Method, device and system for regulating and controlling electricity consumption of household appliances and medium

Abstract

The invention provides a household electrical appliance power consumption regulation and control method, device and system and a medium. The method comprises the following steps: acquiring a power consumption expectation parameter, a green power correction power supply period parameter and a household electrical appliance power consumption characteristic; and according to the electricity consumption expectation parameter and the green electricity correction power supply period parameter, analyzing the electricity consumption characteristics of the household appliance, and determining the optimal electricity consumption period of the household appliance through a multi-objective optimization algorithm, thereby calculating a household appliance starting strategy in real time, and realizing regulation and control of the household appliance. Compared with the prior art, electricity utilization characteristics of the household appliances are also considered besides an electricity price factor, a plurality of factors are analyzed by combining an electricity utilization expectation parameter and a green electricity correction power supply period parameter, the optimal electricity utilization period of the household appliances is determined by utilizing a multi-target optimization algorithm, then a household appliance starting strategy is calculated, and the household appliances are regulated and controlled in real time. The accuracy of regulation and control is effectively improved, and the purpose of effectively reducing energy consumption is achieved.

Description

Technical Field

[0001] The present invention application relates to the field of power regulation, and particularly to a method, device, system and medium for regulating the power consumption of household appliances. Background Art

[0002] With the development of economy and technology and the deepening of the processes of industrialization and urbanization, the number of newly added distributed photovoltaic, wind power and other new energy power generation facilities and electric vehicle charging piles in each distribution transformer substation area (hereinafter referred to as the substation area) is increasing continuously, and the power consumption of household appliances is also rising day by day, and the contradiction between power supply and demand is becoming increasingly prominent. The access of distributed new energy and the charging demands of various different appliances have brought a certain impact on the stable operation of the power grid and are likely to cause the imbalance of power supply and demand in the substation area. The existing technologies mainly consider the electricity prices at different time periods and determine the regulation strategies for household appliances from the economic level, but often ignore the power consumption characteristics of household appliances themselves. Therefore, the existing regulation methods lack sufficient accuracy. Summary of the Invention

[0003] The present invention application provides a method, device, system and medium for regulating the power consumption of household appliances to solve the technical problem of how to improve the accuracy of regulation.

[0004] To solve the above technical problem, the present invention application provides a method for regulating the power consumption of household appliances, including:

[0005] Obtaining power consumption expectation parameters, green power corrected power supply period parameters and household appliance power consumption characteristics, where the household appliance power consumption characteristics include the intensive power consumption duration, sparse power consumption unit power and total power consumption duration of the household appliance;

[0006] Analyzing the household appliance power consumption characteristics according to the power consumption expectation parameters and the green power corrected power supply period parameters, and determining the optimal power consumption period of the household appliance through a multi-objective optimization algorithm, and then calculating the household appliance start-up strategy in real time;

[0007] Regulating the household appliance through the household appliance start-up strategy.

[0008] As a preferred solution, the power consumption expectation parameters include the expected household appliance working end time and the expected household appliance start time; the green power corrected power supply period parameters include the green power corrected power supply start time, the green power corrected power supply end time and the green power corrected power supply price;

[0009] The analyzing the household appliance power consumption characteristics according to the power consumption expectation parameters and the green power corrected power supply period parameters, and determining the optimal power consumption period of the household appliance through a multi-objective optimization algorithm, and then calculating the household appliance start-up strategy in real time includes:

[0010] Taking the expected end time of the home appliance operation and the total power consumption duration as constraint conditions, taking the power supply price and the expected start time of the home appliance as control objectives, correcting the power supply period parameters according to the green electricity, analyzing the power consumption characteristics of the home appliance, determining the optimal power consumption period of the home appliance, and then calculating the home appliance startup strategy in real time.

[0011] As a preferred solution, the method for obtaining the green electricity corrected power supply price includes:

[0012] Obtaining relevant variables of photovoltaic power generation with the same time scale and the same time stamp as the time-of-use electricity price;

[0013] Based on the relevant variables, predicting the change value of the photovoltaic backplane temperature, and then calculating the corrected power generation power; predicting the change value of the power generation power based on the relevant variables;

[0014] Based on the sum of the corrected power generation power and the change value of the power generation power, obtaining the corrected power generation power value;

[0015] Normalizing, approximating, and segmentally quantifying the corrected power generation power value to obtain multiple change amplitude intervals;

[0016] According to the multiple change amplitude intervals and the preset mapping relationship between the electricity price and the change amplitude intervals, calculating and obtaining the predicted green electricity corrected electricity price with the same time scale and time stamp as the time-of-use electricity price, to obtain the green electricity corrected power supply price.

[0017] As a preferred solution, before obtaining the power consumption expectation parameters, the green electricity corrected power supply period parameters, and the power consumption characteristics of the home appliance, it further includes:

[0018] Identifying the types of home appliances connected, where the types of home appliances include all-weather operating home appliances, adjustable home appliances, flexible power consumption home appliances, and home appliances for specific time periods;

[0019] Verifying the connected home appliances through a wireless communication interface;

[0020] When the verification is passed, classifying and storing the home appliance characteristics of the connected home appliances according to the types of the connected home appliances.

[0021] As a preferred solution, the regulation method for the power consumption of the home appliance further includes:

[0022] Obtaining time-of-use power consumption parameters, identifying the time-of-use power consumption parameters, and obtaining the electricity price period, the start time and the end time of the electricity price period;

[0023] According to the real-time clock, the start time and the end time of the electricity price period, judging the temperature control instruction of the home appliance, and using the temperature control instruction to regulate the home appliance.

[0024] Correspondingly, the present invention application also provides a regulation device for household appliances using electricity, including an acquisition module, an analysis module, and a regulation module; wherein,

[0025] The acquisition module is used to acquire the electricity consumption expectation parameters, the green power corrected power supply period parameters, and the household appliance electricity consumption characteristics, where the household appliance electricity consumption characteristics include the intensive electricity consumption duration of the household appliance, the sparse electricity consumption unit power, and the total electricity consumption duration;

[0026] The analysis module is used to analyze the household appliance electricity consumption characteristics according to the electricity consumption expectation parameters and the green power corrected power supply period parameters, and determine the optimal electricity consumption period of the household appliance through a multi-objective optimization algorithm, and then calculate the household appliance startup strategy in real time;

[0027] The regulation module is used to regulate the household appliance through the household appliance startup strategy.

[0028] As a preferred solution, the electricity consumption expectation parameters include the expected household appliance working end time and the expected household appliance startup time; the green power corrected power supply period parameters include the green power corrected power supply start time, the green power corrected power supply end time, and the green power corrected power supply price;

[0029] The analysis module analyzes the household appliance electricity consumption characteristics according to the electricity consumption expectation parameters and the green power corrected power supply period parameters, and determines the optimal electricity consumption period of the household appliance through a multi-objective optimization algorithm, and then calculates the household appliance startup strategy in real time, including:

[0030] The analysis module takes the expected household appliance working end time and the total electricity consumption duration as constraint conditions, takes the power supply price and the expected household appliance startup time as control objectives, analyzes the household appliance electricity consumption characteristics according to the green power corrected power supply period parameters, determines the optimal electricity consumption period of the household appliance, and then calculates the household appliance startup strategy in real time.

[0031] As a preferred solution, the method for obtaining the green power corrected power supply price includes:

[0032] The acquisition module acquires the relevant variables of photovoltaic power generation with the same time scale and the same time stamp as the time-of-use electricity price;

[0033] Based on the relevant variables, predict the change value of the photovoltaic backplane temperature, and then calculate the corrected power generation power; based on the relevant variables, predict the change value of the power generation power;

[0034] Based on the sum of the corrected power generation power and the change value of the power generation power, obtain the corrected power generation power value;

[0035] Normalize, approximate, and segmentally quantize the corrected power generation power value to obtain multiple change amplitude intervals;

[0036] According to the multiple change range intervals and the preset mapping relationship between the electricity price and the change range intervals, a predicted green power corrected electricity price with the same time scale and time stamp as the time-of-use electricity price is calculated to obtain the green power corrected power supply electricity price.

[0037] As a preferred solution, the control device further includes a classification storage module, and the classification storage module is used before obtaining the electricity consumption expectation parameters, the green power corrected power supply time period parameters, and the household appliance electricity consumption characteristics:

[0038] Identify the types of household appliances connected, and the types of household appliances include all-weather operating household appliances, adjustable household appliances, flexible electricity consumption household appliances, and household appliances with electricity consumption at specific time periods;

[0039] Verify the connected household appliances through a wireless communication interface;

[0040] When the verification is passed, classify and store the household appliance characteristics of the connected household appliances according to the types of the connected household appliances.

[0041] As a preferred solution, the control device further includes a temperature adjustment module, and the temperature adjustment module is used to: obtain time-of-use electricity consumption parameters, identify the time-of-use electricity consumption parameters, and obtain the electricity price time period, the start time and the end time of the electricity price time period;

[0042] Judge the temperature control instruction of the household appliance according to the real-time clock, the start time and the end time of the electricity price time period, and use the temperature control instruction to control the household appliance.

[0043] Correspondingly, the present invention application also provides a control system for household appliance electricity consumption, and the control system is used to execute the control method for household appliance electricity consumption in any of the above embodiments; the control system includes a metering master station, a measurement terminal, an electric meter, a gateway, a control terminal, and a socket.

[0044] As a preferred solution, the gateway includes a first carrier communication module, an electric meter interface, a first microprocessor module, and a first watchdog IC module; the gateway is connected to the measurement terminal and the socket through the carrier communication module, and the gateway is connected to the electric meter through the electric meter interface;

[0045] The first microprocessor module is used to execute the following steps before obtaining the electricity consumption expectation parameters, the green power corrected power supply time period parameters, and the household appliance electricity consumption characteristics:

[0046] Identify the types of household appliances connected, and the types of household appliances include all-weather operating household appliances, adjustable household appliances, flexible electricity consumption household appliances, and household appliances with electricity consumption at specific time periods;

[0047] Verify the connected household appliances through a wireless communication interface;

[0048] When the verification is passed, classify and store the appliance characteristics of the connected appliance according to the type of the connected appliance.

[0049] As a preferred solution, the socket includes an infrared control module, a Bluetooth communication module, a voice interface module, a metering module, a temperature measurement module, a relay control module, a second carrier communication module, and a second microprocessor module; the socket is connected to the gateway through the second carrier communication module;

[0050] Among them, the second microprocessor module is used to execute the following steps:

[0051] Obtain the electricity consumption expectation parameters, green power corrected power supply period parameters, and appliance electricity consumption characteristics, where the appliance electricity consumption characteristics include the intensive electricity consumption duration, sparse electricity consumption unit power, and total electricity consumption duration of the appliance;

[0052] Analyze the appliance electricity consumption characteristics according to the electricity consumption expectation parameters and the green power corrected power supply period parameters, and determine the optimal electricity consumption period of the appliance through a multi-objective optimization algorithm, and then calculate the appliance startup strategy in real time;

[0053] Regulate the appliance through the appliance startup strategy.

[0054] Correspondingly, the present invention application also provides a computer-readable storage medium, the computer-readable storage medium includes a stored computer program, wherein when the computer program runs, it controls the device where the computer-readable storage medium is located to execute the appliance electricity consumption regulation method according to any one of the above embodiments.

[0055] Compared with the prior art, the present invention application has the following beneficial effects:

[0056] The present invention application provides a method, device, system and medium for regulating the electricity consumption of household appliances. The method includes: obtaining electricity consumption expectation parameters, green power corrected power supply period parameters and household appliance electricity consumption characteristics, where the household appliance electricity consumption characteristics include the intensive electricity consumption duration, sparse electricity consumption unit power and total electricity consumption duration of the household appliance; analyzing the household appliance electricity consumption characteristics according to the electricity consumption expectation parameters and green power corrected power supply period parameters, and determining the optimal electricity consumption period of the household appliance through a multi-objective optimization algorithm, and then calculating the household appliance startup strategy in real time; regulating the household appliance through the household appliance startup strategy. Compared with the prior art, the present application not only considers the electricity price factor but also considers the household appliance electricity consumption characteristics, specifically including factors such as the intensive electricity consumption duration, sparse electricity consumption unit power and total electricity consumption duration of the household appliance, and combines the electricity consumption expectation parameters and green power corrected power supply period parameters, analyzes these factors, uses a multi-objective optimization algorithm to determine the optimal electricity consumption period of the household appliance, and then calculates the household appliance startup strategy and regulates the household appliance in real time, effectively improving the accuracy of regulation and achieving the purpose of effectively reducing energy consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 : It is a schematic flowchart of an embodiment of the method for regulating the electricity consumption of household appliances provided by the present invention application.

[0058] Figure 2 : It is a schematic diagram of the electricity consumption curve of an example of a fixed-frequency refrigerator provided by the present invention application.

[0059] Figure 3 : It is a schematic diagram of the electricity consumption curve of an example of a fixed-frequency air conditioner provided by the present invention application.

[0060] Figure 4 : It is a schematic diagram of the electricity consumption curve of an example of a drum washing machine provided by the present invention application.

[0061] Figure 5 : It is a schematic diagram of the electricity consumption curve of an example of a rice cooker provided by the present invention application.

[0062] Figure 6 : It is a schematic diagram of flexible energy-saving electricity consumption of an example of a drum washing machine provided by the present invention application.

[0063] Figure 7 : It is a schematic diagram of flexible energy-saving electricity consumption of an example of a rice cooker provided by the present invention application.

[0064] Figure 8 : It is a schematic diagram of the architecture of an embodiment of the temperature regulation system provided by the present invention application.

[0065] Figure 9 : It is a schematic diagram of the architecture of an embodiment of the household appliance electricity consumption regulation system provided by the present invention application.

[0066] Figure 10 : Schematic diagram of the physical object of an embodiment of the gateway provided for the present invention application.

[0067] Figure 11 : Schematic diagram of the physical object of an embodiment of the socket provided for the present invention application.

[0068] Figure 12 : Schematic structural diagram of an embodiment of the regulation device for household appliance power consumption provided for the present invention application.

[0069] Figure 13 : Schematic diagram of the daily photovoltaic power generation power curve of an example under insufficient light provided for the present invention application.

[0070] Figure 14 : Schematic diagram of the daily photovoltaic power generation power curve of an example under sufficient light provided for the present invention application. Detailed implementation manners

[0071] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0072] Embodiment 1

[0073] Please refer to Figure 1 , Figure 1 A regulation method for household appliance power consumption provided for the present invention application, including steps S101 to S103. Each step is described in detail as follows:

[0074] Step S101, obtain the power consumption expectation parameter, the green power corrected power supply period parameter, and the household appliance power consumption characteristics.

[0075] In this step, the household appliance power consumption characteristics include the intensive power consumption duration l J , the sparse power consumption unit power W J and the total power consumption duration L J . The power consumption expectation parameter includes the expected household appliance working end time T EJ and the expected household appliance start time (for example, the expected household appliance starts in advance A J and the household appliance starts with a delay D J ). The green power corrected power supply period parameter includes the green power corrected power supply start time T RI , the green power corrected power supply end time T DI and the green power corrected power supply price V I .

[0076] Before step S102, step S1011 can be executed: identifying the type of home appliance connected, where the types of home appliances include all-weather operating home appliances, adjustable home appliances, flexible power consumption home appliances, and home appliances with power consumption at specific time periods; verifying the connected home appliance through a wireless communication interface (such as a wireless communication interface of the Bluetooth interface, WiFi interface, etc.); when the verification is passed, classifying and storing the home appliance characteristics of the connected home appliance according to the type of the connected home appliance.

[0077] Exemplarily, the type and power consumption characteristics of home appliances in a user's home can be identified through a smart gateway and a smart socket, and reviewed and confirmed by professionals to ensure that each home appliance is correctly identified, classified, and recorded in the database.

[0078] Specifically, the type of home appliance in a user's home is identified through a smart gateway and a smart socket. The types of home appliances specifically include: all-weather operating home appliances (such as a refrigerator, as Figure 2 shown), adjustable home appliances (such as an air conditioner, an electric heater, etc., where the power consumption curve of the air conditioner is as Figure 3 shown), home appliances that can flexibly consume power at different time periods (a washing machine, a heat storage type electric water heater, a rice cooker, etc., where the washing machine is as Figure 4 shown, and the rice cooker is as Figure 5 shown), and home appliances with power consumption at specific time periods (such as a blender, a microwave oven, etc.). At the same time, the power consumption characteristics of each type of home appliance are identified. After identifying the home appliance type and its power consumption characteristics corresponding to each smart socket, it can be uploaded to the metering master station through High-Speed Power Line Communication (HPLC for short) and classified and stored according to different categories of home appliances.

[0079] In some preferred embodiments, the method for obtaining the green power corrected supply price includes:

[0080] Obtaining relevant variables of photovoltaic power generation with the same time scale and the same timestamp as the time-of-use electricity price; predicting the change value of the photovoltaic backplane temperature based on the relevant variables, and then calculating the corrected power generation; predicting the change value of the power generation based on the relevant variables; obtaining the corrected power generation value based on the sum of the corrected power generation and the change value of the power generation; performing normalization processing, approximation processing, and segmented quantization on the corrected power generation value to obtain multiple change amplitude intervals; and calculating and obtaining the predicted green power corrected price with the same time scale and timestamp as the time-of-use electricity price according to the multiple change amplitude intervals and the preset mapping relationship between the electricity price and the change amplitude intervals, so as to obtain the green power corrected supply price.

[0081] Exemplarily, variables related to the photovoltaic power generation intensity (such as light intensity, irradiance, ambient temperature, humidity, and / or wind speed) with the same time scale and timestamp as the time-of-use electricity price can be obtained from the short-term regional meteorological forecast in the substation area, and input into the identified meteorological parameter - photovoltaic backplane temperature model to calculate the predicted backplane temperature change value when the meteorological parameters change according to the same time scale as the time-of-use electricity price. On the other hand, the measured photovoltaic backplane temperature data collected by the intelligent flexible control terminal can be collected through the intelligent terminal, and based on the difference between the backplane temperature change value and the backplane temperature data, the deviation value is calculated; the deviation value is input into the identified photovoltaic backplane temperature - power generation power model to calculate the corrected power generation power; the above-mentioned relevant variables are input into the meteorological parameter - power generation power model to obtain the predicted power generation power change value when the meteorological parameters change, and based on the sum of the corrected power generation power and the power generation power change value, the corrected power generation power value is obtained.

[0082] Further, the specific steps of the normalization process include: for the corrected power generation power value data sequence D = {d 1 ,…d i ,…,d m}, m≥1, each value of this sequence is divided by the rated power Dmax of the photovoltaic power station:

[0083]

[0084] where d i is the corrected power generation power value at the i-th moment, d m is the corrected power generation power value at the m-th moment, and D i is the normalized power generation power at the i-th moment.

[0085] In addition, the normalized power generation power can be processed through a non-overlapping sliding window to reduce the data column with a length of m to data segments with an equal length of n (n << m). Specifically:

[0086]

[0087] n is the segmentation length of the photovoltaic prediction data column during segmented approximation, m is an integer multiple of n, is the j-th value of the segmented data sequence.

[0088] Then, the change amplitude of the approximately processed data sequence is classified and quantified. Specifically, through the Gaussian amplitude change level partition with a set number of levels, it is converted into the quantified values of each classification area. For example, it can be divided into 3 segments. For example, when the change amplitude D J ≤0.4 of the segmented and approximately processed sequence, the converted value is 0; when 0.4 < D J ≤0.7, the converted value is -0.2; when D JWhen it is > 0.7, the converted value is -1. Then, according to 0, -0.2, or -1, the corresponding corrected electricity price (pre-set mapping relationship) is determined. After determining the corresponding corrected electricity price, the corrected electricity price is superimposed on the time series of electricity consumption during the quantization period with a unified timestamp. In this way, a green electricity corrected supply electricity price with the same time scale and timestamp as the time-of-use electricity price can be obtained, that is, the green electricity corrected supply electricity price V described in step S101 I , as well as the remaining green electricity corrected supply period parameters, the start time T of green electricity corrected supply RI and the end time T of green electricity corrected supply DI .

[0089] For example Figure 13 and 14 shown, for Figure 13 , Figure 13 shows the daily photovoltaic power generation curve under insufficient light. During the afternoon flat-rate power supply period, due to insufficient light near the power distribution area, the photovoltaic power generation drops significantly. Therefore, the predicted green electricity corrected electricity price sequence does not make corresponding adjustments to the time-of-use electricity price time series for this period. For Figure 14 , it shows the daily photovoltaic power generation curve under sufficient light. During the afternoon flat-rate power supply period, the light near the power distribution area is sufficient and the power generation reaches a peak. Therefore, the predicted green electricity corrected electricity price sequence makes corresponding corrections to the time-of-use electricity price time series for this period. Through the superimposed correction amount, the corrected time-of-use preferential electricity price drops to a level equivalent to the off-peak electricity price, thereby guiding the household appliances that can be flexibly timed to start during this period in the subsequent steps

[0090] Step S102: Analyze the electricity consumption characteristics of the household appliances according to the electricity consumption expectation parameters and the green electricity corrected supply period parameters, and determine the optimal electricity consumption period of the household appliances through a multi-objective optimization algorithm, and then calculate the household appliance startup strategy in real time

[0091] Specifically, in this step, the expected household appliance end time and the total electricity consumption duration are used as constraint conditions, the supply electricity price and the expected household appliance start time are used as control objectives, and according to the green electricity corrected supply period parameters, the electricity consumption characteristics of the household appliances are analyzed to determine the optimal electricity consumption period of the household appliances, and then the household appliance startup strategy is calculated in real time

[0092] Among them, the electricity consumption expectation parameters can be obtained through the user's mobile phone APP. The electricity consumption characteristics of household appliances can be obtained through a smart electricity meter

[0093] Exemplarily, if the user's electricity consumption expectation is to be able to start A in advance J hours, the end time T of the household appliance operation can be found EJ before meeting the total electricity consumption duration L Jparameters, such as the start time T of green power corrected power supply during valley electricity price, flat electricity price, and peak electricity price periods RI , the end time T of green power corrected power supply DI , and the green power corrected power supply price V I , and sort and record them in ascending order according to the green power corrected power supply price. Furthermore, calculate in ascending order of electricity price, and set the target according to factors such as the best price and the best expected start time. Through an intelligent multi-objective optimization algorithm (such as adaptive grid division, etc.), find the best start period, and calculate and output the start time of the household appliance and the corresponding best start strategy.

[0094] Step S103, regulate the household appliance according to the household appliance start strategy.

[0095] When calculating the best start time and its household appliance start strategy, the start strategy can be transmitted to the corresponding socket through the above-mentioned HPLC and gateway, and the key information of the best start strategy (such as the preset start time, etc.) can be transmitted to the user through the Bluetooth interaction interface of the user's mobile phone and using the APP. After the user confirms or modifies it, the final household appliance start strategy is formed, and the start time of the household appliance, etc. is regulated. Exemplarily, the schematic diagrams of flexible energy-saving electricity consumption for a drum washing machine and a rice cooker are respectively as Figure 6 and 7 shown.

[0096] In this embodiment, in addition to regulating the start time of the household appliance, for household appliances such as air conditioners and electric heaters, their temperature or wind speed can also be regulated. Specifically:

[0097] Obtain time-of-use electricity parameters, identify the time-of-use electricity parameters to obtain the electricity price period, the start time and end time of the electricity price period;

[0098] According to the real-time clock, the start time and end time of the electricity price period, judge the temperature control instruction of the household appliance, and use the temperature control instruction to regulate the household appliance.

[0099] Exemplarily, a temperature regulation system is as Figure 8As shown, the temperature control system includes a zero temperature variable setting module (4300), a first time period judgment module (4301), a first mode changeover switch (4302), a first temperature variable setting module (4303), a second mode changeover switch (4304), a second temperature variable setting module (4305); a second time period judgment module (4306), a third mode changeover switch (4307), a third temperature variable setting module (4308), a fourth mode changeover switch (4309), a fourth temperature variable setting module (4310); a third time period judgment module (4311), a fifth mode changeover switch (4312), a fifth temperature variable setting module (4313), a sixth mode changeover switch (4314), a sixth temperature variable setting module (4315); a first adder module (4316), a second adder module (4317); a first strategy judgment module (4318), a seventh mode changeover switch (4319).

[0100] The setting value of the zero temperature variable setting module (4300) is "0", and its outputs are respectively connected to: the A input terminal of the first mode changeover switch (4302), the A input terminal of the second mode changeover switch (4304), the A input terminal of the third mode changeover switch (4307), and the A input terminal of the fourth mode changeover switch (4309). The first time period judgment module (4301) sets the judgment key code as "Flat period", and its input receives the time-of-use power consumption parameters obtained by the smart meter. When the "Flat period" code is recognized, the start time T of the flat power period is extracted from the data stream of this section RFI , the end time T DFI ; compare with the real-time clock. When the real time reaches T RFI , a "Yes" instruction is issued until the clock reaches T DFI , and it is converted into a "No" instruction. When the time is between T RFI and T DFI , it continuously outputs a "Yes" instruction and sends it to the first mode changeover switch (4302). The changeover switch selects to output the "flat power temperature variable 1" output by the first temperature variable setting module (4303) at the B output to form the first "flat power temperature control adjustment variable" of the "flat power period"; when the time is not between T RFI and T DFI , the first time period judgment module (4301) outputs false, that is, a "No" instruction, and the first mode changeover switch (4302) selects to output at the A end and sends out the "0" value output by the zero temperature variable setting module (4300) to form a temperature control adjustment variable of 0. Similarly, the judgment result of the first time period judgment module (4301) is also sent to the second mode changeover switch (4304). When the time is between T RFI and T DFIWhen it is, the "Flat electricity temperature variable 2" output by the second temperature variable setting module (4305) of the B output is selected to form the second "Flat electricity temperature control adjustment variable" of the "Flat electricity period"; when the time is not within T RFI to T DFI it selects the "0" value output by the zero temperature variable setting module (4300) at the A end to form a temperature control adjustment variable of 0.

[0101] Similarly, the second time period judgment module (4306) is configured to judge that the key code is "Peak period Peak electricity period", and its input is the time-sharing power consumption time parameters obtained by the smart meter. When the "Flat period" code is recognized, the start time T of the flat electricity period is extracted from this section of the data stream RPI , end time T RPI ; Compare with the real-time clock. When the real-time time reaches T RPI , it issues a "Yes" instruction until the clock reaches T DPI , it is converted into a "No" instruction. When the time is within T RPI to T DPI , it outputs true, that is, a "Yes" instruction, to the third mode change switch (4307). The change switch selects the "Peak electricity temperature variable 1" output by the third temperature variable setting module (4308) of the B output to form the first "Peak electricity temperature control adjustment variable" of the "Peak electricity period"; when the time is not within T RPI to T DPI , the second time period judgment module (4306) outputs false, that is, a "No" instruction, and the change switch selects the A end output to send the "0" value output by the zero temperature variable setting module (4300) to form a temperature control adjustment variable of 0. Similarly, the judgment result of the second time period judgment module (4306) is also sent to the fourth mode change switch (4309). When the time is within T RPI to T DPI , it selects the "Peak electricity temperature variable 2" output by the fourth temperature variable setting module (4310) of the B output to form the second "Peak electricity temperature control adjustment variable" of the "Peak electricity period"; when the time is not within T RPI to T RPI , it selects the "0" value output by the zero temperature variable setting module (4300) at the A end to form a temperature control adjustment variable of 0.

[0102] The third time period judgment module (4311) is configured to judge that the key code is "Off Peak period Valley electricity period", and its input is the time-sharing power consumption time parameters obtained by the smart meter. When the "Off Peak period" code is recognized, the start time T of the valley electricity period is extracted from this section of the data stream ROPI , end time T DOPI; Compare with the real-time clock. When the real-time reaches T ROPI , issue a "Yes" instruction until the clock reaches T DOPI , and then convert it to a "No" instruction. When the time is between T ROPI and T DOPI , it outputs true, that is, a "Yes" instruction, and sends it to the fifth mode switch (4312). The switch then selects the "valley electricity temperature variable 1" output by the fifth temperature variable setting module (4313) output from B, forming the first "valley electricity temperature control adjustment variable" during the "valley electricity period"; when the time is not between T ROPI and T DOPI , the third period judgment module (4311) outputs false, that is, a "No" instruction, and the switch selects the output from A and sends out the output of the first mode switch (4302), taking the "temperature control adjustment variable" output by the upper-level "period" selection as the temperature control adjustment variable output. Similarly, the judgment result of the third period judgment module (4311) is also sent to the sixth mode switch (4314). When the time is between T ROPI and T DOPI , it selects the "valley electricity temperature variable 2" output by the sixth temperature variable setting module (4315) output from B, forming the second "valley electricity temperature control adjustment variable" during the "valley electricity period"; when the time is not between T ROPI and T DOPI , it selects the A end and sends out the output of the second mode switch (4304), outputting the "temperature control adjustment variable" output by the upper-level "period" selection.

[0103] The output of the third mode switch (4307) is connected to the first input terminal of the first adder module (4316), and the output of the fifth mode switch (4312) is connected to the second input terminal of the first adder module (4316). The three-period "temperature control adjustment variables" of the first set of "temperature control adjustment" strategies are summarized in the adder to form the first set of continuous time-of-use (ToU) "temperature control adjustment variable" strategies.

[0104] The output of the fourth mode switch (4309) is connected to the first input terminal of the second adder module (4317), and the output of the sixth mode switch (4314) is connected to the second input terminal of the second adder module (4317). The three-period "temperature control adjustment variables" of the second set of "temperature control adjustment" strategies are summarized in the adder to form the second set of continuous time-of-use (ToU) "temperature control adjustment variable" strategies.

[0105] The input of the first strategy temperature control strategy module (4318) receives the "temperature control strategy" selection instruction sent by the user's interaction interface; when the user selects the first set of "temperature control adjustment" strategies through the interaction interface, the first strategy temperature control strategy module (4318) outputs a true, that is, "Yes" instruction, which is sent to the seventh mode switch (4319), and the switch then selects to output the "temperature control adjustment variable" of the first set of "temperature control adjustment" strategies output by B; otherwise, the first strategy temperature control strategy module (4318) outputs a false, that is, "No" instruction, and the switch then selects to output the "temperature control adjustment variable" of the second set of "temperature control adjustment" strategies output by A.

[0106] The user can review whether the calculated "temperature control adjustment variables" for each period are appropriate on the interaction interface and make modifications. After the user confirms that they are appropriate, the "temperature control adjustment variables" will be transmitted to the smart socket of the adjustable household appliance through HPLC, and the control temperature setting value of the household appliance will be regulated according to the time-of-use (ToU) electricity consumption situation.

[0107] Correspondingly, as Figure 9 shown, the present invention application also provides a regulation system for household appliance electricity consumption, and the regulation system is used to execute the regulation method for household appliance electricity consumption described in any one or more of the above embodiments; the regulation system includes a metering master station, a measurement terminal, an electric meter, a gateway, a regulation terminal, and a socket.

[0108] As Figure 10 shown, the gateway includes a first carrier communication module, an electric meter interface, a first microprocessor module, and a first watchdog IC module; the gateway is connected to the measurement terminal and the socket through the carrier communication module, and the gateway is connected to the electric meter through the electric meter interface;

[0109] The first microprocessor module is used to perform the following steps (i.e., step S1011) before obtaining the electricity consumption expectation parameters, green power corrected power supply period parameters, and household appliance electricity consumption characteristics:

[0110] Identify the household appliance types of the connected household appliances, and the household appliance types include all-weather operating household appliances, adjustable household appliances, flexible electricity consumption household appliances, and household appliances with electricity consumption at specific times;

[0111] Verify the connected household appliances through a wireless communication interface (such as a wireless communication interface of the Bluetooth interface, WiFi interface, etc.);

[0112] When the verification is passed, classify and store the household appliance characteristics of the connected household appliances according to the household appliance types of the connected household appliances.

[0113] As Figure 11As shown, the socket includes an infrared control module, a Bluetooth communication module, a voice interface module, a metering module, a temperature measurement module, a relay control module, a second carrier communication module, and a second microprocessor module; the socket is connected to the gateway through the second carrier communication module;

[0114] Among them, the second microprocessor module is used to execute the following steps (i.e., step S101 to step S103):

[0115] Obtain the electricity consumption expectation parameters, green power corrected power supply period parameters, and household appliance electricity consumption characteristics, where the household appliance electricity consumption characteristics include the intensive electricity consumption duration, sparse electricity consumption unit power, and total electricity consumption duration of the household appliance;

[0116] According to the electricity consumption expectation parameters and green power corrected power supply period parameters, analyze the household appliance electricity consumption characteristics, and determine the optimal electricity consumption period of the household appliance through a multi-objective optimization algorithm, and then calculate the household appliance startup strategy in real time;

[0117] Regulate the household appliance through the household appliance startup strategy.

[0118] Among them, the metering master station sends a polling instruction to the substation concentrator (intelligent metering terminal). Then, the intelligent metering terminal uses HPLC (High-Speed Power Line Communication) technology to transfer the relevant instructions to the intelligent electricity meters at each user end.

[0119] The intelligent metering terminal, each electricity meter, and the intelligent flexible control terminal together form a first-level star-shaped HPLC network. Among them, the intelligent metering terminal serves as the central node, and each electricity meter and the intelligent flexible control terminal serve as subordinate nodes, and they communicate with each other in a broadcast manner.

[0120] The HPLC-based gateway of the present application is designed to be inserted into the expansion slot of the user's smart meter. This gateway can identify and manage all HPLC smart devices (such as sockets) connected via the power line, thereby enabling intelligent measurement and control of household appliances plugged into these devices. The first microprocessor module built into the gateway is responsible for calculating the optimal energy-saving strategies for each household appliance in the user's home, namely step S1011. Specifically, this gateway is used to be installed on the expansion interface of the user's smart meter and is responsible for identifying and managing all HPLC smart devices (such as HPLC smart sockets) connected to the power line, including configuring device parameters, monitoring device status, and updating firmware. It conducts real-time two-way communication with the meter through the UART interface and uses the HPLC link between the meter and the intelligent measurement terminal to establish a two-way communication network for metering system data, realizing the reporting of electricity consumption data and the execution of metering system instructions. It obtains weather forecast information from the power grid cloud platform through the intelligent measurement terminal; collects the measured data of the photovoltaic power station in the substation area, makes local corrections to the predicted power, and calculates the power supply time series of each section with green power correction. In addition, the intelligent gateway is also responsible for calculating the optimal energy-saving strategies for each household appliance in the user's home and conducting coordinated control of the in-house electrical equipment.

[0121] Furthermore, the gateway can be provided with two first microprocessor modules, one of which is used to execute step S1011. The other first microprocessor module forms a redundant configuration microprocessor pair with the former and plays the core role in the operation management of the entire gateway. Each component of the gateway is connected through a high-speed intelligent link module.

[0122] The meter interface module of the gateway described in this embodiment is specifically: it inserts into the expansion slot of the smart meter through the UART interface plug to realize the UART communication management with the smart meter. The first watchdog IC module monitors the operation of the main program through the built-in timer to prevent stagnation or "crash" caused by program errors (such as infinite loops), and at the same time protects the circuit from abnormal situations.

[0123] The HPLC-based smart socket of the present application is installed on the user's power line and is designed to realize the intelligent monitoring of household appliances. The second microprocessor module built into it can accurately identify and determine the model, type, and power consumption characteristics of each household appliance connected to each smart socket. These sockets can not only exchange information with the HPLC gateway, receive and transmit the measurement and control instructions and feedback signals of the connected household appliances; but also have functions such as infrared control and ambient temperature detection. With the infrared receiving and transmitting windows on the socket, the HPLC smart socket can conduct fine operation control of household appliances that support infrared remote control.

[0124] The second microprocessor module of the socket described in this embodiment can be used to execute steps S101 to S103. The infrared control module embedded in the HPLC intelligent socket receives / transmits infrared control instructions through the light-transmitting receiving window on the intelligent socket. When an infrared-remote-control intelligent household appliance (such as an air conditioner, a storage-type electric water heater, a TV, a fan, etc.) is plugged into the intelligent socket, this module can convert the intelligent power consumption control signal transmitted by the intelligent electricity meter into an infrared remote control instruction and send it out to control the operating state of the household appliance; at the same time, the infrared receiving end of the infrared control module can also receive the infrared feedback signal of the operating state from the household appliance to ensure that the control instruction matches the actual operating state of the household appliance. Bluetooth communication module: This module provides a microservice call (APP) interface. It allows relevant personnel to perform operations such as parameter setting and status detection on all HPLC intelligent sockets through application programs such as APP by using any HPLC intelligent socket in the home, and to obtain the device working status in real time. This helps to avoid the problem that the device monitoring status is inconsistent with the actual device operating state due to abnormal infrared reception. Voice interface module: This module provides a voice interface. Through the voice interface module, relevant personnel are allowed to implement control parameters, start / stop times, etc. for the intelligent household appliances plugged into the HPLC intelligent socket. Metering module: This module uses the metering IC built into the intelligent socket to detect information such as the current and voltage of the household appliances on the socket in real time, and uploads this information to the metering master station through HPLC to monitor and collect the real-time power consumption information of the household appliances, providing accurate and sufficient information support for intelligent power consumption. Temperature measurement module: This module is built with temperature measurement elements (such as NTC - Negative Temperature Coefficient thermistors, RTD - Resistance Temperature Detector, etc.) to form a monitoring circuit for monitoring the room temperature and providing a real environmental temperature feedback signal for the temperature-controlled household appliances (such as air conditioners, fans, water heaters, etc.) in the room. Relay control module: This module uses the micro relay control circuit in the intelligent socket to control the power on / off of the household appliances plugged into the socket according to the intelligent power consumption control instructions of the household appliances transmitted by the intelligent electricity meter, realizing the intelligent power consumption control of various household appliances.

[0125] Through the BLE (Bluetooth Low Energy) interface on the intelligent socket described in any of the above embodiments, in cooperation with application programs such as APP installed on the mobile phones of relevant personnel, users can conveniently obtain the working status of intelligent devices, monitor and confirm information such as the characteristic parameters of household appliances plugged into the intelligent socket and the setting parameters of the best energy-saving strategies.

[0126] The intelligent HPLC gateway and each HPLC intelligent socket jointly construct the second-level star HPLC network. In this network, the intelligent HPLC gateway acts as the central node, and each HPLC intelligent socket serves as a subordinate node. They still communicate in a broadcast manner. Users only need to use the APP on their mobile phones to easily obtain the working status of all HPLC intelligent sockets, the characteristic parameters of the household appliances connected to the socket, and the setting parameters of the best energy-saving strategies through any HPLC intelligent socket in the home via this level of HPLC network.

[0127] Finally, the metering master station classifies and stores the real-time electricity consumption information of the electrical appliances in each room of each user in the power distribution area uploaded by each intelligent metering terminal. At the same time, the master station also deeply analyzes the user's energy efficiency data, including the opening status of the energy-saving strategy, the cumulative number of times the energy-saving strategy is turned on, and the cumulative electricity cost saved. In addition, the master station can also realize 3D visualization displays of the opening status and energy consumption of various electrical appliances, and can perform advanced processing functions such as tracing the start and stop time periods of various electrical appliances and monitoring energy consumption. Through the metering master station, it is also possible to access the enterprise's cloud platform to obtain various data such as weather forecast information.

[0128] Correspondingly, as Figure 12 shown, the present invention application also provides a control device 1200 for household appliance power consumption, including an acquisition module 1201, an analysis module 1202, and a control module 1203; wherein,

[0129] The acquisition module 1201 is used to acquire the power consumption expectation parameters, the green power corrected power supply time period parameters, and the household appliance power consumption characteristics, and the household appliance power consumption characteristics include the intensive power consumption duration of the household appliance, the sparse power consumption unit power, and the total power consumption duration;

[0130] The analysis module 1202 is used to analyze the household appliance power consumption characteristics according to the power consumption expectation parameters and the green power corrected power supply time period parameters, and determine the best power consumption time period of the household appliance through a multi-objective optimization algorithm, and then calculate the household appliance startup strategy in real time;

[0131] The control module 1203 is used to control the household appliance through the household appliance startup strategy.

[0132] As a preferred solution, the power consumption expectation parameters include the expected household appliance working end time and the expected household appliance startup time; the green power corrected power supply time period parameters include the green power corrected power supply start time, the green power corrected power supply end time, and the green power corrected power supply price;

[0133] The analysis module 1202 analyzes the household appliance power consumption characteristics according to the power consumption expectation parameters and the green power corrected power supply time period parameters, and determines the best power consumption time period of the household appliance through a multi-objective optimization algorithm, and then calculates the household appliance startup strategy in real time, including:

[0134] The analysis module 1202 uses the expected end time of the home appliance operation and the total power consumption duration as constraint conditions, takes the power supply price and the expected start time of the home appliance as control objectives, modifies the power supply period parameters according to the green power, analyzes the power consumption characteristics of the home appliance, determines the optimal power consumption period of the home appliance, and then calculates the home appliance startup strategy in real time.

[0135] As a preferred solution, the method for obtaining the green power corrected power supply price includes:

[0136] The acquisition module 1201 acquires relevant variables of photovoltaic power generation with the same time scale and the same time stamp as the time-of-use electricity price;

[0137] Based on the relevant variables, predict the change value of the photovoltaic backplane temperature, and then calculate the corrected power generation power; based on the relevant variables, predict the change value of the power generation power;

[0138] Based on the sum of the corrected power generation power and the change value of the power generation power, obtain the corrected power generation power value;

[0139] Normalize, approximate, and segmentally quantize the corrected power generation power value to obtain multiple change amplitude intervals;

[0140] According to the multiple change amplitude intervals and the preset mapping relationship between the electricity price and the change amplitude intervals, convert to obtain the predicted green power corrected electricity price with the same time scale and time stamp as the time-of-use electricity price, and obtain the green power corrected power supply price.

[0141] As a preferred solution, the control device 1200 further includes a classification storage module, which is used before acquiring the electricity consumption expectation parameters, the green power corrected power supply period parameters, and the power consumption characteristics of the home appliance:

[0142] Identify the type of home appliance connected, and the types of home appliances include all-weather operating home appliances, adjustable home appliances, flexible power consumption home appliances, and home appliances with specific time period power consumption;

[0143] Verify the connected home appliance through a wireless communication interface;

[0144] When the verification is passed, classify and store the home appliance characteristics of the connected home appliance according to the type of the connected home appliance.

[0145] As a preferred solution, the control device 1200 further includes a temperature adjustment module, which is used to: acquire time-of-use power consumption parameters, identify the time-of-use power consumption parameters, and obtain the electricity price period, the start time and the end time of the electricity price period;

[0146] Based on the real-time clock, the start time and end time of the electricity price period where it is located, determine the temperature control instruction for the household appliance, and use the temperature control instruction to regulate the household appliance.

[0147] Correspondingly, the present invention application also provides a computer-readable storage medium, the computer-readable storage medium includes a stored computer program, wherein, when the computer program runs, it controls the device where the computer-readable storage medium is located to execute the regulation method of household appliance power consumption in any one of the above-mentioned implementation manners.

[0148] Among them, if the modules integrated in the household appliance power consumption regulation device are implemented in the form of software function units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such an understanding, to implement all or part of the processes in the above-mentioned embodiment methods of the present invention, it can also be completed by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-mentioned various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electrical carrier signal, telecommunication signal, and software distribution medium, etc.

[0149] Compared with the prior art, the present invention application has the following beneficial effects:

[0150] The present invention application provides a regulation method, device, system and medium for household appliances using electricity. The method includes: obtaining electricity consumption expectation parameters, green electricity corrected power supply period parameters and household appliance electricity consumption characteristics, where the household appliance electricity consumption characteristics include the intensive electricity consumption duration, sparse electricity consumption unit power and total electricity consumption duration of the household appliance; analyzing the household appliance electricity consumption characteristics according to the electricity consumption expectation parameters and the green electricity corrected power supply period parameters, and determining the optimal electricity consumption period of the household appliance through a multi-objective optimization algorithm, and then calculating the household appliance startup strategy in real time; regulating the household appliance through the household appliance startup strategy. Compared with the prior art, the present application considers not only the electricity price factor but also the household appliance electricity consumption characteristics, specifically including factors such as the intensive electricity consumption duration, sparse electricity consumption unit power and total electricity consumption duration of the household appliance, and combines the electricity consumption expectation parameters and the green electricity corrected power supply period parameters, analyzes these factors, uses a multi-objective optimization algorithm to determine the optimal electricity consumption period of the household appliance, and then calculates the household appliance startup strategy and regulates the household appliance in real time, effectively improving the accuracy of regulation and achieving the purpose of effectively reducing energy consumption.

[0151] The specific embodiments described above have further elaborated on the purpose, technical solutions and beneficial effects of the present invention. It should be understood that the above description is only for the specific embodiments of the present invention and is not used to limit the protection scope of the present invention. In particular, for those skilled in the art, any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for regulating household electrical power consumption, characterized in that: include: Acquire power consumption expectation parameters, green power correction power supply period parameters and power consumption characteristics of household appliances, wherein the power consumption characteristics of household appliances include intensive power consumption duration, sparse power consumption unit power and total power consumption duration of household appliances; Analyze the power consumption characteristics of the household appliances according to the power consumption expectation parameters and the green power correction power supply period parameters, and determine the optimal power consumption period of the household appliances through a multi-objective optimization algorithm, and then calculate the home appliance startup strategy in real time; The home appliances are regulated by the home appliance startup strategy.

2. A method for regulating household electrical power consumption as claimed in claim 1, characterized in that: The expected power consumption parameters include expected home appliance operation end time and expected home appliance startup time; The green electricity correction power supply period parameters include the green electricity correction power supply start time, the green electricity correction power supply end time and the green electricity correction power supply price; The power consumption characteristics of the household appliances are analyzed according to the power consumption expectation parameters and the green power correction power supply period parameters, and the optimal power consumption period of the household appliances is determined through a multi-objective optimization algorithm, and then the home appliance startup strategy is calculated in real time, including: The expected end time of home appliance operation and the total duration of electricity consumption are used as constraints, the power supply price and the expected home appliance startup time are used as control targets, and the power supply period parameters are corrected according to the green electricity. The power consumption characteristics of the home appliances are analyzed to determine the optimal power consumption period for the home appliances, and then the home appliance startup strategy is calculated in real time.

3. A method for regulating household electrical power consumption as claimed in claim 2, characterized in that: The method for obtaining the green electricity revised power supply price includes: Obtain relevant variables of photovoltaic power generation with the same time scale and timestamp as the time-of-use electricity price; Predicting the change value of the photovoltaic back panel temperature based on the relevant variables, and then calculating the corrected power generation; predicting the change value of the power generation based on the relevant variables; Obtaining a modified power generation value based on the sum of the corrected power generation and the power generation change value; The corrected power generation value is normalized, approximated and quantized in sections to obtain a plurality of variation ranges; According to the multiple variation ranges and the preset mapping relationship between the electricity price and the variation ranges, the predicted green electricity corrected electricity price with the same time scale and timestamp as the time-of-use electricity price is converted to obtain the green electricity corrected supply electricity price.

4. A method for regulating household electrical power consumption as claimed in claim 1, characterized in that: Before obtaining the expected power consumption parameters, the green power correction power supply period parameters and the power consumption characteristics of the household appliances, the method further includes: Identify the type of home appliances connected to the home appliance, where the home appliance types include all-weather operation home appliances, adjustable home appliances, flexible power consumption home appliances, and specific time period power consumption home appliances; Verifying the connected home appliance through a wireless communication interface; When the verification is passed, the home appliance characteristics of the connected home appliance are classified and stored according to the type of the connected home appliance.

5. A method for regulating household electrical power consumption according to any one of claims 1 to 4, characterized in that: The method for regulating household appliance electricity consumption also includes: Obtaining time-of-use electricity parameters, identifying the time-of-use electricity parameters, and obtaining the electricity price period, the start time and the end time of the electricity price period; The temperature control instruction of the household appliance is determined according to the real-time clock, the start time and the end time of the electricity price period, and the household appliance is regulated by using the temperature control instruction.

6. A control device for household electrical appliances, characterized in that: It includes acquisition module, analysis module and regulation module; among them, The acquisition module is used to acquire the expected power consumption parameters, the green power correction power supply period parameters and the power consumption characteristics of the household appliances, wherein the power consumption characteristics of the household appliances include the intensive power consumption duration, the sparse power consumption unit power and the total power consumption duration of the household appliances; The analysis module is used to analyze the power consumption characteristics of the household appliances according to the power consumption expectation parameters and the green power correction power supply period parameters, and determine the optimal power consumption period of the household appliances through a multi-objective optimization algorithm, and then calculate the home appliance startup strategy in real time; The control module is used to control the home appliance through the home appliance startup strategy.

7. A control system for household electrical appliances, characterized in that: The control system is used to execute the control method for household appliance electricity consumption as described in any one of claims 1 to 5; the control system includes a metering master station, a measurement terminal, an electric meter, a gateway, a control terminal and a socket.

8. A household appliance power control system as claimed in claim 7, characterized in that: The gateway comprises a first carrier communication module, an electric meter interface, a first microprocessor module and a first watchdog IC module; the gateway is connected to the measurement terminal and the socket through the carrier communication module, and the gateway is connected to the electric meter through the electric meter interface; The first microprocessor module is used to perform the following steps before obtaining the expected power consumption parameters, the green power correction power supply period parameters and the power consumption characteristics of the household appliances: Identify the type of home appliances connected to the home appliance, where the home appliance types include all-weather operation home appliances, adjustable home appliances, flexible power consumption home appliances, and specific time period power consumption home appliances; Verifying the connected home appliance through a wireless communication interface; When the verification is passed, the home appliance characteristics of the connected home appliance are classified and stored according to the type of the connected home appliance.

9. A household appliance power control system as claimed in claim 7, characterized in that: The socket includes an infrared control module, a Bluetooth communication module, a voice interface module, a metering module, a temperature measurement module, a relay control module, a second carrier communication module and a second microprocessor module; the socket is connected to the gateway through the second carrier communication module; Wherein, the second microprocessor module is used to perform the following steps: Acquire power consumption expectation parameters, green power correction power supply period parameters and power consumption characteristics of household appliances, wherein the power consumption characteristics of household appliances include intensive power consumption duration, sparse power consumption unit power and total power consumption duration of household appliances; Analyze the power consumption characteristics of the household appliances according to the power consumption expectation parameters and the green power correction power supply period parameters, and determine the optimal power consumption period of the household appliances through a multi-objective optimization algorithm, and then calculate the home appliance startup strategy in real time; The home appliances are regulated by the home appliance startup strategy.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored computer program, wherein when the computer program is executed, the device where the computer-readable storage medium is located is controlled to execute the method for regulating household appliance electricity consumption as described in any one of claims 1 to 5.

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