Multi-period air conditioner adjusting system and method based on electricity and carbon cost saving

Abstract

The invention relates to the technical field of air conditioner adjusting, in particular to a multi-period air conditioner adjusting system and method based on electricity and carbon cost saving. The adjusting system comprises an environment sensing module used for collecting indoor and outdoor temperature and humidity data and outputting the indoor and outdoor temperature and humidity data to a server, and an electric energy collecting module used for collecting air conditioner electricity consumption data and outputting the air conditioner electricity consumption data to the server. The server is used for issuing an air conditioner adjusting instruction to the command execution module according to the indoor and outdoor temperature and humidity data and the air conditioner electricity consumption data; the command execution module is used for receiving the air conditioner adjusting instruction and controlling the air conditioner according to the air conditioner adjusting instruction; and the environment sensing module, the electric energy acquisition module and the command execution module are electrically communicated with the server. On the premise of balancing the relationship among the user experience, the electricity consumption of the air conditioner and the carbon emission, the use willingness of the user is greatly improved, and automatic load management of the air conditioner is implemented.

Description

Technical Field

[0001] The present invention relates to the technical field of air conditioning regulation, and in particular to a multi-period air conditioning regulation system and method based on saving electricity carbon cost. Background Art

[0002] With the proposal of the "dual carbon" goal, the penetration rate of renewable energy in my country's power system has continued to increase. Due to its inherent intermittent and random characteristics, it has caused great pressure on the balance of supply and demand for the power system. Relying solely on the regulation capacity of the power generation side is not a long-term solution. Therefore, how to fully tap the regulation potential of the load side has become a topic of great concern. Air conditioning load is an important part of the load side and the main reason for widening the daily peak-to-valley difference of the power grid load. Therefore, by optimizing the air conditioning operation mode, the load reduction potential of the air conditioning load can be tapped to reduce peak load and carbon emissions without affecting user comfort to a small extent.

[0003] At present, the existing intelligent air conditioning adjustment technology mainly focuses on air conditioning control methods, air conditioning load modeling and air conditioning load reduction control strategies. However, there are problems such as rough modeling, single algorithm influencing factors, and failure to combine with the current domestic electricity consumption and policy goals. In addition, the existing air conditioning adjustment technology does not consider how to balance the relationship between user experience, air conditioning power consumption and carbon emissions under different electricity prices during peak and valley periods, and implement automatic load management of air conditioning while minimizing user resistance. This leads to users resisting some intelligent air conditioning adjustment methods, and some adjustment methods can only be limited to the simulation level. Summary of the invention

[0004] The technical problem to be solved by the present invention is: in order to solve the technical problem described in the background technology, the present invention provides a multi-period air conditioning adjustment system and method based on saving electricity carbon cost. The present invention ensures that carbon emissions are reduced while improving human comfort. By setting the operation period in the intelligent decision-making module as a supplement and optimization between the pre-cooling period and the early shutdown period, the latest indoor real-time temperature data and air conditioning power consumption data are continuously obtained, and the calculated carbon emissions in the air conditioning operation stage and the resident thermal comfort index are used as the fitness of the genetic algorithm. The temperature value of the individual with the highest fitness in the population is found through iteration, hybridization, and mutation, which is the optimal temperature. After obtaining the optimal temperature, the control command execution module adjusts the air conditioning temperature. Under the premise of balancing the relationship between user experience, air conditioning power consumption and carbon emissions, the present invention greatly improves the user's willingness to use and implements automatic load management of air conditioning.

[0005] The technical solution adopted by the present invention to solve its technical problem is:

[0006] A multi-period air conditioning regulation system based on saving electricity carbon cost, including an environment perception module for collecting indoor and outdoor temperature and humidity data and outputting it to a server, an electric energy collection module for collecting air conditioning power consumption data and outputting it to a server, a server for sending air conditioning regulation instructions to a command execution module according to the indoor and outdoor temperature and humidity data and the air conditioning power consumption data, and a command execution module for receiving the air conditioning regulation instructions and controlling the air conditioning according to the air conditioning regulation instructions; the environment perception module, the electric energy collection module, and the command execution module are all in electrical communication with the server.

[0007] Specifically, the server includes a database module for storing indoor and outdoor temperature and humidity data and air conditioning power consumption data, and an intelligent decision-making module for controlling the air conditioning to adjust the temperature in real time according to different strategies.

[0008] A multi-period air conditioning adjustment method based on saving electricity carbon cost, the specific steps of the air conditioning adjustment method are:

[0009] S1. Set parameters;

[0010] S2, data collection: the environment sensing module and the power collection module continuously collect indoor and outdoor temperature and humidity data and air conditioning power consumption data at a preset frequency within a preset collection time range, and store the indoor and outdoor temperature and humidity data and air conditioning power consumption data in a database of the server;

[0011] S3, air conditioning reservation: start the intelligent decision-making module at the preset pre-cooling period start time, and calculate the advance start time of the air conditioner based on the time prediction strategy;

[0012] S4, real-time control of air conditioning temperature parameters: within the operating time range, two temperature control strategies are respectively implemented according to the peak and valley periods of electricity consumption. These two strategies are based on their own algorithms and real-time indoor and outdoor temperature and humidity data and air conditioning power consumption data. The air conditioning adjustment instructions are output to the command execution module in real time. After obtaining the instructions, the command execution module controls the air conditioning to adjust the air conditioning temperature or switch in real time, and calculates the start time of the early shutdown period through environmental parameters;

[0013] S5, air conditioning early shutdown: at the start time of the early shutdown period, the air conditioning shutdown time is calculated through the time prediction strategy. When the shutdown time arrives, the shutdown command is output to the command execution module in real time. After the command execution module obtains the command, it shuts down the air conditioner in real time.

[0014] Specifically, in step S3, the working steps of the pre-cooling period are:

[0015] S31, perception stage: briefly turn on the air conditioner, read the real-time indoor and outdoor temperature and humidity data from the database, and update some thermal equivalent model calculation parameters;

[0016] S32, shutdown stage; calculate the air conditioner start time in the temperature adjustment stage according to the thermal equivalent model, and output the shutdown instruction to the command execution module, and the command execution module turns off the air conditioner in real time after obtaining the instruction;

[0017] S33, temperature adjustment stage; according to the air-conditioning start-up time calculated in the shutdown stage, the temperature control instruction is output to the command execution module, and the command execution module adjusts the air-conditioning temperature in real time after obtaining the instruction.

[0018] Specifically, in step S4, the working steps of the operation period are:

[0019] S41, judging the peak and valley electricity at the current moment;

[0020] S42, when the time is at a peak or peak, a timed start-stop strategy is adopted, a human body temperature comfort range is preset, and an air conditioning start or stop instruction is obtained by judging whether the indoor real-time temperature data in the database reaches the human body temperature comfort range threshold;

[0021] S43. When the time is at a flat or low point, the most suitable temperature strategy is adopted to use the residents' thermal comfort index and carbon emissions as the fitness of the genetic algorithm. Through iteration, hybridization and mutation, the temperature value of the individual with the highest fitness is found to obtain the optimal temperature. This strategy is set to be executed every ten minutes.

[0022] S44. According to the air conditioning control instructions obtained in step S42 and step S43: restart the command execution module at the start time, and output the air conditioning control instructions to the command execution module.

[0023] Specifically, in step S3, the algorithm of the time prediction strategy is as follows:

[0024] S331. In the perception stage, set the human comfort range T according to the season of the current date. max and T min and the middle value of temperature T mid , take T mid As a temperature control instruction, the air conditioner opening temperature is controlled by the command execution module for a duration of ten minutes, which is used to calculate the environmental parameter QR of the day. The thermal equivalent model formula is as follows:

[0025]

[0026] In the formula, m is the current minute value, T in (m) is the indoor temperature at the mth minute, T o(m) is the outdoor temperature at the mth minute, Δm is the time interval between time m and time m+1, R is the thermal resistance of the enclosure structure, C is the heat capacity of the indoor air, Q is the rated cooling capacity, χ(m)=0 is the room temperature change equation when the air conditioner is stopped, χ(m)=1 is the room temperature change equation when the air conditioner is running, and the outdoor temperature in a short period of time is considered to be consistent. The calculation formulas for the two parameters of the precooling period are as follows:

[0027]

[0028]

[0029] In the formula, is the duration range of the continuous change of the room temperature after the air conditioner stops during the early shutdown period in step S5, is the starting value of the room temperature during the early shutdown period in step S5, is the room temperature termination value of the early shutdown period in step S5, is the outdoor temperature during the early shutdown period in step S5, The duration range of the continuous operation of the air conditioner after it is started in the sensing stage of step S31, causing the room temperature to drop continuously. is the starting value of the room temperature in the sensing stage of step S31, is the room temperature termination value of the sensing stage in step S31, is the outdoor temperature during the shutdown observation period of the previous day in step S5;

[0030] S332: In the shutdown phase, the opening time X of the temperature adjustment phase is derived based on the formula in step S331, and the calculation formula is as follows:

[0031]

[0032] Where, t tpe is the end time of the temperature adjustment stage, ω is the middle temperature value, and T is set o (X), T o (t tpe ), T o (t ppe ) are equal, the calculation formula for the opening time X in the temperature adjustment stage is as follows:

[0033]

[0034] α=ω-T o (t ppe )+QR

[0035] β=T o (t ppe )+T in (t ppe )

[0036] δ=QR

[0037] S333. In the temperature adjustment stage, according to the start-up time X calculated in the shutdown stage, the air conditioner is turned on and the temperature is set to ω, and the control instruction is sent to the command execution module. The command execution module receives the command and controls the air conditioner in real time.

[0038] Specifically, in step S43, the specific steps of the most suitable temperature strategy are:

[0039] S431. Calculate the thermal comfort index of residents. The thermal comfort index of residents is an evaluation index that characterizes the thermal response of the human body. It represents the average value of the hot and cold sensations of most people in the same environment. The formula is as follows:

[0040]

[0041] Where M is the metabolic rate of the human body, W is the mechanical power generated by human activity, and P a is the water vapor partial pressure, T in is the indoor temperature, f cl is the dressing coefficient, T cl is the clothing surface temperature, is the mean radiation temperature, h c is the convective heat transfer coefficient, P a 、f cl 、T cl , and h c The calculation formula is as follows:

[0042]

[0043] In the formula, r h is the relative humidity, V ar is the air velocity, I cl is the thermal resistance of clothing, and its calculation formula is as follows:

[0044]

[0045] Where, T out,6 is the outdoor temperature at 6 a.m.;

[0046] S432. Calculate the carbon emissions during the air conditioning operation phase using the following formula:

[0047] C opr =PλQ P K P / (1-δ)+M ref γGWP ref

[0048] In the formula, P is the power consumed by air conditioning, λ is the proportion of thermal power, Q P is the coal consumption standard for power supply, KP is the CO2 emission factor of standard coal, GWP ref is the global warming potential of the refrigerant, δ is the transmission line loss, M ref is the nameplate refrigerant charge, γ is the leakage rate during the refrigerant service life;

[0049] S433, based on genetic algorithm, the thermal comfort index of residents I PMV and carbon emissions opr As its fitness, the temperature value of the individual with the highest fitness in the population is found through iteration, hybridization and mutation, which is the optimal temperature. After obtaining the optimal temperature, the control command execution module adjusts the air conditioning temperature;

[0050] S434, repeat the above steps every ten minutes to perform real-time processing and control.

[0051] Specifically, the command execution module includes an infrared transmitting module; after the air conditioning adjustment instruction is input into the command execution module, the infrared transmitting module transmits an infrared coded signal to the infrared receiver of the air conditioner to control the air conditioner to adjust the temperature or switch state in real time.

[0052] Specifically, the working steps of the environment perception module are:

[0053] First, the indoor and outdoor temperature and humidity data collected by the sensor are transmitted to the IoT development board in the form of digital signals;

[0054] Secondly, after the IoT development board receives and parses the temperature and humidity data, it encapsulates the temperature and humidity data in sequence through the WiFi module embedded in the IoT development board, and sends them to the message middleware after specifying the topic;

[0055] Finally, the server receives the message from the message middleware by subscribing to the topic, and stores the data in the database after processing.

[0056] Specifically, the working steps of the power collection module are:

[0057] First, the power collection sensor collects the voltage, current and power data of the air conditioner in real time through isolated sampling, and transmits it to the IoT development board in the form of digital signals;

[0058] Secondly, after the IoT development board receives and parses the voltage, current and power data of the air conditioner, it encapsulates the voltage and current data through the WiFi module embedded in the IoT development board, and sends it to the message middleware after specifying the topic;

[0059] Finally, the server receives the message from the message middleware by subscribing to the topic, and stores the data in the database after processing.

[0060] The beneficial effects of the present invention are as follows: the present invention provides a multi-period air conditioning adjustment system and method based on saving electricity carbon costs. The present invention ensures that carbon emissions are reduced while improving human comfort. The operating period in the intelligent decision-making module is set as a supplement and optimization between the pre-cooling period and the early shutdown period. The latest indoor real-time temperature data and air conditioning power consumption data are continuously obtained. The two influencing factors of the calculated carbon emissions during the air conditioning operation stage and the resident thermal comfort index are used as the fitness of the genetic algorithm. The temperature value of the individual with the highest fitness in the population is found through iteration, hybridization, and mutation, which is the optimal temperature. After the optimal temperature is obtained, the control command execution module adjusts the air conditioning temperature. This greatly improves the user's willingness to use the air conditioner on the premise of balancing the relationship between the user experience, air conditioning power consumption, and carbon emissions, and implements automatic load management of the air conditioner. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] The present invention is further described below in conjunction with the accompanying drawings and embodiments.

[0062] Figure 1 is a flow chart of the present invention;

[0063] Figure 2 It is the algorithm diagram of the present invention;

[0064] Figure 3 It is a flow chart of the instruction upload and issuance of the present invention; DETAILED DESCRIPTION

[0065] The present invention will now be described in further detail with reference to the accompanying drawings. These drawings are simplified schematic diagrams, which only illustrate the basic structure of the present invention in a schematic manner, and therefore only show the components related to the present invention.

[0066] Figure 1 is a flow chart of the present invention; Figure 2 It is the algorithm diagram of the present invention; Figure 3 The instruction of the present invention is uploaded

[0067] Flowchart sent.

[0068] The technical solution adopted by the present invention to solve its technical problem is:

[0069] A multi-period air conditioning regulation system based on saving electricity carbon cost, including an environment perception module for collecting indoor and outdoor temperature and humidity data and outputting it to a server, an electric energy collection module for collecting air conditioning power consumption data and outputting it to a server, a server for sending air conditioning regulation instructions to a command execution module according to the indoor and outdoor temperature and humidity data and the air conditioning power consumption data, and a command execution module for receiving the air conditioning regulation instructions and controlling the air conditioning according to the air conditioning regulation instructions; the environment perception module, the electric energy collection module, and the command execution module are all in electrical communication with the server.

[0070] The server includes a database module for storing indoor and outdoor temperature and humidity data and air conditioning power consumption data, and an intelligent decision-making module for controlling the air conditioning to adjust the temperature in real time according to different strategies.

[0071] A multi-period air conditioning adjustment method based on saving electricity carbon cost, the specific steps of the air conditioning adjustment method are:

[0072] S1. Set parameters;

[0073] S2, data collection: the environment sensing module and the power collection module continuously collect indoor and outdoor temperature and humidity data and air conditioning power consumption data at a preset frequency within a preset collection time range, and store the indoor and outdoor temperature and humidity data and air conditioning power consumption data in a database of the server;

[0074] S3, air conditioning reservation: start the intelligent decision-making module at the preset pre-cooling period start time, and calculate the advance start time of the air conditioner based on the time prediction strategy;

[0075] S4, real-time control of air conditioning temperature parameters: within the operating time range, two temperature control strategies are respectively implemented according to the peak and valley periods of electricity consumption. These two strategies are based on their own algorithms and real-time indoor and outdoor temperature and humidity data and air conditioning power consumption data. The air conditioning adjustment instructions are output to the command execution module in real time. After obtaining the instructions, the command execution module controls the air conditioning to adjust the air conditioning temperature or switch in real time, and calculates the start time of the early shutdown period through environmental parameters;

[0076] S5. Shut down the air conditioner in advance: At the start time of the advance shutdown period, the air conditioner shutdown time is calculated through the time prediction strategy. When the shutdown time arrives, the shutdown instruction is output to the command execution module in real time. After the command execution module obtains the instruction, it shuts down the air conditioner in real time.

[0077] In step S3, the working steps of the pre-cooling period are:

[0078] S31, perception stage: briefly turn on the air conditioner, read the real-time indoor and outdoor temperature and humidity data from the database, and update some thermal equivalent model calculation parameters;

[0079] S32, shutdown stage; calculate the air conditioner start time in the temperature adjustment stage according to the thermal equivalent model, and output the shutdown instruction to the command execution module, and the command execution module turns off the air conditioner in real time after obtaining the instruction;

[0080] S33, temperature adjustment stage; according to the air-conditioning start-up time calculated in the shutdown stage, the temperature control instruction is output to the command execution module, and the command execution module adjusts the air-conditioning temperature in real time after obtaining the instruction.

[0081] In step S4, the working steps of the operation period are:

[0082] S41, judging the peak and valley electricity at the current moment;

[0083] S42, when the time is at a peak or peak, a timed start-stop strategy is adopted, a human body temperature comfort range is preset, and an air conditioning start or stop instruction is obtained by judging whether the indoor real-time temperature data in the database reaches the human body temperature comfort range threshold;

[0084] S43. When the time is at a flat or low point, the most suitable temperature strategy is adopted to use the residents' thermal comfort index and carbon emissions as the fitness of the genetic algorithm. Through iteration, hybridization and mutation, the temperature value of the individual with the highest fitness is found to obtain the optimal temperature. This strategy is set to be executed every ten minutes.

[0085] S44. According to the air conditioning control instructions obtained in step S42 and step S43: restart the command execution module at the start time, and output the air conditioning control instructions to the command execution module.

[0086] In step S3, the algorithm of the time prediction strategy is specifically:

[0087] S331. In the perception stage, set the human comfort range T according to the season of the current date. max and T min and the middle value of temperature T mid , take T mid As a temperature control instruction, the air conditioner opening temperature is controlled by the command execution module for a duration of ten minutes, which is used to calculate the environmental parameter QR of the day. The thermal equivalent model formula is as follows:

[0088]

[0089] In the formula, m is the current minute value, T in (m) is the indoor temperature at the mth minute, T o (m) is the outdoor temperature at the mth minute, Δm is the time interval between time m and time m+1, R is the thermal resistance of the enclosure structure, C is the heat capacity of the indoor air, Q is the rated cooling capacity, χ(m)=0 is the room temperature change equation when the air conditioner is stopped, χ(m)=1 is the room temperature change equation when the air conditioner is running, and the outdoor temperature in a short period of time is considered to be consistent. The calculation formulas for the two parameters of the precooling period are as follows:

[0090]

[0091] In the formula, is the duration range of the continuous change of the room temperature after the air conditioner stops during the early shutdown period in step S5, is the starting value of the room temperature during the early shutdown period in step S5, is the room temperature termination value of the early shutdown period in step S5, is the outdoor temperature during the early shutdown period in step S5, The duration range of the continuous operation of the air conditioner after it is started in the sensing stage of step S31, causing the room temperature to drop continuously. is the starting value of the room temperature in the sensing stage of step S31, is the room temperature termination value of the sensing stage in step S31, is the outdoor temperature during the shutdown observation period of the previous day in step S5;

[0092] S332: In the shutdown phase, the opening time X of the temperature adjustment phase is derived based on the formula in step S331, and the calculation formula is as follows:

[0093]

[0094] Where, t tpe is the end time of the temperature adjustment stage, ω is the middle temperature value, and T is set o (X), T o (t tpe ), T o (t ppe ) are equal, the calculation formula for the opening time X in the temperature adjustment stage is as follows:

[0095]

[0096] α=ω-T o (t ppe )+QR

[0097] β=T o (t ppe )+T in (t ppe )

[0098] δ=QR

[0099] S333. In the temperature adjustment stage, according to the start-up time X calculated in the shutdown stage, the air conditioner is turned on and the temperature is set to ω, and the control instruction is sent to the command execution module. The command execution module receives the command and controls the air conditioner in real time.

[0100] In step S43, the specific steps of the most suitable temperature strategy are:

[0101] S431. Calculate the thermal comfort index of residents. The thermal comfort index of residents is an evaluation index that characterizes the thermal response of the human body. It represents the average value of the hot and cold sensations of most people in the same environment. The formula is as follows:

[0102]

[0103] Where M is the metabolic rate of the human body, W is the mechanical power generated by human activity, and P ais the water vapor partial pressure, T in is the indoor temperature, f cl is the dressing coefficient, T cl is the clothing surface temperature, is the mean radiation temperature, h c is the convective heat transfer coefficient, P a 、f cl 、T cl , and h c The calculation formula is as follows:

[0104]

[0105] In the formula, r h is the relative humidity, V ar is the air velocity, I cl is the thermal resistance of clothing, and its calculation formula is as follows:

[0106]

[0107] Where, T out,6 is the outdoor temperature at 6 a.m.;

[0108] S432. Calculate the carbon emissions during the air conditioning operation phase using the following formula:

[0109] C opr =PλQ P K P / (1-δ)+M ref γGWP ref

[0110] In the formula, P is the power consumed by air conditioning, λ is the proportion of thermal power, Q P is the coal consumption standard for power supply, K P is the CO2 emission factor of standard coal, GWP ref is the global warming potential of the refrigerant, δ is the transmission line loss, M ref is the nameplate refrigerant charge, γ is the leakage rate during the refrigerant service life;

[0111] S433, based on genetic algorithm, the thermal comfort index of residents I PMV and carbon emissions opr As its fitness, the temperature value of the individual with the highest fitness in the population is found through iteration, hybridization and mutation, which is the optimal temperature. After obtaining the optimal temperature, the control command execution module adjusts the air conditioning temperature;

[0112] S434, repeat the above steps every ten minutes to perform real-time processing and control.

[0113] The command execution module includes an infrared transmitting module; after the air conditioning adjustment instruction is input into the command execution module, the infrared transmitting module transmits an infrared coded signal to the infrared receiver of the air conditioner to control the air conditioner to adjust the temperature or switch state in real time.

[0114] The working steps of the environment perception module are:

[0115] First, the indoor and outdoor temperature and humidity data collected by the sensor are transmitted to the IoT development board in the form of digital signals;

[0116] Secondly, after the IoT development board receives and parses the temperature and humidity data, it encapsulates the temperature and humidity data in sequence through the WiFi module embedded in the IoT development board, and sends them to the message middleware after specifying the topic;

[0117] Finally, the server receives the message from the message middleware by subscribing to the topic, and stores the data in the database after processing.

[0118] The working steps of the power collection module are:

[0119] First, the power collection sensor collects the voltage, current and power data of the air conditioner in real time through isolated sampling, and transmits it to the IoT development board in the form of digital signals;

[0120] Secondly, after the IoT development board receives and parses the voltage, current and power data of the air conditioner, it encapsulates the voltage and current data through the WiFi module embedded in the IoT development board, and sends it to the message middleware after specifying the topic;

[0121] Finally, the server receives the message from the message middleware by subscribing to the topic, and stores the data in the database after processing.

[0122] The embodiments are:

[0123] 1. Design Process

[0124] 1. Design the environmental perception module and the power collection module, use the temperature and humidity sensors and the power collection sensors to collect the indoor and outdoor temperature and humidity data and the air conditioning power consumption data, and persist the data in the database through the Internet of Things development board, the message middleware and the backend.

[0125] The environmental perception module is specifically as follows: the temperature and humidity sensor collects temperature and humidity data at intervals, and transmits the data to the Internet of Things development board in the form of digital signals through the serial port. The Internet of Things development board receives the data and parses it into readable temperature and humidity data, and then encapsulates the temperature and humidity data through the WiFi (Wireless Fidelity) module in the Internet of Things development board, specifies the topic, and sends it to the message middleware. The data transmission protocol used in this process is the MQTT (Message Queuing Telemetry Transport) protocol; finally, the server subscribes to the topic through the MQTT protocol, receives the message in the message middleware, and persists the data in the database after processing.

[0126] The specific power collection module is as follows: the power collection sensor collects the air conditioner voltage, current and power data at intervals, and transmits the three data to the Internet of Things development board in the form of digital signals through the serial port. The Internet of Things development board receives the data and parses it into readable voltage, current and power data. After the voltage, current and power data are encapsulated through the WiFi module in the Internet of Things development board, the topic is specified and sent to the message middleware through the MQTT protocol. Finally, the server subscribes to the topic, receives the message in the message middleware, and persists the data in the database after processing.

[0127] 2. Design an intelligent decision-making module, which is divided into pre-cooling period, operation period and early shutdown period according to the time period. Different control strategies are used in different time periods to set the start and stop time of the air conditioner and control the air conditioner to adjust the temperature in real time;

[0128] The smart decision-making module is as follows:

[0129] 2.1. Enter the pre-cooling period. The air conditioner start-up time is calculated based on real-time temperature and humidity data and the thermal equivalent model.

[0130] The pre-cooling stage is as follows:

[0131] 2.1.1. Set the human comfort range T according to the season of the current date max and T min and the middle value of temperature T mid , take T mid As a temperature control instruction, the air conditioner is turned on at a temperature controlled by the command execution module for a duration of ten minutes. Combined with the real-time temperature and humidity data obtained from the database, the environmental parameter QR of the day is calculated. The thermal equivalent model formula is as follows:

[0132]

[0133] In the formula, m is the current minute value, T in (m) is the indoor temperature at the mth minute, T o(m) is the outdoor temperature at the mth minute, Δm is the time interval between time m and time m+1, R is the thermal resistance of the enclosure structure, C is the heat capacity of the indoor air, Q is the rated cooling capacity, χ(m)=0 is the room temperature change equation when the air conditioner is stopped, and χ(m)=1 is the room temperature change equation when the air conditioner is running. The outdoor temperature in a short period of time is considered to be consistent. According to the thermal equivalent model, the calculation formulas of the two key parameters of the pre-cooling period can be derived as follows:

[0134]

[0135] In the formula, To predict the duration of room temperature changes after the air conditioner stops during the downtime period. is the starting value of room temperature during the early shutdown period, is the room temperature termination value of the early shutdown period, is the outdoor temperature during the early shutdown period, The duration range of the continuous operation of the air conditioner after it is started in the perception stage, causing the room temperature to drop continuously. is the starting value of room temperature in the sensing stage, is the room temperature termination value of the sensing stage, The outdoor temperature during the shutdown observation period of the previous day;

[0136] D2) Shutdown stage: The air conditioner start time in the temperature adjustment stage is calculated according to the thermal equivalent model, and the shutdown command is output to the command execution module. The command execution module turns off the air conditioner in real time after obtaining the command; the calculation formula is as follows:

[0137]

[0138] Where, t tpe is the end time of the temperature adjustment stage, ω is the middle temperature value, and since the outdoor temperature difference can be ignored in a short time, T is set o (X), T o (t tpe ), T o (t ppe ) are equal, the calculation formula for the opening time X in the temperature adjustment stage can be derived as follows:

[0139]

[0140] α=ω-T o (t ppe )+QR

[0141] β=T o (t ppe )+T in (t ppe )

[0142] δ=QR2.1.3, temperature adjustment stage; according to the opening time X calculated in the shutdown stage, turn on the air conditioner and set the temperature to ω, send the control instruction to the command execution module, the command execution module receives the command and controls the air conditioner in real time.

[0143] 2.2. Entering the operation period. According to the peak and valley periods of electricity consumption, two temperature control strategies are implemented respectively. When the time is at a flat period / valley period, the most suitable temperature strategy is adopted.

[0144] Among them, the most suitable temperature strategy is as follows:

[0145] 2.2.1. Calculate the thermal comfort index of residents. The thermal comfort index of residents is an evaluation index that characterizes the thermal response of the human body. It represents the average value of the hot and cold sensations of most people in the same environment. The formula is as follows:

[0146]

[0147] Where M is the metabolic rate of the human body, W is the mechanical power generated by human activity, and P a is the water vapor partial pressure, T in is the indoor temperature, f cl is the dressing coefficient, T cl is the clothing surface temperature, is the mean radiation temperature, h c is the convective heat transfer coefficient, P a 、f cl 、T cl , and h c The calculation formula is as follows:

[0148]

[0149] In the formula, r h is the relative humidity, V ar is the air velocity, I cl is the thermal resistance of clothing, and its calculation formula is as follows:

[0150]

[0151] Where, T out,6 is the outdoor temperature at 6 a.m.;

[0152] D2) Calculate the carbon emissions during the air conditioning operation phase, the formula is as follows:

[0153] C opr =PλQ P K P / (1-δ)+M ref γGWP ref

[0154] In the formula, P is the power consumed by air conditioning, λ is the proportion of thermal power, Q P is the coal consumption standard for power supply, K P is the CO2 emission factor of standard coal, GWP ref is the global warming potential of the refrigerant, δ is the transmission line loss, M ref is the nameplate refrigerant charge, γ is the leakage rate during the refrigerant service life;

[0155] 2.2.3. Based on genetic algorithm, the residents’ thermal comfort index I PMV and carbon emissions opr As its fitness, the temperature value of the individual with the highest fitness in the population is found through iteration, hybridization and mutation, which is the optimal temperature. After obtaining the optimal temperature, the control command execution module adjusts the air conditioning temperature.

[0156] 2.2.4. Repeat the above steps every ten minutes for real-time processing and control.

[0157] 2. Parameter settings

[0158] In the time setting, set t start is 7:30, i.e. the 450th minute. Set t ppe is 7:40, i.e. the 460th minute. Set t tpe is 8:30, i.e., the 510th minute. Set t tse1 is 11:00, i.e. the 660th minute. Set t ose1 is 15:00, i.e. the 900th minute. Set t tse2 is 17:00, i.e. the 1020th minute. Set t end It is 17:30, which is the 1050th minute.

[0159] In the perception stage, the human comfort range T max and T min and the middle value of temperature T mid Changes with the seasons: In spring and summer, the human comfort range is 24-26℃, with the median temperature being 25℃; in autumn and winter, the human comfort range is 20-22℃, with the median temperature being 21℃.

[0160] In the parameter setting of the resident thermal comfort index formula during operation, considering that most of the people in the room are office workers, M is taken as the state of people sitting and typing, which is about 1.1met. W can be ignored in most activities. For office environment, the air flow rate V ar Usually around 0.1 m / s.

[0161] In the calculation formula of carbon emissions during the equipment operation phase, P is obtained from the power collection module, λ accounts for 67.9% in 2020 and is expected to account for 49.2% by 2030. The annual proportion can be calculated by linear interpolation, Q P Set to 0.3kg / (kWh), K P Set to 2.8495kgCO2 / kg, GWP ref is set to 170, δ is set to 5.6%, M ref Set to 4.5kg and γ to 6%.

[0162] 3. Implementation Process

[0163] Combined with Figure 1 and attached Figure 3 As shown, the implementation process of this embodiment is specifically as follows:

[0164] 1) The environmental perception module collects indoor and outdoor temperature and humidity data every one minute during the preset working hours, that is, from 7 a.m. to 6 p.m. The data is input into the server through the Internet of Things development board and the message middleware and is persisted as the data source for the entire system.

[0165] 2) The intelligent decision-making module is executed in advance before going to work, and is set to 7:30 am to 5:30 pm. First, it enters the pre-cooling period. After the perception stage and the shutdown stage, the start time of the temperature adjustment stage is calculated through the time prediction strategy. When the time arrives, the command execution module sends a command to turn on the air conditioner. At 8:30 in the morning, it can ensure that the temperature is within the comfortable temperature range for the human body. After that, it enters the operation period. When the time is at a peak, the timed start and stop strategy is adopted. When the time is at a flat section / trough, the most suitable temperature strategy is adopted. The triggering time of the timed start and stop strategy depends on whether the real-time detected indoor temperature data reaches the threshold. The most suitable temperature strategy is set to execute once every ten minutes. Finally, it enters the early shutdown period, and the time to shut down the air conditioner in advance is calculated according to the time prediction strategy.

[0166] IV. Implementation Results

[0167] This embodiment carried out a series of comparative experiments in the laboratory to prove the effectiveness of this method. In terms of the impact on room temperature, without air conditioning, the indoor temperature was between 29°C and 31.5°C, the indoor temperature was between 40% RH and 50% RH, and the humidity reached a lower value between 11:00 and 13:00. The reason for the difference in indoor and outdoor temperature and humidity is that the experimental date was June, which was rainy and cloudy. The continuous rain caused the outdoor temperature to be lower than the indoor temperature, and the outdoor humidity was much higher than the indoor humidity. When the air conditioner was manually operated, after working hours, the air conditioner was manually turned on, a lower temperature was set, and the temperature was adjusted around 15:00 and 16:30, which was highly spontaneous and irregular. When the algorithm intervened, there was a significant temperature drop after 7:00, which lasted for 10 minutes. This stage was the perception stage. After that, the temperature rose, and this stage was the shutdown stage. At around 8:20, the temperature adjustment stage was entered, and the indoor temperature reached about 25°C at 8:30 when working hours. 8:30 to 11:00, the room temperature is within the human comfort range T max and T min The room temperature fluctuates back and forth between 11:00 and 15:00, which is affected by the timed start-stop strategy. From 15:00 to 17:00, the room temperature fluctuation amplitude decreases and the change interval shortens, which is affected by the most suitable temperature strategy. From 17:00 to 17:10, the room temperature is affected by the timed start-stop strategy, and then enters the early shutdown period, the air conditioner is turned off, and at 17:30 when it is time to get off work, the indoor temperature is still within the human comfort range.

[0168] In terms of the impact on power consumption, the air conditioner consumes 3.02 kWh of electricity per day when the algorithm intervenes, the slope of the power consumption line graph is relatively gentle, and the power changes frequently. When the air conditioner is manually operated, the air conditioner consumes 5.68 kWh of electricity per day, the slope of the power consumption line graph is relatively steep, and the power changes are relatively small. Compared with the method of manually operating the air conditioner, the power of the air conditioner changes more frequently when the algorithm intervenes. The reason for this phenomenon is that in addition to the constant temperature control technology that comes with the air conditioner, the timed start-stop strategy plays a great role. The power consumption data of the air conditioner is much smaller than that of the manual operation of the air conditioner. The energy consumption difference in one day reaches 2.66 kWh. There are three reasons for this difference. First, the timed start-stop strategy saves some energy consumption by intermittently shutting down the air conditioner. Secondly, the genetic algorithm in the most suitable temperature strategy introduces the consideration of carbon emissions, and electric energy is an element of the carbon emission calculation formula and is proportional to it. Therefore, when the most suitable temperature strategy is executed, it will also affect the power consumption of the air conditioner. Finally, some energy consumption is also saved by setting the pre-cooling period and the early shutdown period.

[0169] Based on the above ideal embodiments of the present invention, the relevant staff can make various changes and modifications without departing from the technical concept of the present invention through the above description. The technical scope of the present invention is not limited to the contents of the specification, and its technical scope must be determined according to the scope of the claims.

Claims

1. A multi-period air conditioning system based on saving electricity carbon cost, characterized in that: It includes an environment perception module for collecting indoor and outdoor temperature and humidity data and outputting them to a server, an energy collection module for collecting air-conditioning power consumption data and outputting them to a server, a server for sending air-conditioning adjustment instructions to a command execution module based on indoor and outdoor temperature and humidity data and air-conditioning power consumption data, and a command execution module for receiving air-conditioning adjustment instructions and controlling the air-conditioning according to the air-conditioning adjustment instructions; the environment perception module, the energy collection module, and the command execution module all communicate electrically with the server.

2. The multi-period air conditioning system based on saving electricity carbon cost according to claim 1 is characterized in that: The server includes a database module for storing indoor and outdoor temperature and humidity data and air conditioning power consumption data, and an intelligent decision-making module for controlling the air conditioning to adjust the temperature in real time according to different strategies.

3. The multi-period air conditioning adjustment method based on saving electricity carbon cost according to claim 1 or 2 is characterized in that: The specific steps of the air conditioning adjustment method are: S1. Set parameters; S2, data collection: the environment sensing module and the power collection module continuously collect indoor and outdoor temperature and humidity data and air conditioning power consumption data at a preset frequency within a preset collection time range, and store the indoor and outdoor temperature and humidity data and air conditioning power consumption data in a database of the server; S3, air conditioning reservation: start the intelligent decision-making module at the preset pre-cooling period start time, and calculate the advance start time of the air conditioner based on the time prediction strategy; S4, real-time control of air conditioning temperature parameters: within the operating time range, two temperature control strategies are respectively implemented according to the peak and valley periods of electricity consumption. These two strategies are based on their own algorithms and real-time indoor and outdoor temperature and humidity data and air conditioning power consumption data. The air conditioning adjustment instructions are output to the command execution module in real time. After obtaining the instructions, the command execution module controls the air conditioning to adjust the air conditioning temperature or switch in real time, and calculates the start time of the early shutdown period through environmental parameters; S5. Shut down the air conditioner in advance: At the start time of the advance shutdown period, the air conditioner shutdown time is calculated through the time prediction strategy. When the shutdown time arrives, the shutdown instruction is output to the command execution module in real time. After the command execution module obtains the instruction, it shuts down the air conditioner in real time.

4. The multi-period air conditioning adjustment method based on saving electricity carbon cost according to claim 3 is characterized in that: In step S3, the working steps of the pre-cooling period are: S31, perception stage: briefly turn on the air conditioner, read the real-time indoor and outdoor temperature and humidity data from the database, and update some thermal equivalent model calculation parameters; S32, shutdown stage; calculate the air conditioner start time in the temperature adjustment stage according to the thermal equivalent model, and output the shutdown instruction to the command execution module, and the command execution module turns off the air conditioner in real time after obtaining the instruction; S33, temperature adjustment stage; according to the air-conditioning start-up time calculated in the shutdown stage, the temperature control instruction is output to the command execution module, and the command execution module adjusts the air-conditioning temperature in real time after obtaining the instruction.

5. The multi-period air conditioning adjustment method based on saving electricity carbon cost according to claim 3 is characterized in that: In step S4, the working steps of the operation period are: S41, judging the peak and valley electricity at the current moment; S42, when the time is at a peak or peak, a timed start-stop strategy is adopted, a human body temperature comfort range is preset, and an air conditioning start or stop instruction is obtained by judging whether the indoor real-time temperature data in the database reaches the human body temperature comfort range threshold; S43. When the time is at a flat or low point, the most suitable temperature strategy is adopted to use the residents' thermal comfort index and carbon emissions as the fitness of the genetic algorithm. Through iteration, hybridization and mutation, the temperature value of the individual with the highest fitness is found to obtain the optimal temperature. This strategy is set to be executed every ten minutes. S44. According to the air conditioning control instructions obtained in step S42 and step S43: restart the command execution module at the start time, and output the air conditioning control instructions to the command execution module.

6. The multi-period air conditioning adjustment method based on saving electricity carbon cost according to claim 4 is characterized in that: In step S3, the algorithm of the time prediction strategy is specifically: S331. In the perception stage, set the human comfort range T according to the season of the current date. max and T min and the middle value of temperature T mid , take T mid As a temperature control instruction, the air conditioner opening temperature is controlled by the command execution module for a duration of ten minutes, which is used to calculate the environmental parameter QR of the day. The thermal equivalent model formula is as follows: In the formula, m is the current minute value, T in (m) is the indoor temperature at the mth minute, T o (m) is the outdoor temperature at the mth minute, Δm is the time interval between time m and time m+1, R is the thermal resistance of the enclosure structure, C is the heat capacity of the indoor air, Q is the rated cooling capacity, χ(m)=0 is the room temperature change equation when the air conditioner is stopped, χ(m)=1 is the room temperature change equation when the air conditioner is running, and the outdoor temperature in a short period of time is considered to be consistent. The calculation formulas for the two parameters of the precooling period are as follows: In the formula, is the duration range of the continuous change of the room temperature after the air conditioner stops during the early shutdown period in step S5, is the starting value of the room temperature during the early shutdown period in step S5, is the room temperature termination value of the early shutdown period in step S5, is the outdoor temperature during the early shutdown period in step S5, The duration range of the continuous operation of the air conditioner after it is started in the sensing stage of step S31, causing the room temperature to drop continuously. is the starting value of the room temperature in the sensing stage of step S31, is the room temperature termination value of the sensing stage in step S31, is the outdoor temperature during the shutdown observation period of the previous day in step S5; S332: In the shutdown phase, the opening time X of the temperature adjustment phase is derived based on the formula in step S331, and the calculation formula is as follows: Where, t tpe is the end time of the temperature adjustment stage, ω is the middle temperature value, and T is set o (X), T o (t tpe ), T o (t ppe ) are equal, the calculation formula for the opening time X in the temperature adjustment stage is as follows: α=ω-T o (t ppe )+QR β=T o (t ppe )+T in (t ppe ) δ=QR S333. In the temperature adjustment stage, according to the start-up time X calculated in the shutdown stage, the air conditioner is turned on and the temperature is set to ω, and the control instruction is sent to the command execution module. The command execution module receives the command and controls the air conditioner in real time.

7. The multi-period air conditioning adjustment method based on saving electricity carbon cost according to claim 5 is characterized in that: In step S43, the specific steps of the most suitable temperature strategy are: S431. Calculate the thermal comfort index of residents. The thermal comfort index of residents is an evaluation index that characterizes the thermal response of the human body. It represents the average value of the hot and cold sensations of most people in the same environment. The formula is as follows: Where M is the metabolic rate of the human body, W is the mechanical power generated by human activity, and P a is the water vapor partial pressure, T in is the indoor temperature, f cl is the dressing coefficient, T cl is the clothing surface temperature, is the mean radiation temperature, h c is the convective heat transfer coefficient, P a 、f cl 、T cl , and h c The calculation formula is as follows: In the formula, r h is the relative humidity, V ar is the air velocity, I cl is the thermal resistance of clothing, and its calculation formula is as follows: Where, T out,6 is the outdoor temperature at 6 a.m.; S432. Calculate the carbon emissions during the air conditioning operation phase using the following formula: C opr =PλQ P K P / (1-d)+M ref γGWP ref In the formula, P is the power consumed by air conditioning, λ is the proportion of thermal power, Q P is the coal consumption standard for power supply, K P is the CO2 emission factor of standard coal, GWP ref is the global warming potential of the refrigerant, δ is the transmission line loss, M ref is the nameplate refrigerant charge, γ is the leakage rate during the refrigerant service life; S433, based on genetic algorithm, the thermal comfort index of residents I PMV and carbon emissions opr As its fitness, the temperature value of the individual with the highest fitness in the population is found through iteration, hybridization and mutation, which is the optimal temperature. After obtaining the optimal temperature, the control command execution module adjusts the air conditioning temperature; S434, repeat the above steps every ten minutes to perform real-time processing and control.

8. The multi-period air conditioning adjustment method based on saving electricity carbon cost according to claim 3 is characterized in that: The command execution module includes an infrared transmitting module; after the air conditioner adjustment instruction is input into the command execution module, the infrared transmitting module transmits an infrared coded signal to the infrared receiver of the air conditioner to control the air conditioner to adjust the temperature or switch state in real time.

9. The multi-period air conditioning adjustment method based on saving electricity carbon cost according to claim 3 is characterized in that: The working steps of the environment perception module are: First, the indoor and outdoor temperature and humidity data collected by the sensor are transmitted to the IoT development board in the form of digital signals; Secondly, after the IoT development board receives and parses the temperature and humidity data, it encapsulates the temperature and humidity data in sequence through the WiFi module embedded in the IoT development board, and sends them to the message middleware after specifying the topic; Finally, the server receives the message from the message middleware by subscribing to the topic, and stores the data in the database after processing.

10. The multi-period air conditioning adjustment method based on saving electricity carbon cost according to claim 3 is characterized in that: The working steps of the power collection module are as follows: First, the power collection sensor collects the voltage, current and power data of the air conditioner in real time through isolated sampling, and transmits it to the IoT development board in the form of digital signals; Secondly, after the IoT development board receives and parses the voltage, current and power data of the air conditioner, it encapsulates the voltage and current data through the WiFi module embedded in the IoT development board, and sends it to the message middleware after specifying the topic; Finally, the server receives the message from the message middleware by subscribing to the topic, and stores the data in the database after processing.

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