A method and device for reconfiguring a distribution network based on operating frequency

Abstract

The present invention discloses a distribution network network reconstruction method and device based on operating frequency, establishes a line switching frequency constraint of the distribution network, uses the line switching frequency constraint to control the operating frequency of each line in the distribution network, can accurately constrain the line switching frequency, and improves the service life of the distribution network line. A linearized power flow constraint is established for the distribution network, and the maximum slack variable is used to replace the nonlinear power flow over-limit of the distribution network, which can convert the original nonlinear problem into a linear problem; the frequency and degree of over-limit of the distribution network state variable are minimized as the objective function, and the objective function is solved in combination with the line switching frequency constraint and the linearized power flow constraint to obtain a dynamic network topology with the lowest risk during the maintenance of the distribution network, which is suitable for use in scenarios such as distribution network maintenance network reconstruction.

Description

Technical Field

[0001] The present invention relates to the technical field of power system operation optimization, and in particular to a distribution network reconstruction method and device based on operating frequency. Background Art

[0002] The distribution network is an important part of the power system. The maintenance of the distribution network is one of the necessary means to ensure the safe and reliable operation of the distribution network and extend the life of the equipment. However, the maintenance of the distribution network will inevitably lead to the shutdown of some lines and the loss of power to some loads. The traditional transfer method may not be able to guarantee the safety of the distribution network operation during the maintenance period. Network reconstruction can change the network topology and is one of the effective methods to improve network security. Therefore, it is necessary to find a network topology optimization solution that minimizes the risk during the maintenance of the distribution network through the network reconstruction method.

[0003] At the same time, if the line switch is frequently operated, the life of the corresponding line will be shortened, resulting in weak links in the distribution network. Therefore, it is necessary to limit the operation frequency of the line switch in the network reconstruction method. The existing restrictions on the number of switches often constrain the total number of switches that can be operated at a time, or directly put the cost of the switch operation in the objective function. On the one hand, this may still cause an excessively high operation frequency, and on the other hand, some lines may frequently operate while the remaining lines remain unchanged. This also exacerbates the problem of unbalanced switch life.

[0004] How to cooperate with maintenance work, how to accurately constrain the operating frequency of each line, and find a distribution network dynamic network reconstruction method that can accurately limit the switch operation frequency are issues that need to be urgently addressed in the field of power system operation optimization technology. Summary of the invention

[0005] The technical problem to be solved by the present invention is to provide a distribution network network reconstruction method and device based on operating frequency, which can avoid too frequent operation of distribution network line switches and improve the service life of line switches.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0007] A method for reconfiguring a distribution network based on operating frequency, comprising the steps of:

[0008] Establishing a line switching frequency constraint of the distribution network, and using the line switching frequency constraint to control the operating frequency of each line in the distribution network;

[0009] Establish linear power flow constraints for the distribution network, and use the maximum slack variable to replace the nonlinear power flow limit of the distribution network;

[0010] Taking the minimization of the frequency and degree of the distribution network state variables exceeding the limit as the objective function, the objective function is solved in combination with the line switching frequency constraint and the linearized power flow constraint to dynamically reconstruct the distribution network with the minimum maintenance risk.

[0011] In order to solve the above technical problems, another technical solution adopted by the present invention is:

[0012] A distribution network reconstruction device based on operating frequency, comprising:

[0013] A line switching frequency constraint establishing module, used to establish a line switching frequency constraint of the distribution network, and use the line switching frequency constraint to control the operating frequency of each line in the distribution network;

[0014] A linearization constraint establishment module is used to establish linearization power flow constraints for the distribution network and use the maximum slack variable to replace the nonlinear power flow limit of the distribution network;

[0015] The distribution network reconstruction module takes minimizing the frequency and degree of the distribution network state variables exceeding the limit as the objective function, combines the line switching frequency constraint and the linearized power flow constraint to solve the objective function, and dynamically reconstructs the distribution network with the minimum maintenance risk.

[0016] Furthermore, the line switch frequency constraint establishing module is used to establish the line switch frequency constraint of the distribution network and includes:

[0017] The line switching frequency constraint of the distribution network is established according to the interval time of the switch operation in the distribution network:

[0018]

[0019]

[0020]

[0021]

[0022] In the formula, x ij,k represents the switch state of branch (i, j) at time k, x ij,k =1 means that branch (i,j) is put into operation at time k, x ij,k =0 means that branch (i, j) is not put into operation at time k, t means the number of the current time section, τ means the maximum time section number within the optimization time period, CT ij and OT ij They represent the continuous time that needs to be maintained after the branch (i, j) is put into operation and cut out of operation, respectively. lc Represents the set of lines involved in the reconstruction.

[0023] Furthermore, the linearization constraint establishing module is used to establish linearization power flow constraints for the distribution network and includes:

[0024] A linearized power flow constraint without considering line network loss is established, and the conditional constraints of active power flow and reactive power flow in the linearized power flow constraint are converted into inequality constraints.

[0025] Furthermore, the linearization constraint establishment module, which is used to replace the nonlinear power flow exceeding limit of the distribution network with the maximum slack variable, includes:

[0026] Establish voltage safety constraints and branch power flow thermal constraints:

[0027]

[0028]

[0029] Where V l Indicates the lower limit of voltage safety operation; V h Indicates the upper limit of voltage safety operation; represents the safe operating apparent power of branch (i, j), i.e., thermal constraint;

[0030] Introducing slack variables to the voltage safety constraint;

[0031] The branch power flow thermal constraint is abstracted into a circular constraint, and after the abstracted circular constraint is converted into a plurality of square constraints, a slack variable is introduced to represent the degree of power flow exceeding the limit at the operating point.

[0032] Furthermore, the linearization constraint establishment module further includes:

[0033] Two slack variables are introduced for voltage safety constraints:

[0034]

[0035]

[0036] In the formula, and The slack variables represent the voltage upper and lower limits, respectively, and indicate the degree to which the node voltage deviates from the safe operating range.

[0037] Furthermore, the linearization constraint establishment module further includes:

[0038] The branch power flow thermal constraint is abstracted into a circle constraint, the abstract circle constraint is converted into four square constraints, and a slack variable is introduced to indicate the degree of power flow exceeding the limit at the operating point:

[0039]

[0040]

[0041]

[0042]

[0043]

[0044]

[0045]

[0046]

[0047]

[0048]

[0049] In the formula, represents the power flow operation point (P ij ,Q ij ), Represents the maximum value of all slack variables at time t.

[0050] Furthermore, the distribution network reconstruction module further includes:

[0051] Establish maintenance line constraints, node injection power constraints, distributed generation injection and substation power constraints, distribution network radial topology constraints, and reference node constraints.

[0052] Furthermore, the distribution network network reconstruction module is used to minimize the frequency and degree of distribution network state variable crossing as the objective function, including:

[0053]

[0054] In the formula, c v represents the cost coefficient of node voltage exceeding the limit, c S Indicates the cost coefficient of line flow exceeding the limit.

[0055] Furthermore, the distribution network reconstruction module is used to solve the objective function in combination with the line switching frequency constraint and the linearized power flow constraint, and dynamically reconstruct the distribution network with the minimum maintenance risk, including:

[0056] Combining the line switching frequency constraints, linearized power flow constraints, maintenance line constraints, node injection power constraints, distributed generation injection and substation power constraints, distribution network radial topology constraints and reference node constraints, a dynamic network reconstruction model is obtained.

[0057] The network topology with the lowest maintenance risk of the distribution network is obtained by solving the dynamic network reconstruction model.

[0058] The beneficial effects of the present invention are: establishing a line switching frequency constraint for the distribution network, using the line switching frequency constraint to control the operating frequency of each line in the distribution network, being able to accurately constrain the line switching frequency, and improving the service life of the distribution network line. Establishing a linearized power flow constraint for the distribution network, and using the maximum slack variable to replace the nonlinear power flow over-limit of the distribution network, the original nonlinear problem can be converted into a linear problem; minimizing the frequency and degree of over-limit of the distribution network state variable as the objective function, combining the line switching frequency constraint and the linearized power flow constraint to solve the objective function, and obtaining a dynamic network topology with the lowest risk during the maintenance of the distribution network, which is suitable for use in scenarios such as distribution network maintenance network reconstruction. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 A flow chart of a method for reconfiguring a power distribution network based on operating frequency according to an embodiment of the present invention;

[0060] Figure 2 It is a schematic diagram of a distribution network reconstruction device based on operating frequency according to an embodiment of the present invention;

[0061] Figure 3 A schematic diagram of a linearized power flow thermal constraint method according to an embodiment of the present invention;

[0062] Figure 4 The figure is a schematic diagram of a method for setting slack variables taking the first quadrant as an example according to an embodiment of the present invention. DETAILED DESCRIPTION

[0063] In order to explain the technical content, achieved objectives and effects of the present invention in detail, the following is an explanation in combination with the implementation modes and the accompanying drawings.

[0064] Please refer to Figure 1 The embodiment of the present invention provides a method for reconfiguring a distribution network based on operating frequency, comprising the steps of:

[0065] Establishing a line switching frequency constraint of the distribution network, and using the line switching frequency constraint to control the operating frequency of each line in the distribution network;

[0066] Establish linear power flow constraints for the distribution network, and use the maximum slack variable to replace the nonlinear power flow limit of the distribution network;

[0067] Taking the minimization of the frequency and degree of the distribution network state variables exceeding the limit as the objective function, the objective function is solved in combination with the line switching frequency constraint and the linearized power flow constraint to dynamically reconstruct the distribution network with the minimum maintenance risk.

[0068] From the above description, it can be seen that the beneficial effects of the present invention are: establishing a line switching frequency constraint for the distribution network, using the line switching frequency constraint to control the operating frequency of each line in the distribution network, being able to accurately constrain the line switching frequency, and improving the service life of the distribution network line. Establishing a linearized power flow constraint for the distribution network, and using the maximum slack variable to replace the nonlinear power flow over-limit of the distribution network, the original nonlinear problem can be converted into a linear problem; minimizing the frequency and degree of over-limit of the distribution network state variable as the objective function, combining the line switching frequency constraint and the linearized power flow constraint to solve the objective function, and obtaining a dynamic network topology with the lowest risk during the maintenance of the distribution network, which is suitable for use in scenarios such as distribution network maintenance network reconstruction.

[0069] Furthermore, the establishing of line switching frequency constraints of the distribution network includes:

[0070] The line switching frequency constraint of the distribution network is established according to the interval time of the switch operation in the distribution network:

[0071]

[0072]

[0073]

[0074]

[0075] In the formula, x ij,k represents the switch state of branch (i, j) at time k, x ij,k =1 means that branch (i,j) is put into operation at time k, x ij,k =0 means that branch (i, j) is not put into operation at time k, t means the number of the current time section, τ means the maximum time section number within the optimization time period, CT ij and OT ij They represent the continuous time that needs to be maintained after the branch (i, j) is put into operation and cut out of operation, respectively. lc Represents the set of lines involved in the reconstruction.

[0076] From the above description, it can be seen that by using line switching frequency constraints, when the switch state of a branch changes, it maintains its state after the action for a period of time before the next action can be performed, thereby improving the service life of the distribution network line.

[0077] Furthermore, establishing linearized power flow constraints on the distribution network includes:

[0078] A linearized power flow constraint without considering line network loss is established, and the conditional constraints of active power flow and reactive power flow in the linearized power flow constraint are converted into inequality constraints.

[0079] From the above description, it can be seen that a linearized power flow constraint is established, and the conditional constraints of active power flow and reactive power flow in the linearized power flow constraint are converted into inequality constraints, which facilitates solving the constraints.

[0080] Furthermore, the use of the maximum slack variable to replace the nonlinear power flow exceeding limit of the distribution network includes:

[0081] Establish voltage safety constraints and branch power flow thermal constraints:

[0082]

[0083]

[0084] Where V l Indicates the lower limit of voltage safety operation; V h Indicates the upper limit of voltage safety operation; represents the safe operating apparent power of branch (i, j), i.e., thermal constraint;

[0085] Introducing slack variables to the voltage safety constraint;

[0086] The branch power flow thermal constraint is abstracted into a circular constraint, and after the abstracted circular constraint is converted into a plurality of square constraints, a slack variable is introduced to represent the degree of power flow exceeding the limit at the operating point.

[0087] From the above description, it can be seen that using the maximum relaxation variable instead of the original nonlinear power flow limiter makes it easier to transform the original nonlinear problem into a linear problem.

[0088] Furthermore, introducing slack variables into the voltage safety constraint includes:

[0089] Two slack variables are introduced for voltage safety constraints:

[0090]

[0091]

[0092] In the formula, and The slack variables represent the voltage upper and lower limits, respectively, and indicate the degree to which the node voltage deviates from the safe operating range.

[0093] From the above description, it can be seen that since the distribution network is prone to not meeting the safety constraints during operation, and the goal of subsequent network reconstruction optimization is to quantify and minimize the degree and frequency of node voltage and branch power flow exceeding the limit, the introduction of slack variables facilitates the calculation of voltage safety constraints.

[0094] Furthermore, the branch power flow thermal constraint is abstracted into a circular constraint, and after the abstracted circular constraint is converted into a plurality of square constraints, a slack variable is introduced to indicate the degree of power flow exceeding the limit at the operating point, including:

[0095] The branch power flow thermal constraint is abstracted into a circle constraint, the abstract circle constraint is converted into four square constraints, and a slack variable is introduced to indicate the degree of power flow exceeding the limit at the operating point:

[0096]

[0097]

[0098]

[0099]

[0100]

[0101]

[0102]

[0103]

[0104]

[0105]

[0106] In the formula, represents the power flow operation point (P ij ,Q ij ), Represents the maximum value of all slack variables at time t.

[0107] From the above description, it can be seen that the branch power flow thermal constraint is a circular constraint, that is, a nonlinear constraint. Therefore, multiple square constraints are used to approximate the circular constraint, and then a slack variable is added to represent the degree of power flow exceeding the limit at the operating point, so that the branch power flow thermal constraint can be converted into a linear constraint.

[0108] Furthermore, the method of minimizing the frequency and degree of the distribution network state variable crossing the limit as the objective function includes:

[0109] Establish maintenance line constraints, node injection power constraints, distributed generation injection and substation power constraints, distribution network radial topology constraints, and reference node constraints.

[0110] From the above description, it can be seen that the establishment of additional constraints on maintenance lines, node injection power constraints, distributed generation injection and substation power constraints, distribution network radial topology constraints and reference node constraints can ensure the integrity of the subsequent dynamic network reconstruction model.

[0111] Furthermore, the objective function of minimizing the frequency and degree of the distribution network state variable crossing the limit includes:

[0112]

[0113] In the formula, c v represents the cost coefficient of node voltage exceeding the limit, c S Indicates the cost coefficient of line flow exceeding the limit.

[0114] From the above description, it can be seen that by minimizing the frequency and degree of distribution network state variables exceeding the limit as the objective function, it is convenient to find the optimal network reconstruction scheme with the smallest total slack variables of voltage and line flow within the optimization time period.

[0115] Furthermore, solving the objective function in combination with the line switching frequency constraint and the linearized power flow constraint, and dynamically reconstructing the distribution network with the minimum maintenance risk includes:

[0116] Combining the line switching frequency constraints, linearized power flow constraints, maintenance line constraints, node injection power constraints, distributed generation injection and substation power constraints, distribution network radial topology constraints and reference node constraints, a dynamic network reconstruction model is obtained.

[0117] The network topology with the lowest maintenance risk of the distribution network is obtained by solving the dynamic network reconstruction model.

[0118] From the above description, it can be seen that, by combining the above constraints, a dynamic network reconstruction model can be obtained. By solving the dynamic network reconstruction model, a network topology with the lowest maintenance risk of the distribution network can be obtained.

[0119] Please refer to Figure 2 Another embodiment of the present invention provides a distribution network reconstruction device based on operating frequency, comprising:

[0120] A line switching frequency constraint establishing module, used to establish a line switching frequency constraint of the distribution network, and use the line switching frequency constraint to control the operating frequency of each line in the distribution network;

[0121] A linearization constraint establishment module is used to establish linearization power flow constraints for the distribution network and use the maximum slack variable to replace the nonlinear power flow limit of the distribution network;

[0122] The distribution network reconstruction module takes minimizing the frequency and degree of the distribution network state variables exceeding the limit as the objective function, combines the line switching frequency constraint and the linearized power flow constraint to solve the objective function, and dynamically reconstructs the distribution network with the minimum maintenance risk.

[0123] From the above description, it can be seen that establishing the line switching frequency constraint of the distribution network and using the line switching frequency constraint to control the operating frequency of each line in the distribution network can accurately constrain the switching frequency of the line and improve the service life of the distribution network line. Establishing a linearized power flow constraint for the distribution network and using the maximum slack variable to replace the nonlinear power flow over-limit of the distribution network can transform the original nonlinear problem into a linear problem; minimizing the frequency and degree of over-limit of the distribution network state variables as the objective function, combining the line switching frequency constraint and the linearized power flow constraint to solve the objective function, and obtain the dynamic network topology with the lowest risk during the distribution network maintenance period, which is suitable for application in scenarios such as distribution network maintenance network reconstruction.

[0124] Furthermore, the line switch frequency constraint establishing module is used to establish the line switch frequency constraint of the distribution network and includes:

[0125] The line switching frequency constraint of the distribution network is established according to the interval time of the switch operation in the distribution network:

[0126]

[0127]

[0128]

[0129]

[0130] In the formula, x ij,k represents the switch state of branch (i, j) at time k, x ij,k =1 means that branch (i,j) is put into operation at time k, x ij,k =0 means that branch (i, j) is not put into operation at time k, t means the number of the current time section, τ means the maximum time section number within the optimization time period, CT ij and OT ij They represent the continuous time that needs to be maintained after the branch (i, j) is put into operation and cut out of operation, respectively. lc Represents the set of lines involved in the reconstruction.

[0131] From the above description, it can be seen that by using line switching frequency constraints, when the switch state of a branch changes, it maintains its state after the action for a period of time before the next action can be performed, thereby improving the service life of the distribution network line.

[0132] Furthermore, the linearization constraint establishing module is used to establish linearization power flow constraints for the distribution network and includes:

[0133] A linearized power flow constraint without considering line network loss is established, and the conditional constraints of active power flow and reactive power flow in the linearized power flow constraint are converted into inequality constraints.

[0134] From the above description, it can be seen that a linearized power flow constraint is established, and the conditional constraints of active power flow and reactive power flow in the linearized power flow constraint are converted into inequality constraints, which facilitates solving the constraints.

[0135] Furthermore, the linearization constraint establishment module, which is used to replace the nonlinear power flow exceeding limit of the distribution network with the maximum slack variable, includes:

[0136] Establish voltage safety constraints and branch power flow thermal constraints:

[0137]

[0138]

[0139] Where V l Indicates the lower limit of voltage safety operation; V h Indicates the upper limit of voltage safety operation; represents the safe operating apparent power of branch (i, j), i.e., thermal constraint;

[0140] Introducing slack variables to the voltage safety constraint;

[0141] The branch power flow thermal constraint is abstracted into a circular constraint, and after the abstracted circular constraint is converted into a plurality of square constraints, a slack variable is introduced to represent the degree of power flow exceeding the limit at the operating point.

[0142] From the above description, it can be seen that using the maximum relaxation variable instead of the original nonlinear power flow limiter makes it easier to transform the original nonlinear problem into a linear problem.

[0143] Furthermore, the linearization constraint establishment module further includes:

[0144] Two slack variables are introduced for voltage safety constraints:

[0145]

[0146]

[0147] In the formula, and The slack variables represent the voltage upper and lower limits, respectively, and indicate the degree to which the node voltage deviates from the safe operating range.

[0148] From the above description, it can be seen that since the distribution network is prone to not meeting the safety constraints during operation, and the goal of subsequent network reconstruction optimization is to quantify and minimize the degree and frequency of node voltage and branch power flow exceeding the limit, the introduction of slack variables facilitates the calculation of voltage safety constraints.

[0149] Furthermore, the linearization constraint establishment module further includes:

[0150] The branch power flow thermal constraint is abstracted into a circle constraint, the abstracted circle constraint is converted into four square constraints, and a slack variable is introduced to represent the degree of power flow exceeding the limit at the operating point:

[0151]

[0152]

[0153]

[0154]

[0155]

[0156]

[0157]

[0158]

[0159]

[0160]

[0161] In the formula, represents the power flow operation point (P ij ,Q ij ), Represents the maximum value of all slack variables at time t.

[0162] From the above description, it can be seen that the branch power flow thermal constraint is a circular constraint, that is, a nonlinear constraint. Therefore, multiple square constraints are used to approximate the circular constraint, and then a slack variable is added to represent the degree of power flow exceeding the limit at the operating point, so that the branch power flow thermal constraint can be converted into a linear constraint.

[0163] Furthermore, the distribution network reconstruction module further includes:

[0164] Establish maintenance line constraints, node injection power constraints, distributed generation injection and substation power constraints, distribution network radial topology constraints, and reference node constraints.

[0165] From the above description, it can be seen that the establishment of additional constraints on maintenance lines, node injection power constraints, distributed generation injection and substation power constraints, distribution network radial topology constraints and reference node constraints can ensure the integrity of the subsequent dynamic network reconstruction model.

[0166] Furthermore, the distribution network network reconstruction module is used to minimize the frequency and degree of the distribution network state variable crossing as the objective function, including:

[0167]

[0168] In the formula, c v represents the cost coefficient of node voltage exceeding the limit, c S Indicates the cost coefficient of line flow exceeding the limit.

[0169] From the above description, it can be seen that by minimizing the frequency and degree of distribution network state variables exceeding the limit as the objective function, it is convenient to find the optimal network reconstruction scheme with the smallest total slack variables of voltage and line flow within the optimization time period.

[0170] Furthermore, the distribution network reconstruction module is used to solve the objective function in combination with the line switching frequency constraint and the linearized power flow constraint, and dynamically reconstruct the distribution network with the minimum maintenance risk, including:

[0171] Combining the line switching frequency constraints, linearized power flow constraints, maintenance line constraints, node injection power constraints, distributed generation injection and substation power constraints, distribution network radial topology constraints and reference node constraints, a dynamic network reconstruction model is obtained.

[0172] The network topology with the lowest maintenance risk of the distribution network is obtained by solving the dynamic network reconstruction model.

[0173] From the above description, it can be seen that, by combining the above constraints, a dynamic network reconstruction model can be obtained. By solving the dynamic network reconstruction model, a network topology with the lowest maintenance risk of the distribution network can be obtained.

[0174] The above-mentioned distribution network network reconstruction method and device based on operating frequency of the present invention are suitable for scenes such as distribution network maintenance network reconstruction, which can avoid too frequent operation of distribution network line switches and improve the life of line switches. The following is an explanation through specific implementation methods:

[0175] Embodiment 1

[0176] Please refer to Figure 1 , a distribution network reconstruction method based on operating frequency, comprising the steps of:

[0177] S1. Establish a line switching frequency constraint for a distribution network, and use the line switching frequency constraint to control the operating frequency of each line in the distribution network.

[0178] Specifically, for each distribution network line, the interval time of its action is constrained, and the line operation frequency constraint is introduced as follows:

[0179]

[0180]

[0181]

[0182]

[0183] In the formula, x ij,k represents the switch state of branch (i, j) at time k, x ij,k =1 means that branch (i,j) is put into operation at time k, x ij,k = 0 means that branch (i, j) was not put into operation at time k and has been cut off, so x ij,k is a binary integer variable; t represents the number of the current time section; τ represents the maximum time section number within the optimization period, CT ij and OT ij They represent the continuous time that needs to be maintained after the branch (i, j) is put into operation and cut out of operation, respectively. lc Represents the set of lines that can participate in reconstruction.

[0184] The purpose of the line operation frequency constraint is that when the switch state of a branch (i, j) changes, it should maintain its state after the action and last for a period of time before the next action can be performed.

[0185] The meaning of the first inequality constraint above is that if t is between 1 and τ-CT ij +1, and at time t the switch state of branch (i, j) changes from 0 to 1, that is, branch (i, j) is put into operation at time t, then from time t to t+CT ij -1 moment total CT ij The operation status should remain unchanged for a period of time, but for a period of time greater than t+CT ij There is no restriction on the line status at time -1.

[0186] The second inequality constraint means that if t is in τ-CTij +2 to τ, and at time t the switch state of branch (i, j) changes from 0 to 1, then the state of operation should remain unchanged from time t to τ.

[0187] The third and fourth inequality constraints stipulate that the switch state of branch (i, j) changes from 1 to 0 at time t, that is, the corresponding constraints are cut out of operation at time t. Their meanings are the same as the first and second inequality constraints.

[0188] S2. Establish linear power flow constraints for the distribution network and use the maximum slack variable to replace the nonlinear power flow limit of the distribution network.

[0189] S21. The linearized power flow equation is as follows:

[0190]

[0191]

[0192]

[0193]

[0194]

[0195]

[0196] Where P ij,t P represents the active power flow from branch (i, j) from i to j at time t; ji,t P represents the active power flow from branch (i, j) to branch i at time t; j,t represents the injected active power of node j at time t; Q ij,t represents the reactive power flow from branch (i, j) from i to j at time t; Q ij,t It represents the reactive power flow from branch (i, j) to branch i at time t; Q j,t represents the injected reactive power of node j at time t; G ij represents the conductance of branch (i, j); B ij represents the susceptance of branch (i, j); V i,t represents the voltage amplitude of node i at time t; θ i,t Represents the voltage phase angle of node i at time t. Φ l represents the set of all branches; T represents the set of all time sections; K(j) represents the set of all nodes directly connected to node j.

[0197] It can be seen that the above linearized power flow constraints do not take line network losses into consideration.

[0198] Since the first two equality constraints in the linearized power flow equation are conditional constraints and are not easy to solve, the "Big M method" can be introduced to transform the original two equality constraints into six inequality constraints as follows:

[0199]

[0200]

[0201]

[0202]

[0203]

[0204]

[0205] Wherein, M is a preset larger number.

[0206] The meaning of the above inequality constraint is that if x ij,k =1, then the term containing M becomes 0, the first and second inequalities together degenerate into an equality constraint on active power, and the third and fourth inequalities together degenerate into an equality constraint on reactive power.

[0207] If x ij,k = 0, then the term containing M becomes a large positive value or a large negative value, which is equivalent to P ij,t and Q ij,t Instead of following the equality constraint, you can take any value in [-M,M]. However, taking any value still does not conform to the actual situation of cutting out the line, so the fifth and sixth inequalities are introduced. The meaning of these two inequalities is that if x ij,k = 0, then the P of branch (i, j) ij,t and Q ij,t Should be strictly equal to 0, so that the constraint conforms to the actual situation.

[0208] S22, voltage safety constraints and branch power flow thermal constraints are generally expressed as follows:

[0209]

[0210]

[0211] Where V l Indicates the lower limit of voltage safety operation; V h Indicates the upper limit of voltage safety operation; Φ all Represents the set of all nodes; represents the safe operation apparent power of branch (i, j), that is, the thermal constraint. In general, during the operation of the distribution network, especially when the distribution network implements the maintenance plan, it is easy to fail to meet the safety constraints. The goal of the network reconstruction optimization method in this embodiment is to quantify and minimize the degree and frequency of node voltage and branch power flow exceeding the limit. Therefore, two slack variables are introduced for the voltage safety constraint:

[0212]

[0213]

[0214] In the formula, and The slack variables that represent the voltage exceeding the upper and lower limits respectively indicate the degree to which the node voltage deviates from the safe operating range. For the same node at the same time, these two slack variables will not be non-zero at the same time. The original branch power flow thermal constraint can be mathematically abstracted as a circle constraint, that is, the operating point within the circle meets the constraint. It is easy to know that this constraint is a nonlinear constraint. If the slack variables are added directly to the circle constraint, it will lead to difficulties in solving. Therefore, 4 square constraints are used to approximate the circle constraint, and then the slack variables are added to indicate the degree to which the operating point power flow exceeds the limit. The specific constraints are as follows:

[0215]

[0216]

[0217]

[0218]

[0219]

[0220]

[0221]

[0222]

[0223]

[0224]

[0225] In the formula, represents the power flow operation point (P ij,t ,Q ij,t ) 16 slack variables, these slack variables will not exist at the same time; Represents the maximum value of all slack variables. For the specific meaning of the above constraints, please refer to Figure 3 and Figure 4 .

[0226] Please refer to Figure 3 , use a regular hexadecagon surrounded by four squares to approximate the original circle constraint, so that the original circle is inscribed in the regular hexadecagon. For each branch (i, j) of the power flow operation point (P ij,t ,Q ij,t ), there are at most 5 slack variables at the same time, which is equal to the number of sides of the regular hexadecagon in the quadrant where it is located. Please refer to Figure 4 In

[0227] The slack variable represents the power flow operation point (P ij,t ,Q ij,t ) to the extension of the side length of the regular hexadecagon in its quadrant, such as For (P ij,t ,Q ij,t ) to the edge The specific number of slack variables is determined by the operating point (P ij,t ,Q ij,t ) is determined by the positional relationship between the extension line of the regular hexadecimal deformation in the quadrant where it is located. ij,t ,Q ij,t ) When the constraint of a certain edge does not exceed the limit, the slack variable is 0, and it can also be considered that the slack variable does not exist. The maximum value of all slack variables is set to The maximum relaxation variable is used to replace the original nonlinear power flow over-limit. ij,t ,Q ij,t ) to the circle and the maximum value of the slack variable after linearization, please refer to Figure 4 , we can see that the lengths are very close, so this approximation method has high accuracy.

[0228] S3. Taking the minimization of the frequency and degree of the distribution network state variables exceeding the limit as the objective function, the objective function is solved in combination with the line switching frequency constraint and the linearized power flow constraint to dynamically reconstruct the distribution network with the minimum maintenance risk.

[0229] S31. After the above-mentioned line switching frequency constraints and linearized power flow constraints are established, for the completeness of the model, it is necessary to supplement the maintenance line constraints, node injection power constraints, distributed power injection and substation power constraints, distribution network radial topology constraints and reference node constraints for the application scenarios of distribution network and maintenance:

[0230] S311. The constraints of the maintenance line are:

[0231]

[0232] In the formula, represents the mth line under maintenance, Φ m represents the set of maintenance lines, T m represents the set of maintenance time periods, N M Indicates the total number of lines that need to be overhauled. During the overhaul period, the overhauled lines will not be put into operation.

[0233] S312, the node injection power constraint is:

[0234]

[0235]

[0236] In the formula, represents the injected active power of the substation connected to node i at time t, represents the injected active power of the distributed generation connected to node i at time t, represents the active power consumed by the load of node i at time t, represents the injected reactive power of the substation connected to node i at time t, represents the injected reactive power of the distributed generation connected to node i at time t, Represents the reactive power consumed by the load of node i at time t; the net power of each node at each moment is equal to all injected power minus the power consumed by the load. Generally, only the root node is connected to the substation.

[0237] S313, the power constraints of distributed generation injection and substation are:

[0238]

[0239]

[0240]

[0241]

[0242] In the formula, represents the predicted value of the active power of the distributed power source connected to node i at time t, λ represents the fixed ratio of reactive power to active power when the distributed power source connected to node i operates in the maximum power tracking mode, Φ dg Represents the collection of nodes connected to distributed power generation, and They represent the minimum and maximum power limits of the active power of the transformer connected to node i, and They represent the minimum and maximum power limits of the reactive power of the substation connected to node i. This constraint does not consider the uncertainty of distributed power sources, and assumes that the output of distributed power sources is consistent with the predicted value and operates in the maximum power tracking mode.

[0243] S314. The radial topology constraints of the distribution network are:

[0244]

[0245]

[0246] Where N node Represents the total number of nodes, N root Indicates the total number of root nodes, FP ij,t Represents the virtual active power of branch (i, j) at time t.

[0247] For radial network operation, the following three constraints need to be met: the first equality constraint means that the sum of lines put into operation should be equal to the number of all nodes minus the total number of root nodes; the second constraint means the power balance of each node, that is, satisfying Kirchhoff's first law, which has been reflected in the node injection power constraint; the third constraint is that except for the root node, that is, except for the node containing the substation, all nodes are load nodes. However, the distribution network may contain distributed power sources and zero injection nodes, which do not meet the third constraint. Therefore, virtual injection power is introduced here. This constraint assumes that each node also has a power balance constraint with a virtual injection active power of -1. All three constraints are reflected, which can ensure that the distribution network maintains a radial operation state under any circumstances.

[0248] S315. The constraints of the reference node are:

[0249]

[0250]

[0251] Where V r,t The voltage amplitude of the reference node r at time t is 1, θ r,t It means that the voltage phase angle of the reference node r at time t is 0.

[0252] S32. After all constraints are set, the objective function to minimize the frequency and degree of over-limit of distribution network state variables is established as follows:

[0253]

[0254] In the formula, c v represents the cost coefficient of node voltage exceeding the limit, c SIndicates the cost coefficient of line flow exceeding the limit.

[0255] The objective function aims to find the optimal network reconstruction scheme with the minimum total slack variables of voltage and line flow during the optimization period. Although the objective function does not follow the definition of narrow risk indicators, it contains the sum of slack variables representing the severity and deviation frequency of state variables, which can reflect the safety of the system during the optimization period and obtain the dynamic network topology with the minimum risk during the maintenance of the distribution network.

[0256] Embodiment 2

[0257] Please refer to Figure 2 , a distribution network reconstruction device based on operating frequency, comprising:

[0258] A line switching frequency constraint establishing module, used to establish a line switching frequency constraint of the distribution network, and use the line switching frequency constraint to control the operating frequency of each line in the distribution network;

[0259] A linearization constraint establishment module is used to establish linearization power flow constraints for the distribution network and use the maximum slack variable to replace the nonlinear power flow limit of the distribution network;

[0260] The distribution network reconstruction module takes minimizing the frequency and degree of the distribution network state variables exceeding the limit as the objective function, combines the line switching frequency constraint and the linearized power flow constraint to solve the objective function, and dynamically reconstructs the distribution network with the minimum maintenance risk.

[0261] In some embodiments, the line switch frequency constraint establishing module is used to establish the line switch frequency constraint of the power distribution network, including:

[0262] The line switching frequency constraint of the distribution network is established according to the interval time of the switch operation in the distribution network:

[0263]

[0264]

[0265]

[0266]

[0267] In the formula, x ij,k represents the switch state of branch (i, j) at time k, x ij,k =1 means that branch (i,j) is put into operation at time k, x ij,k =0 means that branch (i, j) is not put into operation at time k, t means the number of the current time section, τ means the maximum time section number within the optimization time period, CT ij and OTij They represent the continuous time that needs to be maintained after the branch (i, j) is put into operation and cut out of operation, respectively. lc Represents the set of lines involved in the reconstruction.

[0268] In some embodiments, the linearization constraint establishing module, used to establish linearization power flow constraints for the distribution network, includes:

[0269] A linearized power flow constraint without considering line network loss is established, and the conditional constraints of active power flow and reactive power flow in the linearized power flow constraint are converted into inequality constraints.

[0270] Furthermore, the linearization constraint establishment module, which is used to replace the nonlinear power flow exceeding limit of the distribution network with the maximum slack variable, includes:

[0271] Establish voltage safety constraints and branch power flow thermal constraints:

[0272]

[0273]

[0274] Where V l Indicates the lower limit of voltage safety operation; V h Indicates the upper limit of voltage safety operation; represents the safe operating apparent power of branch (i, j), i.e., thermal constraint;

[0275] Introducing slack variables to the voltage safety constraint;

[0276] The branch power flow thermal constraint is abstracted into a circular constraint, and after the abstracted circular constraint is converted into a plurality of square constraints, a slack variable is introduced to represent the degree of power flow exceeding the limit at the operating point.

[0277] In some embodiments, the power distribution network reconstruction module further comprises:

[0278] Establish maintenance line constraints, node injection power constraints, distributed generation injection and substation power constraints, distribution network radial topology constraints, and reference node constraints.

[0279] In some embodiments, the distribution network network reconstruction module is used to minimize the frequency and degree of distribution network state variable crossing as the objective function, including:

[0280]

[0281] In the formula, c v represents the cost coefficient of node voltage exceeding the limit, c S Indicates the cost coefficient of line flow exceeding the limit.

[0282] In some embodiments, the distribution network reconstruction module is used to solve the objective function in combination with the line switching frequency constraint and the linearized power flow constraint, and dynamically reconstruct the distribution network with the minimum maintenance risk, including:

[0283] Combining the line switching frequency constraints, linearized power flow constraints, maintenance line constraints, node injection power constraints, distributed generation injection and substation power constraints, distribution network radial topology constraints and reference node constraints, a dynamic network reconstruction model is obtained.

[0284] The network topology with the lowest maintenance risk of the distribution network is obtained by solving the dynamic network reconstruction model.

[0285] In summary, the present invention provides a distribution network network reconstruction method and device based on operating frequency, which can accurately constrain the switching frequency of the line. The existing network reconstruction model often only constrains the total number of switch action lines under each time section, but this will cause the switch action frequency to be too high, and some lines will be repeatedly switched, which is easy to introduce weak points to the distribution network. Therefore, the line switching frequency constraint is used. When the switch state of a branch changes, it is necessary to maintain its state after the action and continue for a period of time before the next action can be performed. The service life of the distribution network line is improved. This embodiment also cooperates with the distribution network maintenance plan, and takes the frequency and degree of network state variables exceeding the limit as the objective function to obtain a dynamic network topology with the lowest risk during the distribution network maintenance. By establishing a linearized power flow constraint and using the maximum slack variable to replace the original nonlinear power flow exceeding the limit, the original nonlinear problem is converted into a linear problem. At the same time, by using the maximum slack variable to represent the degree of system state variables exceeding the limit, an objective function of minimizing the frequency and degree of distribution network state variables exceeding the limit is established, and a dynamic network topology with the lowest risk during the distribution network maintenance is obtained, which is suitable for use in scenarios such as distribution network maintenance network reconstruction.

[0286] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent transformations made using the contents of the present invention's specification and drawings, or directly or indirectly applied in related technical fields, are also included in the patent protection scope of the present invention.

[0287] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may 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.) containing computer-usable program codes. The schemes in the embodiments of the present invention may be implemented in various computer languages, for example, object-oriented programming language Java and literal scripting language JavaScript, etc.

[0288] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes 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 a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0289] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0290] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0291] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0292] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A distribution network reconstruction method based on operating frequency, characterized in that: Includes steps: Establishing a line switching frequency constraint of the distribution network, and using the line switching frequency constraint to control the operating frequency of each line in the distribution network; Establish linear power flow constraints for the distribution network, and use the maximum slack variable to replace the nonlinear power flow limit of the distribution network; Taking the minimization of the frequency and degree of the distribution network state variables exceeding the limit as the objective function, the objective function is solved in combination with the line switching frequency constraint and the linearized power flow constraint to dynamically reconstruct the distribution network with the minimum maintenance risk; The use of the maximum slack variable to replace the nonlinear power flow exceeding limit of the distribution network includes: Establish voltage safety constraints and branch power flow thermal constraints: ； ； In the formula, V l Indicates the lower limit of voltage safe operation; V h Indicates the upper limit of voltage safety operation; Indicates a branch ( i , j )’s safe operating apparent power, i.e. thermal constraints; represents the branch at time t Active power flow from i to j; represents the branch at time t Reactive power flow from i to j; T Represents the set of all time sections; Represents the set of all nodes; Introducing slack variables to the voltage safety constraint; The branch power flow thermal constraint is abstracted into a circular constraint, and after the abstracted circular constraint is converted into a plurality of square constraints, a slack variable is introduced to represent the degree of power flow exceeding the limit at the operating point; Introducing slack variables into the voltage safety constraint includes: Two slack variables are introduced for voltage safety constraints: ； ； In the formula, and The slack variables for voltages above the upper and lower limits, respectively, indicate the extent to which the node voltage deviates from the safe operating range; The branch power flow thermal constraint is abstracted into a circular constraint, and after the abstracted circular constraint is converted into multiple square constraints, a slack variable is introduced to indicate the degree of power flow exceeding the limit at the operating point, including: The branch power flow thermal constraint is abstracted into a circle constraint, the abstracted circle constraint is converted into four square constraints, and a slack variable is introduced to represent the degree of power flow exceeding the limit at the operating point: ； ； ； ； ； ； ； ； ； ； In the formula, represents the branch at time t ( i , j ) of the power flow operation point ( P ij , Q ij ), represents the maximum value of all slack variables at time t, Represents the set of all branches.

2. A method for reconfiguring a distribution network based on operating frequency according to claim 1, characterized in that: The establishing of line switching frequency constraints of the distribution network includes: The line switching frequency constraint of the distribution network is established according to the interval time of the switch operation in the distribution network: ； ； ； ； In the formula, Indicates branch The switch state at time k, Indicates branch It is put into operation at time k. Indicates branch It is not put into operation at time k, t represents the number of the current time section, Indicates the maximum time section number within the optimization period. and Respectively represent branches The continuous time that needs to be maintained after the start-up and cut-out operations occur. Represents the set of lines involved in the reconstruction.

3. A method for reconfiguring a distribution network based on operating frequency according to claim 1, characterized in that: The establishment of linearized power flow constraints on the distribution network includes: A linearized power flow constraint without considering line network loss is established, and the conditional constraints of active power flow and reactive power flow in the linearized power flow constraint are converted into inequality constraints.

4. A method for reconfiguring a distribution network based on operating frequency according to claim 1, characterized in that: The method of minimizing the frequency and degree of the distribution network state variable crossing the limit as the objective function includes: Establish maintenance line constraints, node injection power constraints, distributed generation injection and substation power constraints, distribution network radial topology constraints, and reference node constraints.

5. The method for reconfiguring a distribution network based on operating frequency according to claim 1, characterized in that: The objective function of minimizing the frequency and degree of the state variables of the distribution network exceeding the limit includes: ； In the formula, represents the cost coefficient of node voltage exceeding the limit, Indicates the cost coefficient of line flow exceeding the limit.

6. A method for reconfiguring a distribution network based on operating frequency according to claim 4, characterized in that: Solving the objective function by combining the line switching frequency constraint and the linearized power flow constraint, and dynamically reconstructing the distribution network with the minimum maintenance risk includes: Combining the line switching frequency constraints, linearized power flow constraints, maintenance line constraints, node injection power constraints, distributed generation injection and substation power constraints, distribution network radial topology constraints and reference node constraints, a dynamic network reconstruction model is obtained. The network topology with the lowest maintenance risk of the distribution network is obtained by solving the dynamic network reconstruction model.

7. A distribution network reconstruction device based on operating frequency, characterized in that: include: A line switching frequency constraint establishing module, used to establish a line switching frequency constraint of the distribution network, and use the line switching frequency constraint to control the operating frequency of each line in the distribution network; A linearization constraint establishment module is used to establish linearization power flow constraints for the distribution network and use the maximum slack variable to replace the nonlinear power flow limit of the distribution network; A distribution network reconstruction module takes minimization of the frequency and degree of over-limit of distribution network state variables as an objective function, combines the line switching frequency constraint and the linearized power flow constraint to solve the objective function, and dynamically reconstructs the distribution network with the minimum maintenance risk; The use of the maximum slack variable to replace the nonlinear power flow exceeding limit of the distribution network includes: Establish voltage safety constraints and branch power flow thermal constraints: ； ； In the formula, V l Indicates the lower limit of voltage safe operation; V h Indicates the upper limit of voltage safety operation; Indicates a branch ( i , j )’s safe operating apparent power, i.e. thermal constraints; represents the branch at time t Active power flow from i to j; represents the branch at time t Reactive power flow from i to j; T Represents the set of all time sections; Represents the set of all nodes; Introducing slack variables to the voltage safety constraint; The branch power flow thermal constraint is abstracted into a circular constraint, and after the abstracted circular constraint is converted into a plurality of square constraints, a slack variable is introduced to represent the degree of power flow exceeding the limit at the operating point; Introducing slack variables into the voltage safety constraint includes: Two slack variables are introduced for voltage safety constraints: ； ； In the formula, and The slack variables for voltages above the upper and lower limits, respectively, indicate the extent to which the node voltage deviates from the safe operating range; The branch power flow thermal constraint is abstracted into a circular constraint, and after the abstracted circular constraint is converted into multiple square constraints, a slack variable is introduced to indicate the degree of power flow exceeding the limit at the operating point, including: The branch power flow thermal constraint is abstracted into a circle constraint, the abstracted circle constraint is converted into four square constraints, and a slack variable is introduced to represent the degree of power flow exceeding the limit at the operating point: ； ； ； ； ； ； ； ； ； ； In the formula, represents the branch at time t ( i , j ) of the power flow operation point ( P ij , Q ij ), represents the maximum value of all slack variables at time t, Represents the set of all branches.

Images