Power grid cascading failure blocking method and system based on coordination of VDCOL and current limiting protection

Abstract

A power grid cascading failure blocking method based on VDCOL and current limiting protection coordination, S1 constructs an improved CSEE-FS simulation model containing multi-loop DC and new energy in MATLAB / SIMULINK, the model adopts a doubly-fed wind farm, the wind farm is connected to the grid at the point of interconnection with current limiting protection, the DC module of the model is a conventional HVDC transmission system, and a traditional VDCOL control strategy is adopted; S2, based on the improved CSEE-FS simulation model containing multi-loop DC and new energy, adopts a multi-kink scheme, processes the traditional VDCOL control strategy in multiple segments, and sets the parameter limit range of the improved VDCOL by considering the wind farm low-voltage off-grid protection limit, whether to put into the current limiter protection, and the wind farm low-voltage ride-through limit analysis; S3, based on the power grid cascading failure simulation data and the parameter limit range of the improved VDCOL, the improved VDCOL parameters are obtained by solving through the DCS algorithm. The design can effectively evaluate the blocking of cascading failure of AC / DC hybrid power grid containing new energy.

Description

TECHNICAL FIELD

[0001] The present application relates to a power grid cascading failure blocking method, and in particular to a power grid cascading failure blocking method and system based on coordination of VDCOL and current limiting protection. BACKGROUND

[0002] With the development of social economy and industry, the power grid is constantly advancing towards low carbonization and AC-DC hybridization. While multi-loop DC is being constructed, large-scale new energy is also being connected to the power grid. The high proportion of new energy connection and the construction of multi-loop DC have brought new operating characteristics to the power grid, and the highly complex power grid structure has also led to an increase in power grid safety risks. In recent years, a number of blackouts caused by cascading failures around the world have posed a great threat to the safe and stable operation of the power grid. How to efficiently and accurately prevent, control and even block cascading failures is of great research significance. At present, cascading failure blocking methods mainly focus on traditional AC power grids. Scholars have analyzed the evolution law of cascading failures, refined key events of cascading failures and controlled them.

[0003] The traditional method has low applicability to cascading failures of AC-DC hybrid power grids containing a high proportion of new energy. In the cascading failure evolution of such new power grids, three types of key events, i.e., AC line short-circuit faults, DC commutation failure faults and new energy off-grid faults, interact with each other. Therefore, there is an urgent need for a cascading failure blocking method that considers the interaction between DC commutation failure and new energy off-grid events and a suppression method to solve the above problems existing in the prior art. SUMMARY

[0004] The purpose of the present application is to overcome the problem in the prior art that the traditional cascading failure blocking method cannot effectively block cascading failures of AC-DC hybrid power grids containing a high proportion of new energy. The present application provides a power grid cascading failure blocking method, system, device and storable medium based on coordination of VDCOL and current limiting protection.

[0005] To achieve the above purpose, the technical solution of the present application is as follows:

[0006] In one aspect, the present application provides a power grid cascading failure blocking method based on coordination of VDCOL and current limiting protection, comprising the following steps:

[0007] S1: An improved CSEE-FS simulation model containing multi-loop DC and new energy is constructed in simulation software. The model uses a doubly-fed wind turbine wind farm, the wind farm is connected to current limiting protection at the grid connection point, the DC module of the model is a conventional HVDC transmission system, and a traditional VDCOL control strategy is used;

[0008] S2 Based on the improved CSEE-FS simulation model containing multi-loop DC and new energy, the multi-kink scheme is adopted to process the traditional VDCOL control strategy in multiple segments, and the parameter limit range of the improved VDCOL is set by considering the wind farm low-voltage off-grid protection limit, whether to put into the current limiter protection, and the wind farm low-voltage ride-through limit analysis.

[0009] S3 Based on the grid cascading failure simulation data and the parameter limit range of the improved VDCOL, the improved VDCOL parameters are obtained by solving the DCS algorithm.

[0010] In S2, the segmented function expression of the improved VDCOL is as follows:

[0011]

[0012] In the formula, I ord is the DC current instruction value; I n is the DC current rated value; U dc is the DC voltage; U max is the upper limit of the VDCOL strategy starting voltage, U min is the lower limit of the VDCOL strategy starting voltage; k is the minimum DC current coefficient; U1 to U5 are the newly added 1 to 5 kinks; k1 to k6 are the slope constants of 1 to 6 segments;

[0013] The target function expression is as follows:

[0014] minf = ∫|U L (t) - U N |dt

[0015] In the formula, U L (t) is the converter bus voltage at time t, and U N is the converter bus voltage rated value.

[0016] Considering the reactive power compensation device and the reactive power characteristics of the converter station, the maximum value range constraint of the improved VDCOL control parameters DC voltage and DC current is obtained as follows:

[0017]

[0018] In the formula, U max is the upper limit of the VDCOL strategy starting voltage, and I ord.max is the upper limit of the VDCOL strategy starting current.

[0019] Therefore, the minimum value range constraint of the improved VDCOL control parameters DC voltage and DC current is as follows:

[0020]

[0021] In the formula, Umin The lower voltage limit for starting the VDCOL strategy; I ord.min The lower limit of the startup current for the VDCOL strategy.

[0022] Consider the wind farm low voltage disconnection protection limit:

[0023] The DC voltage and the wind farm grid connection point voltage affect each other during a fault:

[0024]

[0025] Where, P f ne , Q f ne Respectively represent the active power and reactive power of the wind farm after the fault; P ne , Q ne Represent the active power and reactive power of the wind farm respectively; ΔP f ne , ΔQ f ne They represent the changes in active power and reactive power of the wind farm caused by the fault; P f ac , Q f ac Respectively represent the active power and reactive power of the AC system after the fault; P ac , Q ac Represent the active power and reactive power of the AC system respectively; ΔP d , ΔQ d They represent the changes in active power and reactive power of the DC converter station caused by the fault; ΔQ f ac They represent the reactive power change of the AC system caused by the fault;

[0026] DC voltage after fault U f dc And the voltage U of the wind farm grid connection point f ne It can be expressed as:

[0027]

[0028] Where U f dc Represents the DC voltage after the fault; U f ac Represents the voltage of the AC system after the fault; They represent the vertical component and the horizontal component of the voltage drop of the AC system after the fault respectively; U f ne Represents the voltage at the wind farm grid connection point after the fault; respectively represent the vertical component of voltage drop and the horizontal component of voltage drop at the wind farm grid-connected point after fault;

[0029] At this time, if the current limiter protection is not put into operation, the wind farm bus voltage is the wind farm grid-connected point voltage; after the current limiter protection is put into operation, the wind farm bus voltage is:

[0030]

[0031] wherein, U rf ne is the wind farm bus voltage after the current limiter protection is put into operation, I s is the stator side current of the wind farm unit, R FCL is the resistance value of the current limiter, k t is the transformer ratio of the wind farm grid-connected transformer;

[0032] Considering the wind farm low voltage ride through limit is:

[0033] U ne = I s R FCL / k t 2 + U s ≥ U ne.min

[0034] wherein, U ne is the wind farm bus voltage, I s is the stator side current of the wind farm unit, R FCL is the resistance value of the current limiter, k t is the transformer ratio of the wind farm grid-connected transformer, U s is the terminal voltage of the wind farm unit, U ne.min is the lowest voltage of the wind farm.

[0035] S301, randomly generate a solution matrix X in the parameter limit range of the improved VDCOL, each solution in the solution matrix X represents a set of improved VDCOL model parameters, and then enter step S302 to start iteration;

[0036] S302, according to the objective function values of each solution in the solution matrix X, sort the solutions in descending order of the objective function values, and then enter step S303;

[0037] S303, according to the sorting result of the solutions, calculate the differentiated knowledge acquisition index of each solution, and then enter step S304;

[0038] According to the sorting result of the solutions, the differentiated knowledge acquisition index of the i-th solution includes:

[0039]

[0040] Where η i,t is the differential knowledge acquisition index of the i-th solution; U(0,1) is a random number uniformly distributed in the range [0,1]; is the degree of imperfect knowledge of the i-th solution; the symbol [] indicates the rounding down operation; the symbol Represents the judgment formula Is it established? If so, The value of is 0, if it is not true, the value of is 1; R i,t is the ranking of the i-th solution among all solutions; N is the total number of solutions in the solution matrix X;

[0041] S304: Update each solution according to its differentiated knowledge acquisition index, and then proceed to step S305;

[0042] Based on the differentiated knowledge acquisition index of each solution, updates to each solution include:

[0043] According to the differential knowledge acquisition index of each solution, the solutions are ranked in order from low to high.

[0044] For the solutions ranked in the bottom P%, the solutions are updated according to the following formula:

[0045] v i,d =ωx best,d +λ t (x r2,d -x i,d )+ω i,t (x r1,d -x i,d )

[0046] Where, v i,d is the updated i-th solution, which is the solution ranked in the bottom P% of the differential knowledge acquisition index; ω is the cognitive weight of the optimal solution; ω i,t is the cognitive weight of the ith solution; x best,d is the optimal solution, which is the solution with the minimum objective function value in the solution matrix X; t is the update index, x r2,d is the random solution ranked in the top (1-P)% of the differential knowledge acquisition index, x r1,d To obtain the differential knowledge index ranking in the last P% of random solutions, x i,d is the i-th solution before updating;

[0047] For the solution ranked in the front (1-P) %, the solution is updated according to the following formula:

[0048] v j,d = x s1,d + LK (α, σ)

[0049] wherein v j,d is the updated jth solution, the jth solution is the solution ranked in the front (1-P) %, x s1,d is the random solution ranked in the front (1-P) %, and LK (α, σ) is a random number satisfying the linnik distribution;

[0050] S305, judge whether the iteration time reaches the preset time threshold, if the preset time threshold is reached, stop iteration, after stopping iteration, obtain the optimal solution objective function as the fitness, if the fitness is less than 1, determine that the optimization converges, and enter step S306, if the fitness is greater than 1, the convergence fails, and return to step S301, if the preset time threshold is not reached, return to step S302 and continue iteration;

[0051] S306, select the solution corresponding to the minimum objective function value in the iteration results.

[0052] In another aspect, the present application provides a power grid cascading failure blocking system based on VDCOL and current limiting protection coordination, comprising a simulation model construction module, an improved VDCOL construction module and a parameter solving module;

[0053] The simulation model construction module is used to construct an improved CSEE-FS simulation model containing multi-loop DC and new energy in simulation software, the model adopts a doubly-fed wind turbine wind farm, the wind farm is connected to the current limiting protection at the grid connection point, the DC module of the model is a conventional high-voltage DC power transmission system, and the traditional VDCOL control strategy is adopted;

[0054] The improved VDCOL construction module is used to be based on the improved CSEE-FS simulation model containing multi-loop DC and new energy, adopt a multi-kink scheme, perform multi-segment processing on the traditional VDCOL control strategy, analyze and set the parameter limit range of the improved VDCOL by considering the wind farm low-voltage off-grid protection limit, whether to put into the current limiter protection, and the wind farm low-voltage ride-through limit;

[0055] The parameter solving module is used to solve the improved VDCOL parameters by DCS algorithm based on the power grid cascading failure simulation data and the parameter limit range of the improved VDCOL.

[0056] The segmented function expression of the multi-kink improved VDCOL is as follows:

[0057]

[0058] In the formula, I ord is a direct current command value; I n is a direct current rated value; U dc is a direct current voltage; U max is an upper limit of a VDCOL strategy starting voltage, U min is a lower limit of a VDCOL strategy starting voltage; k is a minimum direct current coefficient; U1 to U5 are one to five new inflection points; k1 to k6 are one to six segment slope constants;

[0059] The objective function expression is as follows:

[0060] minf = ∫|U L (t) - U N |dt

[0061] In the formula, U L (t) is a converter bus voltage at time t, U N is a converter bus voltage rated value;

[0062] Considering the reactive power compensation device and the reactive power characteristics of the converter station, the maximum value range constraint of the improved VDCOL control parameters of the direct current voltage and the direct current is obtained as follows:

[0063]

[0064] In the formula, U max is an upper limit of a VDCOL strategy starting voltage, I ord.max is an upper limit of a VDCOL strategy starting current;

[0065] Therefore, the minimum value range constraint of the improved VDCOL control parameters of the direct current voltage and the direct current is as follows:

[0066]

[0067] In the formula, U min is a lower limit of a VDCOL strategy starting voltage, I ord.min is a lower limit of a VDCOL strategy starting current.

[0068] Considering the low-voltage off-grid protection limit of the wind farm:

[0069] The direct current voltage and the wind farm grid connection point voltage influence each other during the fault:

[0070]

[0071] In the formula, P f ne , Q f neP, Q represent active power and reactive power of the wind farm after fault respectively; ne ne P, Q represent active power and reactive power of the wind farm respectively; f ne P, Q represent active power and reactive power of the wind farm respectively; f ne P, Q represent active power and reactive power of the wind farm respectively; f ac P, Q represent active power and reactive power of the wind farm respectively; f ac P, Q represent active power and reactive power of the AC system after fault respectively; ac ac P, Q represent active power and reactive power of the AC system respectively; d d P, Q represent active power and reactive power of the AC system respectively; f ac P, Q represent reactive power variation of the AC system caused by fault respectively;

[0072] DC voltage U f dc and wind farm grid-connection point voltage U f ne may be expressed as:

[0073]

[0074] In the formula, U f dc represents DC voltage after fault; U f ac represents voltage of the AC system after fault; U, U represent vertical component and horizontal component of voltage drop of the AC system after fault respectively; f ne represents wind farm grid-connection point voltage after fault; U, U represent vertical component and horizontal component of voltage drop of the wind farm grid-connection point after fault respectively;

[0075] At this time, if the current limiter protection is not put into operation, the wind farm bus voltage is the wind farm grid-connection point voltage; after the current limiter protection is put into operation, the wind farm bus voltage is:

[0076]

[0077] In the formula, U rf ne is wind farm bus voltage after the current limiter protection is put into operation, I s is wind farm unit stator side current, R FCL is resistance value of the current limiter, and k t ​​​Ratio of wind farm grid-connected transformer;

[0078] Considering the low voltage ride through limit of the wind farm as:

[0079] U ne =I s R FCL / k t 2 +U s ≥U ne.min

[0080] In the formula, U ne is the bus voltage of the wind farm, I s is the stator side current of the wind farm unit, R FCL is the resistance value of the current limiter, k t is the ratio of the wind farm grid-connected transformer, U s is the terminal voltage of the wind farm unit, U ne.min is the minimum voltage of the wind farm.

[0081] S301, randomly generate a solution matrix X in the parameter limit range of the improved VDCOL, each solution in the solution matrix X represents a set of improved VDCOL model parameters, and then proceed to step S302 to start iteration;

[0082] S302, according to the objective function values of each solution in the solution matrix X, sort the solutions in descending order of the objective function values, and then proceed to step S303;

[0083] S303, according to the sorting result of the solutions, calculate the differentiated knowledge acquisition index of each solution, and then proceed to step S304;

[0084] According to the sorting result of the solutions, the differentiated knowledge acquisition index of the i-th solution includes:

[0085]

[0086] In the formula, η i,t is the differentiated knowledge acquisition index of the i-th solution; U(0,1) is a random number uniformly distributed in the range [0,1]; is the degree of imperfection of the knowledge of the i-th solution; the symbol [] represents the down rounding operation; the symbol represents whether the judgment formula is true, if true, the value of is 0, if not true, the value of is 1; R i,t is the ranking of the i-th solution among all solutions; N is the total number of solutions in the solution matrix X;

[0087] S304, updating each solution according to the differentiated knowledge acquisition index of each solution, and then entering step S305;

[0088] updating each solution according to the differentiated knowledge acquisition index of each solution comprises:

[0089] ordering each solution according to the differentiated knowledge acquisition index of each solution in descending order of the differentiated knowledge acquisition index;

[0090] updating the solution ranked in the last P% according to the following formula:

[0091] v i,d = ωx best,d + λ t (x r2,d - x i,d ) + ω i,t (x r1,d - x i,d )

[0092] wherein v i,d is the updated ith solution, the ith solution is the solution ranked in the last P% of the differentiated knowledge acquisition index; ω is the cognitive weight of the optimal solution; ω i,t is the cognitive weight of the ith solution; x best,d is the optimal solution, which is the solution with the minimum objective function value in the solution matrix X; λ t is the updating index, x r2,d is a random solution ranked in the first (1-P)% of the differentiated knowledge acquisition index, x r1,d is a random solution ranked in the last P% of the differentiated knowledge acquisition index, and x i,d is the ith solution before updating;

[0093] updating the solution ranked in the first (1-P)% according to the following formula:

[0094] v j,d = x s1,d + LK(α, σ)

[0095] wherein v j,d is the updated jth solution, the jth solution is the solution ranked in the first (1-P)%, x s1,d is a random solution ranked in the first (1-P)%, and LK(α, σ) is a random number satisfying a linnik distribution;

[0096] S305, judging whether the iteration time reaches a preset time threshold, if the preset time threshold is reached, stopping iteration, obtaining the optimal solution target function as fitness after stopping iteration, if the fitness is less than 1, judging that optimization converges, and entering step S306, if the fitness is greater than 1, failing to converge, and returning to step S301, if the preset time threshold is not reached, returning to step S302 and continuing iteration;

[0097] S306, selecting the solution corresponding to the minimum target function value in the iteration results.

[0098] In another aspect, the present application provides a power grid cascading failure blocking device based on VDCOL and current limiting protection coordination, comprising a processor and a memory;

[0099] The memory is used for storing computer program codes and transmitting the computer program codes to the processor;

[0100] The processor is used for executing the foregoing power grid cascading failure blocking method based on VDCOL and current limiting protection coordination according to the instructions in the computer program codes.

[0101] In another aspect, the present application provides a computer storage medium, which stores computer programs, and the computer programs are executed by a processor to realize the steps of the foregoing power grid cascading failure blocking method based on VDCOL and current limiting protection coordination.

[0102] Compared with the prior art, the present application has the following beneficial effects:

[0103] 1. The power grid cascading failure blocking method based on VDCOL and current limiting protection coordination divides the conventional linear VDCOL control link into multiple segments through multiple inflection points, utilizes different stage slopes to improve the flexibility of the control link, and strengthens the fault blocking effect.

[0104] 2. The power grid cascading failure blocking method based on VDCOL and current limiting protection coordination comprehensively considers the influence of the VDCOL parameter limitation based on the reactive power characteristics analysis of the converter station and the reactive power compensation device and the control strategy cooperation limiter on the voltage of the wind farm bus as a constraint condition, optimizes the recovery regulation ability of the direct current and the surrounding voltage in the fault process through the reactive power characteristic analysis strategy, further strengthens the low voltage ride through capability of the wind turbine by considering the cooperation influence of the limiter protection, and facilitates better combination of the optimal parameters.

[0105] 3, The application is a power grid cascading failure blocking method based on VDCOL and current limiting protection coordination, which optimizes the multi-end control parameters of VDCOL by using a DCS algorithm, the algorithm is based on the proposed double-strategy method to improve the decision efficiency, and simultaneously simulates the balanced divergence and convergence thinking iterative cycle within the team framework based on the differentiated knowledge acquisition process and retrospective evaluation support. By using the differentiated knowledge acquisition and creative realism concept, the search efficiency and accuracy of the algorithm are further improved. The application further improves the adaptability of the control strategy to the fault by setting the upper and lower limits of each segment function of VDCOL as optimization variables, and can effectively improve the effect of the control strategy. BRIEF DESCRIPTION OF DRAWINGS

[0106] Figure 1 is the multi-kink improved VDCOL characteristic diagram built by the application.

[0107] Figure 2 is a DCS algorithm diagram used by the application.

[0108] Figure 3 is a system topology diagram of embodiment 1 of the application.

[0109] Figure 4 is a current limiter installation diagram of embodiment 1 of the application.

[0110] Figure 5 is a DCS algorithm and PSO algorithm convergence curve comparison diagram of embodiment 1 of the application.

[0111] Figure 6 is a cascading failure wind farm off-grid link blocking diagram of embodiment 1 of the application.

[0112] Figure 7 is a cascading failure DC blocking link blocking diagram of embodiment 1 of the application

[0113] Figure 8 is a schematic diagram of the equipment of the application. DETAILED DESCRIPTION

[0114] The application will be further described in detail in combination with the description of the drawings and specific embodiments.

[0115] Embodiment 1:

[0116] A power grid cascading failure blocking method based on VDCOL and current limiting protection coordination comprises the following steps:

[0117] Referring to Figures 1-4, S1 constructs an improved frequency stability standard simulation model (Chinese Society for Electrical Engineering-Frequency Stability, CSEE-FS) containing multi-loop DC and new energy in MATLAB / SIMULINK, the model adopts a doubly-fed wind farm as a representative of new energy, the wind farm grid-connected point is connected to a current limiter protection, the DC module of the model is a conventional high-voltage direct current transmission system (Line-commuted Converter-High Voltage Direct Current Transmission, LCC-HVDC), and a traditional VDCOL control strategy is adopted;

[0118] S2, based on the improved CSEE-FS simulation model containing multi-loop DC and new energy, adopts a multi-kink scheme to process the traditional VDCOL control strategy in multiple segments, sets the parameter range of each kink point through reactive power characteristic analysis of the converter station and the reactive power compensation device, and considers whether to input the current limiter protection and the low-voltage ride-through limit of the wind farm;

[0119] The segmented function expression of the traditional VDCOL is as follows:

[0120]

[0121] In the formula, I ord is a DC current instruction value; I n is a DC current rated value; U dc is a DC voltage; U max is a VDCOL strategy starting voltage upper limit, U min is a VDCOL strategy starting voltage lower limit; k is a minimum DC current coefficient; k I is a slope constant;

[0122] The segmented function expression of the improved VDCOL with multiple kinks is as follows:

[0123]

[0124] In the formula, U1 to U5 are one to five new DC voltage kinks; k1 to k6 are one to six segment slope constants;

[0125] The target function expression is as follows:

[0126] min f = ∫|U L (t)-U N |dt (3)

[0127] In the formula, U L (t) is a converter bus voltage at t time, UN For the commutation bus voltage rating;

[0128] Considering the reactive power compensation device and the reactive power characteristics of the converter station:

[0129] Q F = ωC R U acR (4)

[0130]

[0131] In the formula, Q F is the reactive power provided by the reactive power compensation device, ω is the angular frequency, C R is the equivalent capacitance of reactive power consumption, U acR is the AC system voltage, Q R is the reactive power consumed by the converter station, N P is the number of poles, k is the transformer ratio of the converter transformer, U L is the commutation bus voltage, α is the advance trigger angle, X C is the commutation reactance, I ord.max is the upper limit of the starting current of the VDCOL strategy, I ord.min is the lower limit of the starting current of the VDCOL strategy, α min is the minimum trigger angle, U max is the upper limit of the starting voltage of the VDCOL strategy, U min is the lower limit of the starting voltage of the VDCOL strategy;

[0132] Therefore, in order to minimize the reactive power absorbed by the converter station from the AC power grid, the improved VDCOL control parameter DC voltage and DC current maximum value range constraint is:

[0133]

[0134] In which, U max is the upper limit of the starting voltage of the VDCOL strategy, I ord.max is the upper limit of the starting current of the VDCOL strategy;

[0135] Therefore, the improved VDCOL control parameter DC voltage and DC current minimum value range constraint is:

[0136]

[0137] In which, U min is the lower limit of the starting voltage of the VDCOL strategy; I ord.min is the lower limit of the starting current of the VDCOL strategy;

[0138] Considering the wind farm low voltage off-grid protection limit:

[0139] When the DC transmission system encounters commutation failure, the original reactive power compensation supply is unbalanced; the DC side absorbs reactive power from the adjacent power grid, causing voltage drop, which makes the voltage U ne Further reduction, thus entering the low voltage ride through (LVRT) stage, so further considering the interaction between DC voltage and wind farm grid connection point voltage during fault:

[0140]

[0141] In the formula, P f ne , Q f ne represent the active power and reactive power of the wind farm after the fault respectively; P ne , Q ne represent the active power and reactive power of the wind farm respectively; ΔP f ne , ΔQ f ne represent the active power and reactive power change of the wind farm caused by the fault respectively; P f ac , Q f ac represent the active power and reactive power of the AC system after the fault respectively; P ac , Q ac represent the active power and reactive power of the AC system respectively; ΔP d , ΔQ d represent the active power and reactive power change of the DC converter station caused by the fault respectively; ΔQ f ac represent the reactive power change of the AC system caused by the fault respectively;

[0142] The DC voltage U f dc and the wind farm grid connection point voltage U f ne after the fault can be expressed as:

[0143]

[0144] In the formula, U f dc represents the DC voltage after the fault; U f ac represents the voltage of the AC system after the fault; represents the vertical component of the voltage drop of the AC system after the fault, and U f ne represents the voltage of the wind farm grid connection point after the fault; respectively represent the vertical component of voltage drop and the horizontal component of voltage drop at the wind farm grid-connection point after fault;

[0145] At this time, if the current limiter protection is not put into operation, the wind farm bus voltage is the wind farm grid-connection point voltage; after the current limiter protection is put into operation, the wind farm bus voltage is:

[0146]

[0147] wherein, U rf ne is the wind farm bus voltage after the current limiter protection is put into operation, I s is the stator side current of the wind farm unit, R FCL is the resistance value of the current limiter, k t is the transformer ratio of the wind farm grid-connection transformer;

[0148] Considering the wind farm low voltage ride through limit, we have:

[0149] U ne = I s R FCL / k t 2 + U s ≥ U ne.min (11)

[0150] wherein, U ne is the wind farm bus voltage, I s is the stator side current of the wind farm unit, R FCL is the resistance value of the current limiter, k t is the transformer ratio of the wind farm grid-connection transformer, U s is the terminal voltage of the wind farm unit, U ne.min is the minimum voltage of the wind farm;

[0151] S3, based on the grid cascading fault simulation data and the parameter limit range of the improved VDCOL, the improved VDCOL parameters are obtained by solving the DCS algorithm,

[0152] S301, a solution matrix X is randomly generated in the parameter limit range of the improved VDCOL, each solution in the solution matrix X represents a group of improved VDCOL model parameters, and then step S302 is entered to start iteration;

[0153] S302, according to the objective function values of each solution in the solution matrix X, the solutions are sorted in descending order of the objective function values, and then step S303 is entered;

[0154] S303, according to the sorting results of the solutions, the differentiated knowledge acquisition index of each solution is calculated, and then step S304 is entered;

[0155] According to the ranking result of the solutions, the differentiated knowledge acquisition index of the i-th solution is calculated, including:

[0156]

[0157] ηi=ηi+ηi+ηi (1) i,t ηi is the differentiated knowledge acquisition index of the i-th solution; U(0, 1) is a random number uniformly distributed in the range of [0, 1]; ηi is the degree of imperfection of knowledge of the i-th solution; the symbol [ ] represents the down rounding operation; the symbol represents whether the judgment formula is true, if true, the value of is 0, if not true, the value of is 1; R i,t is the ranking of the i-th solution among all solutions; N is the total number of solutions in the solution matrix X;

[0158] S304, according to the differentiated knowledge acquisition index of each solution, updating each solution, and then entering step S305;

[0159] According to the differentiated knowledge acquisition index of each solution, updating each solution includes:

[0160] According to the differentiated knowledge acquisition index of each solution, ranking each solution in the order of the differentiated knowledge acquisition index from low to high;

[0161] For the solutions ranked in the last P% according to the following formula, updating the solutions:

[0162] v i,d =ωx best,d +λ t (x r2,d -x i,d )+ω i,t (x r1,d -x i,d ) (14)

[0163] In the formula, v i,d is the updated i-th solution, and the i-th solution is the solution ranked in the last P% according to the differentiated knowledge acquisition index; ω is the cognitive weight of the optimal solution; ω i,t is the cognitive weight of the i-th solution; x best,d is the optimal solution, which is the solution with the minimum objective function value in the solution matrix X; λ t is the updating index, x r2,d is the random solution ranked in the front (1-P)% according to the differentiated knowledge acquisition index, and x r1,dx i,d is the i-th solution before updating;

[0164] For the solutions ranked in the front (1-P)%, the solutions are updated according to the following formula:

[0165] v j,d = x s1,d + LK (a, s) (15)

[0166] wherein, v j,d is the j-th solution after updating, the j-th solution is the solution ranked in the front (1-P)%, x s1,d is the random solution ranked in the front (1-P)%, LK (a, s) is a random number satisfying the linnik distribution;

[0167] S305, judge whether the iteration time reaches the preset time threshold, if the preset time threshold is reached, stop iteration; after stopping iteration, the optimal solution objective function is obtained as the fitness, if the fitness is less than 1, it is judged that the optimization converges, and step S306 is entered, if the fitness is greater than 1, the convergence fails, and the step S301 is returned; if the preset time threshold is not reached, the step S302 is returned and the iteration is continued;

[0168] S306, select the solution corresponding to the minimum objective function value in the iteration results.

[0169] Judge whether the algorithm converges; if it does not converge, i.e. the termination loop condition cannot be met, repeat step S302 to continue iteration; if it converges, i.e. the termination loop condition is met, output the iteration result, obtain the improved VDCOL parameter, and complete optimization. The optimization result is shown as follows:

[0170]

[0171] To illustrate the effectiveness of the DCS algorithm used in the present application, the parameter optimization adaptability convergence curves of the two algorithms are shown in Figure 5 It can be seen from the figure that the DCS algorithm optimization convergence speed is faster than the PSO algorithm, and the final convergence effect is also better

[0172] Based on the following four schemes, the cascading failure simulation verification is carried out, and the schemes are as follows:

[0173] Scheme one: the wind farm has infinite flow protection, and the traditional VDCOL control is adopted.

[0174] Scheme two: the wind farm has current limiting protection, and the traditional VDCOL control is adopted.

[0175] Scheme three: wind farm over-current protection, take the optimization VDCOL control.

[0176] Scheme four: wind farm over-current protection, take the optimization VDCOL control, based on over-current protection coordination optimization (the method in this paper)

[0177] In scheme one, at t = 2s, three-phase permanent metal line grounding fault occurs in line 3-6, which leads to serious overload of line 13-14, and the chain of cascading faults 3-6, 13-15, 12-13, 9-10 is obtained: under the same fault, schemes two, three and four are used to verify the blocking effect of cascading faults. In order to judge the blocking effect of cascading faults of each scheme, the wind farm voltage under four schemes is compared Figure 6 , and the DC off angle is Figure 7 . Figure 6 In scheme three, because the wind farm over-current protection is also lacking as in scheme one, the wind farm bus voltage drops to below 0.25 p.u. after line 13-14 is tripped, which cannot meet the requirement of low voltage ride through operation and causes the wind farm to be off-grid. In scheme two and the method in this paper, the voltage of the wind farm during the fault is increased to 0.39 p.u. and 0.52 p.u. respectively, which can still maintain a certain power output, indicating that the wind farm off-grid event is effectively blocked. Figure 7 In scheme one, the DC transmission system commutation station off angle is less than the minimum off angle for three times in succession, which leads to continuous commutation failure and triggers the blocking fault, and the DC current drops to zero. In contrast, scheme three uses the optimization VDCOL control, and the DC transmission system only experiences one commutation failure, and the minimum off angle is zero degree. Although the DC current fluctuates, it does not trigger the blocking, thereby successfully blocking the development of cascading faults in the DC blocking link. In scheme two and the method in this paper, the DC transmission system also only experiences one commutation failure, and the minimum off angle is zero degree and 8 degrees respectively, and the DC current fluctuation is small. From Figure 6 and Figure 7 It can be seen that the present application has good blocking effect on wind farm off-grid fault and DC blocking fault in cascading fault evolution.

[0178] Embodiment 2:

[0179] A power grid cascading fault blocking system based on coordination of VDCOL and over-current protection, comprising a simulation model construction module, an improved VDCOL construction module and a parameter solving module.

[0180] Simulation model construction module: used for constructing the simulation model of the improved frequency stability standard example (Chinese Society for Electrical Engineering-Frequency Stability, CSEE-FS) containing multi-loop DC and new energy in MATLAB / SIMULINK, the model adopts a double-fed wind farm as a representative of new energy, the wind farm grid connection point is connected to a current limiting protection, the DC module of the model is a conventional high-voltage direct current transmission (Line-commuted Converter-High Voltage Direct Current Transmission, LCC-HVDC) system, and a traditional VDCOL control strategy is adopted;

[0181] Improved VDCOL construction module: used for the improved CSEE-FS simulation model containing multi-loop DC and new energy, adopting a multi-kink scheme, performing multi-segment processing on the traditional VDCOL control strategy, and setting the parameter limit range of the improved VDCOL by considering the wind farm low-voltage off-grid protection limit, whether to input the current limiter protection, and the wind farm low-voltage ride-through limit analysis;

[0182] Parameter solving module: used for solving the improved VDCOL parameters by the DCS algorithm based on the power grid cascading failure simulation data and the parameter limit range of the improved VDCOL.

[0183] The segmented function expression of the improved VDCOL through the multi-kink is as follows:

[0184]

[0185] In the formula, I ord is a DC current instruction value; I n is a DC current rated value; U dc is a DC voltage; U max is a VDCOL strategy starting voltage upper limit, U min is a VDCOL strategy starting voltage lower limit; k is a minimum DC current coefficient; U1 to U5 are one to five new kinks; k1 to k6 are one to six segment slope constants.

[0186] The objective function expression is as follows:

[0187] min f = ∫|U L (t) - U N |dt

[0188] In the formula, U L (t) is a converter bus voltage at t, and U N is a converter bus voltage rated value.

[0189] Considering the reactive power compensation device and the reactive power characteristics of the converter station, the maximum value range constraints of the VDCOL control parameters DC voltage and DC current are obtained as:

[0190]

[0191] wherein U max is the upper limit of the VDCOL strategy starting voltage, I ord.max is the upper limit of the VDCOL strategy starting current;

[0192] Therefore, the minimum value range constraints of the VDCOL control parameters DC voltage and DC current are:

[0193]

[0194] wherein U min is the lower limit of the VDCOL strategy starting voltage, I ord.min is the lower limit of the VDCOL strategy starting current.

[0195] Considering the low-voltage off-grid protection limit of the wind farm:

[0196] The DC voltage and the wind farm grid-connected point voltage influence each other during the fault:

[0197]

[0198] wherein P f ne , Q f ne represent the active power and the reactive power of the wind farm after the fault respectively; P ne , Q ne represent the active power and the reactive power of the wind farm respectively; ΔP f ne , ΔQ f ne represent the active power and the reactive power variation of the wind farm caused by the fault respectively; P f ac , Q f ac represent the active power and the reactive power of the AC system after the fault respectively; P ac , Q ac represent the active power and the reactive power of the AC system respectively; ΔP d , ΔQ d represent the active power and the reactive power variation of the DC converter station caused by the fault respectively; ΔQ f ac represent the reactive power variation of the AC system caused by the fault respectively;

[0199] the DC voltage Uf dc and the wind farm grid-connection point voltage U f ne may be expressed as:

[0200]

[0201] wherein U f dc represents the DC voltage after the fault; U f ac represents the voltage of the AC system after the fault; respectively represent the voltage drop longitudinal component and the voltage drop transverse component of the AC system after the fault; U f ne represents the wind farm grid-connection point voltage after the fault; respectively represent the voltage drop longitudinal component and the voltage drop transverse component of the wind farm grid-connection point after the fault;

[0202] At this time, if the current limiter protection is not put into operation, the wind farm bus voltage is the wind farm grid-connection point voltage; after the current limiter protection is put into operation, the wind farm bus voltage is:

[0203]

[0204] wherein U rf ne is the wind farm bus voltage after the current limiter protection, I s is the wind farm unit stator side current, R FCL is the resistance value of the current limiter, k t is the wind farm grid-connection transformer transformation ratio;

[0205] considering the wind farm low voltage ride through limit:

[0206] U ne = I s R FCL / k t 2 + U s ≥ U ne.min

[0207] wherein U ne is the wind farm bus voltage, I s is the wind farm unit stator side current, R FCL is the resistance value of the current limiter, k t is the wind farm grid-connection transformer transformation ratio, U s is the wind farm unit terminal voltage, U ne.min is the lowest voltage of the wind farm.

[0208] S301, randomly generate a solution matrix X in the parameter limit range of S2, each solution in the solution matrix X represents a set of improved VDCOL model parameters, then go to step S302 to start iteration;

[0209] S302, sort the solutions in the solution matrix X according to the objective function values of the solutions from high to low, then go to step S303;

[0210] S303, calculate the differentiated knowledge acquisition index of each solution according to the sorting result of the solutions, then go to step S304;

[0211] The calculation of the differentiated knowledge acquisition index of the i-th solution according to the sorting result of the solutions includes:

[0212]

[0213]

[0214] ηi i,t is the differentiated knowledge acquisition index of the i-th solution; U(0, 1) is a random number uniformly distributed in [0, 1]; is the degree of imperfection of the knowledge of the i-th solution; the symbol [] represents the down rounding operation; the symbol represents whether the judgment formula is true or not, if true, the value of is 0, if not true, the value of i,t is 1; R is the ranking of the i-th solution among all solutions; N is the total number of solutions in the solution matrix X;

[0215] S304, update each solution according to the differentiated knowledge acquisition index of the solution, then go to step S305;

[0216] The updating of each solution according to the differentiated knowledge acquisition index of the solution includes:

[0217] According to the differentiated knowledge acquisition index of each solution, sort the solutions from low to high according to the differentiated knowledge acquisition index;

[0218] For the solutions ranked in the last P% of the solutions, update the solutions according to the following formula:

[0219] v i,d = ωx best,d + λ t (x r2,d -x i,d )+ω i,t(x r1,d -x i,d )

[0220] wherein v i,d is the i-th solution after updating, the i-th solution is a solution ranked in the last P% in the differential knowledge acquisition index; ω is the cognitive weight of the optimal solution; ω i,t is the cognitive weight of the i-th solution; x best,d is the optimal solution, the optimal solution is a solution with the minimum objective function value in the solution matrix X; λ t is the updating index, x r2,d is a random solution ranked in the first (1-P)% in the differential knowledge acquisition index, x r1,d is a random solution ranked in the last P% in the differential knowledge acquisition index, x i,d is the i-th solution before updating;

[0221] For the solution ranked in the first (1-P)%, the solution is updated according to the following formula:

[0222] v j,d = x s1,d + LK(α, σ)

[0223] wherein v j,d is the j-th solution after updating, the j-th solution is a solution ranked in the first (1-P)%, x s1,d is a random solution ranked in the first (1-P)%, LK(α, σ) is a random number satisfying the linnik distribution;

[0224] S305, judge whether the iteration time reaches the preset time threshold, if the preset time threshold is reached, stop iteration; after stopping iteration, the optimal solution objective function is obtained as the fitness, if the fitness is less than 1, it is determined that the optimization converges, and step S306 is entered, if the fitness is greater than 1, the convergence fails, and the step S301 is returned; if the preset time threshold is not reached, the step S302 is returned and the iteration is continued;

[0225] S306, select the solution corresponding to the minimum objective function value in the iteration result.

[0226] Embodiment 3:

[0227] Referring to Figure 8 , a power grid cascading failure blocking device based on VDCOL and current limiting protection coordination, comprising a processor and a memory;

[0228] The memory is used for storing computer program code and transmitting the computer program code to the processor;

[0229] The processor is configured to execute the method according to the instructions in the computer program code.

[0230] Embodiment 4:

[0231] A computer storage medium, having stored thereon a computer program, which, when executed by a processor, implements the steps of the method according to the instructions in the computer program code.

Claims

1. A method for blocking power grid cascading faults based on coordination between VDCOL and current limiting protection, characterized by: S1 built an improved CSEE-FS simulation model containing multiple DC circuits and renewable energy in the simulation software. The model used a doubly fed wind turbine wind farm, with current limiting protection connected to the grid connection point. The DC module of the model was a conventional high-voltage direct current transmission system, using a traditional VDCOL control strategy. S2 is based on an improved CSEE-FS simulation model with multiple DC loops and renewable energy sources. It adopts a multi-inflection point solution to multi-stage the traditional VDCOL control strategy. By considering the wind farm's low-voltage grid-trip protection restrictions, whether to use the current limiter protection, and the wind farm's low-voltage ride-through limit analysis, the parameter limit range of the improved VDCOL is set. The piecewise function expression of VDCOL improved by multiple inflection points is as follows: Where, I ord is the DC current command value; I n is the DC current rating; U dc is the DC voltage; U max The upper voltage limit for starting the VDCOL strategy, U min is the lower limit of the VDCOL strategy startup voltage; k is the minimum DC current coefficient; U1 to U5 are the newly added 1 to 5 inflection points; k1 to k6 are the slope constants of segments 1 to 6; The objective function expression is as follows: minf=∫∣U L (t)-U N ∣dt Where U L (t) is the commutation bus voltage at time t, U N is the rated value of the commutation bus voltage; Considering the reactive power characteristics of the reactive compensation device and the converter station, the maximum value range constraints of the DC voltage and DC current of the improved VDCOL control parameters are obtained as follows: Among them, U max The upper voltage limit for starting the VDCOL strategy, I ord.max The upper limit of the startup current of the VDCOL strategy; Therefore, the minimum value ranges of the DC voltage and DC current of the improved VDCOL control parameters are constrained to be: Among them, U min The lower voltage limit for starting the VDCOL strategy; I ord.min The lower limit of the starting current of the VDCOL strategy; Based on the grid cascading failure simulation data and the parameter limit range of the improved VDCOL, S3 obtains the improved VDCOL parameters through the DCS algorithm.

2. The method for blocking power grid cascading faults based on coordination between VDCOL and current limiting protection according to claim 1, characterized in that: Consider the wind farm low voltage disconnection protection limit: The DC voltage and the wind farm grid connection point voltage affect each other during a fault: Where, Respectively represent the active power and reactive power of the wind farm after the fault; P ne , Q ne Respectively represent the active power and reactive power of the wind farm; They represent the changes in active power and reactive power of the wind farm caused by the fault respectively; Respectively represent the active power and reactive power of the AC system after the fault; P ac , Q ac Represent the active power and reactive power of the AC system respectively; ΔP d , ΔQ d They represent the changes in active power and reactive power of the DC converter station caused by the fault respectively; They represent the reactive power change of the AC system caused by the fault; DC voltage after fault and wind farm grid connection point voltage It can be expressed as: Where, Represents the DC voltage after the fault; Represents the voltage of the AC system after the fault; They represent the vertical component and the horizontal component of the voltage drop in the AC system after a fault respectively; Represents the voltage at the wind farm grid connection point after the fault; They represent the vertical component and the horizontal component of the voltage drop at the wind farm grid connection point after the fault respectively; At this time, if the current limiter protection is not activated, the bus voltage of the wind farm is the voltage at the wind farm grid connection point; after the current limiter protection is activated, the bus voltage of the wind farm is: Where, is the bus voltage of the wind farm after the current limiting protection is activated, I s is the stator side current of the wind farm unit, R FCL is the resistance value of the current limiter, k t is the wind farm grid-connected transformer ratio; Consider the wind farm low voltage ride-through limit as follows: U ne =I s R FCL / k t 2 +U s ≥U ne.min Where U ne is the bus voltage of the wind farm, I s is the stator side current of the wind farm unit, R FCL is the resistance value of the current limiter, k t is the wind farm grid-connected transformer ratio, U s is the terminal voltage of the wind farm unit, U ne.min The lowest voltage of the wind farm.

3. The method for blocking power grid cascading faults based on coordination between VDCOL and current limiting protection according to claim 1, characterized in that: In the S3, S301, randomly generate a solution matrix X within the parameter restriction range of the improved VDCOL, where each solution in the solution matrix X represents a set of improved VDCOL model parameters, and then proceed to step S302 to start iteration; S302, sorting the solutions in descending order of the objective function values ​​according to the objective function values ​​of the solutions in the solution matrix X, and then proceeding to step S303; S303: Calculate the differentiated knowledge acquisition index of each solution based on the ranking results of the solutions, and then proceed to step S304; According to the ranking results of the solutions, the differential knowledge acquisition index of the i-th solution is calculated including: Where η i,t is the differential knowledge acquisition index of the i-th solution; U(0,1) is a random number uniformly distributed in the range [0,1]; is the degree of imperfect knowledge of the i-th solution; the symbol [] indicates the rounding down operation; the symbol Represents the judgment formula Is it established? If so, The value of is 0, if it is not true, the value of is 1; R i,t is the ranking of the i-th solution among all solutions; N is the total number of solutions in the solution matrix X; S304: Update each solution according to its differentiated knowledge acquisition index, and then proceed to step S305; Based on the differentiated knowledge acquisition index of each solution, updates to each solution include: According to the differential knowledge acquisition index of each solution, the solutions are ranked in order from low to high. For the solutions ranked in the bottom P%, the solutions are updated according to the following formula: v i,d =ωx best,d +λ t (x r2,d -x i,d )+ω i,t (x r1,d -x i,d ) Where, v i,d is the updated i-th solution, which is the solution ranked in the bottom P% of the differential knowledge acquisition index; ω is the cognitive weight of the optimal solution; ω i,t is the cognitive weight of the ith solution; x best,d is the optimal solution, which is the solution with the minimum objective function value in the solution matrix X; t is the update index, x r2,d is the random solution ranked in the top (1-P)% of the differential knowledge acquisition index, x r1,d To obtain the differential knowledge index ranking in the last P% of random solutions, x i,d is the i-th solution before updating; For the top (1-P)% of the ranked solutions, the solution is updated according to the following formula: v j,d =x s1,d +LK(α,σ) Where, v j,d is the jth solution after update, the jth solution is the solution ranked in the top (1-P)%, x s1,d is a random solution ranked in the top (1-P)%, LK(α,σ) is a random number that satisfies the Linnik distribution; S305: Determine whether the iteration time reaches a preset time threshold. If so, stop the iteration. After stopping the iteration, obtain the optimal solution objective function as the fitness. If the fitness is less than 1, it is determined that the optimization has converged and the process proceeds to step S306. If the fitness is greater than 1, convergence has failed and the process returns to step S301. If the preset time threshold is not reached, return to step S302 and continue the iteration. S306. Select the solution with the minimum corresponding objective function value from the results of all previous iterations.

4. A power grid cascading fault blocking system based on coordination between VDCOL and current limiting protection, characterized by: Including simulation model building module, improved VDCOL building module and parameter solution module; Simulation model construction module: used to build an improved CSEE-FS simulation model containing multiple DC circuits and renewable energy in the simulation software. The model uses a doubly fed wind turbine wind farm with current limiting protection connected to the grid connection point. The DC module of the model is a conventional high-voltage direct current transmission system, using the traditional VDCOL control strategy. Improved VDCOL construction module: Based on the improved CSEE-FS simulation model with multi-circuit DC and renewable energy, it adopts a multi-inflection point solution to multi-stage the traditional VDCOL control strategy. By considering the wind farm's low-voltage grid-trip protection restrictions, whether to use the current limiter protection, and the wind farm's low-voltage ride-through limit analysis, the parameter limit range of the improved VDCOL is set; The piecewise function expression of VDCOL improved by multiple inflection points is as follows: Where, I ord is the DC current command value; I n is the DC current rating; U dc is the DC voltage; U max The upper voltage limit for starting the VDCOL strategy, U min is the lower limit of the VDCOL strategy startup voltage; k is the minimum DC current coefficient; U1 to U5 are the newly added 1 to 5 inflection points; k1 to k6 are the slope constants of segments 1 to 6; The objective function expression is as follows: minf=∫∣U L (t)-U N ∣dt Where U L (t) is the commutation bus voltage at time t, U N is the rated value of the commutation bus voltage; Considering the reactive power characteristics of the reactive compensation device and the converter station, the maximum value range constraints of the DC voltage and DC current of the improved VDCOL control parameters are obtained as follows: Among them, U max The upper voltage limit for starting the VDCOL strategy, I ord.max The upper limit of the startup current of the VDCOL strategy; Therefore, the minimum value ranges of the DC voltage and DC current of the improved VDCOL control parameters are constrained to be: Among them, U min The lower voltage limit for starting the VDCOL strategy; I ord.min The module is used to start the lower current limit of the VDCOL strategy; the parameter solution module is used to obtain the improved VDCOL parameters through the DCS algorithm based on the grid cascading failure simulation data and the parameter limit range of the improved VDCOL.

5. The grid cascading fault blocking system based on coordination of VDCOL and current limiting protection according to claim 4, characterized in that: Consider the wind farm low voltage disconnection protection limit: The DC voltage and the wind farm grid connection point voltage affect each other during a fault: Where, Respectively represent the active power and reactive power of the wind farm after the fault; P ne , Q ne Respectively represent the active power and reactive power of the wind farm; They represent the changes in active power and reactive power of the wind farm caused by the fault respectively; Respectively represent the active power and reactive power of the AC system after the fault; P ac , Q ac Represent the active power and reactive power of the AC system respectively; ΔP d , ΔQ d They represent the changes in active power and reactive power of the DC converter station caused by the fault respectively; They represent the reactive power change of the AC system caused by the fault; DC voltage after fault and wind farm grid connection point voltage It can be expressed as: Where, Represents the DC voltage after the fault; Represents the voltage of the AC system after the fault; They represent the vertical component and the horizontal component of the voltage drop in the AC system after a fault respectively; Represents the voltage at the wind farm grid connection point after the fault; They represent the vertical component and the horizontal component of the voltage drop at the wind farm grid connection point after the fault respectively; At this time, if the current limiter protection is not activated, the bus voltage of the wind farm is the voltage at the wind farm grid connection point; after the current limiter protection is activated, the bus voltage of the wind farm is: Where, is the bus voltage of the wind farm after the current limiting protection is activated, I s is the stator side current of the wind farm unit, R FCL is the resistance value of the current limiter, k t is the wind farm grid-connected transformer ratio; Consider the wind farm low voltage ride-through limit as follows: U ne =I s R FCL / k t 2 +U s ≥U ne.min Where U ne is the bus voltage of the wind farm, I s is the stator side current of the wind farm unit, R FCL is the resistance value of the current limiter, k t is the wind farm grid-connected transformer ratio, U s is the terminal voltage of the wind farm unit, U ne.min The lowest voltage of the wind farm.

6. The grid cascading fault blocking system based on coordination of VDCOL and current limiting protection according to claim 4, characterized in that: The parameter solution includes: S301, randomly generate a solution matrix X within the parameter restriction range of the improved VDCOL, where each solution in the solution matrix X represents a set of improved VDCOL model parameters, and then proceed to step S302 to start iteration; S302, sorting the solutions in descending order of the objective function values ​​according to the objective function values ​​of the solutions in the solution matrix X, and then proceeding to step S303; S303: Calculate the differentiated knowledge acquisition index of each solution based on the ranking results of the solutions, and then proceed to step S304; According to the ranking results of the solutions, the differential knowledge acquisition index of the i-th solution is calculated including: Where η i,t is the differential knowledge acquisition index of the i-th solution; U(0,1) is a random number uniformly distributed in the range [0,1]; is the degree of imperfect knowledge of the i-th solution; the symbol [] indicates the rounding down operation; the symbol Represents the judgment formula Is it established? If so, The value of is 0, if it is not true, the value of is 1; R i,t is the ranking of the i-th solution among all solutions; N is the total number of solutions in the solution matrix X; S304: Update each solution according to its differentiated knowledge acquisition index, and then proceed to step S305; Based on the differentiated knowledge acquisition index of each solution, updates to each solution include: According to the differential knowledge acquisition index of each solution, the solutions are ranked in order from low to high. For the solutions ranked in the bottom P%, the solutions are updated according to the following formula: v i,d =ωx best,d +λ t (x r2,d -x i,d )+ω i,t (x r1,d -x i,d ) Where, v i,d is the updated i-th solution, which is the solution ranked in the bottom P% of the differential knowledge acquisition index; ω is the cognitive weight of the optimal solution; ω i,t is the cognitive weight of the ith solution; x best,d is the optimal solution, which is the solution with the minimum objective function value in the solution matrix X; t is the update index, x r2,d is the random solution ranked in the top (1-P)% of the differential knowledge acquisition index, x r1,d To obtain the differential knowledge index ranking in the last P% of random solutions, x i,d is the i-th solution before updating; For the top (1-P)% of the ranked solutions, the solution is updated according to the following formula: v j,d =x s1,d +LK(α,σ) Where, v j,d is the jth solution after update, the jth solution is the solution ranked in the top (1-P)%, x s1,d is a random solution ranked in the top (1-P)%, LK(α,σ) is a random number that satisfies the Linnik distribution; S305: Determine whether the iteration time reaches a preset time threshold. If so, stop the iteration and proceed to step S306. If not, return to step S302 and continue the iteration. S306. Select the solution with the minimum corresponding objective function value from the results of all previous iterations.

7. A power grid cascading fault blocking device based on coordination of VDCOL and current limiting protection, characterized in that: including a processor and a memory; The memory is used to store computer program code and transmit the computer program code to the processor; The processor is configured to execute the power grid cascading fault blocking method based on coordination of VDCOL and current limiting protection according to any one of claims 1 to 3 according to the instructions in the computer program code.

8. A computer storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of a power grid cascading fault blocking method based on coordination of VDCOL and current limiting protection are implemented as described in any one of claims 1 to 3.

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