Safety-constrained economic dispatch linear programming preprocessing method, system and storage medium

Abstract

A method, system and storage medium for preprocessing linear programming of safety-constrained economic dispatch, the method includes the following: constraint and decision variable legality identification, so that conflicting constraints and illegal values ​​do not participate in safety-constrained economic dispatch; parameterized processing of output variables of shutdown units, so that shutdown units do not participate in safety-constrained economic dispatch; section limit redundant constraint identification, by dividing the section into a must-not-go section, a must-go section and a pending state section, and identifying the must-not-go section as a redundant constraint, so that the must-not-go section does not participate in safety-constrained economic dispatch; redundant variable and constraint identification based on matrix operations, so that redundant variables and constraints do not participate in safety-constrained economic dispatch. The present invention has the advantage of customized performance improvement for specific problems, and can improve the solution efficiency to a greater extent. The present invention can eliminate the technical safety risks faced by power grid dispatch optimization operation analysis and power spot market operation, and ensure the safe, stable and economic operation of the power grid.

Description

Technical Field

[0001] The present invention belongs to the technical field of electric power spot market, and in particular relates to a safety-constrained economic dispatch linear programming preprocessing method, system and storage medium. Background Art

[0002] The electricity spot market is a key link in establishing a competitive mechanism and achieving optimal allocation of power resources. It is an important mechanism to change the traditional way of dispatching power generation plans and form an important mechanism to use market transaction results as the main basis for arranging dispatching power generation plans. The benefit distribution of traditional economic dispatch has become difficult. The mode of arranging power generation dispatch plans according to economic dispatch and real-time dispatch has been challenged by fairness. Building an electricity spot market, promoting efficiency through market mechanisms, promoting energy transformation, and achieving optimal allocation of energy and power resources have become important means. Safety-constrained economic dispatch refers to economic dispatch that takes safety constraints into consideration, takes the minimum unit operating cost or the maximum social welfare as the optimization goal, considers factors such as unit operating cost, power balance, unit operating constraints, and power grid safety constraints, and optimizes the unit output plan on the basis of the unit start and stop determination. It can achieve the optimal solution of the goal on the premise of meeting the power grid safety constraints and various practical constraints, thereby ensuring that the calculation results meet the requirements of safety, energy saving and economy. It is a full-featured overall solution. The application of economic dispatch technology in the clearing of the electricity spot market generally considers factors such as market quotations, supply and demand balance, and unit operation constraints. With the goal of maximizing social benefits, the economic dispatch program is used to optimize the output plan of the units in the electricity spot market, and the safety of the power grid and the feasibility of transactions are guaranteed through safety verification and congestion management. Linear programming is an important branch of operations research that has been studied earlier, widely used, and has relatively mature methods. It is a common mathematical method for optimizing management and scheduling decisions in auxiliary engineering practice. The optimization problem based on linear programming consists of a linear objective function and linear constraints. Its model construction mainly considers the range of decision variables, the construction of the objective function based on the decision variables, and the formation of constraints. By solving the extreme value of the objective function and determining the value of the decision variables, it provides decision guidance for actual scheduling management. The most basic method for solving linear programming problems is the simplex method and its derivative methods (such as the improved simplex method, the dual simplex method, etc.).

[0003] Safety-constrained economic dispatch is the core link of the complete business chain of the electricity spot market. The efficiency and optimality of optimization calculations are the key to real-time market clearing business. The provincial safety-constrained economic dispatch optimization problem involves tens of thousands to hundreds of thousands of variables and hundreds of thousands to millions of constraints. It is a large-scale linear programming problem. When using domestic optimization engines to solve it, the problems of calculation speed and calculation accuracy are the difficulties that need to be overcome. At present, the optimization solvers for solving linear programming problems are all foreign commercial optimization engines. On the one hand, in order to realize the localization and independence of the underlying optimization engine, it is necessary to overcome the relevant optimization problem solving technology. One of the important difficulties is the preprocessing of the optimization problem, that is, how to simplify the optimization problem and improve the solving efficiency by identifying redundant constraints and reducing the model dimension of the linear programming problem in advance; on the other hand, the "black box" characteristics of foreign commercial optimization engines make their preprocessing general mathematical processing, which cannot consider the physical meaning and coefficient matrix characteristics of specific problems and perform personalized preprocessing. Summary of the invention

[0004] The purpose of the present invention is to provide a safety-constrained economic dispatch linear programming preprocessing method, system and storage medium to address the problems in the above-mentioned prior art, so as to achieve preprocessing of large-scale safety-constrained economic dispatch problems before solving them, thereby reducing the variables and constraint scale of the optimization problem and simplifying the complexity of solving the optimization problem.

[0005] In order to achieve the above object, the present invention has the following technical solutions:

[0006] In a first aspect, a safety-constrained economic dispatch linear programming preprocessing method is provided, comprising:

[0007] Identify the legality of constraints and decision variables, find out the conflicting constraints and illegal values ​​in the constraints and decision variables, and make sure that the conflicting constraints and illegal values ​​do not participate in the safety-constrained economic dispatch;

[0008] The output variables of the units in shutdown state are obtained and parameterized so that the units in shutdown state do not participate in the safety-constrained economic dispatch;

[0009] Obtain and identify redundant constraints on section limits, divide sections into sections that must not exceed the limit, sections that must exceed the limit, and sections in pending state, and identify sections that must not exceed the limit as redundant constraints, so that sections that must not exceed the limit do not participate in safety-constrained economic dispatch;

[0010] Redundant variables and constraints are identified based on matrix operations, so that they do not participate in safety-constrained economic scheduling.

[0011] Preferably, in the steps of identifying the legitimacy of constraints and decision variables and finding conflicting constraints and illegal values ​​in constraints and decision variables, combined with the physical meaning of the safety-constrained economic dispatch problem, by carrying out the legitimacy and conflicting relationships of constraints and decision power limits in advance, the infeasibility of the optimization problem is predicted before solving the optimization clearing model, and conflicting constraints and illegal values ​​are found.

[0012] Preferably, in the step of parameterizing the output variable of the shutdown state machine group, the parameterizing includes:

[0013] The output optimization variables of the shutdown units are treated as non-optimized variables, and the optimized output value is fixed to 0;

[0014] Alternatively, the output of the shutdown unit is increased by the following constraint set to optimize the output result of the shutdown unit with an output of 0:

[0015]

[0016] In the formula, p i They represent the upper and lower limits of the output power of generator set i respectively.

[0017] Preferably, the cross-section limit redundant constraint identification is implemented based on the limit method, and the cross-section limit constraint is expressed as follows:

[0018]

[0019] Where, Sens PTDF (nd,ln,t) represents the sensitivity transfer factor of node nd to line ln at time t, P Gen (nd,t) is the output of the power generation resource of node nd at time t, P Bus (nd,t) is the load of node nd at time t, P tie (nd,t) is the out-of-area power of node nd at time t, L Bus (nd,t) represents the node load of node nd at time t; Lim(ln) represents the upper capacity limit of line ln; NP Gen (nd,t) represents the power output of node nd at time t, which conforms to the following expression:

[0020]

[0021] In the formula, List NodeGen (nd,i) represents the corresponding relationship between node nd and unit i, P(i,t) is the output of unit i at time t; if List NodeGen (nd,i)=1, it means that unit i is on node nd. If ListNodeGen (nd,i)=0, which means that unit i is not on node nd.

[0022] Preferably, in the step of dividing the section into the section that must not be crossed, the section that must be crossed and the section in pending state, the section that must not be crossed and the section that must be crossed are respectively identified with positive section constraints and reverse section constraints, and the section in pending state is the section remaining after deducting the section that must not be crossed and the section that must be crossed from all sections.

[0023] Preferably, the method for performing positive section constraint identification on the section that must not exceed the limit is as follows:

[0024] For units whose start / stop status is shutdown, the output is set to 0;

[0025] For the unit i whose start / stop status is on:

[0026] If Sens PTDF (i,ln,t)>0, the unit output is assumed to be the maximum technical output P max (i, t), as the worst extreme case where the unit output reaches the maximum, which aggravates the blockage of the section;

[0027] If Sens PTDF (i,ln,t)≤0, the unit output is assumed to be the minimum technical output P min (i, t), as the extreme case where the unit output contribution to alleviate the blockage of the section is the smallest;

[0028] Substituting the above extreme output conditions into the expression of section limit constraints, we can obtain the section flow under extreme conditions:

[0029]

[0030] Among them, i represents the set of units with positive sensitivity, and j represents the set of units with negative sensitivity; if the section flow Flow(ln)<=Lim(ln) in extreme cases, the section is identified as a section that must not exceed the limit.

[0031] Preferably, the method for identifying the reverse section constraint of the section that must not exceed the limit is as follows:

[0032] For units whose start / stop status is shutdown, the output is set to 0;

[0033] For the unit i whose start / stop status is on:

[0034] If Sens PTDF (i,ln,t)>0, the unit output is assumed to be the minimum technical output P min(i, t), as the worst extreme case where the unit output reaches the maximum, which aggravates the blockage of the section;

[0035] If Sens PTDF (i,ln,t)≤0, the unit output is assumed to be the maximum technical output P max (i, t), as the extreme case where the unit output contribution to alleviate the blockage of the section is the smallest;

[0036] Substituting the above extreme output conditions into the expression of section limit constraints, we can obtain the section flow under extreme conditions:

[0037]

[0038] Among them, i represents the set of units with positive sensitivity, and j represents the set of units with negative sensitivity; if the section flow Flow(ln) in the above extreme case is greater than or equal to -Lim(ln), the section is identified as a section that must not exceed the limit.

[0039] Preferably, the method for identifying the positive section constraint of the must-cross-limit section is as follows:

[0040] For units whose start / stop status is shutdown, the output is set to 0;

[0041] For the unit i whose start / stop status is on:

[0042] If Sens PTDF (i,ln,t)>0, the unit output is assumed to be the minimum technical output P min (i, t), as the optimal extreme case where the unit output is minimized to aggravate the blockage of the section;

[0043] If Sens PTDF (i,ln,t)≤0, the unit output is assumed to be the maximum technical output P max (i, t), as the optimal extreme case where the unit output reaches the maximum to alleviate the blockage of the section;

[0044] Substituting the above extreme output conditions into the expression of section limit constraints, we can obtain the section flow under extreme conditions:

[0045]

[0046] Among them, i represents the set of units with positive sensitivity, and j represents the set of units with negative sensitivity; if the section flow Flow(ln)>Lim(ln) in extreme cases, the section is identified as a limit-crossing section.

[0047] Preferably, the method for identifying the reverse section constraint of the must-cross-limit section is as follows:

[0048] For units whose start / stop status is shutdown, the output is set to 0;

[0049] For the unit i whose start / stop status is on:

[0050] If Sens PTDF (i,ln,t)>0, the unit output is assumed to be the maximum technical output P max (i, t), as the worst extreme case where the unit output reaches the maximum, which aggravates the blockage of the section;

[0051] If Sens PTDF (i,ln,t)≤0, the unit output is assumed to be the minimum technical output P min (i, t), as the extreme case where the unit output contribution to alleviate the blockage of the section is the smallest;

[0052] Substituting the above extreme output conditions into the expression of section limit constraints, we can obtain the section flow under extreme conditions:

[0053]

[0054] Among them, i represents the set of units with positive sensitivity, and j represents the set of units with negative sensitivity. If the section flow Flow(ln)<-Lim(ln) in the above extreme case, the section is identified as a limit-crossing section.

[0055] Preferably, in the step of identifying redundant variables and constraints based on matrix operations, the redundant variables and constraints include constant variables, zero variables, non-pole variables, redundant non-zero elements of the coefficient matrix, empty rows or columns, proportional columns, proportional rows and individual columns.

[0056] In a second aspect, a safety-constrained economic dispatch linear programming preprocessing system is provided, comprising:

[0057] The legality identification module is used to identify the legality of constraints and decision variables, find out the conflicting constraints and illegal values ​​in the constraints and decision variables, and prevent the conflicting constraints and illegal values ​​from participating in the safety-constrained economic dispatch;

[0058] A parameterization processing module is used to obtain the output variable of the shutdown unit and perform parameterization processing on the output variable of the shutdown unit so that the shutdown unit does not participate in the safety-constrained economic dispatch;

[0059] The section limit redundancy identification module is used to obtain and identify the section limit redundancy constraints, divide the section into the section that must not exceed the limit, the section that must exceed the limit, and the section in pending state, and identify the section that must not exceed the limit as a redundant constraint, so that the section that must not exceed the limit does not participate in the safety constraint economic dispatch;

[0060] The matrix operation redundancy identification module is used to identify redundant variables and constraints based on matrix operations, so that the redundant variables and constraints do not participate in the safety constraint economic dispatch.

[0061] Preferably, the parameterized processing module processes the output optimization variable of the shutdown state unit as a non-optimized variable, and fixes the optimized output value to 0; or, the output of the shutdown state unit is increased by the following constraint set to optimize the output result of the shutdown unit with an output of 0:

[0062]

[0063] In the formula, p i They represent the upper and lower limits of the output power of generator set i respectively.

[0064] Preferably, the cross-section limit redundancy identification module realizes cross-section limit redundancy constraint identification based on the limit method, and the cross-section limit constraint is expressed as follows:

[0065]

[0066] Where, Sens PTDF (nd,ln,t) represents the sensitivity transfer factor of node nd to line ln at time t, P Gen (nd,t) is the output of the power generation resource of node nd at time t, P Bus (nd,t) is the load of node nd at time t, P tie (nd,t) is the out-of-area power of node nd at time t, L Bus (nd,t) represents the node load of node nd at time t; Lim(ln) represents the upper capacity limit of line ln; NP Gen (nd,t) represents the power output of node nd at time t, which conforms to the following expression:

[0067]

[0068] In the formula, List NodeGen (nd,i) represents the corresponding relationship between node nd and unit i, P(i,t) is the output of unit i at time t; if List NodeGen (nd,i)=1, it means that unit i is on node nd. If List NodeGen (nd,i)=0, which means that unit i is not on node nd.

[0069] Preferably, the section limit redundancy identification module performs forward section constraint and reverse section constraint identification on the sections that must not exceed the limit and the sections that must exceed the limit respectively, and the sections in pending state are the sections remaining after deducting the sections that must not exceed the limit and the sections that must exceed the limit from all sections.

[0070] Preferably, the section limit redundancy identification module performs positive section constraint identification on the section that must not exceed the limit as follows:

[0071] For units whose start / stop status is shutdown, the output is set to 0;

[0072] For the unit i whose start / stop status is on:

[0073] If Sens PTDF (i,ln,t)>0, the unit output is assumed to be the maximum technical output P max (i, t), as the worst extreme case where the unit output reaches the maximum, which aggravates the blockage of the section;

[0074] If Sens PTDF (i,ln,t)≤0, the unit output is assumed to be the minimum technical output P min (i, t), as the extreme case where the unit output contribution to alleviate the blockage of the section is the smallest;

[0075] Substituting the above extreme output conditions into the expression of section limit constraints, we can obtain the section flow under extreme conditions:

[0076]

[0077] Among them, i represents the set of units with positive sensitivity, and j represents the set of units with negative sensitivity; if the section flow Flow(ln) in extreme cases is less than or equal to Lim(ln), the section is identified as a section that must not exceed the limit.

[0078] Preferably, the section limit redundancy identification module performs reverse section constraint identification on the section that must not exceed the limit as follows:

[0079] For units whose start / stop status is shutdown, the output is set to 0;

[0080] For the unit i whose start / stop status is on:

[0081] If Sens PTDF (i,ln,t)>0, the unit output is assumed to be the minimum technical output P min (i, t), as the worst extreme case where the unit output reaches the maximum, which aggravates the blockage of the section;

[0082] If Sens PTDF(i,ln,t)≤0, the unit output is assumed to be the maximum technical output P max (i, t), as the extreme case where the unit output contribution to alleviate the blockage of the section is the smallest;

[0083] Substituting the above extreme output conditions into the expression of section limit constraints, we can obtain the section flow under extreme conditions:

[0084]

[0085] Among them, i represents the set of units with positive sensitivity, and j represents the set of units with negative sensitivity; if the section flow Flow(ln) in the above extreme case is greater than or equal to -Lim(ln), the section is identified as a section that must not exceed the limit.

[0086] Preferably, the section limit redundancy identification module performs positive section constraint identification on the limit-crossing section as follows:

[0087] For units whose start / stop status is shutdown, the output is set to 0;

[0088] For the unit i whose start / stop status is on:

[0089] If Sens PTDF (i,ln,t)>0, the unit output is assumed to be the minimum technical output P min (i, t), as the optimal extreme case where the unit output is minimized to aggravate the blockage of the section;

[0090] If Sens PTDF (i,ln,t)≤0, the unit output is assumed to be the maximum technical output P max (i, t), as the optimal extreme case where the unit output reaches the maximum to alleviate the blockage of the section;

[0091] Substituting the above extreme output conditions into the expression of section limit constraints, we can obtain the section flow under extreme conditions:

[0092]

[0093] Among them, i represents the set of units with positive sensitivity, and j represents the set of units with negative sensitivity; if the section flow Flow(ln)>Lim(ln) in extreme cases, the section is identified as a limit-crossing section.

[0094] Preferably, the section limit redundancy identification module performs reverse section constraint identification on the must-cross-limit section as follows:

[0095] For units whose start / stop status is shutdown, the output is set to 0;

[0096] For the unit i whose start / stop status is on:

[0097] If Sens PTDF (i,ln,t)>0, the unit output is assumed to be the maximum technical output P max (i, t), as the worst extreme case where the unit output reaches the maximum, which aggravates the blockage of the section;

[0098] If Sens PTDF (i,ln,t)≤0, the unit output is assumed to be the minimum technical output P min (i, t), as the extreme case where the unit output contribution to alleviate the blockage of the section is the smallest;

[0099] Substituting the above extreme output conditions into the expression of section limit constraints, we can obtain the section flow under extreme conditions:

[0100]

[0101] Among them, i represents the set of units with positive sensitivity, and j represents the set of units with negative sensitivity. If the section flow Flow(ln)<-Lim(ln) in the above extreme case, the section is identified as a limit-crossing section.

[0102] Preferably, the redundant variables and constraints to be identified by the matrix operation redundancy identification module include constant variables, zero variables, non-pole variables, redundant non-zero elements of the coefficient matrix, empty rows or columns, proportional columns, proportional rows and individual columns.

[0103] According to a third aspect, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the safety-constrained economic dispatch linear programming preprocessing method according to the first aspect is implemented.

[0104] Compared with the prior art, the first aspect of the present invention has at least the following beneficial effects:

[0105] The existing commercial solvers have preprocessing functions before solving linear programming problems, mainly including: identification of constant variables, zero variables, non-pole variables, redundant non-zero elements, identification and processing of empty rows or empty columns, proportional columns, proportional rows, etc., to achieve the identification and simplification of redundant variables and redundant constraints. The preprocessing technology in the existing commercial solvers is a general preprocessing technology for linear programming problems. From the perspective of mathematical operations, redundant constraints and redundant variables are identified and processed through matrix operations. It is impossible to effectively utilize the physical meaning of large-scale safety-constrained economic scheduling problems to perform more effective and in-depth model simplification preprocessing. The "black box" characteristics of commercial software are also unable to make adaptive improvements and performance improvements for spot market businesses. The present invention combines the physical meaning of safety-constrained economic scheduling problems to preprocess linear programming problems. Compared with the existing optimization engine that only performs redundant constraint identification and dimensionality reduction processing from the matrix operation level, the present invention has the advantage of customized performance improvement for specific problems, which can improve the solution efficiency to a greater extent. The preprocessing method proposed in this invention can eliminate the technical safety risks faced by power grid dispatch optimization operation analysis and power spot market operation, and provide technical support for ensuring the safe, stable and economic operation of the power grid. Designing the underlying linear programming engine, developing a safety-constrained economic dispatch engine and applying it in a real-time power market for verification will help realize customized power system economic dispatch software and power market operation software.

[0106] It can be understood that the beneficial effects of the second to third aspects mentioned above can be found in the relevant description of the first aspect mentioned above, and will not be repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0107] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0108] Figure 1 Flow chart of a safety-constrained economic dispatch linear programming preprocessing method according to embodiment 1 of the present invention;

[0109] Figure 2 A structural block diagram of a safety-constrained economic dispatch linear programming preprocessing system according to embodiment 2 of the present invention. DETAILED DESCRIPTION

[0110] In the following description, for the purpose of illustration rather than limitation, specific details such as specific system structures, technologies, etc. are proposed so as to thoroughly understand the embodiments of the present application. However, it should be clear to those skilled in the art that the present application can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits and methods are omitted to prevent unnecessary details from hindering the description of the present application. In addition, in the description of the present application specification and the attached claims, the terms "first", "second", "third", etc. are only used to distinguish descriptions and cannot be interpreted as indicating or implying relative importance.

[0111] Example 1

[0112] See also Figure 1 The embodiment of the present invention provides a linear programming preprocessing method for safety-constrained economic dispatch. Aiming at the characteristics of large-scale safety-constrained economic dispatch, the invention proposes corresponding constraint and decision variable limit validity verification, cross-section redundant constraint identification, decision variable and constraint dimension reduction, special constraint transformation and other technologies to preprocess the large-scale safety-constrained economic dispatch problem before solving it, thereby reducing the variables and constraint scale of the optimization problem, simplifying the complexity of solving the optimization problem, and making the subsequent solution process more efficient. The linear programming preprocessing method for safety-constrained economic dispatch specifically includes:

[0113] S1, Identify the legality of constraints and decision variables, so that conflicting constraints and illegal values ​​do not participate in safety-constrained economic scheduling;

[0114] S2. Parameterized processing of the output variables of the units in shutdown state, so that the shutdown units do not participate in the safety-constrained economic dispatch;

[0115] S3, identification of redundant constraints on section limits, by dividing the sections into sections that must not exceed the limit, sections that must exceed the limit, and sections in pending state, and identifying the sections that must not exceed the limit as redundant constraints, so that the sections that must not exceed the limit do not participate in safety constraint economic dispatch;

[0116] S4. Redundant variables and constraints are identified based on matrix operations, so that redundant variables and constraints do not participate in safety-constrained economic scheduling.

[0117] In one embodiment, step S1 combines the physical meaning of the safety-constrained economic dispatch problem, and by carrying out the constraints and the legality of the decision-making power limit, the conflicting relationship, etc. in advance, the infeasibility of the optimization problem is pre-judged before solving the optimization clearing model, and the conflicting constraints and illegal values ​​are found. On the one hand, time is no longer wasted on solving unsolvable models, and on the other hand, error alarms are issued for conflicting constraints and illegal values ​​to prompt clearing personnel.

[0118] Step S2 performs parameterization processing on the output variables of the shutdown units. The safe economic dispatch is to determine the active output plan of the startup units when the startup and shutdown states of the units are known. Since the startup and shutdown states are known, the shutdown units do not need to participate in the optimization calculation of the safe economic dispatch to reduce the scale of problem solving. The parameterization processing of step S2 includes:

[0119] The output optimization variables of the shutdown units are treated as non-optimized variables, and the optimized output value is fixed to 0;

[0120] Alternatively, the output of the shutdown unit is increased by the following constraint set to optimize the output result of the shutdown unit with an output of 0:

[0121]

[0122] In the formula, p i They represent the upper and lower limits of the output power of generator set i respectively.

[0123] The identification of redundant constraints of section limits described in step S3 is realized based on the limit method. In the safety-constrained economic dispatch optimization model, network security constraints involve a large number of mutually coupled constraints between sections and units, between sections and sections, and between time. Therefore, the network security constraint set is usually the most critical constraint set that affects the solution of the safety-constrained economic dispatch problem. Since the safety margin has been considered in the planning and design of the power grid, and due to power grid planning and urban development, some lines may never experience transmission congestion. In addition, there are some lines. When the line is blocked, there must be one or more lines that are blocked. For both types of lines, the scale of model constraints can be reduced by preprocessing. Therefore, most of the time, such constraints are ineffective constraints. By pre-identifying the redundant section constraints before solving, the complexity of the coupling nesting relationship of the section limit constraints is minimized to improve the calculation efficiency.

[0124] The expression of section limit constraint is as follows:

[0125]

[0126] Where, Sens PTDF (nd,ln,t) represents the sensitivity transfer factor of node nd to line ln at time t, P Gen (nd,t) is the output of the power generation resource of node nd at time t, P Bus (nd,t) is the load of node nd at time t, P tie (nd,t) is the out-of-area power of node nd at time t, L Bus(nd,t) represents the node load of node nd at time t; Lim(ln) represents the upper capacity limit of line ln; NP Gen (nd,t) represents the power output of node nd at time t, which conforms to the following expression:

[0127]

[0128] In the formula, List NodeGen (nd,i) represents the corresponding relationship between node nd and unit i, P(i,t) is the output of unit i at time t; if List NodeGen (nd,i)=1, it means that unit i is on node nd. If List NodeGen (nd,i)=0, which means that unit i is not on node nd.

[0129] The factors affecting whether a section exceeds the limit are analyzed based on the DC power flow method. In the real-time market clearing model, the electricity consumption of users on the load side is not optimizable; the power of inter-provincial interconnection lines is the result of inter-provincial market clearing or inter-provincial planning, and its interconnection line power is not optimizable; the output of non-fixed output units is the optimization variable of the optimization clearing model, which needs to be optimized according to the unit quotation, system balance and reserve requirements, unit operation characteristics requirements, and power grid safety requirements. Therefore, in the real-time market optimization clearing model, the factors affecting whether a section exceeds the limit are mainly the unit output.

[0130] If the sensitivity factor Sens of unit i to section ln at time t is PTDF If (i,ln,t) is positive, it means that the increase in the output of the unit will aggravate the forward blockage of the section; conversely, if the sensitivity factor Sens of unit i to section ln at time t is PTDF If (i,ln,t) is a negative value, it means that increasing the output of the unit will alleviate the forward blockage of the section.

[0131] Based on the above analysis, combined with the idea of ​​limit analysis, before solving the optimization clearing problem, the sections are divided into: sections that must not exceed the limit, sections that must exceed the limit, and sections in pending state based on the influence of the unit output on the section flow. In the optimization clearing, considering that the sections that must not exceed the limit are redundant constraints and will not contribute to the blocking component of the node marginal electricity price, the constraints of the sections that must not exceed the limit are identified as redundant constraints and are no longer added to the optimization clearing model.

[0132] In the step S3 of dividing the section into the section that must not be crossed, the section that must be crossed and the section in pending state, the section that must not be crossed and the section that must be crossed are respectively identified with positive section constraints and reverse section constraints, and the section in pending state is the section remaining after deducting the section that must not be crossed and the section that must be crossed from all sections.

[0133] Furthermore, the method of identifying the positive section constraint without exceeding the limit section is as follows:

[0134] For units whose start / stop status is shutdown, the output is set to 0;

[0135] For the unit i whose start / stop status is on:

[0136] If Sens PTDF (i,ln,t)>0, the unit output is assumed to be the maximum technical output P max (i, t), as the worst extreme case where the unit output reaches the maximum, which aggravates the blockage of the section;

[0137] If Sens PTDF (i,ln,t)≤0, the unit output is assumed to be the minimum technical output P min (i, t), as the extreme case where the unit output contribution to alleviate the blockage of the section is the smallest;

[0138] Substituting the above extreme output conditions into the expression of section limit constraints, we can obtain the section flow under extreme conditions:

[0139]

[0140] Among them, i represents the set of units with positive sensitivity, and j represents the set of units with negative sensitivity; if the section flow Flow(ln) in extreme cases is less than or equal to Lim(ln), it indicates that the extreme conditions of the worst output of the units related to the section will not cause the section to exceed the limit, then the section will be identified as a section that will not exceed the limit.

[0141] Furthermore, the method of identifying the reverse section constraint of the section that must not exceed the limit is as follows:

[0142] For units whose start / stop status is shutdown, the output is set to 0;

[0143] For the unit i whose start / stop status is on:

[0144] If Sens PTDF (i,ln,t)>0, the unit output is assumed to be the minimum technical output P min (i, t), as the worst extreme case where the unit output reaches the maximum, which aggravates the blockage of the section;

[0145] If Sens PTDF (i,ln,t)≤0, the unit output is assumed to be the maximum technical output P max (i, t), as the extreme case where the unit output contribution to alleviate the blockage of the section is the smallest;

[0146] Substituting the above extreme output conditions into the expression of section limit constraints, we can obtain the section flow under extreme conditions:

[0147]

[0148] Among them, i represents the set of units with positive sensitivity, and j represents the set of units with negative sensitivity; if the section flow Flow(ln) in the above extreme conditions is greater than or equal to -Lim(ln), it indicates that the extreme conditions of the worst output of the units related to the section will not cause the section to exceed the limit, then the section will be identified as a section that will not exceed the limit.

[0149] Furthermore, the method of positive section constraint identification for the cross-limit section is as follows:

[0150] For units whose start / stop status is shutdown, the output is set to 0;

[0151] For the unit i whose start / stop status is on:

[0152] If Sens PTDF (i,ln,t)>0, the unit output is assumed to be the minimum technical output P min (i, t), as the optimal extreme case where the unit output is minimized to aggravate the blockage of the section;

[0153] If Sens PTDF (i,ln,t)≤0, the unit output is assumed to be the maximum technical output P max (i, t), as the optimal extreme case where the unit output reaches the maximum to alleviate the blockage of the section;

[0154] Substituting the above extreme output conditions into the expression of section limit constraints, we can obtain the section flow under extreme conditions:

[0155]

[0156] Among them, i represents the set of units with positive sensitivity, and j represents the set of units with negative sensitivity. If the section flow Flow(ln)>Lim(ln) in extreme cases, it means that the extreme conditions of the optimal output of the units related to the section will cause the section to exceed the limit, and the section will be identified as a section that must exceed the limit.

[0157] Furthermore, the method of identifying the reverse section constraint of the cross-limit section is as follows:

[0158] For units whose start / stop status is shutdown, the output is set to 0;

[0159] For the unit i whose start / stop status is on:

[0160] If Sens PTDF (i,ln,t)>0, the unit output is assumed to be the maximum technical output P max (i, t), as the worst extreme case where the unit output reaches the maximum, which aggravates the blockage of the section;

[0161] If Sens PTDF (i,ln,t)≤0, the unit output is assumed to be the minimum technical output P min (i, t), as the extreme case where the unit output contribution to alleviate the blockage of the section is the smallest;

[0162] Substituting the above extreme output conditions into the expression of section limit constraints, we can obtain the section flow under extreme conditions:

[0163]

[0164] Among them, i represents the set of units with positive sensitivity, and j represents the set of units with negative sensitivity. If the section flow Flow(ln)<-Lim(ln) in the above extreme cases, it means that the extreme conditions of the optimal output of the units related to the section will cause the section to exceed the limit, and the section will be identified as a section that must exceed the limit.

[0165] In one embodiment, step S4 identifies and processes the following redundant variables and constraints based on the currently more mature matrix operation processing technology, including but not limited to: constant variables, zero variables, non-pole variables, redundant non-zero elements of the coefficient matrix, empty rows or columns, proportional columns, proportional rows, separate columns, etc.

[0166] The safety-constrained economic dispatch linear programming preprocessing method of the present invention is based on the preprocessing link before solving the large-scale safety-constrained economic dispatch problem. Based on the characteristics of the large-scale safety-constrained economic dispatch problem, it can improve the efficiency of the optimization engine in solving the large-scale safety-constrained economic dispatch problem and achieve accurate and efficient solution of the safety-constrained economic dispatch problem.

[0167] Example 2

[0168] See also Figure 2 The safety-constrained economic dispatch linear programming preprocessing system of the embodiment of the present invention includes:

[0169] The legality identification module 1 is used to identify the legality of constraints and decision variables, find out the conflicting constraints and illegal values ​​in the constraints and decision variables, and make the conflicting constraints and illegal values ​​not participate in the safety constraint economic dispatch;

[0170] The parameterization processing module 2 is used to obtain the output variable of the shutdown state unit and perform parameterization processing on the output variable of the shutdown state unit so that the shutdown unit does not participate in the safety-constrained economic dispatch;

[0171] The section limit redundancy identification module 3 is used to obtain the section limit redundancy constraints and identify the section limit redundancy constraints, divide the section into the section that must not exceed the limit, the section that must exceed the limit and the section in a pending state, and identify the section that must not exceed the limit as a redundant constraint, so that the section that must not exceed the limit does not participate in the safety constraint economic dispatch;

[0172] The matrix operation redundancy identification module 4 is used to identify redundant variables and constraints based on matrix operations, so that the redundant variables and constraints do not participate in the safety constraint economic dispatch.

[0173] In this embodiment, the parameterization processing module 2 processes the output optimization variable of the shutdown state unit as a non-optimized variable, and fixes the optimized output value to 0; or, the output of the shutdown state unit is increased by the following constraint set to optimize the output result of the shutdown unit with an output of 0:

[0174]

[0175] In the formula, p i They represent the upper and lower limits of the output power of generator set i respectively.

[0176] In this embodiment, the cross-section limit redundancy identification module 3 implements cross-section limit redundancy constraint identification based on the limit method. The cross-section limit constraint is expressed as follows:

[0177]

[0178] Where, Sens PTDF (nd,ln,t) represents the sensitivity transfer factor of node nd to line ln at time t, P Gen (nd,t) is the output of the power generation resource of node nd at time t, P Bus (nd,t) is the load of node nd at time t, P tie (nd,t) is the out-of-area power of node nd at time t, L Bus (nd,t) represents the node load of node nd at time t; Lim(ln) represents the upper capacity limit of line ln; NP Gen (nd,t) represents the power output of node nd at time t, which conforms to the following expression:

[0179]

[0180] In the formula, List NodeGen (nd,i) represents the corresponding relationship between node nd and unit i, P(i,t) is the output of unit i at time t; if List NodeGen (nd,i)=1, it means that unit i is on node nd. If ListNodeGen (nd,i)=0, which means that unit i is not on node nd.

[0181] Furthermore, the section limit redundancy identification module 3 of this embodiment performs forward section constraint and reverse section constraint identification on the sections that must not exceed the limit and the sections that must exceed the limit respectively, and the sections in the pending state are the sections remaining after deducting the sections that must not exceed the limit and the sections that must exceed the limit from all sections.

[0182] Furthermore, in this embodiment, the section limit redundancy identification module 3 performs positive section constraint identification on the section that must not exceed the limit as follows:

[0183] For units whose start / stop status is shutdown, the output is set to 0;

[0184] For the unit i whose start / stop status is on:

[0185] If Sens PTDF (i,ln,t)>0, the unit output is assumed to be the maximum technical output P max (i, t), as the worst extreme case where the unit output reaches the maximum, which aggravates the blockage of the section;

[0186] If Sens PTDF (i,ln,t)≤0, the unit output is assumed to be the minimum technical output P min (i, t), as the extreme case where the unit output contribution to alleviate the blockage of the section is the smallest;

[0187] Substituting the above extreme output conditions into the expression of section limit constraints, we can obtain the section flow under extreme conditions:

[0188]

[0189] Among them, i represents the set of units with positive sensitivity, and j represents the set of units with negative sensitivity; if the section flow Flow(ln) in extreme cases is less than or equal to Lim(ln), the section is identified as a section that must not exceed the limit.

[0190] Furthermore, in this embodiment, the section limit redundancy identification module 3 performs reverse section constraint identification on the section that must not exceed the limit as follows:

[0191] For units whose start / stop status is shutdown, the output is set to 0;

[0192] For the unit i whose start / stop status is on:

[0193] If Sens PTDF (i,ln,t)>0, the unit output is assumed to be the minimum technical output P min(i, t), as the worst extreme case where the unit output reaches the maximum, which aggravates the blockage of the section;

[0194] If Sens PTDF (i,ln,t)≤0, the unit output is assumed to be the maximum technical output P max (i, t), as the extreme case where the unit output contribution to alleviate the blockage of the section is the smallest;

[0195] Substituting the above extreme output conditions into the expression of section limit constraints, we can obtain the section flow under extreme conditions:

[0196]

[0197] Among them, i represents the set of units with positive sensitivity, and j represents the set of units with negative sensitivity; if the section flow Flow(ln) in the above extreme case is greater than or equal to -Lim(ln), the section is identified as a section that must not exceed the limit.

[0198] Furthermore, the section limit redundancy identification module 3 of this embodiment performs positive section constraint identification on the must-cross-limit section as follows:

[0199] For units whose start / stop status is shutdown, the output is set to 0;

[0200] For the unit i whose start / stop status is on:

[0201] If Sens PTDF (i,ln,t)>0, the unit output is assumed to be the minimum technical output P min (i, t), as the optimal extreme case where the unit output is minimized to aggravate the blockage of the section;

[0202] If Sens PTDF (i,ln,t)≤0, the unit output is assumed to be the maximum technical output P max (i, t), as the optimal extreme case where the unit output reaches the maximum to alleviate the blockage of the section;

[0203] Substituting the above extreme output conditions into the expression of section limit constraints, we can obtain the section flow under extreme conditions:

[0204]

[0205] Among them, i represents the set of units with positive sensitivity, and j represents the set of units with negative sensitivity; if the section flow Flow(ln)>Lim(ln) in extreme cases, the section is identified as a limit-crossing section.

[0206] Furthermore, in this embodiment, the section limit redundancy identification module 3 performs reverse section constraint identification on the must-cross-limit section as follows:

[0207] For units whose start / stop status is shutdown, the output is set to 0;

[0208] For the unit i whose start / stop status is on:

[0209] If Sens PTDF (i,ln,t)>0, the unit output is assumed to be the maximum technical output P max (i, t), as the worst extreme case where the unit output reaches the maximum, which aggravates the blockage of the section;

[0210] If Sens PTDF (i,ln,t)≤0, the unit output is assumed to be the minimum technical output P min (i, t), as the extreme case where the unit output contribution to alleviate the blockage of the section is the smallest;

[0211] Substituting the above extreme output conditions into the expression of section limit constraints, we can obtain the section flow under extreme conditions:

[0212]

[0213] Among them, i represents the set of units with positive sensitivity, and j represents the set of units with negative sensitivity. If the section flow Flow(ln)<-Lim(ln) in the above extreme case, the section is identified as a limit-crossing section.

[0214] In this embodiment, the redundant variables and constraints to be identified by the matrix operation redundancy identification module 4 include constant variables, zero variables, non-pole variables, redundant non-zero elements of the coefficient matrix, empty rows or columns, proportional columns, proportional rows and separate columns.

[0215] Example 3

[0216] Another embodiment of the present invention further proposes a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the safety-constrained economic scheduling linear programming preprocessing method is implemented. The computer program includes computer program code, which may be in source code form, object code form, executable file or some intermediate form, etc. The computer-readable storage medium may include: any entity or device, medium, USB flash drive, mobile hard disk, disk, optical disk, computer memory, read-only memory, random access memory, electric carrier signal, telecommunication signal and software distribution medium, etc. that can carry the computer program code. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable medium does not include electric carrier signal and telecommunication signal. For the convenience of explanation, the above content only shows the part related to the embodiment of the present invention. For specific technical details not disclosed, please refer to the method part of the embodiment of the present invention. The computer-readable storage medium is non-temporary and can be stored in a storage device formed by various electronic devices, and can implement the execution process recorded in the method of the embodiment of the present invention.

[0217] Those skilled in the art will appreciate 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 code.

[0218] 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 process in the flowchart. 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.

[0219] 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 including 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.

[0220] 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 in the computer or other programmable device. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0221] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A safety-constrained economic dispatch linear programming preprocessing method, characterized in that: include: Identify the legality of constraints and decision variables, find out the conflicting constraints and illegal values ​​in the constraints and decision variables, and make sure that the conflicting constraints and illegal values ​​do not participate in the safety-constrained economic dispatch; The output variables of the units in shutdown state are obtained and parameterized so that the units in shutdown state do not participate in the safety-constrained economic dispatch; Obtaining redundant constraints on section limits and identifying redundant constraints on section limits, dividing the section into sections that must not cross the limit, sections that must cross the limit, and sections in pending states, and identifying the sections that must not cross the limit as redundant constraints, so that the sections that must not cross the limit do not participate in safety-constrained economic dispatch; in the step of dividing the section into sections that must not cross the limit, sections that must cross the limit, and sections in pending states, the sections that must not cross the limit and sections that must cross the limit are respectively identified with forward section constraints and reverse section constraints, and the sections in pending states are the sections remaining after deducting the sections that must not cross the limit and sections that must cross the limit from all sections; Redundant variables and constraints are identified based on matrix operations, so that they do not participate in safety-constrained economic dispatch; In the steps of identifying the legality of constraints and decision variables and finding conflicting constraints and illegal values ​​in constraints and decision variables, combined with the physical meaning of the safety-constrained economic dispatch problem, by carrying out the legality and conflicting relationships of constraints and decision power limits in advance, the infeasibility of the optimization problem is predicted before solving the optimization clearing model, and conflicting constraints and illegal values ​​are found; In the step of parameterizing the output variable of the shutdown state unit, the parameterization includes: The output optimization variables of the shutdown units are treated as non-optimized variables, and the optimized output value is fixed to 0; Alternatively, the output of the shutdown unit is increased by the following constraint set to optimize the output result of the shutdown unit with an output of 0: In the formula, p i Respectively represent the upper and lower limits of the output power of generator set i; The identification of redundant constraints of section limits is implemented based on the limit method, and the expression of section limit constraints is as follows: Where, Sens PTDF (nd,ln,t) represents the sensitivity transfer factor of node nd to line ln at time t, P Gen (nd,t) is the output of the power generation resource of node nd at time t, P Bus (nd,t) is the load of node nd at time t, P tie (nd,t) is the out-of-area power of node nd at time t, L Bus (nd,t) represents the node load of node nd at time t; Lim(ln) represents the upper capacity limit of line ln; NP Gen (nd,t) represents the power output of node nd at time t, which conforms to the following expression: In the formula, List NodeGen (nd,i) represents the corresponding relationship between node nd and unit i, P(i,t) is the output of unit i at time t; if List NodeGen (nd,i)=1, it means that unit i is on node nd. If List NodeGen (nd,i)=0, which means that unit i is not on node nd; In the step of identifying redundant variables and constraints based on matrix operations, the redundant variables and constraints include constant variables, zero variables, non-pole variables, redundant non-zero elements of the coefficient matrix, empty rows or columns, proportional columns, proportional rows, and individual columns.

2. The safety-constrained economic dispatch linear programming preprocessing method according to claim 1 is characterized in that: The method of identifying the positive section constraint of the section that must not exceed the limit is as follows: For units whose start / stop status is shutdown, the output is set to 0; For the unit i whose start / stop status is on: If Sens PTDF (i,ln,t)>0, the unit output is assumed to be the maximum technical output P max (i, t), the worst extreme case where the unit output reaches the maximum, which aggravates the blockage of the section; If Sens PTDF (i,ln,t)≤0, the unit output is assumed to be the minimum technical output P min (i, t), as the extreme case where the unit output contribution to alleviate the blockage of the section is the smallest; Substituting the above extreme output conditions into the expression of section limit constraints, we can obtain the section flow under extreme conditions: Among them, i represents the set of units with positive sensitivity, and j represents the set of units with negative sensitivity; if the section flow Flow(ln) in extreme cases is less than or equal to Lim(ln), the section is identified as a section that must not exceed the limit.

3. The safety-constrained economic dispatch linear programming preprocessing method according to claim 1 is characterized in that: The method of identifying the reverse section constraint of the must-not-cross-limit section is as follows: For units whose start / stop status is shutdown, the output is set to 0; For the unit i whose start / stop status is on: If Sens PTDF (i,ln,t)>0, the unit output is assumed to be the minimum technical output P min (i, t), the worst extreme case where the unit output reaches the maximum, which aggravates the blockage of the section; If Sens PTDF (i,ln,t)≤0, the unit output is assumed to be the maximum technical output P max (i, t), as the extreme case where the unit output contribution to alleviate the blockage of the section is the smallest; Substituting the above extreme output conditions into the expression of section limit constraints, we can obtain the section flow under extreme conditions: Among them, i represents the set of units with positive sensitivity, and j represents the set of units with negative sensitivity; if the section flow Flow(ln) in the above extreme case is greater than or equal to -Lim(ln), the section is identified as a section that must not exceed the limit.

4. The safety-constrained economic dispatch linear programming preprocessing method according to claim 1 is characterized in that: The method of identifying the positive section constraint of the must-cross section is as follows: For units whose start / stop status is shutdown, the output is set to 0; For the unit i whose start / stop status is on: If Sens PTDF (i,ln,t)>0, the unit output is assumed to be the minimum technical output P min (i, t), as the optimal extreme case where the unit output is minimized to aggravate the blockage of the section; If Sens PTDF (i,ln,t)≤0, the unit output is assumed to be the maximum technical output P max (i, t), as the optimal extreme case where the unit output reaches the maximum to alleviate the blockage of the section; Substituting the above extreme output conditions into the expression of section limit constraints, we can obtain the section flow under extreme conditions: Among them, i represents the set of units with positive sensitivity, and j represents the set of units with negative sensitivity; if the section flow Flow(ln)>Lim(ln) in extreme cases, the section is identified as a limit-crossing section.

5. The safety-constrained economic dispatch linear programming preprocessing method according to claim 1 is characterized in that: The method of identifying the reverse section constraint of the must-cross-limit section is as follows: For units whose start / stop status is shutdown, the output is set to 0; For the unit i whose start / stop status is on: If Sens PTDF (i,ln,t)>0, the unit output is assumed to be the maximum technical output P max (i, t), the worst extreme case where the unit output reaches the maximum, which aggravates the blockage of the section; If Sens PTDF (i,ln,t)≤0, the unit output is assumed to be the minimum technical output P min (i, t), as the extreme case where the unit output contribution to alleviate the blockage of the section is the smallest; Substituting the above extreme output conditions into the expression of section limit constraints, we can obtain the section flow under extreme conditions: Among them, i represents the set of units with positive sensitivity, and j represents the set of units with negative sensitivity. If the section flow Flow(ln)<-Lim(ln) in the above extreme case, the section is identified as a limit-crossing section.

6. A safety-constrained economic dispatch linear programming preprocessing system, characterized in that: include: A legality identification module is used to identify the legality of constraints and decision variables, find conflicting constraints and illegal values ​​in constraints and decision variables, and prevent conflicting constraints and illegal values ​​from participating in safety-constrained economic dispatch; in the steps of identifying the legality of constraints and decision variables and finding conflicting constraints and illegal values ​​in constraints and decision variables, combined with the physical meaning of the safety-constrained economic dispatch problem, by carrying out the legality and conflicting relationships of constraints and decision power limits in advance, the infeasibility of the optimization problem is prejudged before solving the optimization clearing model, and conflicting constraints and illegal values ​​are found; The parameterization processing module is used to obtain the output variable of the shutdown state unit and perform parameterization processing on the output variable of the shutdown state unit so that the shutdown unit does not participate in the safety constraint economic dispatch; the parameterization processing module processes the output optimization variable of the shutdown state unit as a non-optimized variable and fixes the optimized output value to 0; or, the output of the shutdown state unit adds the following constraint set to optimize the output result of the shutdown unit with an output of 0: In the formula, p i Respectively represent the upper and lower limits of the output power of generator set i; The section limit redundancy identification module is used to obtain the section limit redundancy constraints and identify the section limit redundancy constraints, divide the section into the section that must not exceed the limit, the section that must exceed the limit and the section in pending state, and identify the section that must not exceed the limit as a redundant constraint, so that the section that must not exceed the limit does not participate in the safety constraint economic dispatch; the section limit redundancy identification module performs forward section constraint and reverse section constraint identification on the section that must not exceed the limit and the section that must exceed the limit respectively, and the section in pending state is the section remaining after deducting the section that must not exceed the limit and the section that must exceed the limit from all sections; the section limit redundancy identification module realizes the section limit redundancy constraint identification based on the limit method, and the expression of the section limit constraint is as follows: Where, Sens PTDF (nd,ln,t) represents the sensitivity transfer factor of node nd to line ln at time t, P Gen (nd,t) is the output of the power generation resource of node nd at time t, P Bus (nd,t) is the load of node nd at time t, P tie (nd,t) is the out-of-area power of node nd at time t, L Bus (nd,t) represents the node load of node nd at time t; Lim(ln) represents the upper capacity limit of line ln; NP Gen (nd,t) represents the power output of node nd at time t, which conforms to the following expression: In the formula, List NodeGen (nd,i) represents the corresponding relationship between node nd and unit i, P(i,t) is the output of unit i at time t; if List NodeGen (nd,i)=1, it means that unit i is on node nd. If List NodeGen (nd,i)=0, which means that unit i is not on node nd; A matrix operation redundancy identification module is used to identify redundant variables and constraints based on matrix operations, so that the redundant variables and constraints do not participate in safety-constrained economic scheduling; the redundant variables and constraints to be identified by the matrix operation redundancy identification module include constant variables, zero variables, non-pole variables, redundant non-zero elements of the coefficient matrix, empty rows or empty columns, proportional columns, proportional rows and separate columns.

7. The safety-constrained economic dispatch linear programming preprocessing system according to claim 6 is characterized by: The section limit redundancy identification module performs positive section constraint identification on the section that must not exceed the limit as follows: For units whose start / stop status is shutdown, the output is set to 0; For the unit i whose start / stop status is on: If Sens PTDF (i,ln,t)>0, the unit output is assumed to be the maximum technical output P max (i, t), the worst extreme case where the unit output reaches the maximum, which aggravates the blockage of the section; If Sens PTDF (i,ln,t)≤0, the unit output is assumed to be the minimum technical output P min (i, t), as the extreme case where the unit output contribution to alleviate the blockage of the section is the smallest; Substituting the above extreme output conditions into the expression of section limit constraints, we can obtain the section flow under extreme conditions: Among them, i represents the set of units with positive sensitivity, and j represents the set of units with negative sensitivity; if the section flow Flow(ln) in extreme cases is less than or equal to Lim(ln), the section is identified as a section that must not exceed the limit.

8. The safety-constrained economic dispatch linear programming preprocessing system according to claim 6 is characterized by: The section limit redundancy identification module performs reverse section constraint identification on the section that must not exceed the limit as follows: For units whose start / stop status is shutdown, the output is set to 0; For the unit i whose start / stop status is on: If Sens PTDF (i,ln,t)>0, the unit output is assumed to be the minimum technical output P min (i, t), the worst extreme case where the unit output reaches the maximum, which aggravates the blockage of the section; If Sens PTDF (i,ln,t)≤0, the unit output is assumed to be the maximum technical output P max (i, t), as the extreme case where the unit output contribution to alleviate the blockage of the section is the smallest; Substituting the above extreme output conditions into the expression of section limit constraints, we can obtain the section flow under extreme conditions: Among them, i represents the set of units with positive sensitivity, and j represents the set of units with negative sensitivity; if the section flow Flow(ln) in the above extreme case is greater than or equal to -Lim(ln), the section is identified as a section that must not exceed the limit.

9. The safety-constrained economic dispatch linear programming preprocessing system according to claim 6, characterized in that: The section limit redundancy identification module performs positive section constraint identification on the limit-crossing section as follows: For units whose start / stop status is shutdown, the output is set to 0; For the unit i whose start / stop status is on: If Sens PTDF (i,ln,t)>0, the unit output is assumed to be the minimum technical output P min (i, t), as the optimal extreme case where the unit output is minimized to aggravate the blockage of the section; If Sens PTDF (i,ln,t)≤0, the unit output is assumed to be the maximum technical output P max (i, t), as the optimal extreme case where the unit output reaches the maximum to alleviate the blockage of the section; Substituting the above extreme output conditions into the expression of section limit constraints, we can obtain the section flow under extreme conditions: Among them, i represents the set of units with positive sensitivity, and j represents the set of units with negative sensitivity; if the section flow Flow(ln)>Lim(ln) in extreme cases, the section is identified as a limit-crossing section.

10. The safety-constrained economic dispatch linear programming preprocessing system according to claim 6, characterized in that: The section limit redundancy identification module performs reverse section constraint identification on the limit-crossing section as follows: For units whose start / stop status is shutdown, the output is set to 0; For the unit i whose start / stop status is on: If Sens PTDF (i,ln,t)>0, the unit output is assumed to be the maximum technical output P max (i, t), the worst extreme case where the unit output reaches the maximum, which aggravates the blockage of the section; If Sens PTDF (i,ln,t)≤0, the unit output is assumed to be the minimum technical output P min (i, t), as the extreme case where the unit output contribution to alleviate the blockage of the section is the smallest; Substituting the above extreme output conditions into the expression of section limit constraints, we can obtain the section flow under extreme conditions: Among them, i represents the set of units with positive sensitivity, and j represents the set of units with negative sensitivity. If the section flow Flow(ln)<-Lim(ln) in the above extreme case, the section is identified as a limit-crossing section.

11. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the safety-constrained economic dispatch linear programming preprocessing method as described in any one of claims 1 to 5 is implemented.

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