CN213457149U - Embedded non-invasive load identification system - Google Patents
Embedded non-invasive load identification system Download PDFInfo
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- CN213457149U CN213457149U CN202022268385.3U CN202022268385U CN213457149U CN 213457149 U CN213457149 U CN 213457149U CN 202022268385 U CN202022268385 U CN 202022268385U CN 213457149 U CN213457149 U CN 213457149U
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Abstract
The utility model provides an embedded non-invasive load identification system. The method comprises the following steps: the embedded equipment terminal consists of a STEM32F767 chip, an electric energy metering chip connected with the STEM32F767 chip, a voltage transformer and a current transformer; the other ends of the electric energy metering chip, the voltage transformer and the current transformer are connected with the intelligent ammeter; the embedded equipment terminal is used for identifying the accessed electric equipment; and the display equipment is in communication connection with the embedded equipment terminal and is used for displaying the identification result of the embedded equipment terminal. The utility model discloses integrated electric energy measurement chip, voltage transformer, current transformer data collection on STM32F767 chip utilizes the artificial intelligence function that STM32F767 chip has simultaneously, directly operates recognition algorithm in STM32F767 chip, realizes embedded non-invasive power consumption load discernment, need not extra server and provides the operation, simple structure, and equipment cost is lower. And the system can operate normally without a network.
Description
Technical Field
The utility model relates to a non-intrusive load monitoring (NILM) field especially relates to an embedded non-intrusive load identification system.
Background
NILM is a hotspot in the field of smart metering of today's power systems. In recent years, the heat level has been increasing day by day. The embedded non-invasive power identification module is installed on the household electricity meter, and the type, the state and the power utilization power of the power equipment in the power utilization range are analyzed and obtained by utilizing the neural network technology, so that the real-time monitoring on the starting and stopping of different equipment and the power consumption is realized. By combining with effective power management, the electric energy can be saved under the condition of not influencing the user experience.
Researches show that the actual energy consumption of the energy consumption in the building is provided for consumers, the energy-saving power of the consumers can be stimulated, and the energy can be effectively saved by 10-20% according to statistics. Therefore, the non-invasive load detection device has wide application prospect.
Most of the prior NILM methods use a cloud server as a data processing center. The collected data are transmitted to a server through wireless communication, and then the server processes the data to obtain a corresponding result. Considering that electricity households and units exceed tens of millions, the method needs a large amount of calculation support of a server. Once a problem occurs with the network, all systems will crash.
Disclosure of Invention
In order to overcome the defects of the prior art, the utility model provides an embedded non-invasive load identification system.
In order to achieve the above purpose, the utility model adopts the following technical scheme: an embedded non-intrusive load identification system, comprising:
the embedded equipment terminal consists of a STEM32F767 chip, an electric energy metering chip connected with the STEM32F767 chip, a voltage transformer and a current transformer; the other ends of the electric energy metering chip, the voltage transformer and the current transformer are connected with an intelligent ammeter; the embedded equipment terminal is used for identifying the accessed electric equipment;
and the display equipment is in communication connection with the embedded equipment terminal and is used for displaying the identification result of the embedded equipment terminal.
As an improved scheme of the embedded non-intrusive load identification system, the system further comprises a cloud end, the embedded equipment terminal is connected with the cloud end in a wireless mode, and the cloud end is connected with the display equipment in a wireless or wired communication mode.
As an improved scheme of the embedded non-invasive load identification system, the embedded equipment terminal is further connected with a WiFi module, the WiFi module is connected with the cloud end, and the cloud end is connected with the display equipment through the Ethernet.
As an improvement of the embedded non-intrusive load identification system, the display device is a mobile terminal device (such as a mobile phone) or a PC.
As an improved scheme of the embedded non-intrusive load identification system, the embedded equipment terminal is also connected with a storage module.
Compared with the prior art, the embedded non-intrusive load identification system architecture has the advantages that: the design structure is simple, and no extra server is needed for providing operation. In addition, the layout is reasonable, and the equipment cost is low.
Drawings
Fig. 1 is the utility model discloses well embedded non-invasive load identification system's schematic structure diagram, wherein, 1 is smart electric meter, 2 is embedded equipment terminal, and 3 is the high in the clouds, and 4 are display device.
Fig. 2 is a hardware structure diagram of the middle embedded device terminal of the present invention.
Detailed Description
As shown in fig. 1, an embedded non-intrusive load identification system includes:
the hardware structure of the embedded equipment terminal 2 is shown in fig. 2 and comprises a STEM32F767 chip, an electric energy metering chip connected with the STEM32F767 chip, a voltage transformer and a current transformer; the other ends of the electric energy metering chip, the voltage transformer and the current transformer are connected with the intelligent ammeter 1; the embedded equipment terminal 2 is used for identifying the accessed electric equipment;
and the display device 4 is in communication connection with the embedded device terminal 2 and is used for displaying the identification result of the embedded device terminal 2.
During operation, the embedded device terminal 2 collects the electric power data of the intelligent electric meter 1 through the connected electric energy metering chip, the voltage transformer and the current transformer, then transmits the electric power data to the STEM32F767 chip to directly process and identify the operating electric equipment, and transmits the identification result to the display device 4 for displaying.
The utility model discloses integrated electric energy measurement chip, voltage transformer, current transformer data collection on STM32F767 chip utilizes the artificial intelligence function that STM32F767 chip has simultaneously, directly operates recognition algorithm in STM32F767 chip, realizes embedded non-invasive power consumption load discernment, need not extra server and provides the operation, simple structure, and equipment cost is lower. And the system can operate normally without a network.
In a preferred embodiment, a training load identification model is established by adopting a convolutional neural network and operates on an STM32F767 chip, sampling data of active power, reactive power, current signals and voltage signals are acquired from data acquired by an electric energy metering chip, a voltage transformer and a current transformer and are input into the STM32F767 chip, and accessed electric equipment and electric information thereof can be identified by the trained load identification model after data processing. And finally, sending the load identification result to the user.
Preferably, the system further comprises a cloud end 3, such as a smart cloud, the embedded device terminal 2 is connected with the cloud end 3, and the cloud end 3 is connected with the display device 4 in a wireless or wired communication mode. The embedded device terminal 2 is further connected with a WiFi module, and the embedded device terminal 2 transmits data to the cloud end 3 through the WiFi module. In order to realize the functions, the firmware of the smart cloud needs to be programmed into the WiFi module.
In the above, the display device 4 is mainly a mobile terminal device or a PC, which is convenient for the user to check and monitor in real time.
In addition, the embedded device terminal 2 may further be connected to a storage module, such as an external storage device like a TF card, for storing the data processing result and the identification result in real time, so that the user can check the past power consumption condition.
The power metering chip model can adopt IM1281B, and the WiFi module can adopt ESP8266, but is not limited thereto.
It should be understood that the above examples are only for clarity of illustration and are not intended to limit the embodiments. Other variations and modifications will be apparent to persons skilled in the art in light of the above description. This need not be, nor should all embodiments be exhaustive. And obvious changes and modifications may be made without departing from the scope of the present invention.
Claims (5)
1. An embedded non-intrusive load identification system, comprising:
the embedded equipment terminal (2) is composed of a STEM32F767 chip, an electric energy metering chip connected with the STEM32F767 chip, a voltage transformer and a current transformer; the other ends of the electric energy metering chip, the voltage transformer and the current transformer are connected with the intelligent ammeter (1); the embedded equipment terminal (2) is used for identifying the accessed electric equipment;
the display device (4) is in communication connection with the embedded device terminal (2) and is used for displaying the identification result of the embedded device terminal (2).
2. The embedded non-intrusive load recognition system of claim 1, further comprising a cloud (3), wherein the embedded device terminal (2) is wirelessly connected with the cloud (3), and the cloud (3) is connected with the display device (4) in a wireless or wired communication manner.
3. The embedded non-intrusive load recognition system as defined in claim 2, wherein the embedded device terminal (2) is further connected with a WiFi module, and is connected with a cloud end (3) through the WiFi module, and the cloud end (3) is connected with the display device (4) through an ethernet.
4. An embedded non-intrusive load recognition system as defined in any of claims 1-3, wherein the display device (4) is a mobile terminal device or a PC.
5. An embedded non-intrusive load recognition system as defined in any of claims 1-3, wherein a memory module is further connected to the embedded device terminal (2).
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202022268385.3U CN213457149U (en) | 2020-10-13 | 2020-10-13 | Embedded non-invasive load identification system |
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| Application Number | Priority Date | Filing Date | Title |
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| CN202022268385.3U CN213457149U (en) | 2020-10-13 | 2020-10-13 | Embedded non-invasive load identification system |
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| CN213457149U true CN213457149U (en) | 2021-06-15 |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113626305A (en) * | 2021-06-23 | 2021-11-09 | 国网浙江省电力有限公司营销服务中心 | Debugging method and debugging system of non-invasive load identification algorithm |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113626305A (en) * | 2021-06-23 | 2021-11-09 | 国网浙江省电力有限公司营销服务中心 | Debugging method and debugging system of non-invasive load identification algorithm |
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