating equipment within the occupied space. The size of the coverage area reflects whether the current operating conditions of the regulating equipment can meet the overall airflow needs of the occupied space. If the coverage area is too small, it indicates insufficient operating power of the regulating equipment, and the airflow cannot reach most areas of the space, thus reflecting the overall coverage efficiency and service capability of the regulating equipment for the target space. From the perspective of the distribution of locally weak areas, the proportion of non-concentrated coverage areas quantifies the overall impact of airflow-weak areas within the occupied space. The proportion of areas not effectively covered by airflow in the target space reflects the degree of impact of airflow distribution on perceived comfort. A higher proportion indicates more severe unevenness in airflow distribution within the space, and a larger range of localized discomfort. Furthermore, the magnitude and orientation of this indicator characteristic reflect the rationality of the air supply angle and outlet position of the regulating equipment. If a high percentage of non-concentrated coverage areas consistently appear in a certain direction, it indicates a directional deviation in the airflow output of the equipment, requiring targeted adjustments to the air supply angle to compensate for insufficient airflow in that area. Therefore, this invention quantitatively correlates the operating status of the regulating equipment with the environmental needs of occupied spaces, calculating environmental coordination characterization parameters to represent the degree of matching and coordination between the airflow operating status of the regulating equipment and the environmental regulation needs of occupied spaces, providing data support for determining the adjustment intensity of the regulating equipment. This invention focuses on directional regulation of occupied spaces, accurately matching human needs, improving the effectiveness of environmental regulation, and the adaptability of equipment operation to the spatial environment. It adjusts the equipment's operating intensity as needed, maximizing energy consumption reduction and meeting the core energy-saving requirements of photovoltaic energy storage direct-drive systems. Attached Figure Description

[0022] Figure 1 A schematic diagram illustrating the steps of an intelligent control method for a photovoltaic energy storage direct-drive five-constant system according to an embodiment of the invention; Figure 2 A logic decision diagram for marking spatial regions in an embodiment of the invention; Figure 3 A logic diagram for determining whether an environmental comfort standard is met in an embodiment of the invention; Figure 4 A logic diagram for marking the environmental quality degradation level of occupied spaces in an embodiment of the invention. Detailed Implementation

[0023] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0024] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0025] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0026] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0027] Please see Figure 1 The diagram illustrates the steps of an intelligent control method for a photovoltaic energy storage direct-drive five-constant system according to an embodiment of the present invention. The intelligent control method for the photovoltaic energy storage direct-drive five-constant system according to an embodiment of the present invention includes: Step S1: Monitor environmental data of several spatial regions to extract environmental state characteristics of each spatial region, including carbon dioxide concentration and thermal humidity deviation value. Step S2: Combining the environmental state characteristics and the fluctuation of the fan noise intensity, analyze the environmental quality characterization value of the spatial area to mark the spatial area; Step S3, in response to the presence of a marked spatial region, performs an environmental assessment and analysis of the spatial region, including, The perceived temperature characteristics of human bodies in occupied spaces are used to determine whether the environment meets the comfort benchmark. Based on the air age difference between the occupied space area and the adjacent space area during the sleep time domain, and the change in the location of the air stagnation area in the occupied space area, the environmental circulation characterization value of the occupied space area is analyzed, and the environmental quality weakening level of the occupied space area is marked. Step S4, based on the environmental quality degradation level, adjust the control equipment in the occupied space area, including, Identify the airflow path coverage area and the directional proportion of non-concentrated coverage areas corresponding to the regulating device, calculate environmental coordination characterization parameters, and determine the regulating force for the regulating device. Send an environmental optimization reminder signal; The human body's perceived temperature characteristics include the uniformity of heat distribution and the area of ​​concentrated heat.

[0028] Specifically, the environmental data includes environmental state characteristics, fan noise intensity fluctuations, human body temperature characteristics, air age difference between occupied and adjacent spaces, changes in the location of air stagnation areas in occupied spaces, airflow path coverage area, and the directional proportion of non-concentrated coverage areas.

[0029] Specifically, there are no specific limitations on the methods for collecting environmental characteristics; they can be collected by deploying infrared carbon dioxide sensors and integrated temperature and humidity sensors.

[0030] Specifically, the thermal humidity deviation value refers to the quantified deviation between the actual temperature and humidity combination and the human body's comfortable temperature and humidity reference value. The absolute temperature difference between the actual temperature and the comfort reference temperature value, and the absolute humidity difference between the actual humidity and the comfort reference humidity value are calculated respectively. Then, a first ratio of the absolute temperature difference to the reference temperature value and a second ratio of the absolute humidity difference to the reference humidity value are determined. The sum of the first ratio and the second ratio is taken as the thermal humidity deviation value. The aforementioned human comfort temperature and humidity benchmark values ​​can be determined according to relevant standards, such as the "Design Code for Heating, Ventilation and Air Conditioning of Civil Buildings", which sets human comfort temperature and humidity benchmark values ​​(summer: 26℃, 60%RH; winter: 22℃, 50%RH; transition season: 24℃, 55%RH).

[0031] Specifically, there is no specific limitation on the method of collecting the noise intensity fluctuation of the fan. A piezoelectric sound level meter or noise sensor is deployed next to the air outlet of the fan. Then, the sensor can be controlled to collect the real-time noise sound pressure level dB value once per second. The noise data for 30 consecutive seconds is taken as a statistical window, and the coefficient of variation of the noise value within the window is calculated, which is the noise intensity fluctuation of the fan.

[0032] Specifically, there are no specific limitations on the method of collecting and acquiring human body temperature characteristics; it can be determined by combining a distributed temperature measuring point array with an infrared thermal imager. Specifically, based on temperature data from multiple points within the space, a temperature variation coefficient is calculated, and this coefficient is normalized to obtain the heat distribution uniformity. For the area of ​​concentrated heat, a pre-set thermal anomaly temperature threshold is established; for example, the deviation from the comfort reference temperature value by ±2℃ is used as the thermal anomaly temperature threshold. Then, an image recognition algorithm is used to extract the thermal anomaly temperature region from the thermal imaging image to determine the area of ​​concentrated heat.

[0033] Specifically, for the air age difference between the occupied space area and the adjacent space area, the tracer gas method or CFD simulation coupled with real-time sensor data can be used to calculate the average air age between the occupied space and the adjacent space. The difference between the two is the air age difference. This is existing technology and will not be elaborated further.

[0034] Specifically, the method for collecting and acquiring the changes in the position of air-trapped areas in occupied spaces is not specifically limited. First, air-trapped areas are identified. Miniature wind speed sensors can be deployed at multiple points within the occupied space. In this embodiment, areas with wind speeds <0.05 m / s are identified as air-trapped areas. Simultaneously, areas with air ages >30 minutes are used to further verify air-trapped areas, and the intersection of these two methods determines the air-trapped area. Combining data from an infrared thermal imager and a wind speed measurement array, a two-dimensional contour and center coordinates of the air-trapped area are generated. A statistical time window is set, such as 10 minutes, and the average displacement of the center coordinates or the rate of change in contour overlap of the air-trapped area at each time point within the window is calculated as the change in position. Of course, those skilled in the art can also use other methods to collect and acquire the changes in the position of air-trapped areas, which will not be elaborated upon here.

[0035] Specifically, the method for acquiring the airflow path coverage area is not specifically limited. It can combine an array of wind speed sensors and a laser airflow velocimeter to collect the effective wind speed at each measuring point in the space when the regulating equipment delivers air. Using an image recognition algorithm, the effective wind speed measuring points are mapped onto a spatial CAD plan to generate the outline of the area effectively covered by the airflow. The physical area of ​​the outline is then calculated, which is the airflow path coverage area. In this embodiment, the effective wind speed is defined as 0.05~0.3m / s, and the effective airflow coverage area is within this wind speed range.

[0036] Areas with effective wind speeds <0.05 m / s are defined as areas where airflow is not concentrated, and the area of ​​such areas is determined. The ratio of the area of ​​non-concentrated coverage to the total physical area of ​​a certain direction is then used as the directional proportion of the non-concentrated coverage area.

[0037] Specifically, there is no specific limitation on how the sleep time range is determined. It can be determined by the system through a combination of clock timing, detection of human presence and behavior, and user mode triggering. For example, the system has a built-in real-time clock (RTC) with a default sleep period of 22:00 to 06:00 the next day. The presence of a human body and its still lying position are detected by millimeter-wave radar, human infrared sensor, or micro-motion sensor. When the system time is between 22:00 and 06:00 the next day and someone in the space remains still for more than 30 minutes, or the user manually turns on sleep mode, or the system matches the sleep time period through self-learning of sleep schedule, the system determines that it has entered the sleep time range.

[0038] Specifically, the process of analyzing the environmental quality characterization values ​​of the aforementioned spatial region includes: The sum of the ratio of carbon dioxide concentration to carbon dioxide concentration threshold and the ratio of thermal humidity deviation value to thermal humidity deviation threshold is used as the first environmental quality characteristic. The ratio of the fluctuation of fan noise intensity to the threshold of fan noise intensity is used as the second environmental quality characteristic. The environmental quality characterization value is determined by weighted summation of the first environmental quality characteristic and the second environmental quality characteristic.

[0039] Specifically, carbon dioxide concentration reflects the efficiency of space ventilation and the risk of oxygen deficiency. Excessive concentration can lead to drowsiness and dizziness, and has long-term health effects, making it a core indicator for measuring indoor environmental quality. Furthermore, the thermal humidity deviation comprehensively characterizes the degree of deviation between the temperature and humidity combination and the human comfort zone, directly determining the perceived heat, and is the primary target for regulation in a five-constant system. These two characteristics together constitute the basic quality of the living environment, directly affecting users' physiological sensations and long-term living experience. The fluctuation in fan noise intensity reflects the stability of equipment operation and the comfort of the acoustic environment. Although fluctuating noise is more likely to disrupt sleep than constant noise, its impact is usually limited to the auditory level and does not involve fundamental health risks or thermal comfort issues; it is an auxiliary indicator of the acoustic environment, with a relatively limited impact on overall environmental quality. Therefore, a higher weighting coefficient is assigned to the first environmental quality characteristic, which can be selected within the range of 0.6 to 0.8; in this embodiment, it is set to 0.7. Correspondingly, the weighting coefficient for the second environmental quality characteristic can be selected within the range of 0.2 to 0.4; in this embodiment, it is set to 0.3. Specific values ​​can be adjusted by those skilled in the art according to the user's sensitivity to the acoustic environment.

[0040] In this embodiment, the purpose of setting thresholds for carbon dioxide concentration, thermal humidity deviation, and fan noise intensity fluctuation is to characterize situations where the living environment in a given space is poorly compliant, the overall comfort level is low, and the equipment operation is poorly adapted to the environment. This is achieved by acquiring historical environmental data for the corresponding space area and then retrieving data on carbon dioxide concentration, thermal humidity deviation, and fan noise intensity fluctuation. The mean carbon dioxide concentration, mean thermal humidity deviation, and mean fan noise intensity fluctuation are calculated. Based on the purpose of setting these three thresholds, the carbon dioxide concentration threshold is determined as the product of the mean carbon dioxide concentration and the concentration deviation coefficient; the thermal humidity deviation threshold is determined as the product of the mean thermal humidity deviation and the thermal humidity deviation coefficient; and the fan noise intensity fluctuation threshold is determined as the product of the mean fan noise intensity fluctuation and the fluctuation deviation coefficient.

[0041] Specifically, considering that carbon dioxide concentration, thermal humidity deviation, and fan noise intensity all experience normal short-term fluctuations in actual living environments due to factors such as foot traffic, opening and closing of doors and windows, and equipment start-up and shutdown, setting thresholds too low would lead to many normal spatial areas being incorrectly marked, causing unnecessary subsequent assessments and adjustments, wasting energy, and affecting user experience. Therefore, each threshold is set to an appropriate multiple of the historical average of the corresponding characteristic quantity, reserving an error tolerance for normal fluctuations to reduce sensitivity, and triggering marking only when quality deteriorates significantly.

[0042] The concentration deviation coefficient is selected within the range [1.1, 1.15]. A coefficient slightly higher than the mean can filter out occasional small increases. In practice, a value of 1.1 is preferred, which can eliminate normal fluctuations while maintaining sensitivity to sustained high concentrations.

[0043] The thermal and humidity deviation coefficient is selected within the range [1.2, 1.3], using a larger amplification factor to distinguish between normal diurnal or seasonal variations and true thermal and humidity discomfort. In practice, a value of 1.2 is preferred, balancing accuracy and timeliness.

[0044] The fluctuation deviation coefficient is selected within the range [1.2, 1.4]. A larger amplification factor can eliminate short-term random fluctuations, such as those occurring at the moment of equipment startup. In practice, a value of 1.2 is preferred to balance false alarms and missed alarms.

[0045] The selection of the above-mentioned preferred values ​​achieves a good balance between recognizing real-world environmental degradation and avoiding overreaction. Of course, those skilled in the art can readjust the value range based on the stability of the actual environment, sensor accuracy, and sensitivity to comfort, or they can adjust the coefficients within a given range.

[0046] Specifically, in practice, nighttime is the period when the five constant systems are used most frequently and when human sensitivity to temperature is highest. Targeted monitoring makes environmental data more closely match actual usage needs. Based on this, this invention constructs a three-in-one quantitative judgment system for indoor environmental quality, human comfort, and equipment operation status, relying on three indicators. In terms of air quality, carbon dioxide concentration reflects the freshness of the air and ventilation efficiency in the space. Human respiration is the main source of carbon dioxide. The concentration value can quantify whether there is a risk of oxygen deficiency in the space. Generally, a concentration exceeding 1000 ppm is considered to cause drowsiness and is a core parameter for testing the effectiveness of fresh air systems or air conditioning ventilation functions. If the concentration remains high, it indicates that the current ventilation volume cannot meet the needs of the population. In terms of thermal comfort, the interaction between temperature and humidity, i.e., the thermal-humidity deviation value, is calculated to quantify the actual degree of warmth or coldness felt by the human body, more realistically reflecting the actual comfort state of the temperature and humidity environment in the space. In terms of quiet and safe operation, the fluctuation of fan noise intensity quantifies whether the fan is operating stably. Furthermore, noise fluctuations, such as sudden increases and decreases in volume, are more disruptive to sleep than continuous background noise. Furthermore, this indicator can quantify the smoothness of the acoustic environment, thereby reflecting the operating conditions of the wind turbine equipment and the stability of the indoor acoustic environment. Further, it analyzes the environmental quality characterization values ​​for specific spatial areas to represent the comprehensive compliance of core indicators of the living environment in those areas, the overall level of human comfort, and the impact of equipment operation on environmental quality, providing data support for subsequent labeling of the spatial areas. This invention improves the targeting and accuracy of environmental monitoring, achieving targeted monitoring, avoiding indiscriminate operation of equipment across the entire area, and reducing the ineffective consumption of photovoltaic energy storage.

[0047] Specifically, please refer to Figure 2 As shown, it is a logic decision diagram for marking spatial regions according to an embodiment of the present invention. Marking the spatial regions includes: If the environmental quality characterization value of a spatial region is greater than or equal to the environmental quality characterization threshold, then the spatial region is marked. If the environmental quality characterization value of a spatial region is less than the environmental quality characterization threshold, then there is no need to mark the spatial region.

[0048] To determine the environmental quality characterization threshold, historical operational data from the same spatial area is used to select time periods with acceptable environmental quality that do not require labeling. The environmental quality characterization values ​​for each time period are calculated, and the mean q and standard deviation h of the sequence are obtained. The sum of the product of the standard deviation h and the sensitivity coefficient k1 and the mean q is used as the environmental quality characterization threshold. Furthermore, the environmental quality characterization threshold should be dynamically updated according to seasonal changes or usage habits to adapt to operating condition drift. Simultaneously, the environmental quality characterization threshold should be coordinated with the carbon dioxide concentration threshold, thermal humidity deviation threshold, and fan noise intensity fluctuation threshold, and can be iteratively optimized by verifying the mislabeling ratio under acceptable operating conditions.

[0049] The sensitivity coefficient k1 can be selected within the range [1.0, 2.0] based on the tolerance for missed detection of environmental quality deterioration; for example, k1 = 1.5. If sufficient historical data is available, the 90th percentile can also be used as the threshold.

[0050] Specifically, please refer to Figure 3 As shown, this is a logic diagram for determining whether an environmental comfort benchmark is met according to an embodiment of the present invention. The determination of whether an environmental comfort benchmark is met includes: If the heat distribution uniformity is greater than the heat distribution uniformity threshold and the heat concentration area is less than the heat concentration area threshold, then it is determined that the environmental comfort benchmark is met.

[0051] In this embodiment, the purpose of setting the heat distribution uniformity threshold and the heat concentration area threshold is to characterize situations where the spatial thermal environment is poorly matched with human comfort. This is achieved by acquiring historical environmental data for the corresponding spatial region and retrieving the heat distribution uniformity data and heat concentration area data for the occupied spatial region. The mean heat distribution uniformity and the mean heat concentration area are then calculated. Based on the purpose of setting these two thresholds, the heat distribution uniformity threshold is determined as the product of the mean heat distribution uniformity and the uniformity deviation coefficient, and the heat concentration area threshold is determined as the product of the mean heat concentration area and the concentration deviation coefficient.

[0052] Specifically, to avoid misjudging discomfort due to normal temperature fluctuations, such as intermittent air conditioning, short-term opening of doors and windows, or temporary thermal anomalies caused by localized small heat sources, such as lamps and electrical appliances, this embodiment shifts the threshold towards "not easily meeting comfort conditions," that is, increasing the threshold for positive indicators and decreasing the threshold for negative indicators, thereby reducing sensitivity and allowing a certain degree of normal fluctuations.

[0053] The uniformity deviation coefficient is selected within the range [1.1, 1.3]. The heat distribution uniformity fluctuates little in a normal indoor environment. A coefficient slightly higher than the average value can eliminate accidental temperature differences. It is only considered comfortable when the overall thermal environment is very uniform. In practice, a value of 1.1 is preferred.

[0054] The concentration deviation coefficient is selected within the range of [0.9, 0.95]. The area of ​​heat concentration may temporarily increase due to daily activities. A coefficient slightly lower than the mean can accommodate these common situations. Comfort is only determined when there is no obvious thermal anomaly. In practice, 0.9 is preferred.

[0055] The selection of the above-mentioned optimal values ​​achieves a good balance between effectively filtering normal fluctuations and accurately identifying mismatches in the actual thermal environment, taking into account both the reliability of comfort identification and system stability. Of course, those skilled in the art can readjust the value range according to the room's thermal insulation performance, the patterns of human activity, and the requirements for comfort, or they can adjust the coefficients within a given range.

[0056] Specifically, for nighttime sleep scenarios, this invention conducts a refined, scenario-based assessment from two dimensions: human comfort and air circulation quality. Focusing on actual human sensations, it incorporates human perceived temperature characteristics to quantify the spatial distribution of the thermal environment and the actual thermal sensations experienced by people in occupied spaces. From the perspective of overall thermal distribution uniformity, it measures the overall temperature difference within the space through the uniformity of heat distribution. A higher value indicates a smaller temperature difference between different areas of the space and a more balanced heat distribution; a lower value indicates significant regional temperature differences, such as a hot head and cold feet, a cold area near the window and a warm center, or a large temperature difference between the head and foot of the bed in the bedroom, indicating an overall imbalance in the thermal environment. In reality, human discomfort with the thermal environment often stems from the shift in perceived temperature caused by spatial temperature differences, such as suddenly feeling cold / hot when moving from the living room to the bedroom. This indicator can quantify this "consistency of sensation." Higher uniformity means that the thermal sensations are more similar across any location within the space, resulting in greater overall comfort and reflecting whether the temperature in occupied spaces is uniform and stable. This invention quantifies the actual coverage of local thermal anomalies and their impact on human comfort by relying on the area of ​​concentrated heat. In reality, human activity within a space is confined to a fixed range, such as the bed area during sleep or the sofa area for prolonged sitting. If the concentrated heat area appears in the main activity area, even with relatively good overall uniformity, it will directly lead to localized discomfort. This indicator quantifies the area of ​​the anomaly to determine its impact on the core living area. The larger the area, the wider the impact, and the higher the probability and degree of human discomfort. Therefore, this invention combines these two features to achieve precise quantification of the overall and local thermal environment and human comfort in occupied spaces. This makes the determination of environmental comfort benchmarks more ergonomic, accurately reflecting the matching degree between the spatial thermal environment and human comfort, and significantly improving the human experience in occupied spaces at night, especially in sleeping environments.

[0057] Specifically, the process of analyzing the environmental circulation characteristics of the occupied space includes: The ratio of the air age difference threshold to the air age difference of the occupied space area and the adjacent space area is used as the first environmental circulation characteristic. The ratio of the change in the position of the air stagnation area in the occupied space to the threshold value of the change in the position of the air stagnation area is used as the second environmental circulation characteristic. The environmental circulation characteristic value is determined by weighted summation of the first environmental circulation characteristic and the second environmental circulation characteristic.

[0058] Specifically, the air age difference between occupied and adjacent spaces reflects the effectiveness of environmental isolation between areas and is fundamental to ensuring a continuous supply of clean fresh air to the sleeping area. Any abnormality can affect respiratory health and sleep quality. It quantifies the difference in air renewal time between occupied and adjacent spaces. If the air age in adjacent spaces is older, it indicates a gradient dynamic for polluted air to diffuse into the sleeping area, continuously reducing the air freshness of the occupied space. The change in the location of air stagnation areas within occupied spaces measures the spatiotemporal activity of these stagnation areas. Large changes indicate that the air is in a state of micro-flow, making it difficult to form fixed dead zones; small changes indicate the existence of long-term stagnation areas where local air is not effectively replaced. This is a localized, detailed indicator with a relatively limited impact, such as corners near the bed, which can be improved by adjusting the air supply locally. Its threat to overall air circulation is lower than that of cross-contamination between areas. In summary, considering that air age difference directly reflects the risk of polluted air diffusion from adjacent spaces, it determines the overall ability of occupied spaces to maintain air freshness. The change in the location of the air stagnation area only reflects the dynamic characteristics of local ventilation dead zones, and its impact on overall environmental quality is relatively limited. Therefore, a higher weighting coefficient is assigned to the first environmental circulation characteristic, which can be selected in the range of 0.6 to 0.8; in this embodiment, it is set to 0.7. Correspondingly, the weighting coefficient of the second environmental circulation characteristic can be selected in the range of 0.2 to 0.4; in this embodiment, it is set to 0.3. Those skilled in the art can adjust the specific values ​​according to the actual apartment layout and the user's sensitivity to local ventilation.

[0059] In this embodiment, the purpose of setting the air age difference threshold and the air stagnation area position change threshold is to characterize situations where the environmental quality of occupied spaces is poor, the ability to maintain air freshness is low, and the risk of cross-contamination barrier failure is high. This is achieved by acquiring historical environmental data for the corresponding space area, and then retrieving air age difference data for the occupied space area and adjacent space areas within the sleep time domain, as well as air stagnation area position change data for the corresponding occupied space area. The mean thermal air age difference and the mean air stagnation area position change are calculated. Based on the purpose of setting the above two thresholds, the air age difference threshold is determined as the product of the mean air age difference and a first deviation coefficient, and the air stagnation area position change threshold is determined as the product of the mean air stagnation area position change and a second deviation coefficient.

[0060] Specifically, considering that users are extremely sensitive to air quality during sleep, in order to avoid missed judgments due to normal minor fluctuations, such as slight changes in natural airflow at night, this embodiment adopts a threshold setting strategy to increase sensitivity. That is, the threshold is lowered for positive indicators and the threshold is raised for negative indicators, so that it is easier to trigger the judgment of poor environmental quality.

[0061] The first deviation coefficient is selected within the range [0.9, 0.95]. A coefficient less than 1 ensures that the threshold is below the average level, enabling sensitive detection of slight increases in air age difference and rapid identification of the risk of polluted air from adjacent spaces spreading to the sleeping area. A value of 0.9 is preferred in practice.

[0062] The second deviation coefficient is selected within the range [1.2, 1.3]. A coefficient greater than 1 ensures that the threshold is higher than the average level, enabling it to accurately identify insufficient movement and a tendency to become fixed in the stagnant zone, thus preventing the formation of long-term ventilation dead zones. In practice, a coefficient of 1.2 is preferred.

[0063] The selection of the above-mentioned optimal values ​​achieves a good balance between improving sensitivity and avoiding an excessively high false alarm rate. Of course, those skilled in the art can readjust the value range according to the user's sensitivity to air quality and the fluctuation of historical data, or they can adjust the coefficients within a given range.

[0064] Specifically, this invention focuses on designing air circulation assessment indicators for the sleep time domain to accurately adapt to the special environmental needs of nighttime sleep. Addressing the high demand for fresh air and a stuffy environment during sleep, it introduces an air age difference index between the occupied space and adjacent spaces. This index quantifies the difference in air freshness between the two areas, assesses the environmental impact of adjacent spaces on the occupied sleeping space, and identifies whether polluted air from adjacent spaces diffuses into the sleeping space, reducing the risk of air freshness issues in the sleeping area. A smaller value indicates a closer similarity in air residence time and a smaller difference in air freshness between the two areas; a larger value indicates a more significant difference in air freshness. If the air age of the adjacent space is older, there is a gradient dynamic for polluted air from the adjacent space to diffuse into the occupied sleeping space, which will continuously reduce the air freshness of the occupied space. Simultaneously, the dynamic changes in the air stagnation area within the sleeping area and the overall activity of air circulation in the occupied space are quantified by the change in the position of the air stagnation area. The larger the value of this indicator, the more frequently the location of the stagnation zone moves and the more significant the area change, indicating that the air in the space is in a state of continuous micro-flow, and the stagnation zone has no fixed landing point. The smaller the value, the more likely the stagnation zone is fixed in a certain location for a long time, such as a corner of the bedroom or next to the bed, forming a fixed ventilation dead corner, where the air cannot be effectively replaced. Furthermore, it can reflect whether there are long-term fixed air stagnation zones in the space, such as those prone to odor growth and stuffiness, making the air circulation assessment more aligned with the specific needs of sleep scenarios for "no stagnation, micro-flow". Therefore, by deeply integrating the above two characteristics, an environmental circulation characterization value is formed to comprehensively assess the environmental quality of occupied spaces, characterizing the ability to maintain air freshness and the effect of cross-contamination prevention within occupied spaces. The environmental circulation characterization value is used as the basis for marking the level of environmental quality degradation, providing a clear quantitative basis for subsequent control and measurement. This invention optimizes the environmental adaptability of sleep scenarios. By relying on the change in the location of air retention areas and the time dimension design of sleep time segments, the environmental assessment is upgraded from static instantaneous data judgment to dynamic process state analysis. It can accurately capture the dynamic changes of the spatial environment during sleep, making the assessment results more consistent with the actual changes in the nighttime environment and enhancing the dynamism and comprehensiveness of the environmental assessment.

[0065] Specifically, please refer to Figure 4 As shown, this is a logic diagram for marking the environmental quality degradation level of occupied spaces in an embodiment of the present invention. Marking the environmental quality degradation level of the occupied spaces includes: If the environmental circulation characterization value of a populated space area is greater than or equal to the environmental circulation characterization threshold, then the populated space area will be marked as having a low environmental quality weakening level. If the environmental circulation characterization value of a populated area is less than the environmental circulation characterization threshold, the populated area will be marked as a high-level deterioration of environmental quality.

[0066] To determine the environmental circulation characterization threshold, historical operational data from the same occupied space area is used to select time periods with good air circulation and no risk of congestion or cross-contamination. The environmental circulation characterization values ​​for each time period are calculated, and the mean e and standard deviation f of the sequence are obtained. The sum of the product of the standard deviation f and the sensitivity coefficient k2 and the mean e is used as the environmental circulation characterization threshold. Furthermore, the environmental circulation characterization threshold should be dynamically updated according to seasonal changes or usage habits to adapt to shifts in operating conditions. Simultaneously, the environmental circulation characterization threshold should be coordinated with the air age difference threshold and the threshold for changes in the location of air stagnation areas, and can be iteratively optimized by verifying the misjudgment ratio under good operating conditions.

[0067] The sensitivity coefficient k2 can be selected within the range [1.0, 2.0] based on the tolerance for missed detection of environmental quality deterioration; for example, k2 = 1.5. If sufficient historical data is available, the 10th percentile can also be used as the threshold.

[0068] Specifically, based on the aforementioned environmental quality degradation level, the regulating equipment is adjusted, including: If the environmental quality degradation level is low, then identify the spatial area covered by the airflow path in the occupied space area and the directional proportion of the non-concentrated coverage area, calculate the environmental coordination characterization parameters, and determine the adjustment intensity for the adjustment device. If the environmental quality degradation level is high degradation level, an environmental optimization reminder signal will be issued.

[0069] Specifically, the process of calculating environmental coordination characterization parameters includes: The ratio of the airflow path coverage area to the airflow path coverage area threshold is used as the first environmental coordination feature. The ratio of the azimuth proportion threshold to the azimuth proportion of non-concentrated coverage areas is used as the second environmental coordination feature. The first environmental coordination feature and the second environmental coordination feature are weighted and summed to determine the environmental coordination characterization parameter.

[0070] Specifically, the airflow path coverage area quantifies the overall airflow range of the regulating equipment in occupied spaces. If the coverage area is too small, even if the proportion of locally weak areas is very low, most areas of the space will still not receive effective airflow, leading to an imbalance in the overall thermal and humidity environment. This characteristic determines whether the regulating equipment can "cover the whole" and is the primary indicator for judging whether the equipment's operating capacity is sufficient. The directional proportion of non-concentrated coverage areas reflects the proportion of areas in the target space where airflow is not effectively covered. This indicator is used to identify the unevenness of airflow distribution and guide local optimizations such as adjusting the air supply angle. Even if the proportion of locally weak areas is high, it can still be compensated for by adjusting the air supply direction as long as the overall coverage area is sufficient. In summary, considering that the airflow path coverage area determines the overall service capability of the regulating equipment in occupied spaces and is a prerequisite for meeting basic airflow requirements, while the directional proportion of non-concentrated coverage areas only reflects the degree of local weakness, it belongs to a refined optimization indicator. Therefore, a higher weighting coefficient is assigned to the first environmental coordination feature, which can be selected in the range of 0.6 to 0.8, and is set to 0.7 in this embodiment. Correspondingly, the weighting coefficient assigned to the second environmental coordination feature can be selected in the range of 0.2 to 0.4, and is set to 0.3 in this embodiment. The specific values ​​can be adjusted by those skilled in the art based on the spatial layout and equipment performance.

[0071] In this embodiment, the purpose of setting the airflow path coverage area threshold and the azimuth proportion threshold is to characterize situations where the matching and coordination between the airflow operation status of the regulating equipment and the environmental regulation needs of the occupied space is low. This is achieved by acquiring historical environmental data for the corresponding spatial area, and then calling the airflow path coverage area data corresponding to the regulating equipment within the occupied space area, as well as the azimuth proportion data for non-concentrated coverage areas. The average thermal airflow path coverage area and the average azimuth proportion are calculated. Based on the purpose of setting the above two thresholds, the airflow path coverage area threshold is determined as the product of the average airflow path coverage area and the coverage deviation coefficient, and the azimuth proportion threshold is determined as the product of the average azimuth proportion and the proportion deviation coefficient.

[0072] It is understandable that during normal use, the coverage area may fluctuate slightly due to minor adjustments in the airflow angle, furniture layout, etc. Therefore, the coverage deviation coefficient is selected within the range of [0.9, 0.95]. A coefficient less than 1 causes the threshold to be below the mean, allowing the area to decrease within a reasonable range without being judged as a mismatch. It is only triggered when the area is significantly smaller. In practice, a value of 0.9 is preferred, balancing sensitivity and stability.

[0073] The proportion is affected by spatial layout and personnel activities, and its normal fluctuation range is moderate. Therefore, the proportion deviation coefficient is selected within the range of [1.1, 1.3]. A coefficient greater than 1 makes the threshold higher than the mean, allowing a certain increase in the proportion without considering it as a serious inconsistency. Control is only triggered when the proportion is significantly high, such as when there is a large area of ​​weak airflow. In practice, a coefficient of 1.1 is preferred to balance missed detections and false detections.

[0074] The selection of the above-mentioned preferred values ​​achieves a good balance between effectively identifying genuine inconsistencies and reducing unnecessary adjustments. Of course, those skilled in the art can readjust the value range according to the actual environmental fluctuation characteristics, sensor accuracy, and user comfort preferences, or they can adjust the coefficients within a given range.

[0075] Specifically, this invention employs a dual-indicator quantification approach to the airflow effect of regulating equipment within occupied spaces, characterizing the actual distribution of airflow within these spaces. From an overall coverage perspective, the airflow path coverage area quantifies the overall airflow range and effective service capability of the regulating equipment within the occupied space. The size of the coverage area reflects whether the current operating conditions of the regulating equipment can meet the overall airflow needs of the occupied space. If the coverage area is too small, it indicates insufficient operating power of the regulating equipment, and the airflow cannot reach most areas of the space, thus reflecting the overall coverage efficiency and service capability of the regulating equipment for the target space. From the perspective of the distribution of locally weak areas, the proportion of non-concentrated coverage areas quantifies the overall impact of airflow-weak areas within the occupied space. The proportion of areas not effectively covered by airflow in the target space reflects the degree of impact of airflow distribution on perceived comfort. A higher proportion indicates more severe unevenness in airflow distribution within the space, and a larger range of localized discomfort. Furthermore, the magnitude and orientation of this indicator characteristic reflect the rationality of the air supply angle and outlet position of the regulating equipment. If a high percentage of non-concentrated coverage areas consistently appear in a certain direction, it indicates a directional deviation in the airflow output of the equipment, requiring targeted adjustments to the air supply angle to compensate for insufficient airflow in that area. Therefore, this invention quantitatively correlates the operating status of the regulating equipment with the environmental needs of occupied spaces, calculating environmental coordination characterization parameters to represent the degree of matching and coordination between the airflow operating status of the regulating equipment and the environmental regulation needs of occupied spaces, providing data support for determining the adjustment intensity of the regulating equipment. This invention focuses on directional regulation of occupied spaces, accurately matching human needs, improving the effectiveness of environmental regulation, and the adaptability of equipment operation to the spatial environment. It adjusts the equipment's operating intensity as needed, maximizing energy consumption reduction and meeting the core energy-saving requirements of photovoltaic energy storage direct-drive systems.

[0076] Specifically, determining the adjustment force for the adjustment device includes: The regulatory intensity is negatively correlated with the environmental coordination characterization parameters.

[0077] In this embodiment, optionally, The environmental coordination characterization parameters are compared with preset first environmental coordination characterization parameter comparison thresholds and second environmental coordination characterization parameter comparison thresholds. When the environmental coordination characterization parameter is greater than the second environmental coordination characterization parameter comparison threshold, the adjustment force is determined to be the first adjustment force, which is set to 1.1 times the initial speed. When the environmental coordination characterization parameter is greater than or equal to the first environmental coordination characterization parameter comparison threshold and less than or equal to the second environmental coordination characterization parameter comparison threshold, the adjustment force is determined to be the second adjustment force, which is set to 1.3 times the initial speed. When the environmental coordination characterization parameter is less than the first environmental coordination characterization parameter comparison threshold, the adjustment force is determined to be the third adjustment force, which is set to 1.5 times the initial speed. Among them, the first environmental coordination characterization parameter comparison threshold is 1.1 times the environmental coordination characterization parameter threshold, and the second environmental coordination characterization parameter comparison threshold is 1.3 times the environmental coordination characterization parameter threshold.

[0078] Understandably, the core purpose of setting the adjustment intensity is to quickly optimize the airflow distribution and thermal and humidity environment of occupied spaces through matching and directional adjustments, while adapting to the energy-saving characteristics of photovoltaic energy storage direct drive and meeting the needs of residential scenarios during nighttime sleep. Furthermore, the adjustment intensity can also be adjusted by those skilled in the art under different circumstances.

[0079] To determine the threshold for environmental coordination characterization parameters, several time periods are selected from historical operating data of the same or similar regulating equipment in the same spatial area. These periods are considered to have acceptable coordination levels and do not require additional regulation. The environmental coordination characterization parameters for each time period are calculated, and the mean c and standard deviation d of the sequence are obtained. The sum of the product of the standard deviation d and the sensitivity coefficient k3 and the mean c is used as the threshold for the environmental coordination characterization parameters. Furthermore, the threshold for environmental coordination characterization parameters should be dynamically updated with seasonal changes or equipment maintenance cycles to adapt to shifts in operating conditions. Simultaneously, the threshold for environmental coordination characterization parameters should be coordinated with the airflow path coverage area threshold and the azimuth proportion threshold, and can be iteratively optimized by verifying the misjudgment ratio under normal operating conditions.

[0080] The sensitivity coefficient k3 can be selected within the range [1.0, 2.0] based on the tolerance for missed detections due to insufficient coordination; for example, k3 = 1.5. If sufficient historical data is available, the 10th percentile can also be used as the threshold.

[0081] Specifically, it also includes adjusting the air supply angle of the regulating device, wherein the air supply angle corresponds to the non-concentrated coverage area.

[0082] If the intelligent control method of the photovoltaic energy storage direct-drive five constant system of the present invention is implemented in the form of software functional units and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in the various embodiments of the present invention. The aforementioned storage medium includes various media that can store program code, such as USB flash drives, mobile hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0083] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. An intelligent control method of a photovoltaic energy storage direct drive five-constant system, characterized in that, include: Environmental data from several spatial regions are monitored to extract environmental state characteristics of each spatial region, including carbon dioxide concentration and thermal humidity deviation value. By combining the environmental characteristics and the fluctuation of the fan noise intensity, the environmental quality characterization value of the spatial area is analyzed to mark the spatial area; In response to the identification of marked spatial regions, an environmental assessment and analysis of those regions is performed. include, The perceived temperature characteristics of human bodies in occupied spaces are used to determine whether the environment meets the comfort benchmark. Based on the air age difference between the occupied space area and the adjacent space area during the sleep time domain, and the change in the location of the air stagnation area in the occupied space area, the environmental circulation characterization value of the occupied space area is analyzed, and the environmental quality weakening level of the occupied space area is marked. Based on the aforementioned environmental quality degradation level, the control equipment in the occupied space area is adjusted. include, Identify the airflow path coverage area and the directional proportion of non-concentrated coverage areas corresponding to the regulating device, calculate environmental coordination characterization parameters, and determine the regulating force for the regulating device. Send an environmental optimization reminder signal; The human body's perceived temperature characteristics include the uniformity of heat distribution and the area of ​​concentrated heat.

2. The intelligent control method of the photovoltaic energy storage and direct drive five-constant system according to claim 1, characterized in that, The process of analyzing the environmental quality characterization values ​​of the aforementioned spatial region includes: The sum of the ratio of carbon dioxide concentration to carbon dioxide concentration threshold and the ratio of thermal humidity deviation value to thermal humidity deviation threshold is used as the first environmental quality characteristic. The ratio of the fluctuation of fan noise intensity to the threshold of fan noise intensity is used as the second environmental quality characteristic. The environmental quality characterization value is determined by weighted summation of the first environmental quality characteristic and the second environmental quality characteristic. 3.The intelligent control method of the photovoltaic energy storage and direct drive five-constant system according to claim 2, characterized in that, Marking the spatial region includes: If the environmental quality characterization value of a spatial region is greater than or equal to the environmental quality characterization threshold, then the spatial region is marked.

4. The intelligent control method for a photovoltaic energy storage direct-drive five-constant system according to claim 1, characterized in that, Determining whether environmental comfort standards are met includes: If the heat distribution uniformity is greater than the heat distribution uniformity threshold and the heat concentration area is less than the heat concentration area threshold, then it is determined that the environmental comfort benchmark is met.

5. The intelligent control method for a photovoltaic energy storage direct-drive five-constant system according to claim 1, characterized in that, The process of analyzing the environmental circulation characteristics of the occupied space includes: The ratio of the air age difference threshold to the air age difference of the occupied space area and the adjacent space area is used as the first environmental circulation characteristic. The ratio of the change in the position of the air stagnation area in the occupied space to the threshold value of the change in the position of the air stagnation area is used as the second environmental circulation characteristic. The environmental circulation characteristic value is determined by weighted summation of the first environmental circulation characteristic and the second environmental circulation characteristic.

6. The intelligent control method for a photovoltaic energy storage direct-drive five-constant system according to claim 5, characterized in that, The environmental quality degradation level of the aforementioned occupied space area is indicated, including: If the environmental circulation characterization value of a populated space area is greater than or equal to the environmental circulation characterization threshold, then the populated space area will be marked as having a low environmental quality weakening level. If the environmental circulation characterization value of a populated area is less than the environmental circulation characterization threshold, the populated area will be marked as a high-level deterioration of environmental quality.

7. The intelligent control method for a photovoltaic energy storage direct-drive five-constant system according to claim 1, characterized in that, Based on the aforementioned environmental quality degradation level, the regulating equipment is adjusted, including: If the environmental quality degradation level is low, then identify the spatial area covered by the airflow path in the occupied space area and the directional proportion of the non-concentrated coverage area, calculate the environmental coordination characterization parameters, and determine the adjustment intensity for the adjustment device. If the environmental quality degradation level is high degradation level, an environmental optimization reminder signal will be issued.

8. The intelligent control method for a photovoltaic energy storage direct-drive five-constant system according to claim 1, characterized in that, The process of calculating environmental coordination characterization parameters includes: The ratio of the airflow path coverage area to the airflow path coverage area threshold is used as the first environmental coordination feature. The ratio of the azimuth proportion threshold to the azimuth proportion of non-concentrated coverage areas is used as the second environmental coordination feature. The first environmental coordination feature and the second environmental coordination feature are weighted and summed to determine the environmental coordination characterization parameter.

9. The intelligent control method for a photovoltaic energy storage direct-drive five-constant system according to claim 8, characterized in that, Determining the adjustment force for the adjustment device includes: The regulatory intensity is negatively correlated with the environmental coordination characterization parameters.

10. The intelligent control method for a photovoltaic energy storage direct-drive five-constant system according to claim 1, characterized in that, It also includes adjusting the air supply angle of the regulating device, wherein the air supply angle corresponds to the non-concentrated coverage area.

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