Quantitative identification method and device for transient overvoltage risk of double-high power system

Abstract

The invention particularly relates to a quantitative identification method and device for a transient overvoltage risk of a double-high power system, and the method comprises the steps: calculating a multi-station short-circuit ratio of each new energy station based on a plurality of initialized power grid basic parameters, and determining a short-circuit ratio lowest point in the multi-station short-circuit ratios, meanwhile, a first target new energy field station with the lowest short-circuit ratio point smaller than the preset short-circuit ratio is screened out, and the output value of the first target new energy field station is adjusted; determining a transient overvoltage high-risk operation condition and matching a fault type according to the short-circuit ratio lowest point corresponding to all the new energy stations and a preset operation condition, performing simulation calculation on the transient overvoltage high-risk operation condition, extracting a voltage effective peak value, comparing the voltage effective peak value with a preset transient overvoltage tolerance value, and determining a fault type of the new energy stations according to the transient overvoltage tolerance value. And outputting a transient overvoltage risk identification signal based on a comparison result so as to obtain transient overvoltage risk identification information.

Description

Technical Field

[0001] The present application relates to the technical field of transient stability analysis and control of power systems, and in particular to a method and device for quantitatively identifying transient overvoltage risks in dual-high power systems. Background Art

[0002] In the "double-high" power system, the importance of transient voltage stability has become increasingly prominent and has become one of the key factors to ensure the safe and stable operation of the system. In the process of transformation from the traditional power system to the "double-high" power system, the transient response characteristics when facing large disturbances (such as short-circuit faults, load mutations, etc.) have become particularly complex and critical. Transient voltage stability is directly related to whether the system can recover quickly after the disturbance and maintain the voltage within an acceptable range. It not only affects the power supply quality and the power demand satisfaction on the user side, but also directly affects the overall safety and stability of the power system.

[0003] Transient voltage stability may cause the unit to be disconnected from the grid, which may trigger a chain reaction and eventually lead to system collapse and large-scale power outages. Especially in the context of a high proportion of renewable energy access, the dynamic characteristics of the "double-high" power system are more complex and changeable, and the requirements for transient voltage stability are more stringent. Therefore, in-depth research on the transient voltage stability mechanism of the "double-high" power system and the identification of transient overvoltage risks in the "double-high" power system are of great significance for improving the system's anti-disturbance capability, ensuring the safe and stable operation of the power grid, and promoting the consumption of renewable energy and energy transformation.

[0004] In related technologies, transient overvoltage risk identification methods mainly include machine learning and full-operating-condition time-domain simulation.

[0005] However, although machine learning methods can process large-scale data, their model performance depends on the quality and quantity of data. In the process of identifying transient overvoltage risks in power systems, high-quality and representative data sets are often difficult to obtain, and they need to cover various fault scenarios and system conditions. If the data is insufficient or biased, the model may not be able to accurately reflect the behavior of the actual system, resulting in inaccurate results. The time domain simulation method requires complex numerical integration calculations on the system, which leads to a huge amount of calculations, especially when considering transient overvoltage risks under various operating conditions. Due to the complexity of the system and the large number of simulations, the entire identification process is time-consuming and resource-intensive, which urgently needs to be solved. Summary of the invention

[0006] The present application provides a quantitative identification method and device for transient overvoltage risks in a dual-high power system to solve the problems that the transient overvoltage risk identification method in the related art is highly dependent on the quality and quantity of data, which reduces the accuracy of the results when the data is insufficient or biased, and increases the amount of calculation based on complex numerical integration calculations, thereby making the entire risk identification process time-consuming and labor-intensive.

[0007] The first aspect of the present application provides a method for quantitatively identifying transient overvoltage risks in a dual-high power system, comprising the following steps:

[0008] Initializing a plurality of basic power grid parameters, and calculating a short-circuit ratio of multiple stations of each of a plurality of new energy stations based on the initialized basic power grid parameters, and determining a minimum point of the short-circuit ratio of the multiple stations of each new energy station;

[0009] Based on the lowest short-circuit ratio point among the short-circuit ratios of multiple stations of each new energy station, a first target new energy station whose lowest short-circuit ratio point is less than a preset short-circuit ratio is screened out, and the output value of the first target new energy station is adjusted, and after the lowest short-circuit ratio point corresponding to the first target new energy station is greater than or equal to the preset short-circuit ratio, a transient overvoltage high-risk operating condition is determined according to the lowest short-circuit ratio points corresponding to all new energy stations and the preset operating condition;

[0010] The fault type is matched based on the transient overvoltage high-risk operating condition, and the transient overvoltage high-risk operating condition is simulated and calculated based on the fault type, the voltage effective peak is extracted, and the voltage effective peak is compared with a preset transient overvoltage tolerance value, and a transient overvoltage risk identification signal is output based on the comparison result to obtain transient overvoltage risk identification information according to the transient overvoltage risk identification signal.

[0011] According to one embodiment of the present application, the initializing multiple basic parameters of the power grid includes:

[0012] Acquiring the plurality of basic power grid parameters;

[0013] A power grid parameter database is formed based on the multiple power grid basic parameters, and the power grid parameter database is input into a preset calculation initialization program, so as to initialize the multiple power grid basic parameters in the power grid parameter database using the preset calculation initialization program.

[0014] According to an embodiment of the present application, the simulating calculation of the transient overvoltage high-risk operating condition based on the fault type to extract the voltage effective peak value includes:

[0015] For a second target new energy station whose short-circuit ratio minimum point is greater than or equal to the preset short-circuit ratio, a simulation calculation is performed on the transient overvoltage high-risk operating condition based on the target output value;

[0016] For the first target new energy station, a simulation calculation is performed on the transient overvoltage high-risk operating condition under the adjusted output value.

[0017] According to an embodiment of the present application, the outputting of a transient overvoltage risk identification signal based on the comparison result to obtain transient overvoltage risk identification information according to the transient overvoltage risk identification signal includes:

[0018] If the voltage effective peak value is less than or equal to the preset transient overvoltage tolerance value, the transient overvoltage risk identification signal is output as 0, so as to obtain transient overvoltage risk identification information when the transient overvoltage risk identification signal is 0;

[0019] If the voltage effective peak value is greater than the preset transient overvoltage tolerance value, the output transient overvoltage risk identification signal is 1, so as to obtain transient overvoltage risk identification information when the transient overvoltage risk identification signal is 1.

[0020] According to the quantitative identification method of transient overvoltage risk in dual-high power system of the embodiment of the present application, the short-circuit ratio of multiple stations of each new energy station is calculated based on the multiple basic parameters of the power grid after initialization, and the lowest point of the short-circuit ratio among the multiple stations is determined. At the same time, the first target new energy station whose lowest point of short-circuit ratio is less than the preset short-circuit ratio is screened out, and its output value is adjusted. After the lowest point of the short-circuit ratio corresponding to the first target new energy station is greater than or equal to the preset short-circuit ratio, the transient overvoltage high-risk operating condition is determined and the fault type is matched according to the lowest point of the short-circuit ratio corresponding to all new energy stations and the preset operating condition, and the transient overvoltage high-risk operating condition is simulated and calculated, the voltage effective peak is extracted, and the voltage effective peak is compared with the preset transient overvoltage tolerance value. Based on the comparison result, a transient overvoltage risk identification signal is output, and then the transient overvoltage risk identification information is obtained. As a result, the problems of transient overvoltage risk identification methods in related technologies being highly dependent on the quality and quantity of data, which reduces the accuracy of results when data is insufficient or biased, and increasing the amount of calculation based on complex numerical integration calculations, making the entire risk identification process time-consuming and labor-intensive, are solved. Through the organic combination of algorithms and real-time simulation technologies, effective identification of transient overvoltage risks in power systems is achieved, thereby improving the safety and stability of the power grid.

[0021] The second aspect of the present application provides a device for quantitatively identifying transient overvoltage risks in a dual-high power system, including:

[0022] A calculation module, used to initialize multiple basic grid parameters, and calculate the short-circuit ratio of multiple stations of each of the multiple new energy stations based on the initialized multiple basic grid parameters, and determine the lowest point of the short-circuit ratio in the short-circuit ratio of multiple stations of each new energy station;

[0023] An adjustment module, for screening out a first target new energy station whose short circuit ratio minimum point is less than a preset short circuit ratio based on the short circuit ratio minimum point of multiple stations of each new energy station, and adjusting the output value of the first target new energy station, and determining a transient overvoltage high-risk operating condition according to the short circuit ratio minimum points corresponding to all new energy stations and a preset operating condition after the short circuit ratio minimum point corresponding to the first target new energy station is greater than or equal to the preset short circuit ratio;

[0024] An acquisition module is used to match the fault type based on the transient overvoltage high-risk operating condition, and simulate the transient overvoltage high-risk operating condition based on the fault type, extract the voltage effective peak value, and compare the voltage effective peak value with a preset transient overvoltage tolerance value, and output a transient overvoltage risk identification signal based on the comparison result to obtain transient overvoltage risk identification information according to the transient overvoltage risk identification signal.

[0025] According to one embodiment of the present application, the computing module includes:

[0026] A first acquisition unit, configured to acquire the plurality of basic power grid parameters;

[0027] An initialization unit is used to form a power grid parameter database based on the multiple power grid basic parameters, and input the power grid parameter database into a preset calculation initialization program to initialize the multiple power grid basic parameters in the power grid parameter database using the preset calculation initialization program.

[0028] According to one embodiment of the present application, the acquisition module includes:

[0029] A first calculation unit is used to perform simulation calculation on the transient overvoltage high-risk operating condition based on a target output value for a second target new energy station whose short-circuit ratio minimum point is greater than or equal to the preset short-circuit ratio;

[0030] The second calculation unit is used to simulate and calculate the transient overvoltage high-risk operating condition under the adjusted output value for the first target new energy station.

[0031] According to one embodiment of the present application, the acquisition module includes:

[0032] A second acquisition unit is used to output a transient overvoltage risk identification signal of 0 if the voltage effective peak value is less than or equal to the preset transient overvoltage tolerance value, so as to obtain transient overvoltage risk identification information when the transient overvoltage risk identification signal is 0;

[0033] The third acquisition unit is used to output a transient overvoltage risk identification signal of 1 if the voltage effective peak value is greater than the preset transient overvoltage tolerance value, so as to obtain transient overvoltage risk identification information when the transient overvoltage risk identification signal is 1.

[0034] According to the quantitative identification device for transient overvoltage risks in a dual-high power system of the embodiment of the present application, the short-circuit ratio of multiple stations of each new energy station is calculated based on the multiple basic parameters of the power grid after initialization, and the lowest point of the short-circuit ratio among the multiple station short-circuit ratios is determined. At the same time, the first target new energy station whose lowest point of the short-circuit ratio is less than the preset short-circuit ratio is screened out, and its output value is adjusted. After the lowest point of the short-circuit ratio corresponding to the first target new energy station is greater than or equal to the preset short-circuit ratio, the transient overvoltage high-risk operating condition is determined and the fault type is matched according to the lowest point of the short-circuit ratio corresponding to all new energy stations and the preset operating condition, and the transient overvoltage high-risk operating condition is simulated and calculated, the voltage effective peak is extracted, the voltage effective peak is compared with the preset transient overvoltage tolerance value, and a transient overvoltage risk identification signal is output based on the comparison result, thereby obtaining transient overvoltage risk identification information. As a result, the problems of transient overvoltage risk identification methods in related technologies being highly dependent on the quality and quantity of data, which reduces the accuracy of results when data is insufficient or biased, and increasing the amount of calculation based on complex numerical integration calculations, making the entire risk identification process time-consuming and labor-intensive, are solved. Through the organic combination of algorithms and real-time simulation technologies, effective identification of transient overvoltage risks in power systems is achieved, thereby improving the safety and stability of the power grid.

[0035] The third aspect of the present application provides an electronic device, comprising: a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the program to implement a method for quantitatively identifying transient overvoltage risks in a dual-high power system as described in the above embodiment.

[0036] The fourth aspect of the present application provides a computer-readable storage medium, which stores computer instructions, and the computer instructions are used to enable the computer to execute the quantitative identification method of transient overvoltage risks in a dual-high power system as described in the above embodiments.

[0037] A fifth aspect of the present invention provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the method for quantitatively identifying transient overvoltage risks in a dual-high power system as described in the above embodiment.

[0038] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0040] Figure 1 A flowchart of a method for quantitatively identifying transient overvoltage risks in a dual-high power system provided according to an embodiment of the present application;

[0041] Figure 2 is a flow chart of an overall method according to an embodiment of the present application;

[0042] Figure 3 : is a block diagram of an exemplary device for quantitatively identifying transient overvoltage risks in a dual-high power system according to an embodiment of the present application;

[0043] Figure 4 Schematic diagram of the structure of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0044] The embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0045] The following describes a quantitative identification method and device for transient overvoltage risks in a dual-high power system according to an embodiment of the present application with reference to the accompanying drawings. In view of the problem that the transient overvoltage risk identification method of the related art mentioned in the above background technology is highly dependent on the quality and quantity of data, which reduces the accuracy of the results when the data is insufficient or there are deviations, and increases the amount of calculation when it is based on complex numerical integral calculations, thereby making the entire risk identification process time-consuming and labor-intensive, the present application provides a quantitative identification method for transient overvoltage risks in a dual-high power system. In this method, the short-circuit ratios of multiple stations of each new energy station are calculated based on multiple basic parameters of the power grid after initialization, and the lowest point of the short-circuit ratio among the multiple station short-circuit ratios is determined, and the short-circuit ratios are screened out at the same time. For the first target new energy station whose lowest point is less than the preset short-circuit ratio, adjust its output value. After the short-circuit ratio lowest point corresponding to the first target new energy station is greater than or equal to the preset short-circuit ratio, determine the transient overvoltage high-risk operating condition and match the fault type according to the short-circuit ratio lowest point corresponding to all new energy stations and the preset operating condition, and simulate and calculate the transient overvoltage high-risk operating condition, extract the voltage effective peak value, compare the voltage effective peak value with the preset transient overvoltage tolerance value, output the transient overvoltage risk identification signal based on the comparison result, and then obtain the transient overvoltage risk identification information. Thus, the transient overvoltage risk identification method of the related technology is highly dependent on the quality and quantity of data, which reduces the accuracy of the results when the data is insufficient or there is a deviation, and when it is based on complex numerical integral calculations, it will increase the amount of calculation, thereby making the entire risk identification process time-consuming and labor-intensive. Through the organic combination of algorithms and real-time simulation and other technologies, the effective identification of transient overvoltage risks in the power system is achieved, thereby improving the safety and stability of the power grid.

[0046] Specifically, before introducing the embodiments of the present application, we first introduce the transient overvoltage risk identification method in the related art, which mainly includes machine learning and full-operating condition time domain simulation.

[0047] Among them, in machine learning, the dynamic behavior characteristics of the power system under various operating conditions are mainly learned through training models, and whether the system will have the risk of transient overvoltage under specific disturbances. Specifically, researchers will collect a large amount of power system operation data, including voltage, current, power and other parameters in normal state and historical fault records, as well as the corresponding system state and disturbance type. These data are used to train machine learning models so that they can learn the laws and characteristics of system voltage response under different disturbances. After the training is completed, the model can receive new power system operation data and potential disturbance information as input, and identify whether the system may have transient overvoltage risks under the disturbance.

[0048] In the full-operating-condition time-domain simulation, by establishing a simulation model of the system, simulating the dynamic response process of the power system after a specific disturbance (such as short circuit, line break, etc.), observing and analyzing the changing trend and characteristics of the system voltage, the dynamic characteristics of each component of the power system (such as generators, transformers, transmission lines, etc.) and their interactions and mutual influences will be considered in detail during the simulation process. Through the method of numerical integration, the values ​​of the system state variables (such as voltage, current, etc.) are gradually calculated and updated to obtain the voltage response curve of the system within a period of time after the disturbance. Based on this voltage response curve, it can be identified whether the system has a risk of transient overvoltage. If the voltage peak is too high, or oscillation, instability, etc. occur during the voltage recovery process, then it can be determined that the system has a risk of transient overvoltage under the disturbance.

[0049] However, (1) risk identification algorithms based on machine learning can handle large-scale data and complex systems and have high application prospects, but the performance of machine learning models is highly dependent on the quality and quantity of training data. In the process of identifying transient overvoltage risks in power systems, high-quality and representative data sets are often difficult to obtain, and they need to cover various fault scenarios and system conditions. If the data is insufficient or biased, the model may not accurately reflect the behavior of the actual system, resulting in inaccurate results; (2) When identifying transient overvoltage risks based on time domain simulation methods, although it has the advantages of being able to fully consider the dynamic characteristics of the system and reflect the actual operating conditions of the system, it also has some obvious disadvantages. The time domain simulation method requires numerical integration of the system's nonlinear equations to simulate the system's dynamic response process after disturbance. This process involves a lot of calculations, especially in large-scale power systems, where the amount of calculations is even greater. If the transient overvoltage risks of various operating conditions are considered, due to the complexity of the system and the large number of simulations, the entire risk identification process is time-consuming and labor-intensive, and also occupies a lot of resources and equipment.

[0050] Therefore, based on the problems existing in the above-mentioned related technologies, the embodiments of the present application propose a systematic method for identifying transient overvoltage risks in "double-high" power systems. Its important role is to significantly improve the safety and stability of the power system and ensure the reliability of power supply by effectively identifying the transient overvoltage risks brought about by the connection of new energy to the grid. The specific implementation methods are as follows.

[0051] Specifically, Figure 1 A flow chart of a method for quantitatively identifying transient overvoltage risks in a dual-high power system provided in an embodiment of the present application.

[0052] like Figure 1 As shown, the quantitative identification method of the transient overvoltage risk of the dual-high power system includes the following steps:

[0053] In step S101, multiple basic grid parameters are initialized, and the short-circuit ratio of multiple stations of each new energy station is calculated based on the initialized multiple basic grid parameters, and the lowest point of the short-circuit ratio in the short-circuit ratio of multiple stations of each new energy station is determined.

[0054] According to one embodiment of the present application, initializing multiple basic power grid parameters includes: acquiring multiple basic power grid parameters; constructing a power grid parameter database based on the multiple basic power grid parameters, and inputting the power grid parameter database into a preset calculation initialization program to initialize the multiple basic power grid parameters in the power grid parameter database using the preset calculation initialization program.

[0055] The preset calculation initialization program can be set by those skilled in the art according to actual test requirements and is not specifically limited here.

[0056] Specifically, Figure 2 As shown, before starting the algorithm of the embodiment of the present application, a parameter initialization step is required, which includes the initial values ​​of all key parameters required for the transient overvoltage risk identification algorithm. First, multiple targeted basic grid parameters are obtained, which are important parameters for transient overvoltage risks, mainly including the short-circuit capacity of each substation, the capacity and type of new energy power stations, the capacity and control strategy of reactive compensation devices, and the 0.1s transient overvoltage tolerance of lightning arresters; secondly, based on the above multiple basic grid parameters and the capacity and reactance of synchronous generators, the capacity ratio and reactance of transformers, the length and unit resistance reactance of transmission lines, a grid parameter database is formed, and the grid parameter database is input into a preset calculation initialization program to initialize multiple basic grid parameters in the grid parameter database. For example, an initialization function or module can be defined in the preset calculation initialization program, which is responsible for reading the stored data and performing necessary data processing, such as data cleaning, data verification, format conversion, etc., to ensure the consistency and integrity of the data, thereby realizing the initialization of multiple basic grid parameters.

[0057] Furthermore, after initializing multiple basic power grid parameters, the embodiment of the present application calculates the multi-station short-circuit ratio of each of the multiple new energy stations based on the initialized multiple basic power grid parameters, and determines the lowest point of the short-circuit ratio among the multiple-station short-circuit ratios of each new energy station.

[0058] Specifically, it is necessary to first calculate the short-circuit ratio of multiple stations in each of the multiple renewable energy stations, so as to obtain each short-circuit ratio in each renewable energy station, and determine the lowest point of the short-circuit ratio in each renewable energy station. Then, the overall stability of multiple renewable energy stations when connected to the power grid at the same time can be better evaluated based on the lowest point of the short-circuit ratio. Assume that the lowest point of the short-circuit ratio of multiple stations in the n-node system is the weak point, and the node number is k, which can be expressed as:

[0059] R k =min{R i}, (i=1,2,...n);

[0060] Among them, R is the short-circuit ratio of multiple stations, R k is the multi-station short-circuit ratio of the k-th renewable energy station; R i is the multi-station short-circuit ratio of the i-th new energy station; n is the number of system nodes.

[0061] In step S102, based on the lowest short-circuit ratio of multiple stations in the short-circuit ratios of each new energy station, the first target new energy station whose lowest short-circuit ratio is less than the preset short-circuit ratio is screened out, and the output value of the first target new energy station is adjusted, and after the lowest short-circuit ratio corresponding to the first target new energy station is greater than or equal to the preset short-circuit ratio, the transient overvoltage high-risk operating condition is determined according to the lowest short-circuit ratios corresponding to all new energy stations and the preset operating conditions.

[0062] Among them, the preset short-circuit ratio and the preset operating conditions can be set by technical personnel in this field according to actual test requirements. The preset short-circuit ratio can also be determined by a limited number of computer simulations, which is not specifically limited here.

[0063] Specifically, Figure 2 As shown, in the embodiment of the present application, after calculating the short-circuit ratio minimum point among the short-circuit ratios of multiple stations of each new energy station, it is necessary to compare the short-circuit ratio minimum point with the preset short-circuit ratio R lim By comparison, the first target new energy station whose short-circuit ratio lowest point is less than the preset short-circuit ratio is selected, and the output value of the first target new energy station is automatically adjusted until the requirement is met, that is, the adjustment is terminated when the short-circuit ratio lowest point corresponding to the first target new energy station is greater than or equal to the preset short-circuit ratio, thereby satisfying the output value adjustment calculation of the short-circuit ratio of multiple stations, and then entering the transient overvoltage high-risk operating condition screening step based on impedance calculation. For example, there are m new energy stations that need to adjust their output values, and the adjusted output values ​​are recorded as P1, P2, ..., Pm, and other new energy stations maintain their original output values, then the satisfied relationship is:

[0064]

[0065] λkj =|Z jj / Z kk |;

[0066] Among them, R lim is the preset short-circuit ratio that multiple stations need to meet; Z jj is the self-impedance of the jth station; Z kk is the self-impedance of the kth station; S k is the short-circuit capacity of the kth station; P k is the adjusted active power of the kth station; P j is the adjusted active power of the jth station; P 0k is the active power of the kth station before adjustment; P 0j is the active power of the jth station before adjustment; λkj is the impedance ratio.

[0067] Furthermore, if the short-circuit ratio lowest point directly calculated is greater than or equal to the preset short-circuit ratio, the transient overvoltage high-risk operating condition screening step based on impedance calculation can be directly entered, and the transient overvoltage high-risk operating condition can be determined according to the short-circuit ratio lowest point corresponding to all new energy stations and the preset operating conditions.

[0068] Specifically, in order to improve the calculation efficiency and accuracy, this step simplifies the new energy system example and only retains the key factors that have a significant impact on the system stability. The specific operation is: input the basic situation of the example into this link, including the number of lines, transformers, and thermal power units included in the example, and take the lowest point of the short-circuit ratio of each new energy station calculated above, that is, the new energy station connected to the k node as the key research object, and other wind farms are equivalent to equivalent new energy stations with the same capacity, as shown in the following formula:

[0069]

[0070] Where eq is the capacity of the equivalent new energy station. The line connecting the new energy station connected to the k-node to the system is set to a circuit, b parallel booster transformers, c surrounding thermal power units, and the impedance of the single circuit line and single booster is calculated to the same voltage level side, denoted as X a , X b , under the premise of satisfying the normal transmission of power flow, screen the Nx (x represents the number of electrical equipment withdrawn) operating conditions where a1 lines are disconnected, b1 transformers are withdrawn, and all thermal power units are withdrawn, solve the optimization objective function Γ, obtain the values ​​of a1 and b1 when Γ is the largest, and sort them from large to small according to Γ. Users can select the top conditions for electromagnetic transient simulation platform call and subsequent transient overvoltage peak extraction according to actual conditions. The expression is as follows:

[0071]

[0072] in,

[0073] a1+b1+c=x;

[0074] In step S103, the fault type is matched based on the transient overvoltage high-risk operating condition, and the transient overvoltage high-risk operating condition is simulated and calculated based on the fault type, the voltage effective peak value is extracted, and the voltage effective peak value is compared with the preset transient overvoltage tolerance value, and a transient overvoltage risk identification signal is output based on the comparison result to obtain transient overvoltage risk identification information according to the transient overvoltage risk identification signal.

[0075] According to one embodiment of the present application, a transient overvoltage high-risk operating condition is simulated and calculated based on the fault type, and the effective peak voltage is extracted, including: for a second target new energy station whose short-circuit ratio lowest point is greater than or equal to a preset short-circuit ratio, the transient overvoltage high-risk operating condition is simulated and calculated based on the target output value; for the first target new energy station, the transient overvoltage high-risk operating condition is simulated and calculated at the adjusted output value.

[0076] Among them, the preset transient overvoltage tolerance value can be set by those skilled in the art according to actual test requirements and is not specifically limited here.

[0077] Specifically, after screening the transient overvoltage high-risk operating conditions, the embodiment of the present application calls the simulation software platform. First, for the screened transient overvoltage high-risk operating conditions, the platform automatically configures a more serious fault type at the fault location that is closer to the electrical distance of the wind farm, such as two-phase short circuit to ground, three-phase short circuit; then, the transient overvoltage high-risk operating conditions are simulated and calculated. For example, for the second target new energy site with a short circuit ratio lower than or equal to the preset short circuit ratio, the transient overvoltage high-risk operating conditions are simulated and calculated based on the target output value, that is, the simulation is performed at the rated output; for the first target new energy site with a short circuit ratio lower than the preset short circuit ratio, the transient overvoltage high-risk operating conditions are simulated and calculated at the adjusted output value, that is, the simulation is performed at the adjusted output P1, P2, ..., Pm of the first m new energy sites. During the simulation process, the platform can capture and record the changes in electrical quantities such as voltage and current in real time, providing data support for subsequent risk assessment. According to the three-phase voltage quantity, the voltage effective value is calculated and the voltage effective value peak value V is extracted. max , the expression is as follows:

[0078] V max =max(V);

[0079] According to one embodiment of the present application, a transient overvoltage risk identification signal is output based on the comparison result to obtain transient overvoltage risk identification information based on the transient overvoltage risk identification signal, including: if the voltage effective peak value is less than or equal to the preset transient overvoltage tolerance value, the transient overvoltage risk identification signal is output as 0 to obtain the transient overvoltage risk identification information when the transient overvoltage risk identification signal is 0; if the voltage effective peak value is greater than the preset transient overvoltage tolerance value, the transient overvoltage risk identification signal is output as 1 to obtain the transient overvoltage risk identification information when the transient overvoltage risk identification signal is 1.

[0080] Specifically, after obtaining the effective peak value of the voltage, the embodiment of the present application compares the effective peak value of the voltage with the preset transient overvoltage tolerance value, that is, the effective peak value of the voltage is compared with the above-mentioned initialized 0.1s transient overvoltage tolerance value of the arrester, and the comparison result is obtained, and the identification signal Flag is set, and the expression is as follows:

[0081]

[0082] Based on the comparison result, a transient overvoltage risk identification signal is output. If the voltage effective peak value is less than or equal to the preset transient overvoltage tolerance value, the output transient overvoltage risk identification signal is 0, that is, V max When ≤0.1sTOV, Flag=0, and it is determined that the system has no transient overvoltage risk under this working condition, so that the transient overvoltage risk identification information can be obtained when the transient overvoltage risk identification signal is 0, such as outputting the safety assessment result; if the voltage effective peak value is greater than the preset transient overvoltage tolerance value, the output transient overvoltage risk identification signal is 1, that is, V max When >0.1sTOV, Flag=1. At this time, it is determined that the system has a potential transient overvoltage risk under this operating condition, so as to obtain the transient overvoltage risk identification information when the transient overvoltage risk identification signal is 1, which mainly includes the operation mode of potential risk, fault type, fault duration, etc.).

[0083] It should be noted that the quantitative identification method of transient overvoltage risks in dual-high power systems and the protection of each step of the software discussed in the embodiment of the present application mainly include an overall transient overvoltage risk identification method, a grid state parameter initialization method for transient overvoltage risk identification, a new energy output value calculation method that meets the short-circuit ratio of multiple stations, a transient overvoltage high-risk operating condition screening method based on impedance calculation, an electromagnetic transient simulation platform calling and transient overvoltage peak extraction method, a transient overvoltage risk identification signal setting and identification information output method. The specific implementation method has been discussed in detail above and will not be repeated here to avoid redundancy.

[0084] Therefore, the embodiment of the present application is based on a quantitative identification method for transient overvoltage risks in a dual-high power system, and through the organic combination of algorithms and real-time simulation technologies, it achieves effective identification of transient overvoltage risks in the power system. The application of this method will help improve the safety and stability of the power grid. At the same time, it also has high scalability and flexibility, and can adapt to the needs of power grids of different sizes.

[0085] According to the quantitative identification method of transient overvoltage risk in dual-high power system of the embodiment of the present application, the short-circuit ratio of multiple stations of each new energy station is calculated based on the multiple basic parameters of the power grid after initialization, and the lowest point of the short-circuit ratio among the multiple stations is determined. At the same time, the first target new energy station whose lowest point of short-circuit ratio is less than the preset short-circuit ratio is screened out, and its output value is adjusted. After the lowest point of the short-circuit ratio corresponding to the first target new energy station is greater than or equal to the preset short-circuit ratio, the transient overvoltage high-risk operating condition is determined and the fault type is matched according to the lowest point of the short-circuit ratio corresponding to all new energy stations and the preset operating condition, and the transient overvoltage high-risk operating condition is simulated and calculated, the voltage effective peak is extracted, and the voltage effective peak is compared with the preset transient overvoltage tolerance value. Based on the comparison result, a transient overvoltage risk identification signal is output, and then the transient overvoltage risk identification information is obtained. As a result, the problems of transient overvoltage risk identification methods in related technologies being highly dependent on the quality and quantity of data, which reduces the accuracy of results when data is insufficient or biased, and increasing the amount of calculation based on complex numerical integration calculations, making the entire risk identification process time-consuming and labor-intensive, are solved. Through the organic combination of algorithms and real-time simulation technologies, effective identification of transient overvoltage risks in power systems is achieved, thereby improving the safety and stability of the power grid.

[0086] Next, a device for quantitatively identifying transient overvoltage risks in a dual-high power system proposed in an embodiment of the present application will be described with reference to the accompanying drawings.

[0087] Figure 3 It is a block diagram of a device for quantitatively identifying transient overvoltage risks in a dual-high power system according to an embodiment of the present application.

[0088] like Figure 3 As shown, the device 10 for quantitatively identifying transient overvoltage risks in a dual-high power system includes: a calculation module 100 , an adjustment module 200 and an acquisition module 300 .

[0089] The calculation module 100 is used to initialize multiple basic grid parameters, calculate the short-circuit ratio of multiple stations of each new energy station in the multiple new energy stations based on the initialized multiple basic grid parameters, and determine the lowest point of the short-circuit ratio in the short-circuit ratio of multiple stations of each new energy station;

[0090] The adjustment module 200 is used to screen out a first target new energy station whose short circuit ratio minimum point is less than a preset short circuit ratio based on the short circuit ratio minimum point of multiple stations of each new energy station, and adjust the output value of the first target new energy station, and after the short circuit ratio minimum point corresponding to the first target new energy station is greater than or equal to the preset short circuit ratio, determine the transient overvoltage high risk operating condition according to the short circuit ratio minimum points corresponding to all new energy stations and the preset operating condition;

[0091] The acquisition module 300 is used to match the fault type based on the transient overvoltage high-risk operating condition, and simulate the transient overvoltage high-risk operating condition based on the fault type, extract the voltage effective peak value, and compare the voltage effective peak value with the preset transient overvoltage tolerance value, and output a transient overvoltage risk identification signal based on the comparison result to obtain transient overvoltage risk identification information according to the transient overvoltage risk identification signal.

[0092] According to one embodiment of the present application, the computing module 100 includes:

[0093] A first acquisition unit, used to acquire a plurality of basic power grid parameters;

[0094] The initialization unit is used to form a power grid parameter database based on multiple power grid basic parameters, and input the power grid parameter database into a preset calculation initialization program to initialize the multiple power grid basic parameters in the power grid parameter database using the preset calculation initialization program.

[0095] According to one embodiment of the present application, the acquisition module 300 includes:

[0096] A first calculation unit is used to simulate and calculate a transient overvoltage high-risk operating condition based on a target output value for a second target new energy station whose short-circuit ratio minimum point is greater than or equal to a preset short-circuit ratio;

[0097] The second calculation unit is used to simulate and calculate the transient overvoltage high-risk operating condition under the adjusted output value for the first target new energy station.

[0098] According to one embodiment of the present application, the acquisition module 300 includes:

[0099] A second acquisition unit is used to output a transient overvoltage risk identification signal of 0 if the voltage effective peak value is less than or equal to a preset transient overvoltage tolerance value, so as to obtain transient overvoltage risk identification information when the transient overvoltage risk identification signal is 0;

[0100] The third acquisition unit is used to output a transient overvoltage risk identification signal of 1 if the voltage effective peak value is greater than a preset transient overvoltage tolerance value, so as to obtain transient overvoltage risk identification information when the transient overvoltage risk identification signal is 1.

[0101] According to the quantitative identification device for transient overvoltage risks in a dual-high power system of the embodiment of the present application, the short-circuit ratio of multiple stations of each new energy station is calculated based on the multiple basic parameters of the power grid after initialization, and the lowest point of the short-circuit ratio among the multiple station short-circuit ratios is determined. At the same time, the first target new energy station whose lowest point of the short-circuit ratio is less than the preset short-circuit ratio is screened out, and its output value is adjusted. After the lowest point of the short-circuit ratio corresponding to the first target new energy station is greater than or equal to the preset short-circuit ratio, the transient overvoltage high-risk operating condition is determined and the fault type is matched according to the lowest point of the short-circuit ratio corresponding to all new energy stations and the preset operating condition, and the transient overvoltage high-risk operating condition is simulated and calculated, the voltage effective peak is extracted, the voltage effective peak is compared with the preset transient overvoltage tolerance value, and a transient overvoltage risk identification signal is output based on the comparison result, thereby obtaining transient overvoltage risk identification information. As a result, the problems of transient overvoltage risk identification methods in related technologies being highly dependent on the quality and quantity of data, which reduces the accuracy of results when data is insufficient or biased, and increasing the amount of calculation based on complex numerical integration calculations, making the entire risk identification process time-consuming and labor-intensive, are solved. Through the organic combination of algorithms and real-time simulation technologies, effective identification of transient overvoltage risks in power systems is achieved, thereby improving the safety and stability of the power grid.

[0102] Figure 4 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device may include:

[0103] Memory 401 , processor 402 , and a computer program stored in the memory 401 and executable on the processor 402 .

[0104] When the processor 402 executes the program, the quantitative identification method for transient overvoltage risk of the dual-high power system provided in the above embodiment is implemented.

[0105] Furthermore, the electronic device further comprises:

[0106] The communication interface 403 is used for communication between the memory 401 and the processor 402 .

[0107] The memory 401 is used to store computer programs that can be executed on the processor 402 .

[0108] The memory 401 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0109] If the memory 401, the processor 402 and the communication interface 403 are implemented independently, the communication interface 403, the memory 401 and the processor 402 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 4 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0110] Optionally, in a specific implementation, if the memory 401, the processor 402 and the communication interface 403 are integrated on a chip, the memory 401, the processor 402 and the communication interface 403 can communicate with each other through an internal interface.

[0111] The processor 402 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0112] This embodiment also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned method for quantitatively identifying transient overvoltage risks in a dual-high power system.

[0113] An embodiment of the present invention also provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the method for quantitatively identifying transient overvoltage risks in a dual-high power system as described in the above embodiment.

[0114] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0115] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0116] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0117] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or N wirings (electronic devices), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or otherwise processing in a suitable manner if necessary, and then stored in a computer memory.

[0118] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiment, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0119] A person skilled in the art may understand that all or part of the steps in the above-mentioned embodiment method may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0120] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0121] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A quantitative identification method for transient overvoltage risk in a dual-high power system, characterized in that: The following steps are involved: Initializing a plurality of basic power grid parameters, and calculating a short-circuit ratio of multiple stations of each of a plurality of new energy stations based on the initialized basic power grid parameters, and determining a minimum point of the short-circuit ratio of the multiple stations of each new energy station; Based on the lowest short-circuit ratio point among the short-circuit ratios of multiple stations of each new energy station, a first target new energy station whose lowest short-circuit ratio point is less than a preset short-circuit ratio is screened out, and the output value of the first target new energy station is adjusted, and after the lowest short-circuit ratio point corresponding to the first target new energy station is greater than or equal to the preset short-circuit ratio, a transient overvoltage high-risk operating condition is determined according to the lowest short-circuit ratio points corresponding to all new energy stations and the preset operating condition; The fault type is matched based on the transient overvoltage high-risk operating condition, and the transient overvoltage high-risk operating condition is simulated and calculated based on the fault type, the voltage effective peak is extracted, and the voltage effective peak is compared with a preset transient overvoltage tolerance value, and a transient overvoltage risk identification signal is output based on the comparison result to obtain transient overvoltage risk identification information according to the transient overvoltage risk identification signal.

2. The method according to claim 1, characterized in that The initialization of multiple basic parameters of the power grid includes: Acquiring the plurality of basic power grid parameters; A power grid parameter database is formed based on the multiple power grid basic parameters, and the power grid parameter database is input into a preset calculation initialization program, so as to initialize the multiple power grid basic parameters in the power grid parameter database using the preset calculation initialization program.

3. The method according to claim 1, characterized in that The simulating and calculating the transient overvoltage high-risk operating condition based on the fault type to extract the voltage effective peak value includes: For a second target new energy station whose short-circuit ratio minimum point is greater than or equal to the preset short-circuit ratio, a simulation calculation is performed on the transient overvoltage high-risk operating condition based on the target output value; For the first target new energy station, a simulation calculation is performed on the transient overvoltage high-risk operating condition under the adjusted output value.

4. The method according to claim 1, characterized in that The outputting of the transient overvoltage risk identification signal based on the comparison result to obtain transient overvoltage risk identification information according to the transient overvoltage risk identification signal includes: If the voltage effective peak value is less than or equal to the preset transient overvoltage tolerance value, the transient overvoltage risk identification signal is output as 0, so as to obtain transient overvoltage risk identification information when the transient overvoltage risk identification signal is 0; If the voltage effective peak value is greater than the preset transient overvoltage tolerance value, the output transient overvoltage risk identification signal is 1, so as to obtain transient overvoltage risk identification information when the transient overvoltage risk identification signal is 1.

5. A quantitative identification device for transient overvoltage risk in a dual-high power system, characterized in that: include: A calculation module, used to initialize multiple basic grid parameters, and calculate the short-circuit ratio of multiple stations of each of the multiple new energy stations based on the initialized multiple basic grid parameters, and determine the lowest point of the short-circuit ratio in the short-circuit ratio of multiple stations of each new energy station; An adjustment module, for screening out a first target new energy station whose short circuit ratio minimum point is less than a preset short circuit ratio based on the short circuit ratio minimum point of multiple stations of each new energy station, and adjusting the output value of the first target new energy station, and determining a transient overvoltage high-risk operating condition according to the short circuit ratio minimum points corresponding to all new energy stations and a preset operating condition after the short circuit ratio minimum point corresponding to the first target new energy station is greater than or equal to the preset short circuit ratio; An acquisition module is used to match the fault type based on the transient overvoltage high-risk operating condition, and simulate the transient overvoltage high-risk operating condition based on the fault type, extract the voltage effective peak value, and compare the voltage effective peak value with a preset transient overvoltage tolerance value, and output a transient overvoltage risk identification signal based on the comparison result to obtain transient overvoltage risk identification information according to the transient overvoltage risk identification signal.

6. The device according to claim 5, characterized in that The computing module comprises: A first acquisition unit, configured to acquire the plurality of basic power grid parameters; An initialization unit is used to form a power grid parameter database based on the multiple power grid basic parameters, and input the power grid parameter database into a preset calculation initialization program to initialize the multiple power grid basic parameters in the power grid parameter database using the preset calculation initialization program.

7. The device according to claim 5, characterized in that The acquisition module comprises: A first calculation unit is used to perform simulation calculation on the transient overvoltage high-risk operating condition based on a target output value for a second target new energy station whose short-circuit ratio minimum point is greater than or equal to the preset short-circuit ratio; The second calculation unit is used to simulate and calculate the transient overvoltage high-risk operating condition under the adjusted output value for the first target new energy station.

8. The device according to claim 5, characterized in that The acquisition module comprises: A second acquisition unit is used to output a transient overvoltage risk identification signal of 0 if the voltage effective peak value is less than or equal to the preset transient overvoltage tolerance value, so as to obtain transient overvoltage risk identification information when the transient overvoltage risk identification signal is 0; The third acquisition unit is used to output a transient overvoltage risk identification signal of 1 if the voltage effective peak value is greater than the preset transient overvoltage tolerance value, so as to obtain transient overvoltage risk identification information when the transient overvoltage risk identification signal is 1.

9. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement a method for quantitatively identifying transient overvoltage risks in a dual-high power system as described in any one of claims 1 to 4.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement a quantitative identification method for transient overvoltage risks in a dual-high power system as described in any one of claims 1-4.

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