Multi-scene power system frequency safety index adaptive partition reconstruction method

Abstract

The invention discloses a multi-scene power system frequency safety index self-adaptive partition reconstruction method, which comprises the following steps: acquiring multi-type frequency modulation resource parameters of a system, and establishing an analytical expression of nonlinear frequency safety index constraints based on a system multi-machine frequency response dynamic model considering multi-type frequency modulation resources; acquiring an original feasible range of system frequency modulation parameters, and sampling to generate an original frequency modulation parameter region and a frequency safety index sample curved surface set in the feasible range of the system frequency modulation parameters; acquiring all sample point subsets on an inertia boundary in the frequency modulation parameter area by traversing sample points meeting a specific equivalent inertia value of the system, acquiring intersection points of frequency safety indexes corresponding to the sample points and constraint limit values of the sample points on an original frequency modulation parameter area boundary, and re-partitioning the original frequency modulation parameter area into a plurality of subareas; and linearizing the linear sub-region which needs to be linearized, outputting a linearization parameter which meets a linear error threshold value requirement, and reconstructing a frequency safety index constraint after partition linearization.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of power systems, in particular to a multi-scenario power system frequency safety index adaptive partition reconstruction method. BACKGROUND

[0002] With the large-scale and continuous grid connection of renewable energy based on converters and the configuration and construction of direct current transmission, the power system is gradually transformed into a high proportion of power electronic interface power system dominated by new energy units. Compared with the traditional power system, the frequency support capability of the new energy dominated power system is continuously declining, which leads to poor system frequency resistance and system frequency deviation exceeding the action threshold of system stability device when facing active disturbance, which will cause serious power outage accidents.

[0003] At present, there have been many power outage accidents caused by insufficient frequency support capability of new energy power system leading to excessive frequency drop. Therefore, how to ensure the frequency safety of the power system has received widespread attention, but the highly nonlinear system frequency response model makes it difficult to be included in various changing operation scenarios, and how to effectively include the frequency safety index constraint in the optimization operation and system planning and other operation scenarios is crucial to the safe and stable operation of the system.

[0004] At present, the methods for including frequency safety constraints in power system operation scenarios mainly include data-driven frequency modulation boundary extraction method and piecewise linear linearization approximation method. The former is difficult to be included in large-scale power systems due to its large computational burden. The latter is widely used in unit commitment related researches at the day-ahead scale due to its acceptable computational efficiency in a single operation scenario. However, the accuracy of the piecewise linear approximation method is affected by the number of segments, and more segments result in a large number of intermediate variables and linear constraints in the approximation model, which greatly increases the size of the overall system model. Therefore, the significant increase in computational burden exposed in the longer time scale model makes it difficult to apply to large-scale power system operation models containing multiple scenarios. SUMMARY

[0005] Therefore, the present application provides a multi-scenario power system frequency safety index adaptive partition reconstruction method to at least solve the problem that the frequency safety index construction method in the prior art is difficult to be high-precision and high-efficiency in multiple operation scenarios.

[0006] In order to achieve the above purpose, the technical scheme adopted by the present application is as follows: A multi-scenario power system frequency safety index adaptive partition reconstruction method, comprising the following steps: S1. In the preset active disturbance Below, the operation time The extreme value of the frequency deviation As a nonlinear frequency safety index, the frequency deviation does not exceed the maximum frequency deviation threshold value that ensures that the system safety and stability device is not triggered is a nonlinear frequency safety index constraint; based on the system multi-type frequency modulation resource parameters, the system equivalent frequency modulation parameters are constructed under the condition of a unified synchronous unit response time constant ; based on the system equivalent frequency modulation parameters, the nonlinear frequency safety index constraint and its analytical expression are constructed ; wherein the system equivalent frequency modulation parameters include: system equivalent inertia , modulation difference coefficient and reheating time coefficient ; S2. Obtain the maximum feasible range of , and as the original frequency modulation parameter feasible range, sample and generate sample points and the corresponding of each sample point in the original frequency modulation parameter feasible range, and correspondingly obtain the sample surface set ; S3. Obtain the original frequency modulation parameter feasible range of corresponding sample surface, traverse the sample surface set and corresponding to and , respectively obtain the intersection of the nonlinear frequency safety index and its constraint limit value on the boundary of the original frequency modulation parameter feasible range, and rezone the original frequency modulation parameter feasible range according to the modulation difference coefficient and corresponding to the obtained intersection, to obtain the partitioned sub-region. S4. Linearize the sub-region that needs to be linearized, and output the linearized parameters that meet the linear error threshold requirement, and reconstruct the nonlinear frequency safety index constraint after linearization to obtain the frequency safety index constraint after partitioning linearization.

[0007] Preferably, the multi-type frequency modulation resource includes: synchronous units, new energy units based on converters, and pumped storage; the multi-type frequency modulation resource parameters include: the installed capacity of each type of frequency modulation resource, the inertia time constant of synchronous units, the primary frequency modulation difference coefficient, the governor response time constant and the turbine reheating time constant, the virtual inertia time constant and the virtual modulation difference coefficient of new energy units, and the inertia time constant and the modulation difference coefficient of pumped storage units.

[0008] Preferably, the nonlinear frequency safety index constraint is expressed as: ; The analytical expression of the nonlinear frequency security index is: ; wherein, is a load damping coefficient; , and are intermediate variables of the nonlinear relationship of the equivalent frequency modulation parameters of the coupling system, is the corresponding time when the frequency deviation reaches the extreme value.

[0009] Preferably, the specific steps of constructing the analytical expression of the nonlinear frequency security index based on the equivalent frequency modulation parameters of the system include: S11. Establishing a system multi-machine frequency dynamic response model, then the first-order differential equation form of the frequency dynamic response of the system under any given operating scenario is: ; In the formula, is the equivalent inertia of the system under any given operating scenario, is the frequency deviation of the system, , and are the primary frequency response power adjustment amounts of the first synchronous unit, the first new energy unit and the first pumped storage power station; , and are the sets of synchronous units, new energy units and pumped storage; wherein, the transfer function of the equivalent prime mover-governor primary frequency power adjustment amount of the synchronous unit and the pumped storage varies with the frequency deviation is: ; ; In the formula, is the gain of the governor of the synchronous unit, is the turbine coefficient of the turbine, is the reheater time constant, is the droop coefficient of the governor of the pumped storage power station, and are the response time constants of the reversible pump-turbine and guide vane of the pumped storage power station; The new energy unit based on the converter participates in frequency response through virtual droop control mode, and its primary frequency power model is: ; In the formula, a droop coefficient of the virtual synchronous machine, a response time constant of the virtual synchronous machine; S11. a response time constant of the unified synchronous machine group The system multi-machine frequency dynamic response model is aggregated into an equivalent frequency modulation parameter model of the system varying with each scenario: ; In the formula, 、 and are virtual inertia time constants of the synchronous machine group, the pumped storage and the new energy machine group respectively, 、 and are installed capacities of the synchronous machine group, the pumped storage and the new energy machine group respectively, is a reference capacity, is a synchronous machine group start-stop state variable, 1 for start and 0 for stop, is a pumped storage power generation state variable, 1 for power generation and 0 for pumping, 、 and are state variables of whether the synchronous machine group, the pumped storage and the new energy machine group provide frequency support, 1 for providing frequency support and 0 for not providing frequency support; S13. Based on the equivalent frequency modulation parameter model of the system, the inverse Laplace transform is used to obtain a time-domain form of a nonlinear frequency safety index constraint and an analytical expression thereof.

[0010] Preferably, the specific content of S2 includes: S21. Based on the current all frequency modulation resource parameters of the system 、 and , the minimum and maximum frequency support schemes are calculated to obtain the maximum feasible range of the system frequency modulation parameters as the original frequency modulation parameter feasible range, and 、 and the original frequency modulation parameter feasible range is: ; S22. Based on Latin hypercube sampling, sample points considering all possible machine group combinations and resource frequency support schemes are generated in , wherein the th sample point is expressed as , , and the frequency deviation extreme value corresponding to all sample points is calculated according to , wherein the frequency deviation extreme value corresponding to the th sample point is denoted as ;​ S23. Adjust the frequency parameters from all sample points. Choose any sample value from the dimensions In determining Obtain the sample surface set under the following conditions: ,in, Indicates the first The extreme coordinates of the frequency deviation corresponding to each sample point It represents the three-dimensional real number space.

[0011] Preferably, the specific content of obtaining the intersection point of the nonlinear frequency safety index and its constraint limit on the feasible range boundary of the original frequency modulation parameters in S3 includes: S31. Obtain Feasible range of original frequency modulation parameters The corresponding sample surface will and The corresponding set of sample surfaces is defined as and : ; ; In the formula, and They represent and The corresponding extreme coordinates of frequency deviation and They represent and The corresponding adjustment coefficient, and They represent and The corresponding extreme value of frequency deviation; S32. Obtain the nonlinear frequency safety index and its constraint limits. The intersection points on the boundaries of the feasible range of the original frequency modulation parameters include: (1) For the index set Perform initialization, that is, let ,in , Indicates the first The extreme value of frequency deviation corresponding to each sample point Is the value the same as Equal binary indexes, when equal When they are not equal ; (2) Iterate through the subset For all sample points, if the extreme value of the frequency deviation corresponding to the sample point is... If equal, let the current binary index and update the index set , otherwise and update the index set ; (3) Obtain the adjustment coefficient that satisfies , which is expressed as: wherein, is the current one binary index, and the corresponding sample point is the sample point on the system inertia boundary where the nonlinear frequency safety index is equal to the frequency safety constraint limit; (4) According to steps (1)-(3), obtain the corresponding adjustment coefficient and the corresponding sample point .

[0012] Preferably, in S3, the original frequency modulation parameter feasible range is re-partitioned according to the adjustment coefficient corresponding to the intersection point obtained, and the obtained sub-regions , and are respectively: ; ; ; wherein, and are the minimum value and the maximum value of , respectively, and are the minimum value and the maximum value of , respectively, and are the minimum value and the maximum value of , respectively.

[0013] Preferably, the specific content in S4 includes: S41. Discard the completely unsafe sub-region , retain the completely safe sub-region , and linearize the partially safe sub-region : linearize the frequency deviation extreme value model in the sub-region using a linear hyperplane fitting method: fit the frequency deviation extreme value nonlinear frequency deviation extreme value by a linear optimization model to obtain a frequency modulation parameter linear form model, and linearize the nonlinear frequency deviation extreme value The sample surface is approximated as a series of linear fitting planes; the linear optimization model is: ; wherein, is the approximation error corresponding to the i th sample point, ensures that the linear result of approximation is above the sample surface, is a linearization error threshold, are linear fitting coefficients of the i th hyperplane, that is, the linearization parameters satisfying the linear error threshold requirement are outputted; is the nonlinear frequency safety index constraint, and the final reconstruction is: .

[0014] Compared with the prior art, the multi-scene power system frequency safety index adaptive partition reconstruction method provided by the technical solution has the following beneficial effects: The present application is based on sampling to obtain a frequency modulation parameter region based on the original frequency modulation parameter range of the system and a series of sample points, and the adaptive partition of the feasible region of the original frequency modulation parameter of the system is realized by introducing a loop judgment link to obtain all sample points on the equivalent inertia boundary of the system through the traversal method, and only the sub-region that needs linear approximation The hyperplane linearization method is introduced, and the frequency safety index adaptive partition reconstruction method is realized. The present application narrows the region that needs linear approximation through adaptive partition, greatly reduces the scale of the reconstructed frequency safety index constraint model and variable, and at the same time avoids the reduction of the overall range of the model input parameters due to the too large linearization parameter range, thereby significantly enhancing the calculation efficiency in the power system operation scene model. The present application has higher solving efficiency and adaptability for the frequency safety constraint of the power system operation and planning in the long time scale multi-operation scene. In related research, it can assist the grid operator to determine a reasonable frequency resource planning layout and operation scheme, and provide support for stable operation of the power system. BRIEF DESCRIPTION OF DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or the prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.

[0016] Figure 1 A flowchart of a multi-scene power system frequency safety index adaptive partition reconstruction method provided by the present application is shown in the figure; Figure 2 ​​This is a test system topology diagram provided in an embodiment of the present invention; Figure 3 This is a schematic diagram comparing the linearity results of a sample surface under the same error constraints using different methods provided in the embodiments of the present invention. Figure 3 (a) is the adaptive partitioning reconstruction method proposed in this invention; Figure 3 (b) is the traditional piecewise linear method; Figure 4 A schematic diagram of the frequency deviation extreme value index obtained by solving the frequency security index reconstruction method proposed in this invention for the four models provided in the embodiments of this invention; Figure 5 The system frequency simulation trajectory diagram provided in the embodiment of the present invention; Figure 6 This is a schematic diagram showing the duration proportion of each sub-region where the frequency modulation parameters obtained by solving the frequency security index partitioning reconstruction method proposed in this invention are located in different models provided in the embodiments of this invention. Figure 6 (a) is Model 1. Figure 6 (b) is Model 2. Figure 6 (c) represents model 3. Figure 6 (d) is model 4. Detailed Implementation

[0017] 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.

[0018] This invention provides an adaptive partitioned reconfiguration method for frequency security indicators in power systems under multiple scenarios, such as... Figure 1 As shown, it includes the following steps: S1. Under the preset active power disturbance Below, the runtime of each running scenario will be... Extreme values ​​of frequency deviation at time As a nonlinear frequency safety indicator, The frequency deviation threshold that does not exceed the maximum frequency required to ensure that the system's safety and stability devices are not triggered To constrain nonlinear frequency safety indicators; based on the system's multi-type frequency regulation resource parameters, under a unified synchronous unit response time constant. Under the given conditions, construct the system's equivalent frequency modulation parameters; based on the system's equivalent frequency modulation parameters, construct the nonlinear frequency safety index constraints and their analytical expressions. The system's equivalent frequency modulation parameters include: system equivalent inertia. Adjustment coefficient and reheat time coefficient ; S2. Obtain , and The maximum feasible range is taken as the feasible range of the original frequency modulation parameters, and sampling is generated within the feasible range of the original frequency modulation parameters. Each sample point and its corresponding data And obtain the corresponding sample surface set. ; S3. Obtain Feasible range of original frequency modulation parameters The corresponding sample surface, traversed and The corresponding sample surface set and The intersection points of the nonlinear frequency safety index and its constraint limit on the feasible range boundary of the original frequency modulation parameters are obtained respectively, and the droop coefficient corresponding to the obtained intersection points is used as the basis for the calculation. and The feasible range of the original frequency modulation parameters is re-partitioned to obtain the partitioned sub-regions; S4. Linearize the sub-regions that need to be linearized and output the linearization parameters that meet the linear error threshold requirements. After reconstructing the nonlinear frequency safety index constraints, the frequency safety index constraints after partition linearization are obtained.

[0019] To further implement the above technical solutions, the various types of frequency regulation resources include: synchronous generator units, converter-based new energy generator units, and pumped storage. The parameters of the various types of frequency regulation resources include: the installed capacity of each type of frequency regulation resource, the inertial time constant, primary frequency regulation droop coefficient, governor response time constant, and turbine reheat time constant of synchronous generator units, the virtual inertial time constant and virtual droop coefficient of new energy generator units, and the inertial time constant and droop coefficient of pumped storage generator units.

[0020] To further implement the above technical solution, the nonlinear frequency safety index constraint is expressed as follows: ; The analytical expression for the nonlinear frequency safety index is: ; in, This is the load damping coefficient; , and These are intermediate variables representing the nonlinear relationship of the equivalent frequency modulation parameters of the coupled system. This represents the moment when the frequency deviation reaches its extreme value.

[0021] To further implement the above technical solutions, the specific steps of constructing the nonlinear frequency safety index analytical expression based on the system equivalent frequency modulation parameter include: S11. Establish a system multi-machine frequency dynamic response model, and the first-order differential equation form of the frequency dynamic response of the system under any given operating scenario is: ; In the formula, is the system equivalent inertia under any given operating scenario, is the system frequency deviation, , and are the primary frequency response power adjustment amounts of the first synchronous unit, the first new energy unit and the first pumped storage power station; , and are the sets of synchronous units, new energy units and pumped storage; Among them, the transfer function of the equivalent prime mover-governor primary frequency power adjustment amount of the synchronous unit and the pumped storage changes with the frequency deviation is expressed as: ; ; In the formula, is the synchronous unit governor gain, is the turbine coefficient of the turbine, is the reheater time constant, is the governor droop coefficient of the pumped storage power station, and are the response time constants of the reversible pump-turbine and guide vane of the pumped storage power station; The new energy unit based on the converter participates in frequency response through virtual droop control mode, and its primary frequency power model is: ; In the formula, is the droop coefficient of the virtual synchronous machine, is the response time constant of the virtual synchronous machine; S11. The response time constant of the unified synchronous unit is , and the system multi-machine frequency dynamic response model is aggregated into a system equivalent frequency modulation parameter model that changes with each scenario: ; In the formula, , and are the virtual inertia time constants of synchronous units, pumped storage units and new energy units respectively, , and are the installed capacities of synchronous units, pumped storage units and new energy units respectively, is the reference capacity, is the state variable of synchronous units start-stop state, start is 1, stop is 0, is the state variable of pumped storage power generation state, 1 in power generation state, 0 in pumping state, , and are the state variables of whether synchronous units, pumped storage units and new energy units provide frequency support, 1 when providing frequency support, 0 when not providing frequency support; S13. Based on the system equivalent frequency modulation parameter model, the Laplace inverse transform is used to obtain the time domain form of the nonlinear frequency safety index constraint and its analytical expression.

[0022] It should be noted that: In multiple scenarios, the frequency modulation parameters of various resources depend on their installed capacity, the state of unit combination of synchronous units, the state of charging and discharging of pumped storage, and the state variable of whether various resources participate in frequency response. Considering that the sensitivity of the unit response time constant is much lower than other parameters, the required time constant of various resources is conservatively assumed to be the uniform synchronous unit response time constant , then the system equivalent frequency modulation parameters include the system equivalent inertia , the modulation coefficient and the reheating time coefficient , which are aggregated into parameters that vary with each scenario through the equivalent frequency response model.

[0023] In order to further implement the above technical solutions, the specific content of S2 includes: S21. Based on the system current all frequency modulation resource parameters , and calculate the minimum and maximum frequency support scheme to obtain the maximum feasible range of system frequency modulation parameters as the original frequency modulation parameter feasible range, then , and the original frequency modulation parameter feasible range is: ; S22. Based on Latin hypercube sampling, generate sample points considering all possible unit combinations and resource frequency support schemes in , where the th sample point is represented as , and according to Calculate the extreme values ​​of frequency deviation for all sample points. , of which The extreme values ​​of frequency deviation corresponding to each sample point are denoted as ; S23. Adjust the frequency parameters from all sample points. Choose any sample value from the dimensions In determining Obtain the sample surface set under the following conditions: ,in, Indicates the first The extreme coordinates of the frequency deviation corresponding to each sample point It represents the three-dimensional real number space.

[0024] It should be noted that: The original feasible range of system frequency modulation parameters is obtained by calculating the minimum and maximum frequency support scheme based on all current frequency modulation resource parameters of the system, and then obtaining the maximum feasible range of system frequency modulation parameters as the original feasible range of frequency modulation parameters. This ensures that the equivalent frequency modulation parameters of the system under any operating scenario are within this range.

[0025] To further implement the above technical solution, the specific content of obtaining the intersection point of the nonlinear frequency safety index and its constraint limit on the boundary of the feasible range of the original frequency modulation parameters in S3 includes: S31. Obtain Feasible range of original frequency modulation parameters The corresponding sample surface will and The corresponding set of sample surfaces is defined as and : ; ; In the formula, and They represent and The corresponding extreme coordinates of frequency deviation and They represent and The corresponding adjustment coefficient, and They represent and The corresponding extreme value of frequency deviation; S32. Obtain the nonlinear frequency safety index and its constraint limits. The intersection points on the boundaries of the feasible range of the original frequency modulation parameters include: (1) For the index set Perform initialization, that is, let ,in , Indicates the first The extreme value of frequency deviation corresponding to each sample point Is the value the same as Equal binary indexes, when equal When they are not equal ; (2) Iterate through the subset For all sample points, if the extreme value of the frequency deviation corresponding to the sample point is... If they are equal, then set the current binary index. Update the index set with this value. ,otherwise Update the index set with this value. ; (3) Obtaining satisfaction adjustment coefficient , represented as: ,in, For the present The preceding binary indicator index, corresponding to the sample point That is, the sample points on the system inertia boundary where the nonlinear frequency safety index is equal to the frequency safety constraint limit; (4) Obtain according to steps (1)-(3) Corresponding adjustment coefficient and the corresponding sample points .

[0026] To further implement the above technical solution, in S3, the feasible range of the original frequency modulation parameters is re-partitioned based on the droop coefficient corresponding to the obtained intersection point, resulting in sub-regions. , and They are respectively: ; ; ; in, and They are respectively The minimum and maximum values, and They are respectively The minimum and maximum values, and They are respectively The minimum and maximum values.

[0027] To further implement the above technical solution, the specific contents of S4 include: S41. Discard completely unsafe subregions. Preserve a completely secure sub-region For partially secure sub-regions Perform linearization: Linear hyperplane fitting method is used for sub-regions Linearization of the frequency deviation extreme value model within: The linear optimization model is used to fit the extreme value of the nonlinear frequency deviation to the nearest value. The linear form model of the frequency modulation parameters, sub-region Nonlinear frequency deviation extremes The sample surface is approximated as a series of linearly fitted planes; the linear optimization model is: ; in, For the first The approximation error corresponding to each sample point To ensure that the approximate linear result lies on the sample surface, To linearize the error threshold, The first The linear fitting coefficients of each hyperplane are the linearization parameters that satisfy the linear error threshold requirement. The nonlinear frequency safety index constraint is then finally reconstructed as follows: .

[0028] It should be noted that: Extreme values ​​of frequency deviation in each sub-region divided by S3 Its constraint limit In comparison, the system skew coefficient ranges from subregion for None of them can meet their limits. The unsafe sub-region of the constraint, from the perspective of frequency safety constraints, is an unreachable region of system frequency modulation parameters and can therefore be ignored; while the range with a large droop coefficient... Corresponding sub-region for All of them meet their safety limits. The frequency safety sub-region represents a frequency modulation parameter range that is equivalent to the frequency safety constraint; while the droop coefficient range located between the two intersection points... Subregions within Some sample points in the middle can meet the frequency security constraint limits, only sub-regions To further convert into equivalent frequency modulation parameters that are easy to incorporate into the system. and linear region in the form of a linear combination of

[0029] The application will be further described below through experiments: Take the annual frequency modulation range index evaluation of the inventory resources of the improved IEEE HRP-38 system in the future planning scenario as an example. Figure 2 To test the system topology, the total capacity of the synchronous generating units, WTs and PVs of the system is modified to 140.14 GW, 60.72 GW and 101.14 GW, and the proportion of new energy is more than 50%. The annual source-load prediction data is generated by the K-means clustering method to generate 8 typical days.

[0030] 1. Effect verification of the adaptive partition reconstruction method The effectiveness of the reconstruction method proposed in the application is verified by comparing the calculation performance and accuracy of the frequency safety index adaptive partition reconstruction method proposed in the application with the traditional piecewise linear method widely used in current research. The feasible frequency modulation parameter range of the HRP-38 system is taken as the original parameter space, and the linear results of a sample curve of different methods under the same error limit are shown in Figure 3 , wherein Figure 3 (a) is the adaptive partition reconstruction method proposed in the application; Figure 3 (b) is the traditional piecewise linear method. The traditional method generates 16 linear subspaces, while the method proposed in the application only needs 2. It can be seen that the adaptive region division reconstruction method of the application greatly reduces the unsafe subregion , greatly narrows the frequency modulation parameter range that needs to be linearized, and divides the frequency safety subregion equivalent to the frequency safety constraint that does not need to be linearized , greatly narrows the frequency modulation parameter range that needs to be linearized, and greatly reduces the number of linear models and intermediate variables representing the piecewise range.

[0031] 2. Application verification of multiple operating scenarios In order to further verify the advantages and adaptability of the frequency safety index adaptive partition reconstruction method proposed in the application applied to the multiple operating scenarios of the power system, four kinds of multi-scenario optimization operation models are set in the HRP-38 system to compare and analyze the solving performance of the method proposed in the application and the traditional piecewise linear method applied to the multiple operating scenarios of the power system containing different frequency modulation resources and different model scales: Model 1: HRP-38 system inventory unit multi-scenario operation model; Model 2: Gas-electric generating units with the same total installed capacity are respectively connected to the HRP-38 system multi-scenario operation model; Model 3: Pumped storage units with the same total installed capacity are respectively connected to the HRP-38 system multi-scenario operation model; Model 4: New energy access to HRP-38 system multi-scenario operation model with equal total installed capacity; After solving the four models with frequency security index constraints by the two methods respectively, the model size and solving time of all examples under the two methods are shown in Table 1: Table 1 ; The subspace of the method of the application is greatly reduced, resulting in a smaller scale of the various multi-scenario operation models than the traditional method. The number of intermediate variables and constraints of the method of the application in the four models is reduced by 13.46% / 45.87%, 9.92% / 32.58%, 9.82% / 32.61%, and 11.23% / 37.57% respectively compared with the traditional method. Therefore, the method of the application greatly enhances the solving effect of the operation model, and the solving time of the four evaluation models is only 1 / 2.85, 1 / 2.59, 1 / 4.88, and 1 / 4.80 respectively of the traditional method. It is worth noting that the enhancement of the solving efficiency of the method of the application is not only due to the much smaller model scale, but also the tighter linearization region avoids linearization of the subspace with too large or too small slope, thereby obtaining linear coefficients with smaller order, which reduces the coefficient range of the evaluation model and contributes to the enhancement of the solving efficiency. The maximum input parameter range of the method of the application is 10 5 , while that of the traditional method is 10 9 . The evaluation objectives solved by the two methods are basically the same, indicating the effectiveness of the method of the application.

[0032] The frequency deviation extreme value index obtained by solving the four models using the frequency safety index reconstruction method of the application is shown in Table 2. Figure 4 It can be seen that the frequency minimum point of different models is kept within the threshold . The accuracy of the proposed frequency safety index adaptive partition reconstruction method is further verified by the frequency response simulation on the simulink simulation platform for model 1. The system frequency simulation at a certain time is shown in Table 3. Figure 5 The relative error between the accurate simulation value of the frequency deviation extreme value obtained by simulation and the linear analytical value obtained by planning is 0.0263, which is within the pre-defined linear error threshold of 0.05, indicating the effectiveness of the frequency safety index reconstruction method of the application. Figure 6 The time length proportion of the frequency modulation parameter in each subspace obtained by solving the four models is shown in Table 4.

[0033] In summary, the method of the present application narrows the feasible range of frequency modulation parameters by region division, greatly reduces the model scale by tightening the piecewise linear region, and avoids high-order linearization coefficients, thereby having higher precision and computational efficiency compared with the traditional piecewise linear method.

[0034] The above examples are only used to illustrate the technical solutions of the present application, but not limit the present application; although the present application has been described in detail with reference to the foregoing examples, those skilled in the art should understand that the technical solutions recorded in the foregoing examples can be modified, or some technical features can be replaced equivalently; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application.

Claims

1. A method for adaptive partitioned reconstruction of frequency security indicators in multi-scenario power systems, characterized in that, Includes the following steps: S1. Under the preset active power disturbance Below, the runtime of each running scenario will be... Extreme values ​​of frequency deviation at time As a nonlinear frequency safety indicator, The frequency deviation threshold that does not exceed the maximum frequency required to ensure that the system's safety and stability devices are not triggered To constrain nonlinear frequency safety indicators; based on the system's multi-type frequency regulation resource parameters, under a unified synchronous unit response time constant. Under the given conditions, construct the system's equivalent frequency modulation parameters; based on the system's equivalent frequency modulation parameters, construct the nonlinear frequency safety index constraints and their analytical expressions. The system's equivalent frequency modulation parameters include: system equivalent inertia. Adjustment coefficient and reheat time coefficient ; S2. Obtain , and The maximum feasible range is taken as the feasible range of the original frequency modulation parameters, and sampling is generated within the feasible range of the original frequency modulation parameters. Each sample point and its corresponding data And obtain the corresponding sample surface set. ; S3. Obtain Feasible range of original frequency modulation parameters The corresponding sample surface, traversed and The corresponding sample surface set and The intersection points of the nonlinear frequency safety index and its constraint limit on the feasible range boundary of the original frequency modulation parameters are obtained respectively, and the droop coefficient corresponding to the obtained intersection points is used as the basis for the calculation. and The feasible range of the original frequency modulation parameters is re-partitioned to obtain the partitioned sub-regions; S4. Linearize the sub-regions that need to be linearized and output the linearization parameters that meet the linear error threshold requirements. After reconstructing the nonlinear frequency safety index constraints, the frequency safety index constraints after partition linearization are obtained.

2. The adaptive partitioning reconstruction method for frequency security indicators of a multi-scenario power system according to claim 1, characterized in that, The various types of frequency regulation resources include: synchronous generator units, converter-based new energy generator units, and pumped storage; the parameters of the various types of frequency regulation resources include: the installed capacity of each type of frequency regulation resource, the inertial time constant, primary frequency regulation droop coefficient, governor response time constant and turbine reheat time constant of synchronous generator units, the virtual inertial time constant and virtual droop coefficient of new energy generator units, and the inertial time constant and droop coefficient of pumped storage generator units.

3. The adaptive partitioning reconstruction method for frequency security indicators of a power system in multiple scenarios according to claim 1, characterized in that, The nonlinear frequency safety index constraint in multiple scenarios is expressed as follows: ； The analytical expression for the nonlinear frequency safety index is: ； in, This is the load damping coefficient; , , and These are intermediate variables representing the nonlinear relationship of the equivalent frequency modulation parameters of the coupled system. This represents the moment when the frequency deviation reaches its extreme value.

4. The adaptive partitioning reconstruction method for frequency security indicators of a multi-scenario power system according to claim 3, characterized in that, The specific steps for constructing an analytical expression for a nonlinear frequency security index based on the system's equivalent frequency modulation parameters include: S11. Establish a multi-machine frequency dynamic response model for the system. The first-order differential equation of the system's frequency dynamic response under any given operating scenario is expressed as: ； In the formula, Let the system's equivalent inertia be given in any given operating scenario. For system frequency deviation, , and The first The first synchronous generator unit, the first Taiwan New Energy Unit and the first The primary frequency regulation response power adjustment of the pumped storage power station; , and It is a collection of synchronous generator units, new energy generator units, and pumped storage units; Among them, the primary frequency regulation power adjustment of the equivalent prime mover-governing device for synchronous generators and pumped storage units varies with frequency deviation. The transfer function of change is expressed as: ； ； In the formula, For the synchronous generator speed governor gain, This refers to the turbine coefficient of the turbine. The reheater time constant is... For the Laplace operator, This refers to the governor droop coefficient of a pumped storage power station. and These are the response time constants of the pumped storage reversible pump turbine and the guide vanes, respectively. For superposition and Equivalent response time constants of pumped storage units after two different response time constants; New energy generating units based on converters participate in frequency response through virtual droop control. Their primary frequency regulation power model is as follows: ； In the formula, This represents the droop factor of the virtual synchronizer. This is the response time constant of the virtual synchronizer; S12. Response time constant of unified synchronous generator units Then, the multi-machine frequency dynamic response model of the system containing multiple scenarios is aggregated into a system equivalent frequency modulation parameter model that varies with each scenario over time: ； In the formula, , and These are the virtual inertial time constants for synchronous generators, pumped storage units, and new energy generators, respectively. , and This refers to the installed capacity of synchronous generating units, pumped storage units, and new energy generating units. As the baseline capacity, This is the start / stop status variable for the synchronous generator unit; 1 indicates start-up, and 0 indicates stop. This represents the state variable for pumped-storage hydropower generation; it is 1 in the power generation state and 0 in the pumping state. , and These are state variables indicating whether frequency support is provided for synchronous generators, pumped storage units, and new energy generators, respectively. The value is 1 when frequency support is provided and 0 when frequency support is not provided. S13. Based on the system's equivalent frequency modulation parameter model, the nonlinear frequency safety index constraint in the time domain and its analytical expression are derived using the inverse Laplace transform.

5. The adaptive partitioning reconstruction method for frequency security indicators of a multi-scenario power system according to claim 1, characterized in that, The specific content of S2 includes: S21. Based on all current frequency modulation resource parameters of the system , and Calculate the minimum and maximum frequency support schemes to obtain the maximum feasible range of system frequency modulation parameters as the original feasible range of frequency modulation parameters. , and The feasible range of the original frequency modulation parameters is: ； S22. Based on Latin hypercube sampling Internally generate sample points considering all possible unit combinations and resource frequency support schemes, where the first... Each sample point is represented as , and according to Calculate the extreme values ​​of frequency deviation for all sample points. , of which The extreme values ​​of frequency deviation corresponding to each sample point are denoted as ; S23. Adjust the frequency parameters from all sample points. Choose any sample value from the dimensions In determining Obtain the sample surface set under the following conditions: ,in, Indicates the first The extreme coordinates of the frequency deviation corresponding to each sample point It represents the three-dimensional real number space.

6. The adaptive partitioning reconstruction method for frequency security indicators of a power system in multiple scenarios according to claim 1, characterized in that, The specific details of obtaining the intersection point of the nonlinear frequency safety index and its constraint limit on the feasible range boundary of the original frequency modulation parameters in S3 include: S31. Obtain Feasible range of original frequency modulation parameters The corresponding sample surface will and The corresponding set of sample surfaces is defined as and : ； ； In the formula, and They represent and The corresponding extreme coordinates of frequency deviation and They represent and The corresponding adjustment coefficient, and They represent and The corresponding extreme value of frequency deviation; S32. Obtain the nonlinear frequency safety index and its constraint limits. The intersection points on the boundaries of the feasible range of the original frequency modulation parameters include: (1) For the index set Perform initialization, that is, let ,in , Indicates the first The extreme value of frequency deviation corresponding to each sample point Is the value the same as Equal binary indexes, when equal When they are not equal ; (2) Iterate through the subset For all sample points, if the extreme value of the frequency deviation corresponding to the sample point is... If they are equal, then set the current binary index. Update the index set with this value. ,otherwise Update the index set with this value. ; (3) Obtaining satisfaction adjustment coefficient , represented as: ,in, For the present The preceding binary indicator index, corresponding to the sample point That is, the sample points on the system inertia boundary where the nonlinear frequency safety index is equal to the frequency safety constraint limit; (4) Obtain according to steps (1)-(3) Corresponding adjustment coefficient and the corresponding sample points .

7. The adaptive partitioning reconstruction method for frequency security indicators of a multi-scenario power system according to claim 1, characterized in that, In S3, the feasible range of the original frequency modulation parameters is re-partitioned based on the droop coefficients corresponding to the obtained intersection points, resulting in sub-regions. , and They are respectively: ； ； ； in, and They are respectively The minimum and maximum values, and They are respectively The minimum and maximum values, and They are respectively The minimum and maximum values.

8. The adaptive partitioning reconstruction method for frequency security indicators of a power system in multiple scenarios according to claim 7, characterized in that, The specific content in S4 includes: S41. Discard completely unsafe subregions. Preserve a completely secure sub-region For partially secure sub-regions Perform linearization: Linear hyperplane fitting method is used for sub-regions Linearization of the frequency deviation extreme value model within: The linear optimization model is used to fit the extreme value of the nonlinear frequency deviation to the nearest value. The linear form model of the frequency modulation parameters, sub-region Nonlinear frequency deviation extremes The sample surface is approximated as a series of linearly fitted planes; the linear optimization model is: ； in, For the first The approximation error corresponding to each sample point To ensure that the approximate linear result lies on the sample surface, To linearize the error threshold, The first The linear fitting coefficients of each hyperplane are the linearization parameters that satisfy the linear error threshold requirement. The nonlinear frequency safety index constraint is then finally reconstructed as follows: 。

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