Intelligent acquisition control terminal for distributed power supply

Abstract

The invention discloses an intelligent acquisition control terminal for a distributed power supply, and relates to the field of distributed power supply management control. The method comprises the following steps: generating a distributed photovoltaic regulation and control strategy for regulating and controlling a distributed power supply according to a regulation and control demand of a user, constructing a control protocol library for controlling a photovoltaic inverter by utilizing the generated distributed photovoltaic regulation and control strategy, setting an out-of-limit condition and an optimal threshold value of operation state parameters of distributed power supply equipment in a normal operation state, and controlling the photovoltaic inverter according to the out-of-limit condition and the optimal threshold value. Power grid out-of-limit risk levels are classified, priorities of all distributed photovoltaic regulation and control strategies which can be used for controlling a photovoltaic inverter are set in a control protocol library when the power grid is at different out-of-limit risk levels, and operation state parameters of distributed power supply equipment at the current # imgabs0 # moment are collected in real time; and evaluating the out-of-limit risk of the distributed power supply equipment at the current # imgabs1 # moment, and sequentially calling the matched distributed photovoltaic regulation and control strategies in the control protocol library according to the set priority to control the photovoltaic inverter.

Description

Technical Field

[0001] The present invention relates to the field of distributed power supply management and control, and in particular to an intelligent acquisition and control terminal for distributed power supply. Background Art

[0002] Distributed power supply devices refer to small modular, environmentally compatible independent power sources with power ranging from several kilowatts to 50 MW. They are distributed at the user end and connected to the power grid of 35kV and below for local consumption. They include solar energy, natural gas, biomass energy, wind energy, hydropower, hydrogen energy, geothermal energy, ocean energy, comprehensive resource utilization power generation (including coal mine gas power generation) and energy storage. These power sources are owned by power departments, power users or third parties to meet the specific requirements of power systems and users. Such as peak load regulation, power supply to remote users or commercial and residential areas, saving power transmission and transformation investment, and improving power supply reliability. A large number of decentralized low-voltage photovoltaic customers are connected to the power grid, which brings challenges to the safe and stable operation of the power grid and the local consumption of new energy power generation. Therefore, improving the data collection, monitoring and analysis capabilities of photovoltaic power generation equipment has become the key to ensuring the safe operation of the power grid.

[0003] At present, the main way for low-voltage distributed photovoltaics to communicate with the power grid is through the grid-connected system, using power line carrier communication technology to achieve grid-connected communication connection. During operation, low-voltage distributed photovoltaic equipment will generate electromagnetic interference, affecting the normal operation of the HPLC communication module, resulting in a decrease in communication quality or even communication interruption. In order to improve the power grid company's ability to collect and monitor low-voltage distributed photovoltaics and realize flexible selection of field equipment, collection schemes and control strategies for multiple application scenarios, a set of control terminals is urgently needed to meet the requirements of group control and group control construction under various investment scales, solve the problems of abnormal power quality and increased control difficulty caused by large-scale access of low-voltage distributed photovoltaics, ensure the safe and stable operation of the power grid, and optimize the current power system energy structure. To this end, we propose an intelligent collection and control terminal for distributed power sources. Summary of the invention

[0004] The main purpose of the present invention is to provide an intelligent data collection and control terminal for distributed power sources, which can effectively solve the problems in the background technology.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is:

[0006] Intelligent acquisition and control terminal for distributed power supply, including:

[0007] A distributed power protocol converter for collecting operating status parameters of at least one photovoltaic inverter;

[0008] An adapter for connecting at least one photovoltaic inverter, wherein the adapter is communicatively connected to the distributed power source protocol converter;

[0009] A control protocol library for storing distributed photovoltaic control strategies; wherein the distributed photovoltaic control strategies are generated according to the control requirements of the user and are used to control the photovoltaic inverter;

[0010] Terminal module for assessing the risk of over-limit of distributed power equipment;

[0011] The terminal module is also used to obtain the current grid over-limit risk level, call the distributed photovoltaic control strategy stored in the control protocol library that matches the current grid over-limit risk level according to the current over-limit risk assessment result, and control the photovoltaic inverter using the called control strategy;

[0012] The workflow of the acquisition control terminal includes the following steps:

[0013] Step S1: obtaining the control demand of the user, generating a distributed photovoltaic control strategy for controlling the distributed power source according to the control demand, and constructing a control protocol library for controlling the photovoltaic inverter by using the generated distributed photovoltaic control strategy;

[0014] Step S2: according to the historical operation data of the power grid system, setting the over-limit conditions and optimal thresholds of the operating state parameters of the distributed power supply equipment under normal operating conditions, wherein the operating state parameters include the voltage value, current value and power value of the distributed power supply equipment;

[0015] Step S3: according to the set over-limit conditions and optimal thresholds, the over-limit risk level of the power grid is divided into four categories: low over-limit risk, medium over-limit risk, high over-limit risk, and in over-limit state;

[0016] Step S4: setting the priorities of all the distributed photovoltaic control strategies that can be used to control the photovoltaic inverter when the power grid is at different risk levels of over-limit in the control protocol library;

[0017] Step S5: Real-time collection of distributed power supply equipment at the current The operating status parameters at the moment are used to evaluate the distributed power supply equipment at the current According to the over-limit risk at the moment, the distributed photovoltaic control strategy matching the control protocol library is called in sequence according to the set priority according to the evaluation result of the current over-limit risk, and the photovoltaic inverter is controlled according to the called control strategy.

[0018] The distributed power protocol converter is also used to send the operating status parameters of the inverter to the power grid and send the control command of the power grid to the photovoltaic inverter.

[0019] The over-limit condition is the threshold interval of the operating state parameter, specifically: [ , ]、[ , ]、[ , ],in, It is the lower limit of the voltage value of the distributed power supply equipment under normal operating conditions; It is the upper limit of the voltage value of the distributed power supply equipment under normal operating conditions; It is the lower limit of the current value of the distributed power supply equipment under normal operating conditions; It is the upper limit of the current value of the distributed power supply equipment under normal operating conditions; It is the lower limit of the power value of the distributed power supply equipment under normal operating conditions; It is the upper limit of the power value of the distributed power supply equipment under normal operating conditions.

[0020] The classification process of the grid over-limit risk level includes the following steps:

[0021] Step S31: Obtaining the optimal threshold value of each operating state parameter under normal operating state , , ,in, is the optimal threshold value of voltage; is the optimal threshold value of the current value; is the optimal threshold value of power value;

[0022] Step S32: Construct a three-dimensional rectangular coordinate system with the optimal threshold , , The value of is taken as the three-dimensional coordinate point in the coordinate system =( , , ), map the threshold intervals of the over-limit conditions of the operating state parameters to the constructed three-dimensional rectangular coordinate system, and obtain the point =( , , ) is the center of the space cuboid ;

[0023] Step S33: Calculate the shortest distance between each optimal threshold and its corresponding crossing condition respectively. , , , the calculation formulas are:

[0024] = ;

[0025] = ;

[0026] = ;

[0027] In the formula, Expressed as taking , The minimum value in ; Expressed as taking , The minimum value in ; Expressed as taking , The minimum value in ;

[0028] Step S34: Set a space cuboid Any point in the interior space of =( , , ),in, , , For point The spatial coordinate values ​​of the points are classified according to the following principles: =( , , ) are classified according to the following classification principles:

[0029] when ≤ hour, is the first level point;

[0030] when < ≤ hour, is the second level point;

[0031] when < ≤ hour, is the third level point;

[0032] when > hour, is the fourth level point;

[0033] in, To obtain , , The minimum value in ; For point With point Distance in three-dimensional rectangular coordinate system;

[0034] Step S35: According to the point Based on the classification results, the grid over-limit risk level is classified. The classification principles are as follows:

[0035] When the mapping points of the operating state parameters in the three-dimensional rectangular coordinate system When it is the first level point, the grid over-limit risk level is low over-limit risk;

[0036] When the mapping points of the operating state parameters in the three-dimensional rectangular coordinate system When it is the second level point, the grid over-limit risk level is medium over-limit risk;

[0037] When the mapping points of the operating state parameters in the three-dimensional rectangular coordinate system When it is the third level point, the grid over-limit risk level is high over-limit risk;

[0038] When the mapping points of the operating state parameters in the three-dimensional rectangular coordinate system When it is the fourth level point, the grid over-limit risk level is in an over-limit state.

[0039] Distributed power supply equipment is currently The risk assessment process for crossing the limit at this moment includes the following steps:

[0040] Step S51: Obtain the current status of the distributed power supply device Real-time operating status parameters at the moment , , , is the real-time sampling value of the voltage; is the real-time sampling value of the current value; is the real-time sampling value of the power value;

[0041] Step S52: Using the grid over-limit risk level classification process to classify the distributed power generation equipment in the current The grid over-limit risk level at the current moment is evaluated, and the current The first risk coefficient used to assess the risk level of distributed power equipment exceeding the limit at the moment ,in, =1,2,3,4; , , , Distributed power equipment is currently The grid over-limit risk level at the moment is low over-limit risk, medium over-limit risk, high over-limit risk, and the risk coefficient when in the over-limit state, and < < < =1;

[0042] Step S53: Obtain the current status of the distributed power supply device Several real-time operating status historical parameters before the moment , , , is the number before the current moment Real-time sampling value of voltage value at the moment; is the number before the current moment Real-time sampling value of current value at the moment; is the number before the current moment Real-time sampling value of power value at the moment;

[0043] Step S54: using the acquired time series data of the historical parameters, construct a trend determination function model for determining the change trend of the operating state parameter, wherein the expression of the trend determination function model is:

[0044] ;

[0045] ;

[0046] ;

[0047] In the formula, , , All are constant coefficients greater than 1; A reasonable threshold for voltage fluctuation of distributed power equipment; Provide a reasonable current floating threshold for distributed power equipment; is the reasonable threshold of power fluctuation of distributed power supply equipment, and , , All are non-negative values;

[0048] Step S55: According to the calculation result of the trend determination function model, obtain the current The second risk coefficient used to assess the risk level of distributed power equipment exceeding the limit at the moment ,in, = × + × + × ; In the formula, , , are weight coefficients, and + + =1;

[0049] Step S56: Based on the first risk factor obtained and the second risk factor Calculate at the current The risk factor used to assess the risk level of distributed power equipment exceeding the limit at the time ,in, = × , using the risk factor As the representation value of the risk level of exceeding the limit, when ≥1, it indicates that the distributed power supply equipment is in an out-of-limit state; and when The closer it is to 1, the higher the risk of over-limit of distributed power equipment.

[0050] The acquisition control terminal also includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, it can implement the classification process of the grid over-limit risk level, the distributed power supply equipment in the current The specific steps of the out-of-limit risk assessment process at the moment.

[0051] The present invention has the following beneficial effects:

[0052] Compared with the prior art, the distributed photovoltaic control strategy for controlling distributed power sources is generated according to the control demand by acquiring the control demand of the user, and the control protocol library for controlling photovoltaic inverters is constructed by using the generated distributed photovoltaic control strategy. According to the historical operation data of the power grid system, the over-limit conditions and optimal thresholds of the operating state parameters of the distributed power supply equipment under normal operating conditions are set. According to the set over-limit conditions and optimal thresholds, the over-limit risk level of the power grid is divided into four categories: low over-limit risk, medium over-limit risk, high over-limit risk, and in over-limit state. When the power grid is in different over-limit risk levels, the priorities of all the distributed photovoltaic control strategies that can be used to control the photovoltaic inverter are set in the control protocol library, and the distributed power supply equipment is collected in real time at the current The operating status parameters at the moment are used to evaluate the distributed power supply equipment at the current The over-limit risk at the moment is determined by the evaluation result of the current over-limit risk, and the matching distributed photovoltaic control strategies in the control protocol library are called in sequence according to the set priority. The photovoltaic inverter is controlled according to the called control strategy, which can solve the problems of abnormal power quality and increased control difficulty caused by large-scale access of low-voltage distributed photovoltaics, and ensure the safe and stable operation of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 This is a working flow chart of the intelligent data acquisition and control terminal for distributed power supply of the present invention;

[0054] Figure 2 The figure is a structural block diagram of the intelligent data acquisition and control terminal for distributed power sources according to the present invention. DETAILED DESCRIPTION

[0055] The present invention will be further described below in conjunction with specific implementation methods, wherein the accompanying drawings are only used for exemplary descriptions and represent only schematic diagrams rather than actual drawings, and should not be understood as limiting the present invention. In order to better illustrate the specific implementation methods of the present invention, some parts of the accompanying drawings may be omitted, enlarged or reduced, and do not represent the size of the actual product.

[0056] The technical solution of the present invention proposes an intelligent data acquisition and control terminal for distributed power sources, comprising:

[0057] A distributed power protocol converter for collecting operating status parameters of at least one photovoltaic inverter, the distributed power protocol converter is also used to send the operating status parameters of the inverter to the power grid and send the control command of the power grid to the photovoltaic inverter;

[0058] An adapter for connecting at least one photovoltaic inverter, the adapter being communicatively connected to a distributed power source protocol converter;

[0059] A control protocol library for storing distributed photovoltaic control strategies; wherein the distributed photovoltaic control strategies are generated according to the user's control requirements and are used to control photovoltaic inverters;

[0060] Terminal module for assessing the risk of over-limit of distributed power equipment;

[0061] The terminal module is also used to obtain the current grid over-limit risk level, call the distributed photovoltaic control strategy matching the current grid over-limit risk level stored in the control protocol library according to the current over-limit risk assessment result, and use the called control strategy to control the photovoltaic inverter; wherein,

[0062] The workflow of the acquisition control terminal includes the following steps:

[0063] Step S1: obtaining the control demand of the user, generating a distributed photovoltaic control strategy for controlling the distributed power source according to the control demand, and constructing a control protocol library for controlling the photovoltaic inverter using the generated distributed photovoltaic control strategy;

[0064] Step S2: according to the historical operation data of the power grid system, set the over-limit conditions and optimal thresholds of the operating state parameters of the distributed power supply equipment under normal operation, and the operating state parameters include the voltage value, current value and power value of the distributed power supply equipment; wherein,

[0065] The limit crossing condition is the threshold range of the operating status parameter, specifically: [ , ]、[ , ]、[ , ],in, It is the lower limit of the voltage value of the distributed power supply equipment under normal operating conditions; It is the upper limit of the voltage value of the distributed power supply equipment under normal operating conditions; It is the lower limit of the current value of the distributed power supply equipment under normal operating conditions; It is the upper limit of the current value of the distributed power supply equipment under normal operating conditions; It is the lower limit of the power value of the distributed power supply equipment under normal operating conditions; It is the upper limit of the power value of the distributed power supply equipment under normal operating conditions.

[0066] Step S3: According to the set over-limit conditions and optimal thresholds, the over-limit risk level of the power grid is divided into four categories: low over-limit risk, medium over-limit risk, high over-limit risk, and in over-limit state;

[0067] The classification process of the grid over-limit risk level includes the following steps:

[0068] Step S31: Obtaining the optimal thresholds of various operating state parameters under normal operating conditions , , ,in, is the optimal threshold value of voltage; is the optimal threshold value of the current value; is the optimal threshold value of power value;

[0069] Step S32: Construct a three-dimensional rectangular coordinate system with the optimal threshold , , The value of is taken as the three-dimensional coordinate point in the coordinate system =( , , ), map the threshold intervals of the over-limit conditions of various operating status parameters to the constructed three-dimensional rectangular coordinate system, and obtain the point =( , , ) is the center of the space cuboid ;

[0070] Step S33: Calculate the shortest distance between each optimal threshold and its corresponding crossing condition , , , the calculation formulas are:

[0071] = ;

[0072] = ;

[0073] = ;

[0074] In the formula, Expressed as taking , The minimum value in ; Expressed as taking , The minimum value in ; Expressed as taking , The minimum value in ;

[0075] Step S34: Set a space cuboid Any point in the interior space of =( , , ),in, , , For point The spatial coordinate values ​​of the points are classified according to the following principles: =( , , ) are classified according to the following classification principles:

[0076] when ≤ hour, is the first level point;

[0077] when < ≤ hour, is the second level point;

[0078] when < ≤ hour, is the third level point;

[0079] when > hour, is the fourth level point;

[0080] in, To obtain , , The minimum value in ; For point With point Distance in three-dimensional rectangular coordinate system;

[0081] Step S35: According to the point Based on the classification results, the grid over-limit risk level is classified. The classification principles are as follows:

[0082] When the mapping points of various operating status parameters in the three-dimensional rectangular coordinate system When it is the first level point, the grid over-limit risk level is low over-limit risk;

[0083] When the mapping points of various operating status parameters in the three-dimensional rectangular coordinate system When it is the second level point, the grid over-limit risk level is medium over-limit risk;

[0084] When the mapping points of various operating status parameters in the three-dimensional rectangular coordinate system When it is the third level point, the grid over-limit risk level is high over-limit risk;

[0085] When the mapping points of various operating status parameters in the three-dimensional rectangular coordinate system When it is the fourth level point, the grid over-limit risk level is in an over-limit state.

[0086] Step S4: setting the priorities of all distributed photovoltaic control strategies that can be used to control photovoltaic inverters when the power grid is at different risk levels of over-limit in the control protocol library;

[0087] Step S5: Real-time collection of distributed power supply equipment at the current The operating status parameters at the moment are used to evaluate the distributed power supply equipment at the current The over-limit risk at the moment, according to the current over-limit risk assessment result, calls the matching distributed photovoltaic control strategies in the control protocol library in sequence according to the set priority, and controls the photovoltaic inverter according to the called control strategy;

[0088] The risk assessment process for over-limit violations includes the following steps:

[0089] Step S51: Obtain the current status of the distributed power supply device Real-time operating status parameters at the moment , , , is the real-time sampling value of the voltage; is the real-time sampling value of the current value; is the real-time sampling value of the power value;

[0090] Step S52: Using the grid over-limit risk level classification process to classify the distributed power generation equipment in the current The grid over-limit risk level at the current moment is evaluated, and the current The first risk coefficient used to assess the risk level of distributed power equipment exceeding the limit at the moment ,in, =1,2,3,4; , , , Distributed power equipment is currently The grid over-limit risk level at the moment is low over-limit risk, medium over-limit risk, high over-limit risk, and the risk coefficient when in the over-limit state, and < < < =1;

[0091] Step S53: Obtain the current status of the distributed power supply device Several real-time operating status historical parameters before the moment , , , is the number before the current moment Real-time sampling value of voltage value at the moment; is the number before the current moment Real-time sampling value of current value at the moment; is the number before the current moment Real-time sampling value of power value at the moment;

[0092] Step S54: using the acquired time series data of the historical parameters, construct a trend determination function model for determining the change trend of the operating state parameter, wherein the expression of the trend determination function model is:

[0093] ;

[0094] ;

[0095] ;

[0096] In the formula, , , All are constant coefficients greater than 1; A reasonable threshold for voltage fluctuation of distributed power equipment; Provide a reasonable current floating threshold for distributed power equipment; is the reasonable threshold of power fluctuation of distributed power supply equipment, and , , All are non-negative values;

[0097] Step S55: According to the calculation result of the trend determination function model, obtain the current The second risk coefficient used to assess the risk level of distributed power equipment exceeding the limit at the moment ,in, = × + × + × ; In the formula, , , are weight coefficients, and + + =1;

[0098] Step S56: Based on the first risk factor obtained and the second risk factor Calculate at the current The risk coefficient used to assess the risk level of distributed power equipment exceeding the limit at the time ,in, = × , using the risk factor As the representation value of the risk level of exceeding the limit, when ≥1, it indicates that the distributed power supply equipment is in an out-of-limit state; and when The closer it is to 1, the higher the risk of over-limit of distributed power equipment.

[0099] The acquisition control terminal of the present invention also includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, it can implement the classification process of the grid over-limit risk level, the distributed power supply equipment in the current The specific steps of the out-of-limit risk assessment process at the moment.

[0100] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. An intelligent data acquisition and control terminal for distributed power sources, characterized in that: include: A distributed power protocol converter for collecting operating status parameters of at least one photovoltaic inverter; An adapter for connecting at least one photovoltaic inverter, wherein the adapter is communicatively connected to the distributed power source protocol converter; A control protocol library for storing distributed photovoltaic control strategies; wherein the distributed photovoltaic control strategies are generated according to the control requirements of the user and are used to control the photovoltaic inverter; Terminal module for assessing the risk of over-limit of distributed power equipment; The terminal module is also used to obtain the current grid over-limit risk level, call the distributed photovoltaic control strategy stored in the control protocol library that matches the current grid over-limit risk level according to the current over-limit risk assessment result, and control the photovoltaic inverter using the called control strategy; The workflow of the acquisition control terminal includes the following steps: Step S1: obtaining the control demand of the user, generating a distributed photovoltaic control strategy for controlling the distributed power source according to the control demand, and constructing a control protocol library for controlling the photovoltaic inverter by using the generated distributed photovoltaic control strategy; Step S2: according to the historical operation data of the power grid system, setting the over-limit conditions and optimal thresholds of the operating state parameters of the distributed power supply equipment under normal operating conditions, wherein the operating state parameters include the voltage value, current value and power value of the distributed power supply equipment; Step S3: according to the set over-limit conditions and optimal thresholds, the over-limit risk level of the power grid is divided into four categories: low over-limit risk, medium over-limit risk, high over-limit risk, and in over-limit state; Step S4: setting the priorities of all the distributed photovoltaic regulation strategies that can be used to control the photovoltaic inverter when the power grid is at different risk levels of over-limit in the control protocol library; Step S5: Real-time collection of distributed power supply equipment at the current The operating status parameters at the moment are used to evaluate the distributed power supply equipment at the current According to the over-limit risk at the moment, the distributed photovoltaic control strategy matching the control protocol library is called in sequence according to the set priority according to the evaluation result of the current over-limit risk, and the photovoltaic inverter is controlled according to the called control strategy.

2. The intelligent data acquisition and control terminal for distributed power supply according to claim 1 is characterized in that: The distributed power protocol converter is also used to send the operating status parameters of the inverter to the power grid and send the control command of the power grid to the photovoltaic inverter.

3. The intelligent data acquisition and control terminal for distributed power supply according to claim 1 is characterized in that: The over-limit condition is the threshold interval of the operating state parameter, specifically: [ , ]、[ , ]、[ , ],in, It is the lower limit of the voltage value of the distributed power supply equipment under normal operating conditions; It is the upper limit of the voltage value of the distributed power supply equipment under normal operating conditions; It is the lower limit of the current value of the distributed power supply equipment under normal operating conditions; It is the upper limit of the current value of the distributed power supply equipment under normal operating conditions; It is the lower limit of the power value of the distributed power supply equipment under normal operating conditions; It is the upper limit of the power value of the distributed power supply equipment under normal operating conditions.

4. The intelligent data acquisition and control terminal for distributed power supply according to claim 3 is characterized in that: The classification process of the grid over-limit risk level includes the following steps: Step S31: Obtaining the optimal threshold value of each operating state parameter under normal operating state , , ,in, is the optimal threshold value of voltage; is the optimal threshold value of the current value; is the optimal threshold value of power value; Step S32: Construct a three-dimensional rectangular coordinate system with the optimal threshold , , The value of is taken as the three-dimensional coordinate point in the coordinate system =( , , ), map the threshold intervals of the over-limit conditions of the operating state parameters to the constructed three-dimensional rectangular coordinate system, and obtain the point =( , , ) is the center of the space cuboid ; Step S33: Calculate the shortest distance between each optimal threshold and its corresponding crossing condition respectively. , , , the calculation formulas are: = ； = ； = ； In the formula, Expressed as taking , The minimum value in ; Expressed as taking , The minimum value in ; Expressed as taking , The minimum value in ; Step S34: Set a space cuboid Any point in the interior space of =( , , ),in, , , For point The spatial coordinate values ​​of the points are classified according to the following principles: =( , , ) are classified according to the following classification principles: when ≤ hour, is the first level point; when < ≤ hour, is the second level point; when < ≤ hour, is the third level point; when > hour, is the fourth level point; in, To obtain , , The minimum value in ; For point With point Distance in three-dimensional rectangular coordinate system; Step S35: According to the point Based on the classification results, the grid over-limit risk level is classified. The classification principles are as follows: When the mapping points of the operating state parameters in the three-dimensional rectangular coordinate system When it is the first level point, the grid over-limit risk level is low over-limit risk; When the mapping points of the operating state parameters in the three-dimensional rectangular coordinate system When it is the second level point, the grid over-limit risk level is medium over-limit risk; When the mapping points of the operating state parameters in the three-dimensional rectangular coordinate system When it is the third level point, the grid over-limit risk level is high over-limit risk; When the mapping points of the operating state parameters in the three-dimensional rectangular coordinate system When it is the fourth level point, the grid over-limit risk level is in an over-limit state.

5. The intelligent data acquisition and control terminal for distributed power supply according to claim 4 is characterized in that: Distributed power supply equipment is currently The risk assessment process for crossing the limit at this moment includes the following steps: Step S51: Obtain the current status of the distributed power supply device Real-time operating status parameters at the moment , , , is the real-time sampling value of the voltage; is the real-time sampling value of the current value; is the real-time sampling value of the power value; Step S52: Using the grid over-limit risk level classification process to classify the distributed power generation equipment in the current The grid over-limit risk level at the current moment is evaluated, and the current The first risk coefficient used to assess the risk level of distributed power equipment exceeding the limit at the moment ,in, =1,2,3,4; , , , Distributed power equipment is currently The grid over-limit risk level at the moment is low over-limit risk, medium over-limit risk, high over-limit risk, and the risk coefficient when in the over-limit state, and < < < =1; Step S53: Obtain the current status of the distributed power supply device Several real-time operating status historical parameters before the moment , , , is the number before the current moment Real-time sampling value of voltage value at the moment; is the number before the current moment Real-time sampling value of current value at the moment; is the number before the current moment Real-time sampling value of power value at the moment; Step S54: using the acquired time series data of the historical parameters, construct a trend determination function model for determining the change trend of the operating state parameter, wherein the expression of the trend determination function model is: ； ； ； In the formula, , , All are constant coefficients greater than 1; A reasonable threshold for voltage fluctuation of distributed power equipment; Provide a reasonable current floating threshold for distributed power equipment; is the reasonable threshold of power fluctuation of distributed power supply equipment, and , , All are non-negative values; Step S55: According to the calculation result of the trend determination function model, obtain the current The second risk coefficient used to assess the risk level of distributed power equipment exceeding the limit at the moment ,in, = × + × + × ; In the formula, , , are weight coefficients, and + + =1; Step S56: Based on the first risk factor obtained and the second risk factor Calculate at the current The risk factor used to assess the risk level of distributed power equipment exceeding the limit at the time ,in, = × , using the risk factor As the representation value of the risk level of exceeding the limit, when ≥1, it indicates that the distributed power supply equipment is in an out-of-limit state; and when The closer it is to 1, the higher the risk of over-limit of distributed power equipment.

6. The intelligent data acquisition and control terminal for distributed power supply according to claim 5 is characterized in that: The acquisition control terminal also includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, it can implement the classification process of the grid over-limit risk level, the distributed power supply equipment in the current The specific steps of the out-of-limit risk assessment process at the moment.

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