Distribution network protection setting value setting method and system under whole county photovoltaic scene

Abstract

The invention discloses a distribution network protection fixed value setting method and system in a whole county photovoltaic scene. The method comprises the steps of obtaining a first target parameter and a second target parameter of a first target distribution network; establishing a second target power distribution network model, wherein the second target power distribution network model is the first target power distribution network simulation model after the distributed power supply is accessed; presetting a first optimization algorithm, and optimizing the second target power distribution network model based on the first optimization algorithm; and based on the optimized second target power distribution network model, in combination with the first setting strategy, performing distribution network protection setting value setting. The quantitative calculation method is applied to an actual power distribution network, the effectiveness and accuracy of the quantitative calculation method are verified through simulation experiments, field tests and other modes, the feasibility of the quantitative calculation method is verified, and powerful support is provided for application and popularization of the quantitative calculation method in actual engineering. Fault features can be rapidly and accurately extracted, and the safety of matching use of the scheme is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of distribution network protection constant value setting, and in particular to a distribution network protection constant value setting method and system in a whole-county photovoltaic scenario. Background Art

[0002] As an important form of renewable energy, photovoltaics have become an important means for promoting energy transformation in various places. In order to improve the popularity and efficiency of photovoltaic power generation, many places have proposed the concept of "whole-county photovoltaics", that is, by systematically planning and building photovoltaic power stations throughout the county, covering various public facilities, abandoned land, etc., to promote the rapid development of the photovoltaic industry;

[0003] In the whole-county photovoltaic scenario, the operation mode and fault characteristics of the distribution network become more complicated. The volatility and intermittent nature of photovoltaic power generation make the direction and size of current no longer single. In the traditional distribution network, the identification and location of faults mainly rely on experience and conventional monitoring methods, which can hardly meet the real-time and accuracy requirements of modern distribution networks. Summary of the invention

[0004] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0005] In view of the above existing problems, the present invention is proposed.

[0006] Therefore, the present invention provides a distribution network protection constant value setting method and system in a whole-county photovoltaic scenario, which can solve the problems mentioned in the background technology.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0008] In a first aspect, the present invention provides a method for setting a fixed value of distribution network protection in a whole-county photovoltaic scenario, comprising:

[0009] Obtaining a first target parameter and a second target parameter of a first target distribution network;

[0010] Establishing a second target distribution network model, where the second target distribution network model is a simulation model of the first target distribution network after the distributed power source is connected;

[0011] Preset a first optimization algorithm, and optimize the second target distribution network model based on the first optimization algorithm;

[0012] Based on the optimized second target distribution network model and combined with the first setting strategy, the distribution network protection constant value setting is performed.

[0013] As a preferred solution of the method for setting the fixed value of distribution network protection in the whole-county photovoltaic scenario described in the present invention, wherein: the preset first optimization algorithm and the optimization of the second target distribution network model based on the first optimization algorithm include:

[0014] Establishing a first objective function according to the user's optimization goal;

[0015] Optimizing a first objective function according to the first optimization algorithm;

[0016] The target configuration parameters of the second target distribution network model are obtained according to the optimized first objective function.

[0017] As a preferred solution of the method for setting the fixed value of distribution network protection in the whole-county photovoltaic scenario described in the present invention, wherein: the setting of the fixed value of distribution network protection based on the optimized second target distribution network model and combined with the first setting strategy includes:

[0018] Optimizing a second target distribution network model according to the target configuration parameters;

[0019] Acquire a third target parameter based on the optimized second target distribution network model;

[0020] The distribution network protection constant value is set according to the third target parameter in combination with the first setting strategy.

[0021] As a preferred solution of the method for setting the fixed value of distribution network protection in the whole-county photovoltaic scenario described in the present invention, the first setting strategy includes:

[0022] Acquiring a third target parameter, and establishing a first tuning operation based on the third target parameter;

[0023] Obtaining a fourth target parameter obtained after the third target parameter is subjected to the first setting operation;

[0024] The first setting operation is any operation for solving a setting value.

[0025] As a preferred solution of the method for setting the fixed value of distribution network protection in the whole-county photovoltaic scenario described in the present invention, wherein: the first objective function is established according to the user's optimization goal, including:

[0026] The user optimization target is an optimization target selected by the user for the second target distribution network model;

[0027] Establishing a first objective function for the user optimization target according to the user optimization target;

[0028] The first objective function at least includes any parameter function that can describe the entire second target distribution network. As a preferred solution of the distribution network protection setting value setting method in the whole county photovoltaic scenario described in the present invention, the establishment of the second target distribution network model includes:

[0029] Determine the grid connection method and target access point of distributed power sources;

[0030] According to the grid connection access mode and the target access point, a second target distribution network model is established in combination with the first target parameter and the second target parameter;

[0031] A simulation test is performed on the second target distribution network model.

[0032] As a preferred scheme of the distribution network protection constant setting method in the whole-county photovoltaic scenario described in the present invention, wherein: the third target parameter at least includes the second target distribution network model operation mode and operation constant.

[0033] In a second aspect, the present invention provides a distribution network protection setting value setting system in a whole-county photovoltaic scenario, characterized in that it includes:

[0034] A data acquisition module, used to acquire a first target parameter and a second target parameter of a first target distribution network;

[0035] A model building module, used to build a second target distribution network model, where the second target distribution network model is a simulation model of the first target distribution network after the distributed power source is connected;

[0036] An optimization module, configured to preset a first optimization algorithm and optimize the second target distribution network model based on the first optimization algorithm;

[0037] The setting module is used to set the distribution network protection constant value based on the optimized second target distribution network model in combination with the first setting strategy.

[0038] In a third aspect, the present invention provides a computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the above-mentioned method when executing the computer program.

[0039] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps of the method described above when executed by a processor.

[0040] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention proposes a method and system for setting the constant value of distribution network protection in a whole-county photovoltaic scenario, obtaining the first target parameter and the second target parameter of the first target distribution network; establishing a second target distribution network model, wherein the second target distribution network model is a simulation model of the first target distribution network after connecting to a distributed power source; presetting a first optimization algorithm, optimizing the second target distribution network model based on the first optimization algorithm; and setting the constant value of distribution network protection based on the optimized second target distribution network model in combination with the first setting strategy. The quantitative calculation method is applied to the actual distribution network, and its effectiveness and accuracy are verified through simulation experiments and field tests, which not only verifies the feasibility of the quantitative calculation method, but also provides strong support for its promotion and application in actual projects. Therefore, through the setting of this scheme, fault characteristics can be extracted quickly and accurately, ensuring the safety of the supporting use of the scheme. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0042] Figure 1 A method flow chart of a method and system for setting a fixed value of distribution network protection in a whole-county photovoltaic scenario provided by an embodiment of the present invention;

[0043] Figure 2 A schematic diagram of a normal component network and a faulty component network when a distribution network containing whole-county photovoltaic fails, provided by a method and system for setting a fixed value of distribution network protection in a whole-county photovoltaic scenario according to an embodiment of the present invention;

[0044] Figure 3 A schematic diagram of a 10kV distribution network feeder line end short circuit diagram of a distribution network protection setting value setting method and system in a whole-county photovoltaic scenario provided by an embodiment of the present invention;

[0045] Figure 4 A distribution network protection setting value setting method and system in a whole-county photovoltaic scenario provided by one embodiment of the present invention; a distribution network protection setting value setting system in a whole-county photovoltaic scenario;

[0046] Figure 5 An internal structural diagram of a computer device of a distribution network protection constant value setting method and system in a whole-county photovoltaic scenario provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0047] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0048] Example 1

[0049] Reference Figure 1-Figure 5 , which is the first embodiment of the present invention, and provides a distribution network protection setting value setting method and system in a whole-county photovoltaic scenario, including:

[0050] There are some problems in the existing related technologies. For example, the distribution network protection constant setting method is not accurate enough and cannot adapt to the complex operating environment after the distributed power source is connected, resulting in the protection device being unable to accurately identify and isolate faults, affecting the safe and stable operation of the distribution network.

[0051] This application provides a method that can effectively solve the above-mentioned problems. Next, we will combine multiple embodiments to explain in detail how to implement the distribution network protection setting value setting method in the whole county photovoltaic scenario;

[0052] Figure 1 A method flow chart of a distribution network protection setting value setting method and system in a whole-county photovoltaic scenario is shown, including:

[0053] S101, obtaining a first target parameter and a second target parameter of a first target distribution network;

[0054] In an optional embodiment, the first target parameter and the second target parameter of the first target distribution network can be actually selected according to the design purpose. For example, in an actual application for the purpose of setting the distribution network protection constant in a whole-county photovoltaic scenario, the first target parameter may include but is not limited to the voltage level, line impedance, transformer capacity, etc. of the distribution network, while the second target parameter may include information such as the type, capacity, and grid-connected location of the distributed power source.

[0055] In another optional embodiment, the process of obtaining the first target parameter and the second target parameter of the first target distribution network can be implemented in a variety of ways. For example, the existing distribution network monitoring system can be used to monitor the operating status of the distribution network in real time through sensors and data acquisition devices, and collect relevant parameters. In addition, these parameters can also be manually input by an operator according to the design drawings and actual operating conditions of the distribution network.

[0056] In another optional embodiment, in order to improve the accuracy of the setting of the distribution network protection setting value, advanced computing models and algorithms can be used to analyze the collected parameters. For example, a machine learning algorithm can be used to train historical fault data and establish a fault prediction model, so as to quickly and accurately identify the fault type and location in actual operation. In addition, the operating status of the distribution network can be dynamically adjusted in combination with real-time weather data and environmental information to adapt to different external conditions.

[0057] In the embodiment of the present application, the first target parameter of the first target distribution network selects parameters such as the main transformer, system impedance, line impedance, distribution transformer and load of the first target distribution network, and the second target parameter selects impedance and distance data between each node of the first target distribution network;

[0058] It should be noted that the first target distribution network is an original network, which is a distribution network that has not been connected to distributed power sources;

[0059] In an optional embodiment, basic data of the distribution network is collected, including the capacity of the main transformer, system impedance and line impedance. By conducting a detailed investigation and measurement of the distribution network, the electrical characteristic data of each node is obtained, and the capacity of the main transformer is reasonably selected, thereby effectively reducing voltage losses and improving power supply reliability.

[0060] In an optional embodiment, the original distribution network is regarded as a whole, and the impedance and distance data between each node are analyzed to establish the original network model, which will be used for subsequent distributed power access analysis;

[0061] Exemplarily, determining the parameters of the main transformer of the distribution network and determining the rated capacity of the main transformer may include:

[0062]

[0063] Among them, p is active power, Q is reactive power. The purpose of determining the main transformer parameters and rated capacity of the distribution network is to ensure the safety and reliability of the system, avoid overload operation of equipment, and thus ensure the stable supply of electricity. At the same time, the accurate determination of these parameters helps to optimize power distribution, improve system efficiency, and provide a basis for fault analysis and protection setting. The complex capacity of the main transformer can be expressed as:

[0064] S=P+jQ(#2)

[0065] Where j is an imaginary unit. Determining the complex capacity of the main transformer is a key step in the setting method of distribution network protection in the whole-county photovoltaic scenario. It provides basic data for subsequent load modeling and system optimization. Its calculation results directly affect the accuracy of the distribution network model and the safety and efficiency of the power system, improve the accuracy and efficiency of power system analysis, and provide support for fault analysis and dynamic simulation. The complex power needs to be further refined as follows:

[0066] S=|S|e jθ (#3)

[0067] in, is the magnitude of the complex power, The power factor is the power factor angle, which indicates the phase relationship between active power and reactive power. It is an important step in determining the parameters of the main transformer of the distribution network and calculating the rated capacity of the main transformer. As mentioned above, when determining the complex capacity of the main transformer, it is necessary to calculate the amplitude and power factor of the complex power, and the refinement of the complex power helps to better understand the relationship between active power and reactive power. This refinement provides basic data for subsequent load modeling and system impedance calculation, thereby affecting the accuracy of the entire distribution network model and the effect of optimal configuration. According to the calculated complex power amplitude, the effectiveness of the system in using electric energy is evaluated, and the power factor is calculated. The power factor is the ratio of active power to apparent power, which is defined as:

[0068]

[0069] The power factor has a value between -1 and 1 and is used to evaluate the efficiency of the power system. A power factor close to 1 indicates a high efficiency of the power system, while a power factor close to 0 indicates a low efficiency.

[0070] In an optional embodiment, the voltage of each node in the system is associated with the injection current and impedance parameters to form a complete power system model. The voltage distribution and power flow of the system are quickly solved by linear algebra methods. The voltage value is updated in each iteration and finally determined. The complex power is expressed in the form of a matrix:

[0071]

[0072] Where S n represents the complex power of the nth load, P n and Q n They are active and reactive power respectively. The matrix form can concentrate the complex power of multiple loads in one structure, which is convenient for systematic analysis and calculation of the power characteristics of the entire distribution network. Through matrix operations, the calculation process of complex power can be simplified. Especially when dealing with complex networks, matrix operations can effectively reduce the calculation steps and improve the calculation efficiency.

[0073] It should be noted that this step allows for a comprehensive analysis of the complex power of all loads in the distribution network, and can simultaneously consider the active and reactive power of multiple loads, providing a comprehensive perspective to understand the operating status of the system. Through the matrix form, linear algebra operations, such as matrix multiplication and inversion, can be used to quickly calculate and analyze complex power, which improves the overall calculation efficiency. The matrix expression makes it easier to take the characteristics of each load into consideration when establishing a distribution network model, thereby providing a basis for subsequent simulation and optimization. In the subsequent optimization steps, the complex power in matrix form can be combined with optimization algorithms, such as particle swarm optimization algorithms, to facilitate complex calculations and optimization configurations, and help achieve more efficient distribution network management.

[0074] In an optional embodiment, through the matrix form, it is more convenient to analyze the dynamic changes of the system at different time points, understand the impact of load changes on system performance, and provide a basis for real-time monitoring and regulation of the distribution network;

[0075] Specifically: In this step, we mainly pave the way for the dynamic simulation design proposed later. First, we build a distribution network model that includes the distributed power sources of the entire county. This model integrates the geographical information, load characteristics and access methods of the distribution network. We use professional power system simulation software for dynamic simulation design. During the simulation process, we set different operating conditions, including normal operating status, load mutations such as sudden peak power consumption and faults. During the dynamic simulation process, we record the changes in voltage, frequency, power flow and electrical characteristics of each node.

[0076] In an optional embodiment, when designing and analyzing a power system, it is critical to consider the active and reactive components of the load. Complex power can be used to more accurately assess the needs of power equipment, and reactive power management is critical to the stability of the power system. Insufficient reactive power may cause voltage drops and affect system operation. Under nonlinear loads, the concept of complex power can also be extended to harmonic analysis to consider the additional reactive power caused by harmonics.

[0077] In an optional embodiment, the rated capacity of the main transformer is determined by first determining the number of winding turns, obtaining the number of winding turns on the primary and secondary sides through the design parameters of the transformer, using the transformation ratio formula to calculate the transformation ratio, and then calculating the voltage relationship, in which the primary and secondary voltage relationship is determined, and the specific voltage value is calculated, that is, the primary voltage is input and the secondary voltage is calculated to verify the power relationship. The specific calculation formula is as follows:

[0078]

[0079] Among them, P1 is the power on the primary side, P2 is the power on the secondary side, V1 is the primary side voltage, I1 is the primary side current, N1 is the number of turns of the primary winding, and N2 is the number of turns of the secondary winding. In an ideal transformer, the power is conserved between the primary and secondary sides, and can be described by the relationship between the transformation ratio and the number of turns;

[0080] It should be noted that when determining the specific steps of the main transformer of the distribution network, formula (#6) is used to calculate the amplitude and power factor of the complex power. This is to ensure that when designing the distribution network, the capacity of the transformer and other equipment can be accurately evaluated to meet the load demand. The amplitude of the complex power represents the total power demand of the system at a certain moment, while the power factor reflects the efficiency of the system. In the subsequent steps, the calculation of the system impedance needs to rely on accurate complex power data. The complex power calculated by formula (#6) can be used as input to help perform more accurate impedance calculations in the dynamic load model, thereby affecting the performance evaluation and fault analysis of the entire distribution network;

[0081] It should be noted that when analyzing the dynamic changes of the distribution network at different time points, the calculated complex power and power factor provide basic data for understanding the impact of load changes on system performance, which is crucial for timely adjustment and optimization of the operating status of the distribution network;

[0082] In the embodiment of the present application, the load impedance is modeled, the impedance of each component is calculated in series and parallel, and the equivalent impedance of the entire system is obtained, which is substituted into the power system model and adjusted;

[0083] In the embodiment of the present application, the stability of the distribution network is improved by managing and calculating reactive power, avoiding voltage drops caused by insufficient reactive power, ensuring the reliability of power supply, and thus enhancing system stability. Through the above method, an accurate mathematical model can be established, and the cause can be quickly analyzed when a fault occurs, and effective treatment measures can be formulated, thereby reducing power outage time and economic losses. Accurately calculating the rated capacity and power factor of the main transformer can also improve the operating efficiency of the power system and reduce overall energy consumption.

[0084] It should be noted that obtaining the first target parameter and the second target parameter of the first target distribution network can provide key data support for real-time monitoring and fault diagnosis of the distribution network. By accurately measuring and calculating the voltage, current and other parameters of the first target distribution network, the operation status of the power grid can be monitored in real time and abnormal conditions can be discovered in time. At the same time, the acquisition of the second target parameters, such as ambient temperature and humidity, is crucial for evaluating the impact of external conditions on the performance of power grid equipment. The comprehensive analysis of these data helps to formulate more accurate protection settings, thereby improving the stability and reliability of the entire distribution network.

[0085] S102, establishing a second target distribution network model, where the second target distribution network model is a simulation model of the first target distribution network after the distributed power source is connected;

[0086] In an optional embodiment, the second target distribution network model can be established using a variety of methods, for example, a distribution network model including distributed power sources can be constructed using power system simulation software based on the parameters of the first target distribution network and the characteristics of the distributed power sources. The model can simulate the impact of the access of distributed power sources on the distribution network, including changes in key parameters such as voltage level, current distribution, and power flow.

[0087] In another optional embodiment, when establishing the second target distribution network model, factors such as the access location, access method, and access capacity of the distributed power source can also be considered to ensure the accuracy and practicality of the model. By simulating the operation under different scenarios, the impact of the access of distributed power sources on the stability and reliability of the distribution network can be evaluated, providing a scientific basis for the subsequent protection setting.

[0088] In another optional embodiment, the second target distribution network model can also be optimized using a machine learning algorithm, and the model can be trained with historical data to predict various operating conditions that may occur after the distributed power source is connected, so as to prepare countermeasures in advance. This method can significantly improve the prediction accuracy and adaptability of the model, and provide strong technical support for the stable operation of the distribution network.

[0089] In another optional embodiment, the second target distribution network model can be further optimized using a digital twin model. Digital twin technology can monitor and analyze the actual operating status of the distribution network in real time by creating a virtual copy of the distribution network. This model can reflect the detailed conditions of the distribution network at different time points, including factors such as equipment aging, load changes, and environmental impacts, thereby providing more accurate operating data.

[0090] In another optional embodiment, the digital twin model can also be combined with advanced prediction algorithms, such as time series analysis, machine learning, etc., to predict the operating trend of the distribution network in the future. In this way, potential risks and problems can be discovered in advance, providing decision support for the maintenance and upgrade of the distribution network. At the same time, the digital twin model can also be used to simulate various extreme situations, such as natural disasters, equipment failures, etc., to evaluate the response capacity and vulnerability of the distribution network, so as to formulate more effective emergency plans.

[0091] In an embodiment of the present application, establishing the second target distribution network model includes:

[0092] Determine the grid connection method and target access point of distributed power sources;

[0093] According to the grid connection access mode and the target access point, a second target distribution network model is established in combination with the first target parameter and the second target parameter;

[0094] The second target distribution network model is simulated and tested.

[0095] Exemplarily, basic data collection for model construction is performed, with priority given to collecting geographic information of the distribution network area, including topography, land use type, and climate conditions. GIS tools are used to visualize and analyze geographic data, identify areas suitable for photovoltaic and wind power installation, and then collect load data on electricity consumption in residential, commercial, and industrial areas. Historical electricity consumption data is used to analyze load characteristics and identify peak load and valley load periods. Finally, the parameters and locations of existing substations, distribution lines, and switchgear are collected, and the capacity and operating status of existing facilities are evaluated to determine their carrying capacity.

[0096] Furthermore, the loads are classified and the electricity consumption patterns of each category are analyzed to establish a load forecasting model, and the subsequent load change trend is predicted based on historical data;

[0097] Furthermore, the access mode of distributed power sources is designed, the grid connection mode of distributed power sources is determined, and its impact on the distribution network is evaluated. The grid connection control strategy is designed to require that the voltage and frequency can be stable during grid connection operation. The access points are selected according to the load distribution and existing facilities, and the electrical characteristics of different access points are evaluated. The access capacity of each distributed power source is calculated according to the load demand and the power generation capacity of the distributed power sources, and the load forecast results are used to ensure the power supply of the distributed power sources during peak load periods. At the same time, the access capacity design is optimized according to the renewable characteristics of the distributed power sources;

[0098] Furthermore, the node model and the line model are selected, and the model is built according to the selection. At the same time, the topology of the distribution network is designed, the connection between each node, line and equipment is determined, and finally the parameters are set to complete the construction of the model. The setting parameters include line parameters, transformer parameters, load model and distributed power supply parameters;

[0099] Furthermore, dynamic simulation design is carried out to simulate various normal operation, load mutation and fault occurrence. At the same time, the system response after the distributed power supply is connected is analyzed and the changes in voltage, frequency and power flow related parameters are recorded. It is necessary to determine the parameters of sensitivity analysis, analyze the impact on the performance of the distribution network by changing the sensitivity parameters, and identify the key parameters;

[0100] It should be noted that the second target distribution network model is established. The second target distribution network model is a simulation model of the first target distribution network after the distributed power source is connected. It can provide a comprehensive perspective for the protection setting of the distribution network. By simulating the operation of the distribution network after the distributed power source is connected, the performance of the system under various operating conditions can be more accurately evaluated, including key parameters such as voltage stability, current distribution and power flow. This provides a scientific basis for the setting of protection settings, ensuring that various abnormal situations can be responded to in a timely and accurate manner in actual operation, thereby improving the reliability and safety of the distribution network.

[0101] S103, presetting a first optimization algorithm, and optimizing the second target distribution network model based on the first optimization algorithm;

[0102] In an embodiment of the present application, a first optimization algorithm is preset, and optimizing the second target distribution network model based on the first optimization algorithm includes:

[0103] Establishing a first objective function according to the user's optimization goal;

[0104] Optimizing a first objective function according to a first optimization algorithm;

[0105] The target configuration parameters of the second target distribution network model are obtained according to the optimized first objective function.

[0106] In an optional embodiment, the first optimization algorithm may be a particle swarm optimization algorithm (PSO), which simulates the foraging behavior of bird flocks and seeks the optimal solution through cooperation and competition among individuals in the flock. In the optimization of the distribution network model, each particle represents a possible solution, and the particle swarm moves in the solution space, updates its own speed and position by tracking the individual historical best position and the group historical best position, thereby gradually approaching the optimal solution.

[0107] In another optional embodiment, the first optimization algorithm may also be a genetic algorithm (GA), which is based on the principles of natural selection and genetics and searches for the optimal solution by simulating the selection, crossover and mutation operations in the biological evolution process. In the distribution network model optimization, each individual represents a set of possible configuration parameters, and new individuals are generated by selecting individuals with high fitness for crossover and mutation operations, and iterating continuously until the optimal solution is found.

[0108] In another optional embodiment, the first optimization algorithm may also be a simulated annealing algorithm (SA), which simulates the solid annealing process and reduces the energy of the system by gradually lowering the "temperature" of the system, thereby finding the lowest energy state of the system, i.e., the optimal solution. In the distribution network model optimization, the optimal configuration is gradually approached by randomly perturbing the current solution and accepting or rejecting the new solution.

[0109] In another optional embodiment, the first optimization algorithm may also be an ant colony optimization (ACO), which simulates the behavior of ants in finding food paths and guides the colony to find the optimal path by releasing pheromones. In the distribution network model optimization, ants represent different configuration schemes, and guide the algorithm to search for the optimal configuration through the accumulation and volatilization of pheromones.

[0110] In another optional embodiment, the first optimization algorithm may also be a differential evolution algorithm (DE), which generates new candidate solutions through vector difference and crossover operations, and retains solutions with higher fitness through selection operations. In the optimization of distribution network models, the differential evolution algorithm can effectively handle optimization problems in multi-dimensional parameter spaces and quickly find the global optimal solution.

[0111] In the embodiment of the present application, the particle swarm optimization algorithm based on random mutation is used to calculate the optimal configuration of the distributed power grid connection to obtain the final optimized model;

[0112] In an embodiment of the present application, establishing a first objective function according to the user optimization goal includes:

[0113] The user optimization target is the optimization target selected by the user for the second target distribution network model;

[0114] Establishing a first objective function for the user optimization target according to the user optimization target;

[0115] The first objective function at least includes any parameter function that can describe the entire second objective power distribution network.

[0116] For example, when the user's optimization goal is to be described by impedance, the components of the system are defined, and the impedance calculation of the defined components is incorporated into the dynamic load model, and the system impedance Z is defined first. system for:

[0117] Z system =Z transformers +Z lines +Z loads (#7)

[0118] This formula is the premise for the subsequent short-circuit current calculation and system dynamic response analysis;

[0119] Among them, Z transformers is the total impedance of all transformers, Z lines is the total impedance of all lines, Z loads is the equivalent impedance of all loads;

[0120] Furthermore, the instantaneous change of load is introduced into the calculation of system impedance to reflect the load fluctuation in the actual operation of the distribution network:

[0121]

[0122] Among them, Z loads (t) is the instantaneous impedance of the load, P(t) is the active power at time t, Q(t) is the reactive power, and V is the system voltage. The active and reactive powers are further subdivided into basic power and instantaneous changes, and their expressions are substituted into the impedance formula to build a dynamic load model:

[0123]

[0124] Among them, P base is the basic active power, Q base is the basic reactive power. Based on the relationship between power and voltage, we start to calculate the instantaneous current:

[0125]

[0126] Furthermore, after obtaining the instantaneous current, the instantaneous impedance of the load is calculated and obtained:

[0127]

[0128] Furthermore, instantaneous impedance can reflect the state of the load at a specific time point, helping the system to monitor load changes in real time. By analyzing the changes in instantaneous impedance, potential faults and unstable factors can be identified. Combined with the system impedance Z system , define a comprehensive objective function F(t), i.e. the first objective function, which is used to represent the performance of the entire distribution network, and is represented by summing the power of each load:

[0129]

[0130] Where N is the number of nodes in the distribution network, P i (t) represents the active power of the i-th load at time t, Q i(t) represents the reactive power of the ith load at time t. The sum of the active power and reactive power of each load can reflect the overall performance of the distribution network at a specific moment, which is convenient for evaluating the operating status of the distribution network under different load conditions.

[0131] Furthermore, the instantaneous variation is integrated to analyze the dynamic changes of the distribution network at different time points. The power and instantaneous variation in the time domain are converted to the frequency domain to capture the dynamic response of the distribution network at different time points. The instantaneous variation ΔF(t) is introduced to represent the change of power:

[0132]

[0133] Where N is the number of nodes in the distribution network, ΔP i (t) and ΔQ i (t) respectively represent the changes in active and reactive power of the i-th load at time t. After obtaining the analysis results, Fourier transform is used to represent the relationship between power and impedance, capture the dynamic response of the distribution network at different time points, assist in understanding the impact of load fluctuations on the power system, and define it in the frequency domain:

[0134]

[0135] It should be noted that this formula is used to convert time domain signals into frequency domain signals. Fourier transform can reveal the frequency components of the signal and help analyze the characteristics of the signal at different frequencies. Through the setting of multiple loads, it is shown that the system can capture the dynamic changes of the distribution network at different time points through the setting of the above formula, which is convenient for real-time monitoring and adjustment of the operating status of the distribution network. The formula can also improve the system's adaptability to load changes and provide technical support for the implementation of smart grids.

[0136] in, represents Fourier transform, F(f) is the comprehensive performance function in the frequency domain. The performance indicators of the distribution network are further integrated through frequency domain analysis. The power of each load in the distribution network and the impedance of the system are integrated, and the influence of load changes and system impedance in the frequency domain are considered. The above expression is expressed as:

[0137]

[0138] Furthermore, the power and impedance characteristics of the distribution network are finally integrated through the comprehensive performance function in the frequency domain to obtain the impedance matrix of the node.

[0139] It should be noted that when using the particle swarm optimization algorithm based on random mutation to calculate the optimal configuration of distributed power grid connection, the complex power data provided by formula (#6) can be used as the basic input of the optimization algorithm to help the algorithm better evaluate the system performance under different configurations, thereby achieving more efficient resource allocation;

[0140] It should also be noted that by introducing instantaneous load changes, the operating status of the distribution network can be monitored and adjusted in real time, and the system's adaptability to load changes can be improved. By analyzing instantaneous current and impedance, potential faults or unstable factors can be identified in a timely manner, and the safety and reliability of the distribution network can be enhanced. This method can effectively deal with the monitoring and debugging difficulties brought about by the access of large-capacity distributed power sources, ensure the effective use of renewable energy and the stable operation of the system, and the above method provides technical support for the implementation of smart grids through the combination of dynamic load models and optimization algorithms, thereby promoting the intelligentization and automation of power systems.

[0141] In an optional embodiment, the first objective function can be actually designed according to actual needs, and relevant technical personnel can adjust and optimize the first objective function according to the specific conditions and requirements of the distribution network. For example, factors such as voltage stability, current limitation, and equipment life can be considered in the scope of consideration of the objective function to achieve a more comprehensive and refined optimization. In addition, the concept of multi-objective optimization can also be introduced to consider multiple optimization goals at the same time, such as minimizing energy loss while maximizing system reliability, so as to achieve a more balanced and optimized configuration effect.

[0142] In another optional embodiment, the first objective function obtained by summing the power of each load in the entire distribution network can accurately reflect the needs of the user's optimization target. In order to further improve the optimization effect, the voltage and current of each node in the distribution network can be used as variables to construct an objective function including voltage stability and current limitation. For example, the objective function can be set to minimize the weighted sum of voltage deviation and current deviation, while considering the equipment life and operating cost, to ensure that while meeting the load demand, the service life of the equipment is extended and the operating cost is reduced.

[0143] In another optional embodiment, in order to adapt to the access of renewable energy and load fluctuations, the objective function can also include consideration of the ability to respond to instantaneous load changes. Through real-time monitoring and adjustment, the system can quickly adapt to load changes and reduce the instability of voltage and current caused by load fluctuations. This not only improves the operating efficiency of the distribution network, but also enhances the flexibility and reliability of the system.

[0144] In another optional embodiment, the objective function can be further refined into a multi-objective optimization model that includes the ability to respond to transient load changes. For example, an objective function can be set to minimize the impact of voltage deviation, current deviation, and transient load changes on system stability, while considering the maintenance cost and operating efficiency of the equipment, so as to optimize the operation and maintenance strategy of the equipment while ensuring system stability.

[0145] It should be noted that the first optimization algorithm is preset, and the optimization of the second target distribution network model based on the first optimization algorithm can achieve efficient optimization of the distribution network model. The algorithm can dynamically adjust the protection setting value according to the real-time data and historical data of the distribution network, so as to ensure that the distribution network can maintain the best operating state under various operating conditions. This optimization can not only reduce power outages caused by equipment failures or load fluctuations, but also improve the power supply reliability and power quality of the entire system.

[0146] It should also be noted that the optimization algorithm can also take into account the maintenance cycle and cost of the equipment, and by reasonably arranging the maintenance plan of the equipment, it can extend the service life of the equipment and reduce the long-term operation and maintenance costs. In practical applications, this optimization algorithm can be integrated into the intelligent monitoring system of the distribution network to achieve automated and intelligent management, thereby improving the management level and economic benefits of the entire distribution network.

[0147] S104, based on the optimized second target distribution network model and in combination with the first setting strategy, setting of distribution network protection constants is performed.

[0148] In the embodiment of the present application, based on the optimized second target distribution network model and in combination with the first setting strategy, the distribution network protection setting value setting includes:

[0149] Optimizing a second target distribution network model according to target configuration parameters;

[0150] Acquire a third target parameter based on the optimized second target distribution network model;

[0151] The distribution network protection constant is set according to the third target parameter in combination with the first setting strategy.

[0152] In the embodiment of the present application, the third target parameter includes at least the second target distribution network model operation mode and operation constant.

[0153] In an optional embodiment, the first setting strategy can be designed by different methods. For example, a machine learning method based on historical data can be used to analyze historical fault data to predict the type and location of future faults, thereby developing a more accurate protection setting. In addition, the protection setting can be dynamically adjusted in combination with real-time data, such as current, voltage and other parameters, to adapt to changes in the operating status of the power grid.

[0154] In another optional embodiment, the first setting strategy can take into account the topological changes of the distribution network, such as the opening and closing of the line, the tap adjustment of the transformer, etc. These changes will affect the protection setting of the distribution network. By real-time monitoring of these changes and combining with the optimization algorithm, the protection setting can be updated in time to ensure the safe and stable operation of the distribution network.

[0155] In another optional embodiment, the first setting strategy may also integrate an expert system to verify and optimize the protection setting value by using the experience and knowledge of experts. The expert system may provide decision support to help operators make more reasonable judgments in complex situations, thereby improving the accuracy and reliability of the distribution network protection setting value setting.

[0156] In the embodiment of the present application, the first setting strategy includes:

[0157] Acquiring a third target parameter and establishing a first tuning operation based on the third target parameter;

[0158] Obtaining a fourth target parameter obtained after the first setting operation of the third target parameter;

[0159] The first tuning operation is any operation that solves for a tuning value.

[0160] In an optional embodiment, the first setting operation can be a dynamic adjustment based on real-time data of the distribution network. For example, when it is detected that the current or voltage parameters of a line in the distribution network are out of the normal range, the system will automatically trigger the recalculation of the protection setting. This dynamic adjustment can be periodic or event-driven to ensure that the protection setting of the distribution network is optimized in any case.

[0161] In another optional embodiment, the first setting operation may also include analysis and learning of historical data. The system may use machine learning algorithms to analyze historical fault data and protection action records, learn from them and predict possible fault modes. In this way, the system can adjust the protection setting in advance to adapt to potential fault risks, thereby improving the anti-interference ability and overall reliability of the distribution network.

[0162] In another optional embodiment, the first setting operation may be a preset rectification process, such as presetting an overcurrent protection setting or a quick-break protection setting operation;

[0163] In the embodiment of the present application, the first setting operation is to adopt the overcurrent protection setting method, set the action current to 1.2 times the rated current, set the delay to 0.2 seconds, adopt the quick-break protection setting method, set the action time to 50 milliseconds, and set the current value to 1.5 times the short-circuit current, adopt the differential protection setting method, and set it to 5% to 10% of the rated current;

[0164] Exemplarily, based on the optimized second target distribution network model and combined with the first setting strategy, the setting of distribution network protection constants specifically includes the voltage and fault current of the fault component nodes of the distribution network affected by the photovoltaic power generation in the whole county obtained through iteration; specifically, through multiple iterative calculations, the voltage and fault current of the fault component nodes of the distribution network under the condition of photovoltaic power generation in the whole county are obtained, and these data can provide important basis for subsequent fault diagnosis; the setting calculation is performed on the constants within the initial setting calculation range; finally, we perform setting calculations on the constants within the initial setting calculation range to ensure the safety of the distribution network under different operating modes. The set distribution network can effectively reduce the risk of equipment damage caused by improper setting and extend the service life of the equipment.

[0165] In an optional embodiment, a distribution network fault involving photovoltaic power generation in the entire county is specifically decomposed into a normal component network and a fault component network. Based on the superposition theorem, the short-circuit current of different fault types of the distribution network containing photovoltaic power generation is quickly solved by equation solving and fast iteration in the phase domain or sequence domain. The current calculation method of the distribution network containing large-scale high-proportion distributed power generation access is as follows:

[0166] Among them, the fault equivalent circuit of the distribution network is decomposed into a normal component network and a fault component network for the convenience of analysis and calculation;

[0167] Furthermore, when performing short-circuit calculation, the initial value of iteration is determined first. For distributed power sources, the rated output current is used as the initial value of iteration, while the injection current of the system power source remains unchanged;

[0168] Furthermore, according to the equivalent circuit of the distribution network, the node voltage equations of the normal component network and the fault component network are listed to clarify the relationship between current and voltage, laying the foundation for subsequent calculations;

[0169] Furthermore, the fault current is calculated by the established equation, and the fault component node voltage is obtained based on the self-impedance of the fault point and the node voltage of the fault point in the normal component network;

[0170] Furthermore, the voltage of each node after the short circuit is the superposition of the normal component and the fault component to ensure the accuracy of the calculation;

[0171] Furthermore, an iteration criterion is set to judge the convergence of the iteration process, thereby ensuring the reliability of the final result;

[0172] Through the above steps, the short-circuit current of the distribution network containing photovoltaic power sources under different fault types can be quickly solved, thereby improving the fault handling capability and reliability of the distribution network.

[0173] In an optional embodiment, the initial value of the iteration is determined preferentially when performing the short-circuit calculation. For the distributed power source, the rated output current is used as the initial value of the iteration, and the injection current of the system power source remains unchanged, which is:

[0174] E S / Z S (#16)

[0175] Among them, E S is the phase electromotive force of the system equivalent power supply, Z S It is the impedance between the protection installation and the equivalent power supply of the system behind it. This formula is used to calculate the short-circuit current when a short-circuit fault occurs in the power system. By calculating the short-circuit current, an appropriate action setting value can be set for the relay protection device, which ensures that when a fault occurs, the protection device can cut off the fault current in time, thereby preventing equipment damage and power system collapse;

[0176] Furthermore, the node voltage equations of the normal component network and the fault component network of the distribution network are written according to the equivalent circuit of the distribution network as follows:

[0177]

[0178] It should be noted that the significance of this equation is to gradually approach the current distribution of each node under normal conditions through iterative calculation. In the nth iteration, the current change of the kth node in the fault component network should be close to zero. This means that in the iterative process, when the current change is less than a certain set threshold, it can be considered to have converged and reached a stable state. By setting the iterative criterion, it is determined whether the iterative calculation can be stopped, ensuring that the current distribution under the fault state can be found quickly and accurately when calculating the short-circuit current, and then the subsequent protection setting and system analysis can be carried out. Therefore, iterative calculation and convergence criteria help engineers understand and predict the current behavior under fault conditions, so as to carry out effective system protection design.

[0179]

[0180] Furthermore, the node current is calculated based on the current of the previous iteration and the impedance of the node in each iteration. Through continuous iteration, the current value will gradually tend to a stable value, reflecting the current distribution of the system under normal operation. By judging whether the current converges, engineers can efficiently find the current distribution under fault conditions, avoid unnecessary calculations, and improve calculation efficiency.

[0181] Furthermore, by establishing the node voltage equation, the relationship between current and voltage can be made clear, which is convenient for subsequent calculations;

[0182] Where i represents the number of nodes; n represents the number of iterations; represents the injected current of each node in the normal component network at the nth iteration; Z represents the node impedance matrix of the network; represents the normal component network node voltage obtained at the nth iteration; represents the current of each node in the fault component network at the nth iteration; represents the fault component node voltage obtained at the nth iteration; Indicates fault current;

[0183] In an optional embodiment, the fault current is:

[0184]

[0185] It should be noted that the above formula reflects how the node voltage is affected by the previous iteration results and the current injection current changes during the iteration process by comprehensively considering the changes in node voltage and injection current. It can more accurately simulate the dynamic behavior of the power system under fault conditions. In the short-circuit analysis of the power system, accurate calculation of the node voltage changes is crucial to evaluating the stability and reliability of the system. Therefore, the above formula also provides basic data for subsequent fault current calculations and protection setting settings.

[0186] In the formula, Z ff is the fault point self-impedance; is the node voltage at the fault point after the n+1th iteration in the normal component network. The node voltage of the fault component can be obtained from the above formula. The voltage of each node after short circuit is equal to the superposition of the normal component and the fault component:

[0187]

[0188] It should be noted that this formula is used to calculate the voltage of node U in the n+1th iteration. It updates the node voltage through the combined influence of the current node voltage and the fault current. The form of this formula shows that the update of the node voltage is a dynamic process, which depends on the voltage and current values ​​at the previous moment. This dynamic adjustment mechanism helps to gradually converge to a stable voltage value during the iteration process;

[0189] Furthermore, by combining the node voltage, fault current and injection current, a method for updating the node voltage is provided. The above formula helps to accurately simulate the behavior of the power system under fault conditions, provides basic data for fault detection and protection device setting, and ensures the safety and reliability of the power system;

[0190] The calculation of node voltage change and the iterative criterion are:

[0191]

[0192] By calculating the change in node voltage, the voltage fluctuation of the power system in different iterations can be monitored in real time. The value of ε gradually decreases, indicating that the node voltage tends to be stable during the iteration process. Otherwise, it may mean that the system is still undergoing major changes or has failed to converge. By calculating the change in node voltage, it provides an important basis for dynamic monitoring, convergence judgment and fault analysis.

[0193] From the above formula, we can see that the entire iterative process can be described as:

[0194]

[0195] It should be noted that the above formula is used to calculate the relative voltage change of node U in the n+1th iteration: It represents the change between the current node voltage and the node voltage of the previous iteration, relative to the ratio of the previous voltage. By standardizing the voltage change, the formula provides a dimensionless way to evaluate the relative size of the voltage change. Calculating the relative change can help determine the convergence of the iteration process. If the relative change gradually decreases, it means that the node voltage is gradually stabilizing. Otherwise, it may indicate that the system is still undergoing major changes. In power system fault analysis, the relative change can reflect the recovery of the node voltage after a fault occurs. By monitoring the relative change, the system's recovery ability and response speed after a fault can be evaluated.

[0196] In the embodiment of the present application, through iterative calculation, the voltage and current can be dynamically adjusted according to the actual operating conditions to improve the reliability of the distribution network, and the superposition method of normal components and fault components is used to make the short-circuit calculation more accurate, which can effectively cope with the complexity brought by the access of distributed power sources. In the specific use process, through real-time calculation and monitoring, faults can be discovered and handled in time, and by analyzing the short-circuit calculation results, the configuration of the distribution network can be effectively optimized, achieving the purpose of quickly extracting fault characteristics, thereby ensuring the use of the device.

[0197] It should be noted that the fault current specifically includes:

[0198] According to the analysis of power system short circuit, without considering the distributed capacitance and distributed leakage conductance of the line, when the power supply electromotive force is constant, the magnitude of the short-circuit current depends on the fault type and the total impedance between the short-circuit point and the power supply, which can generally be expressed as:

[0199]

[0200] In the formula, K k is the fault type coefficient. If it is assumed that the negative sequence and positive sequence impedances of the system are equal, then at the moment of short circuit, the two-phase short-circuit current is a factor of the three-phase short-circuit current. times, so for three-phase short circuit K k =1, for two-phase short circuit

[0201] Among them, in the power system, the size of the short-circuit current directly affects the setting of the protection device and the safety of the power grid. The formula can clearly define the relationship between the short-circuit current and the fault type, and the total impedance between the short-circuit point and the power supply. According to the short-circuit type, such as three-phase short circuit and two-phase short circuit, the short-circuit current can be calculated to help engineers choose the appropriate protection scheme.

[0202] is the phase electromotive force of the system equivalent power supply; Z s To protect the impedance between the installation location and the equivalent power supply of the system behind, this impedance will change with the operation mode of the system; Z k To protect the impedance between the installation location and the short-circuit point, Z L is the impedance of the entire length of the protected line, β is Z k With Z L Ratio It represents the ratio of the distance from the fault point to the total length of the line, 0≤β≤1;

[0203] Among them, the action setting value of the relay protection device is set according to the calculated short-circuit current to ensure that the fault current can be cut off in time when a fault occurs to protect the safety of the equipment. In the actual use process, engineers can adjust the parameters of the protection device according to the fault current and the set value, such as time delay, action current, etc., to ensure that the protection device can quickly and effectively cut off the fault when a fault occurs.

[0204] When a three-phase short circuit occurs at the end of the line, the short-circuit current calculation method is:

[0205]

[0206] It should be noted that this formula is used to calculate the current at node k in the case of a three-phase short circuit. The formula emphasizes the key role of impedance in current calculation. The size of impedance will directly affect the size of the short-circuit current, and thus affect the stability and protection strategy of the system. The formula also provides a basis for fault analysis, which can help engineers evaluate the response of the power system in the case of a three-phase short circuit, identify potential fault points, and formulate corresponding treatment measures;

[0207] When a two-phase short circuit occurs at the end of the line, the short-circuit current is:

[0208]

[0209] It should be noted that two-phase short circuit is a type of fault in the power system. Understanding its current characteristics helps improve the stability of the system. This formula provides a basis for fault analysis and can help engineers evaluate the response of the power system in the case of two-phase short circuit, identify potential fault points, and formulate corresponding treatment measures.

[0210] The above two formulas ensure a comprehensive analysis of fault types in the construction of distribution networks and provide a basis for current calculation. The calculation of short-circuit current is the key to designing power system protection devices. By analyzing the short-circuit current, the stability of the power system under fault conditions can be evaluated and potential safety hazards can be identified.

[0211] It should be noted that by reasonably calculating the short-circuit current and setting the corresponding protection setting, equipment damage and power system collapse can be effectively prevented, and through precise setting, the probability of false operation and refusal of the protection device can be reduced, and the reliability of the power system can be improved. Designing according to this method can optimize the design and resource allocation of the power system and improve the overall operating efficiency of the scheme.

[0212] In an optional embodiment, the fixed value within the initial setting calculation range is set and calculated, specifically including:

[0213] Define the operation mode and operation setting. The operation mode includes normal operation state, fault state, load switching state and equipment maintenance state. The operation customization includes rated current, rated voltage, compound current and short-circuit current.

[0214] Among them, when the equipment is in a stable operating environment, the protection system should avoid unnecessary tripping actions, and the setting value should ensure the stable operation of the system without affecting the continuous supply of power loads. When a system fault occurs, the protection device needs to respond quickly to isolate the faulty part and prevent the fault from expanding. At this time, a more sensitive setting value needs to be set to quickly cut off the power supply. When the grid load is adjusted or the equipment is started and stopped, the protection system needs to consider possible overload or transient conditions. Therefore, the setting value must be able to adapt to these changes to avoid false operations. When the equipment is overhauled or maintained, the protection system may need to adjust the setting parameters to avoid the protection device from misjudging it as a fault and to avoid triggering unnecessary power outages during maintenance.

[0215] Furthermore, the setting method is selected. The overcurrent protection setting method is used, and the action current is set to 1.2 times the rated current, and the delay is set to 0.2 seconds. The quick-break protection setting method is used, and the action time is set to 50 milliseconds, and the current value is set to 1.5 times the short-circuit current. The differential protection setting method is used, and it is set to 5% to 10% of the rated current.

[0216] Among them, the action current is set to 1.2 times the rated current, which means that the protection system will act when the current exceeds 1.2 times the rated value. This setting can prevent overload faults and protect the equipment from damage. The delay is set to 0.2 seconds, which can avoid false operations caused by temporary current fluctuations in the system, while ensuring more robust protection behavior. It should be noted that the action time is set to 50 milliseconds, which is a fast response to short-circuit current. Quick-break protection can effectively prevent equipment damage caused by short circuits, and the current is set to 1.5 times the short-circuit current, which can effectively ensure that the protection device can cut off the power supply in time when a serious short circuit occurs. The differential protection is used to detect the current difference between two locations. It is usually used for the protection of equipment such as transformers and generators. The current is set to 5% to 10% of the rated current, which can respond to asymmetric faults within the system in time to avoid equipment damage.

[0217] Furthermore, the setting calculation is carried out, and the relevant parameters of the distribution network are collected first, including the rated capacity of the main transformer, line impedance, load conditions and historical fault data, and input, and then the action current to be set is calculated to ensure that it does not act during normal operation and can cut off the power supply in case of a fault, and the delay is calculated, and the fault type is matched by the current short-circuit condition. The fault type includes three-phase short-circuit and two-phase short-circuit. According to the matching of the fault type, the corresponding treatment measures are quickly formulated, and the matching equipment characteristics are retrieved. At the same time, the action time and current value of the quick-break protection are calculated, and finally the differential current is calculated;

[0218] Furthermore, the analysis results are verified, the calculated set values ​​to be set are analyzed, fault tests are simulated, the validity of the set values ​​is verified, and the set values ​​are retrospectively analyzed through historical fault data, the calculated set values ​​are recorded and output, and a detailed setting report is formed;

[0219] Furthermore, in later maintenance, the setting values ​​are reviewed and adjusted regularly, and the setting calculations are re-performed when major equipment replacement, system expansion or structural changes occur;

[0220] It should be noted that by optimizing quick-break protection and overcurrent protection, the system can respond to faults quickly, isolate the fault area, and reduce the impact of faults on the power system. Regular setting reviews and system optimization can ensure that the protection system always adapts to the grid environment and equipment changes, thereby improving the overall reliability and safety of the power system. Through the above process, the power protection system can not only achieve accurate fault detection and isolation, but also maintain stable and reliable operation in a changing grid environment, thereby ensuring the safety and continuity of power supply.

[0221] In summary, the present invention proposes a method for setting a distribution network protection constant value in a whole-county photovoltaic scenario, obtaining a first target parameter and a second target parameter of a first target distribution network; establishing a second target distribution network model, the second target distribution network model is a simulation model of the first target distribution network after connecting to a distributed power source; presetting a first optimization algorithm, optimizing the second target distribution network model based on the first optimization algorithm; and setting a distribution network protection constant value based on the optimized second target distribution network model in combination with the first setting strategy. The quantitative calculation method is applied to the actual distribution network, and its effectiveness and accuracy are verified through simulation experiments and field tests, which not only verifies the feasibility of the quantitative calculation method, but also provides strong support for its promotion and application in actual projects. Therefore, through the setting of this scheme, fault characteristics can be extracted quickly and accurately, ensuring the safety of the supporting use of the scheme.

[0222] Example 2

[0223] In an alternative embodiment, the design is as follows Figure 2 , 3The diagram of the normal component network and the fault component network when the distribution network containing the entire county photovoltaic system fails, and the short-circuit diagram of the feeder line end of the 10kV distribution network are shown;

[0224] Figure 2 The left side shows a circuit diagram that contains an active network and a current source. An active network is a portion of a circuit that contains an independent power source (such as a battery or generator). It is usually composed of components such as resistors, capacitors, inductors, and power sources. In circuit analysis, active networks are often used to describe the portion of a circuit that contains a power source, which can be a voltage source or a current source. Current sources are used to simulate current sources in real circuits, such as batteries, generators, or signal sources. The direction and magnitude of the current in the current source are known in circuit analysis and can be used to calculate the voltage and current of other components in the circuit.

[0225] Figure 2 The diagram on the right shows a circuit diagram that contains a passive network and a current source. A passive network is a circuit part that does not contain any independent power source (such as a battery or generator), and is usually composed of components such as resistors, capacitors, and inductors. A current source is a component that provides a constant current, marked as Indicates that it provides a current in the opposite direction to the direction marked in the figure. In circuit analysis, passive networks are usually used to describe characteristics such as signal transmission, filtering or impedance matching. Current sources are used to simulate current sources in actual circuits, such as batteries, generators or signal sources. The current direction and magnitude of the current source are known in circuit analysis and can be used to calculate the voltage and current of other components in the circuit. The current source in the figure is marked as This means that it provides a current in the opposite direction to the direction marked in the diagram. This notation is common in circuit analysis and is used to make the direction of current clear.

[0226] Figure 3 Source (E): The symbol on the left side of the diagram represents the source, usually a generator or substation, that provides electrical energy to the power system. Impedance (Z S / Z T ): The box to the right of the power supply represents the internal impedance of the power supply. This impedance reflects the internal resistance and reactance of the power supply when providing current. Switches (A and B): There are two switches in the figure, marked A and B. These switches are used to control the on and off of the circuit, for example, to disconnect the circuit to protect the system in the event of a fault. Current (I CB2 and ICB1 ): Two current directions are marked in the figure, through switches A and B. These currents represent the current flowing at different locations and are very important for fault detection and protection system design. Impedance (Z AB and Z Bf ): Impedance Z between switches A and B AB and the impedance Z between switch B and the fault pointBf Represents the impedance of the line or equipment. These impedances affect the distribution of current and the current path during a fault. Fault point (f): The symbol on the right side of the figure represents the fault point, which is usually a short circuit or ground fault. The location and type of the fault point are critical to the design of the protection system. Current direction: The direction of the current is marked on the figure, which is very important for understanding the flow path of the current during a fault. The direction of current is usually from the source to the load or fault point. Figure 3 It is usually used to analyze fault conditions in power systems, such as short circuit faults, and to design corresponding protection systems, such as relay protection devices. By analyzing the changes in current and voltage, the location and type of the fault can be determined, and corresponding protection measures can be taken.

[0227] Example 3

[0228] This embodiment also provides a distribution network protection setting value setting system in a whole-county photovoltaic scenario, including:

[0229] A data acquisition module, used to acquire a first target parameter and a second target parameter of a first target distribution network;

[0230] A model building module, used to build a second target distribution network model, where the second target distribution network model is a simulation model of the first target distribution network after the distributed power source is connected;

[0231] An optimization module, used for presetting a first optimization algorithm and optimizing a second target distribution network model based on the first optimization algorithm;

[0232] The setting module is used to set the distribution network protection constant value based on the optimized second target distribution network model in combination with the first setting strategy.

[0233] In a preferred embodiment, it can be designed as follows Figure 4 The specific system architecture shown,

[0234] The data collection submodule is used to collect geographical information, load data and existing facility parameters of the distribution network area in a priority manner;

[0235] The data preprocessing submodule is used to clean, organize and standardize the collected data;

[0236] The model building modules include:

[0237] The distribution network model construction submodule is used to build the distribution network topology according to the collected parameters;

[0238] The load forecasting model submodule is used to classify, analyze and forecast the load;

[0239] The optimization configuration modules include:

[0240] The access mode design submodule is used to evaluate the impact of distributed generation on the distribution network and design the grid-connected control strategy;

[0241] Particle swarm optimization algorithm submodule, used for optimizing the configuration calculation of distributed power grid connection;

[0242] The dynamic simulation module includes:

[0243] Fault simulation submodule, used to simulate normal operation, load mutation and fault occurrence;

[0244] The sensitivity analysis submodule is used to analyze the impact of sensitivity parameters on the performance of the distribution network.

[0245] The fault analysis module includes:

[0246] Fault feature extraction submodule, used to extract fault features and output fault analysis report;

[0247] The fixed value setting module includes:

[0248] The fixed value calculation submodule is used to perform setting calculation on the fixed value within the initial setting calculation range;

[0249] Result output submodule, used to generate setting result report and support data export function;

[0250] The UI interface module provides an operation interface, supports data input, model setting, simulation operation and result display, and has data visualization function;

[0251] The modules interact with each other through standardized interfaces to ensure the efficiency and scalability of the system.

[0252] The system supports input and output of multiple data formats, making it easy to integrate with other systems.

[0253] In this embodiment, firstly, geographic information, load data and existing facility parameters are collected from the distribution network area through the data collection module, wherein the data sources include GIS tools, historical electricity consumption data, equipment manuals, etc., and then the collected data is cleaned, sorted and standardized through the data preprocessing module to ensure the accuracy and consistency of the data. At this time, the system builds a distribution network model containing distributed power sources in the whole county based on the collected data. The model includes the topological structure of the distribution network, the parameters of each node and line, etc. In this model, the access mode of the distributed power source is designed through the optimization configuration module to evaluate its impact on the distribution network. At the same time, the load prediction model will analyze the historical load data, identify the peak load and valley load periods, and establish a prediction model for the load change trend, and use the particle swarm optimization algorithm to perform the optimization configuration calculation of the distributed power grid connection, wherein the access capacity of each distributed power source is calculated to ensure that the power can be stably provided during the peak load period, and the dynamic simulation module simulates the normal operation, load mutation and fault conditions of the distribution network. By setting different simulation scenarios, the system can monitor the changes of parameters such as voltage, frequency and power flow in real time. In this process, the sensitivity analysis module will analyze the impact of key parameters on the performance of the distribution network to help identify potential risks;

[0254] In this link, if a failure occurs in the operation of the system, the fault analysis module will extract the fault characteristics, analyze the voltage and fault current of the fault component node, and output a fault analysis report to provide fault location suggestions. Finally, it should be noted that the constant setting module performs setting calculations on the constants within the initial setting calculation range. This module generates a setting result report based on the simulation results and fault analysis to ensure the accuracy and reliability of the distribution network protection constants.

[0255] The above-mentioned unit modules may be embedded in or independent of a processor in a computer device in the form of hardware, or may be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to the above-mentioned modules.

[0256] This embodiment also provides a computer device, which may be a terminal, and its internal structure diagram may be as shown in FIG. Figure 5As shown. The computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. When the computer program is executed by the processor, a distribution network protection constant value setting method in a whole-county photovoltaic scenario is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a button, trackball or touchpad set on the computer device housing, or an external keyboard, touchpad or mouse.

[0257] This embodiment further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0258] Obtaining a first target parameter and a second target parameter of a first target distribution network;

[0259] Establishing a second target distribution network model, where the second target distribution network model is a simulation model of the first target distribution network after the distributed power source is connected;

[0260] A first optimization algorithm is preset, and a second target distribution network model is optimized based on the first optimization algorithm;

[0261] Based on the optimized second target distribution network model and combined with the first setting strategy, the distribution network protection constant value setting is performed.

[0262] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

[0263] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of complete hardware embodiments, complete software embodiments, or embodiments in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code. The scheme in the embodiments of the present application can be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0264] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0265] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0266] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0267] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0268] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A method for setting the fixed value of distribution network protection in a whole-county photovoltaic scenario, characterized in that: include: Obtaining a first target parameter and a second target parameter of a first target distribution network; Establishing a second target distribution network model, where the second target distribution network model is a simulation model of the first target distribution network after the distributed power source is connected; Preset a first optimization algorithm, and optimize the second target distribution network model based on the first optimization algorithm; Based on the optimized second target distribution network model and combined with the first setting strategy, the distribution network protection constant value setting is performed.

2. The method for setting the fixed value of distribution network protection in the whole-county photovoltaic scenario as claimed in claim 1 is characterized in that: The preset first optimization algorithm and optimizing the second target distribution network model based on the first optimization algorithm include: Establishing a first objective function according to the user's optimization goal; Optimizing a first objective function according to the first optimization algorithm; The target configuration parameters of the second target distribution network model are obtained according to the optimized first objective function.

3. The method for setting the fixed value of distribution network protection in the whole-county photovoltaic scenario as claimed in claim 2 is characterized in that: The method of performing distribution network protection setting value setting based on the optimized second target distribution network model and in combination with the first setting strategy includes: Optimizing a second target distribution network model according to the target configuration parameters; Acquire a third target parameter based on the optimized second target distribution network model; The distribution network protection constant value is set according to the third target parameter in combination with the first setting strategy.

4. The method for setting the fixed value of distribution network protection in the whole-county photovoltaic scenario as claimed in claim 3 is characterized in that: The first setting strategy includes: Acquiring a third target parameter, and establishing a first tuning operation based on the third target parameter; Obtaining a fourth target parameter obtained after the third target parameter is subjected to the first setting operation; The first setting operation is any operation for solving a setting value.

5. The method for setting the fixed value of distribution network protection in the whole-county photovoltaic scenario as claimed in claim 4 is characterized in that: The establishing of the first objective function according to the user optimization objective comprises: The user optimization target is an optimization target selected by the user for the second target distribution network model; Establishing a first objective function for the user optimization target according to the user optimization target; The first objective function at least includes any parameter function that can describe the entire second target power distribution network.

6. The method for setting the fixed value of distribution network protection in the whole-county photovoltaic scenario as claimed in claim 5, characterized in that: The establishing of the second target distribution network model comprises: Determine the grid connection method and target access point of distributed power sources; According to the grid connection access mode and the target access point, a second target distribution network model is established in combination with the first target parameter and the second target parameter; A simulation test is performed on the second target distribution network model.

7. The method for setting the fixed value of distribution network protection in the whole-county photovoltaic scenario as claimed in claim 6, characterized in that: The third target parameter includes at least the second target distribution network model operation mode and operation constant.

8. A distribution network protection setting value setting system in a whole-county photovoltaic scenario, characterized in that: include: A data acquisition module, used to acquire a first target parameter and a second target parameter of a first target distribution network; A model building module, used to build a second target distribution network model, where the second target distribution network model is a simulation model of the first target distribution network after the distributed power source is connected; An optimization module, configured to preset a first optimization algorithm and optimize the second target distribution network model based on the first optimization algorithm; The setting module is used to set the distribution network protection constant value based on the optimized second target distribution network model in combination with the first setting strategy.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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