Blocking line prediction method, device, equipment, medium and product

Abstract

The application discloses a method, device, equipment, medium and product for predicting blocked lines, and relates to the technical field of power system planning. The method is executed before the clearing of a power spot market, and comprises the following steps: rewriting the transmission constraints of power transmission lines by using the output change of generators to obtain rewritten transmission constraints of the power transmission lines; determining the constraints after removing redundancy according to the solution of the feasible region of the rewritten optimal power flow model; determining a first blocked line set according to the output change of the generators, the power transfer distribution factors of the power transmission lines and the generators in a target power transmission line set, and the residual transmission capacity of the power transmission lines in the target power transmission line set; determining a second blocked line set according to the power transfer distribution factors of the power transmission lines and the generators in the target power transmission line set, and the residual transmission capacity of the power transmission lines; and determining the intersection of the two blocked line sets as blocked lines. The application can predict the blocked lines in advance before the clearing of the power spot market.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power system planning, and particularly relates to a congested line prediction method, device, equipment, medium and product. BACKGROUND

[0002] SCTL refers to a set of transmission lines that can be congested at the same time, and determining the number and location of the transmission lines that are congested at the same time (SCTL) is crucial for managing congestion risks in power system and power market operation. Since congestion limits the economic transmission of the power grid, it is very important to distinguish which lines are more likely or more frequently congested than other lines before the power spot market clearing. The existing method for determining the congested line is to solve the generator output obtained by real-time load and power flow calculation during the power market clearing process, which cannot predict the congested line in advance before the power spot market clearing. SUMMARY

[0003] The purpose of the present application is to provide a congested line prediction method, device, equipment, medium and product, which can predict the congested line in advance before the power spot market clearing.

[0004] To achieve the above purpose, the present application provides the following solutions:

[0005] In a first aspect, the present application provides a congested line prediction method, which is executed before the power spot market clearing, and the method comprises:

[0006] constructing an optimal power flow model of a target power system; the optimal power flow model comprises a first objective function and a constraint condition; the constraint condition comprises a completeness constraint and a transmission line transmission constraint; the transmission line transmission constraint comprises transmission constraints of each transmission line in the target power system;

[0007] rewriting the transmission constraints of each transmission line in the transmission line transmission constraint with generator output changes to obtain a transmission line rewritten transmission constraint; the transmission line rewritten transmission constraint comprises rewritten transmission constraints of each transmission line in the target power system;

[0008] determining redundant constraints in the transmission line rewritten transmission constraint according to a solution of a feasible region of a rewritten optimal power flow model, and deleting the redundant constraints from the transmission line rewritten transmission constraint to obtain constraints after removing the redundant constraints; the rewritten optimal power flow model comprises the first objective function, the completeness constraint and the transmission line rewritten transmission constraint;

[0009] determine a first congestion line set according to the power output variation of each generator in the target power system, the power transfer distribution factor of each transmission line and each generator in a target transmission line set, and the residual transmission capacity of each transmission line in the target transmission line set; the target transmission line set is the transmission line corresponding to each constraint after removing redundancy in the constraint;

[0010] determine a second congestion line set according to the power transfer distribution factor of each transmission line and each generator in the target transmission line set, and the residual transmission capacity of each transmission line in the target transmission line set;

[0011] determine the intersection of the first congestion line set and the second congestion line set as the corresponding congestion line of the target power system.

[0012] In a second aspect, the application provides a congestion line prediction device, which is executed before the power spot market clearing, and the congestion line prediction device comprises:

[0013] an optimal power flow model construction module, configured to construct an optimal power flow model of a target power system; the optimal power flow model comprises a first target function and a constraint condition; the constraint condition comprises an integrity constraint and a transmission line transmission constraint; the transmission line transmission constraint comprises a transmission constraint of each transmission line in the target power system;

[0014] a constraint rewriting module, configured to rewrite the transmission constraint of each transmission line in the transmission line transmission constraint with the power output variation of a generator, to obtain a transmission line rewritten transmission constraint; the transmission line rewritten transmission constraint comprises the transmission constraint of each transmission line in the target power system after rewriting;

[0015] a redundant constraint deletion module, configured to determine a redundant constraint in the transmission line rewritten transmission constraint according to a solution of a feasible region of a rewritten optimal power flow model, and delete the redundant constraint from the transmission line rewritten transmission constraint to obtain a constraint after removing redundancy; the rewritten optimal power flow model comprises the first target function, the integrity constraint, and the transmission line rewritten transmission constraint;

[0016] a first congestion line set determination module, configured to determine a first congestion line set according to the power output variation of each generator in the target power system, the power transfer distribution factor of each transmission line and each generator in a target transmission line set, and the residual transmission capacity of each transmission line in the target transmission line set; the target transmission line set is the transmission line corresponding to each constraint after removing redundancy in the constraint;

[0017] a second congestion line set determination module, configured to determine a second congestion line set according to the non-redundant constraints, the remaining transmission capacities of the power transmission lines in the target power transmission line set, and the output changes of the generators in the target power system;

[0018] a congestion line determination module, configured to determine the intersection of the first congestion line set and the second congestion line set as the corresponding congestion line of the target power system.

[0019] In a third aspect, the present application provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor executes the computer program to implement the congestion line prediction method in any of the preceding aspects.

[0020] In a fourth aspect, the present application provides a computer readable storage medium, having a computer program stored thereon, and the computer program is executed by a processor to implement the congestion line prediction method in any of the preceding aspects.

[0021] In a fifth aspect, the present application provides a computer program product, comprising a computer program, and the computer program is executed by a processor to implement the congestion line prediction method in any of the preceding aspects.

[0022] According to the embodiments provided in the present application, the following technical effects are disclosed:

[0023] The present application provides a congestion line prediction method, device, equipment, medium and product, before the power spot market clearing, the transmission constraints of each power transmission line in the transmission constraints of the power transmission line are rewritten by the output change of the generator, and the transmission constraints of the power transmission line are obtained. The transmission constraints of the power transmission line are obtained. According to the feasible region of the rewritten optimal power flow model, the redundant constraints in the transmission constraints of the power transmission line are determined, and the redundant constraints are deleted from the transmission constraints of the power transmission line to obtain the non-redundant constraints. According to the output change of each generator in the target power system, the power transfer distribution factor of each power transmission line and each generator in the target power transmission line set, and the remaining transmission capacity of each power transmission line in the target power transmission line set, a first congestion line set is determined. According to the power transfer distribution factor of each power transmission line and each generator in the target power transmission line set, and the remaining transmission capacity of each power transmission line in the target power transmission line set, a second congestion line set is determined. The intersection of the first congestion line set and the second congestion line set is determined as the corresponding congestion line of the target power system, which solves the problem of solving the congestion line by using the generator output obtained by real-time load and power flow calculation in the power market clearing process, and realizes the technical effect of predicting the congestion line in advance before the power spot market clearing. BRIEF DESCRIPTION OF DRAWINGS

[0024] In order to make the technical solutions in the embodiments of the present application or the prior art clearer, the accompanying drawings needed in the embodiments will be briefly introduced. Obviously, the accompanying drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 An application environment diagram of a blocked line prediction method in an embodiment of the present application;

[0026] Figure 2 A flowchart of a blocked line prediction method provided in an embodiment of the present application;

[0027] Figure 3 A detailed flowchart of a blocked line prediction method provided in an embodiment of the present application;

[0028] Figure 4 A structure diagram of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0029] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative effort belong to the scope of protection of the present application.

[0030] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0031] The blocked line prediction method provided in the embodiments of the present application can be applied to, for example, Figure 1The application environment shown. Among them, the terminal 102 communicates with the server 104 through the network. The data storage system can store the data required by the server 104 to process. The data storage system can be set up separately, or integrated on the server 104, or placed on the cloud or other servers. The terminal 102 can send the target power system to the server 104, and the server 104 receives the target power system. For the target power system, the server 104 builds an optimal power flow model of the target power system before the power spot market is cleared; the optimal power flow model includes a first objective function and a constraint condition; the constraint condition includes integrity constraint and transmission line transmission constraint; the transmission line transmission constraint includes the transmission constraint of each transmission line in the target power system; the transmission constraint of each transmission line in the transmission line transmission constraint is rewritten by the output change of the generator, to obtain the transmission line rewritten transmission constraint; the transmission line rewritten transmission constraint includes the rewritten transmission constraint of each transmission line in the target power system; determine the redundant constraint in the transmission line rewritten transmission constraint according to the solution of the feasible region of the rewritten optimal power flow model, and delete the redundant constraint from the transmission line rewritten transmission constraint to obtain the constraint after removing the redundancy; the rewritten optimal power flow model includes the first objective function, the integrity constraint and the transmission line rewritten transmission constraint; determine the first blocked line set according to the output change of each generator in the target power system, the power transfer distribution factor of each transmission line and each generator in the target transmission line set, and the remaining transmission capacity of each transmission line in the target transmission line set; the target transmission line set is the transmission line corresponding to each constraint in the constraint after removing the redundancy; determine the second blocked line set according to the power transfer distribution factor of each transmission line and each generator in the target transmission line set, and the remaining transmission capacity of each transmission line in the target transmission line set; the intersection of the first blocked line set and the second blocked line set is the blocked line corresponding to the target power system. The server 104 can feed back the obtained blocked line to the terminal 102. In addition, in some embodiments, the blocked line prediction method can also be realized by the server 104 or the terminal 102 alone, such as the terminal 102 can directly determine the blocked line for the target power system, or the server 104 can obtain the target power system from the data storage system and determine the blocked line for the target power system.

[0032] Among them, the terminal 102 can be but not limited to various desktop computers, notebook computers, smart phones, tablet computers, Internet of Things devices and portable wearable devices. The Internet of Things device can be a smart speaker, a smart television, a smart air conditioner, a smart vehicle device, etc. The portable wearable device can be a smart watch, a smart bracelet, a head-mounted device, etc. The server 104 can be realized by an independent server or a server cluster composed of multiple servers, and can also be a cloud server.

[0033] The current operating state of a power system reflects the results of short-term security-constrained economic dispatch, typically expressed as a linear optimal power flow problem. This problem is constrained by certain equality and inequality conditions, which define the feasible region of the optimal solution. For a typical optimal power flow problem, there are usually only a finite number of binding transmission constraints, while unconstrained constraints are redundant for defining the feasible region. Under current operating conditions, studying lines that may be simultaneously congested is beneficial for short-term market analysis. Based on this, this application provides an effective method to identify and eliminate a large number of potentially unconstrained transmission constraints to determine congested lines, thereby helping to support power system and market decisions, such as... Figure 2 As shown, first, step A is executed: based on the Optimal Power Flow (OPF) model, the transmission constraints of transmission lines are rewritten using incremental changes in generator output. The absolute impact of generator output changes on transmission congestion is analyzed, and a constraint reduction method based on maximization elimination is proposed. Then, step B is executed: the sensitivity of power flow between transmission lines is compared with possible changes in generator output, and a constraint reduction method based on comparison elimination is proposed. Based on the maximization elimination method and the comparison elimination method, an intersection algorithm is proposed to determine the set of congested lines. In an exemplary embodiment, as shown... Figure 3 As shown, a method for predicting congested lines before the clearing of the electricity spot market is provided. This method is executed by computer equipment, specifically by a terminal or server alone, or by both a terminal and a server. In this embodiment, the method is applied to... Figure 1 Taking server 104 as an example, the explanation includes the following steps 201 to 206. Wherein:

[0034] Step 201: Construct the optimal power flow model of the target power system. The optimal power flow model includes a first objective function and constraints; the constraints include integrity constraints and transmission line constraints; the transmission line constraints include the transmission constraints of each transmission line in the target power system.

[0035] Step 202: Rewrite the transmission constraints of each transmission line in the transmission line transmission constraints using the changes in generator output, to obtain the rewritten transmission constraints of the transmission lines. The rewritten transmission constraints of the transmission lines include the rewritten transmission constraints of each transmission line in the target power system.

[0036] Step 203: Determine the redundant constraints in the transmission constraints of the rewritten transmission line based on the solution of the feasible region of the rewritten optimal power flow model, and remove the redundant constraints from the rewritten transmission constraints to obtain the constraints after redundancy removal. The rewritten optimal power flow model includes the first objective function, integrity constraints, and the rewritten transmission constraints of the transmission line.

[0037] Step 204: determining a first blocked line set according to the power output variation of each generator in the target power system, the power transfer distribution factor of each transmission line and each generator in the target transmission line set, and the remaining transmission capacity of each transmission line in the target transmission line set. The target transmission line set is the transmission line corresponding to each constraint after removing redundancy in the constraint.

[0038] Step 205: determining a second blocked line set according to the power transfer distribution factor of each transmission line and each generator in the target transmission line set, and the remaining transmission capacity of each transmission line in the target transmission line set.

[0039] Step 206: determining the intersection of the first blocked line set and the second blocked line set as the blocked line corresponding to the target power system.

[0040] By implementing the above steps 201 to 206, the blocked line can be predicted in advance before the power spot market is cleared.

[0041] In practical applications, the first objective function is:

[0042]

[0043] Wherein, min is the minimum value, a i is the cost coefficient of the i-th generator, is the active power output of the i-th generator, and NG is the total number of generators in the target power system.

[0044] The integrity constraint is:

[0045]

[0046] Wherein, D J is the load of the j-th node, N is the total number of nodes, and loss is the network loss of all transmission lines.

[0047] The transmission constraint of the j-th transmission line in the target power system is:

[0048]

[0049] The transmission constraint of the transmission line is:

[0050]

[0051] Wherein, is the upper limit of the active power output of the i-th generator; is the lower limit of the active power output of the i-th generator, and f j is the power flow of the j-th transmission line; and fj,max GSF is the transmission capacity limit of the jth transmission line j,i is the power transfer distribution factor of the jth transmission line and the ith generator; NL is the number of lines.

[0052] In practical applications, the rewritten transmission constraint of the jth transmission line in the target power system is:

[0053]

[0054] where GSF j,i is the power transfer distribution factor of the jth transmission line and the ith generator, is the output change of the ith generator, is the remaining transmission capacity of the jth transmission line, is the minimum output change of the ith generator, is the maximum output change of the ith generator.

[0055] In practical applications, the criterion for determining whether a transmission line rewritten transmission constraint is a redundant constraint is proposed according to the solution of the feasible region of the rewritten optimal power flow model, which specifically includes:

[0056] solving the optimal solution of the feasible region of the rewritten optimal power flow model, obtaining a first optimal solution. For example: for the rewritten optimal power flow model, the feasible region of this problem can be expressed as follows:

[0057]

[0058] For any one transmission line in the target power system, solve the optimal solution of the feasible region of the target rewritten optimal power flow model corresponding to the transmission line, obtain a second optimal solution; the target rewritten optimal power flow model corresponding to the transmission line is obtained by deleting the rewritten transmission constraint of the transmission line from the rewritten optimal power flow model. For example: for the transmission line m, assuming that the optimal solution does not change after removing the constraint (rewritten transmission constraint of the transmission line m), in this case, the new feasible region after removing the constraint is described by a smaller set of constraints, which is as follows:

[0059]

[0060] If the second optimal solution is equal to the first optimal solution, i.e. S=S', the rewritten transmission constraint of the transmission line is a redundant constraint, i.e. the rewritten transmission constraint of the transmission line m is a redundant constraint.

[0061] In practical applications, according to the output variation of each generator in the target power system, the power transfer distribution factor of each transmission line and each generator in the target transmission line set, and the residual transmission capacity of each transmission line in the target transmission line set, the first blocked line set is determined as the absolute influence of the generator output variation on the transmission congestion, and the proposed maximum elimination constraint reduction method specifically includes:

[0062] For the jth transmission line in the target transmission line set, solve the optimization problem Get the output variation of each generator corresponding to the jth transmission line, in this problem, the objective function is composed of two terms, where the constant coefficient (GSF j,i ) in the first term is positive, and the constant coefficient (GSF j,i ) in the second term is negative. In order to maximize the objective function in this problem, the in the first term should be set to its maximum value, and the in the second term should be set to its minimum value. In this way, in the optimal solution, the first and second terms respectively reach their maximum and minimum values. Wherein, M j is the maximum residual transmission capacity of the jth transmission line, max is the maximum value, GSF j,i is the power transfer distribution factor of the jth transmission line and the ith generator, is the output variation of the ith generator, P j is the generator that makes GSF j,i greater than 0, N j is the generator that makes GSF j,i less than 0, is the minimum output variation of the ith generator, is the maximum output variation of the ith generator.

[0063] According to the output variation of each generator corresponding to the jth transmission line, the output variation of all generators that make the power flow on the jth transmission line maximum is obtained.

[0064] If holds, the transmission constraint corresponding to the jth transmission line is a redundant constraint, since the redundant constraint indicates that the transmission constraint of the line is not in effect, i.e. the transmission capacity of the line has not exceeded, the line corresponding to the constraint is a non-congestion line, so the jth transmission line is a non-congestion line, wherein NG is the total number of generators in the target power system, is the output variation of the ith generator that makes the power flow on the jth transmission line maximum, is the generator output variation set that makes the power flow on the jth transmission line maximum, is the residual transmission capacity of the jth transmission line.

[0065] The first blocked line is obtained by deleting all non-blocked lines in the target set of transmission lines.

[0066] In practical application, the second blocked line set is determined according to the power transfer distribution factors of each transmission line and each generator in the target set of transmission lines and the residual transmission capacity of each transmission line in the target set of transmission lines, and the proposed comparison elimination constraint reduction method compares the sensitivity of power flow between transmission lines and the possible change of generator output, and specifically comprises the following steps:

[0067] Dividing the line transmission constraint by both sides And redefining the normalized generation shift factor as: At this time, the line transmission constraint can be expressed as: Considering the jth transmission constraint in the OPF problem, if the normalized generation shift factor c j,i satisfies the following condition: for all c j,i ≤ c k,i , the transmission constraint of the jth transmission line is a redundant constraint. Because, when the inequality holds for line k, it also holds for the jth transmission line under the same generation allocation In other words: this means that the kth constraint prevents the constraint of the jth constraint and defines the boundary of the feasible region. Therefore, the jth constraint can be eliminated as a redundant constraint. So for the jth transmission line in the target set of transmission lines, if for all generators is always true, the transmission constraint corresponding to the jth transmission line is a redundant constraint, since the redundant constraint indicates that the transmission constraint of the line is not in effect, i.e. the transmission capacity of the line has not been exceeded, the line corresponding to the constraint is a non-blocked line, so the jth transmission line is a non-blocked line.

[0068] The second blocked line is obtained by deleting all non-blocked lines in the target set of transmission lines.

[0069] The maximum elimination method and the comparison elimination method are sufficient conditions for identifying redundant transmission constraints. Therefore, from the absolute and relative values, both are conservative criteria and can identify some redundant constraints. However, in each SCTL created by these criteria, there may be some overlapping lines. First, the redundant constraints are determined according to the maximum elimination method and the comparison elimination method. Finally, by taking the non-set of the two sets of redundant constraint sets created by these criteria, two sets of SCTL sets created by different methods are obtained, and the intersection of the two sets can obtain the required smaller SCTL set.

[0070] The application further provides an application scenario of the congestion line prediction method. Specifically, the congestion line prediction method provided by the embodiment can be applied in short-term market analysis. The short-term market analysis includes determining congestion lines and performing market analysis according to the congestion lines. The congestion line prediction method provided by the embodiment belongs to the step of determining congestion lines in the short-term market analysis.

[0071] In an exemplary embodiment, the feasibility and accuracy of the congestion line prediction method provided by the application are verified by performing instance analysis on an IEEE 39-node system.

[0072] The maximization elimination method and the comparison elimination method are further described by using an IEEE 39-node system for simulation research. The IEEE 39-node system has 31 lines, 10 transformers, 39 buses, 10 generators and 17 loads, and it is assumed that the loads change slowly and show a growth trend.

[0073] Firstly, the maximization elimination method will be described. This criterion evaluates the absolute impact of generation on congestion. To this end, the impact of all online generators on congestion is compared according to the information in Table 1 and Table 2. Table 1 shows the GSF of some lines that are most sensitive and least sensitive to generation scheduling, as well as the amount of individual generation change required to form congestion on each line. According to Table 1, line 2-3 is easily congested due to the output increase of most generators. On the other hand, line 4-5 will only be congested if the output of generator G31, G32 or G39 increases. Table 2 shows the additional output change of each generator required to overload the transmission line. Due to display limitations, only the generation output change required to overload lines 2-1, 2-3, 16-15, 4-5 and 16-19 is shown in the respective columns. Among them, “N / A” means no impact. Table 2 also shows the order in which each generator causes line overload. It shows that the amount of generation output increase required to overload some lines is smaller compared to other lines; therefore, these lines will first experience congestion before other lines. For example, the data in column 2, column 4 and row 1 shows that the output increase required to overload line 2-3 with generator G31 is significantly smaller than the amount required to overload line 4-5. This means that under the current operating conditions, if there is no congestion on line 2-3, congestion on line 4-5 is unlikely to occur. The same is true for generators G32 and G39.

[0074] Next, the comparative elimination method is explained. To find the SCTLs, the comparative elimination method evaluates the relative impact of generation on congestion. According to this criterion, the relative sensitivity of line flow to generation output is compared. The result of the comparison is that for most lines, they will only be congested by the generators at a particular location. Among these lines, the lines that are less sensitive to generation changes will not be congested because the more sensitive lines will always be congested first. To further explain the comparative elimination criterion, the information in Tables 1 and 2 is utilized. As shown in the last column of Table 1, line 16-19 is only sensitive to the output of generator groups 33 and 34. Specifically, the calculations show that an increase of 51.6 MW in the output of either of these two generator groups will overload the line. All other lines have a smaller GSF and are less sensitive to changes in the output of generator groups 33 and 34. Therefore, according to the comparative elimination method, it can be concluded that these other lines will not be congested unless line 16-19 is congested.

[0075] The results of the example of the IEEE 39-bus system are shown in Table 3: according to the maximum elimination method, 14 non-redundant constraints are found, and the remaining line set is taken as set A, excluding the non-congested lines corresponding to the redundant constraints; while according to the comparative elimination method, 6 non-redundant constraints are determined, and the same is taken as set B. Through the proposed algorithm, the intersection of set A and set B is finally determined as the SCTLs.

[0076] The feasibility of the congestion line prediction method provided by the above embodiments is verified by the simulation research on the IEEE 39-bus test system. The results of the example analysis confirm that the proposed method has a reasonable accuracy level in identifying congestion lines.

[0077] Table 1 GSF matrix of IEEE 39-bus system

[0078] GSF GSF 2-1,i ]] GSF 2-3,i ]]> GSF 16-15,i ]]> GSF 4-5,i ]]> GSF 16-19,i ]]> G 31 ]] -0.211 -0.632 -0.249 -0.504 0 G 32 ]]> -0.187 -0.645 -0.289 -0.289 0 G 33 ]]> -0.102 -0.636 0.295 0 -1 G 34 ]]> -0.102 -0.636 0.295 0 -1 G 35 ]]> -0.102 -0.636 0.295 0 0 G 36 ]]> -0.102 -0.636 0.295 0 0 G 37 ]] 0 -0.739 0.022 0 0 G 38 ]] -0.048 -0.351 0.105 0 0 G 39 ]]> -0.609 -0.313 -0.122 -0.262 0

[0079] Table 2 Line power flow of IEEE 39-bus system

[0080]

[0081]

[0082] Table 3 Results of example analysis

[0083]

[0084] The method has the following characteristics: firstly, according to an optimal power flow (OPF) model of the power market, transmission constraints of transmission lines are rewritten by using incremental changes of generator outputs, and a criterion for judging whether a transmission constraint is a redundant constraint is defined; on this basis, an absolute influence of generator output changes on transmission congestion is analyzed, a constraint reduction method of maximum elimination is proposed, and a new optimization model is established to obtain corresponding generator output changes. Secondly, the sensitivity of power flow between transmission lines and possible generator output changes are compared, and a constraint reduction method of comparison elimination is proposed. Finally, based on the maximum elimination method and the comparison elimination method, an intersection algorithm is used to determine an SCTL (set of congested lines). The method proposed in the application can not only determine the congested lines before the power spot market clearing, but also eliminate redundant transmission constraints to reduce the dimension of the market clearing optimization problem.

[0085] Based on the same inventive concept, the embodiments of the application also provide a congested line prediction device for implementing the above-mentioned congested line prediction method. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme described in the above method, and therefore the specific limitations in one or more congested line prediction device embodiments provided below can refer to the limitations of the congested line prediction method described above, which will not be repeated here.

[0086] In an exemplary embodiment, a congested line prediction device is provided for execution before the power spot market clearing, and the congested line prediction device comprises:

[0087] An optimal power flow model construction module is configured to construct an optimal power flow model of a target power system; the optimal power flow model comprises a first objective function and constraint conditions; the constraint conditions comprise integrity constraints and transmission constraints of transmission lines; the transmission constraints of transmission lines comprise transmission constraints of each transmission line in the target power system.

[0088] A constraint rewriting module is configured to rewrite the transmission constraints of each transmission line in the transmission constraints of transmission lines by using changes in generator outputs, to obtain rewritten transmission constraints of transmission lines; the rewritten transmission constraints of transmission lines comprise rewritten transmission constraints of each transmission line in the target power system.

[0089] A redundant constraint deletion module is configured to determine redundant constraints in the rewritten transmission constraints of transmission lines according to a feasible region of a rewritten optimal power flow model, and delete the redundant constraints from the rewritten transmission constraints of transmission lines to obtain constraints after redundant constraints are removed; the rewritten optimal power flow model comprises the first objective function, the integrity constraints and the rewritten transmission constraints of transmission lines.

[0090] The first congestion line set determination module is configured to determine a first congestion line set according to power output changes of each generator in the target power system, power transfer distribution factors of each power transmission line and each generator in the target power transmission line set, and residual transmission capacities of each power transmission line in the target power transmission line set.

[0091] The second congestion line set determination module is configured to determine a second congestion line set according to the constraints after removing the redundancy, the residual transmission capacities of each power transmission line in the target power transmission line set, and the power output changes of each generator in the target power system.

[0092] The congestion line determination module is configured to determine an intersection of the first congestion line set and the second congestion line set as the corresponding congestion line of the target power system.

[0093] In an exemplary embodiment, a computer device is provided, which can be a server or a terminal. An internal structure diagram of the computer device can be as shown in Figure 4 The computer device includes a processor, a memory, an input / output interface (I / O), and a communication interface. The processor, the memory, and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for running the operating system and the computer program in the non-volatile storage medium. The database of the computer device is configured to store congestion line prediction data. The input / output interface of the computer device is configured to exchange information between the processor and external devices. The communication interface of the computer device is configured to communicate with external terminals through a network connection. The computer program is executed by the processor to implement a congestion line prediction method.

[0094] Those skilled in the art can understand that Figure 4 The structure shown in the above

[0095] In an exemplary embodiment, a computer device is provided, which can be a server or a terminal. An internal structure diagram of the computer device can be as shown in

[0096] In an exemplary embodiment, a computer readable storage medium storing a computer program is provided, the computer program, when executed by a processor, implements the steps of any of the above method embodiments.

[0097] In an exemplary embodiment, a computer program product is provided, comprising a computer program, which, when executed by a processor, implements the steps of any of the above method embodiments.

[0098] It should be noted that the user information (including but not limited to user equipment information, user personal information, etc.) and data (including but not limited to data for analysis, stored data, displayed data, etc.) involved in the present application are all information and data authorized by the user or authorized by all parties, and the collection, use and processing of related data need to comply with relevant regulations.

[0099] It can be understood by those skilled in the art that all or part of the processes in the above embodiments can be completed by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer readable storage medium. When the computer program is executed, it can include the processes of the above embodiments. Any reference to memory, database or other medium used in the embodiments provided by the present application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical storage, high-density embedded non-volatile memory, resistive memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration but not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0100] The database involved in each of the embodiments provided in the present application can include at least one of a relational database and a non-relational database. The non-relational database can include a distributed database based on a blockchain, and the like, without being limited thereto. The processor involved in each of the embodiments provided in the present application can be a general-purpose processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, and the like, without being limited thereto.

[0101] The technical features of the above embodiments can be combined in any manner. To make the description concise, all possible combinations of the technical features in the above embodiments are not described, but it should be considered that any combination of the technical features is within the scope of the present disclosure, as long as there is no contradiction.

[0102] The principles and implementation manners of the present application are described by using specific examples herein, and the above embodiments are only used to help understand the method of the present application and its core idea. Meanwhile, for those skilled in the art, the specific implementation manners and application ranges can be changed according to the idea of the present application. In summary, the content of the present description should not be understood as a limitation of the present application.

Claims

1. A method of predicting a line seizure, characterized by, The congestion line prediction method is executed before power spot market clearing, and the congestion line prediction method comprises: An optimal power flow model of the target power system is constructed; the optimal power flow model comprises a first objective function and constraint conditions; the constraint conditions comprise integrity constraints and transmission constraints of transmission lines; the transmission constraints of transmission lines comprise transmission constraints of each transmission line in the target power system; Transmission constraints of each transmission line in the transmission constraints of transmission lines are rewritten by power output changes of generators to obtain rewritten transmission constraints of transmission lines; the rewritten transmission constraints of transmission lines comprise rewritten transmission constraints of each transmission line in the target power system; Redundant constraints in the rewritten transmission constraints of transmission lines are determined according to a solution of a feasible region of a rewritten optimal power flow model, and the redundant constraints are deleted from the rewritten transmission constraints of transmission lines to obtain constraints after redundancy removal; the rewritten optimal power flow model comprises the first objective function, the integrity constraints and the rewritten transmission constraints of transmission lines; A first congestion line set is determined according to power output changes of each generator in the target power system, power transfer distribution factors of each transmission line and each generator in a target transmission line set, and residual transmission capacities of each transmission line in the target transmission line set; the target transmission line set is each transmission line corresponding to a constraint after redundancy removal; A second congestion line set is determined according to power transfer distribution factors of each transmission line and each generator in the target transmission line set, and residual transmission capacities of each transmission line in the target transmission line set; An intersection of the first congestion line set and the second congestion line set is determined as a congestion line corresponding to the target power system.

2. The congestion line prediction method according to claim 1, wherein, The first objective function is: wherein min is the minimum value, a i is the cost coefficient of the i-th generator, is the active power output of the i-th generator, and NG is the total number of generators in the target power system. The integrity constraint is: where D J is the load of the Jth node, N is the total number of nodes, and loss is the network loss of all transmission lines. The transmission constraint of the jth transmission line in the target power system is: where, is the upper limit of the active power output of the ith generator; is the lower limit of the active power output of the ith generator, j is the power flow of the jth transmission line; j,max is the transmission capacity limit of the jth transmission line, j,i is the power transfer distribution factor of the jth transmission line and the ith generator.

3. The method of claim 1, wherein, the rewritten transmission constraint of the jth transmission line in the target power system is: where GSF j,i is the power transfer distribution factor of the jth transmission line and the ith generator, is the minimum change of the ith generator, is the remaining transmission capacity of the jth transmission line, is the minimum change of the ith generator, is the maximum change of the ith generator.

4. The method of claim 1, wherein, determining redundant constraints in the rewritten transmission constraints of transmission lines according to a solution of a feasible region of a rewritten optimal power flow model specifically comprises: an optimal solution of the feasible region of the rewritten optimal power flow model is solved to obtain a first optimal solution; for any transmission line in the target power system, an optimal solution of a feasible region of a target rewritten optimal power flow model corresponding to the transmission line is solved to obtain a second optimal solution; the target rewritten optimal power flow model corresponding to the transmission line is obtained by deleting the rewritten transmission constraint of the transmission line from the rewritten optimal power flow model; if the second optimal solution is equal to the first optimal solution, the rewritten transmission constraint of the transmission line is a redundant constraint.

5. The method of claim 1, wherein, determining the first congestion line set according to power output changes of each generator in the target power system, power transfer distribution factors of each transmission line and each generator in a target transmission line set, and residual transmission capacities of each transmission line in the target transmission line set specifically comprises: For the jth transmission line in the target transmission line set, solve to obtain the power change of each generator corresponding to the jth transmission line, where M j is the maximum residual transmission capacity of the jth transmission line, max is the maximum value, GSF j,i is the power transfer distribution factor of the jth transmission line and the ith generator, is the power change of the ith generator, P j is the generator that makes GSF j,i greater than 0, N j is the generator that makes GSF j,i less than 0, is the minimum power change of the ith generator, is the maximum power change of the ith generator; power output changes of all generators that make the power flow on the jth transmission line maximum are obtained according to power output changes of each generator corresponding to the jth transmission line; If the jth transmission line is non-blocking, where NG is the total number of generators in the target power system, to change the output of the ith generator with the largest power flow on the jth transmission line, is the remaining transmission capacity of the jth transmission line. all non-congestion lines in the target transmission line set are deleted to obtain the first congestion line.

6. The method of claim 1, wherein, The second congestion line set is determined according to the power transfer distribution factors of the generators and the transmission lines in the target transmission line set and the residual transmission capacity of each transmission line in the target transmission line set, and specifically comprises the following steps: For the jth transmission line in the target transmission line set, if holds for all generators, the jth transmission line is a non-blocking line. All non-congestion lines in the target transmission line set are deleted to obtain the second congestion line.

7. A device for predicting a line seizure, characterized in that The congestion line prediction device is executed before the power spot market is cleared, and the congestion line prediction device comprises: An optimal power flow model construction module is configured to construct an optimal power flow model of a target power system; the optimal power flow model comprises a first target function and a constraint condition; the constraint condition comprises an integrity constraint and a transmission line transmission constraint; the transmission line transmission constraint comprises transmission constraints of each transmission line in the target power system; A constraint rewriting module is configured to rewrite the transmission constraints of each transmission line in the transmission line transmission constraint with power output changes of the generators to obtain transmission line rewritten transmission constraints; the transmission line rewritten transmission constraints comprise rewritten transmission constraints of each transmission line in the target power system; A redundant constraint deletion module is configured to determine redundant constraints in the transmission line rewritten transmission constraints according to a solution of a feasible region of a rewritten optimal power flow model, and delete the redundant constraints from the transmission line rewritten transmission constraints to obtain constraints after redundant constraints are removed; the rewritten optimal power flow model comprises the first target function, the integrity constraint, and the transmission line rewritten transmission constraint; A first congestion line set determination module is configured to determine a first congestion line set according to power output changes of the generators in the target power system, power transfer distribution factors of the generators and the transmission lines in a target transmission line set, and residual transmission capacities of the transmission lines in the target transmission line set; the target transmission line set is a transmission line corresponding to each constraint after redundant constraints are removed; A second congestion line set determination module is configured to determine a second congestion line set according to the constraints after redundant constraints are removed, the residual transmission capacities of the transmission lines in the target transmission line set, and the power output changes of the generators in the target power system; A congestion line determination module is configured to determine an intersection of the first congestion line set and the second congestion line set as a congestion line corresponding to the target power system.

8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the congestion line prediction method of any one of claims 1-6.

9. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the congestion line prediction method of any one of claims 1-6.

10. A computer program product comprising a computer program, characterized in that, The computer program is executed by the processor to implement the congestion line prediction method of any one of claims 1-6.

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