Distributed photovoltaic grid-connected safety monitoring system based on four fusible terminals

Abstract

The invention discloses a distributed photovoltaic grid-connected safety monitoring system and method based on four fusible terminals, and relates to the technical field of power system monitoring, and the system comprises a data collection module, a first preprocessing module, a reference vector management module, a second preprocessing module, a matrix management module, a real-time monitoring module and an information feedback module. The data acquisition module is used for performing classification according to all parameters of the same data acquisition and different acquisition of the same parameter, the first preprocessing module is used for performing normalization processing on the parameters, and the reference vector management module is used for performing iteration on historical data vectors to output reference vectors; the second preprocessing module is used for obtaining historical data of the same parameter in a classified mode and calculating the statistical magnitude of power grid data, the matrix management module is used for establishing a relation matrix of data items, and the real-time monitoring module is used for obtaining real-time monitoring data of a distributed power grid, conducting normalization processing on the real-time data and sending the data to the data storage module. And the information feedback module is used for obtaining risk assessment value information.

Description

Technical Field

[0001] The present invention relates to the technical field of power system monitoring, and in particular to a distributed photovoltaic grid-connected safety monitoring system based on four fusion terminals. Background Art

[0002] Distributed photovoltaic systems have the advantages of local power generation, local grid connection, local conversion, and local use. They are highly efficient, can alleviate electricity shortages, and are environmentally friendly. They solve the problems of traditional centralized photovoltaic power generation systems, such as long transmission distances, high relay consumption, and complex power dispatching methods, which cannot flexibly allocate electricity.

[0003] Distributed photovoltaic systems are usually built close to users. Common installation locations include residential rooftops, commercial rooftops, factory rooftops, etc. These places are close to people's lives or work, so the operation safety of distributed photovoltaic systems is particularly important. The operating environment of distributed photovoltaic systems is relatively complex and is susceptible to both human and natural influences. For example, the contact resistance at the interface of the grid connection increases or the joints become loose, resulting in the inability of the current to flow smoothly, thus generating leakage current. In addition, the wear, aging or moisture of the insulating material will reduce its insulation performance, allowing the current to leak through weak points. Therefore, it is necessary to monitor the operating status of the distributed power grid in real time and obtain abnormal status in a timely manner to improve the safety method energy of the system. Summary of the invention

[0004] The purpose of the present invention is to provide a distributed photovoltaic grid-connected safety monitoring system based on four fusion terminals to solve the problems raised in the prior art.

[0005] To achieve the above purpose, the present invention provides the following technical solution: a distributed photovoltaic grid-connected safety monitoring system based on four fusion terminals, the system comprising: Data acquisition module, first preprocessing module, reference vector management module, second preprocessing module, matrix management module, real-time monitoring module and information feedback module; The four integration requirements of photovoltaics are observable, measurable, controllable and adjustable; Observable includes: Real-time observation of the power station's operating status through an intelligent monitoring system, including key information such as equipment performance, environmental conditions, and power output, to promptly identify and address potential problems; Measurable includes: accurate prediction and measurement of power generation and various operating data of power plants through big data models, providing a solid foundation for optimizing power plant performance; Controllable includes: remote or automatic control through a digital monitoring platform to ensure safe and reliable operation of the power station; Adjustability includes: through intelligent adjustment, the power station can flexibly respond to changes in grid load and frequency fluctuations; The present invention combines observation data to extract the changing rules of photovoltaic power grid operation, extracts the operating characteristics of the photovoltaic power grid, further establishes a judgment and reference evaluation model, accurately outputs the evaluation results of the power grid operation data, and provides a basis for the precise regulation of distributed photovoltaic power grids.

[0006] Furthermore, the data acquisition module is used to collect historical data of load power, terminal temperature and terminal leakage current of the distributed power grid, and classify them according to all parameters collected at the same time and different collections of the same parameters; the first preprocessing module is used to normalize all parameters collected at the same time, and form the normalized data into a historical data vector; The reference vector management module is used to obtain several historical data vectors from the first preprocessing module, and iterate the historical data vectors to output reference vectors; the second preprocessing module is used to classify and obtain historical data of the same parameters, and calculate the statistics of three data items: load power of the distributed power grid, temperature of the terminal and leakage current of the terminal; the matrix management module is used to obtain the statistics of the three data items, calculate the correlation coefficients between the data items, and establish a relationship matrix of the data items; the real-time monitoring module is used to obtain real-time monitoring data of the distributed power grid and normalize the real-time data; the information feedback module is used to calculate the difference between the real-time monitoring data and the historical records of the distributed power grid, and obtain the risk assessment value. When the difference exceeds the threshold, an alarm message is issued.

[0007] Further, the data acquisition module is connected to the first preprocessing module and the second preprocessing module respectively, the first preprocessing module is connected to the reference vector management module, the second preprocessing module is connected to the matrix management module, and the information feedback module is connected to the real-time monitoring module, the reference vector management module and the matrix management module respectively. Further, the data acquisition module includes: a sensor management unit, a historical data management unit and a data classification unit; The sensor management unit is used to manage load power sensors, temperature sensors and leakage current sensors, wherein the load power sensor is used to collect the system load power of a distributed photovoltaic power generation system, the temperature sensor is used to collect the temperature of the wiring terminals at the grid-connected location of a distributed photovoltaic power generation system, and the leakage current sensor is used to collect the leakage current of the wiring terminals at the grid-connected location of a distributed photovoltaic power generation system; The historical data management unit is used to collect the system load power, the temperature of the wiring terminals and the leakage current of the wiring terminals at the same time in batches, and collect them into data groups. Each data collection corresponds to a data group, and several data groups are collected and recorded in the historical data set; The data classification unit is used to classify the data in the historical data set according to the type of data, wherein all system load powers in the historical data set are collected and recorded in the system load power record set, all temperatures of the terminals in the historical data set are collected and recorded in the temperature record set of the terminals, and all leakage currents of the terminals in the historical data set are collected and recorded in the leakage current set of the terminals.

[0008] Further, the first pre-processing module includes: a power processing unit, a temperature processing unit, a leakage current processing unit and a history vector management unit; The power processing unit is used to normalize the system load power to obtain normalized power, wherein the rated power P of the preset system load is rated , calculate the normalized power P norm , P norm =P history / P rated , P actual Indicates the actual historical record value of system load power; The temperature processing unit is used to normalize the temperature of the terminal to obtain a normalized temperature, wherein the preset terminal rated temperature T rated , obtain the ambient temperature T at the time of data collection amb , calculate the normalized temperature T norm , T norm =(T history -T amb ) / T rated , T history Indicates the actual historical value of the temperature of the terminal block; The leakage current processing unit is used to normalize the leakage current of the terminal to obtain a normalized leakage current, wherein the leakage threshold I is preset. hold , calculate the normalized leakage current I leaknorm , I leaknorm =I leak / I hold , I leak Indicates the actual historical record value of the terminal leakage current; The history vector management unit is used to collect the normalized power, normalized temperature and normalized leakage current corresponding to the system load power, terminal temperature and terminal leakage current in each data group, and form the history data vector X corresponding to each data group, X = (P norm , T norm , I leaknorm ); After data normalization, the evaluation criteria for each data item are unified, the impact of different dimensions between different parameters is reduced, and the accuracy of the data evaluation process is further improved.

[0009] Further, the reference vector management module includes: a data set management unit, an initial vector management unit, a vector iteration unit and a reference vector management unit; The data set management unit is used to collect a number of historical data vectors, and divide the number of historical data vectors into two vector groups, the two vector groups are respectively recorded as a first vector group and a second vector group, wherein the total number of historical data vectors in the second vector group is greater than the total number of historical data vectors in the first vector group; The initial vector management unit is used to obtain all historical data vectors in the first vector group, calculate the average values ​​of all normalized powers, normalized temperatures and normalized leakage currents in the historical data vectors, obtain the average normalized power P0, evaluate the normalized temperature T0 and the average normalized leakage current I0, and form an initial vector k0, k0=(P0, T0, I0); The vector iteration unit is used to obtain the initial vector k0 to iterate all the historical data vectors in the second vector group, wherein the iteration formula is: m =α×q m +(1-α)×k m-1 , k m represents the output result of the mth iteration, q m represents the mth historical data vector in the second vector group, α is the balance coefficient, and satisfies the condition 0<α<1; This scheme adopts the exponential moving average method to improve the accuracy of the reference vector. Considering that the operation of the photovoltaic system may have periodic changes, such as the large difference in power between day and night, the direct use of simple average cannot accurately describe the changes of the distributed photovoltaic system, which will bring more errors to the subsequent comparison process. The iterative method is used to eliminate the calculation error caused by discrete values ​​as much as possible; The reference vector management unit is used to output the result vector when the iterated vector converges, and use the result vector as the reference vector, wherein the total number N1 of historical data vectors in the first vector group is obtained, when m>N1, and ||k m -k m-N1 || / || k m-N1 When ||<δ, output k m , the output vector is recorded as the reference vector μ, where δ represents the vector difference threshold; After several iterations, if the iteration result tends to be stable, the iteration result is output as a reference vector. This iteration vector includes the average information of the average value and the change trend brought about by the system change, which is more in line with the actual situation of the power grid system and is conducive to improving the accuracy of the subsequent judgment process.

[0010] Further, the second preprocessing module includes: a mean calculation unit, a variance calculation unit and a covariance calculation unit; The average calculation unit is used to obtain the load power record set, the temperature record set and the leakage current set from the data classification unit, and calculate the average load power P ave , average temperature T ave and the average leakage current I ave ; The variance calculation unit is used to respectively calculate the variance Var (P) of the load power of the distributed power grid, the variance Var (T) of the temperature of the terminal and the variance Var (I) of the leakage current of the terminal; The covariance calculation unit is used to calculate the covariance Cov (P, T) of the load power and the temperature, the covariance Cov (T, I) of the temperature and the leakage, and the covariance Cov (P, I) of the power and the leakage.

[0011] Further, the matrix management module includes: a relationship coefficient calculation unit and a relationship matrix management unit; The relationship coefficient calculation unit is used to calculate the relationship coefficient ρ xy , , x∈{P, T, I}, y∈{P, T, I}, and x≠y, wherein {P, T, I} represents a parameter set, in which P represents a corresponding parameter for calculating the load power of the distributed power grid, T represents a corresponding parameter for the temperature of the terminal, and I represents a corresponding parameter for the temperature of the terminal; The relationship matrix management unit is used to traverse the parameter set and manage the relationship matrix G, G= .

[0012] Furthermore, the real-time monitoring module includes: a real-time data acquisition unit and a real-time data processing unit; The real-time data acquisition unit is used to collect real-time data of a distributed photovoltaic power generation system. The real-time data includes the real-time value P of the system load power of a distributed photovoltaic power generation system. cur , the real-time value of the temperature of the connection terminal at the grid connection point of a distributed photovoltaic power generation system T cur The real-time value of the leakage current I of the connection terminal of a distributed photovoltaic power generation system cur , and the collected data is merged into a real-time data set (P cur , T cur , I cur ); The real-time data processing unit is used to normalize the real-time data to obtain the real-time data vector Y, Y = (P sta , T sta , I sta ), where P sta ==P cur / P rated , T sta =(T cur -T2 amb ) / T rated , I sta = I cur / I hold , T 2 amb It indicates the ambient temperature of a distributed photovoltaic power generation system when the real-time data group is collected.

[0013] Furthermore, the information feedback module includes: a difference calculation unit, a threshold management unit and an alarm unit; The difference calculation unit is used to obtain the real-time data vector, the management relationship matrix and the reference vector, and calculate the difference D. , Among them, T in the formula for calculating the difference degree D represents a matrix transposition operator, and μ represents a reference vector; The threshold management unit is used to manage the alarm threshold γ; The alarm unit is used to issue an alarm to the management personnel of a distributed photovoltaic power generation system, wherein the alarm condition is D>γ.

[0014] Compared with the prior art, the beneficial effects of the present invention are: by classifying and analyzing the historical data of the distributed photovoltaic system, the characteristics of the parameters and the correlation between the parameters are fully explored, and the reference value is further obtained according to the historical data in an iterative manner. The evaluation model of the real-time data of the distributed photovoltaic system is constructed by integrating the correlation between the reference value and the parameters, eliminating the influence of different dimensions between the parameters, and timely providing the distributed photovoltaic system monitoring information that conforms to the actual situation. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 This is a schematic diagram of the first structure of a distributed photovoltaic grid-connected safety monitoring system based on four fusion terminals of the present invention; Figure 2 This is a second structural schematic diagram of the distributed photovoltaic grid-connected safety monitoring system based on four fusion terminals of the present invention. DETAILED DESCRIPTION

[0016] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0017] Example: Figure 1 and Figure 2As shown, the present invention provides a technical solution, a distributed photovoltaic grid-connected safety monitoring system based on four fusion terminals; The system includes: a data acquisition module, a first preprocessing module, a reference vector management module, a second preprocessing module, a matrix management module, a real-time monitoring module and an information feedback module; Among them, the data acquisition module is connected to the first preprocessing module and the second preprocessing module respectively, the first preprocessing module is connected to the reference vector management module, the second preprocessing module is connected to the matrix management module, and the information feedback module is connected to the real-time monitoring module, the reference vector management module and the matrix management module respectively.

[0018] The data acquisition module is used to collect the historical data of the load power of the distributed power grid, the temperature of the terminal and the leakage current of the terminal, and classify them according to all the parameters collected at the same time and the same parameters collected at different times; Among them, the data acquisition module includes: a sensor management unit, a historical data management unit and a data classification unit; The sensor management unit is used to manage load power sensors, temperature sensors and leakage current sensors, wherein the load power sensor is used to collect the system load power of a distributed photovoltaic power generation system, the temperature sensor is used to collect the temperature of the wiring terminals at the grid-connected location of a distributed photovoltaic power generation system, and the leakage current sensor is used to collect the leakage current of the wiring terminals at the grid-connected location of a distributed photovoltaic power generation system; The historical data management unit is used to collect the system load power, the temperature of the wiring terminals and the leakage current of the wiring terminals at the same time in batches, and collect them into data groups. Each data collection corresponds to a data group, and several data groups are collected and recorded in the historical data set; The data classification unit is used to classify the data in the historical data set according to the type of data, wherein all system load powers in the historical data set are collected and recorded in the system load power record set, all temperatures of the terminals in the historical data set are collected and recorded in the temperature record set of the terminals, and all leakage currents of the terminals in the historical data set are collected and recorded in the leakage current set of the terminals.

[0019] The first preprocessing module is used to normalize all parameters collected at the same time, and form the normalized data into a historical data vector; Wherein, the first pre-processing module includes: a power processing unit, a temperature processing unit, a leakage current processing unit and a history vector management unit; The power processing unit is used to normalize the system load power to obtain normalized power, wherein the rated power P of the preset system load is rated , calculate the normalized power P norm , P norm =P history / P rated , P actual Indicates the actual historical record value of system load power; The temperature processing unit is used to normalize the temperature of the terminal to obtain a normalized temperature, wherein the preset terminal rated temperature T rated , obtain the ambient temperature T at the time of data collection amb , calculate the normalized temperature T norm , T norm =(T history -T amb ) / T rated , T history Indicates the actual historical value of the temperature of the terminal block; The leakage current processing unit is used to normalize the leakage current of the terminal to obtain a normalized leakage current, wherein the leakage threshold I is preset. hold , calculate the normalized leakage current I leaknorm , I leaknorm =I leak / I hold , I leak Indicates the actual historical record value of the terminal leakage current; For example, in a distributed photovoltaic system with a rated power of 20kW, the data set measured in a certain measurement is (15.2kW, 48℃, 5mA), and the ambient temperature at this time is 28℃; Setting T rated =57℃, I hold =30mA; P norm =15.2 / 20=0.76, T norm = (48-28) / 57 = 0.35, I leaknorm =5 / 30=0.17; The history vector management unit is used to collect the normalized power, normalized temperature and normalized leakage current corresponding to the system load power, terminal temperature and terminal leakage current in each data group, and form the history data vector X corresponding to each data group, X = (P norm , T norm , I leaknorm ); In the embodiment, one of the historical data vectors is (0.76, 0.35, 0.17).

[0020] The reference vector management module is used to obtain a number of historical data vectors from the first preprocessing module, and iterate the historical data vectors to output reference vectors; The reference vector management module includes: a data set management unit, an initial vector management unit, a vector iteration unit and a reference vector management unit; The data set management unit is used to collect a number of historical data vectors, and divide the number of historical data vectors into two vector groups, the two vector groups are respectively recorded as a first vector group and a second vector group, wherein the total number of historical data vectors in the second vector group is greater than the total number of historical data vectors in the first vector group; The initial vector management unit is used to obtain all historical data vectors in the first vector group, calculate the average values ​​of all normalized powers, normalized temperatures and normalized leakage currents in the historical data vectors, obtain the average normalized power P0, evaluate the normalized temperature T0 and the average normalized leakage current I0, and form an initial vector k0, k0=(P0, T0, I0); The vector iteration unit is used to obtain the initial vector k0 to iterate all the historical data vectors in the second vector group, wherein the iteration formula is: m =α×q m +(1-α)×k m-1 , k m represents the output result of the mth iteration, q m represents the mth historical data vector in the second vector group, α is the balance coefficient, and satisfies the condition 0<α<1; In the embodiment, the value of α can be selected as 1 / N1. For example, if the first vector group includes 100 historical data vectors, α can be 0.01. Calculate the average value of 100 historical data vectors in the first vector group to obtain the initial vector k0, k0 = (0.72, 0.31, 0.15); When the first historical data vector in the second vector group is (0.76, 0.35, 0.17); Calculate k1 = 0.01 × (0.76, 0.35, 0.17) + 0.99 × (0.72, 0.32, 0.15) = (0.7204, 0.3203, 0.1502); The reference vector management unit is used to output the result vector when the iterated vector converges, and use the result vector as the reference vector, wherein the total number N1 of historical data vectors in the first vector group is obtained, when m>N1, and ||k m -k m-N1 || / || k m-N1 When ||<δ, output k m , the vector output at this time is recorded as the reference vector μ, where δ represents the vector difference threshold. In the embodiment, δ defaults to 5%. After the system runs for a period of time, it can be adjusted according to the operation feedback results.

[0021] The second preprocessing module is used to classify and obtain historical data of the same parameters, and calculate the statistics of three data items: load power of the distributed power grid, temperature of the terminal and leakage current of the terminal; Wherein, the second preprocessing module includes: a mean calculation unit, a variance calculation unit and a covariance calculation unit; The average calculation unit is used to obtain the load power record set, the temperature record set and the leakage current set from the data classification unit, and calculate the average load power P ave , average temperature T ave and the average leakage current I ave ; The variance calculation unit is used to respectively calculate the variance Var (P) of the load power of the distributed power grid, the variance Var (T) of the temperature of the terminal and the variance Var (I) of the leakage current of the terminal; The covariance calculation unit is used to calculate the covariance Cov (P, T) of the load power and temperature, the covariance Cov (T, I) of the temperature and leakage, and the covariance Cov (P, I) of the power and leakage; In the embodiment, n data groups are collected and classified according to the load power of the distributed power grid, the temperature of the terminal and the leakage current of the terminal, and the average power is calculated respectively. , the average temperature and the average value of the leakage current ; Covariance of power and temperature: ; Covariance of temperature and leakage: ; Covariance of power and leakage: ; Among them, P i represents the load power of the distributed power grid in the i-th data group, T i represents the temperature of the terminal block in the i-th data group, I i Represents the leakage current of the terminal in the i-th data group.

[0022] The matrix management module is used to obtain the statistics of three data items, calculate the correlation coefficients between data items, and establish the relationship matrix of data items; Wherein, the matrix management module includes: a relationship coefficient calculation unit and a relationship matrix management unit; The relationship coefficient calculation unit is used to calculate the relationship coefficient ρ xy , , x∈{P, T, I}, y∈{P, T, I}, and x≠y, wherein {P, T, I} represents a parameter set, in which P represents a corresponding parameter for calculating the load power of the distributed power grid, T represents a corresponding parameter for the temperature of the terminal, and I represents a corresponding parameter for the temperature of the terminal; The relationship matrix management unit is used to traverse the parameter set and manage the relationship matrix G, G= ; Due to the symmetry of the calculation, ρ PT =ρ TP , ρ PI =ρ IP , ρ IT =ρ TI .

[0023] The real-time monitoring module is used to obtain real-time monitoring data of the distributed power grid and normalize the real-time data; Wherein, the real-time monitoring module includes: a real-time data acquisition unit and a real-time data processing unit; The real-time data acquisition unit is used to collect real-time data of a distributed photovoltaic power generation system. The real-time data includes the real-time value P of the system load power of a distributed photovoltaic power generation system. cur , the real-time value of the temperature of the connection terminal at the grid connection point of a distributed photovoltaic power generation system T cur The real-time value of the leakage current I of the connection terminal of a distributed photovoltaic power generation system cur , and the collected data is merged into a real-time data set (P cur , T cur , I cur ); The real-time data processing unit is used to normalize the real-time data to obtain the real-time data vector Y, Y = (P sta , T sta , I sta ), where P sta ==P cur / P rated , T sta =(T cur -T 2 amb ) / T rated , I sta = I cur / I hold , T 2 amb It indicates the ambient temperature of a distributed photovoltaic power generation system when the real-time data group is collected.

[0024] The information feedback module is used to calculate the difference between the real-time monitoring data and the historical records of the distributed power grid, and obtain the risk assessment value. When the difference exceeds the threshold, an alarm message is issued. The information feedback module includes: a difference calculation unit, a threshold management unit and an alarm unit; The difference calculation unit is used to obtain the real-time data vector, the management relationship matrix and the reference vector, and calculate the difference D. , Among them, T in the formula for calculating the difference degree D represents a matrix transposition operator, and μ represents a reference vector; The threshold management unit is used to manage the alarm threshold γ; The alarm unit is used to give an alarm to the management personnel of a distributed photovoltaic power generation system, where the alarm condition is D>γ; In the embodiment, γ is 1, G is , the two real-time data vectors are recorded as Y1 and Y2, when Y1-μ=(0.2, -0.1, 0.03), Y2-μ=(0.3, 1.2, 0.1); Calculate the inverse matrix G of G -1 , G -1 = ; Difference D1=0.246, no alarm is issued at this time; The difference D2=1.144, and an alarm is issued.

[0025] Methods include: S1. Collect physical parameters in the distributed photovoltaic system, pre-process the physical parameters, and obtain historical data vectors and reference vectors; S2. Obtain historical data of physical parameters and calculate statistics of three items of data: load power of the distributed power grid, temperature of the wiring terminals, and leakage current of the wiring terminals; S3, obtaining statistics of three data items: load power, terminal temperature and terminal leakage current, calculating correlation coefficients between data items, and establishing a relationship matrix of data items; S4, obtaining real-time monitoring data of the distributed power grid, and normalizing the real-time data of the distributed power grid; S5. Calculate the difference between the real-time monitoring data and the historical records of the distributed power grid to obtain a risk assessment value. When the difference exceeds a threshold, an alarm message is issued.

[0026] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. A distributed photovoltaic grid-connected safety monitoring system based on four fusion terminals, characterized by: The system includes: Data acquisition module, first preprocessing module, reference vector management module, second preprocessing module, matrix management module, real-time monitoring module and information feedback module; The data acquisition module is used to collect the historical data of the load power of the distributed power grid, the temperature of the terminal and the leakage current of the terminal, and classify them according to all the parameters collected at the same time and the same parameters collected at different times; The first preprocessing module is used to normalize all parameters collected at the same time, and form the normalized data into a historical data vector; The reference vector management module is used to obtain a number of historical data vectors from the first preprocessing module, and iterate the historical data vectors to output reference vectors; The second preprocessing module is used to classify and obtain historical data of the same parameters, and calculate the statistics of three data items: load power of the distributed power grid, temperature of the terminal and leakage current of the terminal; The matrix management module is used to obtain the statistics of the three data items, calculate the correlation coefficients between the data items, and establish a relationship matrix of the data items; The real-time monitoring module is used to obtain real-time monitoring data of the distributed power grid and normalize the real-time data; The information feedback module is used to calculate the difference between the real-time monitoring data and the historical records of the distributed power grid, and obtain the risk assessment value. When the difference exceeds the threshold, an alarm message is issued; Among them, the data acquisition module is connected to the first preprocessing module and the second preprocessing module respectively, the first preprocessing module is connected to the reference vector management module, the second preprocessing module is connected to the matrix management module, and the information feedback module is connected to the real-time monitoring module, the reference vector management module and the matrix management module respectively.

2. According to claim 1, the distributed photovoltaic grid-connected safety monitoring system based on four fusion terminals is characterized in that: The data acquisition module includes: a sensor management unit, a historical data management unit and a data classification unit; The sensor management unit is used to manage load power sensors, temperature sensors and leakage current sensors, wherein the load power sensor is used to collect the system load power of a distributed photovoltaic power generation system, the temperature sensor is used to collect the temperature of the wiring terminals at the grid-connected location of a distributed photovoltaic power generation system, and the leakage current sensor is used to collect the leakage current of the wiring terminals at the grid-connected location of a distributed photovoltaic power generation system; The historical data management unit is used to collect the system load power, the temperature of the wiring terminals and the leakage current of the wiring terminals at the same time in batches, and collect them into data groups. Each data collection corresponds to a data group, and several data groups are collected and recorded in the historical data set; The data classification unit is used to classify the data in the historical data set according to the type of data, wherein all system load powers in the historical data set are collected and recorded in the system load power record set, all temperatures of the terminals in the historical data set are collected and recorded in the temperature record set of the terminals, and all leakage currents of the terminals in the historical data set are collected and recorded in the leakage current set of the terminals.

3. The distributed photovoltaic grid-connected safety monitoring system based on four fusion terminals according to claim 2 is characterized in that: The first pre-processing module includes: a power processing unit, a temperature processing unit, a leakage current processing unit and a history vector management unit; The power processing unit is used to normalize the system load power to obtain normalized power, wherein the rated power P of the preset system load is rated , calculate the normalized power P norm , P norm =P history / P rated , P actual Indicates the actual historical record value of system load power; The temperature processing unit is used to normalize the temperature of the terminal to obtain a normalized temperature, wherein the preset terminal rated temperature T rated , obtain the ambient temperature T at the time of data collection amb , calculate the normalized temperature T norm , T norm =(T history -T amb ) / T rated , T history Indicates the actual historical value of the temperature of the terminal block; The leakage current processing unit is used to normalize the leakage current of the terminal to obtain a normalized leakage current, wherein the leakage threshold I is preset. hold , calculate the normalized leakage current I leaknorm , I leaknorm =I leak / I hold , I leak Indicates the actual historical record value of the terminal leakage current; The history vector management unit is used to collect the normalized power, normalized temperature and normalized leakage current corresponding to the system load power, terminal temperature and terminal leakage current in each data group, and form the history data vector X corresponding to each data group, X = (P norm , T norm , I leaknorm ).

4. The distributed photovoltaic grid-connected safety monitoring system based on four fusion terminals according to claim 3 is characterized in that: The reference vector management module includes: a data set management unit, an initial vector management unit, a vector iteration unit and a reference vector management unit; The data set management unit is used to collect a number of historical data vectors, and divide the number of historical data vectors into two vector groups, the two vector groups are respectively recorded as a first vector group and a second vector group, wherein the total number of historical data vectors in the second vector group is greater than the total number of historical data vectors in the first vector group; The initial vector management unit is used to obtain all historical data vectors in the first vector group, calculate the average values ​​of all normalized powers, normalized temperatures and normalized leakage currents in the historical data vectors, obtain the average normalized power P0, evaluate the normalized temperature T0 and the average normalized leakage current I0, and form an initial vector k0, k0=(P0, T0, I0); The vector iteration unit is used to obtain the initial vector k0 to iterate all the historical data vectors in the second vector group, wherein the iteration formula is: m =α×q m +(1-α)×k m-1 , k m represents the output result of the mth iteration, q m represents the mth historical data vector in the second vector group, α is the balance coefficient, and satisfies the condition 0<α<1; The reference vector management unit is used to output the result vector when the iterated vector converges, and use the result vector as the reference vector, wherein the total number N1 of historical data vectors in the first vector group is obtained, when m>N1, and ||k m -k m-N1 || / ||k m-N1 When ||<δ, output k m , the output vector is recorded as the reference vector μ, where δ represents the vector difference threshold.

5. According to claim 4, the distributed photovoltaic grid-connected safety monitoring system based on four fusion terminals is characterized in that: The second preprocessing module includes: a mean calculation unit, a variance calculation unit and a covariance calculation unit; The average calculation unit is used to obtain the load power record set, the temperature record set and the leakage current set from the data classification unit, and calculate the average load power P ave , average temperature T ave and the average leakage current I ave ; The variance calculation unit is used to respectively calculate the variance Var (P) of the load power of the distributed power grid, the variance Var (T) of the temperature of the terminal and the variance Var (I) of the leakage current of the terminal; The covariance calculation unit is used to calculate the covariance Cov (P, T) of the load power and the temperature, the covariance Cov (T, I) of the temperature and the leakage, and the covariance Cov (P, I) of the power and the leakage.

6. The distributed photovoltaic grid-connected safety monitoring system based on four fusion terminals according to claim 5 is characterized in that: The matrix management module includes: a relationship coefficient calculation unit and a relationship matrix management unit; The relationship coefficient calculation unit is used to calculate the relationship coefficient ρ xy , , x∈{P, T, I}, y∈{P, T, I}, and x≠y, wherein {P, T, I} represents a parameter set, in which P represents a corresponding parameter for calculating the load power of the distributed power grid, T represents a corresponding parameter for the temperature of the terminal, and I represents a corresponding parameter for the temperature of the terminal; The relationship matrix management unit is used to traverse the parameter set and manage the relationship matrix G, G= .

7. The distributed photovoltaic grid-connected safety monitoring system based on four fusion terminals according to claim 6 is characterized in that: The real-time monitoring module includes: a real-time data acquisition unit and a real-time data processing unit; The real-time data acquisition unit is used to collect the real-time data of the distributed photovoltaic power generation system, and the real-time data includes the real-time value P of the system load power of the distributed photovoltaic power generation system. cur , the real-time value of the temperature of the connection terminal at the grid connection point of a distributed photovoltaic power generation system T cur The real-time value of the leakage current I of the connection terminal of a distributed photovoltaic power generation system cur , and the collected data is merged into a real-time data set (P cur , T cur , I cur ); The real-time data processing unit is used to normalize the real-time data to obtain the real-time data vector Y, Y = (P sta , T sta , I sta ), where P sta ==P cur / P rated , T sta =(T cur -T 2 amb ) / T rated , I sta = I cur / I hold , T 2 amb It indicates the ambient temperature of a distributed photovoltaic power generation system when the real-time data group is collected.

8. The distributed photovoltaic grid-connected safety monitoring system based on four fusion terminals according to claim 7 is characterized in that: The information feedback module includes: a difference calculation unit, a threshold management unit and an alarm unit; The difference calculation unit is used to obtain the real-time data vector, the management relationship matrix and the reference vector, and calculate the difference D. , Among them, T in the formula for calculating the difference degree D represents a matrix transposition operator, and μ represents a reference vector; The threshold management unit is used to manage the alarm threshold γ; The alarm unit is used to issue an alarm to the management personnel of a distributed photovoltaic power generation system, wherein the alarm condition is D>γ.

9. A distributed photovoltaic grid-connected safety monitoring method based on four fusionable terminals, used in a distributed photovoltaic grid-connected safety monitoring system based on four fusionable terminals as claimed in any one of claims 1 to 8, characterized in that: Methods include: S1. Collect physical parameters in the distributed photovoltaic system, pre-process the physical parameters, and obtain historical data vectors and reference vectors; S2. Obtain historical data of physical parameters and calculate statistics of three items of data: load power of the distributed power grid, temperature of the wiring terminals, and leakage current of the wiring terminals; S3, obtaining statistics of three data items: load power, terminal temperature and terminal leakage current, calculating correlation coefficients between data items, and establishing a relationship matrix of data items; S4, obtaining real-time monitoring data of the distributed power grid, and normalizing the real-time data of the distributed power grid; S5. Calculate the difference between the real-time monitoring data and the historical records of the distributed power grid to obtain a risk assessment value. When the difference exceeds a threshold, an alarm message is issued.

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