A power system frequency security constraint scheduling method considering variable parameter characteristics of thermal power units

Abstract

The application discloses a power system frequency safety constraint scheduling method considering variable parameter characteristics of thermal power generating units, belongs to the field of power system optimal scheduling and frequency safety analysis, and considers the characteristics that the frequency response capability of a TPU changes with operating power, thereby avoiding an aggressive and unrealistic scheduling scheme caused by excessively optimistic assumptions on the PFR capability of the TPU; meanwhile, the method considers frequency safety indexes under positive and negative bidirectional power disturbances, reasonably constrains the frequency safety indexes under potential positive and negative power disturbances, guarantees the ability of the system to resist frequency fluctuation under random disturbance events, avoids overestimation of the performance of the system under conventional rating assumptions, thereby reduces decision risks, and guarantees the frequency safety of power system operation.

Description

Technical Field

[0001] This invention belongs to the field of power system optimization scheduling and frequency security analysis, and more specifically, relates to a power system frequency security constraint scheduling method that considers the variable parameter characteristics of thermal power units. Background Technology

[0002] The frequency instability risk of wind-rich power systems during operation should not be underestimated. On the one hand, the intermittency and volatility of wind power exacerbate the random power disturbances experienced by the system. On the other hand, large-scale wind power development encroaches on the output capacity of thermal power units (TPUs), weakening their primary frequency regulation (PFR) and inertia support quality of service. To address these challenges, it is crucial to ensure sufficient TPU deployment through frequency security-constrained dispatch (FSCD). FSCD ensures sufficient total operating inertia and PFR reserves provided by frequency regulation resources such as TPUs and battery energy storage (BES) within the power system by constraining frequency security indicators under potential power disturbances, thereby enhancing the system's disturbance resilience.

[0003] Existing FSCD methods have certain limitations. Firstly, they typically only consider positive power disturbances such as sudden load increases and sudden wind power decreases. However, achieving frequency security under positive disturbances does not guarantee success under negative disturbances. If similar frequency security constraints are not applied under negative disturbances, the frequency after dispatch plan execution may be excessive, leading to power system security risks. Secondly, in modeling the frequency response of TPUs, existing methods often employ simplified, constant-parameter models, which overestimate the frequency regulation performance of TPUs and introduce aggressive decision-making problems, potentially causing power system security risks. Summary of the Invention

[0004] To address the aforementioned deficiencies or improvement needs of existing technologies, this invention provides a power system frequency security constraint scheduling method that considers the variable parameter characteristics of thermal power units. A variable parameter frequency response model of the TPU is constructed and introduced into the FSCD model. At the same time, frequency security constraints under bidirectional power disturbances are considered, thereby further improving the security of FSCD decision-making.

[0005] To achieve the above objectives, according to a first aspect of the present invention, a power system frequency security constraint dispatch method considering the variable parameter characteristics of thermal power units is provided, wherein the power system includes thermal power unit TPU, wind farms, and battery energy storage BES, and the method includes: With the goal of minimizing the total operating cost of the power system, a frequency security-constrained scheduling model of the power system is established, and the optimal scheduling schemes for TPU, wind farms and BES are obtained by solving the model under preset constraints. The total operating cost of the power system includes the operating cost of the TPU, start-up and shutdown costs, and wind curtailment penalty costs; the preset constraints include frequency security constraints, maximum frequency difference MFD after power disturbance, difference equation for 60-second frequency difference FD60, TPU constraints, BES constraints, wind power constraints, and power system constraints.

[0006] According to a second aspect of the present invention, an electronic device is provided, comprising: a computer-readable storage medium and a processor; The computer-readable storage medium is used to store executable instructions; The processor is configured to read executable instructions stored in the computer-readable storage medium and execute the method as described in the first aspect.

[0007] According to a third aspect of the invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to perform the method as described in the first aspect.

[0008] According to a fourth aspect of the invention, a computer program product is provided, comprising a computer program or instructions that, when executed by a processor, implement the method described in the first aspect.

[0009] In summary, compared with the prior art, the above-described technical solutions conceived by this invention can achieve the following beneficial effects: To address the frequency instability challenges of wind-rich power systems, this invention proposes a power system frequency security-constrained scheduling method considering the variable parameter characteristics of thermal power units. It takes into account the frequency response capability of the TPU (Temporary Power Unit) as a function of operating power, and the frequency security index under both positive and negative power disturbances. To address the nonlinearity of the scheduling model, an iterative solution method is proposed to achieve accurate and rapid solutions to the scheduling problem. Specifically, it has the following advantages: (1) By reasonably constraining the frequency security index under potential positive and negative power disturbances, the system’s ability to resist frequency fluctuations under random disturbance events is guaranteed.

[0010] (2) The variable parameter frequency response characteristics of TPU are taken into account, thereby avoiding the radical and unrealistic scheduling schemes caused by overly optimistic assumptions about its PFR capability. Attached Figure Description

[0011] Figure 1 This is a schematic diagram of the frequency response model of a power system; Figure 2 A schematic diagram of the frequency response model of a thermal power unit; Figure 3 This is a schematic diagram of a typical composite sliding pressure operation curve for TPU; Figure 4 A schematic diagram of the frequency response model for battery energy storage; Figure 5 A power system topology diagram provided as an example in an embodiment of the present invention; Figure 6 A schematic diagram of the TPU composite sliding operation curve provided in the example of the embodiment of the present invention; Figure 7 (a) and (b) in the examples provided by the embodiments of the invention are schematic diagrams of wind power and load power prediction curves. Figure 8 (a) to (f) are schematic diagrams of the initial RoCoF, MFD, and FD60 results under positive and negative power disturbances provided in the embodiments of the present invention. Detailed Implementation

[0012] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention. Furthermore, the technical features involved in the various embodiments of this invention described below can be combined with each other as long as they do not conflict with each other.

[0013] This invention provides a power system frequency security constraint scheduling method considering the variable parameter characteristics of thermal power units, comprising: With the goal of minimizing the total operating cost of the power system, a frequency security-constrained scheduling model of the power system is established, and the optimal scheduling schemes for TPU, wind farms and BES are obtained by solving the model under preset constraints. The total operating cost of the power system includes the operating cost of the TPU, start-up and shutdown costs, and wind curtailment penalty costs; the preset constraints include frequency security constraints, maximum frequency difference MFD after power disturbance, difference equation for 60-second frequency difference FD60, TPU constraints, BES constraints, wind power constraints, and power system constraints.

[0014] Specifically, the method provided by the present invention includes the following steps: Step A: Construct a variable parameter frequency response model for the TPU and integrate it into the overall frequency response model of the power system. Based on this, provide a method for calculating the frequency security index.

[0015] The power system includes PFR resources such as TPUs and BESs. After a power disturbance occurs in the power system, the TPUs and BESs in operation can participate in primary frequency regulation to collaboratively address the risk of frequency instability. Dispatch timing. t The corresponding frequency response model is as follows Figures 1 to 3 As shown, the variable parameters of the TPU are marked in red.

[0016] Figures 1 to 3 In Chinese, italic subscript i , j , t These are the TPU number, BES number, and scheduling time point number, respectively; variables containing the superscript ~ are in per-unit value form. s For the Laplace operator; For system frequency deviation; The frequency response coefficient of the load; The load power at the rated frequency; This represents the system power disturbance value. This indicates the TPU's running status; 1 indicates it is running, and 0 indicates it is not running. H The inertial time constant of TPU; R This refers to the TPU droop coefficient; , , , , For TPU valves, steam drum, superheater, reheater, and the time constant of the front steam chamber of the high-pressure cylinder; , , For changes in TPU valve opening, main steam pressure, and main steam flow rate; , The TPU valve opening and main steam pressure before the disturbance occurred; For the flow coefficient of TPU superheater and main steam pipeline; This refers to the overshoot coefficient of the TPU high-pressure cylinder. The power ratio of the TPU high-pressure cylinder; Rated power for TPU; This represents the change in PFR power of the TPU; , For BES virtual inertia control and droop control gain coefficients; The time constant of the BES converter; Rated power for BES; This represents the change in PFR power of the BES.

[0017] like Figure 1 As shown, The sources of disturbance are load and wind power, and the disturbance is step-like, with both positive and negative directions. Let be the inertial response function of the power system. and As shown in the following formula, where, The positive and negative signs in the equation correspond to positive and negative power disturbances, respectively. Positive and negative disturbances are defined from the perspective of the load side.

[0018]

[0019]

[0020] In the formula, , These are the power disturbances for wind power and loads, respectively.

[0021] like Figure 2 As shown, the variable parameters change with TPU power, as illustrated in the following equation:

[0022]

[0023]

[0024]

[0025] In the formula, This is the composite sliding operation function for TPU; , , , , for , The fitting coefficient; , It can be fitted as a polynomial function of power. By measuring the main steam pressure, flow rate, density, enthalpy, and other state variables of TPU at different power levels, and using these as samples, the above coefficients and polynomial function can be fitted. The TPU's constant pressure mode I, constant pressure mode II, and sliding pressure mode are as follows: Figure 3 As shown.

[0026] like Figure 4 As shown, it is assumed that BES can operate in charging, discharging, and standby modes, and can participate in PFR in any mode.

[0027] The calculation method (difference equation) for frequency security indicators is as follows: In a typical FSCD (Frequency Safety Control), frequency safety metrics usually include the initial rate of change of frequency (RoCoF) after a step disturbance, the maximum frequency deviation (MFD), and the steady-state frequency deviation. Considering the variable parameter characteristics of the TPU (Temperature Processing Unit), the frequency cannot regain stability within 60 seconds after the disturbance. Therefore, the frequency deviation at 60 s after disturbance (FD60) is used instead of the steady-state frequency deviation.

[0028] Common methods for calculating frequency security indicators include inverse Laplace transform and solving difference equations. For low-order models, the former can yield explicit expressions, but it fails for the high-order model of this invention. Therefore, difference equations can be used to calculate the frequency security indicators. Figures 1 to 3 The algebraic differential equations of the frequency response model are fully described, while the difference equations discretize these algebraic differential equations, as detailed below: (1) No. i The TPU in the first The difference equation for each scheduling time point:

[0029]

[0030]

[0031]

[0032]

[0033]

[0034]

[0035]

[0036]

[0037] Among them, italic subscripts n Indicates the number of the difference time step; This refers to the frequency difference at the TPU frequency modulation dead zone output. This refers to the frequency modulation dead zone width of the TPU; The difference step size; This represents the change in superheater steam flow rate. This represents the change in steam drum pressure. , These represent the power change and rate of change at the TPU power limiting input, respectively. This is the power limiting boundary for the TPU.

[0038] (2) No. j The BES in the first The difference equation for each scheduling time point:

[0039]

[0040]

[0041] in, This refers to the frequency difference at the BES FM dead zone exit point. The frequency modulation dead zone width of the BES; This is the power limiting boundary for BES; This represents the power change at the BES power limiting input.

[0042] (3) Load and inertia in the first The difference equation for each scheduling time point:

[0043] (4) in the Frequency safety indicators at each scheduling time point:

[0044]

[0045]

[0046] in, , , These are the initial RoCoF, MFD, and FD60 after the power disturbance, respectively. The rated frequency of the power system is 50Hz; T The duration of a single difference calculation is 60 seconds.

[0047] Step B: Construct the FSCD model of the power system.

[0048] The FSCD model of the power system is as follows: (1) Objective function

[0049]

[0050]

[0051]

[0052] In the formula, italic subscripts l Number the wind farm; , These are the operating and start-up / shutdown costs of the TPU, respectively. The cost of curtailing wind power; , These are the primary and constant operating cost coefficients for the TPU, respectively. The cost of a single start-stop cycle for the TPU; This represents the cost coefficient for wind curtailment penalties. , These are the predicted power output and the dispatched power output (i.e., planned power output) of the wind farm, respectively. Contribute to the TPU project.

[0053] (2) Frequency security constraints Frequency security constraints include difference equations used to calculate frequency security indices (including initial RoCoF, MFD, and FD60), and boundary constraints for the indices. The former has already been introduced in step A and will not be repeated here. The latter is as follows:

[0054]

[0055]

[0056]

[0057]

[0058]

[0059] In the formula, superscript , These respectively represent variables belonging to positive and negative power disturbances; , , These are the initial safety boundaries of RoCoF, MFD, and FD60 after power disturbance, respectively.

[0060] The variable parameter characteristics of TPU and the frequency security constraints under bidirectional power perturbation are both highly nonlinear, which makes the FSCD problem a large-scale mixed integer nonlinear programming problem: the difference equations used to calculate the initial RoCoF, MFD, and FD60 after power perturbation are a set of nonlinear equality constraints, involving nonlinear functions and variable products, which makes the above 6 inequality constraints nonlinear constraints and difficult to solve.

[0061] Considering that the calculation formula for the initial RoCoF after power perturbation is a low-order model, the safety boundary constraints of the initial RoCoF after power perturbation can be transformed into strict linear constraints: Due to the existence of the frequency modulation dead zone, the PFR of the TPU and BES has not yet responded at the initial moment of the disturbance. Therefore, the initial RoCoF after a power disturbance is determined only by the disturbance, load, and inertia. Figure 1 After the negative feedback response part, the remaining transfer function is as follows:

[0062] Applying the inverse Laplace transform to the above equation and taking the derivative at the initial moment, we can obtain the initial RoCoF after the power disturbance. Since the positive and negative disturbances utilize the prediction errors of load and wind power, and these errors are typically of equal amplitude (positive and negative), the initial RoCoF under both disturbances is also of equal amplitude, only in different directions, i.e.:

[0063] Substituting the above equation into the initial RoCoF safety boundary constraints, we obtain its strictly linearized form:

[0064] That is, the difference equations of the initial RoCoF after power disturbance and its frequency security constraints in the FSCD model of the power system. and This is transformed into the linear constraints described above.

[0065] Considering that the calculation formulas for MFD and FD60 after power perturbation are high-order models, the safety boundary constraints of the latter two can be handled by iterative solution methods, as described in step C.

[0066] (3) Other constraints In addition to frequency security constraints, the FSCD model also includes TPU constraints (power constraints, ramp rate constraints, start-stop time constraints), BES constraints (state constraints, power constraints, energy constraints), wind power constraints, and system constraints (power flow constraints, line power constraints, node voltage constraints, power balance constraints, and reserve constraints). These constraints are very mature and fundamental, and can be found in existing materials; they will not be elaborated upon here.

[0067] Step C: Propose a solution method for the FSCD model described in Step B.

[0068] In the MFD and FD60 constraints, there are numerous nonlinear terms arising from the variable parameter characteristics of the TPU. These terms are extensively coupled with the TPU's operational state, making conventional methods such as sequential linear programming, sequential quadratic programming, and Benders decomposition ineffective. Furthermore, the difference equations introduce a massive number of discrete variables. Even linearizing the original FSCD problem can lead to memory overflow and solution failure due to the expansion of variable size. To efficiently and accurately solve the FSCD model, this invention proposes a novel iterative solution method.

[0069] Based on an iterative solution approach, the original scheduling problem in step B is split into a main problem and subproblems. The main problem remains the FSCD problem, inheriting the objective function and most constraints of the original scheduling problem. The key difference lies in that the main problem replaces the difference equations of the frequency response model (i.e., the calculation formulas for MFD and FD60) with more idealized linear constraints. Due to the use of idealized assumptions, the main problem may generate scheduling schemes that underestimate MFD and FD60. Therefore, subproblems are introduced to further verify whether the scheduling scheme provided by the main problem meets the actual operational requirements, based on the original difference equations. The main problem and subproblems iteratively solve the FSCD model.

[0070] (1) Main problem ① The FD60 calculation method (difference equation system) under positive power disturbance should be replaced with the following linear constraints:

[0071]

[0072]

[0073]

[0074]

[0075]

[0076]

[0077]

[0078] In the formula, M For a sufficiently large positive integer, in this invention, 10 is taken. 5 That's sufficient; variable product Due to its nonlinearity, the McCormick envelope method can be used to convert it into a linear constraint. Subsequent variable products can then be handled using this method, which is an existing approach and will not be elaborated upon here. ② The FD60 calculation method (difference equation system) under negative power perturbation should be replaced with the following linear constraints:

[0079]

[0080]

[0081]

[0082]

[0083]

[0084]

[0085]

[0086] In the formula, Contribute minimal technical effort to TPU.

[0087] ③ The MFD calculation method (difference equation system) under positive power disturbance should be replaced with the following linear constraints:

[0088]

[0089]

[0090]

[0091]

[0092]

[0093]

[0094]

[0095] In the formula, , Meaning and , The symbols are the same, both representing the PFR power change of TPU and BES. The different symbols are used to emphasize that the power changes used to calculate FD60 and MFD are independent variables, not the same variable. This is the equivalent cutoff time, representing a constant of 5 seconds.

[0096] ④ The MFD calculation method (difference equation system) under negative power disturbance should be replaced with the following linear constraints:

[0097]

[0098]

[0099]

[0100]

[0101]

[0102]

[0103]

[0104] ⑤ Connection constraints In addition to the calculation methods for MFD and FD60 under positive and negative power perturbations, the main problem also needs to modify the frequency security constraints (i.e., the security constraints for MFD and FD60) described in step B to achieve smooth interaction between the main problem and sub-problems during the iteration process, and to fully realize the guiding role of sub-problems on the main problem. The modified constraints are called connectivity constraints, as follows:

[0105]

[0106]

[0107]

[0108] In the formula, , These are the upper limits imposed by the subproblems on MFD and FD60, respectively. They are updated by the subproblems based on whether the variables exceed the limits during the iteration of the main subproblem.

[0109] (2) Subproblems Because the main problem integrates the idealized linear calculation methods of MFD and FD60, its scheduling results may overstate the system's frequency regulation performance. Therefore, before issuing the power command obtained from the main problem to the TPU and BES, the subproblems should verify it based on the original frequency response model difference equations (i.e., the difference equations of MFD and FD60) from step A, fully assessing whether the formulated plan poses a risk of pushing the system's frequency safety indicators outside the safety boundary. If the scheduling plan is found to be unqualified, the subproblems will tighten the boundaries of the relevant variables, instructing the main problem to recalculate and obtain a more conservative result. This process is iterated until the scheduling result of the main problem withstands the evaluation of the subproblems.

[0110] The steps for verifying the subproblems are as follows: ① Set initial parameters.

[0111] , The initial values ​​are respectively , .

[0112] ② Solve the main problem and pass the key results to the subproblems.

[0113] The results to be transmitted include , , , , , , The superscript "MP" indicates that these variables are for solving the main problem, and their meanings are identical to their prototypes.

[0114] ③ Solve the subproblems to obtain the results used for verification.

[0115] Sub-problems will , , Substitute the difference equations of MFD and FD60 from step A to calculate , , , The superscript "SP" indicates that these variables are for solving subproblems, and their meanings are identical to their prototypes.

[0116] ④ Check the sub-problem for exceeding the safety limits of the frequency safety index and update the safety boundary.

[0117] For any scheduling time point t If it appears , , or For any out-of-bounds situation, the corresponding safety boundary is updated according to the following formula:

[0118]

[0119]

[0120]

[0121] For example, if it occurs Then the main problem will be Updated to .

[0122] ⑤ Select the iterative branch path according to different situations.

[0123] [Case 1] If at any scheduling time point t , , , , If any one of them is updated, return to step ② and start a new round of iteration.

[0124] [Scenario 2] If at any scheduling time point t If no boundary updates occur, it means that MFD and FD60 under positive and negative power perturbations at all time points are within the safe boundary. At this point, the algorithm has converged, exits the iteration, and outputs the solution to the main problem.

[0125] In step C, the solution results of the FSCD model are as follows: 1) TPU: Start-stop status Planned contribution ; 2) Wind farm: Planned output ; 3) BES: Charge / Discharge Status, Charge / Discharge Power Remaining energy; It should be noted that the charge / discharge state and remaining energy of the BES are reflected in the BES charge / discharge state constraints and energy constraints. These constraints are very mature and fundamental, and can be found in existing relevant materials. They will not be elaborated here.

[0126] 4) Optimization objective: Total system cost Wind power absorption rate.

[0127] The method provided by the present invention will be further illustrated below with a specific example.

[0128] Step A: The model in this embodiment is constructed as follows.

[0129] (1) Taking into account TPU operation constraints, BES operation constraints, wind farm operation constraints, system operation constraints, and frequency security constraints, the scheduling model is constructed with the goal of minimizing the sum of TPU operation cost, TPU start-up and shutdown cost, and wind curtailment penalty cost.

[0130] (2) For the specific mathematical expressions in the above model, please refer to the power system frequency response model and power system FSCD model described in steps A and B of the invention content.

[0131] Step B: The parameter settings for this embodiment are as follows.

[0132] (1) Implementation environment: The implementation was tested on a computer with an Intel Xeon Gold 2.70GHz CPU and 256GB of memory. The scheduling model was solved by calling Yalmip through MATLAB R2022a, and the solver was Gurobi 9.1.

[0133] (2) Optimized time scale of the example: The total scheduling time is 1 day, and the unit scheduling time is 15 minutes.

[0134] (3) Implementation example topology diagram: The topology diagram is as follows Figure 5 As shown in the figure. Where WF represents a wind farm.

[0135] (4) The basic parameters of the TPU in the embodiment are shown in Table 1: Table 1 Basic Parameters of TPU

[0136] (5) The polynomial function of the TPU high-pressure cylinder power ratio and overshoot coefficient in the embodiment is shown in the following formula:

[0137]

[0138] In the formula, , These are the rated values ​​for the power ratio of the high-pressure cylinder and the overshoot coefficient, respectively.

[0139] (6) Example of TPU , The fitting coefficients are shown in Table 2: Table 2 , Fit coefficient

[0140] (7) Example: The composite sliding pressure operation curve of TPU is as follows Figure 6 As shown.

[0141] (8) The BES parameters of the embodiment are shown in Table 3: Table 3 BES Parameters

[0142] (9) The wind power and load power prediction curves of the embodiment are as follows: Figure 7 As shown in (a) and (b) in the figure.

[0143] Step C: Optimize the solution for this embodiment and analyze the results.

[0144] To verify the effectiveness of the FSCD method proposed in this invention, four sets of case studies were set up: Case 1 considers the variable parameter characteristics of the TPU and takes into account frequency safety constraints; Case 2 is based on Case 1 but does not consider the variable parameter characteristics of the TPU; Case 3 is based on Case 1 but does not consider the variable parameter characteristics of the TPU and frequency safety constraints, and requires the TPU and BES to directly leave a PFR power adjustable margin at both ends of their power range, the size of which is equal to their power limiting ratio; Case 3 is based on Case 1 but does not consider the variable parameter characteristics of the TPU and frequency safety constraints, and does not require a direct PFR power adjustable margin.

[0145] Optimization calculations were performed on the four cases, and their wind power utilization and economic performance are shown in Table 4. Initial RoCoF, MFD, and FD60 values ​​are as follows: Figure 8 As shown.

[0146] Table 4 Comparison Indicators of Four Cases

[0147] As shown in the table above, the total costs, in descending order, are Case 3, Case 1, Case 2, and Case 4. Case 2 assumes that the frequency response characteristics of the TPU are unaffected by operating power and remain at rated conditions. Therefore, its frequency safety constraints are more lenient, resulting in better economic performance than Case 1. However, due to... Figure 6 It is evident that this approach cannot guarantee the safety of FD60. Case 3 employs a lazy strategy, requiring all TPUs and BES to maintain margins at both ends of the power range. While this crude approach reduces the risk of frequency overruns compared to Case 2, it comes at the cost of economic efficiency. Even so, FD60 overruns still exist. Case 4 completely ignores frequency safety constraints, representing purely economic scheduling. Therefore, it has the lowest total cost but the worst frequency performance. In conclusion, the proposed FSCD strategy can improve the system's frequency safety level with only a minor economic loss.

[0148] In summary, the power system FSCD method considering the variable parameter frequency response characteristics of the TPU provided by this invention objectively reflects the nature of the TPU's frequency regulation capability as operating power changes, avoiding the overestimation of its performance by conventional rated assumptions, thereby reducing decision-making risks and ensuring the frequency security of power system operation. Furthermore, the application of iterative solution methods enables safe and accurate solutions to nonlinear scheduling problems.

[0149] This invention provides an electronic device, including: a computer-readable storage medium and a processor; The computer-readable storage medium is used to store executable instructions; The processor is configured to read executable instructions stored in the computer-readable storage medium and execute the method as described in any of the above embodiments.

[0150] This invention provides a computer-readable storage medium storing computer instructions that cause a processor to perform the method described in any of the above embodiments.

[0151] This invention provides a computer program product, including a computer program or instructions, which, when executed by a processor, implement the method described in any of the above embodiments.

[0152] Those skilled in the art will readily understand that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A power system frequency security constraint dispatch method considering the variable parameter characteristics of thermal power units, wherein the power system includes thermal power unit TPU, wind farms, and battery energy storage BES, characterized in that, The method includes: With the goal of minimizing the total operating cost of the power system, a frequency security-constrained scheduling model of the power system is established, and the optimal scheduling schemes for TPU, wind farms and BES are obtained by solving the model under preset constraints. The total operating cost of the power system includes the operating cost of the TPU, start-up and shutdown costs, and wind curtailment penalty costs; the preset constraints include frequency security constraints, maximum frequency difference MFD after power disturbance, difference equation for 60-second frequency difference FD60, TPU constraints, BES constraints, wind power constraints, and power system constraints.

2. The method as described in claim 1, characterized in that, The frequency security constraint is: in, The rated frequency of the power system. For the first Power disturbance of a wind farm For scheduling time points The power disturbance of the load. , , These are the initial safety boundaries of RoCoF, MFD, and FD60 after the power disturbance. For the first Each TPU at the scheduling time point The running status is 1 if running, and 0 otherwise. For the first The rated power of each TPU, For the first i The inertial time constant of each TPU, , These are the scheduling time points. MFD after positive and negative power disturbances , These are the scheduling time points. FD60 after positive and negative power disturbances; , Total scheduling duration; , This represents the total number of wind farms.

3. The method as described in claim 2, characterized in that, Solving the frequency security constraint scheduling model under preset constraints includes: S1, replace the difference equations of MFD and FD60 after power disturbance in the frequency security constraint scheduling model with the corresponding linear constraints, and change the frequency security constraints in the frequency security constraint scheduling model. , , , Replace them one by one with , , , The replaced frequency security constraint scheduling model is taken as the main problem; in, , These are the scheduling time points. The upper limit of MFD after positive and negative power perturbations , These are the scheduling time points. The upper limit of FD60 after positive and negative power perturbations; S2, let ,Will , The initial value is set to ,Will , The initial value is set to ; S3, Solve the main problem, and extract the solution results from... , , Substituting the difference equations of MFD and FD60 after the power disturbance, we can obtain... , , , approximation , , , ; S4, determine if it occurs , , or If any of the following conditions are met, then the corresponding upper bound in the main problem will be increased. , , or Updated to , , or Return to S3, otherwise... Updated to Return to S3 until Output the solution to the main problem and use it as the optimal scheduling scheme for TPU, wind farm and BES; in, , , , The results obtained from solving the main problem are respectively , , , The estimated value.

4. The method as described in claim 3, characterized in that, The linear constraint corresponding to the difference equation of the MFD after positive power perturbation is: in, For the first Each TPU at the scheduling time point The change in PFR power after a positive power disturbance. For the first Each BES at the scheduling time point The change in PFR power after a positive power disturbance. , For the total number of BES, For the first The rated power of each TPU, For the first The droop factor of each TPU For the first Before the disturbance occurs at the scheduling time point, the [number]th [time point] i The per-unit value of the main steam pressure of each TPU. For the first The per-unit value of MFD after a positive power disturbance at each scheduling time point. For the first The per-unit value of the frequency modulation dead zone width of each TPU. For the first Each TPU at the scheduling time point The power ratio of the high-pressure cylinder, For the first Each TPU at the scheduling time point The overshoot coefficient of the high-pressure cylinder, For equivalent truncation time, For the first Each TPU at the scheduling time point The time constant of the high-pressure cylinder front chamber, , For the first Each TPU at the scheduling time point The plan is to contribute efforts. For the first Power limiting boundary of each TPU For the first The droop control gain coefficient of each BES. For the first The rated power of each BES For the first Each BES at the scheduling time point The plan is to contribute efforts. For the first The power limiting boundary of each BES The frequency response coefficient of the load. For the first Load power at the rated frequency at each scheduling time point; The linear constraint corresponding to the difference equation of the MFD after negative power perturbation is: in, For the first Each TPU at the scheduling time point The change in PFR power after a negative power disturbance. For the first Each BES at the scheduling time point The change in PFR power after a negative power disturbance. For the first Minimum technical output of the rated power of a TPU For the first The per-unit value of MFD after negative power disturbance at each scheduling time point; The linear constraints corresponding to the difference equation of FD60 after positive power perturbation are: in, For the first Each TPU at the scheduling time point The change in PFR power after a positive power disturbance. For the first Each BES at the scheduling time point The change in PFR power after a positive power disturbance. For the first The per-unit value of FD60 after a positive power disturbance at each scheduling time point; The linear constraints corresponding to the difference equation of FD60 after negative power perturbation are: in, For the first Each TPU at the scheduling time point The change in PFR power after a negative power disturbance. For the first Each BES at the scheduling time point The change in PFR power after a negative power disturbance. For the first The per-unit value of FD60 after negative power disturbance at each scheduling time point.

5. The method as described in claim 1, characterized in that, The operating cost of the TPU The calculation formula is: , For the first The operating cost of a single TPU is calculated using a coefficient. For the first The operating cost of a TPU is a constant factor. For the first Each TPU at the scheduling time point The plan is to contribute efforts. For the first Each TPU at the scheduling time point The running status; The start-up and shutdown costs of the TPU The calculation formula is: , No. The cost per start-stop cycle for the TPU. For the first Each TPU at the scheduling time point The running status; The cost of wind curtailment penalty The calculation formula is: , The cost coefficient for wind curtailment penalties. For the first Each wind farm at the dispatch time point The predicted output For the first Each wind farm at the dispatch time point They contributed to the plan.

6. An electronic device, characterized in that, include: Computer-readable storage media and processors; The computer-readable storage medium is used to store executable instructions; The processor is configured to read executable instructions stored in the computer-readable storage medium and execute the method as described in any one of claims 1-5.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing a processor to perform the method as described in any one of claims 1-5.

8. A computer program product, comprising a computer program or instructions, characterized in that, When the computer program or instructions are executed by a processor, they implement the method as described in any one of claims 1-5.

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