Multi-transient support-oriented distributed high-inertia phase modifier optimal configuration method

Abstract

The application is oriented to a distributed high-inertia phase modifier optimization configuration method for multi-transient support, relates to the field of power system planning, and comprises the following steps: obtaining network topology information of a planned regional power system, calculating system critical inertia and system node inertia based on the network topology information, finding out nodes lower than the critical inertia, and configuring the phase modifier; calculating the sensitivity of the inertia of the nodes lower than the critical inertia to the inertia of the phase modifier at each preconfigured node, calculating the comprehensive sensitivity at each preconfigured point in combination with the critical inertia and the node inertia, determining the configuration position with dominant sensitivity according to the comprehensive sensitivity; inputting a target function and a constraint condition, and obtaining a configuration scheme by using a particle swarm optimization algorithm; updating the network topology information, calculating the short-circuit ratio of each grid-connected node according to a system node admittance matrix, configuring the phase modifier at the nodes with a short-circuit ratio less than a preset critical short-circuit ratio, and performing secondary comparison and analysis to obtain a distributed high-inertia phase modifier site selection scheme; and improving the comprehensive support capability of the system.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of power system planning, and more particularly, to a distributed high-inertia phase modifier optimization configuration method for multi-transient support. BACKGROUND

[0002] Analysis shows that the active and reactive power support capability of the power grid is weakened, the frequency intensity and voltage intensity are reduced, the rotating reserve and inertia level are decreased, the low short-circuit ratio and low damping characteristics are obvious, and the active-reactive-frequency-voltage interweaving coupling makes the frequency and voltage stability mechanism fundamentally changed. In terms of frequency, the connection of large-scale new energy bases reduces the proportion of conventional synchronous generator sets with large mechanical rotational inertia and strong anti-interference capability, the rotating reserve capacity of the power grid is reduced, the inertia and damping are decreased, and the frequency intensity is weakened. Under fault conditions, the active-frequency support capability of the new power grid is insufficient, the frequency response fluctuation amplitude is large, and the frequency dynamic security and stability is deteriorated. In terms of voltage, the connection of large-scale new energy bases reduces the reactive power support capacity of synchronous generators, the electrical distance of the power grid is shortened, the short-circuit ratio and impedance ratio are reduced, the voltage fluctuation propagation depth is expanded, and the voltage intensity is weakened. Under fault conditions, the reactive-voltage support capability of the new power grid is insufficient, the voltage recovery capability is lacking, and the voltage dynamic security and stability is deteriorated.

[0003] Disadvantages of the prior art:

[0004] From the application practice, this new type of distributed phase modifier is no longer just a device for providing reactive power and voltage compensation in the modern power grid, especially the emergence of high-inertia energy storage type phase modifier, which is more attractive to some low-inertia systems in improving system frequency characteristics and improving system frequency support capability. However, compared with the active support of the power grid frequency and voltage by large-capacity synchronous machines, the new type of phase modifier with small capacity and distributed access to new energy stations has essential differences in supporting the traditional power grid. In the optimization configuration level, how to realize low-cost and high-performance stable support through the optimization configuration of the phase modifier under the background of "multi-point access and multi-transient support" has become the key to the promotion of the emerging mode of "new energy base + high-inertia phase modifier".

[0005] In view of the above problems, the present application provides a solution. SUMMARY

[0006] In order to overcome the above-mentioned defects of the prior art, the embodiments of the present application provide a distributed high-inertia phase modifier optimization configuration method for multi-transient support, which improves the comprehensive support capability of the whole system and the grid-source friendliness through the configuration of the high-inertia energy storage type phase modifier.

[0007] In order to achieve the above object, the application provides the following technical scheme: a distributed high-inertia phase modifier optimal configuration method for multi-transient support, comprising the following steps: obtaining network topology information of a planning regional power system, calculating system critical inertia and system node inertia based on the network topology information, finding out nodes below the critical inertia, and configuring the phase modifier; calculating the inertia of the nodes below the critical inertia for the sensitivity of the phase modifier inertia at each pre-configuration node, calculating the comprehensive sensitivity at each pre-configuration point in combination with the critical inertia and the node inertia, determining the configuration position with dominant sensitivity according to the comprehensive sensitivity; inputting the objective function and the constraint condition, and obtaining the configuration scheme by using a particle swarm optimization algorithm; updating the network topology information, calculating the short-circuit ratio of each grid-connected node according to the system node admittance matrix, configuring the phase modifier at the node with a short-circuit ratio less than a preset critical short-circuit ratio, and performing secondary comparison and analysis to obtain the site selection scheme of the distributed high-inertia phase modifier.

[0008] In a preferred embodiment, the system critical inertia is obtained as follows: obtaining network topology information of a planning regional power system, obtaining the maximum frequency change rate and the frequency maximum deviation limit value that can ensure stable operation of the system according to the network topology information, and taking the larger one of the maximum frequency change rate and the frequency maximum deviation limit value as the system critical inertia.

[0009] In a preferred embodiment, the specific steps of determining the configuration position with dominant sensitivity according to the comprehensive sensitivity are as follows: combining the node inertia below the critical inertia and the system critical inertia, and the sensitivity between the nodes and the pre-configuration nodes, and obtaining the comprehensive sensitivity at each pre-configuration point by summation.

[0010] When the ratio of the difference between the critical inertia and the node inertia to the critical variable is maximum, that is, the comprehensive sensitivity at the pre-configuration point is maximum, the phase modifier is configured at the pre-configuration point.

[0011] In a preferred embodiment, the particle swarm optimization algorithm step is as follows: randomly generating a group of particle positions and initial velocities, and calculating the initial fitness value, setting the initial position of the particle as the individual extreme value position of each particle; traversing the individual extreme fitness value of all particles to find the minimum fitness value, and setting the individual extreme value position of the corresponding particle as the global extreme value position; for each particle, updating its own position according to the current speed and position, calculating the fitness value of the new position, and updating the individual best position and the global best position of the particle based on the fitness value; when the system node inertia reaches the system critical inertia, the iteration is stopped, and the particle updated position is the phase modifier configuration position.

[0012] In a preferred embodiment, the site selection scheme of the distributed high-inertia phase modifier is specifically obtained as follows: when the short-circuit ratio is greater than the critical short-circuit ratio, the site selection and capacity determination construction scheme of the distributed high-inertia phase modifier can be obtained; when the short-circuit ratio is less than the critical short-circuit ratio, the distributed high-inertia phase modifier is configured at the node, the short-circuit ratio of the node less than the critical short-circuit ratio is calculated again, and if it is higher than the critical short-circuit ratio, the site selection and capacity determination construction scheme of the distributed high-inertia phase modifier can be obtained, and the phase modifier is deployed according to the site selection and capacity determination construction scheme of the distributed high-inertia phase modifier to reduce the transient overvoltage.

[0013] The technical effects and advantages of the method for optimizing configuration of the distributed high-inertia phase modifier facing multi-transient support are as follows:

[0014] 1. The node inertia is used to evaluate the inertia distribution of the system and identify the weak area of frequency support of the system, and then the phase modifier configuration site is selected based on the node inertia sensitivity index, and the critical inertia of the frequency stability condition constraint is used as an inequality constraint to configure the minimum economic type as the optimization target. The distributed high-inertia phase modifier site selection and capacity determination method is direct and efficient, can make the total configuration capacity of the phase modifier lowest, and the economic type highest, and more effectively improve the system frequency support strength. The method has strong practicability and good economy, and has practical significance in power grid; in actual engineering application, the provided index has clear physical meaning, and is easy for decision makers to understand and use the index to quantitatively analyze the advantages and disadvantages of different schemes.

[0015] 2. The mathematical relationship between the short-circuit ratio and the transient overvoltage is established, the severity of the transient overvoltage caused by the fault is reflected through the short-circuit ratio, and the influence of the voltage support strength of the new energy grid-connected system on the transient overvoltage is quantified. The complex mathematical relationship between the voltage support strength and the transient overvoltage under the multi-station feeding structure of the new energy station is revealed, which meets the requirements of engineering practicability and accuracy; for the sending end power grid with high proportion of wind power, the frequency stability and voltage stability are considered comprehensively, and the method for optimizing configuration of the distributed high-inertia phase modifier of the sending end power grid wind power station considering the inertia and short-circuit ratio improvement is constructed, which has more practical significance for stable operation of the power system. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1 The structure diagram of the method for optimizing configuration of the distributed high-inertia phase modifier facing multi-transient support. DETAILED DESCRIPTION

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0018] Example 1, Figure 1 This invention presents an optimized configuration method for distributed high-inertia camera adjustment with multiple transient supports.

[0019] S10: Obtain the network topology information of the power system in the planning area, calculate the critical inertia of the system and the inertia of the system nodes based on the network topology information, find the nodes with inertia below the critical inertia, and configure synchronous condensers.

[0020] Obtain the network topology information of the power system in the planning area, determine the maximum frequency change rate and the maximum frequency deviation limit that can ensure the stable operation of the system, and calculate the critical inertia of the system based on this;

[0021] Calculate the system node inertia, identify nodes with inertia below the critical value, and if they are below the critical value, then a synchronous condenser needs to be configured.

[0022] The rate of change of frequency This represents the rate of frequency change. An excessively high rate of change can cause the frequency to drop rapidly or even exceed a threshold. The maximum rate of frequency change is expressed as... ;

[0023] The frequency deviation This indicates the frequency drop magnitude. If the magnitude is too large, it will trigger the protection device, and in severe cases, it will lead to frequency collapse. The maximum frequency deviation is expressed as... ;

[0024] The critical inertia of the system is that it is simultaneously subjected to and The constrained system obtains the grid inertia under two different constraints, and then takes the larger of the two as the critical inertia of the system.

[0025] The critical inertia of the system The specific calculation formula is as follows:

[0026]

[0027]

[0028] In the formula, It is the critical inertia of the system. This represents the minimum system inertia when the rate of change of frequency does not exceed a threshold. This represents the minimum system inertia when the frequency deviation does not exceed the threshold. is the maximum value of the disturbance power, is the reference frequency, is the time when the frequency minimum point appears, is the maximum frequency deviation, is the maximum frequency change rate;

[0029] The specific formula for calculating the system node inertia is as follows:

[0030]

[0031] In the formula, is the inertia of the node , is the voltage relationship between the node and the generator , represents the element of the row where the node is located, is the inertia of the generator , is the preset synchronous power factor of the generator at the node ;

[0032] In the formula , the acquisition method is as follows:

[0033] Suppose a power system has nodes, the system has generator end nodes, and network nodes in addition to the generator end nodes, so that the augmented admittance matrix of the system is :

[0034]

[0035] In the formula, is the diagonal matrix formed after the generator transient reactance is converted into admittance, and are the self-admittances of the generators and other network nodes, and are the equivalent admittances after the loads at the generator and other network nodes are simplified into equivalent admittances, and are the mutual admittances of the generators and other network nodes, and the conductance is ignored;

[0036] The network equation of the system is as follows:

[0037]

[0038] In the formula, and The voltage of the generator end node and other nodes, The current input to the network from the generator internal potential node, 、 、 、 The augmented admittance matrix has four regions, wherein 、 、 、 ;

[0039] The voltage of the network nodes other than the generator node in the power grid is represented by the voltage of the generator internal potential node, and the formula is as follows:

[0040]

[0041] In the formula, represents the correlation matrix between the voltages, and the element size is mainly affected by the admittance matrix of the power grid;

[0042] The system critical inertia is compared with the system node inertia to find the nodes below the critical inertia, and if the system node inertia is below the critical inertia, a phase modifier needs to be configured;

[0043] S20, calculate the inertia of the node below the critical inertia for the inertia of the phase modifier at each pre-configuration node, combine the critical inertia and the node inertia to calculate the comprehensive sensitivity at each pre-configuration point, and determine the configuration position with superior sensitivity according to the comprehensive sensitivity;

[0044] The node inertia sensitivity is the sensitivity of the node inertia to the inertia of the generator, and the specific calculation formula is as follows:

[0045]

[0046] The specific calculation formula of the comprehensive sensitivity at each pre-configuration point is as follows:

[0047]

[0048] In the formula, is the inertia of the node , is the inertia of the generator , is the preset synchronous power factor of the generator at the node , is the voltage relationship of the node and the generator , represents the elements of the row where the node is located, is the comprehensive sensitivity at each pre-configuration point, is the pre-configuration point, is the node is the sensitivity between the node and the pre-configuration point, is the sensitivity between the node and the pre-configuration point, is the system critical inertia, is the inertia of the node is the inertia of the node

[0049] The comprehensive sensitivity at each pre-configuration point is obtained by summing up the inertia of each node below the critical inertia, the system critical inertia, and the sensitivity between the node and the pre-configuration point. When the ratio of the difference between the critical inertia and the node inertia to the critical variable is maximum, that is, the comprehensive sensitivity at each pre-configuration point is maximum, the phase modifier is configured at the pre-configuration point.

[0050] S30, input the objective function and the constraint condition, and obtain the configuration scheme by using the particle swarm optimization algorithm;

[0051] The objective function is the total capacity of the phase modifier configuration, and the constraint condition is the system critical inertia;

[0052] The objective function, that is, the total capacity of the phase modifier configuration, is specifically calculated as follows:

[0053]

[0054] In the formula, is the total capacity of the phase modifier configuration, is the capacity of the phase modifier configured at the new energy station, is the number of new energy stations of the system;

[0055] The particle swarm optimization algorithm steps are as follows:

[0056] First, a group of particle positions and initial velocities are randomly generated, and the initial fitness value is calculated. The fitness value is the total capacity of the phase modifier configuration. The initial position of the particle is set as the individual extreme value position of each particle;

[0057] The individual extreme fitness values of all particles are traversed to find the minimum fitness value. The individual extreme position of the corresponding particle is set as the global extreme position;

[0058] For each particle, its position is updated according to its current speed and position, the fitness value of the new position is calculated, and the individual best position and global best position of the particle are updated based on the fitness value;

[0059] The specific formula for updating the speed and position of the particle is as follows:

[0060]

[0061]

[0062] In the formula, and They represent the first Individual particles Wei Shang Di Velocity and position at the next iteration It is inertial weight. and It is a preset learning factor. and It is a random number between 0 and 1. Indicates the first The particle in the first The location of the individual extreme value at the next iteration. This indicates that the entire particle swarm is at the th... The location of the global extremum at the next iteration;

[0063] When the system node inertia reaches the system critical inertia, the iteration stops, and the particle update position is the camera configuration position.

[0064] The core idea of ​​particle swarm optimization is to represent the potential solutions to a problem as "particles." These particles search for the optimal solution in the search space by updating their velocity and position. Each particle has two important attributes:

[0065] Position: Represents the current solution;

[0066] Velocity: Controls the direction and amplitude of particle movement in the search space;

[0067] Each particle adjusts its velocity and position based on the following two factors:

[0068] Individual optimal solution: the best position found by the particle in its own history;

[0069] Global optimal solution: the best position found in the entire particle swarm;

[0070] The inertia of nodes below the critical inertia in the system is checked again to determine whether it is greater than the critical inertia. If it is greater than the critical inertia, the optimized configuration of the distributed high-inertia phase shifter based on inertia is completed.

[0071] S40, update network topology information, calculate the short-circuit ratio of each grid-connected node based on the system node admittance matrix, configure synchronous condensers at nodes with short-circuit ratios less than the preset critical short-circuit ratio, and perform secondary comparison analysis to obtain the location scheme of distributed high-inertia synchronous condensers.

[0072] The relationship between the short-circuit ratio and transient overvoltage is as follows:

[0073] Transient overvoltage is usually a transient voltage rise that occurs in the system after the short-circuit condition is removed. The higher the short-circuit ratio, the smaller the short-circuit current of the generator, the stronger the system stability, and the smaller the impact of transient overvoltage.

[0074] The mathematical formula for calculating the relationship between the short-circuit ratio and transient overvoltage is as follows:

[0075]

[0076] In the formula, For the first Voltage at each grid connection point; For communication system and the first The voltage longitudinal component of each grid connection point; For the first The rated voltage of the synchronous condenser at each grid connection point; The system potential; It is the short-circuit ratio at the grid connection point;

[0077] The system node admittance matrix is matrix, It refers to the number of buses, and the system node admittance matrix. The specific calculation formula is as follows:

[0078]

[0079] In the formula, It is the system node admittance matrix. For the diagonal The self-admittance of each node, The first on the diagonal The node and the first Mutual admittance of each node, This represents the number of buses, where n is the bus number. For each The node and the first Inter-bus admittance;

[0080] The node admittance matrix The inverse matrix is ​​the impedance matrix of the power grid. The equivalent impedance of each grid connection point The specific calculation formula is as follows:

[0081]

[0082] In the formula, The first impedance matrix One diagonal element;

[0083] The specific formula for calculating the short-circuit ratio of the grid connection point of the new energy base is as follows:

[0084]

[0085] In the formula, The equivalent impedance of the grid connection point to the system;

[0086] The short-circuit ratio is greater than the critical short-circuit ratio. The specific calculation formula, used as a criterion for determining whether an AC power grid has the capacity to support strong voltage, is as follows:

[0087]

[0088] When the short-circuit ratio is greater than the critical short-circuit ratio, a location and capacity construction scheme for distributed high-inertia camera adjustment can be obtained; distributed high-inertia camera adjustment is configured at nodes where the short-circuit ratio is less than the critical short-circuit ratio.

[0089] The short-circuit ratio of nodes with a ratio less than the critical short-circuit ratio is calculated again. If the ratio is higher than the critical short-circuit ratio, the location and capacity construction scheme of the distributed high-inertia phase shifter can be obtained.

[0090] Deploy the synchronous condenser according to the site selection and capacity construction plan of the distributed high inertia synchronous condenser to reduce transient overvoltage.

[0091] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0092] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, in the form of a computer program product.

[0093] Those skilled in the art will recognize that the modules and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0094] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.

[0095] The above merely provides the specific implementation of the present application, but the protection scope of the present application is not limited to this. Any person skilled in the art can easily think of the changes or replacements within the technical range disclosed by the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

[0096] Finally, the above merely provides the preferred embodiments of the present application, but is not used to limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims

1. A method for optimizing the configuration of distributed high-inertia phase shifters with multi-transient support, characterized in that, Includes the following steps: Obtain the network topology information of the power system in the planning area, calculate the critical inertia and node inertia of the system based on the network topology information, find the nodes with inertia below the critical inertia, and configure synchronous condensers. Calculate the sensitivity of the inertia of nodes below the critical inertia to the inertia of the camera at each pre-configured node. Combine the critical inertia and node inertia to calculate the comprehensive sensitivity at each pre-configured point. Determine the configuration position with dominant sensitivity based on the comprehensive sensitivity. Given the objective function and constraints, the particle swarm optimization algorithm is used to obtain the configuration scheme. Update the network topology information, calculate the short-circuit ratio of each connection point based on the system node admittance matrix, configure synchronous condensers at nodes with short-circuit ratios less than the preset critical short-circuit ratio, and perform a second comparative analysis to obtain the location scheme of distributed high-inertia synchronous condensers. The specific formula for calculating the critical inertia of the system is as follows: In the formula, It is the critical inertia of the system. This represents the minimum system inertia when the rate of change of frequency does not exceed a threshold. This represents the minimum system inertia when the frequency deviation does not exceed the threshold. This represents the maximum disturbance power. As the reference frequency, The moment when the frequency is at its lowest. It is the maximum frequency deviation. It is the maximum rate of change of frequency; The specific formula for calculating system node inertia is as follows: In the formula, For nodes inertia, For nodes and generator Voltage relationship, Indicates retrieving a node The element in the current row, For generator inertia, For generator At the node The preset synchronous power factor at the location.

2. The method for optimizing the configuration of distributed high-inertia camera with multi-transient support according to claim 1, characterized in that, The method for obtaining the critical inertia of the system is as follows: Obtain the network topology information of the power system in the planning area, and based on the network topology information, obtain the maximum frequency change rate and the maximum frequency deviation limit that can ensure the stable operation of the system. The larger of the maximum frequency change rate and the maximum frequency deviation limit is taken as the critical inertia of the system.

3. The method for optimizing the configuration of distributed high-inertia camera with multi-transient support according to claim 1, characterized in that, The specific steps for determining the sensitivity-dominant configuration position based on comprehensive sensitivity are as follows: The overall sensitivity at each pre-configured point is obtained by summing the node inertia below the critical inertia and the system critical inertia, combined with the sensitivity between the node and the pre-configured node. When the ratio of the difference between the critical inertia and the nodal inertia to the critical variable is the largest, that is, when the overall sensitivity at the pre-configuration point is the largest, the synchronous condenser will be configured at the pre-configuration point.

4. The method for optimizing the configuration of distributed high-inertia camera with multi-transient support according to claim 1, characterized in that, The steps of the particle swarm optimization algorithm are as follows: Randomly generate a set of particle positions and initial velocities, calculate initial fitness values, and set the initial position of each particle to the individual extreme position of each particle; Iterate through the individual extreme fitness values ​​of all particles, find the minimum fitness value, and set the corresponding particle's individual extreme position as the global extreme position. For each particle, update its position based on its current velocity and position, calculate the fitness value of the new position, and update the particle's individual best position and global best position based on the fitness value; When the system node inertia reaches the system critical inertia, the iteration stops, and the particle update position is the camera configuration position.

5. The method for optimizing the configuration of distributed high-inertia camera with multi-transient support according to claim 1, characterized in that, The specific method for obtaining the location scheme of the distributed high-inertia camera is as follows: When the short-circuit ratio is greater than the critical short-circuit ratio, a site selection and capacity construction scheme for distributed high-inertia synchronous condensers can be obtained. When the short-circuit ratio is less than the critical short-circuit ratio, a distributed high-inertia camera is configured at the node, and the short-circuit ratio of the node with a ratio less than the critical short-circuit ratio is calculated again. If it is higher than the critical short-circuit ratio, the location and capacity construction scheme of the distributed high-inertia camera can be obtained. Deploy the synchronous condenser according to the site selection and capacity construction plan of the distributed high inertia synchronous condenser to reduce transient overvoltage.

6. The method for optimizing the configuration of distributed high-inertia camera with multi-transient support according to claim 1, characterized in that, The nodal inertia sensitivity is the sensitivity of the nodal inertia to the generator inertia, and the specific calculation formula is as follows: In the formula, For nodes inertia, For generator inertia, For generator At the node The preset synchronous power factor at the location, For nodes and generator Voltage relationship, Indicates retrieving a node The element in the current row; The specific calculation formula for the overall sensitivity at each pre-configured point is as follows: In the formula, It is the overall sensitivity at each pre-configured point. For pre-configured points, For nodes With pre-configured points Sensitivity between It is the critical inertia of the system. For nodes Inertia.

7. The method for optimizing the configuration of distributed high-inertia camera with multi-transient support according to claim 1, characterized in that, The specific formulas for particle update speed and position in the particle swarm optimization algorithm are as follows: In the formula, and They represent the first Individual particles Wei Shang Di Velocity and position at the next iteration It is inertial weight. and It is a preset learning factor. and It is a random number between 0 and 1. Indicates the first The particle in the first The location of the individual extreme value at the next iteration. This indicates that the entire particle swarm is at the th... The location of the global extremum in the next iteration.

8. The method for optimizing the configuration of distributed high-inertia camera with multi-transient support according to claim 5, characterized in that, The mathematical formula for calculating the relationship between the short-circuit ratio and transient overvoltage is as follows: In the formula, For the first Voltage at each grid connection point; For communication system and the first The voltage longitudinal component of each grid connection point; For the first The rated voltage of the synchronous condenser at each grid connection point; The system potential; It is the short-circuit ratio at the grid connection point.

9. The method for optimizing the configuration of distributed high-inertia camera with multi-transient support according to claim 1, characterized in that, The specific formula for calculating the short-circuit ratio of the grid connection point is as follows: In the formula, It is the short-circuit ratio at the grid connection point. It is the equivalent impedance of the grid connection point to the system; The equivalent impedance of each grid connection point is calculated using the following formula: In the formula, It is the equivalent impedance of each grid connection point. The system node admittance matrix is ​​the first Line number The diagonal elements of the column, It is the impedance matrix of the power grid. The impedance matrix of the power grid is the inverse of the node admittance matrix. The specific formula for calculating the system node admittance matrix is ​​as follows: In the formula, It is the system node admittance matrix. For the diagonal The self-admittance of each node, The first on the diagonal The node and the first Mutual admittance of each node, It refers to the number of busbars. Number the busbars. For each The node and the first Mutual admittance between busbars.

Images