A Coordination Optimization Method and System for Inter-region Tie Lines

Abstract

The present invention relates to a method and system for coordinated optimization of inter-region tie lines, randomly generating tie line plans for each scheduling period of multiple inter-region tie lines; determining feasible tie line plans under the current unit commitment mode of the regional power grid based on predefined feasibility determination conditions; determining the feasibility of the tie line plans for the current unit commitment modes of all regional power grids, and when feasible, outputting the current tie line plan, and the formulation of the tie line plan is completed; otherwise, using a distributed penalty primal-dual subgradient optimization algorithm to perform coordinated optimization on the tie line plan and the regional power grids connected thereto to obtain a new tie line plan, and then performing the previous step. Through the above solution, rapid matching of inter-region tie line plans among regional power grids is achieved, and at the same time, the data privacy of each regional power grid is protected.

Description

Technical Field

[0001] The present invention belongs to the field of optimal dispatching of power systems, and particularly relates to a coordinated optimization method and system for inter-regional tie lines. Background Art

[0002] At present, the contradiction between economic development and the uneven distribution of energy resources is prominent. To achieve the optimal allocation of power resources on a larger scale and give full play to the advantages of interconnected power grids in the comprehensive energy transportation system, carrying out inter-regional power trading is conducive to promoting the adjustment of the surplus and deficiency of power resources between regions, the supply-demand complementarity of the power system, and is of great significance for the transmission and consumption of large-scale traditional power sources and renewable energy.

[0003] With the large-scale grid connection of renewable energy and the increasing maturity of the demand-side response mechanism, the uncertainty of the net load of the power system increases, and it is necessary to consider both the positive and negative reserves of the system to ensure the safe and reliable operation of the system. However, the unit commitment model considering positive and negative reserves is more complex than the traditional unit commitment problem, and the solution difficulty becomes larger.

[0004] The existing formulation of the inter-regional tie line plan generally collects the power grid data of all regions in a centralized manner and conducts unified optimal dispatching. With the continuous expansion of the scale of the interconnected power grid, the solution time of the problem will increase sharply, and at the same time, the massive data may cause communication congestion between the dispatching center and each regional power grid; in addition, the centralized method is not conducive to protecting the privacy of the data of each regional power grid. Summary of the Invention

[0005] To make up for the above defects, the present invention provides a coordinated optimization method and system for inter-regional tie lines. Based on the known adjacency relationship of each regional power grid, a distributed optimization method is adopted, and through a consensus coordination mechanism, a reasonable tie line plan is realized.

[0006] The object of the present invention is achieved by the following technical solutions:

[0007] A coordinated optimization method for inter-regional tie lines, the method comprising:

[0008] S1: Randomly generate tie line plans for each scheduling period of multiple inter-regional tie lines;

[0009] S2: Based on the predefined feasibility determination conditions, determine the feasible tie line plans under the current unit commitment mode of the regional power grid;

[0010] S3: Determine the feasibility of the tie-line plan for the current unit commitment modes of all regional power grids. When it is feasible, output the current tie-line plan, and the formulation of the tie-line plan is completed; otherwise, use the distributed penalty primal-dual subgradient optimization algorithm to coordinately optimize the tie-line plan and the regional power grids it is connected to, obtain a new tie-line plan, and then execute step S2.

[0011] Preferably, determining a feasible tie-line plan under the current unit commitment mode of the regional power grid based on predefined feasibility determination conditions includes:

[0012] Construct an incidence matrix between the regional power grid and the inter-regional tie-lines based on the regional power grid system topology diagram;

[0013] Obtain the transmission power on the inter-regional tie-lines based on the incidence matrix between the regional power grid and the inter-regional tie-lines;

[0014] Substitute the sum of the transmission powers of the inter-regional tie-lines into the feasibility determination conditions of the economic allocation problems considering positive and negative reserves of the corresponding regional power grids respectively. If the feasibility determination conditions are met, it indicates that the tie-line plan is feasible under the current unit commitment mode of the regional power grid.

[0015] Furthermore, the feasibility determination conditions are as follows:

[0016]

[0017]

[0018]

[0019]

[0020] where, i is the unit number, n is the regional power grid number, t is the time period number, l is the tie-line number; I' n is the set of currently online units in regional power grid n; P i are the upper and lower limits of the output of unit i; are the maximum positive and negative reserve amounts that unit i can provide; are the positive and negative reserve demands of regional power grid n in time period t; D n,t is the load demand of regional power grid n in time period t; is the incidence relationship between regional power grid n and tie-line l; 1 indicates that regional power grid n transmits power, -1 indicates that regional power grid n receives power, and 0 indicates that there is no direct association between regional power grid n and tie-line l; f l,t is the transmission power of tie-line l in time period t.

[0021] Preferably, the determination of the feasibility of the tie-line plan for the current unit combination mode of all regional power grids includes:

[0022] Introduce the Lagrange multiplier in the regional power grid, relax the cross-regional transaction power constraint, and transform the tie-line plan formulation problem of the regional power grid into an unconstrained optimization problem;

[0023] Compare the current tie-line plan output after introducing the Lagrange multiplier and relaxing the cross-regional transaction power constraint with the previous tie-line plan, and determine whether there is a change between the tie-line plan and the previous tie-line plan. If there is no change, it means that the current tie-line plan is feasible for all regional power grids.

[0024] Further, introduce the Lagrange multiplier in the regional power grid through the following formula to relax the cross-regional transaction power constraint, and transform the tie-line plan formulation problem of the regional power grid into an unconstrained optimization problem:

[0025]

[0026]

[0027] where E l is the total transaction power of tie-line l, [·] + represents non-negative operation, f l,t is the transmission power of tie-line l at time t, is the boundary of the transmission power; μ n,t and ω n,t are both introduced multipliers, f t is the total transmission power of all tie-lines connected to regional power grid n at time t; is the positive and negative reserve requirements of regional power grid n at time t.

[0028] Further, judge whether there is a change between the tie-line plan and the previous tie-line plan through the following formula:

[0029]

[0030] where k represents the number of iterations, is the current tie-line plan, is the previous tie-line plan, and ε is a preset threshold.

[0031] Preferably, the use of the distributed penalty primal-dual subgradient optimization algorithm to coordinately optimize the tie-line plan and the regional power grid connected thereto to obtain a new tie-line plan includes:

[0032] For each regional power grid, obtain the tie-line transmission power variable of the tie-line plan and the subgradient of the Lagrange multiplier;

[0033] Update the tie-line transmission power variable along its negative gradient direction and perform a projection operation within the feasible region, and update the multiplier variable along its positive gradient direction;

[0034] Calculate the subgradients of the updated tie-line transmission power variable and the Lagrange multiplier, and perform consensus coordination on the updated tie-line transmission power variable and the subgradients of the Lagrange multiplier with the connected regional power grid to obtain a new tie-line plan.

[0035] Furthermore, determine the subgradient of the tie-line transmission power variable through the following formula:

[0036]

[0037] where, is the subgradient of the tie-line transmission power variable, is the previous tie-line plan; P i are the upper and lower limits of the output of unit i; E l is the total transaction power of tie-line l, D n,t is the load demand of regional power grid n at time t; is the association relationship between regional power grid n and tie-line l; are the positive and negative reserve demands of regional power grid n at time t.

[0038] Furthermore, determine the subgradient of the Lagrange multiplier through the following formula:

[0039]

[0040]

[0041]

[0042] where, are the subgradients of the Lagrange multipliers μ n,t and ω n,t respectively.

[0043] Furthermore, determine the feasible region of the tie-line transmission power variable through the following formula:

[0044]

[0045] where, is the boundary of the transmission power.

[0046] Further, the updated tie-line transmission power variable and Lagrange multiplier are determined by the following formula:

[0047]

[0048]

[0049]

[0050]

[0051] In the formula, is the updated tie-line transmission power variable, μ n,t (k + 1), ω n,t (k + 1) are both updated Lagrange multipliers.

[0052] Further, a new tie-line plan is determined by the following formula:

[0053]

[0054]

[0055] Preferably, the tie-line plans for each scheduling period of randomly generating multiple inter-regional tie-lines include:

[0056] According to the total length of the scheduling period and the scheduling period interval, the transmission power plans for each scheduling period of multiple inter-regional tie-lines are randomly generated to formulate the tie-line plan.

[0057] A coordinated optimization system for inter-regional tie-lines, the system includes:

[0058] A generation module, configured to randomly generate tie-line plans for each scheduling period of multiple inter-regional tie-lines;

[0059] A determination module, configured to determine a feasible tie-line plan under the current unit combination mode of the regional power grid based on predefined feasibility determination conditions;

[0060] A coordinated optimization module, configured to determine the feasibility of the tie-line plan for the current unit combination mode of all regional power grids. When feasible, output the current tie-line plan, and the tie-line plan is formulated; otherwise, use the distributed penalty primal-dual subgradient optimization algorithm to coordinate and optimize the tie-line plan and the regional power grid connected thereto to obtain a new tie-line plan, and then execute the determination module.

[0061] Compared with the closest prior art, the present invention has the following beneficial effects:

[0062] The solution of the present invention provides a method and system for coordinated optimization of inter-regional tie lines. First, the tie line plans for each scheduling period of multiple inter-regional tie lines are randomly generated. Secondly, based on the pre-defined feasibility determination conditions, the feasible tie line plans under the current unit commitment mode of the regional power grids are determined. The feasibility determination conditions can quickly and accurately judge the feasibility of the current solution by calculating four simple inequalities, which can improve the solution efficiency of the problem.

[0063] Finally, the feasibility of the tie line plan for the current unit commitment mode of all regional power grids is determined. When it is feasible, the current tie line plan is output and the formulation of the tie line plan is completed. Otherwise, the distributed penalty primal-dual subgradient optimization algorithm is used to coordinately optimize the tie line plan and the regional power grids connected thereto to obtain a new tie line plan, and then the previous step is executed. According to the adjacency relationship of each regional power grid, all regional power grids only need to exchange a small amount of data with their neighboring power grids in a distributed optimization manner, and the accurate and reasonable formulation of the tie line plan is realized through a consensus mechanism. This method not only avoids dealing with massive data, improves the solution efficiency of the problem, realizes the rapid matching of the inter-regional tie line plans among the regional power grids, but also protects the data privacy of each regional power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 is the general method flow chart in the specific embodiment of the present invention;

[0065] Figure 2 is the flow chart of the tie line coordinated optimization algorithm in the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0066] The following will describe in detail the specific embodiments of the present invention with reference to the drawings.

[0067] A method for coordinated optimization of inter-regional tie lines provided by the present invention, as Figure 1 shown, includes:

[0068] S1: Randomly generate the tie line plans for each scheduling period of multiple inter-regional tie lines;

[0069] S2: Based on the pre-defined feasibility determination conditions, determine the feasible tie line plans under the current unit commitment mode of the regional power grids;

[0070] S3: Determine the feasibility of the tie line plan for the current unit commitment mode of all regional power grids. When it is feasible, output the current tie line plan and the formulation of the tie line plan is completed. Otherwise, use the distributed penalty primal-dual subgradient optimization algorithm to coordinately optimize the tie line plan and the regional power grids connected thereto to obtain a new tie line plan, and then execute step S2.

[0071] In step S1, the tie-line plan for each scheduling period of randomly generating multiple inter-regional tie-lines described in 1 includes: according to the total length of the scheduling period and the scheduling period interval, randomly generating the transmission power plan for each scheduling period of multiple inter-regional tie-lines, and formulating the tie-line plan.

[0072] In step S2, determining the feasible tie-line plan under the current unit combination mode of the regional power grid based on the pre-defined feasibility determination conditions includes:

[0073] Constructing an incidence matrix between the regional power grid and the inter-regional tie-lines based on the regional power grid system topology diagram;

[0074] Based on the incidence matrix between the regional power grid and the inter-regional tie-lines, obtaining the transmission power on the inter-regional tie-lines;

[0075] Substituting the sum of the transmission powers of the inter-regional tie-lines into the feasibility determination conditions of the economic allocation problem considering positive and negative reserves of the corresponding regional power grid respectively. If the feasibility determination conditions are met, it means that the tie-line plan is feasible under the current unit combination mode of the regional power grid.

[0076] Among them, the feasibility determination conditions are as follows:

[0077]

[0078]

[0079]

[0080]

[0081] In the formula, i is the unit number, n is the regional power grid number, t is the time period number, and l is the tie-line number; I' n is the set of currently operating units in regional power grid n; P i are the upper and lower limits of the output of unit i; is the maximum positive and negative reserve that unit i can provide; are the positive and negative reserve demands of regional power grid n in time period t; D n,t is the load demand of regional power grid n in time period t; is the incidence relationship between regional power grid n and tie-line l; 1 means that regional power grid n supplies power, -1 means that regional power grid n receives power, and 0 means that there is no direct connection between regional power grid n and tie-line l; f l,t is the transmission power of tie-line l in time period t.

[0082] Step S3, determining the feasibility of the tie-line plan for the current unit combination modes of all regional power grids includes:

[0083] Introduce the Lagrange multiplier into the regional power grid to relax the cross - regional transaction power constraint, and transform the problem of formulating the tie - line plan of the regional power grid into an unconstrained optimization problem;

[0084] Compare the current tie - line plan output after introducing the Lagrange multiplier and relaxing the cross - regional transaction power constraint with the previous tie - line plan to determine whether there is a change between the current tie - line plan and the previous tie - line plan. If there is no change, it means that the current tie - line plan is feasible for all regional power grids.

[0085] Introduce the Lagrange multiplier into the regional power grid through the following formula to relax the cross - regional transaction power constraint and transform the problem of formulating the tie - line plan of the regional power grid into an unconstrained optimization problem:

[0086]

[0087]

[0088] where, E l is the total transaction power of tie - line l, [·] + represents non - negative operation, f l,t is the transmission power of tie - line l at time t, is the boundary of the transmission power; μ n,t and ω n,t are both introduced multipliers, f t is the total transmission power of all tie - lines connected to regional power grid n at time t; are the positive and negative reserve demands of regional power grid n at time t.

[0089] Judge whether there is a change between the tie - line plan and the previous tie - line plan through the following formula:

[0090]

[0091] where, k represents the number of iterations, is the current tie - line plan, is the previous tie - line plan, and ε is a preset threshold.

[0092] In step S3, use the distributed penalty primal - dual sub - gradient optimization algorithm to coordinately optimize the tie - line plan and the regional power grid it is connected to, and obtain a new tie - line plan, including:

[0093] For each regional power grid, obtain the tie - line transmission power variable of the tie - line plan and the sub - gradient of the Lagrange multiplier;

[0094] Update the transmission power variable of the tie line along the negative gradient direction of it, and perform projection operation within the feasible region. Update the multiplier variable along the positive gradient direction of it;

[0095] Calculate the subgradients of the updated tie line transmission power variable and the Lagrange multiplier, and perform consensus coordination on the subgradients of the updated tie line transmission power variable and the Lagrange multiplier with the connected regional power grids to obtain a new tie line plan.

[0096] Determine the subgradient of the tie line transmission power variable through the following formula:

[0097]

[0098] Where, is the subgradient of the tie line transmission power variable, is the previous tie line plan; P i are the upper and lower limits of the output of unit i; E l is the total transaction power of tie line l, D n,t is the load demand of regional power grid n at time t; is the association relationship between regional power grid n and tie line l; are the positive and negative reserve demands of regional power grid n at time t.

[0099] Determine the subgradient of the Lagrange multiplier through the following formula:

[0100]

[0101]

[0102]

[0103] Where, are the subgradients of the Lagrange multiplier μ n,t and ω n,t respectively.

[0104] Determine the feasible region of the tie line transmission power variable through the following formula:

[0105]

[0106] Where, is the boundary of the transmission power.

[0107] Determine the updated tie line transmission power variable and Lagrange multiplier through the following formula:

[0108]

[0109]

[0110]

[0111]

[0112] wherein, is the updated transmission power variable of the tie line, μ n,t (k + 1), ω n,t (k + 1) are both updated Lagrange multipliers.

[0113] Determine the new tie line plan through the following formula:

[0114]

[0115]

[0116] Based on the same technical concept, the present invention also provides a coordinated optimization system for inter - regional tie lines, and the system includes:

[0117] A generation module, configured to randomly generate tie line plans for each scheduling period of multiple inter - regional tie lines;

[0118] A determination module, configured to determine a feasible tie line plan under the current unit combination mode of the regional power grid based on predefined feasibility determination conditions;

[0119] A coordinated optimization module, configured to determine the feasibility of the tie line plan for the current unit combination mode of all regional power grids. When it is feasible, output the current tie line plan, and the formulation of the tie line plan is completed; otherwise, use the distributed penalty primal - dual sub - gradient optimization algorithm to perform coordinated optimization on the tie line plan and the regional power grids connected thereto, obtain a new tie line plan, and then execute the determination module.

[0120] Embodiment 1:

[0121] As Figure 2 shown, 1) According to the total length of the scheduling period (24h) and the scheduling period interval (1h), randomly generate tie line plans for each scheduling period of L inter - regional tie lines;

[0122] 2) According to the known system network topology diagram, write out the incidence matrix between the regional power grid and the inter-regional tie lines. Use this incidence matrix to substitute the sum of the powers on the corresponding inter-regional tie lines into the feasibility determination conditions of the economic dispatch problem considering positive and negative reserves for the corresponding regional power grid respectively, and determine whether the current tie line plan is feasible for the current unit combination mode of the regional power grid n. If the iteration number k = 1, then continue to step 3); otherwise, directly jump to step 5).

[0123]

[0124]

[0125]

[0126]

[0127] Among them, i is the unit number, n is the regional power grid number, t is the time period number, and l is the tie line number; I' n is the set of currently operating units in the regional power grid n; P i are the upper and lower limits of the output of unit i; is the maximum positive and negative reserve that unit i can provide; are the positive and negative reserve demands of the regional power grid n at time period t; D n,t is the load demand of the regional power grid n at time period t; is the incidence relationship between the regional power grid n and the tie line l (1 means the regional power grid n sends electricity (flows out), -1 means the regional power grid n receives electricity (flows in), 0 means there is no direct connection between the regional power grid n and the tie line l); f l,t is the transmission power of the tie line l at time period t.

[0128] 3) According to the adjacency matrix between the regional power grids, calculate the adjacency weight matrix that satisfies the row and column double stochastic properties. Among them, the row and column double stochastic property can be expressed as The matrix dimension is the total number N of regional power grids;

[0129] 4) By introducing the lagrange multiplier λ l relax the cross-regional transaction electricity quantity constraint and write it into the objective function as In addition, according to the feasibility determination conditions of the economic dispatch problem considering positive and negative reserves, it is obtained that the total transmission power of all tie lines connected to the regional power grid n at time period t should satisfy By introducing the multipliers μ n,t and ω n,t relax this constraint and write it into the objective function. Assume that the boundary of the transmission power of the tie line determined by its physical characteristics is Then, the unconstrained optimization problem transformed from the tie-line planning problem of regional grid \(n\) is as follows:

[0130]

[0131]

[0132] where \(E\) l is the total transaction power of tie-line \(l\), and \([\cdot]\) + represents non - negative operation.

[0133] 5) Judge whether all four inequalities in step 2) hold. If the judgments of all regional grids hold, it means that the current tie - line plan is feasible under the current unit commitment mode of all regional grids; continue to judge whether the current tie - line plan has not changed compared with the tie - line plan formulated last time. If there is no change, that is If \(\varepsilon\) can take 0.01, it means that the current tie - line plan is the optimal tie - line plan, that is, the current tie - line plan not only meets the cross - regional transaction power constraint, but also ensures feasibility for the current unit commitment mode of all regional grids. Otherwise, if the current tie - line plan does not meet the judgment conditions or does not converge, continue to step 6).

[0134] 6) All regional grids use the distributed penalty primal - dual sub - gradient optimization algorithm to solve the unconstrained optimization problem in step 4). For regional grid \(n\), first, the sub - gradient of the primal variable is:

[0135]

[0136] The sub - gradients of the dual variables \(\mu\) n,t and \(\omega\) n,t are:

[0137]

[0138]

[0139]

[0140] Update the primal variable and the dual variables \(\mu\) n,t and \(\omega\) n,t along the negative gradient direction and the positive gradient direction respectively, and at the same time perform a projection operation on in its feasible region to ensure that the value after gradient update is within its feasible region. Specifically, as follows:

[0141]

[0142]

[0143]

[0144]

[0145] The regional power grid n will update the original variables and the dual variables and perform consensus coordination with the connected regional power grids, specifically:

[0146]

[0147]

[0148] Thereby, a new tie-line plan is obtained, and return to step 2) to continue the determination.

[0149] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0150] The present application is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the functions specified in Figure 1 one or more of the flows Figure 1 or blocks or a combination of multiple blocks.

[0151] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including instruction means, and the instruction means implements the functions specified in Figure 1 one or more of the flows Figure 1 or blocks or a combination of multiple blocks.

[0152] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus, so that a series of operation steps are executed on the computer or other programmable apparatus to produce a computer-implemented process, and thus the instructions executed on the computer or other programmable apparatus provide steps for implementing the functions specified in one process or a plurality of processes and / or blocks Figure 1 one process or a plurality of processes and / or blocks Figure 1 steps for implementing the functions specified in one block or a plurality of blocks.

[0153] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications or equivalent replacements can still be made to the specific embodiments of the present invention. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention shall be covered by the protection scope of the claims of the present invention.

Claims

1. A coordinated optimization method for inter-region tie lines, characterized in that The method includes: S1: Randomly generate tie-line plans for each scheduling period of multiple cross-region tie-lines; S2: Based on predefined feasibility determination conditions, determine the feasible tie-line plans under the current unit commitment mode of the regional power grid; S3: Determine the feasibility of the tie-line plan for the current unit commitment mode of all regional power grids. When it is feasible, output the current tie-line plan, and the tie-line plan formulation is completed; otherwise, use the distributed penalty primal-dual subgradient optimization algorithm to coordinately optimize the tie-line plan and the regional power grid it is connected to, obtain a new tie-line plan, and then execute step S2; The determination of the feasible tie-line plans under the current unit commitment mode of the regional power grid based on the predefined feasibility determination conditions includes: Construct an incidence matrix between the regional power grid and the cross-region tie-lines based on the regional power grid system topology diagram; Based on the incidence matrix between the regional power grid and the cross-region tie-lines, obtain the transmission power on the cross-region tie-lines; Substitute the sum of the transmission powers of the cross-region tie-lines into the feasibility determination conditions of the economic allocation problem considering positive and negative reserves of the corresponding regional power grid respectively. If the feasibility determination conditions are met, it indicates that the tie-line plan is feasible under the current unit commitment mode of the regional power grid; The feasibility determination conditions are as follows: Among them, i is the unit number, n is the regional power grid number, t is the time period number, and l is the tie line number; I' n is the set of currently operating units in regional power grid n; P i are the upper and lower limits of the output of unit i; are the maximum positive and negative reserve capacities that unit i can provide; are the positive and negative reserve demands of regional power grid n in time period t; D n,t is the load demand of regional power grid n in time period t; is the correlation between regional power grid n and tie line l; 1 means regional power grid n transmits power, -1 means regional power grid n receives power, and 0 means there is no direct correlation between regional power grid n and tie line l; f l,t is the transmission power of tie line l in time period t; The use of the distributed penalty primal-dual subgradient optimization algorithm to coordinately optimize the tie-line plan and the regional power grid it is connected to, and obtain a new tie-line plan, includes: For each regional power grid, obtain the subgradient of the tie-line transmission power variable and the Lagrange multiplier of the tie-line plan; Update the tie-line transmission power variable along its negative gradient direction and perform a projection operation within the feasible region, and update the multiplier variable along its positive gradient direction; Calculate the subgradients of the updated tie-line transmission power variable and the Lagrange multiplier, and perform consensus coordination on the updated tie-line transmission power variable and the Lagrange multiplier and the regional power grid it is connected to, to obtain a new tie-line plan.

2. The method according to claim 1, wherein The determination of the feasibility of the tie-line plan for the current unit commitment mode of all regional power grids includes: Introduce a Lagrange multiplier in the regional power grid, relax the cross-region transaction power constraint, and transform the tie-line plan formulation problem of the regional power grid into an unconstrained optimization problem; Compare the current tie-line plan output after introducing the Lagrange multiplier and relaxing the cross-region transaction power constraint with the previous tie-line plan, and determine whether there is a change between the tie-line plan and the previous tie-line plan. If there is no change, it means that the current tie-line plan is feasible for all regional power grids.

3. The method according to claim 2, wherein Introduce a Lagrange multiplier in the regional power grid through the following formula to relax the cross-region transaction power constraint and transform the tie-line plan formulation problem of the regional power grid into an unconstrained optimization problem: Among them, E l is the total transaction power of the tie line l, represents a non - negative operation, f l,t is the transmission power of the tie line l at time t, is the boundary of the transmission power; μ n,t and ω n,t are both introduced multipliers, f t is the total transmission power of all tie lines connected to the regional power grid n at time t; are the positive and negative reserve demands of the regional power grid n at time t.

4. The method according to claim 2, wherein Judge whether there is a change between the tie-line plan and the previous tie-line plan through the following formula: where k represents the number of iterations, is the current tie-line plan, is the previous tie-line plan, and ε is a preset threshold.

5. The method according to claim 1, characterized in that Determine the subgradient of the tie-line transmission power variable through the following formula: Among them, is the subgradient of the transmission power variable of the tie line, is the previous tie line plan; P i are the upper and lower limits of the output of unit i; E l is the total transaction power of tie line l, D n,t is the load demand of regional power grid n at time t; is the correlation between regional power grid n and tie line l; are the positive and negative reserve demands of regional power grid n at time t.

6. The method according to claim 5, wherein Determine the subgradient of the Lagrange multiplier through the following formula: Among them, are Lagrange multipliers respectively μ n,t , ω n,t are subgradients of 7. The method according to claim 6, characterized in that, Determine the feasible region of the tie-line transmission power variable through the following formula: Among them, is the boundary of the transmission power.

8. The method according to claim 7, wherein Determine the updated tie-line transmission power variable and Lagrange multiplier through the following formula: In the formula, is the updated transmission power variable of the tie line, μ n,t (k + 1), ω n,t (k + 1) are both updated Lagrange multipliers.

9. The method according to claim 1, wherein Determine the new tie-line plan through the following formula:

10. The method according to claim 1, wherein The tie-line plans for each scheduling period of randomly generating multiple inter-regional tie-lines include: According to the total length of the scheduling period and the scheduling period interval, randomly generate the transmission power plans for each scheduling period of multiple inter-regional tie-lines, and formulate the tie-line plan.

11. A coordinated optimization system for inter-region connection lines, characterized in that, The system includes: A generation module for randomly generating tie-line plans for each scheduling period of multiple inter-regional tie-lines; A determination module for determining a feasible tie-line plan under the current unit combination mode of the regional power grid based on predefined feasibility determination conditions; A coordination and optimization module for determining the feasibility of the tie-line plan for the current unit combination mode of all regional power grids. When it is feasible, output the current tie-line plan, and the tie-line plan is formulated. Otherwise, use the distributed penalty primal-dual subgradient optimization algorithm to perform coordination and optimization on the tie-line plan and the regional power grid it is connected to, obtain a new tie-line plan, and then execute the determination module; The determination module is specifically used for: Construct an incidence matrix between the regional power grid and the inter-regional tie-line based on the regional power grid system topology diagram; Based on the incidence matrix between the regional power grid and the inter-regional tie-line, obtain the transmission power on the inter-regional tie-line; Substitute the sum of the transmission powers of the inter-regional tie-lines into the feasibility determination conditions of the economic allocation problem considering positive and negative reserves of the corresponding regional power grid respectively. If the feasibility determination conditions are met, it means that the tie-line plan is feasible under the current unit combination mode of the regional power grid; The feasibility determination conditions are as follows: where i is the unit number, n is the regional power grid number, t is the time period number, and l is the tie line number; I' n is the set of currently operating units in regional power grid n; P i are the upper and lower limits of the output of unit i; are the maximum positive and negative reserve powers that unit i can provide; are the positive and negative reserve demands of regional power grid n in time period t; D n,t is the load demand of regional power grid n in time period t; is the association relationship between regional power grid n and tie line l; 1 indicates that regional power grid n transmits power, -1 indicates that regional power grid n receives power, and 0 indicates that there is no direct association between regional power grid n and tie line l; f l,t is the transmission power of tie line l in time period t; The use of the distributed penalty primal-dual subgradient optimization algorithm to perform coordination and optimization on the tie-line plan and the regional power grid it is connected to, and obtain a new tie-line plan, includes: For each regional power grid, obtain the subgradient of the tie-line transmission power variable and the Lagrange multiplier of the tie-line plan; Update the tie-line transmission power variable along its negative gradient direction and perform a projection operation within the feasible region, and update the multiplier variable along its positive gradient direction; Calculate the subgradient of the updated tie-line transmission power variable and the Lagrange multiplier, and perform consensus coordination on the updated tie-line transmission power variable and the Lagrange multiplier and the regional power grid it is connected to, to obtain a new tie-line plan.

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