Energy-saving optimization control method for intelligent constant temperature air conditioning system

Abstract

The present invention relates to the field of energy-saving technology, and discloses an energy-saving optimization control method and system for an intelligent constant temperature air-conditioning system, the method comprising: determining a preset temperature of the air-conditioning system; analyzing the operation mode of the air-conditioning system, calculating the total operation energy of the air-conditioning system, identifying the loss factor of the total operation energy, calculating the energy loss of the air-conditioning system, and determining the temperature control demand of the air-conditioning system; identifying the scene space of the application scene, constructing a multi-region space human thermal sensation sensing device, and constructing a multi-region space human thermal sensation prediction model according to human skin temperature and personnel heart rate; determining the personnel density of the multi-region space, determining the personnel thermal sensation of the multi-region space, calculating the group thermal sensation value of the multi-region space, constructing a temperature adjustment algorithm for the multi-region space, and regionally adjusting the preset temperature of the multi-region space to achieve energy-saving optimization control of the air-conditioning system. The present invention can improve the energy utilization rate of the air-conditioning system.

Description

Technical Field

[0001] The present invention relates to the field of energy-saving technology, and in particular to an energy-saving optimization control method and system for an intelligent constant temperature air-conditioning system. Background Art

[0002] An intelligent constant temperature air conditioning system refers to an air conditioning system that integrates advanced control technology, sensor technology, computer technology, and network communication technology. It can automatically sense changes in the indoor and outdoor environments, and intelligently adjust the operating status of the air conditioner according to set parameters or user needs to maintain constant indoor temperature and humidity, while achieving energy saving and improving comfort.

[0003] The current control method of the constant temperature air-conditioning system is to use a wall-mounted thermostat or an air-conditioning remote control to enable people to set the indoor temperature. The wall-mounted thermostat controls the temperature of the entire area in the same way. Due to the uneven distribution of people indoors, the temperature demand of the indoor area is not consistent, which causes the temperature of some areas to be too cold in summer and too hot in winter after the air-conditioning system is operated and controlled, which easily leads to energy waste. Summary of the invention

[0004] The present invention provides an energy-saving optimization control method and system for an intelligent constant temperature air-conditioning system, the main purpose of which is to improve the energy utilization rate of the air-conditioning system.

[0005] To achieve the above-mentioned purpose, the present invention provides an energy-saving optimization control method for an intelligent constant temperature air conditioning system, comprising:

[0006] Acquire an application scenario of the air-conditioning system, analyze the scenario environment of the application scenario, and determine a preset temperature of the air-conditioning system according to the scenario environment;

[0007] Based on the preset temperature, analyzing the operation mode of the air-conditioning system, calculating the total operation energy of the air-conditioning system according to the operation mode, identifying the loss factor of the total operation energy, calculating the energy loss of the air-conditioning system according to the loss factor, and determining the temperature control demand of the air-conditioning system according to the loss factor and the energy loss;

[0008] According to the temperature control requirement, the scene space of the application scenario is identified, the scene space is divided to obtain a multi-region space, a human thermal sensation sensing device is constructed for the multi-region space, the human thermal sensation sensing device is used to monitor the human skin temperature and the heart rate of the personnel in the multi-region space in real time, and a human thermal sensation prediction model for the multi-region space is constructed according to the human skin temperature and the heart rate of the personnel;

[0009] Determine the density of people in the multi-zone space, use the human thermal sensation prediction model to determine the thermal sensation of people in the multi-zone space, calculate the group thermal sensation value of the multi-zone space according to the thermal sensation of the people and the population density, construct a temperature adjustment algorithm for the multi-zone space according to the group thermal sensation value, and based on the temperature adjustment algorithm, perform regional adjustment on the preset temperature of the multi-zone space to achieve energy-saving optimization and regulation of the air-conditioning system.

[0010] Optionally, determining a preset temperature of the air conditioning system according to the scene environment includes:

[0011] Calculate the spatial volume of the air conditioning system corresponding to the application scenario;

[0012] Determine the outdoor temperature and indoor temperature of the scene environment, and determine the temperature requirement of the application scene according to the outdoor temperature and the indoor temperature;

[0013] Analyze the building structure of the scene environment to determine the thermal insulation properties of the building structure;

[0014] Analyze the lighting range and lighting time of the scene environment;

[0015] The preset temperature of the air conditioning system is determined according to the temperature requirement, the thermal insulation property, the illumination range, the illumination time and the space volume.

[0016] Optionally, calculating the total operating energy of the air-conditioning system according to the operating mode includes:

[0017] determining operating components of the air conditioning system according to the operating mode;

[0018] Determine the operating power of the operating component and collect the operating time of the operating component;

[0019] identifying an energy efficiency ratio of the air conditioning system;

[0020] The total operating energy of the air conditioning system is calculated according to the operating power, operating time and energy efficiency ratio.

[0021] Optionally, calculating the energy loss of the air-conditioning system according to the loss factor includes:

[0022] Measuring the current temperature of the air conditioning system corresponding to the application scenario, and determining the distribution area of ​​the current temperature;

[0023] Determining a heat loss coefficient of the application scenario according to a preset temperature corresponding to the air conditioning system, the current temperature, and the loss factor;

[0024] Determining the operating time of the air conditioning system;

[0025] According to the current temperature, the distribution area, the heat loss coefficient and the working time; the energy loss of the air conditioning system is calculated.

[0026] Optionally, the multi-region space human body thermal sensing device comprises:

[0027] Determining a target object of the multi-region space;

[0028] A temperature sensor and a heart rate sensor configured to monitor the target object;

[0029] Constructing a wireless communication module for the temperature sensor and the heart rate sensor;

[0030] Determine a microcontroller of the wireless communication module and construct a control algorithm of the microcontroller;

[0031] According to the wireless communication module, the microcontroller and the control algorithm, the multi-region space human body thermal sensing device is constructed.

[0032] Optionally, constructing the multi-region space human thermal sensation prediction model according to the human skin temperature and the person's heart rate includes:

[0033] Determining the thermal sensation of the target object corresponding to the multi-region space according to the human skin temperature and the heart rate of the person;

[0034] Constructing an initial model of thermal sensation of a human body in the multi-region space according to the human skin temperature, the heart rate of the person and the thermal sensation;

[0035] Using preset training data to train the initial model of human thermal sensation to obtain a training model of human thermal sensation;

[0036] Verifying the model accuracy of the human thermal sensation training model, and when the model accuracy does not meet the preset accuracy standard, correcting the human thermal sensation training model to obtain a human thermal sensation correction model;

[0037] The model accuracy of the human thermal sensation correction model is verified, and when the human thermal sensation correction model meets a preset standard, the human thermal sensation correction model is used as the human thermal sensation prediction model of the multi-region space.

[0038] In order to solve the above problems, the present invention also provides an energy-saving optimization control system for an intelligent constant temperature air conditioning system, the system comprising:

[0039] A preset temperature module, used to obtain an application scenario of the air-conditioning system, analyze the scenario environment of the application scenario, and determine a preset temperature of the air-conditioning system according to the scenario environment;

[0040] an energy loss analysis module, configured to analyze an operation mode of the air-conditioning system based on the preset temperature, calculate a total operation energy of the air-conditioning system according to the operation mode, identify a loss factor of the total operation energy, calculate an energy loss of the air-conditioning system according to the loss factor, and determine a temperature control requirement of the air-conditioning system according to the loss factor and the energy loss;

[0041] A thermal sensation analysis module, for identifying the scene space of the application scene according to the temperature control requirement, dividing the scene space to obtain a multi-region space, constructing a human thermal sensation sensing device for the multi-region space, using the human thermal sensation sensing device to monitor the human skin temperature and the heart rate of the person in the multi-region space in real time, and constructing a human thermal sensation prediction model for the multi-region space according to the human skin temperature and the heart rate of the person;

[0042] The temperature control module is used to determine the density of people in the multi-zone space, use the human thermal sensation prediction model to determine the thermal sensation of people in the multi-zone space, calculate the group thermal sensation value of the multi-zone space according to the thermal sensation of the people and the density of the people, and construct a temperature adjustment algorithm for the multi-zone space according to the group thermal sensation value. Based on the temperature adjustment algorithm, the preset temperature of the multi-zone space is regionally adjusted to achieve energy-saving optimization and control of the air-conditioning system.

[0043] According to the scene environment, the embodiment of the present invention determines the preset temperature of the air-conditioning system and can adjust the preset temperature according to the actual needs of the scene environment, thereby reducing unnecessary energy consumption, improving the energy efficiency ratio of the air-conditioning system, and achieving energy conservation and emission reduction; optionally, according to the operation mode, the embodiment of the present invention calculates the total operating energy of the air-conditioning system and can accurately calculate the energy consumption of the air-conditioning system in different operation modes, providing data support for energy efficiency management and optimization; according to the loss factor, the embodiment of the present invention calculates the energy loss of the air-conditioning system and can reduce the overall energy consumption of the air-conditioning system, reduce power consumption, and thus reduce operating costs; according to the human skin temperature and the heart rate of the personnel, the embodiment of the present invention constructs the human thermal sensation prediction model of the multi-region space, which can help the air-conditioning system optimize energy use and reduce unnecessary energy consumption while ensuring comfort; according to the personnel density of the multi-region space, the embodiment of the present invention determines the personnel density of the multi-region space and can automatically adjust the operating power and temperature setting of the air-conditioning according to the personnel density, thereby avoiding energy waste in low personnel density areas; finally, according to the group thermal sensation value, the embodiment of the present invention constructs the temperature adjustment algorithm of the multi-region space and can optimize energy distribution, only providing an appropriate amount of heat or cold in the required area and time, thereby reducing energy waste. Therefore, the present invention can improve the energy utilization rate of the air-conditioning system. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1 A schematic diagram of a flow chart of an energy-saving optimization control method for an intelligent constant temperature air conditioning system provided by an embodiment of the present invention;

[0045] Figure 2 A functional module diagram of an energy-saving optimization control system for an intelligent constant temperature air conditioning system provided by an embodiment of the present invention;

[0046] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0047] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0048] The embodiment of the present application provides an energy-saving optimization and control method for an intelligent constant temperature air conditioning system. The execution subject of the energy-saving optimization and control method for the intelligent constant temperature air conditioning system includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided by the embodiment of the present application. In other words, the energy-saving optimization and control method for the intelligent constant temperature air conditioning system can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc. The server can be an independent server, or it can be a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (Content Delivery Network, CDN), and basic cloud computing services such as big data and artificial intelligence platforms.

[0049] Reference Figure 1 FIG. 1 is a flow chart of an energy-saving optimization control method for an intelligent constant temperature air conditioning system provided by an embodiment of the present invention. In this embodiment, the energy-saving optimization control method for the intelligent constant temperature air conditioning system includes:

[0050] S1. Acquire an application scenario of an air-conditioning system, analyze a scenario environment of the application scenario, and determine a preset temperature of the air-conditioning system according to the scenario environment.

[0051] The embodiment of the present invention can adjust the working mode of the air conditioner according to different application scenarios by obtaining the application scenarios of the air conditioner system, so that the air conditioner can operate in an optimal state, thereby improving the energy efficiency ratio and saving energy. The application scenario refers to the specific use of the air conditioner system in different environments and occasions.

[0052] By analyzing the scene environment of the application scenario, the embodiment of the present invention can automatically adjust the air conditioning system's operating mode according to the specific environmental requirements of different scenarios, such as temperature, humidity, and flow of people, to optimize energy efficiency and reduce energy consumption. The scene environment refers to the specific environmental conditions in which the air conditioning system will operate, such as indoor environment, outdoor environment, building characteristics, etc.

[0053] Optionally, as an embodiment of the present invention, the scene environment of analyzing the application scenario may be analyzed by environmental monitoring technology and building information modeling (BIM) technology.

[0054] The embodiment of the present invention can adjust the preset temperature according to the actual needs of the scene environment by determining the preset temperature of the air-conditioning system according to the scene environment, thereby reducing unnecessary energy consumption, improving the energy efficiency ratio of the air-conditioning system, and achieving energy conservation and emission reduction. The preset temperature refers to the target temperature pre-set by the air-conditioning system in a specific application scenario in order to achieve a predetermined comfort level or process requirement. This temperature is the indoor temperature that the air-conditioning system attempts to maintain or achieve when it is running.

[0055] As an embodiment of the present invention, determining the preset temperature of the air conditioning system according to the scene environment includes:

[0056] Calculate the spatial volume of the air conditioning system corresponding to the application scenario;

[0057] Determine the outdoor temperature and indoor temperature of the scene environment, and determine the temperature requirement of the application scene according to the outdoor temperature and the indoor temperature;

[0058] Analyze the building structure of the scene environment to determine the thermal insulation properties of the building structure;

[0059] Analyze the lighting range and lighting time of the scene environment;

[0060] The preset temperature of the air conditioning system is determined according to the temperature requirement, the thermal insulation property, the illumination range, the illumination time and the space volume.

[0061] The spatial volume refers to the three-dimensional size of the indoor space where the air conditioning system needs to adjust the temperature and humidity. The temperature requirement refers to the indoor temperature range determined in a specific application scenario to ensure that the indoor environment meets the thermal comfort standard while taking energy saving and health factors into consideration. The building structure refers to the physical composition and layout of the building itself. The thermal insulation property refers to the effect of the building in terms of thermal insulation.

[0062] S2. Based on the preset temperature, analyze the operating mode of the air-conditioning system, calculate the total operating energy of the air-conditioning system according to the operating mode, identify the loss factor of the total operating energy, calculate the energy loss of the air-conditioning system according to the loss factor, and determine the temperature control demand of the air-conditioning system according to the loss factor and the energy loss.

[0063] The embodiment of the present invention can analyze the operation mode of the air-conditioning system based on the preset temperature, and can optimize the operation strategy of the air-conditioning system by analyzing the energy consumption under different operation modes, reduce unnecessary energy consumption, and improve the energy efficiency ratio or performance coefficient. The operation mode refers to the specific operation mode adopted by the air-conditioning system under different working states and operating conditions.

[0064] Optionally, as an embodiment of the present invention, the analyzing the operating mode of the air-conditioning system based on the preset temperature may be performed by pattern recognition technology.

[0065] The embodiment of the present invention can accurately calculate the energy consumption of the air-conditioning system in different operating modes by calculating the total operating energy of the air-conditioning system according to the operating mode, and provide data support for energy efficiency management and optimization. The total operating energy refers to the total amount of electric energy consumed by the air-conditioning system in a specific operating mode to maintain or change the indoor environmental state (such as temperature, humidity, etc.).

[0066] As an embodiment of the present invention, calculating the total operating energy of the air-conditioning system according to the operating mode includes:

[0067] determining operating components of the air conditioning system according to the operating mode;

[0068] Determine the operating power of the operating component and collect the operating time of the operating component;

[0069] identifying an energy efficiency ratio of the air conditioning system;

[0070] According to the operating power, operating time and energy efficiency ratio, the total operating energy of the air conditioning system is calculated using the following formula:

[0071]

[0072] Among them, D total represents the total running energy, i represents the i-th running component, n represents the total number of running components, G i represents the operating power of the i-th operating component, t i represents the operating time of the i-th operating component, and u represents the energy efficiency ratio of the air-conditioning system.

[0073] Among them, the hardware parts in the air-conditioning system that are responsible for realizing functions such as cooling, heating, ventilation and humidity control, such as compressors, fans, heating elements, etc. The operating power refers to the electrical power consumed by each operating component in the air-conditioning system under normal working conditions. The operating time refers to the actual working time length of each operating component in the air-conditioning system within a specific time period. The energy efficiency ratio refers to the ratio of the cooling capacity provided by the air conditioner or heat pump in the cooling mode to the electrical energy consumed.

[0074] Optionally, as another embodiment of the present invention, the energy efficiency ratio of the air-conditioning system may be calculated by the following formula:

[0075]

[0076] Among them, u represents the energy efficiency ratio of the air conditioning system, CH represents the change value of indoor heat per unit time of the air conditioning system, G x Indicates the electrical power consumed by the air conditioning system per unit time.

[0077] The present invention can optimize the operating efficiency of the air conditioning system and reduce unnecessary energy consumption by identifying the loss factor of the total operating energy and identifying the specific factors that cause energy loss. The loss factor refers to various factors that affect the overall energy efficiency of the system, which may cause ineffective energy loss.

[0078] Optionally, as an embodiment of the present invention, the loss factor of the total operating energy can be identified by an airflow analysis method.

[0079] The embodiment of the present invention can reduce the overall energy consumption of the air-conditioning system, reduce power consumption, and thus reduce operating costs by calculating the energy loss of the air-conditioning system according to the loss factor. The energy loss in the air-conditioning system generally refers to the energy that is inevitably lost during the energy conversion and transmission process.

[0080] As an embodiment of the present invention, calculating the energy loss of the air conditioning system according to the loss factor includes:

[0081] Measuring the current temperature of the air conditioning system corresponding to the application scenario, and determining the distribution area of ​​the current temperature;

[0082] Determining a heat loss coefficient of the application scenario according to a preset temperature corresponding to the air conditioning system, the current temperature, and the loss factor;

[0083] Determining the operating time of the air conditioning system;

[0084] According to the current temperature, the distribution area, the heat loss coefficient and the working time, the energy loss of the air conditioning system is calculated using the following formula:

[0085] H lose =αT g S(W d -W0)

[0086] Among them, H lose represents energy loss, α represents heat loss coefficient, T g represents the working time, S represents the distribution area of ​​the current temperature, W d Indicates the current temperature, and W0 indicates the preset temperature.

[0087] The current temperature refers to the air temperature of the air conditioning system in operation in the application scenario corresponding to the air conditioning system. The distribution area refers to the total area of ​​the current spatial area of ​​the air conditioning system. The heat loss coefficient refers to the heat loss rate per unit area and per unit temperature difference.

[0088] Optionally, the distribution area of ​​the current temperature may be determined by calculation by dividing the area.

[0089] The embodiment of the present invention can more accurately adjust the cooling or heating output of the air-conditioning system by determining the temperature control demand of the air-conditioning system according to the loss factor and the energy loss, so as to keep the indoor temperature within a set range and improve the comfort level. The temperature control demand refers to the various adjustment and control operations that need to be performed during the operation of the air-conditioning system in order to achieve and maintain the set indoor temperature target.

[0090] Optionally, as an embodiment of the present invention, the temperature control requirement of the air-conditioning system determined according to the loss factor and the energy loss can be determined by energy auditing technology. The energy auditing technology refers to a technology that identifies and quantifies energy consumption, finds energy waste links, and proposes improvement measures to improve energy efficiency, reduce energy costs, and reduce environmental impact.

[0091] S3. According to the temperature control demand, the scene space of the application scenario is identified, the scene space is divided to obtain a multi-region space, a human thermal sensation sensing device is constructed in the multi-region space, and the human thermal sensation sensing device is used to monitor the human skin temperature and the heart rate of the personnel in the multi-region space in real time, and a human thermal sensation prediction model of the multi-region space is constructed according to the human skin temperature and the heart rate of the personnel.

[0092] The embodiment of the present invention can provide personalized temperature settings for different areas by identifying the scene space of the application scenario according to the temperature control demand, thereby meeting the comfort requirements of different users. The scene space refers to a specific indoor or outdoor area with clear boundaries in the application of the air conditioning system.

[0093] Optionally, as an embodiment of the present invention, the scene space of the application scene identified according to the temperature control requirement may be identified by a space recognition technology.

[0094] The embodiment of the present invention divides the scene space into a multi-zone space, and can provide more precise temperature control for each zone to meet the specific needs of different zones. The multi-zone space refers to dividing the overall space into a plurality of independent or semi-independent control zones in an indoor environment according to different functions, usage requirements, environmental conditions or user preferences.

[0095] Optionally, the scene space is divided to obtain a multi-region space which can be divided by an open layout design.

[0096] In the embodiment of the present invention, by constructing the multi-region space human thermal sensing device, the air conditioning system can adjust the working state more accurately according to the human thermal sensing data, avoid excessive cooling or heating, and thus save energy. The human thermal sensing device refers to a sensor system that can detect and evaluate the human body's perception of the surrounding environment temperature.

[0097] As an embodiment of the present invention, the human body thermal sensing device for constructing the multi-region space includes:

[0098] Determining a target object of the multi-region space;

[0099] A temperature sensor and a heart rate sensor configured to monitor the target object;

[0100] Constructing a wireless communication module for the temperature sensor and the heart rate sensor;

[0101] Determine a microcontroller of the wireless communication module and construct a control algorithm of the microcontroller;

[0102] According to the wireless communication module, the microcontroller and the control algorithm, the multi-region space human body thermal sensing device is constructed.

[0103] Among them, the target object refers to the personnel in the multi-zone space. The temperature sensor refers to a device that can measure the temperature of an object or environment. The heart rate sensor refers to a device that can detect and monitor the heart rate (heart rate). The wireless communication module refers to an electronic component that can realize wireless data transmission between devices. The microcontroller refers to a component used to control the sensor data acquisition, processing and transmission. The control algorithm refers to the program or instruction set used to manage and optimize the operation of the human body thermal sensing device.

[0104] Optionally, the control algorithm for constructing the microcontroller may be constructed by a comfort evaluation model, such as a PMV model, an adaptive model, and the like.

[0105] The embodiment of the present invention can help to more accurately control the air-conditioning system and reduce energy waste by using the human thermal sensing device to monitor the human skin temperature and heart rate of people in the multi-zone space in real time.

[0106] The embodiment of the present invention can help the air conditioning system optimize energy use and reduce unnecessary energy consumption while ensuring comfort by constructing the human thermal sensation prediction model of the multi-zone space according to the human skin temperature and the heart rate of the person. The human thermal sensation prediction model refers to an analytical model that predicts an individual's feeling of heat under specific environmental conditions.

[0107] As an embodiment of the present invention, constructing the multi-region space human thermal sensation prediction model according to the human skin temperature and the person's heart rate includes:

[0108] Determining the thermal sensation of the target object corresponding to the multi-region space according to the human skin temperature and the heart rate of the person;

[0109] According to the human skin temperature, the heart rate of the person and the thermal sensation, the human thermal sensation initial model of the multi-region space is constructed using the following formula, wherein the human thermal sensation initial model is:

[0110] GJ=aXT+bWD+c

[0111] Among them, GJ represents thermal sensation, XT represents the heart rate of the personnel, WD represents the skin temperature, a represents the heart rate coefficient, b represents the temperature coefficient, and c represents a constant;

[0112] Using preset training data to train the initial model of human thermal sensation to obtain a training model of human thermal sensation;

[0113] Verifying the model accuracy of the human thermal sensation training model, and when the model accuracy does not meet the preset accuracy standard, correcting the human thermal sensation training model to obtain a human thermal sensation correction model;

[0114] The model accuracy of the human thermal sensation correction model is verified, and when the human thermal sensation correction model meets a preset standard, the human thermal sensation correction model is used as the human thermal sensation prediction model of the multi-region space.

[0115] Among them, the thermal sensation refers to the subjective perception of temperature by the human body, especially the perception of heat or warmth. The human thermal sensation initial model refers to a preliminary mathematical model based on known data for predicting human thermal sensation. The human thermal sensation training model refers to a model obtained by training the initial model using a specific data set. The model accuracy refers to the correctness of the model prediction results, which is an important indicator for measuring the performance of machine learning models. The preset accuracy standard refers to a series of rules or thresholds set in the process of establishing and verifying the model to evaluate whether the model performance reaches an acceptable level. The human thermal sensation correction model refers to a model obtained after parameter correction of the human thermal sensation training model in order to improve the prediction accuracy of human thermal sensation.

[0116] Optionally, the correction of the human thermal sensation training model may be performed by adjusting a heartbeat coefficient, a temperature coefficient and a constant of the human thermal sensation training model.

[0117] S4. Determine the density of people in the multi-zone space, use the human thermal sensation prediction model to determine the thermal sensation of people in the multi-zone space, calculate the group thermal sensation value of the multi-zone space according to the thermal sensation of the people and the population density, construct a temperature adjustment algorithm for the multi-zone space according to the group thermal sensation value, and based on the temperature adjustment algorithm, perform regional adjustment on the preset temperature of the multi-zone space to achieve energy-saving optimization and regulation of the air-conditioning system.

[0118] By determining the occupant density of the multi-zone space, the embodiment of the present invention can automatically adjust the operating power and temperature setting of the air conditioner according to the occupant density, thereby avoiding energy waste in low occupant density areas. The occupant density refers to the number of people per unit area or unit volume in a specific space area.

[0119] Optionally, as an embodiment of the present invention, the determination of the population density of the multi-region space may be determined by a video surveillance analysis method.

[0120] The embodiment of the present invention uses the human thermal sensation prediction model to determine the thermal sensation of the personnel in the multi-zone space, and can accurately control the indoor temperature and humidity through the prediction model to avoid excessive cooling or heating, thereby reducing energy consumption. The thermal sensation of the personnel refers to the subjective perception and evaluation of the ambient temperature by the individual.

[0121] As an embodiment of the present invention, the determining the thermal sensation of personnel in the multi-region space by using the human thermal sensation prediction model includes:

[0122] Using the multi-region space corresponding to human body thermal sensation sensor equipment to collect real-time data of the target object corresponding to the multi-region space;

[0123] Identifying abnormal values ​​of the real-time data, and performing data conversion on the abnormal values ​​to obtain converted data;

[0124] Normalizing the converted data to obtain normalized data;

[0125] Inputting the normalized data into the human thermal sensation prediction model to obtain model output data;

[0126] constructing a thermal sensation-time curve of the multi-region space according to the model output data;

[0127] The thermal sensation of the personnel in the multi-zone space is determined according to the thermal sensation-time curve.

[0128] The real-time data includes: real-time human skin temperature and real-time heart rate of personnel. The abnormal value refers to an observation value that is significantly different from other data points. The normalized data refers to data processed by normalization (or standardization). The model output data refers to the final result obtained after data processing and model calculation. The thermal sensation-time curve refers to a chart of the changes in thermal sensation of an individual over a period of time.

[0129] Optionally, the cleaned data is normalized, and the normalized data obtained can be processed by a minimum-maximum normalization method.

[0130] In the embodiment of the present invention, the group thermal sensation value of the multi-region space is calculated according to the thermal sensation of the personnel and the density of the personnel, and the air conditioning, heating and ventilation systems can be adjusted according to the group thermal sensation value to achieve a more comfortable indoor environment while reducing unnecessary energy consumption. The group thermal sensation value refers to a quantitative index reflecting the thermal environment perception of the entire group or people in a specific area, obtained by comprehensive analysis and calculation of individual thermal sensation data in the multi-region space.

[0131] As an embodiment of the present invention, the calculating the group thermal sensation value of the multi-region space according to the thermal sensation of the personnel and the personnel density includes:

[0132] Extracting personal physical fitness indexes of people corresponding to the multi-region space;

[0133] Determining a thermal sensation evaluation coefficient of the person according to the personal physical fitness index;

[0134] According to the individual physical fitness index, the thermal sensation evaluation coefficient, the thermal sensation of the personnel and the personnel density, the group thermal sensation value of the multi-region space is calculated using the following formula:

[0135]

[0136] Among them, QG represents the group thermal sensation value, q represents the qth person in the multi-region space, m represents the person density, and RG q represents the thermal sensation of the qth person in the multi-region space, β represents the thermal sensation evaluation coefficient, and γ q Represents personal physical fitness index.

[0137] The individual physical fitness index refers to a quantitative index used to evaluate an individual's physical health, physiological function and physical ability. The thermal sensation evaluation coefficient refers to a parameter used to quantify an individual's perception of a thermal environment.

[0138] Optionally, the thermal sensation evaluation coefficient of the person determined according to the personal physical fitness index may be determined by a statistical analysis method.

[0139] The embodiment of the present invention can optimize energy allocation by constructing the temperature adjustment algorithm of the multi-zone space according to the group thermal sensation value, providing the right amount of heat or cold only in the required area and time, and reducing energy waste. The temperature adjustment algorithm refers to a computer program or mathematical model for automatically controlling and optimizing the temperature of indoor or outdoor multi-zone spaces.

[0140] As an embodiment of the present invention, constructing the temperature adjustment algorithm of the multi-region space according to the group thermal sensation value includes:

[0141] Measuring a preset temperature of an air conditioning system corresponding to the multi-zone space;

[0142] Determine an upper temperature limit and a lower temperature limit for an operation mode of the air conditioning system;

[0143] Determine a thermal comfort range of the group thermal sensation value, and determine a minimum change value of the group thermal sensation value based on the thermal comfort range;

[0144] According to the group thermal sensation value, the preset temperature, the temperature upper limit value, the temperature lower limit value and the minimum change value, the temperature adjustment algorithm of the multi-zone space is calculated using the following formula, wherein the temperature adjustment algorithm is:

[0145]

[0146] Among them, W y Indicates the optimized temperature value, Wmax Indicates the upper temperature limit, W0 indicates the preset temperature, W mi n represents the lower limit of temperature, θ1 represents the minimum change value of the group thermal sensation value, QG represents the group thermal sensation value, and θ2 represents the level threshold corresponding to the group thermal sensation value.

[0147] The upper temperature limit refers to the maximum allowable temperature set by the air conditioning system to ensure thermal comfort, safety and normal operation of the equipment. The lower temperature limit refers to the minimum allowable temperature set by the air conditioning system to ensure thermal comfort, safety and normal operation of the equipment. The thermal comfort range refers to the air temperature range that most people feel satisfied and comfortable with under certain environmental conditions. The minimum change value refers to the minimum standard for adjusting the group thermal sensation value, such as 0.5 or 1. The level threshold is the group thermal sensation value used to divide the thermal sensation level, for example, θ2 is 2.5.

[0148] The embodiment of the present invention performs regional adjustment on the preset temperature of the multi-zone space based on the temperature adjustment algorithm to achieve energy-saving optimization and regulation of the air-conditioning system, which can not only improve the energy management efficiency, but also improve the overall quality of the indoor environment.

[0149] According to the scene environment, the embodiment of the present invention determines the preset temperature of the air-conditioning system and can adjust the preset temperature according to the actual needs of the scene environment, thereby reducing unnecessary energy consumption, improving the energy efficiency ratio of the air-conditioning system, and achieving energy conservation and emission reduction; optionally, according to the operation mode, the embodiment of the present invention calculates the total operating energy of the air-conditioning system and can accurately calculate the energy consumption of the air-conditioning system in different operation modes, providing data support for energy efficiency management and optimization; according to the loss factor, the embodiment of the present invention calculates the energy loss of the air-conditioning system and can reduce the overall energy consumption of the air-conditioning system, reduce power consumption, and thus reduce operating costs; according to the human skin temperature and the heart rate of the personnel, the embodiment of the present invention constructs the human thermal sensation prediction model of the multi-region space, which can help the air-conditioning system optimize energy use and reduce unnecessary energy consumption while ensuring comfort; according to the personnel density of the multi-region space, the embodiment of the present invention determines the personnel density of the multi-region space and can automatically adjust the operating power and temperature setting of the air-conditioning according to the personnel density, thereby avoiding energy waste in low personnel density areas; finally, according to the group thermal sensation value, the embodiment of the present invention constructs the temperature adjustment algorithm of the multi-region space and can optimize energy distribution, only providing an appropriate amount of heat or cold in the required area and time, thereby reducing energy waste. Therefore, the present invention can improve the energy utilization rate of the air-conditioning system.

[0150] like Figure 2 , which is a functional module diagram of an energy-saving optimization control system of an intelligent constant temperature air conditioning system provided by an embodiment of the present invention.

[0151] The energy-saving optimization control system 200 of the intelligent constant temperature air conditioning system of the present invention can be installed in an electronic device. According to the functions to be implemented, the energy-saving optimization control system 200 of the intelligent constant temperature air conditioning system may include a preset temperature module 201, an energy loss analysis module 202, a thermal sensation analysis module 203 and a temperature control module 204. The module of the present invention can also be referred to as a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device.

[0152] In this embodiment, the functions of each module / unit are as follows:

[0153] The preset temperature module 201 is used to obtain an application scenario of the air conditioning system, analyze the scene environment of the application scenario, and determine the preset temperature of the air conditioning system according to the scene environment;

[0154] The energy loss analysis module 202 is used to analyze the operation mode of the air-conditioning system based on the preset temperature, calculate the total operation energy of the air-conditioning system according to the operation mode, identify the loss factor of the total operation energy, calculate the energy loss of the air-conditioning system according to the loss factor, and determine the temperature control demand of the air-conditioning system according to the loss factor and the energy loss;

[0155] The thermal sensation analysis module 203 is used to identify the scene space of the application scenario according to the temperature control demand, divide the scene space to obtain a multi-region space, construct a human thermal sensation sensing device in the multi-region space, use the human thermal sensation sensing device to monitor the human skin temperature and the heart rate of the personnel in the multi-region space in real time, and construct a human thermal sensation prediction model in the multi-region space according to the human skin temperature and the heart rate of the personnel;

[0156] The temperature control module 204 is used to determine the density of people in the multi-zone space, use the human thermal sensation prediction model to determine the thermal sensation of people in the multi-zone space, calculate the group thermal sensation value of the multi-zone space according to the thermal sensation of the people and the population density, and construct a temperature adjustment algorithm for the multi-zone space according to the group thermal sensation value. Based on the temperature adjustment algorithm, the preset temperature of the multi-zone space is regionally adjusted to achieve energy-saving optimization and control of the air-conditioning system.

[0157] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. An energy-saving optimization control method for an intelligent constant temperature air conditioning system, characterized in that: The method comprises: Acquire an application scenario of the air-conditioning system, analyze the scenario environment of the application scenario, and determine a preset temperature of the air-conditioning system according to the scenario environment; Based on the preset temperature, analyzing the operation mode of the air-conditioning system, calculating the total operation energy of the air-conditioning system according to the operation mode, identifying the loss factor of the total operation energy, calculating the energy loss of the air-conditioning system according to the loss factor, and determining the temperature control demand of the air-conditioning system according to the loss factor and the energy loss; According to the temperature control requirement, the scene space of the application scenario is identified, the scene space is divided to obtain a multi-region space, a human thermal sensation sensing device is constructed for the multi-region space, the human thermal sensation sensing device is used to monitor the human skin temperature and the heart rate of the personnel in the multi-region space in real time, and a human thermal sensation prediction model for the multi-region space is constructed according to the human skin temperature and the heart rate of the personnel; Determine the density of people in the multi-zone space, use the human thermal sensation prediction model to determine the thermal sensation of people in the multi-zone space, calculate the group thermal sensation value of the multi-zone space according to the thermal sensation of the people and the population density, construct a temperature adjustment algorithm for the multi-zone space according to the group thermal sensation value, and based on the temperature adjustment algorithm, perform regional adjustment on the preset temperature of the multi-zone space to achieve energy-saving optimization and regulation of the air-conditioning system.

2. The energy-saving optimization control method of the intelligent constant temperature air conditioning system according to claim 1, characterized in that: The step of determining a preset temperature of the air conditioning system according to the scene environment includes: Calculate the spatial volume of the air conditioning system corresponding to the application scenario; The outdoor temperature and indoor temperature of the scene environment are determined, and the temperature requirement of the application scene is determined according to the outdoor temperature and the indoor temperature.

3. The energy-saving optimization control method of the intelligent constant temperature air conditioning system according to claim 2, characterized in that: Determining the preset temperature of the air conditioning system according to the scene environment includes: analyzing the building structure of the scene environment to determine the thermal insulation properties of the building structure; Analyze the lighting range and lighting time of the scene environment; The preset temperature of the air conditioning system is determined according to the temperature requirement, the thermal insulation property, the illumination range, the illumination time and the space volume.

4. The energy-saving optimization control method of the intelligent constant temperature air conditioning system according to claim 1, characterized in that: Calculating the total operating energy of the air conditioning system according to the operating mode includes: determining operating components of the air conditioning system according to the operating mode; The operating power of the operating component is determined, and the operating time of the operating component is collected.

5. The energy-saving optimization control method of the intelligent constant temperature air conditioning system according to claim 4, characterized in that: The calculating the total operating energy of the air conditioning system according to the operating mode further includes: identifying an energy efficiency ratio of the air conditioning system; The total operating energy of the air conditioning system is calculated according to the operating power, operating time and energy efficiency ratio.

6. The energy-saving optimization control method of the intelligent constant temperature air conditioning system according to claim 1, characterized in that: The human body thermal sensing device for constructing the multi-region space includes: Determining a target object of the multi-region space; A temperature sensor and a heart rate sensor are configured to monitor the target object.

7. The energy-saving optimization control method of the intelligent constant temperature air conditioning system according to claim 6, characterized in that: The human body thermal sensing device for constructing the multi-region space includes: Constructing a wireless communication module for the temperature sensor and the heart rate sensor; Determine a microcontroller of the wireless communication module and construct a control algorithm of the microcontroller; According to the wireless communication module, the microcontroller and the control algorithm, the multi-region space human thermal sensing device is constructed.

8. The energy-saving optimization control method of the intelligent constant temperature air conditioning system according to claim 1, characterized in that: The step of constructing the multi-region space human thermal sensation prediction model according to the human skin temperature and the human heart rate includes: Determining the thermal sensation of the target object corresponding to the multi-region space according to the human skin temperature and the heart rate of the person; According to the human skin temperature, the heart rate of the person and the thermal sensation, the following formula is used to construct the human thermal sensation initial model in the multi-region space, wherein the human thermal sensation initial model.

9. The energy-saving optimization control method of the intelligent constant temperature air conditioning system according to claim 8, characterized in that: The step of constructing the multi-region space human thermal sensation prediction model according to the human skin temperature and the human heart rate includes: Using preset training data to train the initial model of human thermal sensation to obtain a training model of human thermal sensation; Verifying the model accuracy of the human thermal sensation training model, and when the model accuracy does not meet the preset accuracy standard, correcting the human thermal sensation training model to obtain a human thermal sensation correction model; The model accuracy of the human thermal sensation correction model is verified, and when the human thermal sensation correction model meets a preset standard, the human thermal sensation correction model is used as the human thermal sensation prediction model of the multi-region space.

10. An energy-saving optimization control system for an intelligent constant temperature air conditioning system, characterized in that: A method for energy-saving optimization and control of an intelligent constant temperature air conditioning system according to any one of claims 1 to 9, the system comprising: A preset temperature module, used to obtain an application scenario of the air-conditioning system, analyze the scenario environment of the application scenario, and determine a preset temperature of the air-conditioning system according to the scenario environment; an energy loss analysis module, configured to analyze an operation mode of the air-conditioning system based on the preset temperature, calculate a total operation energy of the air-conditioning system according to the operation mode, identify a loss factor of the total operation energy, calculate an energy loss of the air-conditioning system according to the loss factor, and determine a temperature control requirement of the air-conditioning system according to the loss factor and the energy loss; A thermal sensation analysis module, for identifying the scene space of the application scene according to the temperature control requirement, dividing the scene space to obtain a multi-region space, constructing a human thermal sensation sensing device for the multi-region space, using the human thermal sensation sensing device to monitor the human skin temperature and the heart rate of the person in the multi-region space in real time, and constructing a human thermal sensation prediction model for the multi-region space according to the human skin temperature and the heart rate of the person; The temperature control module is used to determine the density of people in the multi-zone space, use the human thermal sensation prediction model to determine the thermal sensation of people in the multi-zone space, calculate the group thermal sensation value of the multi-zone space according to the thermal sensation of the people and the density of the people, and construct a temperature adjustment algorithm for the multi-zone space according to the group thermal sensation value. Based on the temperature adjustment algorithm, the preset temperature of the multi-zone space is regionally adjusted to achieve energy-saving optimization and control of the air-conditioning system.

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