A power generation scheduling plan stability control method, system, device and medium

Abstract

The application discloses a power generation scheduling plan stability control method, system, device and medium, the method comprises the following steps: obtaining the operation boundary data of a target power grid and the original output penalty curve of each generator unit, so as to obtain the flat penalty segment data corresponding to each generator unit respectively; obtaining the distribution characteristic coefficient of each generator unit according to the flat penalty segment data and a preset output distribution algorithm; obtaining the step penalty value corresponding to each output value in the flat penalty segment data according to the distribution characteristic coefficient and the original output penalty curve; updating the original output penalty curve according to the step penalty value and the output value, so as to obtain the optimized output penalty curve; inputting the operation boundary data and the optimized output penalty curve of each generator unit into a pre-constructed power scheduling plan optimization model, so as to obtain the active power output value of each generator unit in a scheduling period, and the stability of power grid operation is improved.

Description

Technical Field

[0001] This invention relates to the field of generator output control technology, specifically to a method, system, equipment, and medium for controlling the stability of power generation dispatching plans. Background Technology

[0002] With the expansion of power dispatch plans to cover different regions, operations research and optimization calculations aimed at minimizing the overall grid's power generation operation penalty, while meeting safety constraints, have become an important research direction for power dispatch. This involves scheduling power generation for each power plant throughout the day. In actual grid output control, scenarios exist where clean energy consumption is difficult. In such cases, multiple unit output allocation schemes can all meet the minimum power generation operation penalty requirements, leading to an infinite number of optimal solutions for the solver. This results in a longer control timeline. As the timeline lengthens, the power generation dispatch calculation results begin to oscillate randomly, which deteriorates unit operating conditions and the safety and stability characteristics of the power system.

[0003] To address the uncertainty in power output allocation caused by multiple optimal solutions, existing technologies mainly employ schemes such as average power output allocation, allocation based on the proportion of medium- and long-term settlement electricity, and multi-level target sequential optimization clearing for power output control. However, in the average power output allocation scheme, units with different actual generation costs receive the same power output allocation, increasing the overall generation cost and being unfair to low-cost units, violating the incentive compatibility principle. The scheme of allocating power output based on the proportion of medium- and long-term settlement electricity employs a two-round clearing method, ignoring the short-term marginal cost of units, resulting in poor flexibility. It may not be able to adapt to rapid changes in the safety boundary conditions of grid dispatching and operation, and there is a risk that market participants may manipulate medium- and long-term contracts to influence power output allocation.

[0004] Finally, the multi-level objective sequential optimization clearing control method establishes multi-level clearing optimization objectives based on market resource allocation objectives. The optimal objective function value of the previous level serves as the operational constraint for the clearing model of the next level, and clearing optimization is carried out sequentially for different levels of objectives. This method has high model complexity and low computational efficiency; the selection, weighting, and priority of multi-level objectives are relatively subjective and opaque, leading to a decrease in the understanding and trust of power generation entities in the results of power generation planning. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention discloses a method, system, equipment, and medium for controlling the stability of power generation dispatching plans, used to reduce the output oscillation of generator sets and improve the operational stability of the power grid.

[0006] To achieve the above objectives, in a first aspect, the present invention discloses a method for controlling the stability of a power generation dispatch plan, comprising: The system acquires the operating boundary data of the target power grid and the original output penalty curve of each generator set, and obtains the flat penalty segment data corresponding to each generator set based on the original output penalty curve; wherein, the flat penalty segment data includes multiple output values ​​corresponding to the same original power generation penalty value; Based on the flat penalty segment data and the preset power distribution algorithm, obtain the distribution characteristic coefficients corresponding to each generator set; Based on the allocation characteristic coefficient and the original power output penalty curve, each original power generation penalty value in the flat penalty segment data is incremented stepwise to obtain the step penalty value corresponding to each power output value in the flat penalty segment data. The original output penalty curve is updated based on the stepped penalty value and the output value to obtain the optimized output penalty curve corresponding to each generator set. The operating boundary data and the optimized output penalty curve of each generator set are input into the pre-constructed power dispatch plan optimization model. The model is solved with the goal of minimizing the generation penalty value of the target power grid, so as to obtain the active power output value of each generator set in the dispatch cycle.

[0007] This invention discloses a power generation dispatch plan stability control method. The method acquires the target power grid's operational boundary data and the original output penalty curve for each generator unit. Based on the original output penalty curve, it obtains the flat penalty segment data corresponding to each generator unit. Then, based on the flat penalty segment data and a preset output allocation algorithm, it obtains the allocation characteristic coefficient corresponding to each generator unit. Next, based on the allocation characteristic coefficient and the original output penalty curve, it increments the original power generation penalty value in the flat penalty segment data stepwise to obtain the step penalty value corresponding to each output value in the flat penalty segment data. Then, it updates the original output penalty curve based on the step penalty value and the output value to obtain the optimized output penalty curve corresponding to each generator unit. Finally, it inputs the operational boundary data and the optimized output penalty curve of each generator unit into a pre-constructed power dispatch plan optimization model, and solves the model with the objective of minimizing the power generation penalty value of the target power grid to obtain the active power output value of each generator unit within the dispatch cycle. In summary, the method disclosed in this invention transforms the original flat penalty segment into a stepped increasing penalty value sequence through the above processing, resulting in an optimized output penalty curve with deterministic gradient and strict convexity. This eliminates random oscillations caused by multiple optimal solutions in power dispatching plans, makes the output plan unique and stable, and improves the stability of power grid operation.

[0008] As a preferred example, the step of acquiring the operating boundary data of the target power grid and the original output penalty curve of each generator unit, and acquiring the flat penalty segment data corresponding to each generator unit based on the original output penalty curve, includes: For any generator set, obtain the original output penalty curve of the generator set; wherein, the original output penalty curve includes multiple output segments; each output segment includes an initial output value, an end output value and a constant penalty value corresponding to the output segment; Traverse each of the output segments in the original output penalty curve, and identify several consecutive output segments in which the constant penalty value remains unchanged as flat penalty segments; For any given flat penalty segment, the starting output value, ending output value, segment length, and the same constant penalty value of the flat penalty segment are obtained as the flat penalty segment data of the flat penalty segment.

[0009] The above scheme, for any generator set, obtains the original output penalty curve of the generator set. This curve includes multiple output segments, each of which includes an initial output value, an ending output value, and a corresponding constant penalty value. It then iterates through each output segment in the original output penalty curve, identifying several consecutive output segments with unchanged constant penalty values ​​as flat penalty segments. For any flat penalty segment, it obtains the starting output value, ending output value, segment length, and the same constant penalty value for that flat penalty segment, using these as the flat penalty segment data. Through this process, output segment data with constant and continuous penalty values ​​are extracted from the original output penalty curve, resulting in a structured set of flat penalty segment parameters. This enables precise positioning of output segments requiring stepped modification, avoids unnecessary processing of non-flat segments, and improves data preprocessing efficiency.

[0010] As a preferred example, the step of obtaining the allocation characteristic coefficients corresponding to each generator set based on the flat penalty segment data and the preset power allocation algorithm includes: Obtain multiple generator sets with the same constant penalty value from the target power grid, and obtain the flat penalty segment data corresponding to each generator set; The output distribution ratio between each generator set is determined based on the length of the segment. Based on the power distribution ratio, the distribution characteristic coefficients corresponding to each generator set are matched so that when multiple generator sets have the same constant penalty value, the product of the power output value of each generator set and its corresponding distribution characteristic coefficient is equal.

[0011] The above scheme obtains multiple generator sets with the same constant penalty value from the target power grid, and acquires the flat penalty segment data corresponding to each generator set; determines the output allocation ratio between each generator set based on the segment length; and matches the allocation characteristic coefficient corresponding to each generator set based on this output allocation ratio, so that when multiple generator sets have the same constant penalty value, the product of the output value of each generator set and its corresponding allocation characteristic coefficient is equal. Through the above processing, the preset output allocation principle (such as proportional allocation according to segment length, allocation according to capacity, or allocation according to regulation rate) is quantified into allocation characteristic coefficients, obtaining parameters that can be embedded in the step penalty value construction process, thereby achieving the technical effect that the final solved output plan spontaneously meets the fair allocation requirements without secondary optimization or manual intervention.

[0012] As a preferred example, the step of progressively increasing each original power generation penalty value in the flat penalty segment data according to the allocation characteristic coefficient and the original power output penalty curve to obtain the progressive penalty value corresponding to each power output value in the flat penalty segment data includes: For any flat penalty section of any generator set, the flat penalty section is uniformly subdivided into multiple sub-output sections; wherein each sub-output section corresponds to several output values; Obtain the constant penalty value of the next output segment adjacent to the flat penalty segment from the original output penalty curve corresponding to the generator set; Obtain the difference between the constant penalty value of the next output segment and the constant penalty value of the flat penalty segment; Based on the distribution characteristic coefficient of the generator set and the difference, the penalty value step size corresponding to the flat penalty segment is determined; wherein, the product of the penalty value step size and the number of sub-output segments is less than or equal to the difference; Based on the output values ​​in ascending order, determine the penalty value step size corresponding to each sub-output segment, and use the product of the penalty value step size and the penalty value step size as the penalty value increment corresponding to each sub-output segment. The constant penalty value of the flat penalty segment and the sum of the penalty value increments are used as the step penalty value corresponding to each of the output values.

[0013] The above scheme, for any flat penalty segment of any generator set, uniformly subdivides the flat penalty segment into multiple sub-output segments, each sub-output segment corresponding to several output values; obtains the constant penalty value of the next output segment adjacent to the flat penalty segment from the original output penalty curve corresponding to the generator set; obtains the difference between the constant penalty value of the next output segment and the constant penalty value of the flat penalty segment; determines the penalty value step size corresponding to the flat penalty segment based on the distribution characteristic coefficient of the generator set and the difference, wherein the product of the penalty value step size and the number of sub-output segments is less than or equal to the difference; determines the penalty value step size number corresponding to each sub-output segment according to the order of output values ​​from smallest to largest, and uses the product of the penalty value step size number and the penalty value step size as the penalty value increment corresponding to each sub-output segment; the sum of the constant penalty value and the penalty value increment of the flat penalty segment is used as the step penalty value corresponding to each output value. Through the above processing, while maintaining the monotonous and non-decreasing characteristics of the original penalty curve, the flat penalty segment is transformed into a strictly increasing stepped penalty sequence, resulting in stepped penalty value data with deterministic gradients and constrained by the penalty difference between adjacent segments. This achieves the technical effect of making the optimization objective function strictly convex, guiding the solver to converge to the unique optimal solution, and ensuring that the transformation does not destroy the original penalty stepped structure.

[0014] As a preferred example, updating the original output penalty curve based on the stepped penalty value and the output value to obtain the optimized output penalty curve for each generator set includes: For any flat penalty segment of each generator set, the constant penalty value of the flat penalty segment is replaced with the step penalty value corresponding to each output value to obtain the step penalty segment corresponding to the flat penalty segment. The original output penalty curve of each generator set is updated according to the stepped penalty segment to obtain the optimized output penalty curve corresponding to each generator set.

[0015] The above scheme replaces the constant penalty value of any flat penalty segment for each generator unit with the stepped penalty value corresponding to each output value, thus obtaining the stepped penalty segment corresponding to that flat penalty segment. The original output penalty curve of each generator unit is then updated based on the stepped penalty segment, resulting in the optimized output penalty curve for each generator unit. Through this process, the flat portion of the original piecewise constant curve is replaced with multiple progressively increasing sub-segments, which are then concatenated with the unmodified output segments in output order. This yields a complete optimized output penalty curve from minimum to maximum output, which can be directly input into existing optimization models. This achieves a zero-intrusion modification of the original scheduling plan optimization model, eliminating multi-solution oscillations without modifying the model's internal algorithm.

[0016] As a preferred example, the operating boundary data includes the total grid load value for each time period within the scheduling cycle and the constraints corresponding to the target grid. The step of inputting the operating boundary data and the optimized output penalty curve of each generator unit into a pre-constructed power dispatch plan optimization model, and solving the model with the objective of minimizing the generation penalty value of the target power grid, yields the active power output value of each generator unit within the dispatch cycle, including: The active power output of each generator set in each time period within the scheduling cycle is used as a decision variable. The optimized output penalty curve of each generator set is used as the penalty coefficient corresponding to the active power output value; Based on the decision variables and the penalty coefficients, an objective function is constructed with the goal of minimizing the generation penalty value of the target power grid. The objective function, the total load value of the power grid, and the constraints are input into a preset power dispatch plan optimization model, and linear programming is performed to obtain the active power output value of each generator unit in each time period within the dispatch cycle.

[0017] The above scheme uses operational boundary data including the total grid load value for each time period within the scheduling cycle and the corresponding constraints of the target grid. The active power output value of each generator unit in each time period within the scheduling cycle is used as the decision variable, and the optimized output penalty curve of each generator unit is used as the penalty coefficient corresponding to the active power output value. Based on the decision variables and penalty coefficients, an objective function is constructed with the goal of minimizing the generation penalty value of the target grid. The objective function, the total grid load value, and the constraints are input into a preset power dispatch plan optimization model for linear programming solution, yielding the active power output value of each generator unit in each time period within the scheduling cycle. Through the above processing, under the combined effect of power balance constraints, output upper and lower limit constraints, ramping constraints, and network security constraints, linear programming solution is performed using the modified objective function with strict convexity to obtain unique output plan data that satisfies security constraints. This achieves the technical effects of smoothing the output plan with load changes across different time periods, eliminating random jumps, and improving the operational stability of the power system.

[0018] In a second aspect, the present invention discloses a power generation dispatch plan stability control system, including a flat penalty module, a power output allocation module, a stepped penalty module, a penalty optimization module, and a power output control module; The flat penalty module is used to acquire the operating boundary data of the target power grid and the original output penalty curve of each generator set, and to acquire the flat penalty segment data corresponding to each generator set according to the original output penalty curve; wherein, the flat penalty segment data includes multiple output values ​​corresponding to the same original power generation penalty value; The power distribution module is used to obtain the distribution characteristic coefficients corresponding to each generator set based on the flat penalty segment data and the preset power distribution algorithm. The stepped penalty module is used to incrementally increase each of the original power generation penalty values ​​in the flat penalty segment data according to the allocation characteristic coefficient and the original power output penalty curve, so as to obtain the stepped penalty value corresponding to each of the power output values ​​in the flat penalty segment data. The penalty optimization module is used to update the original output penalty curve according to the stepped penalty value and the output value, so as to obtain the optimized output penalty curve corresponding to each generator set. The output control module is used to input the operating boundary data and the optimized output penalty curve of each generator set into a pre-built power dispatch plan optimization model, and solve the problem with the goal of minimizing the generation penalty value of the target power grid, so as to obtain the active power output value of each generator set in the dispatch cycle.

[0019] This invention discloses a power generation dispatch plan stability control system. It acquires the operating boundary data of the target power grid and the original output penalty curve of each generator unit, and obtains the flat penalty segment data corresponding to each generator unit based on the original output penalty curve. Then, it obtains the allocation characteristic coefficient corresponding to each generator unit based on the flat penalty segment data and a preset output allocation algorithm. Next, based on the allocation characteristic coefficient and the original output penalty curve, it increments each original power generation penalty value in the flat penalty segment data stepwise to obtain the step penalty value corresponding to each output value in the flat penalty segment data. Then, it updates the original output penalty curve based on the step penalty value and the output value to obtain the optimized output penalty curve corresponding to each generator unit. Finally, it inputs the operating boundary data and the optimized output penalty curve of each generator unit into a pre-constructed power dispatch plan optimization model, and solves the problem with the objective of minimizing the power generation penalty value of the target power grid to obtain the active power output value of each generator unit within the dispatch cycle. In summary, the method disclosed in this invention transforms the original flat penalty segment into a stepped increasing penalty value sequence through the above processing, resulting in an optimized output penalty curve with deterministic gradient and strict convexity. This eliminates random oscillations caused by multiple optimal solutions in power dispatching plans, makes the output plan unique and stable, and improves the stability of power grid operation.

[0020] As a preferred example, the flatness penalty module includes a curve division unit, a curve traversal unit, and a curve recognition unit; The curve division unit is used to obtain the original output penalty curve of any generator set; wherein, the original output penalty curve includes multiple output segments; each output segment includes an initial output value, an end output value and a constant penalty value corresponding to the output segment; The curve traversal unit is used to traverse each of the output segments in the original output penalty curve and identify several consecutive output segments in which the constant penalty value remains unchanged as flat penalty segments. The curve recognition unit is used to obtain the starting output value, ending output value, segment length, and the same constant penalty value of the flat penalty segment for any given flat penalty segment, as the flat penalty segment data of the flat penalty segment.

[0021] The above scheme, for any generator set, obtains the original output penalty curve of the generator set. This curve includes multiple output segments, each of which includes an initial output value, an ending output value, and a corresponding constant penalty value. It then iterates through each output segment in the original output penalty curve, identifying several consecutive output segments with unchanged constant penalty values ​​as flat penalty segments. For any flat penalty segment, it obtains the starting output value, ending output value, segment length, and the same constant penalty value for that flat penalty segment, using these as the flat penalty segment data. Through this process, output segment data with constant and continuous penalty values ​​are extracted from the original output penalty curve, resulting in a structured set of flat penalty segment parameters. This enables precise positioning of output segments requiring stepped modification, avoids unnecessary processing of non-flat segments, and improves data preprocessing efficiency.

[0022] Thirdly, the present invention discloses a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements a power generation dispatch plan stability control method as described in any of the first aspects.

[0023] Fourthly, the present invention discloses a computer-readable storage medium comprising: a stored computer program, wherein, when the computer program is executed, the device in which the computer-readable storage medium is located is controlled to perform a power generation dispatch plan stability control method as described in any of the first aspects. Attached Figure Description

[0024] To more clearly illustrate the technical solution of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0025] Figure 1 This is a flowchart illustrating a power generation dispatch plan stability control method disclosed in an embodiment of the present invention; Figure 2This is a schematic diagram of an original power generation penalty curve disclosed in an embodiment of the present invention; Figure 3 This is a schematic diagram of a linearized power generation penalty curve disclosed in an embodiment of the present invention; Figure 4 This is a schematic diagram of a stepped incremental power generation penalty curve disclosed in an embodiment of the present invention; Figure 5 This is a test comparison diagram disclosed in an embodiment of the present invention; Figure 6 This is a schematic diagram of the structure of a power generation dispatching plan stability control system disclosed in an embodiment of the present invention. Detailed Implementation

[0026] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0027] See Figure 1 To address the technical problem of random oscillations in generator output control in existing technologies, which affect the stability of power grid operation, this embodiment discloses a power generation dispatch plan stability control method, including: Step 101: Obtain the operating boundary data of the target power grid and the original output penalty curve of each generator set, and obtain the flat penalty segment data corresponding to each generator set according to the original output penalty curve; wherein, the flat penalty segment data includes multiple output values ​​corresponding to the same original power generation penalty value.

[0028] Step 102: Based on the flat penalty segment data and the preset power distribution algorithm, obtain the distribution characteristic coefficients corresponding to each generator set.

[0029] Step 103: Based on the allocation characteristic coefficient and the original output penalty curve, each original power generation penalty value in the flat penalty segment data is incremented stepwise to obtain the step penalty value corresponding to each output value in the flat penalty segment data.

[0030] Step 104: Update the original output penalty curve according to the stepped penalty value and the output value to obtain the optimized output penalty curve corresponding to each generator set.

[0031] Step 105: Input the operating boundary data and the optimized output penalty curve of each generator set into the pre-constructed power dispatch plan optimization model, and solve the problem with the goal of minimizing the generation penalty value of the target power grid to obtain the active power output value of each generator set in the dispatch cycle.

[0032] In this embodiment, the target power grid refers to the power grid area for power dispatch plan optimization calculation; the operational boundary data refers to the boundary conditions required for power dispatch optimization, including system load forecast, network topology, equipment status, line / section transmission limits, unit output upper and lower limits, ramp rate, etc.; the original output penalty curve refers to a piecewise constant curve with unit output value on the x-axis and generation penalty value on the y-axis, with each segment corresponding to a constant penalty value; the flat penalty segment data refers to the data corresponding to the continuous output segment in the original output penalty curve where the penalty value remains unchanged, including the starting output value, ending output value, segment length, and the uniform constant penalty value of the segment (i.e., the original generation penalty value), while multiple output values ​​refer to the various output values ​​from the beginning to the end within the flat penalty segment; the preset output allocation algorithm determines the allocation of power when multiple units have the same original penalty value. The principle of power allocation ratio is used to obtain the allocation characteristic coefficient, which is a positive coefficient determined for each unit according to the algorithm, so that the product of the output value of each unit and its coefficient is equal; the step-by-step increase refers to increasing the constant original penalty value in the flat penalty segment by a fixed step size in order of output from small to large, forming a step penalty value (the new penalty value corresponding to each sub-output segment); the optimized output penalty curve refers to the complete piecewise constant curve formed by replacing the flat penalty segment in the original curve with the step penalty value and splicing it with the unmodified segment; the power dispatch plan optimization model refers to a linear programming model with the goal of minimizing the total power generation penalty of the whole network and satisfying constraints such as power balance, output upper and lower limits, ramping, and network security; the dispatch cycle is usually one day (24 hours) and divided into multiple time periods; the final active power output value is the planned active power of each generator unit in each time period.

[0033] In this embodiment, step 101 includes: Step 1011: For any generator set, obtain the original output penalty curve of the generator set; wherein, the original output penalty curve includes multiple output segments; each output segment includes an initial output value, an end output value and a constant penalty value corresponding to the output segment.

[0034] Step 1012: Traverse each of the output segments in the original output penalty curve, and identify several consecutive output segments in which the constant penalty value remains unchanged as flat penalty segments; Step 1013: For any of the flat penalty segments, obtain the starting output value, ending output value, segment length, and the same constant penalty value of the flat penalty segment as the flat penalty segment data.

[0035] In this embodiment, for any given generator set, the original output penalty curve of that generator set is obtained. For example, the original output penalty curve is as follows: Figure 2 As shown, the horizontal axis represents the output power from smallest to largest; the vertical axis represents the generation penalty. Specifically, the original segmented output penalty curve reported by each generator unit is read from the data platform of the power dispatch center or the market reporting system. The original output penalty curve consists of multiple continuous and non-overlapping output segments, each of which includes an initial output value, an ending output value, and a constant penalty value corresponding to that output segment.

[0036] Next, each output segment in the original output penalty curve is traversed, and several consecutive output segments with the constant penalty value remaining unchanged are identified as flat penalty segments. When there are multiple consecutive output segments with the same constant penalty value, these output segments are merged and identified as a flat penalty segment.

[0037] Then, for any flat penalty segment, the starting output value, ending output value, segment length, and the same constant penalty value of the flat penalty segment are obtained as the flat penalty segment data. Taking the first segment of a certain unit as an example, the starting output value is 0 MW, the ending output value is 100 MW, the segment length is 100 MW, and the constant penalty value is 0 yuan / MWh.

[0038] For any given generator set, the above implementation method obtains the original output penalty curve of the generator set. This curve includes multiple output segments, each of which includes an initial output value, an ending output value, and a corresponding constant penalty value. It then iterates through each output segment in the original output penalty curve, identifying several consecutive output segments with unchanged constant penalty values ​​as flat penalty segments. For any flat penalty segment, it obtains the initial output value, ending output value, segment length, and the same constant penalty value for that flat penalty segment, using these as the flat penalty segment data. Through this process, output segment data with constant and continuous penalty values ​​are extracted from the original output penalty curve, resulting in a structured flat penalty segment parameter set. This enables precise positioning of output segments requiring stepped modification, avoids unnecessary processing of non-flat segments, and improves data preprocessing efficiency.

[0039] In this embodiment, step 102 includes: Step 1021: Obtain multiple generator sets with the same constant penalty value from the target power grid, and obtain the flat penalty segment data corresponding to each generator set; Step 1022: Determine the output distribution ratio between each generator set based on the segment length; Step 1023: Based on the power distribution ratio, match the distribution characteristic coefficient corresponding to each generator set so that when multiple generator sets have the same constant penalty value, the product of the power output value of each generator set and its corresponding distribution characteristic coefficient is equal.

[0040] In this embodiment, based on the specific requirements of power generation plan calculation, the principle of output allocation for each unit when the power generation penalty value is consistent is clarified. This principle will serve as the basic framework for subsequent power generation penalty value modification and power generation plan value oscillation suppression. Regarding the penalty value... Given m identical generating units, let P be the output vector of these units in this penalty cost segment. The allocation principle can be derived from a diagonal characteristic matrix A = (in >0 indicates that the requirement is: ( ) That is, all components of AP are equal, which is equivalent to the existence of a constant such that AP = H*1; where, the 1 is a vector consisting entirely of 1s.

[0041] Diagonal elements of characteristic matrix A Different allocation principles (such as based on unit capacity, regulation rate, etc.) can be set to flexibly achieve various allocation objectives. In this embodiment, the allocation principle is based on the fair consumption of clean energy, which requires that each unit call up an equal number of new subdivided output segments in the original 0 power generation penalty segment.

[0042] Based on the aforementioned flat penalty segment data and the preset power allocation algorithm, the allocation characteristic coefficients corresponding to each generator set are obtained. Specifically, multiple generator sets with the same constant penalty value are obtained from the target power grid, and the flat penalty segment data corresponding to each generator set is obtained; the power allocation ratio between each generator set is determined according to the segment length; based on the power allocation ratio, the allocation characteristic coefficients corresponding to each generator set are matched so that when multiple generator sets have the same constant penalty value, the product of the power output value of each generator set and its corresponding allocation characteristic coefficient is equal.

[0043] Taking a scenario where clean energy consumption is difficult as an example, assume that the power generation penalty value of multiple clean energy units is all zero. If the principle for allocation is to ensure fairness in clean energy consumption, that is, assuming there are m units available for allocation, according to the principle of minimizing the power generation penalty value, the number of newly subdivided output segments k that each unit can access within the original 0 power generation penalty segment is equal. Assume the length of the 0 power generation penalty output segment for unit i is... Then we can obtain that the diagonal elements of the characteristic matrix A in step 1 satisfy: =N Where N is the number of subdivisions in the subsequent discretization process.

[0044] The above implementation method obtains multiple generator sets with the same constant penalty value from the target power grid, and acquires the flat penalty segment data corresponding to each generator set; determines the output allocation ratio between each generator set based on the segment length; and matches the allocation characteristic coefficient corresponding to each generator set based on this output allocation ratio, so that when multiple generator sets have the same constant penalty value, the product of the output value of each generator set and its corresponding allocation characteristic coefficient is equal. Through the above processing, the preset output allocation principle (such as proportional allocation according to segment length, allocation according to capacity, or allocation according to regulation rate) is quantified into allocation characteristic coefficients, obtaining parameters that can be embedded in the step penalty value construction process, thereby achieving the technical effect that the final solved output plan spontaneously meets the fair allocation requirements without secondary optimization or manual intervention.

[0045] In this embodiment, step 103 includes: Step 1031: For any flat penalty section of any generator set, the flat penalty section is evenly subdivided into multiple sub-output sections; wherein each sub-output section corresponds to several output values; Step 1032: Obtain the constant penalty value of the next output segment adjacent to the flat penalty segment from the original output penalty curve corresponding to the generator set; Step 1033: Obtain the difference between the constant penalty value of the next output segment and the constant penalty value of the flat penalty segment; Step 1034: Determine the penalty value step size corresponding to the flat penalty segment based on the distribution characteristic coefficient of the generator set and the difference; wherein the product of the penalty value step size and the number of sub-output segments is less than or equal to the difference; Step 1035: Determine the number of penalty value steps corresponding to each sub-output segment according to the order of output values ​​from smallest to largest, so that the product of the number of penalty value steps and the penalty value step is used as the penalty value increment corresponding to each sub-output segment. Step 1036: The sum of the constant penalty value of the flat penalty segment and the penalty value increment is used as the step penalty value corresponding to each output value.

[0046] In this embodiment, based on the allocation characteristic coefficient and the original power output penalty curve, each original power generation penalty value in the flat penalty segment data is incremented stepwise to obtain the stepwise penalty value corresponding to each power output value in the flat penalty segment data. The specific steps are as follows: Based on the established allocation principles, a corresponding incremental mechanism for generating power penalty is designed. By introducing an incremental term related to output, the generating power penalty for this section of the unit is changed from a constant. Revised to pertain to its power generation output value The function is a linear function, which transforms the penalty for the power generation penalty segment into a quadratic function of its power output value, thus giving it strict convexity and facilitating optimization solutions. Furthermore, the penalty for exceeding safety constraints is set much higher than the power generation penalty to ensure that safety constraints are not breached.

[0047] To achieve the above allocation principle, the original power generation penalty segment (penalty value) of each marginal unit is allocated. ,length The generation penalty value is transformed into a linearly increasing value with strict convexity, and the constructed generation penalty function is as follows: in, For small positive numbers ( The value only needs to satisfy the condition that the maximum value of the original power generation penalty value after linearization does not exceed the minimum value of the original next segment power generation penalty value. For the unit The starting power of this generation penalty segment. Specifically, the revised generation penalty becomes related to... monotonically increasing function ,like Figure 3 As shown. This function ensures that the power generation penalty increases strictly monotonically with increasing power output, and assigns strict convexity to the power generation penalty function. The corresponding calling function is: .

[0048] During the power dispatching plan formation process, the unit with the highest generation penalty value has the highest penalty value. Then for all groups with the same penalty value, we have: It can be seen that the introduction of incremental terms This ensures the strict convexity of the called function, making the optimization solution unique and exactly in line with the predetermined allocation principle.

[0049] To adapt to the segmented, tiered mechanism of generation penalty values ​​in power dispatching plans, the continuously increasing function is discretized into N segments of tiered penalties. Based on discrete testing with 20, 50, and 100 segments, the results show that an excessive number of segments significantly increases the model's computation time and the risk of computational failure. Considering both computational performance and efficiency, N=10 is recommended.

[0050] The total penalty increment for each original output segment length L is fixed at ΔC. To maintain the monotonically non-decreasing nature of the penalty value after segmentation, ΔC is specified to be less than the minimum allowable increase in the original step penalty value. That is, the maximum total penalty increment ΔC after segmentation is limited to: not exceeding the minimum allowable increase in the original adjacent output segment penalty value. Currently, the minimum unit of original output is 0.01 MW, and the unit penalty value setting accuracy is 1 yuan / MWh, so ΔC is set to 0.01 yuan / MWh.

[0051] The output L is split into N new segments, forming a new stepped penalty. The penalty value for the newly formed k-th segment (k=1,2,…,N) of unit i is: Specifically, regarding the penalty value After discretization, the resulting step penalty is as follows: Figure 4 As shown. From Figure 4 It can be seen that this stepped power generation penalty value structure not only retains the trend of penalty increasing with output, but also simplifies the actual operation and calculation process, and can be directly input into the power generation plan solver to participate in optimization.

[0052] For any flat penalty segment of any generator set, the flat penalty segment is uniformly subdivided into N sub-output segments, each sub-output segment corresponding to several output values. The constant penalty value of the next output segment adjacent to the flat penalty segment is obtained from the original output penalty curve corresponding to the generator set, and this difference is obtained. Based on the distribution characteristic coefficient of the generator set and this difference, the penalty value step size Δp = ΔCN corresponding to the flat penalty segment is determined, such that the product of the penalty value step size and the number of sub-output segments N, ΔC, is less than or equal to this difference. According to the ascending order of output values, the number of penalty value step sizes k corresponding to each sub-output segment is determined. The product of the number of penalty value step sizes and the penalty value step size is used as the penalty value increment corresponding to each sub-output segment. The sum of the constant penalty value and the penalty value increment of the flat penalty segment is used as the step penalty value corresponding to each output value.

[0053] Taking a scenario where clean energy consumption is difficult as an example, assume that the power generation penalty value of each unit is zero. The number of new subdivision output segments, k, called by each unit in the original zero-penalty segment is equal, that is: Assume the length of the zero-power generation penalty output section of unit i is Then the power generation dispatch output value of unit i is: Then the characteristic matrix can be obtained. The diagonal elements satisfy: It can be seen that under the above power generation control arrangement, when the number of segments k is large enough, under a specific power grid operation boundary, the output value will be uniquely determined by the number of output segments called. This feature eliminates the phenomenon of multiple solutions in the optimization calculation process, and the solution of power generation output will become unique.

[0054] In the above implementation method, for any flat penalty segment of any generator set, the flat penalty segment is uniformly subdivided into multiple sub-output segments, each sub-output segment corresponding to several output values; the constant penalty value of the next output segment adjacent to the flat penalty segment is obtained from the original output penalty curve corresponding to the generator set; the difference between the constant penalty value of the next output segment and the constant penalty value of the flat penalty segment is obtained; the penalty value step size corresponding to the flat penalty segment is determined according to the distribution characteristic coefficient of the generator set and the difference, wherein the product of the penalty value step size and the number of sub-output segments is less than or equal to the difference; the number of penalty value step sizes corresponding to each sub-output segment is determined according to the order of output values ​​from smallest to largest, and the product of the number of penalty value step sizes and the penalty value step size is used as the penalty value increment corresponding to each sub-output segment; the sum of the constant penalty value and the penalty value increment of the flat penalty segment is used as the step penalty value corresponding to each output value. Through the above processing, while maintaining the monotonous and non-decreasing characteristics of the original penalty curve, the flat penalty segment is transformed into a strictly increasing stepped penalty sequence, resulting in stepped penalty value data with deterministic gradients and constrained by the penalty difference between adjacent segments. This achieves the technical effect of making the optimization objective function strictly convex, guiding the solver to converge to the unique optimal solution, and ensuring that the transformation does not destroy the original penalty stepped structure.

[0055] In this embodiment, step 104 includes: Step 1041: For any flat penalty segment of each generator set, replace the constant penalty value of the flat penalty segment with the step penalty value corresponding to each output value to obtain the step penalty segment corresponding to the flat penalty segment. Step 1042: Update the original output penalty curve of each generator set according to the stepped penalty segment to obtain the optimized output penalty curve corresponding to each generator set.

[0056] In this embodiment, the original output penalty curve is updated based on the stepped penalty value and the output value to obtain the optimized output penalty curve corresponding to each generator set. Specifically, for any flat penalty segment of each generator set, the constant penalty value of the flat penalty segment is replaced with the stepped penalty value corresponding to each output value to obtain the stepped penalty segment corresponding to the flat penalty segment; the original output penalty curve of each generator set is updated based on the stepped penalty segment, that is: the multiple stepped penalty values ​​obtained after modifying each flat penalty segment are arranged in output order, replacing the original flat penalty segment, and combined with the unmodified output segment to form a complete piecewise constant input penalty curve for each generator set from minimum output to maximum output, so as to obtain the optimized output penalty curve corresponding to each generator set.

[0057] In the above implementation method, for any flat penalty segment of each generator unit, the constant penalty value of the flat penalty segment is replaced with the stepped penalty value corresponding to each output value, resulting in a stepped penalty segment corresponding to the flat penalty segment. The original output penalty curve of each generator unit is updated according to the stepped penalty segment to obtain the optimized output penalty curve corresponding to each generator unit. Through the above processing, the flat part of the original piecewise constant curve is replaced with multiple sub-segments with progressively increasing steps, and spliced ​​with the unmodified output segment in output order to obtain a complete optimized output penalty curve from minimum output to maximum output that can be directly input into the existing optimization model. This achieves a zero-intrusion modification of the original scheduling plan optimization model, eliminating the technical effect of multi-solution oscillation without modifying the internal algorithm of the model.

[0058] In this embodiment, step 105 includes: Step 1051: The step of inputting the operating boundary data and the optimized output penalty curve of each generator unit into the pre-constructed power dispatch plan optimization model, and solving the model with the objective of minimizing the generation penalty value of the target power grid, to obtain the active power output value of each generator unit within the dispatch cycle, includes: Step 1052: Use the active power output value of each generator set in each time period within the scheduling cycle as a decision variable; Step 1053: Use the optimized output penalty curve of each generator set as the penalty coefficient corresponding to the active power output value; Step 1054: Based on the decision variables and the penalty coefficients, construct an objective function with the goal of minimizing the power generation penalty value of the target power grid; Step 1055: Input the objective function, the total load value of the power grid, and the constraints into the preset power dispatch plan optimization model, perform linear programming solution, and obtain the active power output value of each generator unit in each time period within the dispatch cycle.

[0059] In this embodiment, the operating boundary data and the optimized output penalty curve of each generator set are input into a pre-constructed power dispatch plan optimization model. The model is solved with the goal of minimizing the generation penalty value of the target power grid to obtain the active power output value of each generator set within the dispatch cycle.

[0060] Specifically, the operational boundary data includes the total grid load value for each time period within the scheduling cycle and the corresponding constraints of the target grid. The active power output value of each generating unit in each time period within the scheduling cycle is used as a decision variable, and the optimized output penalty curve of each generating unit is used as the penalty coefficient corresponding to the active power output value. Based on the decision variables and penalty coefficients, an objective function is constructed with the goal of minimizing the generation penalty value of the target grid. The objective function, the total grid load value, and the constraints are input into a preset power dispatch plan optimization model, and linear programming is performed to obtain the active power output value of each generating unit in each time period within the scheduling cycle.

[0061] The constraints include: power balance constraints where the sum of the output of all generator units in each time period equals the total load value of the power grid in that time period; upper and lower limits of output constraints where the output of each generator unit does not exceed its maximum technical output and is not lower than its minimum technical output; ramping constraints where the output change between adjacent time periods does not exceed the ramping rate of the generator unit; and network security constraints where the transmission power of the line and cross section does not exceed its thermal stability limit.

[0062] Through the above steps, the output plan obtained is the same when solved multiple times under the same input conditions. The output value between adjacent time periods changes smoothly with the boundary conditions of the power grid operation without random jumps, and automatically meets the preset output allocation principle, thus realizing the fair consumption of clean energy.

[0063] In the above implementation, the operational boundary data includes the total grid load value for each time period within the scheduling cycle and the corresponding constraints of the target grid. The active power output value of each generating unit in each time period within the scheduling cycle is used as the decision variable, and the optimized output penalty curve of each generating unit is used as the penalty coefficient corresponding to the active power output value. Based on the decision variables and penalty coefficients, an objective function is constructed with the goal of minimizing the generation penalty value of the target grid. The objective function, the total grid load value, and the constraints are input into a preset power dispatch plan optimization model, and linear programming is performed to obtain the active power output value of each generating unit in each time period within the scheduling cycle. Through the above processing, under the combined effect of power balance constraints, output upper and lower limit constraints, ramping constraints, and network security constraints, linear programming is performed using the modified objective function with strict convexity to obtain unique output plan data that satisfies security constraints. This achieves the technical effects of smoothing the output plan with load changes across different time periods, eliminating random jumps, and improving the operational stability of the power system.

[0064] In this first embodiment, the power dispatching plan optimization calculation model for the southern region is used as the basis for... Figure 1 The effectiveness of the method shown was tested. Specifically, the original power generation penalty value was modified according to the power generation penalty function modification method described above. Figure 1 The method shown is compared to the original optimization calculation model of the Southern Region Power Dispatch Plan; Based on the optimized calculation model of the original Southern Regional Power Dispatch Plan, the power output was calculated and... Figure 1 After testing the optimized Southern Regional Power Dispatch Plan Optimization Model using the method shown, a time-sharing statistical comparison of the system-wide generation penalty values ​​reveals that when testing the original Southern Regional Power Dispatch Plan Optimization Model using the original mechanism, the system optimization was more prone to degradation, leading to sudden increases and decreases in generation penalties between different calculation periods, with a more pronounced randomness in the generation penalty. However, when testing the optimized Southern Regional Power Dispatch Plan Optimization Model, each iteration had a relatively definite solution, resulting in a more continuous trend in generation cost changes between different periods.

[0065] Furthermore, due to the existence of multiple solutions, methods such as... were not used. Figure 1 The unit output generated by the method shown will exhibit random oscillations over a wider range. And as... Figure 1 After optimization with the addition of oscillation suppression technology, the basis for measuring the unit's power generation penalty is clearer. The power generation plan is only affected by changes in electricity load, the unit's power generation plan arrangement is more continuous, the sawtooth shape caused by random power output allocation is eliminated, the problem of random power output oscillation is significantly improved, and the stability of power system operation is enhanced.

[0066] To test the effect of oscillation suppression technology on power generation plan allocation, four test case parameter settings were configured, further dividing the original penalty value output segment into 100 segments, 50 segments, 20 segments, and 10 segments respectively. First, the output calculation results of eight randomly selected different types of power sources during the same period are presented as a comparison in a scenario where the technology is not used. The situation is as follows. Figure 5 As shown. From Figure 5 As can be seen from the data, in the control case, due to the random oscillation of power generation output, the power distribution of each unit exhibits significant randomness. However, in multiple test cases with different numbers of segments, the power distribution ratio of each unit in the zero-penalty segment is nearly consistent, demonstrating significant stability.

[0067] Reference Figure 6 This embodiment also discloses a power generation dispatch plan stability control system, including a flat penalty module 1, a power distribution module 2, a stepped penalty module 3, a penalty optimization module 4, and a power output control module 5; The flat penalty module 1 is used to acquire the operating boundary data of the target power grid and the original output penalty curve of each generator set, and to acquire the flat penalty segment data corresponding to each generator set according to the original output penalty curve; wherein, the flat penalty segment data includes multiple output values ​​corresponding to the same original power generation penalty value. The power distribution module 2 is used to obtain the distribution characteristic coefficients corresponding to each generator set based on the flat penalty section data and the preset power distribution algorithm. The stepped penalty module 3 is used to incrementally increase each of the original power generation penalty values ​​in the flat penalty segment data according to the allocation characteristic coefficient and the original power output penalty curve, so as to obtain the stepped penalty value corresponding to each of the power output values ​​in the flat penalty segment data. The penalty optimization module 4 is used to update the original output penalty curve according to the stepped penalty value and the output value, so as to obtain the optimized output penalty curve corresponding to each generator set. The output control module 5 is used to input the operating boundary data and the optimized output penalty curve of each generator set into the pre-constructed power dispatch plan optimization model, and solve the problem with the goal of minimizing the power generation penalty value of the target power grid, so as to obtain the active power output value of each generator set in the dispatch cycle.

[0068] In this embodiment, the flatness penalty module 1 includes a curve division unit, a curve traversal unit, and a curve recognition unit; The curve division unit is used to obtain the original output penalty curve of any generator set; wherein, the original output penalty curve includes multiple output segments; each output segment includes an initial output value, an end output value and a constant penalty value corresponding to the output segment; The curve traversal unit is used to traverse each of the output segments in the original output penalty curve and identify several consecutive output segments in which the constant penalty value remains unchanged as flat penalty segments. The curve recognition unit is used to obtain the starting output value, ending output value, segment length, and the same constant penalty value of the flat penalty segment for any given flat penalty segment, as the flat penalty segment data of the flat penalty segment.

[0069] It should be noted that the device embodiments described above are merely illustrative, and some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can specifically be implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0070] Based on the above-described embodiment of a power generation dispatch plan stability control method, another embodiment of the present invention provides a terminal device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements a power generation dispatch plan stability control method according to any embodiment of the present invention.

[0071] For example, in this embodiment, the computer program can be divided into one or more modules, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules may be a series of computer program instruction segments capable of performing specific functions, which describe the execution process of the computer program in the terminal device. The terminal device may be a computing device such as a desktop computer, laptop, handheld computer, or cloud server. The terminal device may include, but is not limited to, a processor and memory.

[0072] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the terminal device, connecting all parts of the terminal device via various interfaces and lines.

[0073] Based on the above-described method embodiments, another embodiment of the present invention provides a computer-readable storage medium including a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to execute a power generation dispatch plan stability control method as described in any of the above-described method embodiments of the present invention.

[0074] The modules / units integrated in the device / terminal equipment, if implemented as software functional units and sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0075] This embodiment discloses a method, system, equipment, and medium for controlling the stability of power generation scheduling plans. It reveals a mechanism for incrementally modifying homogeneous power generation penalties: while retaining the original power generation penalty value information, it transforms flat power generation penalty segments into strictly monotonically increasing multi-segment power generation penalty values ​​through discretization processing with a fixed height difference, eliminating the degradation condition of the objective function; a balance design between randomness and intention: the order of magnitude of the incremental increment is crucial, requiring it to not affect the accuracy of power generation plan optimization calculations, not change the monotonically non-decreasing trend of the original power generation penalty values, and ensure that the optimization solver can perceive gradient differences; quantitative implementation of the output allocation principle: by combining the output allocation principle with discretization segmentation, the power generation scheduling plan solution spontaneously achieves the preset allocation target without subsequent manual intervention; computational efficiency control: each original segment of power generation penalty is fixedly subdivided into 10 segments, reducing randomness by an order of magnitude while increasing computation time by less than 5%, meeting the actual operational efficiency requirements.

[0076] Regarding the mechanism disclosed in this application, this application only performs preprocessing at the data input layer, without modifying the original power dispatch plan optimization calculation model and core algorithm. This minimizes the impact on the existing power generation planning architecture, resulting in low implementation costs. Simultaneously, it effectively improves the stability and continuity of power generation plan calculation results, avoiding problems such as unit fatigue damage or inability to operate according to plan due to rapid and repeated oscillations in the power generation plan. Furthermore, compared to existing technologies where a single optimization calculation can achieve proportional power allocation, and compared to quadratic programming and sequential optimization algorithms, the process is simpler and does not change the objective of minimizing the power generation operation penalty value, meeting the efficient operation requirements of large-scale complex power grid dispatch. The homogeneous penalty micro-increase modification mechanism does not violate the original penalty ladder, and the micro-increase is extremely small, not altering the impact of other constraints on the calculation results within the accuracy range.

[0077] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. In particular, it should be noted that any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention for those skilled in the art.

Claims

1. A method for stability control of power generation dispatching plans, characterized in that, include: The system acquires the operating boundary data of the target power grid and the original output penalty curve of each generator set, and obtains the flat penalty segment data corresponding to each generator set based on the original output penalty curve; wherein, the flat penalty segment data includes multiple output values ​​corresponding to the same original power generation penalty value; Based on the flat penalty segment data and the preset power distribution algorithm, the distribution characteristic coefficients corresponding to each generator set are obtained. Based on the allocation characteristic coefficient and the original power output penalty curve, each original power generation penalty value in the flat penalty segment data is incremented stepwise to obtain the step penalty value corresponding to each power output value in the flat penalty segment data. The original output penalty curve is updated based on the stepped penalty value and the output value to obtain the optimized output penalty curve corresponding to each generator set. The operating boundary data and the optimized output penalty curve of each generator set are input into the pre-constructed power dispatch plan optimization model. The model is solved with the goal of minimizing the generation penalty value of the target power grid, so as to obtain the active power output value of each generator set in the dispatch cycle.

2. The power generation dispatch plan stability control method according to claim 1, characterized in that, The process of acquiring the target power grid's operating boundary data and the original output penalty curve for each generator unit, and acquiring the flat penalty segment data corresponding to each generator unit based on the original output penalty curve, includes: For any generator set, obtain the original output penalty curve of the generator set; wherein, the original output penalty curve includes multiple output segments; each output segment includes an initial output value, an end output value and a constant penalty value corresponding to the output segment; Traverse each of the output segments in the original output penalty curve, and identify several consecutive output segments in which the constant penalty value remains unchanged as flat penalty segments; For any given flat penalty segment, the starting output value, ending output value, segment length, and the same constant penalty value of the flat penalty segment are obtained as the flat penalty segment data of the flat penalty segment.

3. The power generation dispatch plan stability control method according to claim 2, characterized in that, The step of obtaining the allocation characteristic coefficients corresponding to each generator set based on the flat penalty segment data and the preset power allocation algorithm includes: Obtain multiple generator sets with the same constant penalty value from the target power grid, and obtain the flat penalty segment data corresponding to each generator set; The output distribution ratio between each generator set is determined based on the length of the segment. Based on the power distribution ratio, the distribution characteristic coefficients corresponding to each generator set are matched so that when multiple generator sets have the same constant penalty value, the product of the power output value of each generator set and its corresponding distribution characteristic coefficient is equal.

4. A method for controlling the stability of a power generation dispatch plan according to any one of claims 2-3, characterized in that, The step of incrementally increasing each original power generation penalty value in the flat penalty segment data according to the allocation characteristic coefficient and the original power output penalty curve to obtain the step penalty value corresponding to each power output value in the flat penalty segment data includes: For any flat penalty section of any generator set, the flat penalty section is uniformly subdivided into multiple sub-output sections; wherein each sub-output section corresponds to several output values; Obtain the constant penalty value of the next output segment adjacent to the flat penalty segment from the original output penalty curve corresponding to the generator set; Obtain the difference between the constant penalty value of the next output segment and the constant penalty value of the flat penalty segment; Based on the distribution characteristic coefficient of the generator set and the difference, the penalty value step size corresponding to the flat penalty segment is determined; wherein, the product of the penalty value step size and the number of sub-output segments is less than or equal to the difference; Based on the output values ​​in ascending order, determine the penalty value step size corresponding to each sub-output segment, and use the product of the penalty value step size and the penalty value step size as the penalty value increment corresponding to each sub-output segment. The constant penalty value of the flat penalty segment and the sum of the penalty value increments are used as the step penalty value corresponding to each output value.

5. The power generation dispatch plan stability control method according to claim 1, characterized in that, The step of updating the original output penalty curve based on the stepped penalty value and the output value to obtain the optimized output penalty curve for each generator set includes: For any flat penalty segment of each generator set, the constant penalty value of the flat penalty segment is replaced with the step penalty value corresponding to each output value to obtain the step penalty segment corresponding to the flat penalty segment. The original output penalty curve of each generator set is updated according to the stepped penalty segment to obtain the optimized output penalty curve corresponding to each generator set.

6. The power generation dispatch plan stability control method according to claim 1, characterized in that, The operational boundary data includes the total grid load value for each time period within the scheduling cycle and the constraints corresponding to the target grid. The process involves inputting the operational boundary data and the optimized output penalty curve of each generator unit into a pre-constructed power dispatch plan optimization model, and solving the model with the objective of minimizing the generation penalty value of the target power grid, to obtain the active power output value of each generator unit within the dispatch cycle, including: The active power output of each generator set in each time period within the scheduling cycle is used as a decision variable. The optimized output penalty curve of each generator set is used as the penalty coefficient corresponding to the active power output value; Based on the decision variables and the penalty coefficients, an objective function is constructed with the goal of minimizing the generation penalty value of the target power grid. The objective function, the total load value of the power grid, and the constraints are input into a preset power dispatch plan optimization model, and linear programming is performed to obtain the active power output value of each generator unit in each time period within the dispatch cycle.

7. A power generation dispatching plan stability control system, characterized in that, It includes a flat penalty module, an output distribution module, a stepped penalty module, a penalty optimization module, and an output control module; The flat penalty module is used to acquire the operating boundary data of the target power grid and the original output penalty curve of each generator set, and to acquire the flat penalty segment data corresponding to each generator set according to the original output penalty curve; wherein, the flat penalty segment data includes multiple output values ​​corresponding to the same original power generation penalty value; The power distribution module is used to obtain the distribution characteristic coefficients corresponding to each generator set based on the flat penalty segment data and the preset power distribution algorithm. The stepped penalty module is used to incrementally increase each of the original power generation penalty values ​​in the flat penalty segment data according to the allocation characteristic coefficient and the original power output penalty curve, so as to obtain the stepped penalty value corresponding to each of the power output values ​​in the flat penalty segment data. The penalty optimization module is used to update the original output penalty curve according to the stepped penalty value and the output value, so as to obtain the optimized output penalty curve corresponding to each generator set. The output control module is used to input the operating boundary data and the optimized output penalty curve of each generator set into a pre-built power dispatch plan optimization model, and solve the problem with the goal of minimizing the generation penalty value of the target power grid, so as to obtain the active power output value of each generator set in the dispatch cycle.

8. A power generation dispatching plan stability control system according to claim 7, characterized in that, The flatness penalty module includes a curve division unit, a curve traversal unit, and a curve recognition unit. The curve division unit is used to obtain the original output penalty curve of any generator set; wherein, the original output penalty curve includes multiple output segments; each output segment includes an initial output value, an end output value and a constant penalty value corresponding to the output segment; The curve traversal unit is used to traverse each of the output segments in the original output penalty curve and identify several consecutive output segments in which the constant penalty value remains unchanged as flat penalty segments. The curve recognition unit is used to obtain the starting output value, ending output value, segment length, and the same constant penalty value of the flat penalty segment for any given flat penalty segment, as the flat penalty segment data of the flat penalty segment.

9. A terminal device, characterized in that, The system includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements a power generation dispatch plan stability control method as described in any one of claims 1-6.

10. A computer-readable storage medium, characterized in that, include: A stored computer program, wherein, when the computer program is executed, it controls the device containing the computer-readable storage medium to perform a power generation dispatch plan stability control method as described in any one of claims 1-6.

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