CN114189044A - A fusion method of substation monitoring technology based on power Internet of things - Google Patents

Abstract

The invention discloses a substation monitoring technology fusion method based on the power internet of things, including sensors and a system master station. The intelligent monitoring terminal transmits the collected data to the intelligent information aggregator through the first gateway for data aggregation. The aggregated data is transmitted through the second gateway using 4G network and industrial-grade Ethernet network, and then transmitted to the system master station for data transmission. Data analysis and calculation, the results are stored and displayed, and early warning information is given. At the same time, the system master station will transmit the obtained results to the IoT cloud platform through the wireless public network and the IoT substation, and the system master station will also transmit the results to the IoT cloud platform. Directly transmit data information to the local background system to achieve the power Internet of Things. The invention can realize the security intelligent perception of the equipment of the substation.

Description

A fusion method of substation monitoring technology based on power Internet of things

technical field

The patent of the invention belongs to the field of monitoring of substations, and in particular relates to a method for integrating monitoring technologies of substations based on the power Internet of things.

Background technique

With the rapid development of social economy, in order to adapt to China's energy shortage problem and the characteristics of regional distribution of load consumption, and to match the grid development mode adopted by China's current and future social development, vigorously developing new energy has become an inevitable trend. Realize large-scale and high-efficiency allocation of energy resources. In the construction of smart grid, smart substations have become one of the core platforms. At present, the safety monitoring of substations is almost always based on people. First of all, people cannot do 24 hours a day. It cannot guarantee the inspection accuracy of the equipment. Secondly, it is difficult to monitor the inside of the equipment and the narrow equipment room. The work of the inspectors is more difficult, and the original old station does not have the detection of partial discharge information, switch cabinets and GIS rooms, etc. Hidden faults in important locations cannot be found in time, and underground cable trenches are not equipped with groundwater intrusion detection equipment. Sewage soaking will damage the insulation performance of cables, lack of video surveillance systems and access control systems, weak visualization capabilities, and low security levels.

The functions of each system are independent. In most cases, manual troubleshooting is still required. The real-time performance of traditional detection is weak, and the data is discontinuous, so it is impossible to continuously analyze the operation of the equipment. As the core and hub of the power grid system, the substation plays the role of collecting electric energy, raising and lowering voltage and distributing electric energy. Whether its operation is safe or not is directly related to the safety and stability of the power grid. It is of great significance for various electrical equipment to provide a safe and stable operating environment, and the maintenance cost of the substation in the later period will be greatly reduced.

SUMMARY OF THE INVENTION

The technical problem to be solved by the present invention is: to overcome the deficiencies of the prior art, to provide a method that integrates the Internet of Things and the existing power grid information system, realizes the integration of power grid operation management and safety environment information, and can diagnose and diagnose after comprehensive processing. The integration method of substation monitoring technology based on the power Internet of Things, which is based on the health status of equipment and gives early warning and alarm information.

The technical scheme adopted by the present invention for solving the technical problem is:

A substation monitoring technology fusion method based on the power Internet of things, including sensors and a system master station, the sensors are arranged in the equipment and the environment in the substation that need to monitor the operating state, and each of the sensors utilizes wireless and its own intelligence. Monitoring terminal connection, the sensors include temperature sensor, humidity sensor, SF6 gas concentration sensor and partial discharge detection sensor. In addition to each sensor, it also includes video camera and access control status switch collector. The sensor, video camera and access control status switch collector collect their respective The real-time parameter information of the responsible equipment is transmitted to the respective intelligent monitoring terminals, and each of the intelligent monitoring terminals transmits the collected data to the intelligent information aggregator through the first gateway for data aggregation, that is, the intelligent monitoring terminal and the intelligent information Collectors together form the data acquisition layer.

The aggregated data is transmitted through the second gateway using 4G network and industrial-grade Ethernet network, and transmitted to the system master station and the local background, that is, the data transmission layer is formed. The system master station analyzes and calculates the data, and obtains The results are stored and displayed, and early warning information is given. At the same time, the system master station will transmit the obtained results to the IoT cloud platform via the wireless public network and the IoT sub-station, and the system master station will also directly report to the local background. The system transmits data information to achieve the power Internet of Things, which is convenient for operators to monitor in real time.

When the sensor collects data, a temperature compensator is installed for each sensor, and the sensor transmits the monitored data stream to the first MCU module in the corresponding intelligent monitoring terminal, and the first MCU module in the corresponding intelligent monitoring terminal. An MCU module removes invalid and disturbed signal bands and reduces current noise through a signal filter and a noise reduction module respectively, and stores data in time through the first memory chip and the first synchronous dynamic random access memory after the processing is completed, Then, the signal is sent through the first wireless radio frequency module. When sending, the signal is enhanced and amplified through the first power amplifier, so that the transmission quality and distance are better guaranteed, and finally the data signal is sent through the first antenna.

When the information aggregator receives the data sent by the intelligent monitoring terminal, it uses the second antenna for wireless reception, and after receiving the data, it processes the signal through the second power amplifier on it, and transmits it to the second wireless radio frequency module Perform signal conversion, after the conversion, the second MCU module collects and stores data through the second memory chip and the second synchronous dynamic random access memory, and the stored data is amplified and enhanced by the third power amplifier. The second gateway transmits the amplified data to the third MCU module in the system main station, and the third MCU module performs fusion analysis and processing on the data information collected by the intelligent information aggregator, and the result obtained is in the It can be displayed on the system interface of the local background system or the mobile APP, locate and evaluate the faults of the equipment in the substation and the health status of the equipment, display early warning information for the equipment in an unhealthy state, and send alarm information for the equipment that has failed. .

When performing fusion analysis and processing, the sensor information needs to be refined using formula (1) first.

The formula and extraction result are expressed as:

变电站设备演化控制参数特征输出值；in,

Substation equipment evolution control parameter characteristic output value;

i: represents the discrete sampling length of fault information;

a _i : is the amplitude;

p: is the cumulative total value;

n: The sampling value of the input sample for each sensor information;

The sampled values of the extracted parameter features are further processed and fused, as shown in the following formula (2):

Dynamic optimization model of fusion parameters:

Wherein, x _k : the output value of the excitation inductor current of the substation equipment;

a _n : represents the current offset of the excitation inductance of the substation equipment;

k: the number of iterations of deep learning;

Use formula (3) to continue the fusion calculation of the output excitation inductor current value, and use the deep learning method to extract the fault evolution state vector and convert it into a feature quantity, as shown below:

Wherein, F _nd (x): the extraction output value of the fault feature;

μ: is the position parameter of fault location;

δ: is the characteristic clustering coefficient of the system;

After the fusion parameters are extracted and converted into feature quantities, a first-level decision is made, and a preliminary judgment is made according to the information fusion result. If the fusion result is 0, there is no fault; if the fusion result is not 0, a fault has occurred, and it is divided into circuits Fault and magnetic circuit fault, if it is judged to be a fault, on the basis of the first-level fusion, continue to find the type of the fault, make a second-level decision, and perform a second-level information fusion processing. Faults, short-circuit faults and discharge faults, output alarm information on the system interface immediately after judgment.

In this way, the monitoring data is converted into a typical feature quantity, and normalized, and the obtained evidence is calculated by deep learning, and fused according to certain decision rules, and finally a diagnosis conclusion is drawn. The calculation method conforms to the IEC60099-5 standard, and realizes the security intelligent perception of substation equipment.

The positive beneficial effects of the present invention are:

1. The present invention is a method of data collection and transmission based on the Internet of Power Internet of Things, and a method of integrating and analyzing various monitoring technologies of the substation. As well as various parameters of the environment, analyze and calculate the collected parameters, extract and convert them into intuitive information, integrate the Internet of Things with the existing power grid information system, and realize the integration of power grid operation management and safety environment information. After comprehensive processing, it can diagnose the health status of the equipment and give early warning and alarm information.

2. In the present invention, industrial-grade wireless communication connection is used during transmission, which has the characteristics of strong penetrating ability and reliable communication, and is convenient for connecting with other intelligent devices such as sensors.

3. In the present invention, the main station of the system can receive the real-time equipment data parameters sent by the intelligent information collector, analyze through the algorithm, perform data extraction, deletion and fusion, and perform the evaluation of the safe operation of the substation after the data is stored, It is displayed on the main station of the system, and there is information such as early warning. This kind of monitoring data is converted into a typical feature quantity, and normalized, and the obtained evidence is calculated by deep learning, and is carried out according to certain decision rules. Fusion, and finally a diagnosis conclusion is obtained. After such processing, the security intelligent perception of substation equipment is realized.

Description of drawings

Fig. 1 is the general schematic diagram of the substation equipment monitoring system in the present invention;

Fig. 2 is the hardware principle diagram of substation equipment monitoring terminal system in the present invention;

Fig. 3 is the hardware principle diagram of the main station of the substation system in the present invention.

Detailed ways

Embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the invention are shown in the drawings, it should be understood that the invention may be embodied in various forms and should not be construed as limited to the embodiments set forth herein, but rather are provided for the purpose of A more thorough and complete understanding of the present invention. It should be understood that the drawings and embodiments of the present invention are only used for exemplary purposes, and are not used to limit the protection scope of the present invention.

As used herein, the term "including" and variations thereof are open-ended inclusions, ie, "including but not limited to".

It should be noted that the concepts such as "first", "second", and "third" mentioned in the present invention are only used to distinguish different devices, modules or units, and are not used to limit the types of these devices, modules or units. The order or interdependence of functions performed.

The names of messages or information exchanged between multiple devices in the embodiments of the present invention are only used for illustrative purposes, and are not used to limit the scope of these messages or information.

See Figure 1, Figure 2 and Figure 3: In the figure, 1-Sensor, 1-1-Switch cabinet temperature sensor, 1-2-SF6 gas concentration sensor, 1-3-Cable joint temperature sensor, 1-4-PD Monitoring sensor, 1-5-room and switch room temperature humidity sensor, 1-6-groundwater level sensor, 1-7-DC screen battery condition sensor, 2-system master station, 3-intelligent monitoring terminal, 4-th 1-gateway, 5-intelligent information concentrator, 6-second gateway, 7-local background, 8-wireless public network, 9-IoT substation, 10-IoT cloud platform, 11-temperature compensator, 12-data Stream, 13-first MCU module, 14-signal filter, 15-noise reduction module, 16-first memory chip, 17-first synchronous dynamic random access memory, 18-first wireless radio frequency module, 19-first power Amplifier, 20-first antenna, 21-second antenna, 22-second power amplifier, 23-second wireless radio frequency module, 24-second MCU module, 25-second memory chip, 26-second synchronous dynamic random Memory, 27-third power amplifier, 28-third MCU module, 29-system interface 29, 30-mobile phone APP.

Embodiment: A method for integrating monitoring technologies of substations based on the Internet of Things, including a sensor 1 and a system master station 2, the sensor 1 is arranged in the equipment and the environment in the substation that need to monitor the operating state, and each sensor 1 They are all connected to their respective intelligent monitoring terminals 3 by wireless. Sensor 1 includes switch cabinet temperature sensor 1-1, SF6 gas concentration sensor 1-2, cable joint temperature sensor 1-3, partial discharge monitoring sensor 1-4, equipment room and switch Room temperature humidity sensor 1-5, groundwater level height sensor 1-6, DC screen battery working condition sensor 1-7, through each sensor 1 to collect the real-time parameters and operating status of each device and transmit it to the respective intelligent monitoring terminal 3,

The switch cabinet temperature sensor 1-1 is responsible for monitoring the temperature of the switch cabinet. If the temperature of the switch cabinet is too high or too low, the power supply will be unstable and affect the normal operation of the equipment; the SF6 gas concentration sensor 1-2 is responsible for monitoring the concentration value of SF6 gas. Under the action of high-temperature arc, toxic impurities will be produced, which is life-threatening to personnel; cable joint temperature sensors 1-3 are responsible for monitoring the temperature of cables; partial discharge monitoring sensors 1-4 will High frequency, etc. for effective monitoring; temperature and humidity sensors 1-5 are installed in the computer room and switch room because there are many instruments in the switch room, and there are certain requirements for air humidity, so temperature and humidity sensors 1-5 are used for detection; due to the current The equipment cannot effectively monitor the underground cable, especially when it is flooded, it will cause serious consequences, so the groundwater level sensor 1-6 is installed to monitor the groundwater level; Health status and working status are monitored.

Each of the intelligent monitoring terminals 3 transmits the collected data to the intelligent information aggregator 5 through the first gateway 4 for data aggregation, that is, the intelligent monitoring terminal 3 and the intelligent information aggregator 5 together form a data collection layer.

The aggregated data is transmitted through the second gateway 6 using the 4G network and the industrial-grade Ethernet network, and transmitted to the system main station 2 and the local background 7, that is, the data transmission layer is formed, and the system main station 2 analyzes and analyzes the data. Calculate, store and display the results after obtaining the results, and give early warning information, and at the same time, the system main station 2 transmits the obtained results to the Internet of Things cloud platform 10 via the wireless public network 8 and the Internet of Things sub-station 9. The system main station 2 also directly transmits data information to the local background 7 system to achieve the power Internet of Things, which is convenient for operators to monitor in real time.

Only when the sensor 1 works within a certain temperature range can it reach the ideal working state. Therefore, when the sensor 1 collects data, a temperature compensator 11 is installed for each of the sensors 1, which is responsible for adjusting the working temperature of the sensor 1 in time. The sensor 1 transmits the monitored data stream 12 to the first MCU module 13 in the corresponding intelligent monitoring terminal 3, and the first MCU module 13 controls the data stream through the signal filter 14 and the noise reduction module 15 respectively. 12. Remove invalid and interfering signal bands and reduce current noise, store data in time through the first memory chip 16 and the first synchronous dynamic random access memory 17 after processing, and then send the signal through the first radio frequency module 18. , when sending, the signal is enhanced and amplified through the first power amplifier 19, so that the transmission quality and distance are better guaranteed, and finally the data signal is sent out through the first antenna 20.

When the information aggregator 5 receives the data sent by the intelligent monitoring terminal 3, it uses the second antenna 21 for wireless reception, and after receiving the data, it processes the signal through the second power amplifier 22 on it, and transmits it to the second antenna 21. The second radio frequency module 23 converts the signal, after the conversion, the second MCU module 24 collects and stores data through the second memory chip 25 and the second synchronous dynamic random access memory 26, and the stored data passes through the third power amplifier 27. The amplification of the signal is enhanced, and the amplified data is transmitted to the third MCU module 28 in the system master station 2 through the second gateway 6 , and the third MCU module 28 collects the intelligent information collector 5 . The data information of the substation is fused and analyzed, and the obtained results are displayed on the system interface 29 of the local background 7 system or the mobile phone APP 30, to locate and evaluate the faults of the equipment in the substation and the health status of the equipment, and for those in the unhealthy state. Status equipment displays early warning information, and sends alarm information to equipment that has failed, which helps to improve the reliability of power grid operation and greatly reduces the work intensity of maintenance personnel.

The equipment monitoring of substations is a process of fusion of multiple information sources. The information comes from the measurement data of sensor 1. The collected data may be similar, the same or different, which are called cross information, redundant information and complementary information respectively. Therefore, it is necessary to The information of the sensor 1 is refined to find out some characteristic information, and then the diagnosis is carried out by the fault characterization to determine whether the system has faults and the nature and category of the faults.

Taking the monitoring system of water immersion sensor 1 as an example, the water immersion sensor 1 uses the principle of liquid conduction for detection. Normally, the two-pole probe is insulated by air; in the state of water immersion, the probe conducts, and when water touches the probe of sensor 1, sensor 1 outputs a signal to the information aggregator 5. The information aggregator 5 sends it to the system master station 2 for analysis, extraction and fusion.

When performing fusion analysis and processing on data, the information of sensor 1 needs to be refined using formula (1) first.

The formula and extraction result are expressed as:

变电站设备演化控制参数特征输出值；in,

Substation equipment evolution control parameter characteristic output value;

i: represents the discrete sampling length of fault information;

a _i : is the amplitude;

p: is the cumulative total value;

n: the sampling value of each sensor 1 information input sample;

It is refined into some parameter features of substation evolution control, such as: low SF6 gas pressure, intelligent terminal power failure alarm, insufficient contact insertion depth and other feature information, and further processing and fusion of the extracted parameter feature sampling values, the following formula (2 ) as shown:

Dynamic optimization model of fusion parameters:

Wherein, x _k : the output value of the excitation inductor current of the substation equipment;

a _n : represents the current offset of the excitation inductance of the substation equipment;

k: the number of iterations of deep learning;

Use formula (3) to continue the fusion calculation of the output excitation inductor current value, and use the deep learning method to extract the fault evolution state vector and convert it into a feature quantity, as shown below:

Wherein, F _nd (x): the extraction output value of the fault feature;

μ: is the position parameter of fault location;

δ: is the characteristic clustering coefficient of the system;

After the fusion parameters are extracted and converted into feature quantities, a first-level decision is made, and a preliminary judgment is made according to the information fusion result. If the fusion result is 0, there is no fault; if the fusion result is not 0, a fault has occurred, and it is divided into circuits Fault and magnetic circuit fault, if it is judged to be a fault, on the basis of the first-level fusion, continue to find the type of the fault, make a second-level decision, and perform a second-level information fusion processing. Faults, short-circuit faults and discharge faults are judged and output alarm information on the system interface 29 immediately.

Note that the above are only preferred embodiments of the present invention and applied technical principles. Those skilled in the art will understand that the present invention is not limited to the specific embodiments herein, and various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the protection scope of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and can also include more other equivalent embodiments without departing from the concept of the present invention. The scope is determined by the scope of the appended claims.

Claims (4)

1. a kind of substation monitoring technology fusion method based on power Internet of things, including sensor and system main station, it is characterized in that: described sensor is arranged at each equipment place in the substation, each described sensor utilizes wireless and respective intelligent The monitoring terminals are connected, and each of the intelligent monitoring terminals transmits the collected data to the intelligent information aggregator through the first gateway for data aggregation, and the aggregated data uses the 4G network and the industrial-grade Ethernet network to carry out data through the second gateway. Transmission, transmission to the main station of the system for data analysis and calculation, storage and display after the results are obtained, and early warning information is given. The station transmits data to the Internet of Things cloud platform, and the system main station also directly transmits data information to the local background system to achieve the power Internet of Things. 2 . The method for integrating substation monitoring technologies based on the power Internet of Things according to claim 1 , wherein: when the sensors collect data, a temperature compensator is installed for each of the sensors, and the The sensor transmits the monitored data stream to the first MCU module in the corresponding intelligent monitoring terminal, and the first MCU module removes invalid and interfering signal bands from the data stream through a signal filter and a noise reduction module respectively. And reduce the current noise, store data in time through the first memory chip and the first synchronous dynamic random access memory after processing, and then send the signal through the first radio frequency module, and enhance the signal through the first power amplifier when sending Amplification, so that the transmission quality and distance are better guaranteed, and finally the data signal is sent out through the first antenna. 3. The method for integrating substation monitoring technologies based on the power Internet of Things according to claim 2, wherein the information aggregator utilizes a second antenna to perform wireless communication when receiving data from the intelligent monitoring terminal. Receive, after the data is received, the signal is processed by the second power amplifier on it, and the signal is transmitted to the second radio frequency module for signal conversion. After the conversion, the second MCU module passes through the second memory chip and the second synchronous dynamic random access memory. Collect and store data, the stored data is amplified and enhanced by the third power amplifier, and the amplified data is transmitted to the third MCU module in the system master station through the second gateway, and the third power amplifier The three MCU modules perform fusion analysis and processing on the data information collected by the intelligent information aggregator, and the obtained results are displayed on the system interface of the local background system or on the mobile phone APP, and the faults of the equipment in the substation and the health status of the equipment are displayed. Perform positioning and evaluation, and display early warning information for equipment that is in an unhealthy state, and send alarm information for equipment that has failed. 4. a kind of substation monitoring technology fusion method based on power Internet of things according to claim 3, is characterized in that: when carrying out fusion analysis and processing, need to use formula (1) to refine the information of the sensor, The formula and extraction result are expressed as:

in,

Substation equipment evolution control parameter characteristic output value; i: represents the discrete sampling length of fault information; a _i : is the amplitude; p: is the cumulative total value; n: The sampling value of the input sample for each sensor information; The sampled values of the extracted parameter features are further processed and fused, as shown in the following formula (2): Dynamic optimization model of fusion parameters:

Wherein, x _k : the output value of the excitation inductor current of the substation equipment; a _n : represents the current offset of the excitation inductance of the substation equipment; k: the number of iterations of deep learning; Use formula (3) to continue the fusion calculation of the output excitation inductor current value, and use the deep learning method to extract the fault evolution state vector and convert it into a feature quantity, as shown below:

Wherein, F _nd (x): the extraction output value of the fault feature; μ: is the position parameter of fault location; δ: is the characteristic clustering coefficient of the system; After the fusion parameters are extracted and converted into feature quantities, a first-level decision is made, and a preliminary judgment is made according to the information fusion result. If the fusion result is 0, there is no fault; if the fusion result is not 0, a fault has occurred, and it is divided into circuits Fault and magnetic circuit fault, if it is judged to be a fault, on the basis of the first-level fusion, continue to find the type of the fault, make a second-level decision, and perform a second-level information fusion processing. Faults, short-circuit faults and discharge faults, output alarm information on the system interface immediately after judgment.

Images