A power grid cascading failure island division recovery method, device and equipment

Abstract

The application relates to a power grid cascading failure island division recovery method, device and equipment, wherein the method comprises the following steps: generating a cascading failure accident chain set based on an accident chain theory; determining a cascading failure scene corresponding to a fault based on the cascading failure accident chain set when the fault occurs; constructing a target function of island division and determining a constraint condition of the target function; solving the target function of island division by using a preset algorithm according to the constraint condition of the target function; and dividing the power system under the cascading failure scene into islands according to the solving result of the target function of island division. The application can improve the safety and reliability of power supply of the power grid.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power distribution network power supply, in particular to a power grid cascading failure island division recovery method, device and equipment. BACKGROUND

[0002] In recent years, power outages have occurred in various countries around the world to varying degrees, seriously affecting the development of the national economy and the stable operation of the power grid. Cascading failure is a small probability and high loss serious event, which refers to the process of continuous failure of other components caused by the removal of one or more components in the system due to failure or other reasons, and is the culprit leading to such events. At present, the research on cascading failure of power systems is mainly based on complex network theory and pattern search theory. In order to solve the influence of wind power output uncertainty on the evolution path of power grid cascading failure, some researchers have considered the uncertainty of wind power output, and used a stochastic power flow algorithm to process wind power output fluctuations, load fluctuations and other uncertain factors, combined with line power probability density and line outage function to establish a line failure outage probability model. Some researchers have established a line vulnerability evaluation index set from the perspectives of line impact and disconnection consequences, and taken the overload risk factor as the weighted breaking probability of the line to identify the weak link of the cascading failure of the power grid and improve the reliability of the risk line. Some researchers have proposed a cascading failure path prediction method for large-scale wind power grid-connected systems considering wind power uncertainty using a probabilistic power flow model, and determined the subsequent failure based on a double-layer multi-objective decision model.

[0003] However, due to the continuous increase in the proportion of renewable energy installed in the power grid, its uncertainty and volatility have also increased the coupling and complexity of the power grid, so the existing technical solutions cannot ensure the power supply reliability of the power grid with a high proportion of renewable energy clusters. SUMMARY

[0004] The technical problem to be solved by the present application is to provide a power grid cascading failure island division recovery method, device and equipment, which can improve the safety and reliability of power grid power supply.

[0005] The technical solution adopted by the present application to solve the technical problem is to provide a power grid cascading failure island division recovery method, comprising the following steps:

[0006] Generating a cascading failure incident chain set based on the incident chain theory;

[0007] When a fault occurs, determining the cascading failure scenario corresponding to the fault based on the cascading failure incident chain set;

[0008] Constructing an objective function for island division and determining the constraint conditions of the objective function;

[0009] Solve the island division target function by using a preset algorithm according to the constraint condition of the target function, and perform island division on the power system under the cascading failure scenario according to the solving result of the island division target function.

[0010] The cascading failure accident chain set is generated based on the accident chain theory, and includes:

[0011] A plurality of groups of distributed resource random output scenarios are generated by using a clustering algorithm, and system power flow distribution of the power system under each group of distributed resource random output scenarios is calculated to obtain random power flow of each line under different scenarios;

[0012] The load rate is used as a judgment standard of the failure occurrence rate, and an initial failure selection index is calculated based on the random power flow of each line under different scenarios;

[0013] The line with the initial failure selection index exceeding a threshold value is selected as an initial failure;

[0014] A cascading failure accident chain set is generated according to all the initial failures.

[0015] The cascading failure accident chain set is generated according to all the initial failures, and includes:

[0016] Each line in all the initial failure lines is traversed;

[0017] It is judged whether the system is stable, if the system is not stable, the explicit failure of the line is determined according to the system power flow distribution, the probability of the implicit failure of the line is calculated, the implicit failure with a probability lower than a threshold value is excluded according to the probability of the explicit failure and the implicit failure, the next level failure line is selected in order of the probability of the explicit failure and the implicit failure, and the step is repeated until the system is stable; if the system is stable, the initial failure line and the selected next level failure line are output as an accident chain.

[0018] The initial failure selection index is calculated by , wherein I i represents the initial failure selection index of the line i, represents the random power flow of the line i under different scenarios, represents the limit transmission power of the line i, L represents a set of lines in the system, max(·) is a maximum value, and mean(·) is an average value.

[0019] The probability of the implicit failure is calculated by q(P i )=k(P i )(1-P act_ref )+(1-k(P i ))P Nact_missThe calculation result is: wherein, q(P i ) is the probability of implicit failure, P act_ref is the average probability of line protection device refusing to act, P Nact_miss represents the average probability of line protection device misacting, k(P i ) represents the relationship between the line transmission power and the probability of line protection action, represents the rated power of the line i; p i0 is the average probability of protection implicit failure.

[0020] The objective function for constructing the island division is wherein, f represents the objective function, N represents the set of loads in the system, y i′ represents whether the load i' is restored to power supply, when y i′ is a first preset value, it represents that the power supply is restored, when y i′ is a second preset value, it represents that the operation is exited; ω i′ represents the weight of the load i', P i′ represents the power value of the load i'.

[0021] The constraint conditions of the objective function include the power balance constraint: The node voltage constraint: U i″,min ≤ U i″ ≤ U i″,max , the branch power constraint: S ≤ S t ≤ S t,max , wherein, P i″ , Q i″ are the active power and the reactive power injected by the node i", respectively, and M is the total number of nodes; U i″ and U j″ are the voltage amplitudes of the node i" and the node j", respectively; G i″j″ , B i″j″ , and α i″j″ are the conductance, the susceptance, and the phase angle difference between the node i" and the node j", respectively; U i″,min and U i″,max represent the maximum and minimum values of the voltage of the node i", respectively; S t is the actual power value of the branch, and S t,max is the maximum power value of the branch.

[0022] Based on the constraint conditions of the objective function, the objective function of the island division is solved by using a discrete binary positive sine cosine algorithm, comprising:

[0023] An initial solution is randomly selected by using the sine cosine algorithm;

[0024] The solved data is discretely processed by using positive and negative information to obtain a discrete solution set.

[0025] Judge the fitness of each individual in all discrete solutions, if the constraints are not met, use the sine function or cosine function and combine the random factor to update the value of the solution, and return to the previous step until the constraints are met; Wherein each solution is an alternative scheme of island division.

[0026] The technical scheme adopted by the present application to solve its technical problems is: provide a kind of power grid cascading failure island division recovery device, including:

[0027] Generation module, for generating cascading failure incident chain set based on incident chain theory;

[0028] Determination module, for determining the cascading failure scenario corresponding to the fault based on the cascading failure incident chain set when the fault occurs;

[0029] Construction module, for constructing the objective function of island division and determining the constraint condition of the objective function;

[0030] Solving module, for solving the objective function of island division according to the constraint condition of the objective function by using a predetermined algorithm, and according to the solving result of the objective function of island division, the power system under cascading failure scenario is implemented to island division.

[0031] The technical scheme adopted by the present application to solve its technical problems is: provide a kind of electronic equipment, including memory, processor and computer program stored on memory and can be run on the processor, when the processor executes the computer program, the steps of the power grid cascading failure island division recovery method are realized.

[0032] The technical scheme adopted by the present application to solve its technical problems is: provide a kind of computer readable storage medium, which stores computer program, when the processor executes the computer program, the steps of the power grid cascading failure island division recovery method are realized.

[0033] Beneficial effects

[0034] Due to the adoption of the above technical scheme, compared with the prior art, the present application has the following advantages and positive effects: the present application generates multiple groups of cascading failure scenarios of high proportion distributed resource cluster access power grid based on incident chain theory, can realize the cascading failure diagnosis and prediction of new energy high proportion power system, and through discrete binary positive cosine algorithm, the power system under the cascading failure scenario is implemented to island division, provides the optimal recovery power supply scheme of non-fault area, improves the safety and reliability of power supply of power grid. BRIEF DESCRIPTION OF DRAWINGS

[0035] Figure 1This is a flowchart of the power grid cascading fault islanding and recovery method according to the first embodiment of the present invention;

[0036] Figure 2 This is a flowchart of generating a chain of cascading failure incidents in the first embodiment of the present invention;

[0037] Figure 3 This is a flowchart of the discrete binary sine and cosine algorithm solution in the first embodiment of the present invention;

[0038] Figure 4 This is a schematic diagram of the power grid interlocking fault islanding and recovery device according to the second embodiment of the present invention. Detailed Implementation

[0039] The present invention will be further illustrated below with reference to specific embodiments. It should be understood that these embodiments are for illustrative purposes only and are not intended to limit the scope of the invention. Furthermore, it should be understood that after reading the teachings of this invention, those skilled in the art can make various alterations or modifications to the invention, and these equivalent forms also fall within the scope defined by the appended claims.

[0040] The first embodiment of the present invention relates to a method for islanding and restoring power grid cascading faults, such as... Figure 1 As shown, the method includes the following steps: generating a cascading failure accident chain set based on the accident chain theory; determining the cascading failure scenario corresponding to the fault based on the cascading failure accident chain set when a fault occurs; constructing an objective function for islanding partitioning and determining the constraints of the objective function; solving the objective function for islanding partitioning using a preset algorithm according to the constraints of the objective function, and performing islanding partitioning on the power system under the cascading failure scenario based on the solution result of the objective function for islanding partitioning. This implementation aims to improve the power supply reliability of the power grid containing a high proportion of renewable energy clusters under cascading failure emergency conditions, realize islanding fault recovery under emergency conditions, and quickly restore the power loss load of non-faulty areas during the fault period, thereby reducing economic losses. Specifically:

[0041] In a cascading failure propagation process, failures are successively eliminated, forming a unidirectional transmission sequence that can be analyzed using the accident chain theory. The accident chain theory states that a large-scale accident is not caused by a single incident, but rather by the simultaneous fulfillment of multiple conditions. When all conditions are met simultaneously, the various links are connected like a chain, triggering the accident. Let the i-th accident chain L be defined. i The expression is:

[0042]

[0043] T ij (j = 1, 2, ..., n) i) is the jth factor causing the accident of the ith accident chain, and all T ij equal to 1 will lead to an accident.

[0044] All the accident chains constitute an accident chain set F, which includes all possible cascading failure conditions:

[0045]

[0046] At the same time, since in the cascading failure condition, all failures occur in a certain order and form a chain with each other, the probability of the occurrence of the accident chain can be expressed as a conditional probability, as follows:

[0047]

[0048] where p(T i2 | T i1 ) represents the probability of the occurrence of T i1 failure under the condition of T i2 failure.

[0049] To study the cascading failure of the power system, it is necessary to first generate an initial fault set. The power system includes various elements, and the probabilities of the occurrence of failures of the elements are different. In the present embodiment, the load rate is used as a criterion for the failure rate, and the lower the load rate of an element, the lower the probability of the occurrence of failure of the element, and the smaller the proportion of the load of the element in the total load of the system, the smaller the propagation probability after the failure. Therefore, the establishment of the initial fault set needs to exclude elements with low failure rates and propagation rates.

[0050] As shown in Figure 2 , the generation of the cascading failure accident chain set specifically includes: generating multiple groups of distributed resource random output scenarios by using a clustering algorithm, and calculating the system power flow distribution under different distributed resource random output scenarios; taking the load rate as a criterion for the failure rate, calculating an initial fault selection index; taking a line with the initial fault selection index exceeding a threshold value as an initial fault, so as to exclude elements with low failure rates; and generating a cascading failure accident chain set according to the initial fault based on the accident chain theory.

[0051] In generating the cascading failure accident chain set based on the accident chain theory according to the initial fault, each line in the line of the initial fault is traversed; it is judged whether the system is stable, if the system is not stable, the explicit fault of the line is determined according to the system power flow distribution and the probability of the implicit fault of the line is calculated, the implicit fault with a probability lower than a threshold is excluded, that is, the element with a low propagation rate can be excluded through the probability of the implicit fault, and the next level fault line is selected in order of probability according to the probability of the explicit fault and the implicit fault, and the step is repeated until the system is stable; if the system is stable, the line of the initial fault and the selected next level fault line are taken as the output accident chain. The judgment basis for the stability of the system is: one: the line is the last level line in the system, two: there is no explicit fault in the next level line after the line and the probability of the hard fault is lower than a threshold. Specifically:

[0052] Firstly, a fuzzy C-means clustering algorithm FCM is used to generate multiple sets of distributed resource random output scenarios, and then the system power flow distribution under different scenarios is calculated. The FCM algorithm is a partition-based clustering algorithm, and its idea is to maximize the similarity between objects divided into the same cluster and minimize the similarity between different clusters. The fuzzy C-means algorithm is an improvement of the ordinary C-means algorithm, and the ordinary C-means algorithm is hard for data partitioning, while FCM is a flexible fuzzy partitioning. Multiple typical scenarios of distributed resource output are generated by FCM clustering algorithm, and the power flow distribution under each scenario is calculated. For convenience of calculation, the elements in the system are regarded as unified lines, and the proportion of element load rate and system total load rate is replaced by the ratio of element load rate and element load rate with the largest expected value in the system. The initial fault selection index is as follows:

[0053]

[0054] Where, I i represents the initial fault selection index of line i, represents the random power flow of line i under different scenarios, represents the limit transmission power of line i, L represents the set of lines in the system, max(·) is the maximum value, and mean(·) is the average value.

[0055] After the initial fault is generated, according to the characteristics of the cascading fault, the fault of a certain line in the system may also trigger a cascading fault. When the i-th order fault occurs, the i+1-th order fault may inevitably occur, such as system overload, line instability, etc., which is called explicit trigger. The i+1-th order fault may also have a certain probability to occur, such as protection refusal or misoperation, etc., which is called implicit trigger. The explicit trigger can be calculated by power flow analysis, and the implicit trigger is calculated by probability. The relationship k(P i ) between the line transmission power and the probability of line protection action is:

[0056]

[0057] wherein, represents the rated power of the line i; p i0 is the average probability of implicit fault of the protection.

[0058] The line fault probability q(P i ) of the circuit breaker misoperation or refusal is:

[0059] q(P i ) = k(P i )(1-P act-ref ) + (1-k(P i ))P Nact_-mis

[0060] wherein, P act_ref is the average probability of refusal of the line protection device, and P Nact_miss represents the average probability of misoperation of the line protection device. Thus, the cascading fault accident chain can be calculated.

[0061] After the fault occurs, the cascading fault scenario corresponding to the fault is determined based on the set of cascading fault accident chains, and then the objective function of island division is constructed, and the objective function of island division is solved by discrete binary positive sine algorithm, so as to realize island division of the power system under the cascading fault scenario.

[0062] In the embodiment, after the fault occurs, the load needs to be restored according to the priority, and different types of loads are divided into first, second and third levels. The first level load is related to the lifeline of national economy and needs to be restored first, while the third level load has lower priority and can be temporarily restored. At the same time, the island division should preferentially restore the concentrated load and cut off the smaller load, so the objective function of island division is:

[0063]

[0064] wherein, f represents the objective function, N represents the set of loads in the system, y i′ represents whether the load i' is restored for power supply, and yi′ For the first preset value, for example, when y i′ = 1, it means to resume power supply, when y i′ is the second preset value, for example, when y i′ = 0, it means to exit operation; ω i′ represents the weight of the load i', P i′ represents the power value of the load i'.

[0065] At the same time, the island needs to meet the constraint condition to keep stable, the constraint condition of the objective function in the embodiment includes:

[0066] Power balance constraint:

[0067]

[0068] Where, P i″ , Q i″ are the active power and reactive power injected by node i", M is the total number of nodes; U i″ and U j″ are the voltage amplitudes of node i" and node j", respectively; G i″j″ , B i″j″ , α i″j″ are the conductance, susceptance and phase angle difference between node i" and node j".

[0069] Node voltage constraint:

[0070] U i″,min ≤ U i″ ≤ U i″,max

[0071] Where, U i″,min and U i″,max represent the maximum and minimum values of the voltage of node i", respectively.

[0072] Branch power capacity constraint:

[0073] S t ≤ S t,max

[0074] Where, S t is the actual power value of the branch, S t,max is the maximum power value of the branch.

[0075] As Figure 3As shown, the embodiment adopts a binary positive sine-cosine algorithm to solve the island division problem, in solving, the sine-cosine algorithm is used to randomly select an initial solution; the obtained data is discretized by positive and negative information to obtain a discrete solution set; the fitness of all individuals is judged, if the constraint is not met, the value of the solution is updated by using the sine function or the cosine function combined with a random factor, and the previous step is returned until the constraint is met; wherein each solution is an alternative scheme for the island division.

[0076] Wherein, when the value of the solution is updated, the updating mode is:

[0077]

[0078] Wherein, Is the position of the i-th dimension of the t-th generation of the current individual; r2 is a random number between 0 and 2π; r3 is a random number between 0 and 2; r4 is a random number between 0 and 1, P i t Indicates the i-th dimension position of the t-th generation optimal individual.

[0079]

[0080] Wherein, a is a constant; t is the current iteration number; T is the maximum iteration number; when r1 is small, the change amount is small each time, which helps to improve the local search ability, and when r1 is large, it helps to improve the global development ability.

[0081] The discrete binary positive sine-cosine algorithm discretizes the obtained data through positive and negative information, and each input and output makes all solutions X(i,j) between [-1,1], to obtain a discrete solution set Y(i,j)

[0082]

[0083]

[0084] The binary positive sine-cosine algorithm obtains the optimal solution of island division of the power grid with high proportion of distributed resource clusters under the condition of chain failure.

[0085] It is not difficult to find that the present application generates multiple groups of chain failure scenarios of high proportion of distributed resource clusters accessing the power grid based on the accident chain theory, can realize the chain failure diagnosis and prediction of the new energy high proportion power system, and performs island division on the power system under the chain failure scenario through the discrete binary positive sine-cosine algorithm, provides an optimal recovery power supply scheme for the non-fault area, and improves the safety and reliability of power supply of the power grid.

[0086] The second embodiment of the present application relates to a power grid chain failure island division recovery device, as shown in the figure, comprising: Figure 4 As shown, comprising:

[0087] generating a cascading failure accident chain set based on an accident chain theory;

[0088] determining, when a fault occurs, a cascading failure scenario corresponding to the fault based on the cascading failure accident chain set;

[0089] constructing a target function of island division and determining a constraint condition of the target function;

[0090] solving the target function of island division by using a preset algorithm according to the constraint condition of the target function, and performing island division on the power system under the cascading failure scenario according to a solving result of the target function of island division.

[0091] The generating module comprises:

[0092] a clustering unit configured to generate multiple groups of distributed resource random output scenarios by using a clustering algorithm, and calculate system power flow distribution of the power system under each group of distributed resource random output scenarios;

[0093] a calculating unit configured to take a load rate as a judgment standard of fault occurrence rate, and calculate an initial fault selection index based on the system power flow distribution;

[0094] an initial fault setting unit configured to take a line whose initial fault selection index exceeds a threshold value as an initial fault;

[0095] a generating unit configured to generate a cascading failure accident chain set according to all the initial faults.

[0096] The generating unit comprises:

[0097] a traversing subunit configured to traverse each line in the lines of all the initial faults;

[0098] a judging subunit configured to judge whether the system is stable, if the system is not stable, determine an explicit fault of the line and calculate a probability of an implicit fault of the line according to the system power flow distribution, exclude the implicit fault whose probability is lower than a threshold value, and select a next level fault line in order according to the probability, and repeat the step until the system is stable, and if the system is stable, output the line of the initial fault and the selected next level fault line as an accident chain.

[0099] The calculating unit calculates an initial fault selection index by wherein, I i represents the initial fault selection index of the line i, represents random power flow of the line i under different scenarios, Let represent the maximum transmission power of line i, L represent the set of lines in the system, max(·) is the maximum value, and mean(·) is the average value.

[0100] The judgment subunit uses q(P) i )=k(P i (1-P) act_ref )+(1-k(P i ))P Nact_miss Calculate the probability of implicit faults, where q(P) i Let P be the probability of a hidden fault. act_ref P represents the average probability of a line protection device failing to operate. Nact_miss k(P) represents the average probability of malfunction of the line protection device. i This represents the relationship between line transmission power and the probability of line protection operation. p represents the rated power of line i; i0 To protect the average probability of implicit faults.

[0101] The solution module includes a construction unit, and the objective function for island partitioning constructed by the construction unit is: Where f represents the objective function, N represents the set of loads in the system, and y i′ Indicates whether power supply has been restored to load i′, when y i′ When y is the first preset value, it indicates that power supply has been restored. i′ When the value is the second preset value, it indicates that the program will exit the run; ω i′ P represents the weight of load i′. i′ This represents the power value of load i′.

[0102] The constraints of the objective function include power balance constraints: Node voltage constraint: U i″,min ≤U i″ ≤U i″,max Branch power approximately Bundle: S t ≤S t,max , where P i″ Q i″ Let U represent the active and reactive power injected into node i″, respectively, and M be the total number of nodes; i″ and U j″ G represents the voltage magnitudes at nodes i″ and j″, respectively; i″j″ B i″j″ ,α i″j″ These represent the conductance, susceptance, and phase angle difference between nodes i″ and j″, respectively; U i″,min and U i″,max S represents the maximum and minimum voltage values ​​at node i″, respectively; tS is an actual power value of the branch t,max Smax is a maximum power value of the branch.

[0103] The solving module further comprises:

[0104] An initial calculation unit is configured to randomly select an initial solution by using a sine-cosine algorithm.

[0105] A discretization unit is configured to discretize the data of the solution by using positive and negative information to obtain a discrete solution set.

[0106] A fitness judgment unit is configured to judge the fitness of each individual in all discrete solution sets, and if the constraint is not met, the value of the solution is updated by using a sine function or a cosine function combined with a random factor, and the discretization unit is returned until the constraint is met, wherein each solution is an alternative scheme of the island division.

[0107] The third embodiment of the present application relates to an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the power grid cascading failure island division recovery method of the first embodiment when the computer program is executed.

[0108] The fourth embodiment of the present application relates to a computer readable storage medium, which stores a computer program, wherein the computer program implements the steps of the power grid cascading failure island division recovery method of the first embodiment when executed by a processor.

[0109] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system or a computer program product. Therefore, the present application can be in the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware aspects. Moreover, the present application can be in the form of a computer program product implemented on one or more computer usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer usable program code. The solutions in the embodiments of the present application can be implemented in various computer languages, such as object-oriented programming language Java and interpreted scripting language JavaScript.

[0110] The present application is described in reference to the flowchart illustrations and / or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams.

[0111] These computer program instructions can also be stored in a computer- readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instructions which implement the functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams.

[0112] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams. Figure 1 one or more functions specified in the flowchart illustrations and / or block diagrams.

[0113] While preferred embodiments of the application have been described, modifications and variations can be apparent to those skilled in the art once aware of the general underlying concepts. Accordingly, the appended claims intend to embrace all such modifications and variations as fall within the scope of the application.

[0114] Obviously, numerous modifications and variations of the present application are possible in light of the above teachings. It is therefore to be understood that within the scope of the appended claims and their equivalents, the application can be practiced otherwise than as specifically described.

Claims

1. A method for power grid cascading failure island partition recovery, characterized in that, Includes the following steps: Based on the accident chain theory, a set of cascading failure accident chains is generated, including: Clustering algorithms are used to generate multiple sets of distributed resource random output scenarios, and the power flow distribution of the power system under each set of distributed resource random output scenarios is calculated to obtain the random power flow of each line under different scenarios. The load factor is used as the criterion for judging the failure rate, and the initial failure selection index is calculated based on the random power flow of each line under different scenarios. The initial fault selection index is defined as the line whose index exceeds the threshold. Generate a cascading fault incident chain set based on all the initial faults, including: Iterate through each of the initial faults mentioned above; Determine if the system is stable. If the system is unstable, determine the probability of explicit faults and implicit faults of the lines based on the system power flow distribution. Based on the probabilities of explicit and implicit faults, eliminate implicit faults with probabilities below a threshold. Select the next level fault line in order of the probability of explicit and implicit faults. Repeat this step until the system is stable. If the system is stable, output the initial fault line and the selected next level fault line as the fault chain. The probability of the implicit failure is calculated by q(P i ) = k(P i )(1-P act_ref ) + (1-k(P i ))P Nact_miss , wherein q(P i ) is the probability of the implicit failure, P act_ref is the average probability of the line protection device refusing to act, P Nact_miss represents the average probability of the line protection device malfunctioning, and k(P i ) represents the relationship between the line transmission power and the probability of the line protection acting. represents the rated power of the line i; This represents the random power flow of line i under different scenarios; p represents the maximum transmission power of line i; i0 To protect the average probability of implicit faults; When a fault occurs, the cascading fault scenario corresponding to the fault is determined based on the set of cascading fault incident chains. Construct the objective function for island partitioning and determine the constraints of the objective function; Based on the constraints of the objective function, the objective function of islanding is solved using a preset algorithm, and based on the solution of the objective function of islanding, islanding is performed on the power system under the cascading failure scenario.

2. The method for islanding and restoring power grid cascading faults according to claim 1, characterized in that, The initial fault selection index is obtained through The calculation yields, where I i Let represent the initial fault selection index for line i, L represent the set of lines in the system, max(·) is to take the maximum value, and mean(·) is to take the average value.

3. The method for islanding and restoring power grid cascading faults according to claim 1, characterized in that, The objective function for constructing island partitioning is: Where f represents the objective function, N represents the set of loads in the system, and y i′ Indicates whether power supply has been restored to load i′, when y i′ When y is the first preset value, it indicates that power supply has been restored. i′ When the value is the second preset value, it indicates that the program will exit the run; ω i′ P represents the weight of load i′. i′ This represents the power value of load i′.

4. The method for islanding and restoring power grid cascading faults according to claim 1, characterized in that, The constraints of the objective function include power balance constraints: Node voltage constraint: U i″,min ≤U i″ ≤U i″,max Branch power constraint: S t ≤S t,max , where P i″ Q i″ Let U represent the active and reactive power injected into node i″, respectively, and M be the total number of nodes; i″ and U j″ G represents the voltage magnitudes at nodes i″ and j″, respectively; i″j″ B i″j″ ,α i″j″ These represent the conductance, susceptance, and phase angle difference between nodes i″ and j″, respectively; U i″,min and U i″,max S represents the maximum and minimum voltage values ​​at node i″, respectively; t S represents the actual power value of the branch. t,max This represents the maximum power value of the branch.

5. The method for islanding and restoring power grid cascading faults according to claim 1, characterized in that, The objective function, based on the constraints of the objective function, is used to solve the objective function for island partitioning using the discrete binary sine and cosine algorithm, including: The initial solution is randomly selected using a sine and cosine algorithm; The obtained data is discretized using positive and negative information to obtain a discrete solution set; Determine the fitness of each individual in all discrete solution sets. If the constraints are not met, update the value of the solution using a sine or cosine function combined with a random factor, and return to the previous step until the constraints are met. Each solution is a candidate scheme for the island partitioning.

6. A power grid interlocking fault islanding recovery device, characterized in that, include: The generation module is used to generate a set of cascading failure accident chains based on the accident chain theory. The generation module includes: Clustering unit is used to generate multiple sets of distributed resource random output scenarios using clustering algorithms, and to calculate the power flow distribution of the power system under each set of distributed resource random output scenarios; The calculation unit is used to use the load rate as the criterion for judging the failure rate and to calculate the initial failure selection index based on the power flow distribution of the system. An initial fault setting unit is used to select lines whose initial fault selection indicators exceed a threshold as initial faults. A generation unit is used to generate a set of cascading fault accident chains based on all the initial faults; the generation unit includes: a traversal subunit, used to traverse each of the lines with all the initial faults; The judgment subunit is used to determine whether the system is stable. If the system is unstable, it determines the probability of explicit line faults and calculates the probability of implicit line faults based on the system power flow distribution. Implicit faults with probabilities below a threshold are eliminated, and the next level of faulty lines are selected in order of probability. This step is repeated until the system is stable. If the system is stable, The initial faulty line and the selected next-level faulty line will then be output as an accident chain. The judgment subunit uses q(P) i )=k(P i (1-P) act_ref )+(1-k(P i ))P Nact_miss Calculate the probability of implicit faults, where q(P) i Let P be the probability of a hidden fault. act_ref P represents the average probability of a line protection device failing to operate. Nact_miss k(P) represents the average probability of malfunction of the line protection device. i This represents the relationship between line transmission power and the probability of line protection operation. This indicates the rated power of line i; This represents the random power flow of line i under different scenarios. p represents the maximum transmission power of line i; i0 To protect the average probability of implicit faults; The determination module is used to determine the cascading failure scenario corresponding to the failure based on the cascading failure accident chain set when the failure occurs. A construction module is used to construct the objective function for island partitioning and determine the constraints of the objective function; The solution module is used to solve the objective function of island partitioning using a preset algorithm based on the constraints of the objective function, and to perform island partitioning on the power system under the cascading failure scenario based on the solution result of the objective function of island partitioning.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the power grid cascading fault islanding and recovery method as described in any one of claims 1-5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the power grid cascading fault islanding and recovery method as described in any one of claims 1-5.

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