CN117239926A - Power distribution area monitoring system and method based on multi-parameter sensing - Google Patents
Power distribution area monitoring system and method based on multi-parameter sensing Download PDFInfo
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Abstract
The invention relates to the technical field of monitoring of power distribution areas, and provides a power distribution area monitoring system based on multi-parameter sensing, which comprises the following components: the invention further provides a power distribution station monitoring method based on multi-parameter perception. According to the invention, panoramic image monitoring can be carried out on the distribution line through a multi-view image analysis technology, so that the safety external damage monitoring of the periphery of a distribution area is realized; based on a multi-state sensing fusion monitoring digital twin technology, abnormal states of the transformer and the line temperature in the distribution area can be monitored; based on wavelet signal fault analysis positioning and three-phase wave recording technology, the grounding short circuit judgment can be carried out on the distribution line so as to accurately and rapidly position the fault of the line, thereby ensuring the safe operation of the distribution transformer area.
Description
Technical Field
The invention relates to the technical field of monitoring of power distribution areas, in particular to a power distribution area monitoring system and method based on multi-parameter sensing.
Background
Distribution transformer areas, also known as substations or substations, are a critical facility in an electrical power system for distributing electrical energy to individual subscribers. It generally includes distribution transformers, high voltage switching devices, metering devices, relay protection devices, communication devices, and the like. The main function of the distribution transformer area is to convert the electric energy received from the power plant or transmission system into a voltage level suitable for the user to use, and to distribute and protect.
Along with the acceleration of the urban process, the electric power demand continuously grows, the safe and stable operation of the distribution transformer area faces more and more pressure, and the distribution transformer area is used as a key link of urban power supply, so that the safe and stable operation of the distribution transformer area is very important. At present, a low-voltage distribution area in a power grid is weak in digital comprehensive monitoring, line faults cannot be effectively positioned, external damage behaviors cannot be timely restrained, faults or accidents can be caused under serious conditions, and the cause of the faults cannot be traced, so that effective monitoring and fault diagnosis of the distribution area are particularly necessary.
Disclosure of Invention
In order to overcome the defects that the low-voltage distribution area in the current power grid is weak in digital comprehensive monitoring, line faults cannot be effectively positioned, external damage behaviors cannot be timely restrained, faults or accidents can be caused under serious conditions, and the causes of the faults cannot be traced, the invention has the following technical problems: a power distribution area monitoring system and method based on multi-parameter sensing are provided, and the purpose is to improve the operation reliability and safety of the power distribution area.
The invention provides the following technical scheme: a power distribution substation monitoring system based on multi-parameter sensing, comprising:
the data acquisition module is used for acquiring various operation parameters of the power distribution area;
the data preprocessing module is used for preprocessing the acquired original data, wherein the preprocessing comprises data cleaning, filtering and denoising operations;
the multispectral multi-view image monitoring module is used for monitoring different areas of the power distribution area in real time and acquiring key information quantity;
the data transmission module is used for transmitting the preprocessed data to the control center through the communication network so as to analyze and process the preprocessed data;
the data storage module is used for storing the collected real-time data and historical data so as to inquire and analyze the collected real-time data and the historical data in the future;
the control center is used for carrying out load prediction, power quality analysis and fault diagnosis on the collected data;
the monitoring display module is used for monitoring the running condition of the power distribution area in real time and displaying various running parameters to operators in a visual mode;
the alarm management module is used for carrying out early warning on potential faults and risks according to analysis results and notifying related personnel to process;
the remote control module is used for realizing remote control including opening and closing of a switch and adjustment of parameters for the distribution area;
and the system maintenance module is used for periodically checking, maintaining and upgrading the system to ensure the stability and reliability of the system.
Further, the data acquisition module comprises a sensor, an intelligent ammeter and a three-phase oscillograph, and is used for acquiring voltage, current, power and temperature data of the line monitoring points of the distribution transformer area in real time.
Further, the multispectral and multi-view image monitoring module comprises a multispectral camera and a thermal infrared imager.
Further, the key information includes wire temperature, pole switch contact temperature and pole tilt information.
Further, the multi-spectrum camera channel is not less than 4 paths, the infrared thermal imaging adopts a vanadium oxide uncooled detector, and the resolution is not less than 256×192.
Further, the fault diagnosis comprises diagnosis of ground faults and short-circuit faults of the distribution transformer area lines, and the specific working steps are as follows:
step one: synchronous acquisition of three-phase voltage and current signals of a distribution line is carried out by a three-phase oscillometer;
step two: performing wavelet transformation on the collected three-phase voltage and current signals to obtain wavelet coefficients;
step three: extracting characteristic values including energy and mutation indexes by analyzing wavelet coefficients;
step four: judging fault types according to the characteristic values, wherein the fault types comprise ground short circuits and interphase short circuits;
step five: determining the position of fault occurrence by utilizing the positioning characteristic of wavelet transformation;
step six: analyzing waveforms of the three-phase voltage and the three-phase current, and further verifying the fault type and the fault position;
step seven: and outputting the fault judgment result and the three-phase wave recording analysis result.
Further, the system also comprises a construction work vehicle identification module, wherein the construction work vehicle including a bulldozer, an engineering vehicle and a lifter is identified by using AI, and the surrounding environment of the construction work vehicle is monitored, and the specific steps are as follows:
a. collecting image data of construction operation vehicles under different types, angles and light conditions, wherein the image data is from real-time monitoring video or the Internet of a construction site;
b. marking the construction work vehicle in the collected image data;
c. constructing a convolutional neural network deep learning model based on a deep learning framework TensorFlow;
d. training the constructed deep learning model by using the marked image data;
e. evaluating the performance of the model using the test dataset;
f. and deploying the trained model into an actual construction site monitoring system, and identifying and monitoring the construction operation vehicle in real time.
The invention also provides a distribution station monitoring method based on multi-parameter sensing, which comprises the following steps:
s1, deploying various multispectral cameras, infrared thermal imagers and sensors in a power distribution area, and collecting image, fault, temperature and inclination angle data, wherein the data comprise real-time data acquired at high frequency and historical data in a period of time;
s2, denoising, filtering and standardized preprocessing are carried out on the acquired data, and time synchronization is carried out on the data of different data sources;
s3, constructing a virtual model which completely corresponds to the actual power distribution station by utilizing a digital twin technology, and simulating the running condition of the actual power distribution station in real time;
s4, based on the constructed data twin model, various parameters of the power distribution area are monitored in real time, and a threshold value and an early warning rule which can immediately send early warning information when equipment fails, the temperature is too high and the inclination angle is abnormal are set;
and S5, adjusting and optimizing the running condition of the distribution area according to the safety early warning result, and feeding the optimized result back to the data twin model for continuous iteration and optimization.
Further, the method also comprises the step of continuously collecting new data to update and optimize the model periodically, wherein the collected and used image data meets the requirements of related data privacy regulations.
Further, the adjusting and optimizing includes maintaining the malfunctioning device or adjusting the device position.
Compared with the prior art, the invention has the following advantages:
the invention solves the problem of visualization of the distribution line channel through a multi-view image analysis technology, can carry out panoramic image monitoring on the distribution line, and realizes the safety external damage supervision of the periphery of a distribution area; based on a multi-state sensing fusion monitoring digital twin technology, through integrating data such as fault temperature, inclination angle, images and the like on various state parameters of a power distribution area, abnormal states of transformers and lines of the power distribution area can be monitored, and fault trend judgment can be carried out on the data of the area; based on wavelet signal fault analysis positioning and three-phase wave recording technology, the grounding short circuit judgment can be carried out on the distribution line so as to accurately and rapidly position the fault of the line, thereby ensuring the safe operation of the distribution transformer area.
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FIG. 1 is a schematic diagram of a power distribution substation monitoring system based on multi-parameter sensing according to the present invention;
fig. 2 is a schematic flow chart of a method for monitoring a distribution area based on multi-parameter sensing according to the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1: a power distribution substation monitoring system based on multi-parameter sensing, as shown with reference to fig. 1, comprising:
the data acquisition module is used for acquiring various operation parameters of the power distribution station, and specifically comprises a sensor, an intelligent ammeter and a three-phase oscillometer, and is used for acquiring voltage, current, power and temperature data of a line monitoring point of the power distribution station in real time;
the data preprocessing module is used for preprocessing the acquired original data, wherein the preprocessing comprises data cleaning, filtering and denoising operations;
the multispectral multi-view image monitoring module is used for monitoring and acquiring key information quantity including wire temperature, pole switch contact temperature and pole inclination information in different areas of a distribution area in real time, and concretely comprises a multispectral camera and an infrared thermal imager, wherein a multispectral camera channel is 20 paths, industrial-level high-definition gun type cameras are adopted for front-view channel lenses and rear-view channel lenses, 200 ten thousand night vision lenses are matched, and illuminance is less than or equal to 0.001Lux; the down-looking camera is provided with a 500-ten-thousand-pixel wide-angle lens, the field angle is 120 degrees, the infrared thermal imaging adopts a vanadium oxide uncooled detector, the resolution ratio is not lower than 256 multiplied by 192, the intelligent monitoring of fire points is supported, the infrared temperature measurement and abnormal temperature alarm are supported, and the linkage function of thermal imaging and visible light is also supported;
the data transmission module is used for transmitting the preprocessed data to the control center through the communication network so as to analyze and process, the communication transmission mode adopts 2G/3G/4G wireless transmission, the telecommunication, the communication and the mobile self-adaption are met, the 2G, 3G and 4G networks of three operators are supported, and the operators can be selected according to the field condition;
the data storage module is used for storing the collected real-time data and historical data so as to inquire and analyze the collected real-time data and the historical data in the future;
the control center is used for carrying out load prediction, power quality analysis and fault diagnosis on the collected data, wherein the fault diagnosis comprises the diagnosis on the grounding fault and the short-circuit fault of the distribution transformer area line, and the specific working steps are as follows:
step one: synchronous acquisition of three-phase voltage and current signals of a distribution line is carried out by a three-phase oscillometer;
step two: performing wavelet transformation on the collected three-phase voltage and current signals to obtain wavelet coefficients;
step three: extracting characteristic values including energy and mutation indexes by analyzing wavelet coefficients;
step four: judging fault types according to the characteristic values, wherein the fault types comprise faults such as grounding short circuits, interphase short circuits and the like in a distribution transformer area system circuit;
step five: the method has the advantages that the position of the fault is determined by utilizing the positioning characteristic of wavelet transformation, and as the wavelet transformation can decompose the signals into components with different time scales and different frequencies, the edges, peaks or other local features in the signals can be extracted, the fundamental frequency, harmonic waves or other frequency components in the signals can be extracted, the signals can be subjected to multi-scale decomposition through the wavelet transformation, so that the time and frequency positioning is realized, and the fault source is accurately positioned.
Step six: analyzing waveforms of the three-phase voltage and the three-phase current, and further verifying the fault type and the fault position;
step seven: and outputting the fault judgment result and the three-phase wave recording analysis result.
The monitoring display module is used for monitoring the running condition of the power distribution area in real time, displaying various running parameters to operators in a visual mode, and for example, updating the latest running parameters in real time in a monitoring display screen;
the alarm management module is used for carrying out early warning on potential faults and risks according to analysis results and notifying related personnel to process;
the remote control module is used for realizing remote control including opening and closing of a switch and adjustment of parameters for the distribution area;
and the system maintenance module is used for periodically checking, maintaining and upgrading the system to ensure the stability and reliability of the system.
As a more preferred embodiment, the system further comprises a construction work vehicle identification module for identifying a construction work vehicle including a bulldozer, an engineering vehicle and a lifter by using the AI, and monitoring the surrounding environment of the construction work vehicle to maintain the safety of the production environment, and the method comprises the following specific steps:
a. collecting image data of construction operation vehicles under different types, angles and light conditions, wherein the image data is from real-time monitoring videos of a construction site or the Internet, and collecting construction operation vehicle images under different types, angles and light conditions, so that the image data can be ensured to have diversity, and the generalization capability of a model is improved;
b. marking construction work vehicles in the collected image data, and determining which images contain the construction work vehicles such as bulldozers, engineering vehicles, elevators and the like, wherein the data marking can be completed manually or assisted by using some automatic tools;
c. constructing a convolutional neural network deep learning model based on a deep learning framework TensorFlow;
d. training the constructed deep learning model by using the marked image data, wherein the training process also comprises optimization means such as model parameter adjustment, learning rate adjustment and the like, and the detailed description is omitted;
e. evaluating the performance of the model using the test dataset to ensure that the model is able to accurately identify the construction work vehicle in the actual application scenario;
f. and deploying the trained model into an actual construction site monitoring system, and identifying and monitoring the construction operation vehicle in real time.
Example 2: a power distribution area monitoring method based on multi-parameter sensing, as shown in fig. 2, comprises the following steps:
s1, deploying various multispectral cameras, infrared thermal imagers and sensors in a power distribution area, collecting image, fault, temperature and inclination angle data, wherein the data comprise real-time data acquired at high frequency and historical data in a period of time, and periodically updating and optimizing a model by continuously collecting new data, wherein the collected and used image data meet the requirements of related data privacy regulations;
s2, denoising, filtering and standardized preprocessing are carried out on the acquired data, and time synchronization is carried out on the data of different data sources, wherein the time synchronization can ensure that the data among the different data sources are consistent in time, so that the accuracy of a data analysis result is ensured, and if the data time is not synchronous, data misreading or error analysis can be caused;
s3, constructing a virtual model which completely corresponds to the actual power distribution station by utilizing a digital twin technology, and simulating the running condition of the actual power distribution station in real time;
s4, based on the constructed data twin model, various parameters of the power distribution area are monitored in real time, and a threshold value and an early warning rule which can immediately send early warning information when equipment fails, the temperature is too high and the inclination angle is abnormal are set;
and S5, adjusting and optimizing the running condition of the distribution area according to the safety precaution result, including maintaining fault equipment or adjusting the position of the equipment, and feeding the optimized result back to the data twin model for continuous iteration and optimization.
While the invention has been described with reference to exemplary embodiments, it is to be understood that the invention is not limited to the disclosed exemplary embodiments. The scope of the following claims is to be accorded the broadest interpretation so as to encompass all such modifications and equivalent structures and functions.
Claims (10)
1. A power distribution substation monitoring system based on multi-parameter sensing, comprising:
the data acquisition module is used for acquiring various operation parameters of the power distribution area;
the data preprocessing module is used for preprocessing the acquired original data, wherein the preprocessing comprises data cleaning, filtering and denoising operations;
the multispectral multi-view image monitoring module is used for monitoring different areas of the power distribution area in real time and acquiring key information quantity;
the data transmission module is used for transmitting the preprocessed data to the control center through the communication network so as to analyze and process the preprocessed data;
the data storage module is used for storing the collected real-time data and historical data so as to inquire and analyze the collected real-time data and the historical data in the future;
the control center is used for carrying out load prediction, power quality analysis and fault diagnosis on the collected data; the monitoring display module is used for monitoring the running condition of the power distribution area in real time and displaying various running parameters to operators in a visual mode;
the alarm management module is used for carrying out early warning on potential faults and risks according to analysis results and notifying related personnel to process;
the remote control module is used for realizing remote control including opening and closing of a switch and adjustment of parameters for the distribution area;
and the system maintenance module is used for periodically checking, maintaining and upgrading the system to ensure the stability and reliability of the system.
2. The power distribution substation monitoring system based on multi-parameter sensing according to claim 1, wherein the data acquisition module comprises a sensor, a smart meter and a three-phase oscillometer, and is used for acquiring voltage, current, power and temperature data of line monitoring points of the power distribution substation in real time.
3. The multi-parameter sensing-based power distribution substation monitoring system according to claim 1, wherein the multi-spectral multi-view image monitoring module comprises a multi-spectral camera and a thermal infrared imager.
4. The multi-parameter sensing-based power distribution substation monitoring system according to claim 1, wherein the key information amounts include wire temperature, pole-on-switch contact temperature, and pole tilt information.
5. The multi-parameter sensing-based power distribution substation monitoring system according to claim 2, wherein said multi-spectral camera channels are not less than 4 paths, and said infrared thermal imaging employs vanadium oxide uncooled detectors ， And the resolution is not lower than 256×192.
6. The multi-parameter sensing-based power distribution substation monitoring system according to claim 1, wherein the fault diagnosis includes diagnosis of ground faults and short-circuit faults of the power distribution substation line, and the specific working steps are as follows:
step one: synchronous acquisition of three-phase voltage and current signals of a distribution line is carried out by a three-phase oscillometer;
step two: performing wavelet transformation on the collected three-phase voltage and current signals to obtain wavelet coefficients;
step three: extracting characteristic values including energy and mutation indexes by analyzing wavelet coefficients;
step four: judging fault types according to the characteristic values, wherein the fault types comprise ground short circuits and interphase short circuits;
step five: determining the position of fault occurrence by utilizing the positioning characteristic of wavelet transformation;
step six: analyzing waveforms of the three-phase voltage and the three-phase current, and further verifying the fault type and the fault position;
step seven: and outputting the fault judgment result and the three-phase wave recording analysis result.
7. The multi-parameter sensing-based power distribution substation monitoring system according to claim 1 or 6, further comprising a construction work vehicle identification module for identifying a construction work vehicle including a bulldozer, an engineering vehicle, and an elevator by using AI, and monitoring a surrounding environment of the construction work vehicle, comprising the steps of:
a. collecting image data of construction operation vehicles under different types, angles and light conditions, wherein the image data is from real-time monitoring video or the Internet of a construction site;
b. marking the construction work vehicle in the collected image data;
c. constructing a convolutional neural network deep learning model based on a deep learning framework TensorFlow;
d. training the constructed deep learning model by using the marked image data;
e. evaluating the performance of the model using the test dataset;
f. and deploying the trained model into an actual construction site monitoring system, and identifying and monitoring the construction operation vehicle in real time.
8. The power distribution area monitoring method based on multi-parameter sensing is characterized by comprising the following steps of:
s1, deploying various multispectral cameras, infrared thermal imagers and sensors in a power distribution area, and collecting image, fault, temperature and inclination angle data, wherein the data comprise real-time data acquired at high frequency and historical data in a period of time;
s2, denoising, filtering and standardized preprocessing are carried out on the acquired data, and time synchronization is carried out on the data of different data sources;
s3, constructing a virtual model which completely corresponds to the actual power distribution station by utilizing a digital twin technology, and simulating the running condition of the actual power distribution station in real time;
s4, based on the constructed data twin model, various parameters of the power distribution area are monitored in real time, and a threshold value and an early warning rule which can immediately send early warning information when equipment fails, the temperature is too high and the inclination angle is abnormal are set;
and S5, adjusting and optimizing the running condition of the distribution area according to the safety early warning result, and feeding the optimized result back to the data twin model for continuous iteration and optimization.
9. The multi-parameter awareness based power distribution substation monitoring method of claim 8 further comprising periodically updating and optimizing the model by continuously collecting new data, wherein the collected and used image data meets relevant data privacy regulations.
10. The multi-parameter sensing-based power distribution substation monitoring method according to claim 8, wherein the adjusting and optimizing includes maintaining faulty equipment or adjusting equipment location.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117638928A (en) * | 2024-01-26 | 2024-03-01 | 山西林业职业技术学院 | Intelligent power distribution network management system based on cloud computing |
| CN117893203A (en) * | 2024-03-18 | 2024-04-16 | 国网江苏省电力有限公司无锡供电分公司 | Operation and maintenance analysis processing system for mechanical structure of high-voltage switch cabinet |
| CN118071387A (en) * | 2024-04-22 | 2024-05-24 | 厦门市盛迅信息技术股份有限公司 | Electric power facility operation cost prediction method and system based on digital twin |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117638928A (en) * | 2024-01-26 | 2024-03-01 | 山西林业职业技术学院 | Intelligent power distribution network management system based on cloud computing |
| CN117638928B (en) * | 2024-01-26 | 2024-04-12 | 山西林业职业技术学院 | Intelligent power distribution network management system based on cloud computing |
| CN117893203A (en) * | 2024-03-18 | 2024-04-16 | 国网江苏省电力有限公司无锡供电分公司 | Operation and maintenance analysis processing system for mechanical structure of high-voltage switch cabinet |
| CN117893203B (en) * | 2024-03-18 | 2024-05-10 | 国网江苏省电力有限公司无锡供电分公司 | Operation and maintenance analysis processing system for mechanical structure of high-voltage switch cabinet |
| CN118071387A (en) * | 2024-04-22 | 2024-05-24 | 厦门市盛迅信息技术股份有限公司 | Electric power facility operation cost prediction method and system based on digital twin |
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