A security constrained unit commitment method and system

Abstract

The application discloses a security constrained unit commitment method and system, comprising: obtaining the number of units, the capacity of units, the system reserve capacity, and the dispatchable load in a target system, and selecting one or more as a decision variable; bringing the decision variable into a pre-constructed security constrained unit commitment model to solve, and obtaining a dynamic adjustment value of a transmission section limit; the security constrained unit commitment model is constructed based on a stable limit dynamic constraint. The application enables the model to dynamically adjust the transmission section limit according to the random unit commitment change.

Description

Technical Field

[0001] This invention relates to the field of power grid dispatching, and specifically to a method and system for combining units with safety constraints. Background Technology

[0002] With the comprehensive rollout of the Smart Grid Dispatch Technology Support System (D5000) across the State Grid Corporation of China, Security-Constrained Economic Dispatch (SCED) technology has become a core supporting technology for provincial power grid dispatch planning. Security-Constrained Unit Combination (SCUC) technology has also seen initial application. SCUC technology is one of the core technologies supporting generation planning and electricity spot market clearing. The thermal stability limits of power grid branches and the dynamic stability limits of transmission sections are important components of the security-constrained unit combination constraint model. Since SCUC and SCED are core technologies for generation planning and the electricity spot market, they are of great significance for improving power grid operation security, achieving energy conservation and emission reduction, and enhancing the level of refined management of dispatch planning.

[0003] Current SCUC research has achieved significant breakthroughs in model construction and rapid solution of large-scale systems through various methods such as model description improvement, new algorithms, system dimensionality reduction, and decomposition coordination. To address the stochastic issues brought about by large-scale wind and solar grid integration, robust methods, interval and fuzzy algorithms are employed to enhance the adaptability of deterministic unit combination results to external stochasticity. While existing methods address the branch and transmission section power limit constraints required for unit combination and economic dispatch, their processing methods are not perfect. This is mainly reflected in the fact that transmission section power limits are stability limits based on grid operation modes, which depend on many factors such as system grid structure, load levels, start-up methods, and positive and negative reserve capacity. In this context, the power grid structure, given the known outage plans for transmission and transformation equipment, can be considered a known, definite quantity. The unit combination results directly affect the unit start-up mode and positive and negative reserve capacity, thus different start-up modes will influence the power limit of the transmission section. On the other hand, if load dispatch is considered, the load demand changes from a definite load forecast value to a decision variable that needs to consider the optimization results of dispatchable load, which can also affect the transmission section limit. Therefore, when constructing a safety-constrained unit combination model using the transmission section power limit as a known value, only conservative section limits can be selected to avoid the safety risks caused by changes in the limit due to mode adjustments. Summary of the Invention

[0004] To address the aforementioned shortcomings in existing technologies, this invention provides a safety-constrained unit combination method and system. The technical solution provided by this invention incorporates the impact of factors such as the number of operating units, operating capacity, reserve capacity, and load level on grid mode limits into the unit combination model, constructing a safety-constrained unit combination model that takes into account dynamic adjustment of stability limits.

[0005] This invention provides a method for combining safety-constrained generator units, comprising:

[0006] Obtain the number of units in operation, operating capacity, system reserve capacity, and dispatchable load in the target system, and select one or more as decision variables;

[0007] The decision variables are substituted into a pre-built safety-constrained unit combination model for solution to obtain the dynamic adjustment value of the transmission section limit;

[0008] The safety-constrained unit combination model is constructed based on dynamic constraints of stability limits.

[0009] Preferably, the construction of the safety-constrained unit combination model includes:

[0010] Based on the optimization objective of minimizing the sum of the unit's start-up cost, operating cost, and dispatch compensation cost of the dispatchable load within the scheduling cycle, an objective function is constructed.

[0011] Construct conventional constraints and dynamic constraints with stable limits for the objective function;

[0012] The conventional constraints include system balance constraints, system reserve constraints, unit operation constraints, unit start-up and shutdown time constraints, dispatchable load operation constraints, and branch / section limit constraints.

[0013] Preferably, the objective function is as follows:

[0014]

[0015] Where: T is the total time period within the scheduling cycle; I is the total number of generating units; D is the total number of dispatchable loads; S i,t Let p be the state of unit i in time period t, and p be the decision variable. i,t Let p be the output value of unit i in time period t, and let p be the decision variable. d,t Let U(p) be the dispatchable load d during time period t, and let U(p) be the decision variable. i,t F(p) represents the operating cost of unit i during time period t; i,t F(p) represents the operating cost of unit i during time period t. d,t ) represents the cost of scheduling load d for time period t.

[0016] Preferably, the dynamic constraint of the stability limit is as shown in the following formula:

[0017]

[0018] Where: M m,n R is the nth limit value determined by the method for section m; m,r,tR is the expression for the r-th dependent variable affecting the limit of section m at time t. m,r,n The upper limit of the range of values ​​for the dependent variable expression; R m,r,n+1 This represents the lower limit of the range of values ​​for the dependent variable expression.

[0019] Preferably, the expression R of the r-th dependent variable of the influencing section m at time t is... m,r,t As shown in the following formula:

[0020]

[0021] In the formula: S i,t p represents the state of unit i during time period t; i,t p represents the output value of unit i during time period t; d,t The dispatchable output of the dispatchable load d during time period t.

[0022] Preferably, the expression R of the r-th dependent variable of the influencing section m at time t is... m,r,t Satisfy the following formula:

[0023]

[0024] In the formula: y m,r,n For the expression of the m-th boundary and the r-th dependent variable, and y m,r,n ∈ Variable matrix Y m,r,n .

[0025] Preferably, the variable matrix Y m,r,n Let m be a two-dimensional matrix with all elements being 0-1 variables, where m represents the matrix for the m-th "dynamic" boundary, r represents that the dynamic boundary is determined by r dependent variable expressions, and n represents that the r-th dependent variable expression divides the "dynamic" limit into n segments.

[0026] Preferably, the step of substituting the decision variables into a pre-constructed safety-constrained unit combination model for solution to obtain the dynamic adjustment value of the transmission section limit includes:

[0027] By using CPLEX software to solve the safety-constrained unit combination model, the dynamic adjustment value of the transmission section limit is obtained.

[0028] Based on the same inventive concept, the present invention also provides a safety constraint unit combination system, comprising:

[0029] The selection module is used to obtain the number of units in operation, operating capacity, system reserve capacity, and dispatchable load of units in the target system, and select one or more as decision variables;

[0030] The solution module is used to input the decision variables into a pre-built safety-constrained unit combination model for solution, and obtain the dynamic adjustment value of the transmission section limit;

[0031] The safety-constrained unit combination model is constructed based on dynamic constraints of stability limits.

[0032] Preferably, the system further includes a construction module, which is specifically used for:

[0033] Based on the optimization objective of minimizing the sum of the unit's start-up cost, operating cost, and dispatch compensation cost of the dispatchable load within the scheduling cycle, an objective function is constructed.

[0034] Construct conventional constraints and dynamic constraints with stable limits for the objective function;

[0035] The conventional constraints include system balance constraints, system reserve constraints, unit operation constraints, unit start-up and shutdown time constraints, dispatchable load operation constraints, and branch / section limit constraints.

[0036] Compared with the closest existing technology, the technical solution provided by the present invention has the following beneficial effects:

[0037] The technical solution provided by this invention obtains the number of operating units, operating capacity, system reserve capacity, and dispatchable load of units in the target system, and selects one or more as decision variables; the decision variables are then substituted into a pre-constructed safety-constrained unit combination model for solution to obtain the dynamic adjustment value of the transmission section limit. The safety-constrained unit combination model in this invention is constructed based on the dynamic constraint of stable limit, therefore, the model considers the dynamic adjustment of the section limit due to the random combination change after the mode adjustment, thus improving the safety performance of the system. Attached Figure Description

[0038] Figure 1 This is a flowchart of a safety-constrained unit combination method according to the present invention;

[0039] Figure 2 This is a schematic diagram comparing the output of Unit 1 under different methods in an embodiment of the present invention;

[0040] Figure 3 This is a schematic diagram of the dispatchable load output curve in an embodiment of the present invention;

[0041] Figure 4 This is a schematic diagram showing the output comparison of Unit 1 after increasing the load in an embodiment of the present invention. Detailed Implementation

[0042] To better understand this invention, the following description, in conjunction with the accompanying drawings and examples, will further illustrate the invention.

[0043] This invention incorporates the impact of factors such as the number of operating units, operating capacity, reserve capacity, and load level on mode limits into the unit combination model, constructs a safety-constrained unit combination model that takes into account dynamic adjustment of stability limits, and proposes a complex logical constraint processing strategy that couples decision variables.

[0044] like Figure 1 As shown, the present invention provides a method for combining safety-constrained units, comprising:

[0045] Step S1: Obtain the number of units in operation, operating capacity, system reserve capacity, and dispatchable load in the target system, and select one or more as decision variables;

[0046] Step S2: Substitute the decision variables into the pre-built safety constraint unit combination model for solution to obtain the dynamic adjustment value of the transmission section limit;

[0047] The safety-constrained unit combination model is constructed based on dynamic constraints of stability limits.

[0048] right Figure 1 The construction of the safety-constrained unit combination model of the safety-constrained unit combination method shown in the figure will be analyzed in detail. The construction steps include:

[0049] Step 1: Develop optimization goals.

[0050] The optimization objective of unit combination is to minimize the sum of unit start-up costs, operating costs, and dispatchable load compensation costs within the scheduling cycle. The objective function is:

[0051]

[0052] In the formula, T is the total time period within the planning period; I is the total number of generating units; D is the total dispatchable load; S i,t Let p represent the state of unit i during time period t, and let p be the decision variable (1 indicates unit is running, 0 indicates unit is shut down); i,t Let p be the output value of unit i in time period t, and let p be the decision variable. d,t Let U(p) be the dispatchable load d during time period t, and let U(p) be the decision variable. i,t F(p) represents the operating cost of unit i during time period t; i,t F(p) represents the operating cost of unit i during time period t. d,t The cost of scheduling load d during time period t is the compensation cost for its dispatch.

[0053] F(p i,t The cost is typically described using a quadratic function as follows:

[0054]

[0055] In the formula, a, b, and c are characteristic values ​​of the quadratic function, and their specific values ​​are related to the characteristics of the unit. To solve the model using mixed-integer programming, the operating costs are typically piecewise linearized.

[0056] The dispatchable load considered in this invention is based on normal load demand, with subsidies used to increase or decrease load demand. In this invention, subsidy costs are calculated based on the absolute value of the response amount, regardless of whether the demand is increased or decreased.

[0057] F(p d,t The cost is described using a piecewise function as follows:

[0058]

[0059] In the formula, p d,max The maximum adjustable load for the dispatchable load is L, where L is the total number of segments; △p d,t The value for each segment after segmentation; ψ d,l β is a 0-1 variable, representing the indicator that the schedulable load d is in segment l; d,l The dispatch compensation cost that can be obtained when the dispatchable load d output is in segment l.

[0060] Step 2: Construct regular constraints.

[0061] (1) System equilibrium constraints.

[0062]

[0063] In the formula: P load,t Let P be the total system demand at time t; y,t Let P be the predicted system load at time t, which is a known quantity. dz,t To increase the dispatchable load power, it will increase the total load demand of the system. dj,t To reduce the power of the dispatchable load, it will decrease the total load demand of the system.

[0064] (2) System backup constraints.

[0065]

[0066] In the formula, P i,max P i,min P represents the upper and lower limits of unit i; i,up,rev For the system's positive and backup requirements; P i,dn,rev This represents the system's negative backup requirement. Backup provided by dispatchable load is not considered at this time.

[0067] (3) Unit operation constraints.

[0068] This includes constraints on unit output limits, unit ramp-up constraints, and maximum number of unit start-stop cycles.

[0069] In the formula, P i,up P i,down For the ramp-up and ramp-down limits of unit i. SN i This represents the maximum number of start-stop cycles for unit i.

[0070] (4) Time constraints for unit start-up and shutdown.

[0071]

[0072] In the formula: K i,on K represents the minimum operating time requirement for unit i; i,off This represents the minimum downtime requirement for unit i. This represents the duration during which unit i has been in operation or has been out of service.

[0073] (5) Scheduled load operation constraints.

[0074] This includes constraints on the output limit of dispatchable load and constraints on the ramp-up of dispatchable load.

[0075]

[0076] In the formula: P d,max P i,min P represents the upper and lower limits for adjusting the dispatchable load d; d,up P d,down The ramp-up and ramp-down limits for the dispatchable load d.

[0077] (6) Branch road / section quota constraints.

[0078] The power flow calculation model uses the DC power flow method. The branch thermal stability limit constraints are shown below.

[0079]

[0080] In the formula, l z,t For branch z, the current flow at time t; z,max λ is the upper limit of thermal stability for branch l; i,z,t λ represents the active power sensitivity of unit i to branch z at time t; d,z,t P represents the active power sensitivity of the dispatchable load d to branch z at time t. bus,z,t The power flow contribution of all conventional bus loads to this branch at time t.

[0081] The quota constraints for cross-section methods are shown below.

[0082]

[0083] In the formula, M m,tLet M be the active power flow at section m at time t. m,t,max Let z be the mode limit value for section m at time t. z∈m represents the branch configuration of section m.

[0084] Step 3: Construct dynamic constraints for stable quotas.

[0085] In the traditional SCUC model, M m,t,max For a known value that is determined, the present invention will use M m,t,max Defined as a "dynamic" boundary, it is associated with decision variables such as unit start-up, output, and dispatchable load.

[0086] The dependent variable expression is defined as follows:

[0087]

[0088] In the formula, R m,r,t The expression for the r-th dependent variable affecting the limit of section m at time t can be the number of operating units, operating capacity, system reserve, system load level, etc. The "dynamic" boundary M m,t,max Through R m,r,t It is expressed as follows:

[0089]

[0090] In the formula, M m,n Let R be the nth limit value determined by the method for section m, and let R be a known quantity. m,r,n R m,r,n+1 These are the upper and lower limits of the range of values ​​for the dependent variable expression, and are known quantities. If M m,t,max It is determined by multiple dependent variable expressions, so multiple expressions (12) can be directly written.

[0091] Step 4: Solve the problem of dynamic limits changing with decision-making volume.

[0092] Traditional unit combination models, after segmenting and linearizing the start-up cost and generation cost curves, can be converted into mixed integer programming models, and therefore can be solved using mature commercial software CPLEX. This invention introduces dynamic adjustment of the stability limit, so R in equation (12)... m,r,t For the expression of decision variables, R is undeterminable before the decision variables are solved. m,r,t The range of values ​​is limited, so although equation (12) can intuitively represent the physical meaning, it cannot be directly translated to form a model that satisfies the characteristics of mixed integer programming. Here, the present invention modifies the model by introducing 0-1 "positioning" variables.

[0093] Define a 0-1 “positioning” variable matrix Y m,r,nThe matrix is ​​a two-dimensional matrix with all elements being 0-1 variables, where m represents the matrix for the m-th "dynamic" boundary, r represents that the dynamic boundary is determined by r dependent variable expressions, and n represents that the r-th dependent variable expression divides the "dynamic" limit into n segments.

[0094] Now, we select the r-th dependent variable expression for modification. First, the "dynamic" limit is represented as follows:

[0095]

[0096] In the formula, y m,r,n For the m-th "dynamic" boundary, the r-th dependent variable expression, and the n-th segment's 0-1 "positioning" variable. Equation (13) represents the "dynamic" boundary M. m,t,max It can only be in one of the n segments.

[0097] Secondly, the dependent variable expression is as follows:

[0098]

[0099] Because y m,r,n Since there is only one variable, the model of equation (12) can be constructed by combining equations (13) and (14), and it satisfies the characteristics of mixed integer programming model, which can be solved directly using commercial software.

[0100] This invention addresses the problem that traditional mixed-integer programming methods cannot solve unit combination problems that consider dynamic adjustment of stability limits by introducing 0-1 "positioning" variables to modify the model.

[0101] Step 5: Solve the model using CPLEX software to complete the system construction. In this embodiment, to test the effectiveness of the model proposed in this invention, the proposed method is applied to the New England 10-unit 39-node standard case and a provincial power grid in China; this verification requires adjustments to the 10-unit 39-node case. The adjustment method is as follows: Unit 1, originally connected to node BUS39, is changed to be connected to BUS39 through a transmission section (the original system becomes 9 units and 1 externally connected unit). The limit of this transmission section method is shown in Table 2; two dispatchable loads are connected to BUS4 and BUS18, and the operating parameters of the dispatchable loads are shown in Table 3.

[0102] Table 2. Limits for Transmission Section Types

[0103]

[0104] Table 3. Scheduled Load Information

[0105]

[0106] For this example, comparative tests were conducted: 1) without considering transmission section limits; 2) considering transmission section limits, using conservative limits; 3) considering transmission section limits, with limits dynamically adjusted according to operating capacity; 4) considering transmission section limits, with limits dynamically adjusted according to operating capacity and reserve capacity; 5) considering transmission section limits, with limits dynamically adjusted according to operating capacity and reserve capacity, and considering the reduction of output from dispatchable load. The optimal system values ​​for these scenarios are shown in Table 4, and the corresponding output of Unit 1 is as follows: Figure 2 As shown, the corresponding dispatchable load conditions output is as follows: Figure 3 As shown in Table 4, after the dynamic adjustment of the quota, the economic efficiency can be improved by 1.55% by releasing the output space of economic units. Considering the reduction of output of dispatchable load, the economic efficiency can be improved by 1.59% by reducing peak load demand.

[0107] Table 4. Optimal values ​​for different scenarios

[0108]

[0109]

[0110] For this example, Comparative Test 2 was conducted: Based on Scenario 4 of Comparative Test 1, the impact of load level on the limit was considered. Since increasing the load always negatively affects the total cost, the cost of Unit 1 was adjusted. For every additional MWh of electricity generated by Unit 1, the cost was reduced by $30. The output curve of Unit 1 at this time is as follows: Figure 4 As shown in the figure, although the external conditions of the dispatchable load test 2 are the same as those of test 1 (scenario 4), the increased cost reduction of unit 1's output, through the start-up and shutdown of other units, allows unit 1 to maintain a high output throughout the day. Considering the release of the section limit due to the increased load, the additional 50MW output of dispatchable load 1 in time period 12 can further increase the output of unit 1 by 40MW during peak hours.

[0111] Therefore, the above verification demonstrates the effectiveness of the method proposed in this invention. It also proves that by dynamically adjusting the stable limit, network limits can be further released, improving the economic efficiency of power grid operation and the utilization efficiency of transmission and transformation equipment.

[0112] When constructing a safety constraint unit combination model that takes into account dynamic adjustment of stability limits, this invention incorporates the impact of operating capacity, number of operating units, load level, and reserve capacity on the limits into the model.

[0113] The technical solution provided by this invention addresses the issue that the boundary conditions of constraints in the model vary with the decision variables, a feature not addressed in traditional unit combination models. Therefore, this invention proposes a strategy for handling complex logical constraints involving the coupling of decision variables. During the solution process, by entering a 0-1 "positioning" variable matrix, the complex logical constraints involving the coupling of decision variables can be transformed into a mixed-integer programming model, allowing for the use of mature commercial software for model solving.

[0114] Example 2

[0115] Based on the same inventive concept, the present invention also provides a safety constraint unit combination system, comprising:

[0116] The selection module is used to obtain the number of units in operation, operating capacity, system reserve capacity, and dispatchable load of units in the target system, and select one or more as decision variables;

[0117] The solution module is used to input the decision variables into a pre-built safety-constrained unit combination model for solution, and obtain the dynamic adjustment value of the transmission section limit;

[0118] The safety-constrained unit combination model is constructed based on dynamic constraints of stability limits.

[0119] In this embodiment, the system further includes a construction module, which is specifically used for:

[0120] Based on the optimization objective of minimizing the sum of the unit's start-up cost, operating cost, and dispatch compensation cost of the dispatchable load within the scheduling cycle, an objective function is constructed.

[0121] Construct conventional constraints and dynamic constraints with stable limits for the objective function;

[0122] The conventional constraints include system balance constraints, system reserve constraints, unit operation constraints, unit start-up and shutdown time constraints, dispatchable load operation constraints, and branch / section limit constraints.

[0123] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied 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.

[0124] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0125] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0126] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0127] The above are merely embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention are included within the scope of the claims of the present invention pending approval.

Claims

1. A method for combining safety-constrained generator units, characterized in that, include: Obtain the number of units in operation, operating capacity, system reserve capacity, and dispatchable load in the target system, and select one or more as decision variables; The decision variables are substituted into a pre-built safety-constrained unit combination model for solution to obtain the dynamic adjustment value of the transmission section limit; The safety-constrained unit combination model is constructed based on dynamic constraints of stability limits; The construction of the safety-constrained unit combination model includes: Based on the optimization objective of minimizing the sum of the unit's start-up cost, operating cost, and dispatch compensation cost of the dispatchable load within the scheduling cycle, an objective function is constructed. Construct conventional constraints and dynamic constraints with stable limits for the objective function; The conventional constraints include system balance constraints, system reserve constraints, unit operation constraints, unit start-up and shutdown time constraints, dispatchable load operation constraints, and branch / section limit constraints. The dynamic constraint of the stability limit is shown in the following formula: Where: M m,n R is the nth limit value determined by the method for section m; m,r,t R is the expression for the r-th dependent variable affecting the limit of section m at time t. m,r,n The upper limit of the range of values ​​for the dependent variable expression; R m,r,n+1 This represents the lower limit of the range of values ​​for the dependent variable expression.

2. The method as described in claim 1, characterized in that, The objective function is shown in the following equation: Where: T is the total time period within the scheduling cycle; I is the total number of generating units; D is the total number of dispatchable loads; S i,t Let p be the state of unit i in time period t, and p be the decision variable. i,t Let p be the output value of unit i in time period t, and let p be the decision variable. d,t Let U(p) be the dispatchable load d during time period t, and let U(p) be the decision variable. i,t F(p) represents the operating cost of unit i during time period t; i,t F(p) represents the operating cost of unit i during time period t. d,t ) represents the cost of scheduling load d for time period t.

3. The method as described in claim 1, characterized in that, The expression R of the r-th dependent variable of the influencing section m at time t is... m,r,t As shown in the following formula: In the formula: S i,t p represents the state of unit i during time period t; i,t p represents the output value of unit i during time period t; d,t The dispatchable output of the dispatchable load d during time period t.

4. The method as described in claim 3, characterized in that, The expression R of the r-th dependent variable of the influencing section m at time t is... m,r,t Satisfy the following formula: In the formula: y m,r,n For the expression of the m-th boundary and the r-th dependent variable, and y m,r,n ∈ Variable matrix Y m,r,n .

5. The method as described in claim 4, characterized in that, The variable matrix Y m,r,n Let m be a two-dimensional matrix with all elements being 0-1 variables, where m represents the matrix for the m-th "dynamic" boundary, r represents that the dynamic boundary is determined by r dependent variable expressions, and n represents that the r-th dependent variable expression divides the "dynamic" limit into n limit values.

6. The method as described in claim 5, characterized in that, The step of substituting the decision variables into a pre-built safety-constrained unit combination model for solution to obtain the dynamic adjustment value of the transmission section limit includes: By using CPLEX software to solve the safety-constrained unit combination model, the dynamic adjustment value of the transmission section limit is obtained.

7. A safety-constrained unit combination system, characterized in that, include: The selection module is used to obtain the number of units in operation, operating capacity, system reserve capacity, and dispatchable load of units in the target system, and select one or more as decision variables; The solution module is used to input the decision variables into a pre-built safety-constrained unit combination model for solution, and obtain the dynamic adjustment value of the transmission section limit; The safety-constrained unit combination model is constructed based on dynamic constraints of stability limits; The system further includes a construction module, which is specifically used for: Based on the optimization objective of minimizing the sum of the unit's start-up cost, operating cost, and dispatch compensation cost of the dispatchable load within the scheduling cycle, an objective function is constructed. Construct conventional constraints and dynamic constraints with stable limits for the objective function; The conventional constraints include system balance constraints, system reserve constraints, unit operation constraints, unit start-up and shutdown time constraints, dispatchable load operation constraints, and branch / section limit constraints. The dynamic constraint of the stability limit is shown in the following formula: Where: M m,n R is the nth limit value determined by the method for section m; m,r,t R is the expression for the r-th dependent variable affecting the limit of section m at time t. m,r,n The upper limit of the range of values ​​for the dependent variable expression; R m,r,n+1 This represents the lower limit of the range of values ​​for the dependent variable expression.

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