Solutions and related devices for power grid constraint violation events

Abstract

The present invention discloses a method for solving power grid constraint violation events and a related device. The method includes: obtaining target power grid line parameters corresponding to n nodes in a target power grid, determining m constraint violation nodes based on the target power grid line parameters, determining k allocation methods of a constraint violation event resolution device among the m constraint violation nodes, determining k constraint violation event resolution capability values ​​corresponding to the k allocation methods, determining the maximum constraint violation event resolution capability value among the k constraint violation event resolution capability values, determining the allocation method corresponding to the maximum constraint violation event resolution capability value, and obtaining a target allocation method. The target allocation method is used to resolve the constraint violation events in the m constraint violation nodes. The embodiments of the present application improve the cost-effectiveness of resolving power grid constraint violation events.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid planning, and in particular to a solution to power grid constraint violation events and a related device. Background Art

[0002] With the rapid development of modern society and the economy, electricity demand continues to rise, and power grids are expanding and becoming increasingly complex. Power grids face numerous challenges during operation, among which constraint violations are a key factor affecting their safe and stable operation. While recent advances in power system analysis technology have made it possible to address constraint violations in power grids, the cost-effectiveness of addressing these issues remains low. Summary of the Invention

[0003] The embodiments of the present application provide a solution to a power grid constraint violation event, thereby improving the cost-effectiveness of solving the power grid constraint violation event.

[0004] In a first aspect, embodiments of the present application provide a solution to a grid constraint violation event, including:

[0005] Obtain the grid line parameters corresponding to n nodes in the target grid to obtain the target grid line parameters; n is a positive integer;

[0006] Determine, based on the target power grid line parameters, nodes where constraint violation events occur among n nodes, and obtain m constraint violation nodes; m is an integer less than or equal to n;

[0007] Determining a distribution method of constraint violation event resolution devices among m constraint violation nodes using an AC power flow model to obtain k distribution methods; the constraint violation event resolution device is any one of the following: an infrastructure upgrade device, a voltage regulator, and an energy storage device; each constraint violation node corresponds to one constraint violation event resolution device, and k is an integer greater than or equal to 2;

[0008] determining a constraint violation event resolution capability value of a constraint violation event resolution device corresponding to each of the k allocation methods to resolve the corresponding constraint violation event, thereby obtaining k constraint violation event resolution capability values;

[0009] determining a maximum constraint violation event resolution capability value among the k constraint violation event resolution capability values;

[0010] An allocation method corresponding to a maximum constraint violation event resolution capability value is determined to obtain a target allocation method; the target allocation method is used to resolve the constraint violation events in the m constraint violation nodes.

[0011] In a second aspect, an embodiment of the present application provides a device for resolving a power grid constraint violation event, the device for resolving a power grid constraint violation event comprising: an acquisition unit and a processing unit;

[0012] An acquisition unit is used to acquire the grid line parameters corresponding to n nodes in the target grid to obtain the target grid line parameters; n is a positive integer;

[0013] a processing unit, configured to determine, based on the target power grid line parameters, nodes where constraint violation events occur among the n nodes, and obtain m constraint violation nodes; m is an integer less than or equal to n;

[0014] Determining a distribution method of constraint violation event resolution devices among m constraint violation nodes using an AC power flow model to obtain k distribution methods; the constraint violation event resolution device is any one of the following: an infrastructure upgrade device, a voltage regulator, and an energy storage device; each constraint violation node corresponds to one constraint violation event resolution device, and k is an integer greater than or equal to 2;

[0015] determining a constraint violation event resolution capability value of a constraint violation event resolution device corresponding to each of the k allocation methods to resolve the corresponding constraint violation event, thereby obtaining k constraint violation event resolution capability values;

[0016] determining a maximum constraint violation event resolution capability value among the k constraint violation event resolution capability values;

[0017] An allocation method corresponding to a maximum constraint violation event resolution capability value is determined to obtain a target allocation method; the target allocation method is used to resolve the constraint violation events in the m constraint violation nodes.

[0018] In a third aspect, an embodiment of the present application provides an electronic device comprising: a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor so that the electronic device performs the method of the first aspect.

[0019] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the method of the first aspect.

[0020] In a fifth aspect, an embodiment of the present application provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, so that a computer executes the method of the first aspect.

[0021] The implementation of the present application has the following beneficial effects:

[0022] It can be seen that the solution to the power grid constraint violation event described in the embodiment of the present application obtains the power grid line parameters corresponding to n nodes in the target power grid to obtain the target power grid line parameters, determines the node where the constraint violation event occurs among the n nodes based on the target power grid line parameters to obtain m constraint violation nodes, determines the distribution method of the constraint violation event resolution device among the m constraint violation nodes through the AC power flow model to obtain k distribution methods, and the constraint violation event resolution device is any one of the following: an infrastructure upgrade device, a voltage regulator and an energy storage device, each constraint violation node corresponds to a constraint violation event resolution device, determines the constraint violation event resolution capability value of the constraint violation event resolution device corresponding to each distribution method in the k distribution methods to resolve the corresponding constraint violation event, obtains k constraint violation event resolution capability values, determines the maximum constraint violation event resolution capability value among the k constraint violation event resolution capability values, determines the distribution method corresponding to the maximum constraint violation event resolution capability value, and obtains the target distribution method; the target distribution method is used to resolve the constraint violation events in the m constraint violation nodes, thereby improving the cost-effectiveness of resolving power grid constraint violation events. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the implementation methods or background technologies of the present application, the drawings required for use in the implementation methods or background technologies of the present application will be described below.

[0024] Figure 1 This is a flow chart of a solution to a power grid constraint violation event provided by an embodiment of the present application;

[0025] Figure 2 This is a flow chart of determining k constraint violation event resolution capability values ​​provided by an embodiment of the present application;

[0026] Figure 3 This is a schematic structural diagram of a device for resolving power grid constraint violation events provided by an embodiment of the present application;

[0027] Figure 4 It is a structural diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0028] In order to enable those skilled in the art to better understand the present invention, the following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0029] The terms "first," "second," and the like in the specification and claims of this application and the accompanying drawings are used to distinguish between different objects, not to describe a particular order. Furthermore, the terms "including," "having," and any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or elements is not limited to the listed steps or elements but may optionally include steps or elements not listed, or may optionally include other steps or elements inherent to the process, method, product, or apparatus.

[0030] Reference herein to an "embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the present application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it refer to independent or alternative embodiments that are mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0031] See also Figure 1 , Figure 1 This is a flowchart of a solution to a power grid constraint violation event provided by an embodiment of the present application, including but not limited to the following steps:

[0032] S101: Obtain grid line parameters corresponding to n nodes in a target grid to obtain target grid line parameters.

[0033] In this embodiment, n is a positive integer. The target grid refers to the specific scope of the power network being studied or operated. The target grid includes numerous nodes (such as substations, distribution rooms, user access points, etc.) and the lines connecting these nodes (transmission lines, distribution lines, etc.). Grid line parameters include voltage parameters, power flow parameters, physical characteristic parameters, and load characteristic parameters. Specifically, the target grid includes n nodes, each of which has corresponding grid line parameters. Specifically, each node has a corresponding rated voltage value, which is the voltage standard expected by the node during normal grid operation. Each node has a corresponding rated power, which specifies the upper limit of power that the node can safely and stably transmit or distribute, including active power and reactive power. For example, the rated active power of a substation node may be determined based on the capacity of the transformer and the current carrying capacity of the line, which helps determine whether power flow congestion will occur. Physical characteristic parameters include line impedance, line length, and connection relationships between nodes. Load characteristic parameters include load type, load capacity, and load variation patterns. Grid line parameters also include the actual voltage and actual power flow corresponding to each of the n nodes at different time periods.

[0034] S102: Determine nodes where constraint violation events occur among n nodes based on target power grid line parameters, and obtain m constraint violation nodes.

[0035] In this embodiment, m is an integer less than or equal to n. Constraint violation events include overvoltage events and power flow congestion events. First, the rated voltage of each node is obtained, which represents the normal operating voltage range specified in the grid design. The actual voltage is then extracted from the target grid line parameters. If the actual voltage corresponding to a node is greater than the rated voltage, an overvoltage event is determined for that node. For each node, the rated power transmission capacity of its connecting line is determined. The actual power flow of the node is then obtained from the target grid line parameters. If the actual power flow of a node is greater than the rated power transmission capacity, a power flow congestion event is determined for that node. This congestion can cause line overload, leading to heating and insulation damage, seriously impacting the safe operation of the grid. For each of the n nodes, a determination is made to determine whether the actual voltage is greater than the rated voltage and whether the actual power flow is greater than the rated power transmission capacity. Whenever a constraint violation is detected for a node, it is recorded. Finally, the number of all constraint-violating nodes is counted, resulting in m constraint-violating nodes.

[0036] S103: Determine the allocation method of the constraint violation event resolution device among the m constraint violation nodes through the AC power flow model to obtain k allocation methods.

[0037] In this embodiment, the constraint violation event resolution device is any one of the following: an infrastructure upgrade device, a voltage regulator, and an energy storage device. Each constraint violation node corresponds to a constraint violation event resolution device, and k is an integer greater than or equal to 2.

[0038] It should be noted that infrastructure upgrades can resolve congestion issues. For nodes with power flow congestion constraints, consider upgrading the line (such as increasing the conductor cross-sectional area) or replacing a large-capacity transformer. The new current-carrying capacity of each node after using the infrastructure upgrade can be calculated using the following formula:

[0039]

[0040] Where t is the current time, The new current carrying capacity of the current node after using the infrastructure upgrade device, is the percentage of the rated power flow to the actual power flow of the current node, is the actual power flow of the current node, and l is the line corresponding to the current node.

[0041] The voltage regulator can adjust the voltage. For nodes with overvoltage problems, the voltage regulator is placed at the node and the voltage is reduced according to its regulation characteristics (such as being able to reduce the voltage within a certain range).

[0042] Installing energy storage devices at nodes next to congested lines can solve local congestion problems. Since nodes may be connected to one or more congested lines, the maximum charge and discharge rating required to solve local congestion on the line can be calculated by the maximum difference between the rating of the new conductor and the original conductor. The calculation formula is:

[0043]

[0044] in, The maximum charge and discharge rating required to resolve local congestion on the line, is the new conductor rating, Rated for original conductors.

[0045] In this implementation, the AC power flow model is an important tool for analyzing the distribution of voltage and power (active and reactive power) across power grid nodes and lines. It is based on Kirchhoff's laws (including the current law and the voltage law) and the electrical characteristics of power system components (such as generators, transformers, and lines). Its core is a set of nonlinear equations that describe the relationship between node-injected power and node voltage and phase angle, as well as the relationship between voltage and current at both ends of a line. Based on the target grid's topology (node ​​connectivity) and line parameters (such as resistance, reactance, and transformer ratio), the AC power flow model is used to construct a mathematical model of the grid. The current voltage, power, and other parameters of m constraint-violating nodes are input into the model as initial conditions. Furthermore, the basic parameter ranges of the constraint-violation event resolution devices (infrastructure upgrade devices, voltage regulators, and energy storage devices) must be determined. For constraint violation nodes with power flow congestion, consider resolving the problem by upgrading the lines (such as increasing the cross-sectional area of ​​the conductor) or replacing large-capacity transformers. For nodes with voltage problems (overvoltage or undervoltage), consider allocating voltage regulators and placing them at the nodes. For nodes with large power fluctuations (which may cause power flow congestion or voltage problems), consider allocating energy storage devices. By allocating the constraint violation event resolution device multiple times, k different allocation methods are generated. Each allocation method represents a solution for arranging the constraint violation event resolution device on m constraint violation nodes.

[0046] It should be explained that in practical applications, a combination of multiple devices can also be considered for allocation. For example, for a node with both power flow congestion and voltage problems, infrastructure upgrade devices and voltage regulators, or infrastructure upgrade devices and energy storage devices can be allocated at the same time. The AC power flow model can be used to simulate the impact of these combined devices working together on the grid power flow and voltage. The line can be upgraded first to solve some power flow congestion problems, and then the voltage regulator can be used to fine-tune the point voltage, or the energy storage device can be used to smooth out power fluctuations to reduce line pressure and stabilize voltage.

[0047] It can be seen that the AC power flow model can accurately analyze the specific problems of each constraint violation node, such as whether the voltage deviation is too high or too low, the degree of power flow congestion, etc. Based on this detailed information, different solution devices are allocated in a targeted manner. The AC power flow model can simulate the operating status of the entire power grid. When determining the device allocation method, it not only considers the improvement of the constraint violation node itself, but also the impact on other parts of the power grid. This model-based allocation method enables the power grid to more effectively respond to constraint violation events under various complex operating conditions, reducing the risk of power outages and the possibility of damage to power grid equipment.

[0048] S104: Determine the constraint violation event resolution capability value of the constraint violation event resolution device corresponding to each of the k allocation methods to resolve the corresponding constraint violation event, and obtain k constraint violation event resolution capability values.

[0049] In this implementation, see Figure 2 , Figure 2 The flowchart of determining k constraint violation event resolution capability values ​​provided by an embodiment of the present application includes but is not limited to the following steps:

[0050] S201: Determine the technical effect value of processing the constraint violation event corresponding to each allocation method in k allocation methods to obtain k technical effect values.

[0051] In this embodiment, the constraint violation event includes an overvoltage event and a power flow congestion event.

[0052] First, determine the technical effect value of the first allocation method on each of the m constraint violation nodes to obtain m reference technical effect values. The first allocation method is any one of the k allocation methods. Exemplarily, the overvoltage duration, maximum voltage amplitude, power flow congestion duration and maximum power flow corresponding to the first constraint violation node are determined according to the target grid line parameters. The first constraint violation node is any one of the m constraint violation nodes. Then, the overvoltage duration, maximum voltage amplitude, power flow congestion duration, maximum power flow and are input into the neural network model corresponding to the first allocation method for prediction to obtain the overvoltage duration reduction rate, maximum voltage amplitude reduction rate, power flow congestion time reduction rate and maximum power flow reduction rate. Specifically, the neural network model corresponding to the first allocation method is specially constructed or trained to evaluate the performance under this allocation method. The overvoltage duration, maximum voltage amplitude, power flow congestion duration and maximum power flow extracted above are input as input data into the neural network model. The neural network model predicts the proportion of possible reduction of the overvoltage duration after the first allocation method is adopted based on the input historical data and its own training results, and obtains the overvoltage duration reduction rate; predicts the proportion of the maximum voltage amplitude that can be reduced after the first allocation method is adopted, and obtains the maximum voltage amplitude reduction rate; predicts the proportion of shortening of the power flow congestion duration after the allocation method is adopted, and obtains the power flow congestion time reduction rate; predicts the proportion of the maximum power flow that can be reduced after the allocation method is adopted, and obtains the maximum power flow reduction rate.

[0053] Exemplarily, a reference technical effect value corresponding to the first constraint violation node is determined based on the overvoltage duration reduction rate, the maximum voltage amplitude reduction rate, the power flow congestion time reduction rate, and the maximum power flow reduction rate. Exemplarily, a first reference weight corresponding to the overvoltage duration reduction rate is determined. Specifically, this may be a preset mapping relationship between the overvoltage duration reduction rate and the reference weight. Based on this mapping relationship, the first reference weight corresponding to the overvoltage duration reduction rate can be determined. Exemplarily, the line load corresponding to the first constraint violation node is obtained. Specifically, since there is a close relationship between line load and voltage in the power system, when the line load increases, the current increases, which may cause the node voltage to decrease. Conversely, when the line load decreases, the current decreases, the voltage drop decreases, and the node voltage may increase. Therefore, the line load corresponding to the first constraint violation node is obtained. Exemplarily, a first optimization factor corresponding to the line load is determined. Specifically, this may be a preset mapping relationship between the line load and the optimization factor. Based on this mapping relationship, the first optimization factor corresponding to the line load can be determined. Exemplarily, the first reference weight is optimized based on the first optimization factor to obtain a first target weight, specifically calculated using the following formula: first target weight = first reference weight × (1 + first optimization factor); the first target weight can be obtained based on the above formula. Exemplarily, a second target weight corresponding to the maximum voltage amplitude is determined based on the first target weight, where the sum of the first target weight and the second target weight is 1. Exemplarily, an overvoltage mitigation index corresponding to the first constraint violation node is determined based on the overvoltage duration reduction rate, the maximum voltage amplitude reduction rate, the first target weight, and the second target weight. Specifically, the overvoltage mitigation index corresponding to the first constraint violation node is calculated according to the following formula: overvoltage mitigation index = overvoltage duration reduction rate × first target weight + maximum voltage amplitude reduction rate × second target weight. Exemplarily, a third reference weight corresponding to the power flow congestion time reduction rate is determined, which can be a preset mapping relationship between the power flow congestion time reduction rate and the reference weight. Based on this mapping relationship, the third reference weight corresponding to the power flow congestion time reduction rate can be determined. Exemplarily, the cross-sectional area of ​​the conductor corresponding to the first constraint violation node is obtained. Specifically, the cross-sectional area of ​​the conductor is one of the key factors affecting the line resistance. Lower resistance means that under the same current, the power loss of the line is reduced, and it can withstand a larger current without overheating, thereby improving the current carrying capacity of the line. For the power flow congestion problem, the improvement of the current carrying capacity is a key factor in alleviating congestion. When the cross-sectional area of ​​the conductor increases, the line can allow more power to flow through, which enables the power to be evacuated more quickly through the line when power flow congestion occurs, thereby helping to reduce the power flow congestion time. Therefore, it is necessary to obtain the cross-sectional area of ​​the conductor corresponding to the first constraint violation node.Exemplarily, a second optimization factor corresponding to the cross-sectional area is determined. Specifically, it can be a mapping relationship between a preset cross-sectional area and an optimization factor. Based on the mapping relationship, the second optimization factor corresponding to the cross-sectional area can be determined. Exemplarily, the third reference weight is optimized based on the second optimization factor to obtain a third target weight. The specific calculation formula is as follows: third target weight = third reference weight × (1 + second optimization factor); the third target weight can be obtained according to the above formula. Exemplarily, a fourth target weight corresponding to the maximum power flow reduction rate is determined based on the third target weight, and the sum of the third target weight and the fourth target weight is 1. Exemplarily, the power flow congestion relief index corresponding to the first constraint violation node is determined based on the power flow congestion time reduction rate, the maximum power flow reduction rate, the third target weight and the fourth target weight. Specifically, the power flow congestion relief index corresponding to the first constraint violation node is calculated according to the following formula: overvoltage relief index = power flow congestion time reduction rate × third target weight + maximum power flow reduction rate × fourth target weight.

[0054] Exemplarily, the reference technical effect value corresponding to the first constraint violation node is determined based on the overvoltage relief index and the power flow congestion relief index. Specifically, the first weight corresponding to the overvoltage relief index and the second weight corresponding to the power flow congestion relief index are first determined, and the sum of the first weight and the second weight is 1. Then, the reference technical effect value is determined based on the first weight, the second weight, the overvoltage relief index and the power flow congestion relief index. The reference technical effect value is calculated specifically according to the following formula: overvoltage relief index = overvoltage relief index × first weight + power flow congestion relief index × second weight.

[0055] It can be seen that when determining the overvoltage relief index and the power flow congestion relief index, fixed weights are not simply used to integrate the various reduction rates. Instead, the weights are optimized based on actual grid parameters such as line load and conductor cross-sectional area. For the power flow congestion problem, the conductor cross-sectional area is a key factor. Adjusting the weight of the power flow congestion time reduction rate based on the cross-sectional area can better reflect the impact of the physical characteristics of the line itself on the power flow congestion relief. By separately determining the overvoltage relief index and the power flow congestion relief index, the relief of the two key aspects of voltage and power are comprehensively considered. The evaluation method based on the dynamic adjustment of actual grid parameters can better adapt to changes in the grid, timely and accurately reflect the effectiveness of technical measures under different operating conditions, and provide a more reliable basis for the stable operation and optimization adjustment of the grid.

[0056] According to the above method for determining the reference technical effect value of the first allocation method for the first constraint violation node, the technical effect value of the first allocation method for each of the m constraint violation nodes can be determined to obtain m reference technical effect values.

[0057] After obtaining m reference technical effect values, the technical effect value corresponding to the first allocation method is determined based on the m reference technical effect values. Specifically, the weight corresponding to each reference technical effect value in the m reference technical effect values ​​can be determined according to the preset mapping relationship, and then each reference technical effect value is multiplied by its corresponding weight. Finally, these values ​​are added together to determine the technical effect value corresponding to the first allocation method.

[0058] It should be noted that, according to the method for determining the technical effect value corresponding to the first allocation method, the technical effect value of the processing constraint violation event corresponding to each of the k allocation methods can be determined to obtain k technical effect values.

[0059] It can be seen that by determining the overvoltage duration, maximum voltage amplitude, power flow congestion duration and maximum power flow through the target grid line parameters, the severity of the problem of each constraint violation node can be accurately grasped. The reference technical effect value is determined based on various reduction rates, and the improvement of multiple aspects is comprehensively considered to avoid the one-sidedness of single indicator evaluation. The technical effect value corresponding to the first allocation method is determined based on m reference technical effect values, and the allocation method is evaluated as a whole. In this way, the advantages and disadvantages of different allocation methods can be compared, avoiding the situation of only focusing on some nodes and ignoring the overall effect. The evaluation method based on specific parameters and neural network prediction can timely re-evaluate the technical effect of the allocation method according to the new situation.

[0060] S202: Determine the cost value corresponding to each of the k allocation methods to obtain k cost values.

[0061] In this embodiment, for each of the k allocation methods, the costs of the above parts are calculated separately according to the specific circumstances of the infrastructure upgrade device, voltage regulator and energy storage device configured on the m constraint violation nodes, and then all costs are added together to obtain the cost value corresponding to the allocation method. Finally, the cost value corresponding to each of the k allocation methods is obtained, and k cost values ​​are obtained.

[0062] S203: Determine a constraint violation event resolution capability value corresponding to each of the k allocation methods based on the k technical effect values ​​and the k cost values, and obtain k constraint violation event resolution capability values.

[0063] In this embodiment, illustratively, a first technical effect value and a first cost value corresponding to the first allocation method are determined. The first technical effect value is the technical effect value corresponding to the first allocation method among the k technical effect values, and the first cost value is the cost value corresponding to the first allocation method among the k cost values. Then, the maximum technical effect value and the minimum technical effect value among the k technical effect values, as well as the maximum cost value and the minimum cost value among the k cost values, are determined. Then, based on the first technical effect value, the maximum technical effect value, and the minimum technical effect value, the first constraint violation event resolution capability value is determined. The specific calculation formula is as follows:

[0064]

[0065] Among them, F1 is the first constraint violation event resolution capability value, A is the first technical effect value, A max is the maximum technical effect value, A min is the minimum technical effect value.

[0066] The second constraint violation event resolution capability value is then determined based on the first cost value, the maximum cost value, and the minimum cost value. The specific calculation formula is as follows:

[0067]

[0068] Among them, F2 is the second constraint violation event resolution capability value, B is the first cost value, B max is the maximum cost value, B min is the minimum cost value.

[0069] Exemplarily, the constraint violation event resolution capability value corresponding to the first allocation method is determined based on the first constraint violation event resolution capability value and the second constraint violation event resolution capability value. Specifically, the third weight corresponding to the first constraint violation event resolution capability value and the fourth weight corresponding to the second constraint violation event resolution capability value can be first determined according to a preset mapping relationship, and the sum of the third weight and the fourth weight is 1. Then, the constraint violation event resolution capability value corresponding to the first allocation method is determined based on the first constraint violation event resolution capability value, the second constraint violation event resolution capability value, the third weight, and the fourth weight. Specifically, the reference technical effect value is calculated according to the following formula: constraint violation event resolution capability value corresponding to the first allocation method = first constraint violation event resolution capability value × third weight + second constraint violation event resolution capability value × fourth weight.

[0070] It can be seen that by determining the first technical effect value and the first cost value corresponding to the first allocation method, the two key factors of technology and economy are clearly quantified. When determining the constraint violation event resolution capability value, the maximum and minimum technical effect values ​​among the k technical effect values, as well as the maximum and minimum cost values ​​among the k cost values, are considered. This makes the evaluation of the first allocation method no longer isolated, but is considered within the scope of all possible allocation methods. Finally, the constraint violation event resolution capability value corresponding to the first allocation method is determined based on the first constraint violation event resolution capability value and the second constraint violation event resolution capability value, and the evaluation results of the two aspects of technology and cost are integrated. This comprehensive consideration avoids one-sided evaluation that only focuses on technical effects and ignores costs, or only looks at costs without considering technical feasibility.

[0071] S105: Determine the maximum constraint violation event resolution capability value among the k constraint violation event resolution capability values.

[0072] In this embodiment, for each allocation method obtained through the AC power flow model, the corresponding constraint violation event resolution capability value is calculated, that is, k constraint violation event resolution capability values. These resolution capability values ​​are a quantitative indicator that comprehensively measures the effectiveness of the allocation method in resolving corresponding constraint violation events. Its calculation usually takes into account multiple factors, such as the degree of improvement of constraint violation problems such as voltage anomalies and power flow congestion under the allocation method, and the cost required to implement the allocation method. After obtaining these k constraint violation event resolution capability values, they need to be compared to find the value with the largest value. This process can be achieved through a simple sorting algorithm or comparison logic. The purpose is to find the value that represents the strongest resolution capability among the many scheme evaluation values, so as to screen out the most advantageous allocation method.

[0073] It should be noted that the overvoltage event resolution capability and power flow congestion event resolution capability of the infrastructure upgrade device, voltage regulator, and energy storage device, respectively, for each of the m constraint violation nodes can be calculated. First, the overvoltage event resolution capability and power flow congestion event resolution capability of the infrastructure upgrade device in the constraint violation node can be calculated using the following formula:

[0074]

[0075] in, Improve the ability of infrastructure to handle overvoltage events. The ability to resolve power flow congestion events for infrastructure upgrades, is the voltage drop change value of the current node before and after using the infrastructure upgrade device, Cross-section before using the infrastructure upgrade device for the current node, Cross-section after applying the infrastructure upgrade device to the current node.

[0076] The voltage regulator's ability to resolve overvoltage events in constraint violation nodes and its ability to resolve power flow congestion events can be calculated using the following formula:

[0077]

[0078] in, The ability to handle overvoltage events for voltage regulators, The ability to resolve power flow congestion events for voltage regulators, is the voltage drop change of the current node before using the voltage regulator, ΔV nb,t is the voltage change amplitude of the node at time t, is the voltage drop change of the current node after using the voltage regulator.

[0079] The ability of the energy storage device to resolve overvoltage events in constraint violation nodes and power flow congestion events can be calculated according to the following formula:

[0080]

[0081] in, The ability to handle overvoltage events for energy storage devices, is the charge of the current node, S l,t is the power flow of the node at time t, is the power flow of the current node after using the energy storage device, The ability of energy storage devices to resolve power flow congestion events, is the voltage change difference corresponding to the current node.

[0082] After determining the infrastructure upgrade device's ability to resolve overvoltage events, the infrastructure upgrade device's ability to resolve power flow congestion events, the voltage regulator's ability to resolve overvoltage events, the voltage regulator's ability to resolve power flow congestion events, the energy storage device's ability to resolve overvoltage events in constraint violation nodes, and its ability to resolve power flow congestion events, the constraint violation event resolution capability value corresponding to each of the k allocation methods can also be determined based on the infrastructure upgrade device's ability to resolve overvoltage events, the infrastructure upgrade device's ability to resolve power flow congestion events, the voltage regulator's ability to resolve overvoltage events, the voltage regulator's ability to resolve power flow congestion events, the energy storage device's ability to resolve overvoltage events in constraint violation nodes, and its ability to resolve power flow congestion events, thereby obtaining k constraint violation event resolution capability values.

[0083] S106: Determine the allocation method corresponding to the maximum constraint violation event resolution capability value to obtain a target allocation method.

[0084] In this embodiment, a target allocation scheme is used to resolve constraint violation events in m constraint violation nodes. Since each constraint violation event resolution capability value corresponds to a specific allocation scheme, after finding the maximum constraint violation event resolution capability value, the allocation scheme corresponding to that maximum constraint violation event resolution capability value must be found to obtain the target allocation scheme. Once the target allocation scheme is determined, it becomes a specific solution for resolving constraint violation events in the m constraint violation nodes. This means that corresponding constraint violation event resolution devices (infrastructure upgrade devices, voltage regulators, or energy storage devices) must be deployed on these m nodes according to this allocation scheme.

[0085] It should be noted that in this embodiment, it is also necessary to determine the severity value corresponding to each of the m constraint violation nodes to obtain m target severity values. Exemplarily, a voltage amplitude difference is determined based on the maximum voltage amplitude and a preset voltage amplitude threshold, a power flow difference is determined based on the maximum power flow and a preset power flow threshold, and a reference severity value corresponding to the first constraint violation node is determined based on the voltage amplitude difference and the power flow difference. Specifically, a mapping relationship between a preset voltage amplitude difference and a reference severity value can be determined based on which a first reference severity value corresponding to the voltage amplitude difference is determined. Alternatively, a mapping relationship between a preset power flow difference and a reference severity value can be determined based on which a second reference severity value corresponding to the power flow difference is determined. Then, weights of the first reference severity value and the second reference severity value are determined, respectively, and then a weighted calculation is performed to obtain the reference severity value corresponding to the first constraint violation node. Exemplarily, a first adjustment parameter corresponding to the overvoltage duration and a second adjustment parameter corresponding to the power flow congestion duration are determined. Specifically, a mapping relationship between the overvoltage duration and the adjustment parameters can be preset, based on which the first adjustment parameter corresponding to the overvoltage duration can be determined. Alternatively, a mapping relationship between the power flow congestion duration and the adjustment parameters can be preset, based on which the second adjustment parameter corresponding to the power flow congestion duration can be determined. Exemplarily, a reference severity value is adjusted based on the first adjustment parameter and the second adjustment parameter to obtain a target severity value corresponding to the first constraint violation node. Specifically, the specific calculation formula is as follows: target severity value = reference severity value × (1 + first adjustment parameter) × (1 + second adjustment parameter). The target severity value can be obtained according to the above formula.

[0086] Exemplarily, the priority corresponding to each of the m constraint violation nodes is determined based on m target severity values, and m priorities are obtained. Specifically, in the power system, the higher the amplitude and the longer the duration of high-severity constraint violation events, such as overvoltage, the greater the risk of damage to the insulation system of the electrical equipment. For the case of power flow congestion, a high severity value means that the power exceeds the rated capacity of the line or equipment to a large extent and for a long time. Overvoltage or undervoltage nodes with high severity will have a greater negative impact on the voltage stability of the power grid. Therefore, the priority corresponding to each of the m constraint violation nodes is determined based on the m target severity values, and m priorities are obtained. The larger the severity value corresponding to each node in the m constraint violation nodes, the higher the priority.

[0087] It should be noted that in this embodiment, for example, it is also necessary to determine the order of resolving constraint violation events corresponding to m constraint violation nodes based on m priorities. Specifically, the priorities of the m constraint violation nodes have been determined based on factors such as the severity value of each constraint violation node. These priorities reflect the severity or importance of the constraint violation event of each node. The higher the priority, the greater the threat posed by the constraint violation event of the node to the safety, stability and normal operation of the power grid, and it needs to be handled first. According to these priorities, the m constraint violation nodes are sorted from high to low according to priority, thereby obtaining a resolution order for the constraint violation event. Exemplarily, constraint violation events in m constraint violation nodes are resolved based on a target allocation method and a constraint violation event resolution order. Specifically, the target allocation method is the optimal allocation method previously determined through a series of evaluations and screenings. It clarifies how to configure constraint violation event resolution devices (such as infrastructure upgrade devices, voltage regulators, and energy storage devices) on the constraint violation nodes to achieve the best resolution effect. However, when there are fewer constraint violation event resolution devices, it is necessary to consider resolving constraint violation events on constraint violation nodes with higher priority. This ensures that the entire resolution process takes into account the urgency and importance of different nodes, and uses the most optimized device configuration plan to resolve constraint violation problems in the power grid in a systematic and orderly manner, ultimately restoring the power grid to normal operation and improving the reliability and stability of the power grid.

[0088] It can be seen that by comparing the maximum voltage amplitude with the preset voltage amplitude threshold to obtain the voltage amplitude difference, and the maximum power flow with the preset power flow threshold to obtain the power flow difference, it is possible to quantify the abnormality of the constraint violation node from the perspective of two key grid operation indicators, voltage and power, and determine the first adjustment parameter corresponding to the overvoltage duration and the second adjustment parameter corresponding to the power flow congestion duration. The time factor is further incorporated into the severity assessment, and the priority is determined according to the target severity value of each node. This enables grid operation and maintenance personnel to clearly understand which nodes' constraint violation events are more urgent and serious and need to be handled first. This helps to reasonably allocate resources and prioritize more manpower, material resources and time to solve the node problems that pose the greatest threat to the safe and stable operation of the grid. The order of solving constraint violation events is determined based on priority, and the target allocation method is combined to solve node problems, which can achieve systematic repair of grid constraint violation events.

[0089] In summary, the implementation of the embodiments of this application has the following beneficial effects:

[0090] It can be seen that the solution to the power grid constraint violation event described in the embodiment of the present application obtains the power grid line parameters corresponding to n nodes in the target power grid to obtain the target power grid line parameters, determines the node where the constraint violation event occurs among the n nodes based on the target power grid line parameters to obtain m constraint violation nodes, determines the distribution method of the constraint violation event resolution device among the m constraint violation nodes through the AC power flow model to obtain k distribution methods, and the constraint violation event resolution device is any one of the following: an infrastructure upgrade device, a voltage regulator and an energy storage device, each constraint violation node corresponds to a constraint violation event resolution device, determines the constraint violation event resolution capability value of the constraint violation event resolution device corresponding to each distribution method in the k distribution methods to resolve the corresponding constraint violation event, obtains k constraint violation event resolution capability values, determines the maximum constraint violation event resolution capability value among the k constraint violation event resolution capability values, determines the distribution method corresponding to the maximum constraint violation event resolution capability value, and obtains the target distribution method; the target distribution method is used to resolve the constraint violation events in the m constraint violation nodes, thereby improving the cost-effectiveness of resolving power grid constraint violation events.

[0091] See also Figure 3 , Figure 3 Schematic diagram of a power grid constraint violation event resolution device provided by an embodiment of the present application. The power grid constraint violation event resolution device 300 includes: an acquisition unit 301 and a processing unit 302;

[0092] The acquisition unit 301 is configured to acquire the grid line parameters corresponding to n nodes in the target grid to obtain the target grid line parameters; n is a positive integer;

[0093] The processing unit 302 is configured to determine, based on the target power grid line parameters, nodes where constraint violation events occur among the n nodes, and obtain m constraint violation nodes, where m is an integer less than or equal to n.

[0094] Determining a distribution method of constraint violation event resolution devices among m constraint violation nodes using an AC power flow model to obtain k distribution methods; the constraint violation event resolution device is any one of the following: an infrastructure upgrade device, a voltage regulator, and an energy storage device; each constraint violation node corresponds to one constraint violation event resolution device, and k is an integer greater than or equal to 2;

[0095] determining a constraint violation event resolution capability value of a constraint violation event resolution device corresponding to each of the k allocation methods to resolve the corresponding constraint violation event, thereby obtaining k constraint violation event resolution capability values;

[0096] determining a maximum constraint violation event resolution capability value among the k constraint violation event resolution capability values;

[0097] An allocation method corresponding to a maximum constraint violation event resolution capability value is determined to obtain a target allocation method; the target allocation method is used to resolve the constraint violation events in the m constraint violation nodes.

[0098] In some possible implementations, in determining the constraint violation event resolution capability value of the constraint violation event resolution device corresponding to each of the k allocation methods to resolve the corresponding constraint violation event and obtaining the k constraint violation event resolution capability values, the processing unit 302 is specifically configured to:

[0099] Determine the technical effect value of handling the constraint violation event corresponding to each of the k allocation methods to obtain k technical effect values;

[0100] Determine the cost value corresponding to each of the k allocation methods to obtain k cost values;

[0101] A constraint violation event resolution capability value corresponding to each of the k allocation methods is determined based on the k technical effect values ​​and the k cost values, thereby obtaining k constraint violation event resolution capability values.

[0102] In some possible implementations, in determining the technical effect value of processing the constraint violation event corresponding to each of the k allocation methods to obtain the k technical effect values, the processing unit 302 is specifically configured to:

[0103] According to the determination method in steps S1-S3 below, the technical effect value of each of the m constraint violation nodes in the first allocation method is determined to obtain m reference technical effect values. The first allocation method is any one of the k allocation methods. Specifically, the following steps are performed:

[0104] S1. Determine, based on the target power grid line parameters, the overvoltage duration, maximum voltage amplitude, power flow congestion duration, and maximum power flow corresponding to the first constraint violation node; the first constraint violation node is any one of the m constraint violation nodes;

[0105] S2. Input the overvoltage duration, maximum voltage amplitude, power flow congestion duration, and maximum power flow into a neural network model corresponding to the first allocation mode for prediction, and obtain a reduction rate of the overvoltage duration, a reduction rate of the maximum voltage amplitude, a reduction rate of the power flow congestion time, and a reduction rate of the maximum power flow;

[0106] S3. Determine a reference technical effect value corresponding to the first constraint violation node based on the overvoltage duration reduction rate, the maximum voltage amplitude reduction rate, the power flow congestion time reduction rate, and the maximum power flow reduction rate;

[0107] A technical effect value corresponding to the first allocation method is determined based on the m reference technical effect values.

[0108] In some possible implementations, in determining the reference technical effect value corresponding to the first constraint violation node based on the overvoltage duration reduction rate, the maximum voltage amplitude reduction rate, the power flow congestion time reduction rate, and the maximum power flow reduction rate, the processing unit 302 is specifically configured to:

[0109] Determining a first reference weight corresponding to the overvoltage duration reduction rate;

[0110] Obtain the line load corresponding to the first constraint violation node;

[0111] determining a first optimization factor corresponding to the line load;

[0112] Optimizing the first reference weight according to the first optimization factor to obtain a first target weight;

[0113] determining a second target weight corresponding to the maximum voltage amplitude based on the first target weight; the sum of the first target weight and the second target weight is 1;

[0114] Determine an overvoltage mitigation index corresponding to the first constraint violation node based on the overvoltage duration reduction rate, the maximum voltage amplitude reduction rate, the first target weight, and the second target weight;

[0115] determining a third reference weight corresponding to a power flow congestion time reduction rate;

[0116] Obtaining the cross-sectional area of ​​the conductor corresponding to the first constraint violation node;

[0117] determining a second optimization factor corresponding to the cross-sectional area;

[0118] Optimizing the third reference weight based on the second optimization factor to obtain a third target weight;

[0119] determining a fourth target weight corresponding to the maximum power flow reduction rate based on the third target weight; wherein the sum of the third target weight and the fourth target weight is 1;

[0120] Determine a power flow congestion relief index corresponding to the first constraint violation node based on the power flow congestion time reduction rate, the maximum power flow reduction rate, the third target weight, and the fourth target weight;

[0121] A reference technical effect value corresponding to the first constraint violation node is determined based on the overvoltage relief index and the power flow congestion relief index.

[0122] In some possible implementations, in determining the constraint violation event resolution capability value corresponding to each of the k allocation methods based on the k technical effect values ​​and the k cost values ​​to obtain the k constraint violation event resolution capability values, the processing unit 302 is specifically configured to:

[0123] Determine a first technical effect value and a first cost value corresponding to the first allocation method; the first technical effect value is the technical effect value corresponding to the first allocation method among the k technical effect values, and the first cost value is the cost value corresponding to the first allocation method among the k cost values;

[0124] Determine the maximum technical effect value and the minimum technical effect value among the k technical effect values, and the maximum cost value and the minimum cost value among the k cost values;

[0125] The first constraint violation event resolution capability value is determined based on the first technical effect value, the maximum technical effect value, and the minimum technical effect value. The specific calculation formula is as follows:

[0126]

[0127] Among them, F1 is the first constraint violation event resolution capability value, A is the first technical effect value, A max is the maximum technical effect value, A min is the minimum technical effect value;

[0128] The second constraint violation event resolution capability value is determined based on the first cost value, the maximum cost value, and the minimum cost value. The specific calculation formula is as follows:

[0129]

[0130] Among them, F2 is the second constraint violation event resolution capability value, B is the first cost value, B max is the maximum cost value, B min is the minimum cost value;

[0131] The constraint violation event resolving capability value corresponding to the first allocation method is determined based on the first constraint violation event resolving capability value and the second constraint violation event resolving capability value.

[0132] In some possible implementations, the processing unit 302 is further specifically configured to:

[0133] Determine the severity value corresponding to each of the m constraint violation nodes to obtain m target severity values;

[0134] Determine the priority corresponding to each of the m constraint violation nodes based on the m target severity values, and obtain m priorities;

[0135] The severity value corresponding to each of the m constraint violation nodes is determined to obtain m target severity values, including:

[0136] A1. Determine a voltage amplitude difference based on the maximum voltage amplitude and a preset voltage amplitude threshold, and determine a power flow difference based on the maximum power flow and a preset power flow threshold;

[0137] A2. Determine a reference severity value corresponding to the first constraint violation node based on the voltage amplitude difference and the power flow difference;

[0138] A3. Determine a first adjustment parameter corresponding to the overvoltage duration and a second adjustment parameter corresponding to the power flow congestion duration;

[0139] A4. Adjust the reference severity value based on the first adjustment parameter and the second adjustment parameter to obtain a target severity value corresponding to the first constraint violation node.

[0140] In some possible implementations, the processing unit 302 is further specifically configured to:

[0141] Determine the order of resolving constraint violation events corresponding to m constraint violation nodes based on m priorities;

[0142] Resolve constraint violation events in m constraint violation nodes based on the target allocation method and the constraint violation event resolution order.

[0143] See also Figure 4 , Figure 4 This is a schematic diagram of the structure of an electronic device provided by the embodiment of this application. Figure 4As shown, electronic device 400 includes transceiver 401, processor 402 and memory 403. They are connected via bus 404. Memory 403 is used to store computer programs and data, and transceiver 401 can transmit data stored in memory 403 to processor 402. The above program includes instructions for executing the following steps:

[0144] Obtain the grid line parameters corresponding to n nodes in the target grid to obtain the target grid line parameters; n is a positive integer;

[0145] Determine, based on the target power grid line parameters, nodes where constraint violation events occur among n nodes, and obtain m constraint violation nodes; m is an integer less than or equal to n;

[0146] Determining a distribution method of constraint violation event resolution devices among m constraint violation nodes using an AC power flow model to obtain k distribution methods; the constraint violation event resolution device is any one of the following: an infrastructure upgrade device, a voltage regulator, and an energy storage device; each constraint violation node corresponds to one constraint violation event resolution device, and k is an integer greater than or equal to 2;

[0147] determining a constraint violation event resolution capability value of a constraint violation event resolution device corresponding to each of the k allocation methods to resolve the corresponding constraint violation event, thereby obtaining k constraint violation event resolution capability values;

[0148] determining a maximum constraint violation event resolution capability value among the k constraint violation event resolution capability values;

[0149] An allocation method corresponding to a maximum constraint violation event resolution capability value is determined to obtain a target allocation method; the target allocation method is used to resolve the constraint violation events in the m constraint violation nodes.

[0150] In some possible implementations, in determining the constraint violation event resolution capability value of the constraint violation event resolution device corresponding to each of the k allocation methods for resolving the corresponding constraint violation event, and obtaining the k constraint violation event resolution capability values, the program includes instructions for executing the following steps:

[0151] Determine the technical effect value of handling the constraint violation event corresponding to each of the k allocation methods to obtain k technical effect values;

[0152] Determine the cost value corresponding to each of the k allocation methods to obtain k cost values;

[0153] A constraint violation event resolution capability value corresponding to each of the k allocation methods is determined based on the k technical effect values ​​and the k cost values, thereby obtaining k constraint violation event resolution capability values.

[0154] In some possible implementations, in determining the technical effect value of handling the constraint violation event corresponding to each of the k allocation methods to obtain the k technical effect values, the program includes instructions for performing the following steps:

[0155] According to the determination method in steps S1-S3 below, the technical effect value of each of the m constraint violation nodes in the first allocation method is determined to obtain m reference technical effect values. The first allocation method is any one of the k allocation methods. Specifically, the following steps are performed:

[0156] S1. Determine, based on the target power grid line parameters, the overvoltage duration, maximum voltage amplitude, power flow congestion duration, and maximum power flow corresponding to the first constraint violation node; the first constraint violation node is any one of the m constraint violation nodes;

[0157] S2. Input the overvoltage duration, maximum voltage amplitude, power flow congestion duration, and maximum power flow into a neural network model corresponding to the first allocation mode for prediction, and obtain a reduction rate of the overvoltage duration, a reduction rate of the maximum voltage amplitude, a reduction rate of the power flow congestion time, and a reduction rate of the maximum power flow;

[0158] S3. Determine a reference technical effect value corresponding to the first constraint violation node based on the overvoltage duration reduction rate, the maximum voltage amplitude reduction rate, the power flow congestion time reduction rate, and the maximum power flow reduction rate;

[0159] A technical effect value corresponding to the first allocation method is determined based on the m reference technical effect values.

[0160] In some possible implementations, in determining the reference technical effect value corresponding to the first constraint violation node based on the overvoltage duration reduction rate, the maximum voltage amplitude reduction rate, the power flow congestion time reduction rate, and the maximum power flow reduction rate, the program includes instructions for performing the following steps:

[0161] Determining a first reference weight corresponding to the overvoltage duration reduction rate;

[0162] Obtain the line load corresponding to the first constraint violation node;

[0163] determining a first optimization factor corresponding to the line load;

[0164] Optimizing the first reference weight according to the first optimization factor to obtain a first target weight;

[0165] determining a second target weight corresponding to the maximum voltage amplitude based on the first target weight; the sum of the first target weight and the second target weight is 1;

[0166] Determine an overvoltage mitigation index corresponding to the first constraint violation node based on the overvoltage duration reduction rate, the maximum voltage amplitude reduction rate, the first target weight, and the second target weight;

[0167] determining a third reference weight corresponding to a power flow congestion time reduction rate;

[0168] Obtaining the cross-sectional area of ​​the conductor corresponding to the first constraint violation node;

[0169] determining a second optimization factor corresponding to the cross-sectional area;

[0170] Optimizing the third reference weight based on the second optimization factor to obtain a third target weight;

[0171] determining a fourth target weight corresponding to the maximum power flow reduction rate based on the third target weight; wherein the sum of the third target weight and the fourth target weight is 1;

[0172] Determine a power flow congestion relief index corresponding to the first constraint violation node based on the power flow congestion time reduction rate, the maximum power flow reduction rate, the third target weight, and the fourth target weight;

[0173] A reference technical effect value corresponding to the first constraint violation node is determined based on the overvoltage relief index and the power flow congestion relief index.

[0174] In some possible implementations, in terms of determining a constraint violation event resolution capability value corresponding to each of k allocation methods based on the k technical effect values ​​and the k cost values ​​to obtain the k constraint violation event resolution capability values, the program includes instructions for performing the following steps:

[0175] Determine a first technical effect value and a first cost value corresponding to the first allocation method; the first technical effect value is the technical effect value corresponding to the first allocation method among the k technical effect values, and the first cost value is the cost value corresponding to the first allocation method among the k cost values;

[0176] Determine the maximum technical effect value and the minimum technical effect value among the k technical effect values, and the maximum cost value and the minimum cost value among the k cost values;

[0177] The first constraint violation event resolution capability value is determined based on the first technical effect value, the maximum technical effect value, and the minimum technical effect value. The specific calculation formula is as follows:

[0178]

[0179] Among them, F1 is the first constraint violation event resolution capability value, A is the first technical effect value, A max is the maximum technical effect value, A min is the minimum technical effect value;

[0180] The second constraint violation event resolution capability value is determined based on the first cost value, the maximum cost value, and the minimum cost value. The specific calculation formula is as follows:

[0181]

[0182] Among them, F2 is the second constraint violation event resolution capability value, B is the first cost value, B max is the maximum cost value, B min is the minimum cost value;

[0183] The constraint violation event resolving capability value corresponding to the first allocation method is determined based on the first constraint violation event resolving capability value and the second constraint violation event resolving capability value.

[0184] In some possible implementations, the above program includes instructions for performing the following steps:

[0185] Determine the severity value corresponding to each of the m constraint violation nodes to obtain m target severity values;

[0186] Determine the priority corresponding to each of the m constraint violation nodes based on the m target severity values, and obtain m priorities;

[0187] The severity value corresponding to each of the m constraint violation nodes is determined to obtain m target severity values, including:

[0188] A1. Determine a voltage amplitude difference based on the maximum voltage amplitude and a preset voltage amplitude threshold, and determine a power flow difference based on the maximum power flow and a preset power flow threshold;

[0189] A2. Determine a reference severity value corresponding to the first constraint violation node based on the voltage amplitude difference and the power flow difference;

[0190] A3. Determine a first adjustment parameter corresponding to the overvoltage duration and a second adjustment parameter corresponding to the power flow congestion duration;

[0191] A4. Adjust the reference severity value based on the first adjustment parameter and the second adjustment parameter to obtain a target severity value corresponding to the first constraint violation node.

[0192] In some possible implementations, the above program includes instructions for performing the following steps:

[0193] Determine the order of resolving constraint violation events corresponding to m constraint violation nodes based on m priorities;

[0194] Resolve constraint violation events in m constraint violation nodes based on the target allocation method and the constraint violation event resolution order.

[0195] It should be understood that the electronic devices in this application may include smartphones (such as Android phones, iOS phones, Windows Phone phones, etc.), tablet computers, PDAs, laptops, mobile Internet devices (MIDs) or wearable devices, or servers, edge computing nodes, etc. The above electronic devices are only examples and are not exhaustive, including but not limited to the above electronic devices.

[0196] The embodiments of the present application further provide a computer-readable storage medium storing a computer program, which is executed by a processor to implement part or all of the steps of any solution to a grid constraint violation event as described in the above method embodiments.

[0197] An embodiment of the present application further provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, wherein the computer program is operable to cause a computer to execute some or all of the steps of any one of the methods for resolving a grid constraint violation event as described in the above method embodiments.

[0198] It should be noted that for the aforementioned method implementations, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited by the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the implementations described in the specification are all optional implementations, and the actions and modules involved are not necessarily required by this application.

[0199] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0200] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of units is merely a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0201] Units described as separate components may or may not be physically separate, and components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0202] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or in the form of software program modules.

[0203] If the integrated unit is implemented in the form of a software program module and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes a number of instructions for enabling a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the various implementation methods of the present application. The aforementioned memory includes: various media that can store program codes, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a mobile hard disk, a magnetic disk or an optical disk.

[0204] Those skilled in the art will appreciate that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable memory, which may include: a flash drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, etc.

[0205] The above is a detailed introduction to the implementation methods of the present application. Specific examples are used herein to illustrate the principles and implementation methods of the present application. The description of the above implementation methods is only used to help understand the method and core idea of ​​the present application. At the same time, for those skilled in the art, based on the ideas of the present application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A method for solving a power grid constraint violation event, characterized in that: include: Obtaining grid line parameters corresponding to n nodes in the target grid to obtain target grid line parameters; n is a positive integer; Determine, based on the target power grid line parameters, nodes where constraint violation events occur among the n nodes, to obtain m constraint violation nodes; m is an integer less than or equal to n; Determining, using an AC power flow model, a distribution method of constraint violation event resolution devices among the m constraint violation nodes to obtain k distribution methods; the constraint violation event resolution device is any one of the following: an infrastructure upgrade device, a voltage regulator, and an energy storage device, each constraint violation node corresponds to one constraint violation event resolution device, and k is an integer greater than or equal to 2; determining a constraint violation event resolution capability value of a constraint violation event resolution device corresponding to each of the k allocation modes to resolve the corresponding constraint violation event, thereby obtaining k constraint violation event resolution capability values; determining a maximum constraint violation event resolution capability value among the k constraint violation event resolution capability values; An allocation method corresponding to the maximum constraint violation event resolution capability value is determined to obtain a target allocation method; the target allocation method is used to resolve the constraint violation events in the m constraint violation nodes.

2. The method according to claim 1, wherein The step of determining the constraint violation event resolution capability value of the constraint violation event resolution device corresponding to each of the k allocation modes to resolve the corresponding constraint violation event, and obtaining the k constraint violation event resolution capability values, includes: Determine a technical effect value of processing a constraint violation event corresponding to each of the k allocation methods to obtain k technical effect values; Determine a cost value corresponding to each of the k allocation methods to obtain k cost values; A constraint violation event resolution capability value corresponding to each of the k allocation methods is determined based on the k technical effect values ​​and the k cost values ​​to obtain the k constraint violation event resolution capability values.

3. The method according to claim 2, wherein When the constraint violation event includes an overvoltage event and a power flow congestion event, determining the technical effect value of processing the constraint violation event corresponding to each of the k allocation methods to obtain k technical effect values ​​includes: According to the determination method in steps S1 to S3 below, a technical effect value of a first allocation method on each of the m constraint violation nodes is determined to obtain m reference technical effect values, where the first allocation method is any one of the k allocation methods. Specifically, the following steps are performed: S1. Determine, based on the target power grid line parameters, the overvoltage duration, maximum voltage amplitude, power flow congestion duration, and maximum power flow corresponding to a first constraint violation node; the first constraint violation node is any one of the m constraint violation nodes; S2. Input the overvoltage duration, the maximum voltage amplitude, the power flow congestion duration, and the maximum power flow into a neural network model corresponding to the first allocation mode for prediction, to obtain an overvoltage duration reduction rate, a maximum voltage amplitude reduction rate, a power flow congestion time reduction rate, and a maximum power flow reduction rate; S3. Determine a reference technical effect value corresponding to the first constraint violation node based on the overvoltage duration reduction rate, the maximum voltage amplitude reduction rate, the power flow congestion time reduction rate, and the maximum power flow reduction rate; A technical effect value corresponding to the first allocation method is determined based on the m reference technical effect values.

4. The method according to claim 3, wherein The determining, based on the overvoltage duration reduction rate, the maximum voltage amplitude reduction rate, the power flow congestion time reduction rate, and the maximum power flow reduction rate, of a reference technical effect value corresponding to the first constraint violation node includes: Determining a first reference weight corresponding to the overvoltage duration reduction rate; Obtaining a line load corresponding to the first constraint violation node; determining a first optimization factor corresponding to the line load; Optimizing the first reference weight according to the first optimization factor to obtain a first target weight; determining a second target weight corresponding to the maximum voltage amplitude based on the first target weight; the sum of the first target weight and the second target weight is 1; determining an overvoltage mitigation index corresponding to the first constraint violation node based on the overvoltage duration reduction rate, the maximum voltage amplitude reduction rate, the first target weight, and the second target weight; determining a third reference weight corresponding to the power flow congestion time reduction rate; Obtaining a cross-sectional area of ​​a conductor corresponding to the first constraint violation node; determining a second optimization factor corresponding to the cross-sectional area; Optimizing the third reference weight based on the second optimization factor to obtain a third target weight; determining a fourth target weight corresponding to the maximum power flow reduction rate based on the third target weight; wherein the sum of the third target weight and the fourth target weight is 1; Determine a power flow congestion relief index corresponding to the first constraint violation node based on the power flow congestion time reduction rate, the maximum power flow reduction rate, the third target weight, and the fourth target weight; The reference technical effect value corresponding to the first constraint violation node is determined based on the overvoltage relief index and the power flow congestion relief index.

5. The method according to claim 4, wherein The determining, based on the k technical effect values ​​and the k cost values, a constraint violation event resolution capability value corresponding to each of the k allocation methods to obtain the k constraint violation event resolution capability values ​​includes: Determining a first technical effect value and a first cost value corresponding to the first allocation method; the first technical effect value is a technical effect value corresponding to the first allocation method among the k technical effect values, and the first cost value is a cost value corresponding to the first allocation method among the k cost values; Determining a maximum technical effect value and a minimum technical effect value among the k technical effect values, and a maximum cost value and a minimum cost value among the k cost values; A first constraint violation event resolution capability value is determined based on the first technical effect value, the maximum technical effect value, and the minimum technical effect value. The specific calculation formula is as follows: Among them, F1 is the first constraint violation event resolution capability value, A is the first technical effect value, A max is the maximum technical effect value, A min is the minimum technical effect value; The second constraint violation event resolution capability value is determined based on the first cost value, the maximum cost value, and the minimum cost value. The specific calculation formula is as follows: Wherein, F2 is the second constraint violation event resolution capability value, B is the first cost value, and B max is the maximum cost value, B min is the minimum cost value; A constraint violation event resolving capability value corresponding to the first allocation method is determined based on the first constraint violation event resolving capability value and the second constraint violation event resolving capability value.

6. The method according to any one of claims 3 to 5, characterized in that The method further comprises: Determine a severity value corresponding to each of the m constraint violation nodes to obtain m target severity values; Determine a priority corresponding to each of the m constraint violation nodes based on the m target severity values ​​to obtain m priorities; The determining of the severity value corresponding to each of the m constraint violation nodes to obtain m target severity values ​​includes: A1. determining a voltage amplitude difference based on the maximum voltage amplitude and a preset voltage amplitude threshold, and determining a power flow difference based on the maximum power flow and a preset power flow threshold; A2. determining a reference severity value corresponding to the first constraint violation node based on the voltage amplitude difference and the power flow difference; A3. Determine a first adjustment parameter corresponding to the overvoltage duration and a second adjustment parameter corresponding to the power flow congestion duration; A4. Adjust the reference severity value based on the first adjustment parameter and the second adjustment parameter to obtain a target severity value corresponding to the first constraint violation node.

7. The method according to claim 6, wherein The method further comprises: Determining a constraint violation event resolution order corresponding to the m constraint violation nodes based on the m priorities; The constraint violation events in the m constraint violation nodes are resolved based on the target allocation method and the constraint violation event resolution order.

8. A device for resolving power grid constraint violation events, characterized in that: The apparatus for resolving power grid constraint violation events includes: an acquisition unit and a processing unit; The acquisition unit is used to acquire the grid line parameters corresponding to n nodes in the target grid to obtain the target grid line parameters; n is a positive integer; The processing unit is configured to determine, based on the target power grid line parameter, nodes where constraint violation events occur among the n nodes, to obtain m constraint violation nodes, where m is an integer less than or equal to n; Determining, using an AC power flow model, a distribution method of constraint violation event resolution devices among the m constraint violation nodes to obtain k distribution methods; the constraint violation event resolution device is any one of the following: an infrastructure upgrade device, a voltage regulator, and an energy storage device, each constraint violation node corresponds to one constraint violation event resolution device, and k is an integer greater than or equal to 2; determining a constraint violation event resolution capability value of a constraint violation event resolution device corresponding to each of the k allocation modes to resolve the corresponding constraint violation event, thereby obtaining k constraint violation event resolution capability values; determining a maximum constraint violation event resolution capability value among the k constraint violation event resolution capability values; An allocation method corresponding to the maximum constraint violation event resolution capability value is determined to obtain a target allocation method; the target allocation method is used to resolve the constraint violation events in the m constraint violation nodes.

9. An electronic device, characterized in that: The method comprises a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the one or more programs include instructions for executing the steps in the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the method according to any one of claims 1 to 7.

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