Multi-back back-to-back flexible direct current access scheme determination method and device

Abstract

The invention provides a multi-back-to-back flexible direct current access scheme determination method and a related device. The method comprises the following steps: acquiring basic parameters of a researched receiving-end power grid based on a pre-constructed evaluation system; solving a pre-established multi-objective optimization model by adopting a multi-objective particle swarm optimization algorithm to obtain a plurality of non-inferior solutions of a multi-back-to-back flexible direct current access scheme for the receiving-end power grid; selecting the plurality of multi-back-to-back flexible direct current access schemes by adopting an analytic hierarchy process to obtain a final multi-back-to-back flexible direct current access scheme; the bottommost layer in the analytic hierarchy process is a plurality of candidate multi-back-to-back flexible direct current access schemes, the middle layer is a plurality of evaluation indexes, and the highest layer is a final direct current access scheme. According to the method, the evaluation system containing the multi-dimensional evaluation indexes is constructed, the most suitable multi-back back-to-back flexible direct current access scheme can be determined from numerous candidate schemes, and the comprehensive performance and the operation benefit of the receiving-end power grid when the back-to-back flexible direct current is accessed can be improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of power system planning and operation, and in particular relates to a method and device for determining a multi-circuit back-to-back flexible direct current access scheme. Background Art

[0002] For the receiving power grid with multiple conventional DC feeds, the electrical distance between the DC busbars is often short, and AC faults can easily cause multiple converter stations to fail to commutate at the same time. In severe cases, it can cause multiple commutation failures or even shutdown, posing a serious threat to the safe operation of the system. On the other hand, the short-circuit current of the receiving power grid is often high. In order to control the short-circuit current, the grid structure needs to be adjusted (such as stopping the line or disconnecting the line), which may cause a significant reduction in the strength of the grid and increase the risk of system instability. Connecting back-to-back flexible DC at one or more suitable locations in the receiving power grid can effectively reduce the risk of simultaneous commutation failure of multiple conventional DCs, and can reasonably reduce the short-circuit current, which is one of the effective ways to solve the above problems. Therefore, it is of great practical significance to study the access scheme of single or multiple back-to-back flexible DC in the receiving power grid. At present, there is no research on the access scheme of multiple back-to-back flexible DC in the receiving power grid. Summary of the invention

[0003] In view of this, the purpose of the present invention is to propose a method and device for determining a multi-circuit back-to-back flexible DC access scheme, which can effectively reduce the risk of simultaneous commutation failure of multiple conventional DC circuits, and at the same time can reasonably reduce the short-circuit current. This method can simultaneously consider the economy of the access scheme and its impact on the safety and stability of the system.

[0004] In order to achieve the above object, the technical solution provided by the present invention is as follows:

[0005] In a first aspect, the present invention provides a method for determining a multi-circuit back-to-back flexible direct current access scheme, comprising the following steps:

[0006] The basic parameters of the receiving-end power grid under study are obtained based on a pre-built evaluation system; the evaluation system includes several evaluation indicators for evaluating the multi-circuit back-to-back flexible DC access scheme;

[0007] Based on basic parameters, a multi-objective particle swarm algorithm is used to solve the pre-established multi-objective optimization model to obtain several non-inferior solutions, each of which is a multi-circuit back-to-back flexible DC access scheme for the receiving power grid; the multi-objective optimization model is a mathematical model that takes the optimization of several evaluation indicators of the multi-circuit back-to-back flexible DC access scheme as the optimization objective, and takes the rated capacity of each back-to-back flexible DC in each multi-circuit back-to-back flexible DC access scheme as the optimization variable;

[0008] The hierarchical analysis method is used to select the multi-circuit back-to-back flexible DC access schemes corresponding to several non-inferior solutions to obtain the final multi-circuit back-to-back flexible DC access scheme; the bottom layer of the hierarchical analysis method is several candidate multi-circuit back-to-back flexible DC access schemes, the middle layer is several evaluation indicators, and the highest layer is the final DC access scheme.

[0009] Furthermore, a multi-objective particle swarm algorithm is used to solve the pre-established multi-objective optimization model and obtain several non-inferior solutions, including:

[0010] Set and initialize the particle swarm; the particle swarm includes 1 master particle swarm, several slave particle swarms and 1 reserve set; the several slave particle swarms correspond to several evaluation indicators one by one and are optimized as their respective goals;

[0011] Iteratively update the particle swarm; the iterative update operation includes randomly selecting particles from the reserve set as the global guide particles of the master particle swarm, and each slave particle swarm uses the best particle in the reserve set corresponding to its respective optimization target as the global guide particle, and the master and slave particle swarms are iteratively updated based on their respective global guide particles and local guide particles;

[0012] Update the reserve set; the update operation includes adding the non-inferior extreme value particles obtained from the particle swarm to the main particle swarm after each iteration, adding the non-inferior particles obtained from the main and slave particle swarms to the reserve set, and updating the reserve set to remove particles in the reserve set that are not non-inferior solutions;

[0013] Repeat the iterative update operation of the particle swarm and the update operation of the reserve set until the termination condition is met, and obtain the non-inferior solution set in the reserve set. Each non-inferior solution in the solution set represents a back-to-back flexible DC access scheme.

[0014] Furthermore, in the iterative update of the master-slave particle swarm based on their respective global guide particles and local guide particles, the iterative search formula is as follows:

[0015]

[0016]

[0017] In the formula, , are the search speeds of the dth variable of particle i at the k+1th and kth iterations, respectively; ω is the inertia weight; c1 and c2 are learning factors; r1 and r2 are random numbers that obey uniform distribution on [0, 1]; , , They are respectively the current value of the d-th variable position of particle i in the k-th iteration, the value of the d-th variable position of the individual local guiding particle, and the value of the d-th variable position of the global guiding particle.

[0018] Furthermore, the evaluation index includes the risk index caused by conventional DC commutation failure. Given a set of test faults {F1,,..,F R} and mode data, for the fault F in the test fault set j , the calculation expression of the risk index is as follows:

[0019]

[0020] In the formula, It is a risk indicator caused by conventional DC commutation failure; is the number of faults in a given test fault set, is the fault sequence number index; is the number of conventional DC circuits fed into the receiving grid, It is the conventional DC serial number index; Fault F j In the case of commutation failure of the conventional DC circuit, u i,j =1 means the ith DC current is at F j Commutation failure occurs under fault conditions, u i,j =0 means Back to normal DC at fault F j No commutation failure occurred; is the transmission power of the i-th conventional DC.

[0021] Furthermore, the evaluation index also includes the maximum short-circuit current index of the system. For the multi-circuit back-to-back flexible DC access scheme to be evaluated, under given operation mode data, for the busbars {B1, B2, ..., B M}, the calculation expression of the system maximum short-circuit current index is as follows:

[0022]

[0023] In the formula, It is the maximum short-circuit current indicator of the system; To investigate the number of buses with short-circuit current, The bus number index for examining the short-circuit current; and For the The three-phase current and single-phase short-circuit current of the bus; I max and I min is the short-circuit current threshold.

[0024] Furthermore, the evaluation index also includes the construction cost of the back-to-back flexible DC access scheme. For the multiple back-to-back flexible DC access schemes to be evaluated, the calculation expression of the construction cost of the back-to-back flexible DC access scheme is as follows:

[0025]

[0026] In the formula, Construction costs for the back-to-back flexible DC access solution; is the number of candidate channels that can be connected to back-to-back flexible DC, is the candidate channel sequence index, is the construction cost of the back-to-back flexible DC unit capacity of the i-th channel, The rated active power of the back-to-back flexible DC configured for the i-th channel, is the upper limit of construction cost, Whether the i-th channel is configured with back-to-back flexible DC, Indicates configuration, Indicates no configuration.

[0027] Furthermore, the evaluation index also includes the system stability level index. For the multi-circuit back-to-back flexible DC access scheme to be evaluated, under a given fault set { , ,.., } and operation mode data, the calculation expression of the system stability level index is as follows:

[0028]

[0029] In the formula, is the system stability level indicator, The minimum number of failures that cause the system to lose stability, The number of failures in the given test failure set.

[0030] Furthermore, in the system stability level index, the minimum number of failures that causes the system to lose stability The particle swarm algorithm is used to solve the problem. The solution process includes the following steps:

[0031] Set the objective function to , K is the number of faults that cause the system to lose stability;

[0032] Set a particle swarm; the particle swarm has a total of S particles, for particle i, , It refers to the transmission power of the jth back-to-back flexible DC in the scheme to be evaluated, , is the rated capacity of the jth back-to-back flexible DC link, The number of channels configured with back-to-back flexible DC;

[0033] For particle i, a fault time domain simulation analysis is performed based on the given operation mode data and fault set; the total number of faults that cause the system to lose stability is counted as the fitness value of the particle. The smaller the fitness, the better the particle, which is recorded as , n is the number of iterations, and the best result for the particle after the nth iteration is recorded as ;

[0034] Update each particle according to the following formula:

[0035]

[0036]

[0037]

[0038]

[0039] In the formula, , , , are control parameters, n, N iter is the current iteration number and the total iteration number, rand() is a random number between (0,1); represents the value of the jth position of the ith particle after the nth iteration, Ulocal i,j (n) is the value of the jth position of the local optimal individual of the ith particle after the nth iteration, Uglobal j (n) is the value of the jth position of the optimal individual of the entire particle swarm after the nth iteration; V i,j (n) represents the velocity value of the i-th particle at the j-th position after the n-th iteration, , Respectively represent V i,j (n) lower and upper limits; represents the best particle of the particle swarm after the nth iteration;

[0040] Repeat the above iterative process until the termination condition is met. The number of failures that cause the system to lose stability corresponding to the optimal solution at this time is recorded as .

[0041] Furthermore, the analytic hierarchy process is used to select several multi-circuit back-to-back flexible DC access schemes, including:

[0042] The first matrix and the second matrix are used to respectively calculate the first weight coefficients of the plurality of evaluation indicators and the second weight coefficients of the plurality of candidate multi-circuit back-to-back flexible direct current access schemes under the plurality of evaluation indicators; the first matrix and the second matrix are judgment matrices of the highest layer and the middle layer, and the middle layer and the lowest layer, respectively;

[0043] The final weight coefficient of each multi-circuit back-to-back flexible DC access scheme is calculated based on the first weight coefficient and the second weight coefficient, and the candidate scheme with the largest final weight coefficient is selected as the final DC access scheme; the final weight coefficient is calculated according to the following formula:

[0044]

[0045] In the formula, For the The final weight coefficient of the candidate solutions is is the number of evaluation indicators, is the first weight coefficient after normalization of the jth evaluation index, For the The second weight coefficient of the candidate solutions after normalization under the jth evaluation index.

[0046] In a second aspect, the present invention provides a device for determining a multi-circuit back-to-back flexible direct current access scheme, comprising:

[0047] A data acquisition module is used to obtain basic parameters of the receiving-end power grid under study based on a pre-built evaluation system; the evaluation system includes several evaluation indicators for evaluating the multi-circuit back-to-back flexible DC access scheme;

[0048] The model solving module is used to solve the pre-established multi-objective optimization model based on basic parameters by using a multi-objective particle swarm algorithm to obtain several non-inferior solutions, each of which is a multi-circuit back-to-back flexible DC access scheme for the receiving-end power grid; the multi-objective optimization model is a mathematical model that takes the optimization of several evaluation indicators of the multi-circuit back-to-back flexible DC access scheme as the optimization objective, and takes the rated capacity of each back-to-back flexible DC in each multi-circuit back-to-back flexible DC access scheme as the optimization variable;

[0049] The scheme determination module is used to select the multi-circuit back-to-back flexible DC access schemes corresponding to several non-inferior solutions using the hierarchical analysis method to obtain the final multi-circuit back-to-back flexible DC access scheme; the bottom layer of the hierarchical analysis method is several candidate multi-circuit back-to-back flexible DC access schemes, the middle layer is several evaluation indicators, and the top layer is the final DC access scheme.

[0050] In a third aspect, the present invention provides a computer device, the device comprising a processor and a memory:

[0051] The memory is used to store the computer program and send the instructions of the computer program to the processor;

[0052] The processor executes a method for determining a multi-circuit back-to-back flexible direct current access scheme according to instructions of the computer program.

[0053] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements a method for determining a multi-circuit back-to-back flexible direct current access scheme as in the first aspect.

[0054] In summary, the present invention provides a method and related device for determining a multi-circuit back-to-back flexible DC access scheme, including obtaining basic parameters of the receiving power grid under study based on a pre-constructed evaluation system; based on the basic parameters, using a multi-objective particle swarm algorithm to solve a pre-established multi-objective optimization model to obtain a number of non-inferior solutions, each of which is a multi-circuit back-to-back flexible DC access scheme for the receiving power grid; the multi-objective optimization model is a mathematical model that takes the optimization of a number of evaluation indicators of the multi-circuit back-to-back flexible DC access scheme as the optimization target, and takes the rated capacity of each back-to-back flexible DC in each multi-circuit back-to-back flexible DC access scheme as the optimization variable; using a hierarchical analysis method to select a number of multi-circuit back-to-back flexible DC access schemes to obtain a final multi-circuit back-to-back flexible DC access scheme; the bottom layer in the hierarchical analysis method is a number of candidate multi-circuit back-to-back flexible DC access schemes, the middle layer is a number of evaluation indicators, and the highest layer is the final DC access scheme. The present invention comprehensively considers various factors and can scientifically and reasonably determine the most suitable multi-circuit back-to-back flexible DC access scheme from numerous candidate schemes, which helps to improve the comprehensive performance and operating efficiency of the receiving power grid when accessing back-to-back flexible DC, and ensure stable and efficient operation of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0056] Figure 1 A flowchart of a method for determining a multi-circuit back-to-back flexible direct current access solution provided by an embodiment of the present invention;

[0057] Figure 2 A schematic diagram of determining a final multi-circuit back-to-back flexible direct current access solution using the hierarchical analysis method provided in an embodiment of the present invention;

[0058] Figure 3A block diagram of a device for determining a multi-circuit back-to-back flexible direct current access solution provided by an embodiment of the present invention;

[0059] Figure 4 A block diagram of a computer device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0060] In order to make the purpose, features and advantages of the present invention more obvious and easy to understand, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described below are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0061] See also Figure 1 The embodiment of the present invention provides a method for determining a multi-circuit back-to-back flexible direct current access solution, comprising the following steps:

[0062] S11: Obtain basic parameters of the receiving-end power grid under study based on a pre-constructed evaluation system; the evaluation system includes several evaluation indicators for evaluating a multi-circuit back-to-back flexible DC access solution.

[0063] It should be noted that this step is based on the pre-built evaluation system. This evaluation system is established based on the specific evaluation requirements of the multi-circuit back-to-back flexible DC access solution. It contains multiple evaluation indicators, which are determined by analyzing many factors such as the technical requirements, economic feasibility, and environmental impact of the power system.

[0064] The basic parameters include numerous characteristic data related to the receiving power grid, such as the relevant parameters of the conventional DC fed into the receiving power grid (such as the number of conventional DC loops, the rated power of each conventional DC loop, etc.), the bus information for examining short-circuit current (the number of buses, the number of each bus, etc.), and the relevant parameters of the candidate channels that can be connected to the back-to-back flexible DC (such as the maximum transmittable active power of the back-to-back flexible DC that can be constructed for each channel, etc.). It may also involve the existing operating mode data of the power grid, fault-related data, etc. These parameters can reflect the basic structure and operating characteristics of the receiving power grid.

[0065] This step obtains various basic information related to the receiving power grid to form a basic data set for subsequent calculation and analysis.

[0066] S12: Based on basic parameters, a multi-objective particle swarm algorithm is used to solve the pre-established multi-objective optimization model to obtain several non-inferior solutions, each of which is a multi-circuit back-to-back flexible DC access scheme for the receiving power grid; the multi-objective optimization model is a mathematical model with the optimization of several evaluation indicators of the multi-circuit back-to-back flexible DC access scheme as the optimization objective, and the rated capacity of each back-to-back flexible DC in each multi-circuit back-to-back flexible DC access scheme as the optimization variable.

[0067] It should be noted that the particle swarm algorithm is an optimization algorithm based on swarm intelligence, which simulates the mechanism of mutual cooperation and information sharing between individuals in the foraging process of a flock of birds and other groups to find the optimal solution. In the solution of this embodiment, it is used to search for a better solution combination among many possible multi-circuit back-to-back flexible DC access solutions.

[0068] The multi-objective optimization model is a mathematical model constructed by considering multiple different objectives (such as ensuring stable operation of the power grid and controlling construction costs) when determining the multi-circuit back-to-back flexible DC access plan. Its objective function is composed of multiple evaluation indicators, and its purpose is to find a set of solutions that can make these evaluation indicators reach the best state as much as possible, rather than the optimal solution for only a single objective.

[0069] In multi-objective optimization problems, there is no solution that is absolutely better than other solutions in all objectives. Non-inferior solutions (Pareto optimal solutions) refer to those solutions that have no other solutions that are better than them in all objectives, that is, better solutions that achieve a relative balance between various objectives.

[0070] Evaluation indicators specifically refer to quantitative indicators in multiple dimensions that measure the quality of multiple back-to-back flexible DC access solutions, such as risk indicators caused by conventional DC commutation failure (reflecting the impact on conventional DC operation), system maximum short-circuit current indicators (reflecting the impact on the short-circuit safety performance of the power grid), back-to-back flexible DC access solution construction costs (related to economic costs), system stability level indicators (assessing the effect on the overall stability of the power grid), etc. These indicators are calculated and determined based on the basic parameters mentioned above and factors such as the rated capacity of the back-to-back flexible DC.

[0071] This step uses the search capability of the particle swarm algorithm to find multiple non-inferior solutions that achieve a relative balance between different objectives in a complex solution space (many possible access scheme combinations), providing a rich candidate set for further screening of the final optimal access scheme, avoiding the situation where only considering a single objective leads to poor performance in other aspects, and fully taking into account the various needs of power grid operation.

[0072] S13: A hierarchical analysis method is used to select the multi-circuit back-to-back flexible DC access schemes corresponding to several non-inferior solutions to obtain a final multi-circuit back-to-back flexible DC access scheme; the bottom layer of the hierarchical analysis method is a plurality of candidate multi-circuit back-to-back flexible DC access schemes, the middle layer is a plurality of evaluation indicators, and the top layer is the final DC access scheme.

[0073] It should be noted that the analytic hierarchy process is a multi-criteria decision-making method that divides complex decision problems into layers, constructs a judgment matrix by comparing the elements of each layer in pairs, calculates the weight coefficient, and then comprehensively evaluates and obtains the optimal decision solution. In the solution of this embodiment, it is used to select the final multi-circuit back-to-back flexible DC access solution from multiple non-inferior solutions obtained by the particle swarm algorithm.

[0074] The process of using the analytic hierarchy process to determine the final solution is to place multiple candidate multi-circuit back-to-back flexible DC access solutions corresponding to several non-inferior solutions at the bottom of the analytic hierarchy process, place multiple evaluation indicators determined previously in the middle layer, and place the DC access solution to be determined at the top layer. Then, the relative importance of each evaluation indicator is determined by expert scoring, a judgment matrix is ​​constructed, and the weight of each evaluation indicator is calculated. Then, the candidate access solutions at the bottom layer are comprehensively evaluated and ranked, and the solution with the best overall performance is finally selected as the final multi-circuit back-to-back flexible DC access solution.

[0075] This step can comprehensively consider various factors by scientifically quantifying the relative importance of different evaluation indicators and candidate solutions, and accurately select the final access solution that best meets the overall requirements from multiple non-inferior solutions obtained by the particle swarm algorithm, so that the selection of the final solution no longer depends on subjective conjecture, but is based on rigorous mathematical calculations and reasonable weight distribution.

[0076] This embodiment provides a method for determining a multi-circuit back-to-back flexible DC access scheme. This method uses a multi-objective optimization model to take into account multiple evaluation indicators that are critical to the operation of the power grid, such as technical performance (conventional DC commutation, short-circuit current, system stability) and economic cost (construction cost), so that the final access scheme can achieve a relatively optimal balance in multiple dimensions, which is more in line with the comprehensive needs of the actual complex power grid operation. Secondly, the particle swarm algorithm and the hierarchical analysis method are organically combined. The particle swarm algorithm is good at performing global search in a complex solution space to find multiple non-inferior solutions, while the hierarchical analysis method can perform reasonable comprehensive evaluation and decision-making selection based on the importance of different indicators on the basis of multiple non-inferior solutions. The combination of the two gives full play to their respective advantages, effectively making up for the limitations of a single algorithm in solving such complex multi-objective decision-making problems, and improving the scientificity and rationality of the final access scheme determination.

[0077] The following makes assumptions about some basic parameters of the receiving grid under study, so as to facilitate the subsequent introduction of relevant evaluation indicators. dc The rated power of each circuit is P1, P2, ..., P Ndc ; There are M buses whose short-circuit current needs to be examined, which are denoted as B1, B2, ..., B M There are N candidate channels that can be connected to the back-to-back flexible DC. The maximum transmittable active power of the back-to-back flexible DC that can be constructed by the i-th channel is P max,i ,i=1,2,...,N;Assume that for back-to-back flexible DC, its rated reactive power is α times of the rated active power. For a given multi-back-to-back flexible DC access scheme {P e1 ,P e2 ,...,P eN}, P ei Rated active power of the back-to-back flexible DC power supply configured for the i-th channel.

[0078] In one embodiment of the present invention, a risk index Id1 caused by conventional DC commutation failure is defined as one of the evaluation indicators. For a multi-circuit back-to-back flexible DC solution to be evaluated, given a test fault set {F1,,..,F R} and mode data, for fault F j , N dc The commutation failure of the conventional DC is {u 1,j ,u 2,j ,...,u Ndc,j},u i,j =1 or 0, 1 represents commutation failure, 0 represents no commutation failure, i=1,2,...,N dc . Then the indicator Id1 is:

[0079] (1)

[0080] In the formula, is a risk indicator caused by the conventional DC commutation failure; is the number of faults in a given test fault set, is the fault sequence number index; is the number of conventional DC circuits fed into the receiving power grid, It is the conventional DC serial number index; Fault F j In the case of commutation failure of the conventional DC circuit, u i,j =1 means the ith DC current is at F j Commutation failure occurs under fault conditions; is the transmission power of the i-th conventional DC.

[0081] In another embodiment of the present invention, the maximum short-circuit current index Id2 of the system is defined as one of the evaluation indicators. For the multi-circuit back-to-back flexible DC scheme to be evaluated, given the operation mode data, the busbars {B1, B2, ..., B M}, calculate the three-phase and single-phase short-circuit current of each bus, denoted as I abc,i and I a,i ,i=1,2,...,M。I max ,I min is the pre-set short-circuit current threshold value, then the indicator Id2 is:

[0082] (2)

[0083] In the formula, is the maximum short-circuit current index of the system; is the number of buses with short-circuit current, The bus serial number index of the short-circuit current; and For the The three-phase current and single-phase short-circuit current of the bus; I max and I min is the short-circuit current threshold.

[0084] In another embodiment of the present invention, the back-to-back flexible DC access scheme construction cost Id3 is defined as one of the evaluation indicators. For the multi-circuit back-to-back flexible DC scheme to be evaluated, it is assumed that the back-to-back flexible DC construction cost of the i-th channel is C i Yuan / unit capacity. Then the indicator Id3 is:

[0085] (3)

[0086] In the formula, The construction cost of the back-to-back flexible DC access solution; is the number of candidate channels that can be connected to back-to-back flexible DC, is the candidate channel sequence index, is the back-to-back flexible DC construction cost of the i-th channel, The rated active power of the back-to-back flexible DC configured for the i-th channel, is the upper limit of construction cost, Whether the i-th channel is configured with back-to-back flexible DC, Indicates configuration, Indicates no configuration.

[0087] In another embodiment of the present invention, a system stability level indicator Id4 is defined. For a multi-circuit back-to-back flexible DC scheme to be evaluated, given operation mode data and a fault set { , ,.., }(common Faults), the system stability characteristics of the system under a given fault set are analyzed through time domain simulation. With the goal of minimizing the number of faults that make the system lose stability, the following optimization model is established and solved using the particle swarm optimization algorithm.

[0088] (4)

[0089] , i=1,...,N(5)

[0090] In the formula, is the stability level indicator of the system, The minimum number of failures that cause the system to lose stability, The number of failures in the given test failure set.

[0091] With the goal of minimizing the number of failures that cause the system to lose stability, the following optimization model is established and solved using the particle swarm optimization algorithm.

[0092] Objective function: , K is the number of failures that cause the system to lose stability (6)

[0093] The solution process using particle swarm algorithm is as follows:

[0094] The actual transmission power of the back-to-back flexible DC access scheme to be evaluated is used as the optimization variable to solve the problem. Assume that the particle swarm has S particles. For particle i, , It refers to the transmission power of the jth back-to-back flexible DC in the configuration scheme to be evaluated, , is the rated capacity of the jth back-to-back flexible DC link, is the number of channels configured with back-to-back flexible DC. For particle i, a fault time domain simulation analysis is performed based on the given operation mode data and fault set, and the total number of faults that cause the system to lose stability is counted as the fitness value of the particle. The smaller the fitness, the better the particle, which is recorded as , n is the number of iterations, and the best result for the particle after the nth iteration is recorded as (with the smallest fitness value) .

[0095] Update each particle according to the following formula:

[0096] (7)

[0097] (8)

[0098] (9)

[0099] (10)

[0100] In the formula, , , , are control parameters, n, N iter is the current iteration number and the total iteration number, and rand() is a random number between (0,1). represents the value of the jth position of the ith particle after the nth iteration, Ulocal i,j (n) is the value of the jth position of the local optimal individual of the ith particle after the nth iteration, Uglobal j (n) is the value of the jth position of the optimal individual of the entire particle swarm after the nth iteration. i,j (n) represents the velocity value of the i-th particle at the j-th position after the n-th iteration, , Respectively represent V i,j (n) The lower and upper limits. Represents the best particle (with the smallest fitness) of the particle swarm after the nth iteration.

[0101] Repeat the above iterative process until the termination condition is met. The number of failures that cause the system to lose stability corresponding to the optimal solution at this time is recorded as K min , then Id4 can be obtained according to formula (4).

[0102] When evaluating the multi-circuit back-to-back flexible direct current access scheme, the above four evaluation indicators are set. For each access scheme, the specific values ​​of these evaluation indicators can be calculated by the indicator calculation method proposed in the above embodiment. In order to solve the multi-objective optimization problem of making the schemes evaluated by these evaluation indicators reach a non-inferior state, the present invention adopts a multi-objective particle swarm optimization algorithm. The algorithm continuously explores and approaches the frontier of non-inferior solutions in the target space composed of multiple evaluation indicators through iterative search and information sharing of particle groups, thereby determining a series of non-inferior solutions that meet the requirements of multi-objective optimization.

[0103] According to the four evaluation indicators provided in the above embodiments, the following multi-objective optimization model for the multi-circuit back-to-back flexible DC access solution can be established:

[0104] The objective function f=(f1,f2,f3,f4), where

[0105] The optimization variable is the rated capacity of the back-to-back flexible DC connected to the N candidate channels that can be connected to the back-to-back flexible DC (P e1 ,P e2 ,...,P eN ), P ei ≤P max,i , i=1,2,...,N. For multi-objective optimization problems, in one embodiment of the present invention, a method for solving a pre-established multi-objective optimization model using a multi-objective particle swarm algorithm is provided, wherein the method sets the particle swarm as a master particle swarm, several slave particle swarms, and a reserve set; the several slave particle swarms correspond one-to-one to several evaluation indicators and are optimized as their respective objectives. Taking the multi-objective optimization problem consisting of the above four evaluation indicators as an example, the method divides the particle swarm into a master particle swarm, four slave particle swarms, and a reserve set. The reserve set is used to store Pareto optimal solutions. Slave particle swarm 1 is optimized with f1 as the target, particle swarm 2 is optimized with f2 as the target, particle swarm 3 is optimized with f3 as the target, and particle swarm 4 is optimized with f4 as the target. Taking the above four evaluation indicators as an example, the specific process of the multi-group particle swarm algorithm is introduced as follows:

[0106] a. Initialization. Read the maximum transmittable active power P of the candidate channels that can be connected to the back-to-back flexible DC. max,i , i=1,2,...,N. Read in all the data needed to calculate the indicator.

[0107] b. Divide the particle swarm into 1 master particle swarm and 4 slave particle swarms. Optimize the slave particle swarm 1 with f1 as the target, optimize the slave particle swarm 2 with f2 as the target, optimize the slave particle swarm 3 with f3 as the target, and optimize the slave particle swarm 4 with f4 as the target. Initialize the particle swarm parameters, including the master and slave population size, learning factor, inertia weight, upper and lower limits of particle position and speed, and maximum number of iterations; initialize each particle swarm (randomly generate the position of particles) and particle speed, calculate the four index values ​​of each particle, and save the non-inferior solutions in the master and slave particle swarms to the external reserve set.

[0108] c. Randomly select particles from the external reserve set as the global guiding particles of the master particle group, and each slave particle group uses the particle with the best corresponding optimization target in the external reserve set as the global guiding particle. The master and slave particle groups are iteratively updated according to the iterative search formula of the particles (such as equations 11 and 12 in the subsequent embodiments) to calculate the fitness value of each particle. For the master particle group, if the new particle is not dominated by its local optimal solution, it becomes the local guiding particle of the original particle.

[0109] d. After each iteration, the non-inferior extreme value particles obtained from the particle swarm are added to the main particle swarm, and the non-inferior particles obtained from the master and slave particle swarms are added to the external reserve set, the reserve set is updated, and the particles in the reserve set that are not non-inferior solutions are removed.

[0110] e. Repeat steps c and d until the termination condition is met. The non-inferior solution set in the external reserve is the Pareto optimal solution set. Assume that there are N best , denoted as S1, S2, ..., S Nbest , each non-inferior solution represents a back-to-back flexible DC access scheme.

[0111] Based on the process of solving the multi-objective optimization model by the particle swarm algorithm provided in the above embodiment, in a further embodiment of the present invention, particles in the particle swarm perform iterative search in the solution space according to individual local guide particles and global guide particles, and the formula is as follows:

[0112] (11)

[0113] (12)

[0114] In the formula, , are the search speeds of the d-th variable of particle i at the k+1th and kth iterations, respectively. , V max,d 、V min,d are the upper and lower limits of the search speed of the dth variable; ω is the inertia weight; c1 and c2 are learning factors; r1 and r2 are random numbers that obey uniform distribution on [0, 1]; , , are the current value of the d-th variable position of particle i in the k-th iteration, the value of the d-th variable position of the individual local guide particle, and the value of the d-th variable position of the global guide particle. The global guide particle is given by the external reserve set. After each iteration, the best particles are passed to the external reserve set.

[0115] In one embodiment, a hierarchy analysis method is used to select several multi-circuit back-to-back flexible direct current access schemes, including:

[0116] S uses the first matrix and the second matrix to respectively calculate the first weight coefficients of several evaluation indicators and the second weight coefficients of several candidate multi-circuit back-to-back flexible direct current access schemes under several evaluation indicators; the first matrix and the second matrix are judgment matrices of the highest layer and the middle layer, and the middle layer and the lowest layer, respectively;

[0117] The final weight coefficient of each multi-circuit back-to-back flexible DC access scheme is calculated based on the first weight coefficient and the second weight coefficient, and the candidate scheme with the largest final weight coefficient is selected as the final DC access scheme; the final weight coefficient is calculated according to the following formula:

[0118] (13)

[0119] In the formula, For the The final weight coefficient of the candidate solutions is is the number of evaluation indicators, is the first weight coefficient after normalization of the jth evaluation index, For the The second weight coefficient of the candidate solutions after normalization under the jth evaluation index.

[0120] In a further embodiment, the values ​​of the elements of the first matrix and the second matrix are determined using a 9-level comparison scale.

[0121] The following introduces the selection of the final DC access solution by the analytic hierarchy process using the four indicators proposed in the above embodiment as an example. Figure 2 The hierarchical structure shown in the figure has the highest level (overall target level) as the final multi-circuit back-to-back flexible DC access scheme, the middle level (reference level) as the four types of indicators considered, and the lowest level (scheme level) as the candidate multi-circuit back-to-back flexible DC access schemes (i=1,…,N best ).

[0122] Paired comparative analysis was conducted on adjacent upper and lower layers (the highest layer and the middle layer, the middle layer and the lowest layer) using a 9-level comparison scale, as shown in Table 1:

[0123]

[0124] The judgment matrix A of the highest layer and the middle layer is calculated as:

[0125] (14)

[0126] The element a in the matrix A ij Representative indicator ID i With Id j The comparison result is the same. According to the specific values ​​of the four types of indicators of each candidate line, the judgment matrices of the middle and bottom indicators Id1, Id2, Id3, and Id4 are obtained as B1, B2, B3, and B4 respectively:

[0127] ,j=1,2,3,4(15)

[0128] Matrix B j Elements in Represents the indicator ID j Next candidate route S k With S l According to the hierarchical analysis method, matrix A and matrix B need to be compared. j (j=1,…,4) to perform consistency check. If the consistency check fails, it is necessary to check the matrix A and the matrix B. j (j=1,…,5) and re-modify until the consistency check is satisfied.

[0129] When matrix A and matrix B j When the consistency test is satisfied, the weight coefficient of each candidate solution for achieving the overall goal is calculated. First, the weight coefficients of the four types of indicators (after normalization) are obtained through matrix A, which are: w A1 、w A2 、w A3 、w A4 , each candidate solution S i (i=1,…,N best ) in the indicator Id j The weight coefficients (after normalization) of (j=1,…,4) are: w Bi_1 、w Bi_2 ,…,w Bi_4 According to formula 13, we finally get the candidate solution S i The larger the final weight coefficient of a line, the more critical the line is.

[0130] Based on the same inventive concept, the embodiment of the present application also provides a device for determining a multi-circuit back-to-back flexible DC access scheme for implementing the method for determining a multi-circuit back-to-back flexible DC access scheme involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the embodiment of the device for determining a multi-circuit back-to-back flexible DC access scheme provided below can be referred to the limitations of the method for determining a multi-circuit back-to-back flexible DC access scheme above, and will not be repeated here.

[0131] See also Figure 3 The embodiment of the present invention further provides a device for determining a multi-circuit back-to-back flexible direct current access scheme, comprising:

[0132] A data acquisition module is used to obtain basic parameters of the receiving-end power grid under study based on a pre-built evaluation system; the evaluation system includes several evaluation indicators for evaluating the multi-circuit back-to-back flexible DC access scheme;

[0133] The model solving module is used to solve the pre-established multi-objective optimization model based on basic parameters by using a multi-objective particle swarm algorithm to obtain several non-inferior solutions, each of which is a multi-circuit back-to-back flexible DC access scheme for the receiving-end power grid; the multi-objective optimization model is a mathematical model that takes the optimization of several evaluation indicators of the multi-circuit back-to-back flexible DC access scheme as the optimization objective, and takes the rated capacity of each back-to-back flexible DC in each multi-circuit back-to-back flexible DC access scheme as the optimization variable;

[0134] The scheme determination module is used to select the multi-circuit back-to-back flexible DC access schemes corresponding to several non-inferior solutions using the hierarchical analysis method to obtain the final multi-circuit back-to-back flexible DC access scheme; the bottom layer of the hierarchical analysis method is several candidate multi-circuit back-to-back flexible DC access schemes, the middle layer is several evaluation indicators, and the top layer is the final DC access scheme.

[0135] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the system can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiment can be integrated in a processing unit, or each unit can exist physically separately, or two or more units can be integrated in one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units and modules in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0136] Reference Figure 4 An embodiment of the present invention further provides a computer device, comprising: a memory and a processor and a computer program stored in the memory. When the computer program is executed on the processor, a method for determining a multi-circuit back-to-back flexible direct current access scheme as described in any one of the above methods is implemented.

[0137] The computer device may be a desktop computer, a notebook, a PDA, a cloud server or other computing device. The computer device may include, but is not limited to, a processor and a memory. Those skilled in the art will understand that Figure 4 It is only an example of a computer device and does not constitute a limitation of the computer device. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, it may also include input and output devices, network access devices, etc.

[0138] The processor may be a central processing unit (CPU), other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0139] In some embodiments, the memory may be an internal storage unit of the computer device, such as a hard disk or memory of the computer device. In other embodiments, the memory may also be an external storage device of the computer device, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. equipped on the computer device. Further, the memory may include both an internal storage unit and an external storage device of the computer device. The memory is used to store an operating system, an application program, a boot loader (BootLoader), data, and other programs, such as the program code of the computer program. The memory may also be used to temporarily store data that has been output or is to be output.

[0140] An embodiment of the present invention further provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for determining a multi-circuit back-to-back flexible direct current access scheme as described in any one of the above methods is implemented.

[0141] In this embodiment, if the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the steps of the above-mentioned various method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium can at least include: any entity or device that can carry the computer program code to the camera / terminal device, recording medium, computer memory, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), electric carrier signal, telecommunication signal and software distribution medium. For example, USB flash drive, mobile hard disk, disk or optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals and telecommunication signals.

[0142] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0143] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0144] In the embodiments disclosed in the present application, it should be understood that the disclosed devices / terminal equipment and methods can be implemented in other ways. For example, the device / terminal equipment embodiments described above are only schematic. For example, the division of the modules or units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0145] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for determining a multi-circuit back-to-back flexible direct current access scheme, characterized in that: The steps include: Obtaining basic parameters of the receiving-end power grid under study based on a pre-built evaluation system; the evaluation system includes a number of evaluation indicators for evaluating a multi-circuit back-to-back flexible direct current access solution; Based on the basic parameters, a multi-objective particle swarm algorithm is used to solve a pre-established multi-objective optimization model to obtain several non-inferior solutions, each of which is a multi-circuit back-to-back flexible DC access scheme for the receiving power grid; the multi-objective optimization model is a mathematical model that takes the optimization of several evaluation indicators of the multi-circuit back-to-back flexible DC access scheme as the optimization target, and takes the rated capacity of each back-to-back flexible DC in each of the multi-circuit back-to-back flexible DC access scheme as the optimization variable; A hierarchical analysis method is used to select the multiple back-to-back flexible DC access schemes corresponding to several non-inferior solutions to obtain a final multiple back-to-back flexible DC access scheme; the bottom layer of the hierarchical analysis method is several candidate multiple back-to-back flexible DC access schemes, the middle layer is several evaluation indicators, and the top layer is the final DC access scheme.

2. The method for determining a multi-circuit back-to-back flexible direct current access scheme according to claim 1, characterized in that: The multi-objective particle swarm algorithm is used to solve the pre-established multi-objective optimization model and obtain several non-inferior solutions, including: Setting and initializing a particle swarm; the particle swarm includes a master particle swarm, several slave particle swarms and a reserve set; the several slave particle swarms correspond to the several evaluation indicators one by one and are optimized as their respective goals; Iteratively updating the particle swarm; the iterative updating operation includes randomly selecting particles from the reserve set as global guiding particles of the master particle swarm, each of the slave particle swarms uses the best particle in the reserve set corresponding to the respective optimization target as the global guiding particle, and the master and slave particle swarms are iteratively updated based on their respective global guiding particles and local guiding particles; The reserve set is updated; the update operation includes adding the non-inferior extreme value particles obtained from the slave particle group to the master particle group after each iteration, adding the non-inferior particles obtained from the master and slave particle groups to the reserve set, and updating the reserve set to remove particles in the reserve set that are not non-inferior solutions; Repeat the iterative update operation of the particle swarm and the update operation of the reserve set until the termination condition is met, and obtain a non-inferior solution set in the reserve set, each non-inferior solution in the solution set represents a back-to-back flexible DC access scheme.

3. The method for determining a multi-circuit back-to-back flexible direct current access scheme according to claim 2, characterized in that: In the iterative update of the master-slave particle swarm based on their respective global guide particles and local guide particles, the iterative search formula is as follows: In the formula, , are the search speeds of the dth variable of particle i at the k+1th and kth iterations, respectively; ω is the inertia weight; c1 and c2 are learning factors; r1 and r2 are random numbers that obey uniform distribution on [0, 1]; , , They are respectively the current value of the d-th variable position of particle i in the k-th iteration, the value of the d-th variable position of the individual local guiding particle, and the value of the d-th variable position of the global guiding particle.

4. The method for determining a multi-circuit back-to-back flexible direct current access scheme according to claim 1 or 2, characterized in that: The evaluation index includes the risk index caused by conventional DC commutation failure. For the multi-circuit back-to-back flexible DC access scheme to be evaluated, in a given test fault set {F1,,..,F R } and operation mode data, for the fault F in the test fault set j , the calculation expression of the risk index is as follows: In the formula, is a risk indicator caused by the conventional DC commutation failure; is the number of faults in a given test fault set, is the fault sequence number index; is the number of conventional DC circuits fed into the receiving power grid, It is the conventional DC serial number index; F j Next, Back to the conventional DC commutation failure situation, u i,j =1 means Back to normal DC at fault F j Commutation failure occurs, u i,j =0 means Back to normal DC at fault F j No commutation failure occurred; For the Back to conventional DC transmission power.

5. The method for determining a multi-circuit back-to-back flexible direct current access scheme according to claim 1 or 2, characterized in that: The evaluation index also includes the maximum short-circuit current index of the system. For the multi-circuit back-to-back flexible DC access scheme to be evaluated, under given operation mode data, for the busbars {B1, B2, ..., B M }, the calculation expression of the maximum short-circuit current index of the system is as follows: In the formula, is the maximum short-circuit current index of the system; To investigate the number of buses with short-circuit current, The bus number index for examining the short-circuit current; and For the The three-phase current and single-phase short-circuit current of the bus; I max and I min is the short-circuit current threshold.

6. The method for determining a multi-circuit back-to-back flexible direct current access scheme according to claim 1 or 2, characterized in that: The evaluation index also includes the construction cost of the back-to-back flexible DC access scheme. For the multiple back-to-back flexible DC access schemes to be evaluated, the calculation expression of the construction cost of the back-to-back flexible DC access scheme is as follows: In the formula, The construction cost of the back-to-back flexible DC access solution; is the number of candidate channels that can be connected to back-to-back flexible DC, is the candidate channel sequence index, For the The construction cost of the unit capacity of back-to-back flexible direct current channels is For the The rated active power of the back-to-back flexible DC with 1 channel configuration, is the upper limit of construction cost, Whether the i-th channel is configured with back-to-back flexible DC, Indicates configuration, Indicates no configuration.

7. The method for determining a multi-circuit back-to-back flexible direct current access scheme according to claim 1 or 2, characterized in that: The evaluation index also includes a system stability level index. For the multi-circuit back-to-back flexible DC access scheme to be evaluated, under a given fault set { , ,.., } and operation mode data, the calculation expression of the system stability level index is as follows: In the formula, is the stability level indicator of the system, The minimum number of failures that cause the system to lose stability, is the number of faults in a given fault set.

8. The method for determining a multi-circuit back-to-back flexible direct current access scheme according to claim 7, characterized in that: The minimum number of failures that cause the system to lose stability in the system stability level indicator The particle swarm algorithm is used to solve the problem. The solution process includes the following steps: Set the objective function to , K is the number of faults that cause the system to lose stability; Set a particle swarm; the particle swarm has a total of S particles, for particle i, , It refers to the transmission power of the jth back-to-back flexible DC in the scheme to be evaluated, , is the rated capacity of the jth back-to-back flexible DC link, The number of channels configured with back-to-back flexible DC; For particle i, a fault time domain simulation analysis is performed based on the given operation mode data and fault set; the total number of faults that cause the system to lose stability is counted as the fitness value of the particle. The smaller the fitness, the better the particle, which is recorded as , n is the number of iterations, and the best result for the particle after the nth iteration is recorded as ; Update each particle according to the following formula: In the formula, , , , are control parameters, n, N iter is the current iteration number and the total iteration number, rand() is a random number between (0,1); represents the value of the jth position of the ith particle after the nth iteration, Ulocal i,j (n) is the value of the jth position of the local optimal individual of the ith particle after the nth iteration, Uglobal j (n) is the value of the jth position of the optimal individual of the entire particle swarm after the nth iteration; V i,j (n) represents the velocity value of the i-th particle at the j-th position after the n-th iteration, , Respectively represent V i,j (n) lower and upper limits; represents the best particle of the particle swarm after the nth iteration; Repeat the above iterative process until the termination condition is met. The number of failures that cause the system to lose stability corresponding to the optimal solution at this time is recorded as .

9. The method for determining a multi-circuit back-to-back flexible direct current access scheme according to claim 1, characterized in that: The analytic hierarchy process is used to select the multiple back-to-back flexible direct current access schemes corresponding to the non-inferior solutions, including: The first matrix and the second matrix are used to respectively calculate the first weight coefficients of the plurality of evaluation indicators and the second weight coefficients of the plurality of candidate multi-circuit back-to-back flexible direct current access schemes under the plurality of evaluation indicators; the first matrix and the second matrix are judgment matrices of the highest layer and the middle layer, and the middle layer and the lowest layer, respectively; The final weight coefficient of each of the multiple back-to-back flexible DC access schemes is calculated based on the first weight coefficient and the second weight coefficient, and the candidate scheme with the largest final weight coefficient is selected as the final DC access scheme; the final weight coefficient is calculated according to the following formula: In the formula, For the The final weight coefficient of the candidate solutions is is the number of evaluation indicators, is the first weight coefficient after normalization of the j-th evaluation index, For the The second weight coefficient of a candidate solution normalized under the jth evaluation index.

10. A device for determining a multi-circuit back-to-back flexible direct current access scheme, characterized in that: include: A data acquisition module, used to acquire basic parameters of the receiving-end power grid under study based on a pre-built evaluation system; the evaluation system includes a number of evaluation indicators for evaluating a multi-circuit back-to-back flexible direct current access scheme; A model solving module is used to solve a pre-established multi-objective optimization model based on the basic parameters using a multi-objective particle swarm algorithm to obtain a plurality of non-inferior solutions, each of which is a multi-circuit back-to-back flexible direct current access scheme for the receiving-end power grid; the multi-objective optimization model is a mathematical model that takes the optimization of a plurality of evaluation indicators of the multi-circuit back-to-back flexible direct current access scheme as an optimization target, and takes the rated capacity of each back-to-back flexible direct current in each of the multi-circuit back-to-back flexible direct current access scheme as an optimization variable; The scheme determination module is used to select the multiple back-to-back flexible DC access schemes corresponding to the multiple non-inferior solutions by using a hierarchical analysis method to obtain a final multiple back-to-back flexible DC access scheme; the bottom layer of the hierarchical analysis method is the multiple candidate multiple back-to-back flexible DC access schemes, the middle layer is the multiple evaluation indicators, and the top layer is the final DC access scheme.

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