A method and related device for evaluating transient voltage instability risk of a receiving power grid

Abstract

The application discloses a kind of receiving end power grid transient voltage instability risk assessment method and related device, the present application is according to the active power injection of different output of new energy cluster and the grid connection point of new energy cluster basic operating mode under receiving end power grid, determine the typical operating mode scenario of receiving end power grid, according to the distribution of load node in receiving end power grid, determine the pivot node in receiving end power grid, carry out time domain simulation to the typical fault set of receiving end power grid, determine the transient voltage instability probability of each pivot node under typical operating mode scenario, carry out receiving end power grid transient voltage instability risk assessment, can provide reference for receiving end power grid operating mode arrangement and control strategy formulation, can provide strong support for guaranteeing the safe and stable operation of receiving end power grid connected with new energy cluster.

Description

Technical Field

[0001] This invention relates to a method and related apparatus for assessing the risk of transient voltage instability in a receiving-end power grid, belonging to the field of power system safety and stability analysis technology. Background Technology

[0002] Driven by the "dual-carbon" strategic goal, the proportion of new energy power generation such as solar and wind power is gradually increasing. The large-scale replacement of conventional power sources by new energy sources, with their output uncertainty and weak frequency and voltage support characteristics, can easily lead to many new safety and stability risks in the power grid. Furthermore, after the construction of large-scale new energy clusters in the receiving-end power grid of large load centers, the voltage support capacity of the power grid will be even weaker as new energy sources replace conventional power sources on a large scale, highlighting the risk of transient voltage instability.

[0003] Current technologies mainly focus on the assessment and improvement of transient voltage stability in traditional power grid scenarios, as well as the mechanism or assessment of new energy access in a single scenario. They lack the risk assessment of transient voltage instability in the receiving-end power grid when new energy clusters are connected. Summary of the Invention

[0004] This invention provides a method and related apparatus for assessing the risk of transient voltage instability in the receiving-end power grid, which solves the problems disclosed in the background art.

[0005] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows:

[0006] A method for assessing the risk of transient voltage instability in a receiving-end power grid includes:

[0007] Based on the different power outputs of the new energy clusters and the active power injection at the grid connection points of the new energy clusters under the basic operation mode of the receiving-end power grid, the typical operation mode scenarios of the receiving-end power grid are determined.

[0008] Based on the distribution of load nodes in the receiving-end power grid, the key nodes in the receiving-end power grid are determined; among them, the key nodes are load nodes that are prone to causing transient voltage instability in the receiving-end power grid.

[0009] For each typical operating mode scenario, time-domain simulation is performed on the typical fault set of the receiving-end power grid to determine the transient voltage stability of each hub node. Based on the transient voltage stability of each hub node, the transient voltage instability probability of each hub node is determined.

[0010] Based on the transient voltage instability probability of each hub node under each typical operating mode scenario, a transient voltage instability risk assessment of the receiving-end power grid is conducted.

[0011] Based on the different power outputs of the renewable energy clusters and the active power injection at the grid connection points of the renewable energy clusters under the different operating modes of the receiving-end power grid, typical operating mode scenarios of the receiving-end power grid are determined, including:

[0012] Calculate the power difference between the active power injection at the grid connection point of the new energy cluster under different power output and receiving-end grid basic operation modes;

[0013] The power difference is equally distributed among the generators in the receiving-end power grid to obtain typical operating scenarios of the receiving-end power grid.

[0014] Based on the distribution of load nodes in the receiving-end power grid, determine the key nodes in the receiving-end power grid, including:

[0015] Based on the distribution of load nodes in the receiving-end power grid, determine N, which is not less than the preset voltage level. L_Total There are N candidate hub nodes; among them, N L_Total The preset number of candidate hub nodes;

[0016] Based on the equivalent potential of the new energy cluster, the equivalent impedance from the new energy cluster to the candidate hub node, the equivalent potential of the generator node, and the equivalent impedance from the generator node to the candidate hub node, calculate the short-circuit capacity provided by the generator node and the grid connection point of the new energy cluster to each candidate hub node.

[0017] Based on short-circuit capacity, the hub nodes in the receiving-end power grid are determined from the candidate hub nodes.

[0018] The formula for calculating the short-circuit capacity provided by generator nodes and new energy cluster grid connection points to each candidate hub node is as follows:

[0019]

[0020]

[0021]

[0022] Among them, S aci S provides the short-circuit capacity for the i-th candidate hub node to the generator node and the new energy cluster grid connection point. aci-New S provides the short-circuit capacity to the i-th candidate hub node for the new energy cluster grid connection point. aci-Gj N is the short-circuit capacity provided by the j-th generator node to the i-th candidate hub node. G E represents the number of generator nodes. New-i Z represents the equivalent potential of the new energy cluster. New-i E represents the equivalent impedance from the new energy cluster to the i-th candidate hub node. Gj-i Z is the equivalent potential of the j-th generator node. Gj-i Let be the equivalent impedance from the j-th generator node to the i-th candidate hub node.

[0023] Based on short-circuit capacity, the hub nodes in the receiving-end power grid are determined from the candidate hub nodes, including:

[0024] Sort the short-circuit capacities and select N in ascending order. L N candidate hub nodes are selected as hub nodes in the receiving-end power grid; among them, N L The preset number of hub nodes.

[0025] For each typical operating mode scenario, time-domain simulations are performed on the typical fault set of the receiving-end power grid to determine the transient voltage stability of each hub node. Based on the transient voltage stability of each hub node, the transient voltage instability probability of each hub node is determined, including:

[0026] 1) In the f-th typical operating mode scenario, increase the load level of the i1-th hub node according to the preset rules, and determine the various first load verification points of the i1-th hub node; wherein, each first load verification point corresponds to a load level, and the initial value of i1 is 1;

[0027] 2) Under the k-th type of first load verification point, perform time-domain simulation on the typical fault set of the receiving-end power grid to determine the transient voltage stability of the i1-th hub node under the k-th type of first load verification point; where k is initially 1.

[0028] 3) If the transient voltage is stable and k+1 is not greater than k end If k = k + 1, go to step 2);

[0029] If the transient voltage is stable and k+1 is greater than k end Then proceed to step 5);

[0030] If the transient voltage is unstable, then the transient voltage at all first load checkpoints greater than or equal to k is unstable, and proceed to 4);

[0031] Where, k end This represents the number of first load checkpoints for the i1th hub node.

[0032] 4) Based on the possible load level range of the i1th hub node and the load level statistics within the preset historical time period, determine the load level of the i1th hub node in the kth period. s The transient voltage instability probability under the first load check point is shown in section 5); where k s =k, k+1, ..., k end ;

[0033] 5) If i1+1 is not greater than N L Then i1 = i1 + 1, go to 1); where N L The preset number of hub nodes;

[0034] If i1+1 is greater than N L Then the process of determining the transient voltage instability probability under the f-th typical operating mode scenario ends.

[0035] Increase the load level of the i1th hub node according to preset rules, and determine various first load checkpoints for the i1th hub node, including:

[0036] Increase the active and reactive power of the i1th hub node proportionally by 1% each time, until the load level of the i1th hub node changes from S. i1 Growth to KS i1 ,get The first load check point; among them, S i1 The initial load level of the i1th hub node is given by K, which is a preset multiple, and l% is a preset power increase percentage.

[0037] Based on the possible load level range of the i1th hub node and the load level statistics within the preset historical time period, the load level of the i1th hub node in the kth period is determined. s The transient voltage instability probability under the first load check point includes:

[0038] Based on the possible load level range of the i1th hub node and the load level statistics within the preset historical time period, the load level of the i1th hub node in the kth period is determined. s The probability under the first load checkpoint;

[0039] According to the i1th hub node at the kth s The probability of the first load check point is calculated, and the probability of the i1th hub node at the kth load point is calculated. s The probability of transient voltage instability under the first load check point.

[0040] Based on the possible load level range of the i1th hub node and the load level statistics within the preset historical time period, the load level of the i1th hub node in the kth period is determined. s The probabilities under the first load checkpoint include:

[0041] Divide the possible load level intervals of the i1th hub node into equal intervals to determine the various second load check points of the i1th hub node; wherein, each second load check point is a load level corresponding to an interval, and the set of first load check points is a subset of the set of second load check points;

[0042] Based on the load level corresponding to each second load checkpoint and the preset positive and negative fluctuations, determine the statistical load level range corresponding to each second load checkpoint;

[0043] Based on the load level statistics of the i1th hub node within a preset historical period, determine the probability that the hourly average load level falls within each statistical load level interval within the preset historical period.

[0044] Based on the probability that the hourly average load level falls within each statistical load level interval during a preset historical period, the i1th hub node is determined at the kth... s The probability under the first load check point.

[0045] Calculate the i1th hub node at the kth position. s The transient voltage instability probability under the first load check point is given by the following formula:

[0046]

[0047] Wherein, Ψ(f,i1,k) s ) represents the i1th hub node in the kth typical operating scenario. s The transient voltage instability probability under the first load check point, λ f The probability of new energy output corresponding to the f-th typical operating mode scenario, For the i1th hub node at the kth... s The probability of the first load checkpoint, μ i1 (k s ) = 1 indicates that the i1th hub node is at the kth node. s Transient voltage instability under the first load check point, μ i1 (k s ) = 0 indicates that the i1th hub node is at the kth node. s The transient voltage is stable under the first load check point.

[0048] A receiving-end power grid transient voltage instability risk assessment device, comprising:

[0049] The typical operation mode scenario module determines the typical operation mode scenario of the receiving-end power grid based on the different outputs of the new energy clusters and the active power injection of the new energy cluster grid connection points under the basic operation mode of the receiving-end power grid.

[0050] The hub node module determines the hub nodes in the receiving-end power grid based on the distribution of load nodes in the receiving-end power grid; wherein, the hub node is a load node that is prone to causing transient voltage instability in the receiving-end power grid.

[0051] The transient voltage instability probability module performs time-domain simulations of typical fault sets of the receiving-end power grid for each typical operating mode scenario, determines the transient voltage stability of each hub node, and determines the transient voltage instability probability of each hub node based on the transient voltage stability of each hub node.

[0052] The risk assessment module assesses the risk of transient voltage instability in the receiving-end power grid based on the probability of transient voltage instability at each hub node under each typical operating mode scenario.

[0053] A computer-readable storage medium storing one or more programs, the one or more programs including instructions that, when executed by a computing device, cause the computing device to perform a method for assessing the risk of transient voltage instability in a receiving-end power grid.

[0054] A computing device includes one or more processors, one or more memories, and one or more programs, wherein the one or more programs are stored in the one or more memories and configured to be executed by the one or more processors, and the one or more programs include instructions for performing a receiving-end power grid transient voltage instability risk assessment method.

[0055] The beneficial effects achieved by this invention are as follows: Based on the different outputs of the new energy clusters and the active power injection of the grid-connected points of the new energy clusters under the basic operation mode of the receiving-end power grid, this invention determines the typical operation mode scenarios of the receiving-end power grid. Based on the distribution of load nodes in the receiving-end power grid, it determines the hub nodes in the receiving-end power grid. It performs time-domain simulation on the typical fault set of the receiving-end power grid, determines the transient voltage instability probability of each hub node under the typical operation mode scenarios, and conducts a transient voltage instability risk assessment of the receiving-end power grid. This can provide a reference for the arrangement of the operation mode and the formulation of control strategies for the receiving-end power grid, and can provide strong support for ensuring the safe and stable operation of the receiving-end power grid connected to the new energy clusters. Attached Figure Description

[0056] Figure 1 A flowchart of a method for assessing the risk of transient voltage instability in the receiving-end power grid;

[0057] Figure 2 A flowchart for determining the transient voltage instability probability of each hub node under typical operating scenarios. Detailed Implementation

[0058] The present invention will be further described below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and should not be used to limit the scope of protection of the present invention.

[0059] like Figure 1 As shown, a method for assessing the risk of transient voltage instability in a receiving-end power grid includes the following steps:

[0060] Step 1: Determine the typical operating mode scenario of the receiving-end power grid based on the different outputs of the new energy clusters and the active power injection of the new energy cluster grid connection points under the basic operating mode of the receiving-end power grid.

[0061] Step 2: Based on the distribution of load nodes in the receiving-end power grid, determine the hub nodes in the receiving-end power grid; whereby hub nodes are load nodes that are prone to causing transient voltage instability in the receiving-end power grid.

[0062] Step 3: For each typical operating mode scenario, perform time-domain simulation of the typical fault set of the receiving-end power grid to determine the transient voltage stability of each hub node, and determine the transient voltage instability probability of each hub node based on the transient voltage stability of each hub node.

[0063] Step 4: Based on the transient voltage instability probability of each hub node under each typical operating mode scenario, conduct a transient voltage instability risk assessment of the receiving-end power grid.

[0064] The above method determines the typical operating mode scenarios of the receiving-end power grid based on the different outputs of the new energy clusters and the active power injection of the grid connection points of the new energy clusters under the basic operating mode of the receiving-end power grid. Based on the distribution of load nodes in the receiving-end power grid, it identifies the hub nodes in the receiving-end power grid. It performs time-domain simulation on the typical fault set of the receiving-end power grid to determine the transient voltage instability probability of each hub node under the typical operating mode scenarios and conducts a transient voltage instability risk assessment of the receiving-end power grid. This can provide a reference for the arrangement of the operating mode and the formulation of control strategies for the receiving-end power grid and provide strong support for ensuring the safe and stable operation of the receiving-end power grid connected to the new energy clusters.

[0065] Currently, the power output of new energy clusters is mainly divided into three categories: large-scale, medium-scale, and small-scale, with the corresponding power output denoted as P. new-hig P new-mid P new-low When determining the typical operating scenarios for the connection of a renewable energy cluster to the receiving-end power grid, the power difference between the renewable energy cluster's output and the active power injection at the grid connection point of the renewable energy cluster under different power outputs and the basic operating modes of the receiving-end power grid can be calculated first, denoted as ΔP1 = P new-hig -P base-new ΔP2=P new-mid -P base-new ΔP3=P new-low -P base-new The power difference is equally distributed among the generators in the receiving-end power grid to obtain three typical operating scenarios of the receiving-end power grid under the power output levels of the new energy cluster: large, medium, and small generation.

[0066] The receiving-end power grid has many nodes, such as load nodes and generator nodes. Among the load nodes, some nodes are prone to causing transient voltage instability in the receiving-end power grid. These nodes are referred to as hub nodes. It is necessary to further determine the hub nodes in the receiving-end power grid based on the distribution of load nodes. Specifically, it can be as follows:

[0067] A1) Based on the distribution of load nodes in the receiving-end power grid, determine N, which is not less than the preset voltage level. L_Total There are N candidate hub nodes; among them, N L_Total The preset number of candidate hub nodes.

[0068] Based on the specific distribution of load nodes and actual production experience, the N value for voltage levels of 220kV and above is determined. L_Total There are 5 candidate hub nodes, generally 5 ≤ N. L_Total ≤10.

[0069] A2) Based on the equivalent potential of the new energy cluster, the equivalent impedance from the new energy cluster to the candidate hub node, the equivalent potential of the generator node, and the equivalent impedance from the generator node to the candidate hub node, calculate the short-circuit capacity provided by the generator node and the grid connection point of the new energy cluster to each candidate hub node.

[0070] The calculation formula can be expressed as:

[0071]

[0072]

[0073]

[0074] Among them, S aci S provides the short-circuit capacity for the i-th candidate hub node to the generator node and the new energy cluster grid connection point. aci-New S provides the short-circuit capacity to the i-th candidate hub node for the new energy cluster grid connection point. aci-Gj N is the short-circuit capacity provided by the j-th generator node to the i-th candidate hub node. G E represents the number of generator nodes. New-i Z represents the equivalent potential of the new energy cluster. New-i E represents the equivalent impedance from the new energy cluster to the i-th candidate hub node. Gj-i Z is the equivalent potential of the j-th generator node. Gj-i Let be the equivalent impedance from the j-th generator node to the i-th candidate hub node.

[0075] A3) Based on short-circuit capacity, determine the hub nodes in the receiving-end power grid from the candidate hub nodes; specifically, sort the short-circuit capacities and select N in ascending order. L N candidate hub nodes are selected as hub nodes in the receiving-end power grid; among them, N L The preset number of hub nodes is typically N. L <5.

[0076] For each typical operation mode scenario, perform time-domain simulation on the typical fault set of the receiving-end power grid, determine the transient voltage stability of each hub node according to engineering criteria, and determine the transient voltage instability probability of each hub node based on the transient voltage stability of each hub node.

[0077] Figure 2 Taking the f-th typical operation mode scenario as an example, the specific steps are as follows:

[0078] 1) Under the f-th typical operation mode scenario, increase the load level of the i1-th hub node according to a preset rule, and determine various first load checking points of the i1-th hub node; where each first load checking point corresponds to a load level, and the initial value of i1 is 1.

[0079] Increase the load level of the i1-th hub node according to a preset rule, and determine various first load checking points of the i1-th hub node, including: increase the active power and reactive power of the i1-th hub node by the same proportion of l% each time until the load of the i1-th hub node increases from S i1 to KS i1 , and obtain types of first load checking points; where S i1 is the initial load level of the i1-th hub node, K is a preset multiple, l% is a preset power increase percentage, and generally 10% is taken.

[0080] Based on the initial load S i1 of the i1-th hub node under the typical operation mode, increase the active power and reactive power by the same proportion of 10% each time until it increases to K times the initial load (1 < K < 2, and it is an integer multiple of 0.1, determined according to the maximum possible load level in actual production experience). The initial active and reactive outputs of the i1-th hub node are P i1 , Q i1 , and the increased active and reactive powers are P i1 ′ = K · P i1 , Q i ′1 = K · Q i1 , forming k end = K / 0.1 types of first load checking points.

[0081] 2) Under the k-th first load checking point, perform time-domain simulation on the typical fault set of the receiving-end power grid to determine the transient voltage stability of the i1-th hub node under the k-th first load checking point; where the initial value of k is 1.

[0082] 3) If the transient voltage is stable and k + 1 is not greater than k end , then k = k + 1, and go to 2);

[0083] If the transient voltage is stable and k+1 is greater than k end Then proceed to step 5);

[0084] If the transient voltage is unstable, then the transient voltage at all first load checkpoints greater than or equal to k is unstable, and proceed to 4);

[0085] Where, k end This represents the number of first load checkpoints for the i1th hub node.

[0086] If the hub point voltage recovers to above 0.8 pu within 10 seconds after fault clearance under all typical faults in the typical fault set, then the transient voltage at the load check point is stable, expressed in μ. i1 (k) = 0 indicates that the transient voltage is stable (i1 is the hub point number, k is the load check point number); if, under any typical fault in the typical fault set, the voltage at the hub monitoring point fails to recover to above 0.8 pu within 10 seconds after the fault is cleared, then the transient voltage at that load check point is determined to be unstable, denoted as μ. i1 (k) = 1, and record the fault that caused the transient voltage instability and the load checkpoint number k when the hub node first experienced transient voltage instability. iEnd And denote that greater than or equal to k iEnd At that time, μ i1 (k) = 1.

[0087] 4) Based on the possible load level range of the i1th hub node and the load level statistics within the preset historical time period, determine the load level of the i1th hub node in the kth period. s The transient voltage instability probability under the first load check point is shown in section 5); where k s =k, k+1, ..., k end .

[0088] In 4), the i1th hub node is determined to be at the kth position. s The transient voltage instability probability under the first load check point includes:

[0089] 41) Based on the possible load level range of the i1th hub node and the load level statistics within the preset historical time period, determine the load level of the i1th hub node in the kth period. s The probability under the first load check point.

[0090] For renewable energy clusters, large-scale power generation is considered to be above 80% of the cluster's rated capacity; medium-scale power generation is considered to be between 30% and 80% of the cluster's rated capacity; and small-scale power generation is considered to be below 30% of the cluster's rated capacity. Based on historical statistics from the actual receiving-end power grid over the past year, probability values ​​λ for different power outputs of large, medium, and small-scale renewable energy clusters are obtained. a =T a / 8760、λ b =T b / 8760、λ c =T c / 8760; where T a T b T c These represent the converted hours under large, medium, and small load factors over the past year. First, the possible load level intervals of the i1th hub node can be equally divided to determine various second load checkpoints for the i1th hub node. Each second load checkpoint corresponds to a load level within a specific interval, and the set of first load checkpoints is a subset of the set of second load checkpoints. Then, based on the load level corresponding to each second load checkpoint and the preset positive and negative fluctuations, the corresponding statistical load level interval for each second load checkpoint is determined. Finally, based on the load level statistics of the i1th hub node within a preset historical period, the probability that the hourly average load level within the preset historical period falls within each statistical load level interval is determined, thus determining the probability of the i1th hub node at load factor k. s The probability under the first load check point.

[0091] Specifically, it is assumed that the initial load level S of the i1th hub node in the typical operating mode is... i1 Based on production operation experience, the minimum possible load level is determined to be K. a S i1 (0.5≤K a <1, and is an integer multiple of 0.1), determine the maximum possible load level as KS. i1 Within the possible load level range [K] a S i1 KS i1 [Within 0.1S] i1 Interval (KK) a There are 0.1+1 second load checkpoints, each corresponding to a load and a statistical load level interval. For example, the m-th second load checkpoint corresponds to a load S. i1m Corresponding load range [S] i1m -0.05S i1 ,S i1m +0.05S i1 ); where ±0.05S i1 The preset positive and negative fluctuations.

[0092] Based on the historical statistical results of the i1th hub node in the actual receiving-end power grid over the past year, and based on the hourly average load level, the average load level falling within the interval [S] is statistically analyzed. i1m -0.05S i1 ,S i1m +0.05S i1The probability Φ within ) i1m =N i1m / 8760, where N i1m For the average load level to fall within the interval [S] i1m -0.05S i1 ,S i1m +0.05S i1 The number of times ) is recorded as Φ. i1m Let be the probability of the i1th hub node under the mth second load checkpoint. Since the set of first load checkpoints is a subset of the set of second load checkpoints, the corresponding probability of the i1th hub node under the kth load checkpoint can be obtained from the above probability. s The probability under the first load check point.

[0093] 42) Based on the i1th hub node at the kth... s The probability of the first load check point is calculated, and the probability of the i1th hub node at the kth load point is calculated. s The transient voltage instability probability under the first load check point can be calculated using the following formula:

[0094]

[0095] Wherein, Ψ(f,i1,k) s ) represents the i1th hub node in the kth typical operating scenario. s The transient voltage instability probability under the first load check point, λ f The probability of new energy output corresponding to the f-th typical operating mode scenario, For the i1th hub node at the kth... s The probability of the first load checkpoint, μ i1 (k s ) = 1 indicates that the i1th hub node is at the kth node. s Transient voltage instability under the first load check point, μ i1 (k s ) = 0 indicates that the i1th hub node is at the kth node. s The transient voltage is stable under the first load check point.

[0096] 5) If i1+1 is not greater than N L Then i1 = i1 + 1, go to 1); where N L The preset number of hub nodes;

[0097] If i1+1 is greater than N L Then the process of determining the transient voltage instability probability under the f-th typical operating mode scenario ends.

[0098] This allows us to obtain the transient voltage instability probability of each hub node under each typical operating mode scenario. Based on the transient voltage instability probability of each hub node under each typical operating mode scenario, we can conduct a transient voltage instability risk assessment of the receiving-end power grid. Specifically, we record the typical operating mode, hub node, and its load level when the transient voltage instability probability is not zero.

[0099] The above method enables the assessment of transient voltage instability risk in the receiving-end power grid connected to the new energy cluster. Based on the transient voltage instability risk of the receiving-end power grid under different operating modes of large, medium, and small power generation in the new energy cluster, the operating mode of the receiving-end power grid and the formulation of control strategies can be arranged. According to the voltage weak points and instability risks of the power grid, control measures can be taken in a timely manner for areas with voltage instability risks to ensure the safe and stable operation of the receiving-end power grid.

[0100] Based on the same technical solution, this invention also discloses a software device for the above method, a receiving-end power grid transient voltage instability risk assessment device, comprising:

[0101] The typical operation mode scenario module determines the typical operation mode scenario of the receiving-end power grid based on the different outputs of the new energy clusters and the active power injection of the new energy cluster grid connection points under the basic operation mode of the receiving-end power grid.

[0102] The hub node module determines the hub nodes in the receiving-end power grid based on the distribution of load nodes in the receiving-end power grid; wherein, the hub node is a load node that is prone to causing transient voltage instability in the receiving-end power grid.

[0103] The transient voltage instability probability module performs time-domain simulations of typical fault sets of the receiving-end power grid for each typical operating mode scenario, determines the transient voltage stability of each hub node, and determines the transient voltage instability probability of each hub node based on the transient voltage stability of each hub node.

[0104] The risk assessment module assesses the risk of transient voltage instability in the receiving-end power grid based on the probability of transient voltage instability at each hub node under each typical operating mode scenario.

[0105] The data processing flow and methods of each module in the above system are consistent and will not be described again here.

[0106] Based on the same technical solution, the present invention also discloses a computer-readable storage medium storing one or more programs, the one or more programs including instructions that, when executed by a computing device, cause the computing device to perform a method for assessing the risk of transient voltage instability in the receiving-end power grid.

[0107] Based on the same technical solution, the present invention also discloses a computing device, including one or more processors, one or more memories, and one or more programs, wherein the one or more programs are stored in the one or more memories and configured to be executed by the one or more processors, and the one or more programs include instructions for executing a method for assessing the risk of transient voltage instability in the receiving-end power grid.

[0108] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0109] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0110] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0111] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0112] The above are merely embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention are included within the scope of the claims of the present invention pending approval.

Claims

1. A method for assessing the risk of transient voltage instability in a receiving-end power grid, characterized in that, include: Based on the different power outputs of the new energy clusters and the active power injection at the grid connection points of the new energy clusters under the basic operation mode of the receiving-end power grid, the typical operation mode scenarios of the receiving-end power grid are determined. Based on the distribution of load nodes in the receiving-end power grid, determine N, which is not less than the preset voltage level. L_Total For each candidate hub node, based on the equivalent potential of the renewable energy cluster, the equivalent impedance from the renewable energy cluster to the candidate hub node, the equivalent potential of the generator node, and the equivalent impedance from the generator node to the candidate hub node, the short-circuit capacity provided by the generator node and the renewable energy cluster grid connection point to each candidate hub node is calculated. Based on the short-circuit capacity, the hub node in the receiving-end power grid is determined from the candidate hub nodes; where N L_Total The number of candidate hub nodes is preset; hub nodes are load nodes that are prone to causing transient voltage instability in the receiving-end power grid. For each typical operating mode scenario, time-domain simulation is performed on the typical fault set of the receiving-end power grid to determine the transient voltage stability of each hub node. Based on the transient voltage stability of each hub node, the transient voltage instability probability of each hub node is determined. Based on the transient voltage instability probability of each hub node under each typical operating mode scenario, a transient voltage instability risk assessment of the receiving-end power grid is conducted. For each typical operating mode scenario, time-domain simulations are performed on typical fault sets of the receiving-end power grid to determine the transient voltage stability of each hub node. Based on the transient voltage stability of each hub node, the transient voltage instability probability of each hub node is determined, including: 1) In the f-th typical operating mode scenario, increase the load level of the i1-th hub node according to the preset rules, and determine the various first load verification points of the i1-th hub node; wherein, each first load verification point corresponds to a load level, and the initial value of i1 is 1; 2) Under the k-th type of first load verification point, perform time-domain simulation on the typical fault set of the receiving-end power grid to determine the transient voltage stability of the i1-th hub node under the k-th type of first load verification point; where k is initially 1. 3) If the transient voltage is stable and k+1 is not greater than k end If k = k + 1, go to step 2); If the transient voltage is stable and k+1 is greater than k end Then proceed to step 5); If the transient voltage is unstable, then the transient voltage at all first load checkpoints greater than or equal to k is unstable, and proceed to 4); Where, k end This represents the number of first load checkpoints for the i1th hub node. 4) Based on the possible load level range of the i1th hub node and the load level statistics within the preset historical time period, determine the load level of the i1th hub node in the kth period. s The transient voltage instability probability under the first load check point is shown in section 5); where k s =k, k+1, ..., k end ; 5) If i1+1 is not greater than N L Then i1 = i1 + 1, go to 1); where N L The preset number of hub nodes; If i1+1 is greater than N L Then the process of determining the transient voltage instability probability under the f-th typical operating mode scenario ends.

2. The method for assessing the risk of transient voltage instability in a receiving-end power grid according to claim 1, characterized in that, Based on the different power outputs of the renewable energy clusters and the active power injection at the grid connection points of the renewable energy clusters under the different operating modes of the receiving-end power grid, typical operating mode scenarios of the receiving-end power grid are determined, including: Calculate the power difference between the active power injection at the grid connection point of the new energy cluster under different power output and receiving-end grid basic operation modes; The power difference is equally distributed among the generators in the receiving-end power grid to obtain typical operating scenarios of the receiving-end power grid.

3. The method for assessing the risk of transient voltage instability in a receiving-end power grid according to claim 1, characterized in that, The formula for calculating the short-circuit capacity provided by generator nodes and new energy cluster grid connection points to each candidate hub node is as follows: Among them, S aci S provides the short-circuit capacity for the i-th candidate hub node to the generator node and the new energy cluster grid connection point. aci-New S provides the short-circuit capacity to the i-th candidate hub node for the new energy cluster grid connection point. aci-Gj N is the short-circuit capacity provided by the j-th generator node to the i-th candidate hub node. G E represents the number of generator nodes. New-i Z represents the equivalent potential of the new energy cluster. New-i E represents the equivalent impedance from the new energy cluster to the i-th candidate hub node. Gj-i Z is the equivalent potential of the j-th generator node. Gj-i Let be the equivalent impedance from the j-th generator node to the i-th candidate hub node.

4. The method for assessing the risk of transient voltage instability in a receiving-end power grid according to claim 1, characterized in that, Based on short-circuit capacity, the hub nodes in the receiving-end power grid are determined from the candidate hub nodes, including: Sort the short-circuit capacities and select N in ascending order. L The candidate hub nodes serve as hub nodes in the receiving-end power grid.

5. The method for assessing the risk of transient voltage instability in a receiving-end power grid according to claim 1, characterized in that, Increase the load level of the i1th hub node according to preset rules, and determine various first load checkpoints for the i1th hub node, including: Increase the active and reactive power of the i1th hub node proportionally by 1% each time, until the load level of the i1th hub node changes from S. i1 Growth to KS i1 ,get The first load check point; among them, S i1 The initial load level of the i1th hub node is given by K, which is a preset multiple, and l% is a preset power increase percentage.

6. The method for assessing the risk of transient voltage instability in a receiving-end power grid according to claim 1, characterized in that, Based on the possible load level range of the i1th hub node and the load level statistics within the preset historical time period, the load level of the i1th hub node in the kth period is determined. s The transient voltage instability probability under the first load check point includes: Based on the possible load level range of the i1th hub node and the load level statistics within the preset historical time period, the load level of the i1th hub node in the kth period is determined. s The probability under the first load checkpoint; According to the i1th hub node at the kth s The probability of the first load check point is calculated, and the probability of the i1th hub node at the kth load point is calculated. s The probability of transient voltage instability under the first load check point.

7. The method for assessing the risk of transient voltage instability in a receiving-end power grid according to claim 6, characterized in that, Based on the possible load level range of the i1th hub node and the load level statistics within the preset historical time period, the load level of the i1th hub node in the kth period is determined. s The probabilities under the first load checkpoint include: Divide the possible load level intervals of the i1th hub node into equal intervals to determine the various second load check points of the i1th hub node; wherein, each second load check point is a load level corresponding to an interval, and the set of first load check points is a subset of the set of second load check points; Based on the load level corresponding to each second load checkpoint and the preset positive and negative fluctuations, determine the statistical load level range corresponding to each second load checkpoint; Based on the load level statistics of the i1th hub node within a preset historical period, determine the probability that the hourly average load level falls within each statistical load level interval within the preset historical period. Based on the probability that the hourly average load level falls within each statistical load level interval during a preset historical period, the i1th hub node is determined at the kth... s The probability under the first load check point.

8. The method for assessing the risk of transient voltage instability in a receiving-end power grid according to claim 6, characterized in that, Calculate the i1th hub node at the kth position. s The transient voltage instability probability under the first load check point is given by the following formula: Wherein, Ψ(f,i1,k) s ) represents the i1th hub node in the kth typical operating scenario. s The transient voltage instability probability under the first load check point, λ f The probability of new energy output corresponding to the f-th typical operating mode scenario, For the i1th hub node at the kth... s The probability of the first load checkpoint, μ i1 (k s ) = 1 indicates that the i1th hub node is at the kth node. s Transient voltage instability under the first load check point, μ i1 (k s ) = 0 indicates that the i1th hub node is at the kth node. s The transient voltage is stable under the first load check point.

9. A device for assessing the risk of transient voltage instability in a receiving-end power grid, characterized in that, include: The typical operation mode scenario module determines the typical operation mode scenario of the receiving-end power grid based on the different outputs of the new energy clusters and the active power injection of the new energy cluster grid connection points under the basic operation mode of the receiving-end power grid. The hub node module, based on the distribution of load nodes in the receiving-end power grid, determines N, which is not less than a preset voltage level. L_Total For each candidate hub node, based on the equivalent potential of the renewable energy cluster, the equivalent impedance from the renewable energy cluster to the candidate hub node, the equivalent potential of the generator node, and the equivalent impedance from the generator node to the candidate hub node, the short-circuit capacity provided by the generator node and the renewable energy cluster grid connection point to each candidate hub node is calculated. Based on the short-circuit capacity, the hub node in the receiving-end power grid is determined from the candidate hub nodes; where N L_Total The number of candidate hub nodes is preset; hub nodes are load nodes that are prone to causing transient voltage instability in the receiving-end power grid. The transient voltage instability probability module performs time-domain simulations of typical fault sets of the receiving-end power grid for each typical operating mode scenario, determines the transient voltage stability of each hub node, and determines the transient voltage instability probability of each hub node based on the transient voltage stability of each hub node. The risk assessment module assesses the risk of transient voltage instability in the receiving-end power grid based on the probability of transient voltage instability at each hub node under each typical operating mode scenario. In the aforementioned transient voltage instability probability module, for each typical operating mode scenario, time-domain simulation is performed on the typical fault set of the receiving-end power grid to determine the transient voltage stability of each hub node. Based on the transient voltage stability of each hub node, the transient voltage instability probability of each hub node is determined, including: 1) In the f-th typical operating mode scenario, increase the load level of the i1-th hub node according to the preset rules, and determine the various first load verification points of the i1-th hub node; wherein, each first load verification point corresponds to a load level, and the initial value of i1 is 1; 2) Under the k-th type of first load verification point, perform time-domain simulation on the typical fault set of the receiving-end power grid to determine the transient voltage stability of the i1-th hub node under the k-th type of first load verification point; where k is initially 1. 3) If the transient voltage is stable and k+1 is not greater than k end If k = k + 1, go to step 2); If the transient voltage is stable and k+1 is greater than k end Then proceed to step 5); If the transient voltage is unstable, then the transient voltage at all first load checkpoints greater than or equal to k is unstable, and proceed to 4); Where, k end This represents the number of first load checkpoints for the i1th hub node. 4) Based on the possible load level range of the i1th hub node and the load level statistics within the preset historical time period, determine the load level of the i1th hub node in the kth period. s The transient voltage instability probability under the first load check point is shown in section 5); where k s =k, k+1, ..., k end ; 5) If i1+1 is not greater than N L Then i1 = i1 + 1, go to 1); where N L The preset number of hub nodes; If i1+1 is greater than N L Then the process of determining the transient voltage instability probability under the f-th typical operating mode scenario ends.

10. A computer-readable storage medium for storing one or more programs, characterized in that, The one or more programs include instructions that, when executed by a computing device, cause the computing device to perform any of the methods according to claims 1 to 8.

11. A computing device, characterized in that, include: One or more processors, one or more memories, and one or more programs, wherein the one or more programs are stored in the one or more memories and configured to be executed by the one or more processors, the one or more programs including instructions for performing any of the methods according to claims 1 to 8.

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