A method and device for identifying a dominant instability form of a power grid and a medium

Abstract

This invention discloses a method, device, and medium for determining the dominant instability mode of a power grid. The method includes: after a power grid fault is cleared, identifying key nodes and their associated branches within a preset time window in real time, and collecting the start and end parameter data of each associated branch; calculating a discrimination index for the dominant instability mode of the power grid in real time based on the start and end parameter data of each associated branch; and determining the dominant instability mode of the power grid based on pre-set dominant instability mode criteria and discrimination index.

Description

Technical Field

[0001] This invention relates to the field of large power grid stability analysis and control technology, and more specifically, to a method, device and medium for identifying the dominant instability mode of a power grid. Background Technology

[0002] With the large-scale integration of new energy power generation equipment, the uncertainty of system operation has increased significantly; the integrated characteristics of AC / DC hybrid power grid structures are becoming increasingly prominent, and the impact of a single fault is global; the rising proportion of new loads such as distributed power sources and energy storage is driving load reconfiguration, and load-side power flow exhibits bidirectional characteristics. Against this backdrop, the stability characteristics of the power grid have undergone profound changes, and stability issues remain a key factor threatening the safe operation of the system.

[0003] Transient power angle instability and transient voltage instability are two typical instability modes in AC / DC hybrid power grids. Under large disturbances, power angle and voltage influence and interact with each other, making it difficult to identify the dominant instability mode. This restricts the formulation of effective control strategies. Conducting identification of the dominant instability mode is the premise and foundation for correctly identifying the causes of power system instability and taking targeted emergency control measures.

[0004] Current research focuses on reactive power in wide-area branches, analyzing its spatiotemporal distribution characteristics and differential features under different instability modes. A dominant instability discrimination index, Dru, is constructed by combining the reactive power product and voltage amplitude product at the beginning and end of the branch. However, extensive simulations of actual power grids show that when electrical connections between power plants are too close, interconnected branches may be misidentified as critical branches, leading to misjudgments. In such cases, the Dru index for critical branches fails to accurately reflect the dominant instability mode of the system. Therefore, a more accurate real-time discrimination method for dominant instability modes is urgently needed. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a method, apparatus, and medium for identifying the dominant instability mode of a power grid.

[0006] According to one aspect of the present invention, a method for determining the dominant instability mode of a power grid is provided, comprising:

[0007] After the power grid fault is cleared, the key nodes of the power grid and their associated branches are identified in real time within a preset time window, and the first and last parameter data of each associated branch are collected.

[0008] The dominant instability mode of the power grid is determined in real time based on the first and last parameter data of each associated branch.

[0009] The dominant instability mode of the power grid is determined based on the pre-set dominant instability mode criteria and discrimination indicators.

[0010] Optionally, after a power grid fault is cleared, key nodes of the power grid and their associated branches are identified in real time, including:

[0011] After the power grid fault is cleared, voltage amplitude information of each node at a preset time window is collected.

[0012] Based on the voltage amplitude information at each time point, the node with the lowest voltage amplitude within the preset time window is identified as the critical node, and the associated branches directly connected to the critical node are determined.

[0013] Optionally, the parameter data of the beginning and end of the associated branch include the susceptance to ground, voltage amplitude, and measured reactive power of the beginning and end of the associated branch, and

[0014] The dominant instability mode of the power grid is determined in real time based on the first and last parameter data of each associated branch, including:

[0015] Calculate the charging power of the first and last terminals of each associated branch based on the ground susceptance and voltage amplitude of the first and last terminals.

[0016] Calculate the first and last reactive power of each associated branch based on the measured reactive power at the beginning and end of the associated branch and the first and last charging power at the beginning and end.

[0017] Based on the reactive power flowing at the beginning and end of each associated branch, the discrimination index of the dominant instability mode of the power grid within the preset time window is calculated for each associated branch.

[0018] Optionally, the formula for calculating the discriminant index S is:

[0019]

[0020] in,

[0021]

[0022]

[0023]

[0024] In the formula, Q yA Q is the charging power at the beginning of the associated branch. yB For the end-charging power of the associated branch, B A For the susceptance to ground at the beginning of the associated branch, B B For the susceptance to ground at the end of the associated branch, U A U represents the voltage amplitude at the first node of the associated branch. B Q represents the voltage magnitude at the terminal node of the associated branch. AB For measuring reactive power at the beginning of the associated branch, Q BA For measuring reactive power at the end of the associated branch, Q12 For the reactive power flowing at the beginning of the associated branch, Q 21 The reactive power flowing at the end of the associated branch.

[0025] Optionally, the dominant instability mode of the power grid is determined based on pre-set dominant instability mode criteria and discrimination indicators, including:

[0026] Within a preset time window, if any associated branch satisfies 0.6 < S ≤ 1, the dominant instability mode of the power grid is determined to be the power angle instability mode.

[0027] If all associated branches satisfy 0≤S<0.4 within the preset time window, the dominant instability mode of the power grid is determined to be voltage instability mode.

[0028] Otherwise, data from the next preset time window is collected to determine the dominant instability mode of the power grid.

[0029] According to another aspect of the present invention, a device for determining the dominant instability mode of a power grid is provided, comprising:

[0030] The identification module is used to identify key nodes and their associated branches of the power grid in real time within a preset time window after the power grid fault is cleared, and to collect the first and last parameter data of each associated branch.

[0031] The calculation module is used to calculate the discrimination index of the dominant instability mode of the power grid in real time based on the first and last parameter data of each associated branch;

[0032] The determination module is used to determine the dominant instability mode of the power grid based on pre-set dominant instability mode criteria and discrimination indicators.

[0033] According to another aspect of the present invention, a computer-readable storage medium is provided, the storage medium storing a computer program for performing the methods described in any of the above aspects of the present invention.

[0034] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising: a processor; a memory for storing executable instructions of the processor; the processor being configured to read the executable instructions from the memory and execute the instructions to implement the method described in any of the preceding aspects of the present invention.

[0035] Therefore, this application identifies key nodes and their associated branches in real time; collects the start and end parameter data of key node-associated branches in real time; calculates the dominant instability mode discrimination index in real time; and determines the dominant instability mode in real time. When the system is predicted to be about to become unstable, the dominant mode discrimination result can provide a decision-making basis for emergency control before instability, and can also provide a trigger signal for initiating the stability criterion of the corresponding mode. Control measures are then implemented after the criterion indicates that the system has become unstable. This allows for targeted emergency control measures to reduce the risk of power grid instability. Attached Figure Description

[0036] Exemplary embodiments of the present invention can be more fully understood by referring to the following figures:

[0037] Figure 1 This is a flowchart illustrating a method for determining the dominant instability mode of a power grid provided in an exemplary embodiment of the present invention.

[0038] Figure 2 This is a schematic diagram of an AC / DC hybrid power transmission grid provided in an exemplary embodiment of the present invention;

[0039] Figure 3 a and Figure 3 b are schematic diagrams of the transient response curves of the AC / DC hybrid power transmission grid and the node voltage provided in an exemplary embodiment of the present invention;

[0040] Figure 4 This is a schematic diagram of the discrimination index of the HC associated branch with the lowest voltage point provided in an exemplary embodiment of the present invention;

[0041] Figure 5 This is a schematic diagram of the ZJ Southern Power Grid provided in an exemplary embodiment of the present invention;

[0042] Figure 6 a and Figure 6 b is a schematic diagram of the transient response curves of the power generation angle and node voltage of the ZJ Southern Power Grid provided in an exemplary embodiment of the present invention;

[0043] Figure 7 This is a flowchart illustrating a method for determining the dominant instability mode of a power grid provided in an exemplary embodiment of the present invention.

[0044] Figure 8 This is a schematic diagram of the structure of a power grid dominant instability mode discrimination device provided in an exemplary embodiment of the present invention;

[0045] Figure 9 This is the structure of an electronic device provided in an exemplary embodiment of the present invention. Detailed Implementation

[0046] Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings. It is obvious that the described embodiments are merely some embodiments of the present invention, and not all embodiments of the present invention, and it should be understood that the present invention is not limited to the exemplary embodiments described herein.

[0047] It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps described in these embodiments do not limit the scope of the invention.

[0048] Those skilled in the art will understand that the terms "first," "second," etc., in the embodiments of the present invention are only used to distinguish different steps, devices, or modules, and do not represent any specific technical meaning, nor do they indicate a necessary logical order between them.

[0049] It should also be understood that in the embodiments of the present invention, "multiple" can refer to two or more, and "at least one" can refer to one, two or more.

[0050] It should also be understood that any component, data or structure mentioned in the embodiments of the present invention can generally be understood as one or more unless explicitly defined or given contrary instructions in the context.

[0051] Furthermore, the term "and / or" in this invention is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this invention generally indicates that the preceding and following related objects have an "or" relationship.

[0052] It should also be understood that the description of the various embodiments in this invention emphasizes the differences between the various embodiments, and the similarities or similarities can be referred to each other. For the sake of brevity, they will not be described in detail.

[0053] At the same time, it should be understood that, for ease of description, the dimensions of the various parts shown in the accompanying drawings are not drawn according to actual scale.

[0054] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the invention or its application or use.

[0055] Techniques, methods, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, they should be considered part of the specification.

[0056] It should be noted that similar labels and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be discussed further in subsequent figures.

[0057] The embodiments of this invention can be applied to electronic devices such as terminal devices, computer systems, and servers, and can operate together with a wide range of other general-purpose or special-purpose computing system environments or configurations. Well-known examples of terminal devices, computing systems, environments, and / or configurations suitable for use with electronic devices such as terminal devices, computer systems, and servers include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, handheld or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputer systems, mainframe computer systems, and distributed cloud computing environments including any of the above systems, etc.

[0058] Electronic devices such as terminal devices, computer systems, and servers can be described in the general context of computer system executable instructions (such as program modules) executed by a computer system. Typically, program modules can include routines, programs, object programs, components, logic, data structures, etc., which perform specific tasks or implement specific abstract data types. Computer systems / servers can be implemented in distributed cloud computing environments, where tasks are executed by remote processing devices linked through communication networks. In distributed cloud computing environments, program modules can reside on local or remote computing system storage media, including storage devices.

[0059] Exemplary methods

[0060] Figure 1 This is a flowchart illustrating a method for determining the dominant instability mode of a power grid according to an exemplary embodiment of the present invention. This embodiment can be applied to electronic devices, such as... Figure 1 As shown, the method 100 for determining the dominant instability mode of a power grid includes the following steps:

[0061] Step 101: After the power grid fault is cleared, identify the key nodes of the power grid and their associated branches in real time within a preset time window, and collect the first and last parameter data of each associated branch.

[0062] Step 102: Calculate the discrimination index of the dominant instability mode of the power grid in real time based on the first and last parameter data of each associated branch;

[0063] Step 103: Determine the dominant instability mode of the power grid based on the pre-set dominant instability mode criteria and discrimination indicators.

[0064] Specifically, this invention proposes a method for identifying the dominant instability mode of a power grid based on the associated branches of key nodes. This includes: 1. Real-time identification of key nodes and their associated branches; 2. Real-time acquisition of reactive power measurements at the beginning and end of the associated branches of key nodes; 3. Real-time calculation of dominant instability mode identification indicators; 4. Real-time identification of the dominant instability mode.

[0065] Step 1: Identify key nodes and their associated branches in real time:

[0066] For example, for a 500kV node across the entire network, after fault clearance T th1 Then, the real-time scrolling acquisition window size is T. th2 Node voltage amplitude information; identification [T] th1 ,T th1 +T th2 The node with the lowest voltage amplitude at each time point within the time period is identified as the critical node, and the branch directly connected to it is determined.

[0067] Step 2: Real-time collection of reactive power measurements at the beginning and end of the associated branches of key nodes:

[0068] For each associated branch directly connected to a key node, its head and tail susceptance to ground is obtained for index calculation, and [T] is collected in real time. th1 ,T th1 +T th2 The voltage amplitude U at the starting node of the associated branch within the time period A , End node voltage amplitude U B , First-end measurement of reactive power Q AB Terminal measurement of reactive power Q BA .

[0069] Step 3: Real-time calculation of dominant instability pattern discrimination indicators:

[0070] Calculate [T] using equation (1) th1 ,T th1 +T th2 The charging power Q at the beginning of the associated branch during the time period yA .

[0071]

[0072] In the formula, B A The susceptance to ground at the beginning of the associated branch.

[0073] Calculate [T] using equation (2) th1 ,T th1 +T th2 The end-charge power Q of the associated branch within the time period yB .

[0074]

[0075] In the formula, B B The susceptance to ground at the end of the associated branch.

[0076] Calculate [T] using equation (3) th1 ,Tth1 +T th2 The reactive power Q flowing at the beginning of the associated branch during the time period 12 and end-flow reactive power Q 21 .

[0077]

[0078] Calculate [T] using equation (4) th1 ,T th1 +T th2 The S-index of associated branches within the time period.

[0079]

[0080] Step 4: Real-time identification of dominant instability patterns:

[0081] (1) The dominant mode of instability at the angle of power:

[0082] In [T] th1 ,T th1 +T th2 If any associated branch satisfies equation (5) within a given time period, it can be determined that the power angle is dominant.

[0083] 0.6<S≤1 (5)

[0084] (2) Voltage instability mode is dominant:

[0085] In [T] th1 ,T th1 +T th2 If all associated branches satisfy equation (6) within a given time period, then voltage dominance can be determined.

[0086] 0 ≤ S < 0.4 (6)

[0087] (3) The current dominant unstable pattern is difficult to determine:

[0088] In [T] th1 ,T th1 +T th2 If the associated branch does not meet the above two conditions within the time period, it indicates that the current dominant instability pattern is difficult to determine and it is necessary to jump to the next time moment for continuous determination.

[0089] When a system is predicted to be on the verge of instability, the dominant mode determination result can provide a basis for emergency control decisions before instability occurs, and can also provide a trigger signal for initiating stability criteria for the corresponding mode. Control measures are then implemented only after the criteria indicate that the system has already become unstable. This allows for targeted emergency control measures to reduce the risk of power grid instability.

[0090] Example 1: AC / DC power transmission grid

[0091] AC / DC hybrid power grid structure such as Figure 2 As shown, the sending-end AC grid of the YM to MJ±500kV / 3000MW ultra-high voltage DC (hereinafter referred to as YM DC) is interconnected with the DB main grid through three AC branches: HB-XL-LD-FT, YM-YC-FT, and YM-HC-WL, each with a double-circuit 500kV line.

[0092] Under a certain operating mode, the YM DC power supply delivers 2000MW, while the XL-LD, YC-FT, and YM-HC AC branches deliver a total of 3520MW. At 0.2s, a three-phase permanent short circuit occurs in the YC-FT branch; at 0.3s, the double-circuit line is disconnected, and the YM DC single-pole is blocked. The generator power angle and 500kV node voltage curves are as follows: Figure 3 a and Figure 3 As shown in Figure b, it can be seen from the figure that the power angle of the MD cluster relative to the DB main network cluster continuously increases and loses synchronization. At the same time, the voltage of the entire network also continues to drop and then exhibits periodic large oscillations.

[0093] T th1 The value is 0.10s, T th2 When the value is 0.10s, firstly, based on the real-time acquisition of voltage amplitude information of the 500kV nodes of the entire network by the measuring device, the lowest voltage point at each moment under the time window of [0.40s, 0.50s] is identified as node HC, which is the key node; secondly, the associated branches of the key node HC are YM-HC and WL-HC; then, the S index values ​​of the above two associated branches are calculated according to equations (1)-(4), and the calculation results are as follows. Figure 4 As shown; finally, the dominant instability pattern is judged by combining equations (5)-(6).

[0094] Depend on Figure 4 It can be seen that the S index value of branch YM-HC at each time point is greater than 0.4 and less than 1, which indicates that the above instability mode is dominated by the power angle.

[0095] Example 2: ZJ Southern Power Grid

[0096] The structure of the local AC power grid in southern ZJ is as follows: Figure 5 As shown, there is no direct electrical connection between the 220kV power grids supplied by the 500kV substations DX, NH, HP, and TL; that is, there is no 500kV / 220kV electromagnetic loop network. Due to the heavy load, the local power grid needs to receive a large amount of power from the main grid through the 6 circuits of the 3 branch lines LD-OH, DX-HP, and NH-HP. After a fault impact, there is a problem of voltage instability.

[0097] At 0.5s, a three-phase permanent short circuit occurred on the LD-OH line. At 0.6s, the faulty line and the fault on the other parallel line were cleared. The generator power angle and 500kV node voltage curves are as follows: Figure 6 a and Figure 6 As shown in Figure b, it can be seen from the figure that the ZJ Southern Power Grid will lose voltage stability due to the impact of short-circuit faults and the large-scale power flow transfer.

[0098] T th1 The value is 0.10s, T th2 When the value is 0.10s, firstly, based on the real-time voltage amplitude information of the 500kV nodes of the entire network collected by the measuring device, the lowest voltage point at each moment under the time window of [0.70s, 0.80s] is identified as node LQ, which is the key node; secondly, the associated branch of the key node LQ is found to be TZ-LQ; then, the S index value of the associated branch is calculated according to equations (1)-(4), and the calculation results are as follows. Figure 6 As shown; finally, the dominant instability pattern is judged by combining equations (5)-(6).

[0099] Depend on Figure 7 It can be seen that the S index value of branch TZ-LQ at each time point is less than 0.4 and greater than 0, which indicates that the above instability mode is dominated by voltage.

[0100] Therefore, this application identifies key nodes and their associated branches in real time; collects reactive power measurements at the beginning and end of the associated branches of key nodes in real time; calculates dominant instability mode discrimination indicators in real time; and determines the dominant instability mode in real time. When the system is predicted to be about to become unstable, the dominant mode discrimination results can provide a decision-making basis for emergency control before instability, and can also provide a trigger signal for initiating the stability criteria of the corresponding mode. Control measures are then implemented after the criteria indicate that the system has become unstable. This allows for targeted emergency control measures to reduce the risk of power grid instability.

[0101] Exemplary device

[0102] Figure 8 This is a schematic diagram of the structure of a power grid dominant instability mode discrimination device provided in an exemplary embodiment of the present invention. Figure 8 As shown, the device 800 includes:

[0103] The identification module 810 is used to identify key nodes and their associated branches of the power grid in real time within a preset time window after the power grid fault is cleared, and to collect the first and last parameter data of each associated branch.

[0104] The calculation module 820 is used to calculate the discrimination index of the dominant instability mode of the power grid in real time based on the first and last parameter data of each associated branch.

[0105] The determination module 830 is used to determine the dominant instability mode of the power grid based on the pre-set dominant instability mode criteria and discrimination indicators.

[0106] Optionally, the identification module 810 includes:

[0107] The data acquisition submodule is used to collect voltage amplitude information of each node within a preset time window after the power grid fault is cleared.

[0108] The identification submodule is used to identify the node with the lowest voltage amplitude within a preset time window as the key node based on the voltage amplitude information of each node at each time point, and to determine the associated branches directly connected to the key node.

[0109] Optionally, the parameter data of the beginning and end of the associated branch include the susceptance to ground, voltage amplitude, and measured reactive power of the beginning and end of the associated branch, and

[0110] Calculation module 820 includes:

[0111] The first calculation submodule is used to calculate the first and last charging power of each associated branch based on the first and last susceptance to ground and the voltage amplitude of the associated branch.

[0112] The second calculation submodule is used to calculate the first and last reactive power of each associated branch based on the measured reactive power at the first and last ends of the associated branch and the charging power at the first and last ends.

[0113] The third calculation submodule is used to calculate the discrimination index of the dominant instability mode of the power grid for each associated branch within a preset time window based on the reactive power flow at the beginning and end of each associated branch.

[0114] Optionally, the formula for calculating the discriminant index S is:

[0115]

[0116] in,

[0117]

[0118]

[0119]

[0120] In the formula, Q yA Q is the charging power at the beginning of the associated branch. yB For the end-charging power of the associated branch, B A For the susceptance to ground at the beginning of the associated branch, B B For the susceptance to ground at the end of the associated branch, U A U represents the voltage amplitude at the first node of the associated branch. B Q represents the voltage magnitude at the terminal node of the associated branch. AB For measuring reactive power at the beginning of the associated branch, Q BA For measuring reactive power at the end of the associated branch, Q 12For the reactive power flowing at the beginning of the associated branch, Q 21 The reactive power flowing at the end of the associated branch.

[0121] Optionally, module 830 is defined, including:

[0122] The first determination submodule is used to determine the dominant instability mode of the power grid as the power angle instability mode if any associated branch satisfies 0.6<S≤1 within a preset time window.

[0123] The second determination submodule is used to determine that the dominant instability mode of the power grid is voltage instability mode if all associated branches satisfy 0≤S<0.4 within a preset time window.

[0124] The third determination submodule is used to otherwise collect data from the next preset time window to determine the dominant instability mode of the power grid.

[0125] Exemplary electronic devices

[0126] Figure 9 This is the structure of an electronic device provided in an exemplary embodiment of the present invention. For example... Figure 9 As shown, the electronic device 90 includes one or more processors 91 and memory 92.

[0127] The processor 91 may be a central processing unit (CPU) or other form of processing unit with data processing and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions.

[0128] The memory 92 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 91 may execute the program instructions to implement the methods of the software programs of the various embodiments of the present invention described above, and / or other desired functions. In one example, the electronic device may also include an input device 93 and an output device 94, these components being interconnected via a bus system and / or other forms of connection mechanisms (not shown).

[0129] In addition, the input device 93 may also include, for example, a keyboard, a mouse, etc.

[0130] The output device 94 can output various information to the outside. The output device 94 may include, for example, a display, a speaker, a printer, and a communication network and its connected remote output devices, etc.

[0131] Of course, for the sake of simplicity, Figure 9 Only some of the components of this electronic device relevant to the present invention are shown, omitting components such as buses, input / output interfaces, etc. In addition, the electronic device may include any other suitable components depending on the specific application.

[0132] Exemplary computer program products and computer-readable storage media

[0133] In addition to the methods and apparatus described above, embodiments of the present invention may also be computer program products, which include computer program instructions that, when executed by a processor, cause the processor to perform the steps of the methods according to various embodiments of the present invention described in the "Exemplary Methods" section above.

[0134] The computer program product can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments of the present invention. The programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0135] Furthermore, embodiments of the present invention may also be computer-readable storage media storing computer program instructions thereon, which, when executed by a processor, cause the processor to perform the steps of the methods according to various embodiments of the present invention described in the "Exemplary Methods" section above.

[0136] The computer-readable storage medium may be any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or any combination thereof. More specific examples (a non-exhaustive list) of readable storage media include: an electrical connection having one or more wires, a portable disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof.

[0137] The basic principles of the present invention have been described above with reference to specific embodiments. However, it should be noted that the advantages, benefits, and effects mentioned in the present invention are merely examples and not limitations, and should not be considered as essential features of each embodiment of the present invention. Furthermore, the specific details disclosed above are for illustrative and facilitative purposes only, and are not limitations. These details do not limit the present invention to the necessity of employing the aforementioned specific details.

[0138] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For system embodiments, since they largely correspond to method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0139] The block diagrams of devices, systems, devices, and systems involved in this invention are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, systems, devices, and systems can be connected, arranged, and configured in any manner. Words such as “comprising,” “including,” “having,” etc., are open-ended terms meaning “including but not limited to,” and are used interchangeably with them. The terms “or” and “and” as used herein refer to the terms “and / or,” and are used interchangeably with them unless the context clearly indicates otherwise. The term “such as” as used herein refers to the phrase “such as but not limited to,” and is used interchangeably with it.

[0140] The methods and systems of the present invention may be implemented in many ways. For example, they may be implemented by software, hardware, firmware, or any combination of software, hardware, and firmware. The above-described order of steps for the methods is for illustrative purposes only, and the steps of the methods of the present invention are not limited to the order specifically described above unless otherwise specifically stated. Furthermore, in some embodiments, the present invention may also be implemented as a program recorded on a recording medium, the program comprising machine-readable instructions for implementing the methods according to the present invention. Thus, the present invention also covers recording media storing programs for performing the methods according to the present invention.

[0141] It should also be noted that in the systems, apparatus, and methods of the present invention, the components or steps can be disassembled and / or recombined. These disassemblies and / or recombinations should be considered equivalents of the present invention. The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the invention. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of the invention. Therefore, the invention is not intended to be limited to the aspects shown herein, but rather to be carried out within the widest scope consistent with the principles and novel features disclosed herein.

[0142] The above description has been given for purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of the invention to the forms disclosed herein. Although numerous exemplary aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations thereof.

Claims

1. A method for identifying the dominant instability mode of a power grid, characterized in that, include: After the fault in the power grid is cleared, the key nodes of the power grid and their associated branches are identified in real time within a preset time window, and the first and last parameter data of each associated branch are collected. The first and last parameter data of the associated branch include the first and last susceptance to ground, voltage amplitude and reactive power of the associated branch. The discrimination index of the dominant instability mode of the power grid is calculated in real time based on the first and last parameter data of each associated branch. The dominant instability mode of the power grid is determined based on the pre-set dominant instability mode criterion and the discrimination index. The dominant instability mode of the power grid is determined in real time based on the first and last parameter data of each associated branch, including: Calculate the charging power of the first and last terminals of each associated branch based on the ground susceptance and voltage amplitude of the first and last terminals of the associated branch. Based on the measured reactive power at the beginning and end of the associated branch and the charging power at the beginning and end, calculate the flowing reactive power at the beginning and end of each associated branch; Based on the first and last reactive power flows of each associated branch, calculate the discrimination index of the dominant instability mode of the power grid within the preset time window for each associated branch. The formula for calculating the discriminant index S is as follows: in, In the formula, Q yA Q is the charging power at the beginning of the associated branch. yB For the end-charging power of the associated branch, B A For the susceptance to ground at the beginning of the associated branch, B B For the susceptance to ground at the end of the associated branch, U A U represents the voltage amplitude at the first node of the associated branch. B Q represents the voltage magnitude at the terminal node of the associated branch. AB For measuring reactive power at the beginning of the associated branch, Q BA For measuring reactive power at the end of the associated branch, Q 12 For the reactive power flowing at the beginning of the associated branch, Q 21 Reactive power is flowing at the end of the associated branch; The dominant instability mode of the power grid is determined based on the pre-set dominant instability mode criterion and the discrimination index, including: Within the preset time window, if any associated branch satisfies 0.6 < S ≤ 1, the dominant instability mode of the power grid is determined to be the power angle instability mode. If all associated branches satisfy 0≤S<0.4 within the preset time window, the dominant instability mode of the power grid is determined to be voltage instability mode. Otherwise, data from the next preset time window is collected to determine the dominant instability mode of the power grid.

2. The method according to claim 1, characterized in that, After a power grid fault is cleared, the key nodes of the power grid and their associated branches are identified in real time, including: After the fault in the power grid is cleared, the voltage amplitude information of each time node within the preset time window is collected; Based on the voltage amplitude information at each time point, the node with the lowest voltage amplitude within the preset time window is identified as the key node, and the associated branch directly connected to the key node is determined.

3. A device for determining the dominant instability mode of a power grid, used to implement the method described in any one of claims 1-2, characterized in that, include: The identification module is used to identify key nodes and their associated branches of the power grid in real time within a preset time window after the power grid fault is cleared, and to collect the first and last parameter data of each associated branch. The calculation module is used to calculate the discrimination index of the dominant instability mode of the power grid in real time based on the first and last parameter data of each associated branch; The determination module is used to determine the dominant instability mode of the power grid based on the pre-set dominant instability mode criterion and the discrimination index.

4. The apparatus according to claim 3, characterized in that, The identification module includes: The acquisition submodule is used to acquire voltage amplitude information of each node within the preset time window after the fault in the power grid is cleared. The identification submodule is used to identify the node with the lowest voltage amplitude within the preset time window as the key node based on the voltage amplitude information of each time node, and to determine the associated branch directly connected to the key node.

5. The apparatus according to claim 3, characterized in that, The parameter data of the beginning and end of the associated branch include the susceptance to ground, voltage amplitude, and measured reactive power of the beginning and end of the associated branch, and The calculation module includes: The first calculation submodule is used to calculate the first and last charging power of each associated branch based on the first and last susceptance to ground and the voltage amplitude of the associated branch. The second calculation submodule is used to calculate the first and last flow reactive power of each associated branch based on the measured reactive power at the first and last ends of the associated branch and the charging power at the first and last ends. The third calculation submodule is used to calculate the discrimination index of the dominant instability mode of the power grid for each associated branch within the preset time window based on the first and last reactive power flows of each associated branch.

6. The apparatus according to claim 5, characterized in that, The formula for calculating the discriminant index S is as follows: in, In the formula, Q yA Q is the charging power at the beginning of the associated branch. yB For the end-charging power of the associated branch, B A For the susceptance to ground at the beginning of the associated branch, B B For the susceptance to ground at the end of the associated branch, U A U represents the voltage amplitude at the first node of the associated branch. B Q represents the voltage magnitude at the terminal node of the associated branch. AB For measuring reactive power at the beginning of the associated branch, Q BA For measuring reactive power at the end of the associated branch, Q 12 For the reactive power flowing at the beginning of the associated branch, Q 21 The reactive power flowing at the end of the associated branch.

7. The apparatus according to claim 3, characterized in that, The module to be determined includes: The first determination submodule is used to determine if any associated branch satisfies the preset time window. 0.6＜S≤1 The dominant instability mode of the power grid is determined to be the power angle instability mode. The second determination submodule is used to determine whether all associated branches satisfy the conditions within the preset time window. 0≤S＜0.4 The dominant instability mode of the power grid is determined to be voltage instability. The third determination submodule is used to otherwise collect data from the next preset time window to determine the dominant instability mode of the power grid.

8. A computer-readable storage medium, characterized in that, The storage medium stores a computer program for performing the method described in any one of claims 1-2.

9. An electronic device, characterized in that, The electronic device includes: processor; Memory used to store the processor's executable instructions; The processor is configured to read the executable instructions from the memory and execute the instructions to implement the method described in any one of claims 1-2.

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