CN211606196U - Load decomposition device of remote monitoring electric equipment - Google Patents

Abstract

A load decomposition device of remote monitoring electric equipment comprises a data acquisition module, a data transmission module, a data processing module and a data feedback module, wherein the data acquisition module acquires electric power and environmental parameters through a sensor and uploads the electric power and the environmental parameters to the data processing module through the data transmission module; the data processing module is used for processing the transmitted power parameters and feeding back the processed information to the application unit through the data feedback module; the utility model discloses a concentrate and gather required electric power data, need not to install collection equipment respectively for a plurality of electrical apparatus, alleviate user use cost, improve the clean and tidy degree and the aesthetic measure that use the scene, carry on environmental parameter collection and analysis function, optimize user experience.

Description

Load decomposition device of remote monitoring electric equipment

Technical Field

The utility model relates to an electricity monitoring device especially relates to a load decomposition device that can remote monitoring consumer.

Background

At present, distributed power supplies, controllable loads and distributed energy storage devices cover multiple fields around people, but no good management system can integrate distributed energy around people so far, and a detailed energy utilization analysis report cannot be provided for each user so as to assist the user in carrying out reasonable energy utilization regulation. On one hand, the energy utilization of each user is still in a state of freedom, liberalization and no scientific plan, and pressure is caused to peak shaving of the integral power utilization in a garden or a larger range, so that the safety and the stability of a power grid are not facilitated. On the other hand, the structure of the energy source is changing deeply at present, but the intermittent fluctuation of the clean energy source is not beneficial to the consumption and the scheduling of the clean energy source.

The energy utilization equipment terminal is provided with a detection device, the whole data of the energy of the user is collected and accessed to the intelligent service platform, and the data is analyzed and processed by using a load decomposition technology at the cloud end and then fed back to the user end. For a power grid user, the whole power utilization condition in the management range can be checked in real time and processed in time, and corresponding measures are set to guide the user to save energy; for a common user, the specific use condition of the electric appliance can be known, the electric utilization plan can be reasonably made, the energy is saved from bottom to top, and the quality and the efficiency of the power grid are improved and enhanced.

Chinese patent application (application number: 201910970443.6) discloses a novel intelligent monitoring device and system for power distribution cabinets based on the internet of things, which includes: the system comprises a microcontroller, an environmental information monitoring module, a power parameter acquisition module, an image acquisition module, a touch screen display module and a wireless communication module; the wireless communication module, the environmental information monitoring module, the power parameter acquisition module, the image acquisition module and the touch screen display module are respectively connected with the microcontroller; the microcontroller acquires environmental information inside the power distribution cabinet through the environmental information monitoring module and uploads the acquired environmental information to the Internet of things cloud platform through the wireless communication module; the microcontroller acquires power supply parameter information inside the power distribution cabinet through the power parameter acquisition module and uploads the acquired power supply parameter information to the Internet of things cloud platform through the wireless communication module; the microcontroller acquires image information inside the power distribution cabinet through the image acquisition module and uploads the acquired image information to the Internet of things cloud platform through the wireless communication module; the microcontroller acquires control information input by a user through the touch screen display module, and displays the state information of the power distribution cabinet and the state information of the device through the touch screen display module.

However, the prior art can not acquire the required data through one device, and a plurality of electrical appliances are respectively provided with the acquisition devices, so that the use cost of a user is increased, and meanwhile, the hardware structure is high in cost, is not suitable for large-scale production and use, and does not meet the market demand.

SUMMERY OF THE UTILITY MODEL

An object of the utility model is to provide a load decomposition device of remote monitoring consumer to solve the technical problem that "this prior art (application number: 201910970443.6) mentioned in the background art can not gather required data through an equipment, and adopts a plurality of electrical apparatus to install collection equipment respectively, has increased user use cost, and simultaneously, this hardware architecture is with high costs, is unsuitable for large-scale production and use, is not conform to market demand".

In order to achieve the above object, the utility model provides a following technical scheme:

a load decomposition device of remote monitoring electric equipment comprises a data acquisition module, a data transmission module, a data processing module and a data feedback module, wherein the data acquisition module acquires electric power and environmental parameters through a sensor and uploads the electric power and the environmental parameters to the data processing module through the data transmission module; the data processing module is used for processing the transmitted power parameters and feeding back the processed information to the application unit through the data feedback module;

the data acquisition module comprises a power parameter acquisition unit and an environmental parameter acquisition unit; the power parameter acquisition unit acquires total power data of user power consumption through the intelligent socket, wherein the sampling frequency of the intelligent socket

Collecting and collecting carbon dioxide concentration, air temperature and humidity and air fine particulate matter concentration information for the environmental parameter collecting unit through a carbon dioxide concentration sensor, an air temperature and humidity sensor and a PM2.5 sensor;

the data transmission module transmits power utilization total power data and real-time data acquired by the sensor to the data processing module for processing through a WiFi transmission circuit taking an RAK415 chip as a core;

the data processing module comprises a data preprocessing unit, a data storage unit and an intelligent analysis unit; the data preprocessing unit is used for adjusting the acquired data into an input sequence format of a transfer learning model after carrying out noise filtering, isolation and amplification on the acquired data; the data storage unit is used for storing the preprocessed data into a database; the intelligent analysis unit is used for adjusting the hierarchical structure and the output dimension of the encoder and the decoder;

the data feedback module comprises a PC end application unit and a mobile end application unit; the PC side application unit feeds back the total controllable load number of the current area and the service condition data of the intelligent socket processed by the service layer to a webpage; and the mobile terminal application unit feeds back the user electricity utilization information processed by the service layer to the developed APP.

Preferably: the electric power parameter acquisition unit comprises a voltage source and relay circuit, a voltage stabilizer circuit, a CS5463 high-speed power metering circuit, a voltage sampling circuit, an alternating current transformer circuit, an ARMCortex-M series STM32F051 core chip control circuit and a WiFi transmission circuit; the voltage source and relay circuit is connected with a zero line and a live line on a strong current side, and the 220V alternating current of the commercial power is converted into +5V voltage for subsequent modules by controlling the on-off of the relay; the voltage stabilizer circuit converts the +5V voltage into +3.3V voltage for subsequent electronic components; the CS5463 high-speed power metering circuit calculates power data by using the voltage data acquired by the voltage sampling circuit and the current data acquired by the alternating current transformer circuit through a multiplier, and transmits the power data to the data processing module through the WiFi transmission circuit under the control of the STM32F051 core chip control circuit.

Compared with the prior art, the beneficial effects of the utility model are that:

the utility model discloses an equipment can gather required data, need not to install the collection equipment respectively for a plurality of electrical apparatus, alleviates user's use cost, improves the clean and tidy degree and the aesthetic measure who uses the scene.

Drawings

Fig. 1 is a schematic diagram of the system structure of the present invention;

FIG. 2 is a circuit diagram of a voltage source and relay according to the present invention;

fig. 3 is a circuit diagram of the CS5463 high-speed power meter of the present invention;

fig. 4 is a circuit diagram of the voltage sampling circuit of the present invention;

fig. 5 is a circuit diagram of the ac current transformer of the present invention;

fig. 6 is a core control circuit diagram of STM32F051 according to the present invention;

fig. 7 is a circuit diagram of the LED display of the present invention;

fig. 8 is a WiFi transmission circuit diagram of the present invention;

fig. 9 is a circuit diagram of the voltage regulator of the present invention.

Detailed Description

The invention will be further elucidated with reference to the drawings and specific embodiments, it being understood that these examples are intended to illustrate the invention only and are not intended to limit the scope of the invention, and that modifications to the various equivalent forms of the invention, which may occur to those skilled in the art after reading the present invention, fall within the scope of the invention as defined in the claims appended hereto.

A load decomposition device of remote monitoring electric equipment comprises a data acquisition module, a data transmission module, a data processing module and a data feedback module, wherein the data acquisition module acquires electric power and environmental parameters through a sensor and uploads the electric power and the environmental parameters to the data processing module through the data transmission module; the data processing module is used for processing the transmitted power parameters and feeding back the processed information to the application unit through the data feedback module; the data acquisition module comprises a power parameter acquisition unit and an environmental parameter acquisition unit; the power parameter acquisition unit acquires total power data of user power consumption through the intelligent socket, wherein the sampling frequency of the intelligent socket is

The environment parameter acquisition unit is used for acquiring environment parameters through dioxygenThe carbon dioxide concentration sensor, the air temperature and humidity sensor and the PM2.5 sensor collect and collect carbon dioxide concentration, air temperature and humidity and air fine particle concentration information. The data transmission module transmits power utilization total power data and real-time data acquired by the sensors to the data processing module for processing through a WiFi transmission circuit taking an RAK415 chip as a core; the data processing module comprises a data preprocessing unit, a data storage unit and an intelligent analysis unit; the data preprocessing unit is used for adjusting the acquired data into an input sequence format of a learning migration model after carrying out noise filtering, isolation and amplification on the acquired data, and separating a training set and a test set; the data storage unit is used for storing the preprocessed data into a MySQL database; the intelligent analysis unit builds a transfer learning model for the stored information by adopting an Encoder-Decoder framework, and adjusts the hierarchical structure and the output dimension of the Encoder and the Decoder; the data feedback module utilizes the data processed in the data processing module to realize the making of statistical charts, the drawing of power and environment curves. The power parameter acquisition unit comprises a voltage source and relay circuit, a voltage stabilizer circuit, a CS5463 high-speed power metering circuit, a voltage sampling circuit, an alternating current transformer circuit, an ARMCortex-M series STM32F051 core chip control circuit, a WiFi transmission circuit and an LED display circuit; the voltage source and relay circuit is connected with a zero line and a live line on a strong current side, and the 220V alternating current of the commercial power is converted into +5V voltage for subsequent modules by controlling the on-off of the relay; the voltage stabilizer circuit converts the +5V voltage into +3.3V voltage for subsequent electronic components; the CS5463 high-speed power metering circuit calculates power data by using the voltage data acquired by the voltage sampling circuit and the current data acquired by the alternating current transformer circuit through a multiplier, and transmits the power data to a data processing module (service layer) through a WiFi transmission circuit (access layer) under the control of an STM32F051 core chip control circuit; the environmental parameters collected by the environmental sensor, including carbon dioxide concentration, air temperature and air humidity information, are transmitted to the data processing module (service layer) through the WiFi transmission circuit. The data feedback module comprises: PC side application unit, thereinThe PC end application unit is mainly used by a power grid user, provides the power utilization condition in the current management area for power grid scheduling personnel, and feeds back data such as the total controllable load number, the total user number, the user activity, the intelligent socket use conditions in all regions of the country and the like processed by a service layer to a webpage, so that the power utilization condition in the controlled area can be monitored in real time by the power grid user conveniently, and convenience is provided for scheduling. The function of a real-time monitoring part is mainly provided for power grid users; the real-time detection part is used for checking the total controllable load number, the total user number and the user activity in the current control range and checking the use condition of sockets in various regions across the country in real time; the data feedback module further comprises a mobile terminal application unit: the mobile terminal application unit is mainly used by a common user and feeds back the user electricity utilization information processed by the service layer to the developed APP. And drawing a corresponding curve according to time by using the processed information of the electric power, the total power and the consumed electric quantity of each electric appliance, and providing a monthly power consumption information statistical graph or a daily power consumption information statistical graph and the like for the user. For more convenient use experience of a user, the unit provides a function of remotely controlling the electric appliance for the user. In addition, an environment condition feedback function is designed, so that the environment condition in the power utilization scene is displayed for the mobile terminal user, and whether the environment condition is displayed or not is set according to the actual requirement of the user in practical application. The mobile terminal application unit comprises a power utilization information inquiry part and a remote control part. The electricity consumption information inquiry part is used for displaying electricity consumption at different time intervals and drawing an electricity consumption characteristic curve graph; the remote control part is used for remotely controlling the electric appliances, checking the power utilization information of the specific electric appliances and performing entrusted control by a user through a mobile phone.

Example 1

In the field of power data processing, a load decomposition technology, such as a Non-intrusive load decomposition (NILM), is commonly used in the prior art, and the technology is a metering means for acquiring total power information of a user from an intelligent socket installed on a main circuit of the user and analyzing the information to obtain operating states of various electrical appliances. One use case is to generate a family's itemized electricity bill using a family smart jack. The final aim is to help users to make scientific power utilization plans, reduce energy economic loss and eliminate potential safety hazards; the method helps the power grid dispatching department to improve the safety and stability of the power grid, save energy consumption, reduce carbon emission and the like. However, at present, no good management system can integrate distributed energy resources nearby, and a detailed energy consumption analysis report cannot be provided for each user so as to assist the user in performing reasonable energy consumption adjustment. While NILM was first proposed by Hart et al of the massachusetts institute of technology of the last century, bayesian algorithms, Hidden Markov Models (HMMs), Support Vector Machines (SVMs), neural network models (ANN), and the like, were subsequently used in the NILM field. With the rise of deep learning, a Convolutional Neural Network (CNN) and a Recurrent Neural Network (RNN) are both used in the field of power load decomposition. Such NILM methods are widely used because they only monitor the total power of the subscriber ports to monitor the activity of the load, involving low implementation cost and complexity. Experts propose an attention mechanism according to the research on human vision, and realize the efficient allocation of information processing resources. At present, models based on the mechanism are widely applied to various engineering technical fields, especially the field of power load decomposition, and are used for realizing a non-invasive load decomposition method.

Load decomposition device of remote monitoring consumer to smart jack inserts the power consumption scene as the carrier, connects the electric wire netting generating line and uses electrical apparatus, including data acquisition module (perception layer), data transmission module (access layer), data processing module (service layer), data feedback module (application layer).

At the sensing layer, the electricity used by a user is connected to an STM32F051 core control circuit (figure 6) through a voltage source and a relay circuit (figure 2), wherein the voltage source and the relay circuit take a TEA1522T chip and an HF115F chip as cores, have an isolation function and are used for controlling the opening and the closing of the circuit. The +5V voltage generated by the circuit is converted to +3.3V voltage suitable for subsequent devices by a voltage regulator (fig. 9). The collected voltage data and current data are converted into power data through a high-speed power metering circuit (figure 3) taking CS5463 as a core and are connected to an STM32F051 core control circuit, wherein the data are subjected to voltage sampling by using a voltage sampling circuit (figure 4) and adopting a resistance voltage division network; the current data reduces the alternating voltage and the large current to a value which can be directly measured by the instrument in proportion by using the TA0913 chip through an alternating current transformer circuit (figure 5), so that the current value is convenient to measure. The operating state of the device is shown by the indicator light status of the LED display circuit (fig. 7). And acquiring environmental data by using carbon dioxide, temperature and humidity sensors. All the finally acquired data enter the access layer through a WiFi transmission circuit (figure 8) taking an RAK415 chip as a core under the control of an STM32F051 core control circuit.

As shown in fig. 2, the voltage source and RELAY circuit connects the 220V ac power of the utility power to the device through the L terminal and the Lout terminal, and when the MCU _ RELAY1 terminal and the MCU _ RELAY2 terminal receive the control signal sent from the STM32F051 microcontroller, the RELAY part using the HF115F chip as the core realizes the opening and closing of the internal circuit of the device. When the relay part controls to open the circuit, external alternating current passes through and enters the voltage source part taking the TEA1522T chip as the core on the right side. The alternating current firstly passes through the RV1 piezoresistor, and when the voltage of the circuit is too large, the piezoresistor can control the voltage to a relatively fixed voltage value, absorb the redundant voltage and protect sensitive devices in a later-stage circuit. After entering the TEA1522T chip, the current acts as a voltage source and a current source in the device, and then passes through LC filtering to output +5V voltage for the subsequent modules.

The core chips of the voltage source and the relay circuit are a TEA1522T chip and an HF115F chip. The specification of an integrated power switch of the TEA1522T chip is 12 omega and 650V, the supply range of an operating integrated power supply is 80-276V, and the integrated power supply has self-protection functions of current, undervoltage, temperature, short-circuit winding and the like; the HF115F chip part requires a contact resistance smaller than 100m omega, a maximum switching current of 8A, a maximum switching power of 2000VA, a working humidity range of 5-85% RH and a working temperature of-40-85 ℃.

As shown in fig. 9(a), the +5V voltage generated by the voltage source and the relay circuit is converted into +3.3V voltage by the voltage regulator circuit with the LM1117 chip as the core, and then enters the high-speed power metering circuit.

As shown in fig. 3, the high-speed power metering circuit is based on a CS5463 chip, which is a highly integrated circuit with a serial interface and a delta-sigma analog-to-digital converter that is capable of high-speed power (power) calculation. The circuit works under +3.3V voltage, voltage data are collected by connecting VIN + and VIN-ends with a voltage sampling circuit, and current data are collected by connecting IIN + and IIN-ends with an alternating current transformer circuit, so that active power is calculated. The calculated power data enters the core control circuit of the STM32F051 through a CS5463_ RST end and a CS _ MEAS end.

The linearity of the electric energy data of the high-speed power calculation circuit in a dynamic range of 1000:1 is +/-0.1%, the differential mode analog input range of a voltage channel is +/-250 mV, and the differential mode analog input range of a current channel is +/-50 mV.

As shown in fig. 4, the voltage sampling circuit adopts a resistance voltage-dividing network to perform voltage sampling, and utilizes a resistor and a capacitor in an input loop to weaken the interference of high-frequency signals in input signals. The method has the characteristics of interference resistance and low cost.

As shown in fig. 5, the ac current transformer circuit collects current data in a manner of adding a resistor to a current transformer, and has good current and temperature characteristics and interference resistance. The circuit uses the TA0913-F6 vertical core-through miniature precise AC current transformer to reduce the AC heavy current to a value which can be directly measured by an instrument in proportion, and has the advantages of convenient installation, beautiful appearance, good mechanical and environmental resistance performance and strong voltage isolation capability.

The circuit of the alternating current transformer requires the ambient temperature of minus 55 ℃ to 85 ℃, the relative humidity of not more than 90 percent, the insulation resistance of more than 1000 MOmega, the power frequency 6000V 50HZ/1 minute can be borne by the electric strength, and the flame retardance accords with the UL94-Vo level.

As shown in fig. 6, the STM32F051 core control circuit receives active power data of the high-speed power calculation circuit, and performs CRC cyclic redundancy check on the active power data, so as to ensure the correctness of data transmission. Data which is verified to be correct is sent to a WiFi transmission circuit through a USART1_ TX end and a USART1_ RX end; when a user sends a command of remotely opening/closing the electric appliance at an application layer, the circuit realizes remote control of the control voltage source and the relay part in the relay circuit (shown in figure 2) and realizes the functions of protecting abnormal conditions of stable output, overheating, overcurrent, undervoltage, overvoltage and the like at each stage. And meanwhile, the current running state of the device is displayed through the LED lamps, as shown in fig. 7, the device flashes red light at a slow speed when being opened, flashes red light at a medium speed when running, and flashes red light at a fast speed when WiFi connection is carried out.

In addition, the perception layer still has other data acquisition functions, realizes the collection of information such as carbon dioxide concentration, air temperature, air humidity, air fine particle concentration.

The BYC11-CO2 gas sensor is selected for the carbon dioxide concentration acquisition function, a Pin Pin1 is used for signal output, a Pin4 is grounded, and a Pin5 is used for power supply input. This part sends a group of 16-bit data bits and 8-bit check bits for a total of 24-bit data, depicted as the duration of a high signal, with a low signal as an end marker.

The air temperature acquisition function selects a DHT11 sensor, uses a Pin Pin1 for power supply input, and outputs a Pin3 signal, wherein the Pin2 is grounded. The part sends a group of 24 bits of data, the upper 8 bits are check bits, the lower 16 bits are temperature data, and the highest bit is a positive and negative value identifier.

The air humidity acquisition function selects a DHT12 sensor, uses Pin Pin1 to supply power for input, and Pin2 signal output, Pin3 ground connection belong to and feel wet resistance humidity transducer, and reliability, stability are strong. This part sends a set of 24 bits of data, with the upper 8 bits being the check bits and the lower 16 bits being the temperature data.

The concentration acquisition function of the fine particulate matters in the air adopts an SDS011 sensor to measure the concentration of suspended particulate matters with the size of 0.3-10 mu g in the air. The sensor adopts a laser scattering principle, and can generate weak light scattering when laser irradiates on particles passing through a detection position.

As shown in fig. 8, the access layer uses a WiFi transmission circuit with a RAK415 chip as a core to send and receive data through a TCP/IP protocol, and accesses the electric energy data and other data collected by the sensing layer to the service layer. And simultaneously, the instruction of the user is transmitted from the server to the sensing layer to control the hardware equipment to work. The circuit realizes transparent transmission, works under the voltage of 3.3V generated by the voltage stabilizer shown in the figure 9(a) and the figure (b), and has the characteristics of stable performance and low power consumption.

The WiFi transmission circuit has the working voltage of 3.3V, the lowest power consumption of only 1-2 muA and the maximum baud rate of data stream communication of 921600bps, and has the data protection function of network disconnection and socket reconnection.

The service layer data preprocessing unit is used for carrying out noise filtering and preprocessing on the data, adjusting the acquired data into an input sequence format of a transfer learning model commonly adopted in the field of electric power data processing, and separating a training set and a test set; the data storage unit is used for storing the preprocessed data into a MySQL database; the intelligent analysis unit builds a transfer learning model based on an attention mechanism by adopting an Encoder-Decoder framework according to stored information, adjusts the hierarchical structure and the output dimension of an Encoder and a Decoder, trains an input sequence by the transfer learning model, continuously optimizes additional operation and update parameters in a sublayer, improves the training precision of the model, obtains the trained transfer learning model, tests the model and calculates the prediction accuracy of the model.

The transfer learning model technology belongs to the prior art, the working principle of the transfer learning model technology can refer to related transfer learning reference books or Chinese patent applications (application number: CN2018104459486, publication number: CN108664607A) and a paper research and implementation of the electric energy meter character automatic identification technology based on the neural network technology, and an author of the paper proposes that the transfer learning model technology is used for realizing the feature extraction of electric energy meter character data, and then a Softmax classifier in the model is used for classifying the features, so that a good identification effect is achieved, and the electric power parameter information collected by the electric energy meter is effectively processed. The model is applied to the NILM field, and the recognition efficiency is remarkably improved beyond the framework of the traditional recurrent neural network and the convolutional neural network.

In addition, the module converts binary data transmitted by the sensing layer environment data acquisition unit into decimal data, particularly sets the positive and negative values of the binary data according to low 16-bit data for temperature data, and calculates the concentration of the fine particulate matters in the air by utilizing a waveform classification system and a conversion formula of different particle sizes to obtain the concentration of the fine particulate matters in the air.

And the data feedback module of the application layer realizes generation of a statistical chart, drawing of a power curve and other related applications by using the data processed by the server.

The PC end application unit is mainly used by a power grid user, provides the power utilization condition in the current management area for power grid scheduling personnel, and feeds back data such as the total controllable load number, the total user number, the user activity, the service conditions of intelligent sockets in all regions of the country and the like processed by a service layer to a webpage, so that the power utilization condition in a controlled area can be conveniently monitored by the power grid user in real time, and convenience is provided for scheduling. In order to enable the application to be more humanized, the functions of customer problem management and customer demand response are provided for power grid users.

The PC end application unit comprises a real-time monitoring part; the real-time detection part is used for checking the total controllable load number, the total user number and the user activity in the current management and control range and checking the service conditions of all regional sockets across the country in real time.

The mobile terminal application unit is mainly used by a common power utilization user, and feeds back the power utilization information of the user processed by the service layer to the developed APP. And drawing a corresponding curve according to time by using the processed information of the electric power, the total power and the consumed electric quantity of each electric appliance, and providing a monthly power consumption information statistical graph or a daily power consumption information statistical graph and the like for the user. For more convenient use experience of a user, the unit provides a function of remotely controlling the electric appliance for the user.

The mobile terminal application unit comprises a power utilization information inquiry part, a remote control part and a charging pile service part. The electricity consumption information inquiry part is used for displaying electricity consumption at different time intervals and drawing an electricity consumption characteristic curve graph; the remote control part is used for remotely controlling the electric appliances, checking the power utilization information of the specific electric appliances and performing entrusted control by a user through a mobile phone.

In addition, an environment condition feedback function is designed, so that the environment condition in the power utilization scene is displayed for the mobile terminal user, and whether the environment condition is displayed or not is set according to the actual requirement of the user in practical application.

The foregoing shows and describes the general principles, essential features, and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the above embodiments, and that the principles of the present invention may be applied to any other embodiment without departing from the spirit and scope of the present invention. The scope of the invention is defined by the appended claims and equivalents thereof.

Claims (2)

1. A load decomposition device of remote monitoring electric equipment comprises a data acquisition module, a data transmission module, a data processing module and a data feedback module, wherein the data acquisition module acquires electric power and environmental parameters through a sensor and uploads the electric power and the environmental parameters to the data processing module through the data transmission module; the data processing module is used for processing the transmitted power parameters and feeding back the processed information to the application unit through the data feedback module; it is characterized in that:

the data acquisition module comprises a power parameter acquisition unit and an environmental parameter acquisition unit; the power parameter acquisition unit acquires total power data of user power consumption through the intelligent socket, wherein the sampling frequency of the intelligent socket is

The environment parameter acquisition unit acquires and collects carbon dioxide concentration, air temperature and humidity and air fine particle concentration information through a carbon dioxide concentration sensor, an air temperature and humidity sensor and a PM2.5 sensor;

the data transmission module transmits power utilization total power data and real-time data acquired by the sensor to the data processing module for processing through a WiFi transmission circuit taking an RAK415 chip as a core;

the data processing module comprises a data preprocessing unit, a data storage unit and an intelligent analysis unit; the data preprocessing unit is used for adjusting the acquired data into an input sequence format of a transfer learning model after carrying out noise filtering, isolation and amplification on the acquired data; the data storage unit is used for storing the preprocessed data into a database; the intelligent analysis unit is used for adjusting the hierarchical structure and the output dimension of the encoder and the decoder;

the data feedback module comprises a PC end application unit and a mobile end application unit; the PC side application unit feeds back the total controllable load number of the current area and the service condition data of the intelligent socket processed by the service layer to a webpage; and the mobile terminal application unit feeds back the user electricity utilization information processed by the service layer to the developed APP.

2. The load shedding apparatus for remotely monitoring electric devices according to claim 1, wherein: the electric power parameter acquisition unit comprises a voltage source and relay circuit, a voltage stabilizer circuit, a CS5463 high-speed power metering circuit, a voltage sampling circuit, an alternating current transformer circuit, an ARMCortex-M series STM32F051 core chip control circuit and a WiFi transmission circuit; the voltage source and relay circuit is connected with a zero line and a live line on a strong current side, and the 220V alternating current of the commercial power is converted into +5V voltage for subsequent modules by controlling the on-off of the relay; the voltage stabilizer circuit converts the +5V voltage into +3.3V voltage for subsequent electronic components; the CS5463 high-speed power metering circuit calculates power data by using the voltage data acquired by the voltage sampling circuit and the current data acquired by the alternating current transformer circuit through a multiplier, and transmits the power data to the data processing module through the WiFi transmission circuit under the control of the STM32F051 core chip control circuit.

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