Object searching method, system and device for power grid stability control strategy and medium

Abstract

The invention discloses an object searching method, system and device for a power grid stability control strategy and a medium. The method comprises the following steps: acquiring the power grid topology and the capacity of each node; determining an input power grid node according to the type of the stability control equipment; based on the input power grid node and the power grid topology, obtaining a risk assessment object set through a breadth-first neighbor expansion strategy; the risk assessment object set is nodes and lines included in a stability control coverage range, and represents an attention range of stability risk analysis; based on the risk assessment object set and the capacity of each node, obtaining a key section object set through a multi-head parallel recursive search strategy; sorting the stations according to the key section object set, and determining a stable control object set; the stable control object set is used for representing a stable control attention range. According to the embodiment of the invention, the stability control strategy making efficiency and the application universality can be improved. The method can be widely applied to the technical field of power grid management and control.

Description

Technical Field

[0001] The present invention relates to the field of power grid control technology, and in particular to an object search method, system, device and medium for a power grid stabilization control strategy. Background Art

[0002] As the scale of my country's power grid continues to expand and the scale of ultra-high voltage and long-distance direct current transmission continues to develop, the types and intensity of disturbances threatening the safe operation of the power grid continue to increase, the system safety and stability risks are more complex, and the safe and stable operation of new power systems is increasingly dependent on safety and stability control systems.

[0003] In the related technology, the control strategy formulation of the safety and stability control system (referred to as stability control strategy) mainly adopts the mode of "offline calculation, online matching". The formulation of the stability control strategy requires manual pre-setting of the operating mode set and the expected fault set. Through a large number of fault simulations and stability risk analysis, the stability control action strategy is summarized and organized, and the coverage and selectivity of the strategy are verified by an exhaustive stability simulation scan. The manual formulation and verification of the stability control strategy is computationally huge and time-consuming, and is often iterated on a yearly basis. This method has become increasingly difficult to meet the safety and stability control needs of new power systems with more complex and changeable operating modes, and constantly evolving dynamic characteristics and instability modes. Summary of the invention

[0004] The purpose of the present invention is to solve one of the technical problems existing in the prior art to at least a certain extent.

[0005] To this end, an object of the present invention is to provide an efficient object search method, system, device and medium for a power grid stabilization strategy.

[0006] In order to achieve the above technical purpose, one aspect of the embodiment of the present invention provides an object search method for a power grid stabilization strategy, including the following steps: obtaining the power grid topology and the capacity of each node; determining the input power grid node according to the type of stabilization equipment; based on the input power grid node and the power grid topology, obtaining a risk assessment object set through a width-first neighbor expansion strategy; the risk assessment object set is the nodes and lines included in the stabilization coverage, characterizing the focus range of the stability risk analysis; based on the risk assessment object set and the capacity of each node, obtaining a key section object set through a multi-head parallel recursive search strategy; the key section object set is used to characterize the maintenance and fault setting focus range; the station is sorted according to the key section object set to determine the stability control object set; the stability control object set is used to characterize the stability control focus range. The embodiment of the present application defines the stability risk analysis focus range, the maintenance and fault setting focus range and the stability control focus range through the risk assessment object set, the key section object set and the stability control object set, respectively, and then formulates the stabilization strategy, which is conducive to improving the efficiency and wide application of the formulation of the stabilization strategy.

[0007] In some embodiments, the object search method for the power grid stabilization strategy of the embodiment of the present invention, based on the input power grid node and the power grid topology, obtains the risk assessment object set through the breadth-first neighbor expansion strategy, including:

[0008] Determine a node adjacent to the input grid node as a first-order node;

[0009] If the search number of layers does not reach the preset number of layers, the nodes adjacent to the current order node will be determined as the next order nodes, until the search number of layers reaches the preset number of layers, duplicate nodes and lines will be screened out to obtain a risk assessment object set.

[0010] In some embodiments, in one embodiment of the present invention, the critical section object set is obtained through a multi-head parallel recursive search strategy based on the risk assessment object set and the capacity of each node, including:

[0011] Determine a starting point set, an aggregation node set, and a power source set according to the risk assessment object set; the aggregation node set and the power source set correspond to each other;

[0012] Search for new nodes and key sections, recursively aggregate node sets and power supply sets, and determine whether to add the key sections to the key section object set based on key section identification indicators.

[0013] In some embodiments, in one embodiment of the present invention, searching for new nodes and key sections, recursively aggregating node sets and power supply sets, and determining whether to add the key sections to the key section object set according to the key section identification index includes:

[0014] Searching in parallel for a second node at the opposite end of a line connected to a node in the current set, adding the second node that does not belong to any of the previous sets to a next set, and determining a line set;

[0015] Adding the lines whose head end nodes in the line set belong to the previous aggregation node set and whose terminal nodes do not belong to the previous aggregation node set to the candidate section subset;

[0016] According to the capacity and the line of the relevant nodes in the candidate section subset, based on the key section discrimination index, determining whether to add the candidate section subset to the key section object set;

[0017] The line set is traversed to aggregate a new aggregation node set and a power source set.

[0018] In some embodiments, in an embodiment of the present invention, the determining whether to add the candidate section subset to the critical section object set based on the capacity and the line of the relevant node in the candidate section subset and the critical section discrimination index comprises:

[0019] Determine the key section identification index according to the installed capacity of the relevant nodes in the candidate section subset, the transmission capacity of the candidate section subset, and the transmission channel of the candidate section subset;

[0020] If the key section identification index meets the preset conditions, the candidate section subset is added to the key section object set.

[0021] In some embodiments, in one embodiment of the present invention, traversing the line set and aggregating a new aggregation node set and a power source set includes:

[0022] If there are a preset number of aggregate node set elements, the aggregate node set elements are merged through line connections in the line set;

[0023] If the third node is connected to the merged aggregate node set element and the third node belongs to the next set, the third node is added to the new aggregate node set, and a corresponding new power source set is generated.

[0024] In some embodiments, in one embodiment of the present invention, the step of sorting the stations according to the key section object set to determine the stable control object set includes:

[0025] If the candidate section subset is added to the key section object set, the control degree of the nodes related to the candidate section subset is updated;

[0026] All nodes of the power grid are sorted in order from large to small or from small to large according to the control degree, and a number of nodes are selected to obtain a stable control object set.

[0027] On the other hand, an embodiment of the present invention proposes an object search system for a power grid stabilization strategy, including:

[0028] The first module is used to obtain the power grid topology and the capacity of each node;

[0029] The second module is used to determine the input grid node according to the type of stabilization equipment;

[0030] The third module is used to obtain a risk assessment object set based on the input power grid node and the power grid topology through a breadth-first neighbor expansion strategy; the risk assessment object set is the nodes and lines included in the stability control coverage, representing the focus range of stability risk analysis;

[0031] The fourth module is used to obtain a critical section object set based on the risk assessment object set and the capacity of each node through a multi-head parallel recursive search strategy; the critical section object set is used to characterize the maintenance and fault setting focus range;

[0032] The fifth module is used to sort the stations according to the key section object set to determine the stable control object set; the stable control object set is used to characterize the stable control focus range.

[0033] On the other hand, an embodiment of the present invention provides an object search device for a power grid stabilization strategy, comprising:

[0034] at least one processor;

[0035] at least one memory for storing at least one program;

[0036] When the at least one program is executed by the at least one processor, the at least one processor implements the above-mentioned object search method for the power grid stabilization strategy.

[0037] On the other hand, an embodiment of the present invention provides a storage medium storing a program executable by a processor, wherein the program executable by the processor is used to implement the above-mentioned object search method for the power grid stabilization strategy when executed by the processor.

[0038] The embodiment of the present application includes at least the following beneficial effects: the method provided by the embodiment of the present invention includes: obtaining the power grid topology and the capacity of each node; determining the input power grid node according to the type of stabilization control equipment; based on the input power grid node and the power grid topology, obtaining a risk assessment object set through a width-first neighbor expansion strategy; the risk assessment object set is the nodes and lines included in the stabilization control coverage, characterizing the focus range of the stability risk analysis; based on the risk assessment object set and the capacity of each node, obtaining a key section object set through a multi-head parallel recursive search strategy; the key section object set is used to characterize the maintenance and fault setting focus range; the station is sorted according to the key section object set to determine the stabilization control object set; the stabilization control object set is used to characterize the stabilization control focus range. The embodiment of the present application defines the stabilization risk analysis focus range, the maintenance and fault setting focus range and the stabilization control focus range through the risk assessment object set, the key section object set and the stabilization control object set, and then formulates the stabilization control strategy, which is conducive to improving the efficiency and wide application of the formulation of the stabilization control strategy. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the embodiments of the present invention or the drawings of related technical solutions in the prior art are introduced below. It should be understood that the drawings introduced below are only for the convenience of clearly describing some embodiments of the technical solutions of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0040] Figure 1 A flow chart of an embodiment of an object search method for a power grid stabilization control strategy provided by the present invention;

[0041] Figure 2 A flow chart of another embodiment of the object search method for the power grid stabilization control strategy provided by the present invention;

[0042] Figure 3 A schematic diagram of power grid connection in an embodiment provided in the present application;

[0043] Figure 4 for Figure 3 Schematic diagram of the process of generating the risk assessment object set under the example;

[0044] Figure 5 for Figure 3 Schematic diagram of the generation process of the key section object set under the example;

[0045] Figure 6 A schematic diagram of the structure of an embodiment of an object search system for a power grid stabilization strategy provided by the present invention;

[0046] Figure 7 A structural schematic diagram of an embodiment of an object search device for a power grid stabilization strategy provided by the present invention. DETAILED DESCRIPTION

[0047] The embodiments of the present invention are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and are not to be construed as limitations of the present invention. For the step numbers in the following embodiments, they are only provided for the convenience of explanation, and the order between the steps is not limited in any way, and the execution order of each step in the embodiment can be adaptively adjusted according to the understanding of those skilled in the art.

[0048] As the scale of my country's power grid continues to expand and the scale of ultra-high voltage and long-distance direct current transmission continues to develop, the types and intensity of disturbances threatening the safe operation of the power grid continue to increase, the system safety and stability risks are more complex, and the safe and stable operation of new power systems is increasingly dependent on safety and stability control systems.

[0049] At present, the formulation of control strategies for safety and stability control systems (referred to as stability control strategies) mainly adopts the mode of "offline calculation, online matching". The formulation of stability control strategies requires manual pre-setting of operating mode sets and expected fault sets. Through a large number of fault simulations and stability risk analysis, the stability control action strategy is summarized and organized, and the coverage and selectivity of the strategy are verified by exhaustive stability simulation scanning. The manual formulation and verification of stability control strategies are computationally intensive and time-consuming, and are often iterated on a yearly basis. This method has become increasingly difficult to meet the safety and stability control needs of new power systems with more complex and changeable operating modes, and whose dynamic characteristics and instability modes are constantly evolving. There is an urgent need to study the automated formulation technology and methods of power grid stability control strategies.

[0050] Aiming at the demand for automated formulation of power system stability control system, the present invention first proposes the definition of the key object set that the stability control strategy focuses on, and then proposes an automatic search method for the risk assessment object set, the key section object set and the stability control object set in the key object set. The technical highlights of the proposed method include: (1) A method for dividing the key object set for stability control strategy research is proposed. The risk assessment object set, the key section object set and the stability control object set are used to define the stability risk analysis focus range, the maintenance and fault setting focus range and the stability control focus range, which can greatly reduce the number of simulation cases in the process of formulating the stability control strategy; (2) Based on the power grid topology, an automatic search algorithm for the key object set based on breadth-first nearest neighbor expansion and multi-head parallel recursive search is proposed.

[0051] The object search method and system for a power grid stabilization strategy proposed in an embodiment of the present invention will be described in detail below with reference to the accompanying drawings. First, the object search method for a power grid stabilization strategy proposed in an embodiment of the present invention will be described with reference to the accompanying drawings.

[0052] Reference Figure 1 In an embodiment of the present invention, an object search method for a power grid stabilization strategy is provided. The object search method for a power grid stabilization strategy in the embodiment of the present invention can be applied to a terminal, or to a server, or can be software running in a terminal or a server, etc. The terminal can be a tablet computer, a laptop computer, a desktop computer, etc., but is not limited thereto. The server can be an independent physical server, or a server cluster or a distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The object search method for a power grid stabilization strategy in the embodiment of the present invention mainly includes the following steps:

[0053] S100: Obtain the power grid topology and the capacity of each node;

[0054] S200: Determine the input grid node according to the type of stabilization control equipment;

[0055] S300: Based on the input grid nodes and the grid topology, a risk assessment object set is obtained through a breadth-first neighbor expansion strategy; the risk assessment object set is nodes and lines included in the stability control coverage, representing the focus range of stability risk analysis;

[0056] S400: Based on the risk assessment object set and the capacity of each node, a critical section object set is obtained through a multi-head parallel recursive search strategy; the critical section object set is used to characterize the focus range of maintenance and fault setting;

[0057] S500: Sort the stations according to the key section object set to determine a stable control object set; the stable control object set is used to characterize a stable control focus range.

[0058] In some possible implementations, the node includes a site, specifically, a power plant, an inverter station, a converter station, etc.

[0059] Optionally, in one embodiment of the present invention, the risk assessment object set is obtained based on the input grid node and the grid topology by a breadth-first neighbor expansion strategy, including:

[0060] Determine a node adjacent to the input grid node as a first-order node;

[0061] If the search number of layers does not reach the preset number of layers, the nodes adjacent to the current order node will be determined as the next order nodes, until the search number of layers reaches the preset number of layers, duplicate nodes and lines will be screened out to obtain a risk assessment object set.

[0062] Optionally, in one embodiment of the present invention, the critical section object set is obtained by a multi-head parallel recursive search strategy based on the risk assessment object set and the capacity of each node, including:

[0063] Determine a starting point set, an aggregation node set, and a power source set according to the risk assessment object set; the aggregation node set and the power source set correspond to each other;

[0064] Search for new nodes and key sections, recursively aggregate node sets and power supply sets, and determine whether to add the key sections to the key section object set based on key section identification indicators.

[0065] Optionally, in one embodiment of the present invention, searching for new nodes and key sections, recursively aggregating node sets and power supply sets, and determining whether to add the key sections to the key section object set according to key section discrimination indicators, includes:

[0066] Searching in parallel for a second node at the opposite end of a line connected to a node in the current set, adding the second node that does not belong to any of the previous sets to a next set, and determining a line set;

[0067] Adding the lines whose head end nodes in the line set belong to the previous aggregation node set and whose terminal nodes do not belong to the previous aggregation node set to the candidate section subset;

[0068] According to the capacity and the line of the relevant nodes in the candidate section subset, based on the key section discrimination index, determining whether to add the candidate section subset to the key section object set;

[0069] The line set is traversed to aggregate a new aggregation node set and a power source set.

[0070] Optionally, in one embodiment of the present invention, the determining whether to add the candidate section subset to the critical section object set based on the capacity and the line of the relevant node in the candidate section subset and the critical section discrimination index comprises:

[0071] Determine the key section identification index according to the installed capacity of the relevant nodes in the candidate section subset, the transmission capacity of the candidate section subset, and the transmission channel of the candidate section subset;

[0072] If the key section identification index meets the preset conditions, the candidate section subset is added to the key section object set.

[0073] Optionally, in one embodiment of the present invention, traversing the line set and aggregating a new aggregation node set and a power source set includes:

[0074] If there are a preset number of aggregate node set elements, the aggregate node set elements are merged through line connections in the line set;

[0075] If the third node is connected to the merged aggregate node set element and the third node belongs to the next set, the third node is added to the new aggregate node set, and a corresponding new power source set is generated.

[0076] Optionally, in one embodiment of the present invention, the step of sorting the stations according to the key section object set to determine the stable control object set includes:

[0077] If the candidate section subset is added to the key section object set, the control degree of the nodes related to the candidate section subset is updated;

[0078] All nodes of the power grid are sorted in order from large to small or from small to large according to the control degree, and a number of nodes are selected to obtain a stable control object set.

[0079] The following is a detailed description of the search method provided by the present application using a specific embodiment:

[0080] About the definition of the key object set of the stability control strategy in this application. Each set of stability control system is customized for the local safety and stability risks in the large power grid, and is highly targeted. In the process of researching and formulating the stability control strategy, it is necessary to avoid the expansion of the problems solved by the stability control strategy and to prevent the omission of the safety risks that should be covered. To realize the automation of the formulation of the stability control strategy, it is first necessary to reasonably define the scope of attention of the safety and stability simulation evaluation, including the nodes and branch operation risks included in the stability control coverage, the line maintenance and unit power generation methods that should be considered, and the control objects that can be included in the control scope. This application defines the concept of key object set. According to the needs of the above three different focus ranges, three sets of sets, namely risk assessment object set, key section object set and stability control object set, are defined in layers, which together constitute the key object set. And an automatic search algorithm for the three sets is proposed.

[0081] On the other hand, the present application provides an automatic search algorithm for the key object set of the stability control strategy. Taking the power grid topology and power plant capacity as input, an automatic search algorithm for the key object set with breadth-first nearest neighbor expansion and multi-head parallel recursive search is proposed, which can automatically search and extract the risk assessment object set, key section object set and stability control object set in the key object set, thereby effectively defining the focus range of stability risk analysis, the focus range of maintenance and fault setting and the focus range of stability control, and greatly reducing the number of simulation cases for the formulation of stability control strategies.

[0082] The concept and division of key object sets for stabilization strategy research:

[0083] Whether it is a DC stabilization system, a regional stabilization system or a power transmission section stabilization system, they are all customized for the safety and stability risks of local areas in large power grids, focusing on solving the safety and stability risks of local areas of the power grid. One of the core issues in realizing the automated formulation of stabilization strategies is how to automatically search and determine the safety and stability issues that need to be solved by the stabilization system through algorithms, greatly narrowing the scope of attention in the formulation of stabilization strategies. To this end, this patent proposes the concept of a key object set for stabilization strategy research and a hierarchical division scheme.

[0084] The key object set for the stability control strategy research is a set of power grid analysis or control objects consisting of power generation stations, DC converter stations, busbars (nodes) and transmission lines, which together constitute the set of power grid equipment that is of interest for the control strategy research of a given stability control system. In some embodiments, this is also the power grid topology.

[0085] According to the different needs of the stabilization strategy, the key object set is set to consist of three hierarchical sets, namely: risk assessment object set Key Section Object Set and stable control object set

[0086] Risk Assessment Object Set It includes all the stations (i.e. nodes in this application) and lines that need to be paid attention to in the formulation and research of stabilization strategies. The transmission line in the The node voltage in the The synchronous instability or power oscillation of the generator as the leading unstable unit requires a targeted solution by the stabilization strategy. The grid operation risks in the process may not be included in the evaluation scope of the stability control strategy.

[0087] Key Section Object Set It is composed of transmission section subsets. The key section object set includes the output section subset. Each transmission section subset consists of One or more circuits form a transmission section. A transmission line can appear in multiple section subsets, but there cannot be two completely equal section subsets. When setting the maintenance operation mode and fault in the process of formulating the stability control strategy, you only need to Select each subset from the cross-section and select any combination of maintenance lines and fault lines. Combinations of maintenance lines and fault lines that do not belong to the cross-section subset do not need to be considered.

[0088] Stability Control Object Set Depend on They include both the dominant regulation object of power generation mode adjustment in stability control research and the control object of export adjustment of stability control strategy.

[0089] Regarding the automatic search algorithm for key object sets, this patent proposes an automatic search algorithm for key object sets based on breadth-first nearest neighbor expansion and multi-head parallel recursive search.

[0090] First, the breadth-first nearest neighbor expansion method is used to automatically search and generate a risk assessment object set. In formulating a stabilization strategy, only The security and stability risks of the objects in the system.

[0091] Secondly, Taking all power plants and DC converter stations in as the starting point, the width-first method is used to search the transmission channel in parallel. In the search process, power plants and DC converter stations are recursively aggregated, and the key section discrimination index M is calculated. The key section discrimination index M is defined as formula (1).

[0092]

[0093] In the formula, C g is the installed capacity of the aggregated power plant / converter station associated with the section, C t is the transmission capacity of the key section, n t is the number of transmission channels. For details on the generation method of sections and aggregated power plants / converter stations, see step 4.2.

[0094] If the critical section meets the set conditions (see step 4.2 for details), the corresponding transmission section subset is added to the critical section object set. At the same time, the power plants and DC converter stations associated with the section subset are recorded, and the plant control degree d of the corresponding power plants and DC converter stations is increased by one.

[0095] Repeat the breadth-first search until all All objects in the search are found. Finally, they are sorted from high to low according to the number of times to form a stable control object set.

[0096] When combining the repair equipment and the faulty equipment in the formulation of the stabilization strategy, you only need to select The control object in the formulation of the stabilization control strategy only needs to be Optimization screening is performed in the algorithm flow chart. Figure 2 Specifically, the steps include:

[0097] Step 4.1 Determine the risk assessment object set using the breadth-first nearest neighbor expansion method

[0098] A core grid node number is input as the algorithm input for the type of stabilization control equipment (i.e., in this application, the input grid node is determined according to the type of stabilization control equipment). For example, for DC stabilization control, the AC node number of the DC converter station is input; for power delivery or regional stabilization control system, the node number of one or more power plant high-voltage busbars is input.

[0099] Take the input node as the starting point N0, let k=0, and the search layer limit value K. Usually, the search layer limit value K can be taken as 4~6.

[0100] Using a breadth-first search strategy, perform the following steps:

[0101] STEP-1: For set N k For each node in the grid, search for its first-order neighbor nodes, that is, all nodes directly connected to it by transmission lines, and execute STEP-2;

[0102] STEP-2: Find all the nodes that do not belong to the set N0~N k Nodes form a set N k+1 , execute STEP-3;

[0103] STEP-3 Check whether k is greater than or equal to the search layer limit K, and the set contains at least one power plant node. If yes, execute STEP-4; if not, set k = k + 1 and execute STEP-1;

[0104] STEP-4: Add all searched power plants, DC converter stations, transmission lines, etc. to the risk assessment object set

[0105] Step 4.2 Multi-head parallel recursive search to form a transmission section set

[0106] The formal description is as follows:

[0107] STEP-5: Set up the transmission section set Empty, All power plants and DC converter station AC nodes in the system are added to the starting point set P0. The plant control degree d of each plant node is set to 0. Start the breadth-first search. For each layer of the new node set P j , and set two sets of interrelated set variables, namely the aggregation node set CL j and CL j The corresponding aggregate power set g j .

[0108] Initialization: Set the count value j = 0, and all power plants and DC converter station AC nodes in P0 are added to the aggregation node set CL0 and the aggregation power source set g0. At this time, each power plant or DC converter station is regarded as an independent subset of CL0 and g0.

[0109] Start a multi-head parallel search.

[0110] STEP-6: Generate a set (corresponding to the starting set in this application) P j+1 In parallel, j For any node a in the (current set), search for the transmission line and the opposite node b to which the node a is connected. In some embodiments, For the peer node b, if it does not belong to P0~P j , then add it to the next level node set P j+1 , (i.e. the second node that does not belong to any set in the previous order is added to the next set); at the same time, the first and last nodes of the corresponding transmission line are recorded in the access set (i.e. the line set in this application) L j ={L m,n}, where m line is P j The nodes in P j or P j+1 Nodes in .

[0111] STEP-7: Search for critical sections.

[0112] About CL j Each subset element CL j,k , from L j Filter out all the head-end nodes belonging to CL j,k , the terminal node does not belong to CL j,k The lines of the section subset are combined to form a candidate section subset. It is determined whether the section subset satisfies the constraints of the following formula (2) or formula (3) (i.e., the preset conditions in this application). If yes, the subset is added to the transmission section set. At the same time, the corresponding g j,k The plant control degree d of each plant node is obtained and operated as shown in formula (4).

[0113] N L≤3 (2)

[0114] M≥0 (3)

[0115] Where N L is the number of outgoing lines from the node, and M is the key section identification index, see formula (1).

[0116] d=d+1 (4)

[0117] STEP-8: Generate set CL j+1 and g j+1 .

[0118] Traverse the set L j If there are two or more (i.e., the preset number in this application is greater than or equal to 2) aggregate node set elements CL j,k Connected together through the transmission line, these aggregate node set elements are merged into one set, and the corresponding power source set element g j,k Also merge into one set, repeat the operation until no new merge occurs. j ) connected to P j+1 The node set in is added to CL as an element (i.e., the third node in this application) j+1 .

[0119] STEP-9: Check If all objects in the search have been found, the search stops. Otherwise, the count value j=j+1, and STEP-6 is executed.

[0120] Step 4.3 Determine the control object set

[0121] For the AC nodes of power plants and DC converter stations in the starting point set P0 in the previous step, sort them from high to low according to their plant control degree d, and according to the upper limit C of the control object set by the stability control system, take the first C power plants and DC converter stations to add to the control object set

[0122] A specific example is used for detailed description: the example system includes 18 nodes, 4 power plant nodes and 2 DC inverter station nodes. The wiring diagram is as follows Figure 3 shown.

[0123] Figure 3 In the example, G1, G2, G3 and G4 are power plants with capacities of 6, 1, 2 and 2 million kilowatts respectively, D1 and D2 are DC inverter stations with capacities of 3 million kilowatts each, and the transmission capacity of each line is 2 million kilowatts. The DC stabilization strategy of D1 is studied in this example. The input node is the DC converter station D1, K=4, C=3. The automatic search calculation process is as follows:

[0124] Step 2.1 Risk assessment object set generate;

[0125] Taking DC converter station D1 as the algorithm input, taking K = 4, and obtaining the risk assessment object set based on the strategy of breadth-first and nearest neighbor expansion The process of obtaining it is as follows Figure 4 shown.

[0126] The line with an arrow indicates that the newly searched node is already in the set and will not be added repeatedly.

[0127] Depend on Figure 4 It can be seen that the risk assessment object set It is formula (5).

[0128]

[0129] Step 2.2 Transmission Section Set generate;

[0130] The process of obtaining Figure 5 As shown in the figure, the numbers next to the lines indicate the number of outgoing lines, and the lines with arrows indicate that the newly searched nodes are already in the set and will not be added repeatedly.

[0131] (STEP-5) Initialization.

[0132] Will All power plants and DC converter station AC nodes in are taken as the starting point set P0, as shown in formula (6).

[0133] P0:{D1,G1,G3,G2,D2}(6)

[0134] The corresponding relationship between the starting aggregation node set CL0 and the corresponding power source set g0 is shown in Table 1.

[0135]

[0136]

[0137] Table 1

[0138] 2.2.1 Execute STEP-6 for the first time;

[0139] (STEP-6) Set the next level node set P1 to be empty and start to improve the set P1. In parallel, for any node a in P0, search for the transmission line connected to node a and the opposite node b.

[0140] The searched line is L0 = {L D1 ,2,L D2 ,5,LD1 ,3,L D1 ,4,L G2 ,2,L G1 ,3,L G3 ,3,L G3 ,1,L G1 ,1,L G1 , 11}

[0141] For the peer node b, if it does not belong to P0, it is added to the next level node set P1.

[0142] Finally, we get P1={4,3,2,1,11,5}.

[0143] (STEP-7) Search for the critical section. In parallel, search for the element CL in the aggregate node set CL0 0,i , if the constraints of the above formula (2) or formula (3) are satisfied, then 0,i The set of connected transmission lines is recorded as a transmission section subset, and the transmission section set is added At the same time, CL 0,i The corresponding power supply set g 0,i The plant control degree d of each plant node included in is operated as formula (4). The specific calculation process is shown in Table 2.

[0144]

[0145]

[0146] Table 2

[0147] (STEP-8) Generate sets CL1 and g1.

[0148] Traverse the set L0, if there are two or more aggregate node set elements CL j,k After being connected together by L0, these aggregate node set elements are merged into one set, and the corresponding power set element g 0,k Also merged into one set (for example, search for L(D1,3)L(G1,3)L(G3,3), connect CL01, CL03, CL04; search for L(D1,2)L(G2,2), connect CL02, CL04. At this time, the four CLs are aggregated into one), repeat the operation until no new merger occurs. All the node sets in P1 connected to the merged aggregate node set nodes (located in set P0) are added as elements to CL1. The specific process is shown in Table 3.

[0149]

[0150] Table 3

[0151] The newly formed aggregation node set CL1 = {CL 1,1 ,CL 1,2}.

[0152] (STEP-9) Inspection Have all the objects in been searched? The objects that have not been searched are:

[0153] {6,7,8,12,L 2,1 ,L 4,12 ,L 4,5 ,L 3,4 ,L 12,11 ,L 5,6 ,L 6,7 ,L 6,8}

[0154] The count value j=j+1, and STEP-6 is executed for the second time.

[0155] 2.2.2 Execute STEP-6 for the second time;

[0156] (STEP-6) Improve the set P2. In parallel, for any node a in P1, search for the transmission line connected to node a and the opposite node b.

[0157] The searched line is L2 = {L 2,1 ,L 4,12 ,L 4,5 ,L 3,4 ,L 12,11 ,L 5,6}

[0158] For the peer node b, if it does not belong to P1, it is added to the next level node set P2.

[0159] Finally, we get P2={12,6}.

[0160] (STEP-7) Search for the critical section. In parallel, search for the element CL in the aggregate node set CL1 1,i , if the following constraints (2) or (3) are satisfied, then 1,i The set of connected transmission lines is recorded as a transmission section subset, and the transmission section set is added At the same time, CL 1,i The corresponding power supply set g 1,i The plant control degree d of each plant node included in is operated as formula (4). The specific process is shown in Table 4.

[0161]

[0162] Table 4

[0163] (STEP-8) Generate sets CL2 and g2.

[0164] Traverse the set L1, if there are two or more aggregate node set elements CL 1,k Connected together through the transmission line, these aggregate node set elements are merged into one set, and the corresponding power source set element g 1,k Also merged into a set, repeat the operation until no new merge occurs. All the node sets in P1 that are connected to the merged aggregate node set nodes (located in set P0) are added as elements to CL2. The specific process is shown in Table 5.

[0165]

[0166] Table 5

[0167] The new aggregate node set CL2 is formed = {CL 2，1}.

[0168] (STEP-9) Inspection Have all the objects in been searched? The objects that have not been searched are:

[0169] {7,8,L 6,7 ,L 6,8};

[0170] The count value j=j+1, and STEP-6 is executed for the third time.

[0171] 2.2.3 Execute STEP-6 for the third time;

[0172] (STEP-6) Improve the set P3. In parallel, for any node a in P2, search for the transmission line connected to the node a and the opposite node b.

[0173] The searched line is L3 = {L 6,7 ,L 6,8}

[0174] For the peer node b, if it does not belong to P2, it is added to the next level node set P3.

[0175] Finally, we get P3={7,8}.

[0176] (STEP-7) Search for the critical section. In parallel, search for the element CL in the aggregate node set CL2 2,i , if the following constraints (2) or (3) are satisfied, then 2,i The set of connected transmission lines is recorded as a transmission section subset, and the transmission section set is added At the same time, CL 2,i The corresponding power supply set g 2,iThe plant control degree d of each plant node included in is operated as formula (4). The specific process is shown in Table 6.

[0177]

[0178] Table 6

[0179] (STEP-8) Generate sets CL3 and g3.

[0180] Traverse the set L3, if there are two or more aggregate node set elements CL 2,k Connected together through the transmission line, these aggregate node set elements are merged into one set, and the corresponding power source set element g 2,k Also merged into a set, repeat the operation until no new merge occurs. (No merge occurs in this operation) All the node sets in P1 that are connected to the merged aggregate node set nodes (located in set P0) are added as elements to CL3. The specific process is shown in Table 7.

[0181]

[0182] Table 7

[0183] The newly formed aggregation node set CL3 = {CL 3，1}.

[0184] (STEP-9) Inspection Have all the objects in the search been found? If all have been found, the process ends.

[0185] 2.3 Control Object Set generate;

[0186] The AC nodes of the power plants and DC converter stations in the starting point set P0 in the previous step are sorted from high to low according to their control degree coefficients. The final values ​​of the plant and station control degrees are shown in Table 8.

[0187] Factory Station Plant control degree <![CDATA[G1]]> 3 <![CDATA[G2]]> 3 <![CDATA[G3]]> 3 <![CDATA[D1]]> 2 <![CDATA[D2]]> 2

[0188] Table 8

[0189] It can be seen that if the upper limit of the control object set by the stability control system is C = 3, the first C power plants and DC converter stations are added to the control object set Control Object Set As shown in formula (14).

[0190]

[0191] In summary, the method provided by the embodiment of the present application includes: obtaining the power grid topology and the capacity of each node; determining the input power grid node according to the type of stabilization control equipment; based on the input power grid node and the power grid topology, obtaining a risk assessment object set through a width-first neighbor expansion strategy; the risk assessment object set is the nodes and lines included in the stabilization control coverage, characterizing the focus range of the stability risk analysis; based on the risk assessment object set and the capacity of each node, obtaining a key section object set through a multi-head parallel recursive search strategy; the key section object set is used to characterize the maintenance and fault setting focus range; the station is sorted according to the key section object set to determine the stabilization control object set; the stabilization control object set is used to characterize the stabilization control focus range. The embodiment of the present application defines the stabilization risk analysis focus range, the maintenance and fault setting focus range and the stabilization control focus range through the risk assessment object set, the key section object set and the stabilization control object set, and then formulates the stabilization control strategy, which is conducive to improving the efficiency and wide application of the formulation of the stabilization control strategy.

[0192] Secondly, refer to the attached Figure 6 An object search system for a power grid stabilization strategy proposed according to an embodiment of the present invention is described.

[0193] Figure 6 1 is a schematic diagram of the structure of an object search system for a power grid stabilization strategy according to an embodiment of the present invention, wherein the system specifically includes:

[0194] The first module 610 is used to obtain the power grid topology and the capacity of each node;

[0195] The second module 620 is used to determine the input grid node according to the type of stabilization control equipment;

[0196] The third module 630 is used to obtain a risk assessment object set based on the input power grid node and the power grid topology through a breadth-first neighbor expansion strategy; the risk assessment object set is the nodes and lines included in the stability control coverage, representing the focus range of stability risk analysis;

[0197] The fourth module 640 is used to obtain a critical section object set based on the risk assessment object set and the capacity of each node through a multi-head parallel recursive search strategy; the critical section object set is used to characterize the maintenance and fault setting focus range;

[0198] The fifth module 650 is used to sort the stations according to the key section object set to determine a stable control object set; the stable control object set is used to characterize the stable control focus range.

[0199] It can be seen that the contents of the above method embodiments are all applicable to the present system embodiments, the functions specifically implemented by the present system embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0200] Reference Figure 7 The embodiment of the present invention provides an object search device for a power grid stabilization strategy, comprising:

[0201] at least one processor 710;

[0202] At least one memory 720, used to store at least one program;

[0203] When the at least one program is executed by the at least one processor 710, the at least one processor 710 implements the object search method for the power grid stabilization strategy.

[0204] Similarly, the contents of the above method embodiments are all applicable to the present device embodiments. The functions specifically implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0205] An embodiment of the present invention further provides a computer-readable storage medium, in which a program executable by a processor is stored. When the program executable by the processor is executed by the processor, it is used to execute the above-mentioned object search method for the power grid stabilization strategy.

[0206] Similarly, the contents of the above method embodiments are all applicable to the present storage medium embodiments. The functions specifically implemented by the present storage medium embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0207] In some selectable embodiments, the function / operation mentioned in the block diagram may not occur in the order mentioned in the operation diagram. For example, depending on the function / operation involved, the two boxes shown in succession can actually be executed substantially simultaneously or the boxes can sometimes be executed in reverse order. In addition, the embodiment presented and described in the flow chart of the present invention is provided by way of example, for the purpose of providing a more comprehensive understanding of technology. The disclosed method is not limited to the operation and logic flow presented herein. Selectable embodiments are expected, wherein the order of various operations is changed and the sub-operation of a part for which is described as a larger operation is performed independently.

[0208] In addition, although the present invention is described in the context of functional modules, it should be understood that, unless otherwise specified, one or more of the functions and / or features can be integrated into a single physical device and / or software module, or one or more functions and / or features can be implemented in a separate physical device or software module. It is also understood that a detailed discussion of the actual implementation of each module is unnecessary for understanding the present invention. More specifically, in view of the properties, functions and internal relationships of the various functional modules in the device disclosed herein, the actual implementation of the module will be understood within the conventional skills of the engineer. Therefore, those skilled in the art can implement the present invention set forth in the claims without excessive experimentation using ordinary techniques. It is also understood that the specific concepts disclosed are merely illustrative and are not intended to limit the scope of the present invention, which is determined by the full scope of the appended claims and their equivalents.

[0209] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several programs to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0210] The logic and / or steps represented in the flowchart or otherwise described herein, for example, may be considered as an ordered list of executable programs for implementing the logical functions, and may be embodied in any computer-readable medium for use by a program execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch and execute a program from a program execution system, device or apparatus), or in conjunction with such program execution systems, devices or apparatuses. For purposes of this specification, a "computer-readable medium" may be any device that can contain, store, communicate, propagate or transmit a program for use by a program execution system, device or apparatus, or in conjunction with such program execution systems, devices or apparatuses.

[0211] More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk case (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be a paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, deciphering or, if necessary, processing in another suitable manner, and then stored in a computer memory.

[0212] It should be understood that the various parts of the present invention can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable program execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0213] In the above description of this specification, the description with reference to the terms "one embodiment / example", "another embodiment / example" or "certain embodiments / examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0214] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the claims and their equivalents.

[0215] The above is a specific description of the preferred implementation of the present invention, but the present invention is not limited to the embodiments. Those skilled in the art may make various equivalent modifications or substitutions without violating the spirit of the present invention. These equivalent modifications or substitutions are all included in the scope defined by the claims of the present invention.

Claims

1. An object search method for a power grid stabilization strategy, characterized in that: The following steps are involved: Obtain the grid topology and capacity of each node; Determine the input grid node according to the type of stabilization equipment; Based on the input grid nodes and the grid topology, a risk assessment object set is obtained through a breadth-first neighbor expansion strategy; the risk assessment object set is nodes and lines included in the stability control coverage, representing the focus range of stability risk analysis; Based on the risk assessment object set and the capacity of each node, a critical section object set is obtained through a multi-head parallel recursive search strategy; the critical section object set is used to characterize the focus range of maintenance and fault setting; The stations are sorted according to the key section object set to determine a stable control object set; the stable control object set is used to characterize the stable control focus range.

2. The object search method for power grid stabilization strategy according to claim 1, characterized in that: The risk assessment object set is obtained based on the input grid node and the grid topology through a breadth-first neighbor expansion strategy, including: Determine a node adjacent to the input grid node as a first-order node; If the search number of layers does not reach the preset number of layers, the nodes adjacent to the current order node will be determined as the next order nodes, until the search number of layers reaches the preset number of layers, duplicate nodes and lines will be screened out to obtain a risk assessment object set.

3. The object search method for power grid stabilization strategy according to claim 1, characterized in that: The critical section object set is obtained based on the risk assessment object set and the capacity of each node through a multi-head parallel recursive search strategy, including: Determine a starting point set, an aggregation node set, and a power source set according to the risk assessment object set; the aggregation node set and the power source set correspond to each other; Search for new nodes and key sections, recursively aggregate node sets and power supply sets, and determine whether to add the key sections to the key section object set based on key section identification indicators.

4. The object search method for power grid stabilization strategy according to claim 3 is characterized in that: The searching for new nodes and key sections, recursively aggregating node sets and power supply sets, and determining whether to add the key sections to the key section object set according to key section identification indicators, includes: Searching in parallel for a second node at the opposite end of a line connected to a node in the current set, adding the second node that does not belong to any of the previous sets to a next set, and determining a line set; Adding the lines whose head end nodes in the line set belong to the previous aggregation node set and whose terminal nodes do not belong to the previous aggregation node set to the candidate section subset; According to the capacity and the line of the relevant nodes in the candidate section subset, based on the key section discrimination index, determining whether to add the candidate section subset to the key section object set; The line set is traversed to aggregate a new aggregation node set and a power source set.

5. The object search method for power grid stabilization strategy according to claim 4, characterized in that: The determining whether to add the candidate section subset to the critical section object set based on the capacity and the line of the relevant node in the candidate section subset and the critical section identification index comprises: Determine the key section identification index according to the installed capacity of the relevant nodes in the candidate section subset, the transmission capacity of the candidate section subset, and the transmission channel of the candidate section subset; If the key section identification index meets the preset conditions, the candidate section subset is added to the key section object set.

6. The object search method for power grid stabilization strategy according to claim 4, characterized in that: The traversing the line set and aggregating a new aggregation node set and a power source set includes: If there are a preset number of aggregate node set elements, the aggregate node set elements are merged through line connections in the line set; If the third node is connected to the merged aggregate node set element and the third node belongs to the next set, the third node is added to the new aggregate node set, and a corresponding new power source set is generated.

7. The object search method for power grid stabilization strategy according to claim 4, characterized in that: The step of sorting the stations according to the key section object set to determine the stability control object set includes: If the candidate section subset is added to the key section object set, the control degree of the nodes related to the candidate section subset is updated; All nodes of the power grid are sorted in order from large to small or from small to large according to the control degree, and a number of nodes are selected to obtain a stable control object set.

8. An object search system for power grid stabilization strategy, characterized in that: include: The first module is used to obtain the power grid topology and the capacity of each node; The second module is used to determine the input grid node according to the type of stabilization equipment; The third module is used to obtain a risk assessment object set based on the input power grid node and the power grid topology through a breadth-first neighbor expansion strategy; the risk assessment object set is the nodes and lines included in the stability control coverage, representing the focus range of stability risk analysis; The fourth module is used to obtain a critical section object set based on the risk assessment object set and the capacity of each node through a multi-head parallel recursive search strategy; the critical section object set is used to characterize the maintenance and fault setting focus range; The fifth module is used to sort the stations according to the key section object set to determine the stable control object set; the stable control object set is used to characterize the stable control focus range.

9. An object search device for a power grid stabilization strategy, characterized in that: include: at least one processor; at least one memory for storing at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the object search method for a power grid stabilization strategy according to any one of claims 1 to 7.

10. A computer-readable storage medium storing a program executable by a processor, characterized in that: The program executable by the processor is used to implement the object search method for a power grid stabilization strategy as described in any one of claims 1 to 7 when executed by the processor.

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