A method for quantitatively evaluating system frequency characteristics considering frequency quadratic drop

Abstract

The application relates to a system frequency characteristic quantification evaluation method considering frequency secondary drop, and belongs to the technical field of power system frequency modulation. The method first considers the relationship between the system overall frequency response characteristic and the power response Delta P L (s) of each power generation device and the frequency-active transfer function G(s) of each power generation device in a multi-machine power system containing power generation devices e (s) is expressed by a frequency common mode component Delta omega (s); through an iterative algorithm, the power response under disturbance of each power generation device is approximated by using a differential-proportional-first-order lag structure for the frequency common mode component, and a frequency modulation capacity quantification parameter is obtained; the frequency characteristic quantification index is calculated by using the obtained frequency modulation capacity quantification parameter, and is compared with a frequency characteristic critical value allowed by the system to perform frequency characteristic evaluation. The application determines whether the system frequency minimum point and the system frequency average change rate meet the system frequency modulation requirement through frequency characteristic evaluation, so that frequency modulation is realized.

Description

Technical Field

[0001] This invention belongs to the field of power system frequency regulation technology and relates to a method for evaluating the frequency characteristics of a power system, specifically a method for quantitatively evaluating the frequency characteristics of a system that takes into account the second frequency drop. Background Technology

[0002] In recent years, the penetration rate of new energy sources such as wind and solar power in the power system has been continuously increasing. Since new energy sources generally operate in maximum power point tracking mode and do not participate in frequency regulation, this reduces system inertia and frequency regulation capability, adversely affecting system frequency stability. To address this, scholars at home and abroad have proposed control strategies for new energy sources to actively participate in frequency regulation upon grid connection.

[0003] Wind turbines are typically connected to the grid via converters, decoupling their rotor speed from the power system frequency. To utilize the kinetic energy in the turbine rotor to support the frequency, additional frequency regulation control is required. During frequency support, the turbine releases rotor kinetic energy, causing its speed to decrease. Once the rotor reaches its minimum speed limit, it can no longer release kinetic energy to support the system frequency; instead, it needs to absorb power from the grid to increase its speed, potentially leading to a secondary frequency sag. Currently, wind turbine frequency regulation parameters are generally set based on the wind power's own adjustable frequency resources, without considering the secondary frequency sag. This parameter setting allows the turbine to provide as much active power support as possible during the first frequency sag, but correspondingly, it needs to absorb more power to restore rotor speed during the second frequency sag. This may result in the lowest point of the secondary sag being lower than the first sag, which is detrimental to system frequency stability.

[0004] Therefore, to provide effective frequency support for the system and meet its actual frequency regulation requirements, the entire frequency dynamic process, including both primary and secondary frequency drops, needs to be comprehensively considered. To achieve this, the entire frequency dynamic process needs to be analyzed. Analyzing the frequency dynamics requires combining models of all power generation equipment in the system; however, considering detailed models of each device simultaneously can lead to difficulties in analyzing the frequency response due to excessively high model orders. Therefore, it is necessary to find a suitable transfer function structure to approximate the models of each power generation device, thereby simplifying the analysis and effectively quantifying and evaluating the required frequency characteristics. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of existing technologies, effectively evaluate the frequency regulation effect of wind turbine units, and provide a quantitative evaluation method for system frequency characteristics that takes into account the second frequency drop. This method can quantitatively analyze the average rate of change of frequency, the first minimum frequency point, and the second minimum frequency point through parameters with very simple form.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows:

[0007] A method for quantitatively evaluating the frequency characteristics of a system that takes into account frequency dips includes the following steps:

[0008] Step (1): In a multi-machine power system containing power generation equipment, power disturbances are considered. Below, the overall frequency response characteristics of the system and the power response of each power generation device are analyzed. Frequency-active power transfer function of each power generation device The relationship between the two systems; the overall frequency response characteristics of the system described use the frequency common-mode component. express;

[0009] Step (2): Through iterative algorithm, for the frequency common mode component, the power response of each power generation device under disturbance is approximated by the differential-proportional-first-order lag structure, and four frequency regulation capability quantification parameters are obtained: effective inertia, effective damping coefficient, effective static droop coefficient and system droop time constant.

[0010] Step (3): Calculate the frequency characteristic quantization index using the frequency modulation capability quantization parameters obtained in step (2);

[0011] Step (4) compare the frequency characteristic quantification index obtained in step (3) with the frequency characteristic threshold value allowed by the system to evaluate the frequency characteristics.

[0012] Furthermore, preferably, the power generation equipment includes a synchronous machine and a wind turbine.

[0013] Furthermore, preferably, the specific method of step (1) is as follows:

[0014] A multi-machine power system has a total of n frequency-modulated power generation devices; G i (s) is the frequency-power transfer function of the i-th power generation device. ; Let be the active power generated by the i-th generating device; the power disturbance is . , s represents the Laplace operator. Indicates the magnitude of the disturbance;

[0015] System frequency common-mode components With power disturbance The relationship is as follows:

[0016] .

[0017] Furthermore, preferably, the specific method of step (2) is as follows:

[0018] The expression for the differential-proportional-first-order hysteresis structure is:

[0019]

[0020] In the formula, J u Du and K u These are respectively represented as effective inertia, effective damping coefficient, and effective static droop coefficient, with T0 being the system droop time constant;

[0021] By approximating each device as a differential-proportional-first-order hysteresis structure parameter optimization problem, the following iterative algorithm is used to obtain four frequency modulation capability quantification parameters: effective inertia, effective damping coefficient, effective static droop coefficient, and system droop time constant.

[0022] 2.1) Set initial values ​​for the inertia parameters, damping parameters, static droop parameters, and droop time parameters of the differential-proportional-first-order lag structure of each power generation device, thereby obtaining the initial differential-proportional-first-order lag structure of each device. and the system's initial differential-proportional-first-order hysteresis structure :

[0023]

[0024]

[0025] in, , and These represent the initial values ​​of the inertia parameter, damping parameter, and static droop parameter for each generator's differential-proportional-first-order lag, respectively. This represents the initial value of the system descent time parameter; , , Let these represent the initial inertia parameter, damping parameter, and static droop parameter of the system, respectively, satisfying... , , S i This is expressed as the rated capacity of each power generation device;

[0026] 2.2) Let the inner loop variable r = 1; the outer loop variable j = 1;

[0027] 2.3) In the r-th iteration, the frequency trajectory is obtained according to the following formula. ;

[0028]

[0029] in, This indicates the differential-proportional-first-order lag structure of the generator system during the (r-1)th iteration. This represents the frequency trajectory corresponding to the common-mode component of the (r-1)th iteration.

[0030] 2.4) Establish the following parameter optimization problem:

[0031]

[0032] Among them, t0, t f These represent the initial and final times of the selected time period, respectively. The initial moment of the disturbance; The frequency-active power transfer function of each power generation device The calculated power trajectory, Differential-proportional-first-order lag structure for each power generation device Calculated power trajectory; power trajectory Obtained by inverse Laplace transform Power trajectory Obtained by inverse Laplace transform ;

[0033] The optimization problem is solved using the least squares method to obtain the parameters. , and ;

[0034] 2.5) Let r = r + 1, and repeat steps 2.2) to 2.4) until the parameters converge. Record the obtained equivalent parameters; the equivalent parameters are... , , ;

[0035] 2.6) Exit the inner loop and enter the outer loop, let ;

[0036] 2.7) Let j = j + 1, and repeat steps 2.2) to 2.7) until the optimal value is found, thus obtaining the equivalent parameters of the unified structure. , , , .

[0037] Furthermore, preferably, t f Set to 4t nadir , t nadir The moment when the frequency trajectory reaches its lowest point; The value range is -0.5 to 0.5.

[0038] Furthermore, preferably, the specific method of step (3) is as follows:

[0039] The approximate frequency time-domain analytical expression is:

[0040] In the formula,

[0041]

[0042] Among them, J us1D us1 1 / K us1 J represents the system uniform structure effective coefficient when wind turbines participate in frequency regulation. us2 D us2 1 / K us2 This represents the coefficient after the wind turbine is removed from frequency regulation; step (2) yields the effective coefficients of all power generation equipment in the system, which are then summed to obtain the system's effective coefficient J. us1 D us1 1 / K us1 J us2 D us2 1 / K us2 The system efficiency coefficient after removing the wind power equivalent coefficient; , These represent the damped oscillation frequencies during the first and second frequency drops of the system, respectively. , These represent the attenuation coefficients during the first and second frequency drops of the system, respectively; t1 represents the time when the wind turbine exits frequency regulation. This represents the system input power disturbance at time t1;

[0043] Frequency characteristic indicators include the average rate of change of frequency. The frequency dropped to its lowest point. and the lowest point of the second frequency drop It is obtained using the following formula:

[0044]

[0045]

[0046] In the formula,

[0047]

[0048] Among them, t p2max The moment when the second maximum frequency deviation occurs; e is the natural constant, n t =t p1max / t p1 , t p1max The time t is when the maximum frequency deviation occurs. p1 This indicates the time t after the disturbance occurs. p1 The time point used for the average rate of change of internal frequency.

[0049] Furthermore, preferably, the specific method of step (4) is as follows:

[0050] Based on the frequency characteristic index obtained in step (3): the lowest point of the first frequency drop The lowest point of the second frequency drop and the average rate of change of frequency Three indicators are used to evaluate frequency characteristics; specifically:

[0051] 4.1) Evaluation of the lowest point of frequency characteristics:

[0052] When calculated , All are less than the minimum allowable frequency threshold of the system. When the system frequency is at its lowest point, the system frequency regulation requirement is met, and proceed to 4.2); otherwise, it is not met.

[0053] 4.2) Evaluation of frequency change rate:

[0054] When calculated Less than the system's allowable average rate of change critical value When the system frequency average rate of change is within a certain range, it meets the system frequency regulation requirements; otherwise, it does not.

[0055] In this invention, there are no specific restrictions on setting the initial values ​​of the inertia parameters, damping parameters, static droop parameters, and droop time parameters of the differential-proportional-first-order lag structure of each power generation device; the initial values ​​can be set arbitrarily.

[0056] Compared with the prior art, the beneficial effects of this invention are as follows:

[0057] This invention can approximate the frequency response of various power generation devices in a power system that covers the second frequency drop process using a very simple differential-proportional-first-order hysteresis structure. Because the frequency trajectory is considered in the parameter acquisition process, the accuracy is high. Based on the inertia-damped-integral first-order hysteresis structure, it can obtain the first and second minimum points of frequency and the average rate of change, effectively evaluating the dynamic frequency characteristics involved in the second frequency drop process caused by wind turbine frequency regulation. By evaluating the frequency characteristics, it can determine whether the system frequency minimum point and the system frequency average rate of change meet the system frequency regulation requirements, thereby realizing frequency regulation. Attached Figure Description

[0058] Figure 1 This is a flowchart illustrating the method of the present invention.

[0059] Figure 2 This is a schematic diagram of the three-machine system in the simulation verification of an embodiment of the present invention.

[0060] Figure 3 This is a model diagram of the turbine governor system in the simulation verification of an embodiment of the present invention.

[0061] Figure 4 This is a power control diagram of a wind turbine generator in a simulation verification of an embodiment of the present invention.

[0062] Figure 5 The following are comparison diagrams of the simulated trajectory and the approximate trajectory of the differential-proportional-first-order lag structure in the simulation verification of the embodiments of the present invention; wherein, (a) is a comparison diagram of the simulated trajectory of the wind turbine without frequency regulation and the approximate trajectory of the differential-proportional-first-order lag structure in the simulation verification of the embodiments of the present invention; (b) is a comparison diagram of the simulated trajectory of the wind turbine with frequency regulation and the approximate trajectory of the differential-proportional-first-order lag structure in the simulation verification of the embodiments of the present invention.

[0063] Figure 6 An iterative flowchart for solving the optimization problem. Detailed Implementation

[0064] The present invention will now be described in further detail with reference to the embodiments.

[0065] Those skilled in the art will understand that the following embodiments are for illustrative purposes only and should not be construed as limiting the scope of the invention. Where specific techniques or conditions are not specified in the embodiments, they are performed in accordance with the techniques or conditions described in the literature in the field or according to the product instructions. Materials or equipment whose manufacturers are not specified are all conventional products that can be obtained by purchase.

[0066] 1) In multi-machine power systems that include generating equipment (such as synchronous generators, wind turbines, etc.), power disturbances should be considered. Below, the overall frequency response characteristics of the system (frequency common-mode component) and the power response of each power generation device Frequency-active power transfer function of each power generation device The relationship between them;

[0067] 2) Through iterative algorithms, for the frequency common-mode components, the power response of each power generation device under disturbance is approximated by a differential-proportional-first-order lag structure (i.e., a unified structure), to obtain the approximate power trajectory, and to obtain four parameters: effective inertia, effective damping coefficient, effective static droop coefficient, and system droop time constant.

[0068] 3) Establish frequency characteristic quantization indicators using the above-mentioned frequency modulation capability quantization parameters;

[0069] 4) Use the frequency characteristic index calculation formula to obtain the system frequency characteristic quantification result, compare it with the system's allowable frequency characteristic critical value, and conduct frequency characteristic evaluation;

[0070] In step 1), the multi-machine power system has a total of n frequency-regulating generating devices (to consider the dynamic response of loads and other equipment, these can be treated as special generators); establish the overall frequency response characteristics of the system (frequency common-mode components). With power disturbance The relationship is as follows:

[0071]

[0072] In the formula, G i (s) is the frequency-power transfer function of the i-th power generation device. ; Let be the power response of the i-th generating unit; the power disturbance that occurs (such as a sudden load increase) is . , s represents the Laplace operator. Indicates the magnitude of the disturbance;

[0073] In step 2), the differential-proportional-first-order hysteresis structure is as follows:

[0074]

[0075] In the formula, J u D u and K u These are respectively represented as effective inertia, effective damping coefficient, and effective static droop coefficient, with T0 being the system droop time constant;

[0076] By approximating each device as a differential-proportional-first-order hysteresis structure parameter optimization problem, the following iterative algorithm is used to obtain four frequency modulation capability quantification parameters: effective inertia, effective damping coefficient, effective static droop coefficient, and system droop time constant.

[0077] 2.1) Set the initial values ​​for the inertia parameters, damping parameters, static droop parameters, and droop time parameters of the differential-proportional-first-order lag structure of each power generation device, and calculate the initial differential-proportional-first-order lag structure of each device. and the system's initial differential-proportional-first-order hysteresis structure :

[0078]

[0079]

[0080] in, , and These represent the initial values ​​of the inertia parameter, damping parameter, and static droop parameter for each generator's differential-proportional-first-order lag, respectively. This represents the initial value of the system descent time parameter; , , Let these represent the initial inertia parameter, damping parameter, and static droop parameter of the system, respectively, satisfying... , , S iThis is expressed as the rated capacity (per unit value) of each power generation device;

[0081] 2.2) Let the inner loop variable r = 1; the outer loop variable j = 1;

[0082] 2.3) In the r-th iteration, the frequency trajectory is obtained according to the following formula. ;

[0083]

[0084] in, This indicates the differential-proportional-first-order lag structure of the generator system during the (r-1)th iteration. This represents the frequency trajectory corresponding to the common-mode component of the (r-1)th iteration.

[0085] 2.4) Establish the following parameter optimization problem:

[0086]

[0087] Where t0, t f These represent the initial and final times of the selected time period, respectively. At the initial time of the disturbance, t f 4t is generally selected. nadir , t nadir The moment when the frequency trajectory reaches its lowest point; The frequency-active power transfer function of each power generation device The calculated power trajectory, Differential-proportional-first-order lag structure for each power generation device Calculated power trajectory; power trajectory Obtained by inverse Laplace transform Power trajectory Obtained by inverse Laplace transform ;

[0088] The objective function is solved using the least squares method to obtain the parameters. , and ;

[0089] 2.5) Let r = r+1, and repeat steps 2.2) to 2.4) until the parameters converge. Record the obtained equivalent parameters. , , ;

[0090] 2.6) Exit the inner loop and enter the outer loop, let , The value range is -0.5 to 0.5 (use the larger value first). Search for the possible range where the optimal T0 might appear, and then use a smaller range. (Search within the optimal interval)

[0091] 2.7) Let j = j + 1, and repeat steps 2.2) to 2.7) until the optimal value is found, thus obtaining the equivalent parameters of the unified structure. , , , .

[0092] In step 3), the approximate frequency trajectory under step disturbance can be obtained based on the unified structural parameters obtained through iterative optimization:

[0093]

[0094] In the formula, J us D us and K us These represent the system's effective inertia, effective damping coefficient, and effective static droop coefficient, respectively, with T0 being the system's droop time constant.

[0095] If the wind turbines are removed from frequency regulation after a period of time, the uniform structural parameters of the system and the system input power disturbance will change. Define J. us1 D us1 1 / K us1 J is the effective coefficient of the unified structure of the system when wind turbines participate in frequency regulation. us2 D us2 1 / K us2 The coefficient of the wind turbine after it is removed from frequency regulation at time t1;

[0096] Step 2) yields the efficiency coefficients of all power generation equipment in a system, which, when summed, constitute the system's efficiency coefficient J. us1 D us1 1 / K us1 J us2 D us2 1 / K us2 The system efficiency coefficient after removing the wind power equivalent coefficient; The magnitude of the system input power disturbance at time t1 and the magnitude of the power disturbance at time t0. This is related to the speed recovery strategy adopted by the wind turbine when it exits frequency regulation; if the wind turbine adopts a constant output electromagnetic power recovery strategy, then the change in the electromagnetic power output of the wind turbine at time t1 is... , This represents the change in mechanical power input to the wind turbine at time t1. To customize the power difference, satisfy .

[0097] An approximate frequency-time domain analytical expression considering wind turbine participation in and withdrawal from frequency regulation can be obtained using the state-space method:

[0098]

[0099] In the formula,

[0100]

[0101] in, , , , These represent the damped oscillation frequency and attenuation coefficient during the first and second frequency drops of the system, respectively; t1 represents the time when the wind turbine exits frequency regulation.

[0102] If a doubly-fed wind turbine is used, the expression for the input mechanical power of the wind turbine is:

[0103]

[0104] In the formula, , , These are air density, rotor radius, and undisturbed wind speed, respectively. For the wind energy utilization coefficient, we have:

[0105]

[0106] in, , These are the tip speed ratio and the blade pitch angle, respectively. Represented as the rotor speed of the wind turbine; coefficient satisfy: .

[0107] The frequency characteristics evaluated included the average rate of change of frequency. Frequency drop to its lowest point and the lowest point of the second frequency drop The following formula can be used to approximate the result:

[0108]

[0109]

[0110]

[0111] In the formula,

[0112]

[0113] Among them, t p2maxThe second maximum frequency deviation occurs at this point. The cause of the second frequency drop is the power difference resulting from the wind turbines withdrawing from frequency regulation and absorbing active power from the grid; e is a natural constant parameter, n t =t p1max / t p1 t represents the number of segments in the calculation of the frequency change rate, from the occurrence of the disturbance to the maximum frequency shift. p1max The time t is when the maximum frequency deviation occurs. p1 This indicates the time t after the disturbance occurs. p1 The time point used for the average rate of change of internal frequency.

[0114] In step 4), the obtained frequency characteristic index is the lowest point of the first frequency drop. The lowest point of the second frequency drop and the average rate of change of frequency

[0115] The above indicators were used to evaluate the relevant frequency characteristics:

[0116] (1) Evaluate the lowest point of frequency characteristics:

[0117] When calculated , All are less than the minimum allowable frequency threshold (maximum amplitude) of the system. At that time, the lowest point of the system frequency meets the system frequency regulation requirements.

[0118] (2) Evaluate the rate of change of frequency: when the calculated Less than the system's allowable average rate of change critical value (maximum amplitude). At that time, the average rate of change of the system frequency meets the system frequency regulation requirements.

[0119] Application Examples

[0120] like Figure 1 As shown, the method of this invention is used to process power generation equipment in a multi-machine power system, including synchronous generators and wind turbines. The frequency-active power transfer function matrix of each power generation device is then considered. The power disturbance is obtained With the overall frequency response of the system The relationship is then established. An iterative algorithm is used to convert each power generation device into a differential-proportional-first-order lag structure, yielding an approximate critical trajectory and four parameters: effective inertia, effective damping, effective static droop, and system droop time constant. Finally, these parameters are used to obtain the frequency characteristics and evaluate the system frequency features.

[0121] Specific embodiments of the present invention are as follows:

[0122] Establish a three-machine power system in Matlab / Simulink software, such as Figure 2 As shown in the diagram, the synchronous generators G1 and G2 at nodes 1 and 2 have capacities of 200MVA and 100MVA respectively, both using steam turbines as prime movers. The doubly-fed wind turbine WTG3 at node 3 has a capacity of 100MVA. Nodes 4-6 are network nodes. Nodes 7-9 are load nodes, and the loads are constant power loads. Network nodes and load nodes are collectively referred to as constant power nodes. The line is purely inductive; when per-unit scaling is performed using the capacity of G2 as the capacity reference value, the line parameters are shown in Table 1. In steady state, the voltage at each node is converted to 1, and the phase angle difference between each line is converted to 0.

[0123] Table 1. Line reactance values ​​in simulation verification of the embodiments.

[0124]

[0125] Using the capacity of G2 as the baseline capacity value, then F i This represents the ratio of the capacities of each power generation device.

[0126] G1 Frequency-Active Transfer Function for

[0127]

[0128] in, The transfer function of the G1 governor-turbine system (referred to as the governor system) is shown in the model below. Figure 3 As shown. The parameters under its own rated capacity per unit are: moment of inertia. Damping coefficient ; rate of decline Speed ​​governor time constant Steam inlet chamber time constant The time constant of the reheater High-pressure cylinder power ratio .

[0129] G2 Frequency-Active Transfer Function for

[0130]

[0131] in The transfer function of the G2 speed governor system is shown in the model as follows. Figure 4 As shown. The parameters under its own rated capacity per unit are: moment of inertia. Damping coefficient ; Decrease rate R2 = 0.05; Governor time constant T G2 =0.2s; Steam inlet chamber time constant T CH2=0.3s; Time constant T of the reheater RH2 =5s; High-pressure cylinder power ratio F HP2 =0.3.

[0132] Wind turbines using the DFIG model, such as Figure 4 As shown in the figure, V sq q-axis component of stator-side voltage of wind turbine generator; PLL is phase-locked loop; This is the rated value of the power grid angular frequency; The angular frequency of the power grid; K represents the rotor speed of the wind turbine. J K is the virtual inertia coefficient. D P is the droop coefficient; T1 is the time constant of the filter stage; P MPPT P is the active power reference value obtained from the MPPT curve. in With P dp These are the virtual inertia and the additional active reference value components generated by droop control, respectively; P ref P is the reference value for the active power of the wind turbine. WT Wind power generates electromagnetic power; The difference between mechanical power and electromagnetic power at the moment of exiting frequency modulation.

[0133] Frequency-active power transfer function in electromechanical scale for

[0134]

[0135] The parameter values ​​are shown in Table 2.

[0136] Table 2 shows the parameter values ​​of some inverter variables in the simulation verification of the embodiment.

[0137]

[0138] Using the method of this invention, the relationship between disturbance and frequency response is obtained:

[0139]

[0140] When a 50MW power disturbance occurs at node 8, an iterative algorithm is used as follows: Figure 6 As shown, for the common-mode component, the generators are converted into a differential-proportional-first-order lag structure within an 8-second timeframe after the disturbance to obtain an approximate frequency trajectory. The calculation results are shown in Table 3.

[0141] Table 3. Differential-proportional-first-order lag structure parameters of each power generation device

[0142]

[0143] According to the method of this invention, frequency characteristics are obtained using effective parameters. Calculations show that the lowest point of the system's common-mode frequency occurs 2-4 seconds after the disturbance, both when the wind turbine is not participating in frequency regulation and when it is participating in frequency regulation. When calculating the overall inertia, n is taken as... t =4, meaning the average rate of change of frequency is calculated using approximately several hundred milliseconds after the disturbance. The system requires a minimum frequency threshold of 0.8 Hz and a minimum average rate of change of 0.9 Hz / s. Table 4 shows the comparison and evaluation results of the calculated average rate of change of frequency, the frequency characteristics at the first and second minimum points, and the frequency characteristics obtained from the time-domain simulation.

[0144] Table 4 Comparison Results of Frequency Dynamic Characteristics Evaluation

[0145]

[0146] The simulation results show that the relative error between the theoretical minimum frequency drop point obtained from the unified structure and the minimum frequency drop point in the system simulation is within 3.5%, the relative error between the minimum frequency drop point is within 1.5%, and the relative error between the frequency change rate is within 3%. The results indicate that the established unified structure model and the system effective parameter calculation method can accurately analyze the overall frequency characteristics of the system over a relatively long period of time and calculate the required frequency support dynamic frequency characteristics, effectively evaluating the system frequency dynamic support effect after the wind turbine is connected to the grid.

[0147] The examples of this invention demonstrate the effectiveness of the approximate method for the overall frequency trajectory of a multi-machine power system including wind turbines and the quantitative evaluation method for system frequency characteristics. The established parameters can evaluate frequency characteristics such as the average rate of change of frequency and the first and second minimum points.

[0148] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of this invention is defined by the appended claims and their equivalents.

Claims

1. A method for quantitatively evaluating the frequency characteristics of a system considering frequency dips, characterized in that, Includes the following steps: Step (1): In a multi-machine power system containing power generation equipment, power disturbances are considered. Below, the overall frequency response characteristics of the system and the power response of each power generation device are analyzed. Frequency-active power transfer function of each power generation device The relationship between the two systems; the overall frequency response characteristics of the system described use the frequency common-mode component. express; Step (2): Through iterative algorithm, for the frequency common mode component, the power response of each power generation device under disturbance is approximated by the differential-proportional-first-order lag structure, and four frequency regulation capability quantification parameters are obtained: effective inertia, effective damping coefficient, effective static droop coefficient and system droop time constant. Step (3): Calculate the frequency characteristic quantization index using the frequency modulation capability quantization parameters obtained in step (2); Step (4) compare the frequency characteristic quantification index obtained in step (3) with the frequency characteristic threshold value allowed by the system to evaluate the frequency characteristics.

2. The method for quantitatively evaluating the frequency characteristics of a system considering frequency dips according to claim 1, characterized in that, Power generation equipment includes synchronous generators and wind turbines.

3. The method for quantitatively evaluating the frequency characteristics of a system considering frequency dips according to claim 1, characterized in that, The specific method for step (1) is as follows: A multi-machine power system has a total of n frequency-modulated power generation devices; G i (s) is the frequency-power transfer function of the i-th power generation device. ; Let be the power response of the i-th generating device; the power disturbance is . , s represents the Laplace operator. Indicates the magnitude of the disturbance; System frequency common-mode components With power disturbance The relationship is as follows: 。 4. The system frequency characteristic evaluation method considering frequency dips according to claim 3, characterized in that, The specific method for step (2) is as follows: The expression for the differential-proportional-first-order hysteresis structure is: In the formula, J u D u and K u These are respectively represented as effective inertia, effective damping coefficient, and effective static droop coefficient, with T0 being the system droop time constant; By approximating each device as a differential-proportional-first-order hysteresis structure parameter optimization problem, the following iterative algorithm is used to obtain four frequency modulation capability quantification parameters: effective inertia, effective damping coefficient, effective static droop coefficient, and system droop time constant. 2.1) Set initial values ​​for the inertia parameters, damping parameters, static droop parameters, and droop time parameters of the differential-proportional-first-order lag structure of each power generation device, thereby obtaining the initial differential-proportional-first-order lag structure of each device. and the system's initial differential-proportional-first-order hysteresis structure : in, , and These represent the initial values ​​of the inertia parameter, damping parameter, and static droop parameter for each generator's differential-proportional-first-order lag, respectively. This represents the initial value of the system descent time parameter; , , Let these represent the initial inertia parameter, damping parameter, and static droop parameter of the system, respectively, satisfying... , , S i This is expressed as the rated capacity of each power generation device; 2.2) Let the inner loop variable r = 1; the outer loop variable j = 1; 2.3) In the r-th iteration, the frequency trajectory is obtained according to the following formula. ; in, This indicates the differential-proportional-first-order lag structure of the generator system during the (r-1)th iteration. This represents the frequency trajectory corresponding to the common-mode component of the (r-1)th iteration. 2.4) Establish the following parameter optimization problem: Among them, t0, t f These represent the initial and final times of the selected time period, respectively. The initial moment of the disturbance; The frequency-active power transfer function of each power generation device The calculated power trajectory, Differential-proportional-first-order lag structure for each power generation device Calculated power trajectory; power trajectory Obtained by inverse Laplace transform Power trajectory Obtained by inverse Laplace transform ; The optimization problem is solved using the least squares method to obtain the parameters. , and ; 2.5) Let r = r + 1, and repeat steps 2.2) to 2.4) until the parameters converge. Record the obtained equivalent parameters; the equivalent parameters are... , , ; 2.6) Exit the inner loop and enter the outer loop, let ; 2.7) Let j = j + 1, and repeat steps 2.2) to 2.7) until the optimal value is found, thus obtaining the equivalent parameters of the unified structure. , , , The unified structure described is a differential-proportional-first-order hysteresis structure.

5. The system frequency characteristic evaluation method considering frequency dips according to claim 4, characterized in that, t f Set to 4t nadir , t nadir The moment when the frequency trajectory reaches its lowest point; The value range is -0.5 to 0.

5.

6. The system frequency characteristic evaluation method considering frequency dips according to claim 4, characterized in that, The specific method for step (3) is as follows: The approximate frequency time-domain analytical expression is: In the formula, Among them, J us1 D us1 1 / K us1 J represents the system uniform structure effective coefficient when wind turbines participate in frequency regulation. us2 D us2 1 / K us2 This represents the coefficient after the wind turbine is removed from frequency regulation. , These represent the damped oscillation frequencies during the first and second frequency drops of the system, respectively. , These represent the attenuation coefficients during the first and second frequency drops of the system, respectively; t1 represents the time when the wind turbine exits frequency regulation. This represents the system input power disturbance at time t1; Frequency characteristic indicators include the average rate of change of frequency. The frequency dropped to its lowest point. and the lowest point of the second frequency drop It is obtained using the following formula: In the formula, Among them, t p2max The moment when the second maximum frequency deviation occurs; e is the natural constant, n t =t p1max / t p1 , t p1max The time t is when the maximum frequency deviation occurs. p1 This indicates the time t after the disturbance occurs. p1 The time point used for the average rate of change of internal frequency.

7. The method for quantitatively evaluating the frequency characteristics of a system considering frequency dips according to claim 6, characterized in that, The specific method for step (4) is as follows: Based on the frequency characteristic index obtained in step (3): the lowest point of the first frequency drop The lowest point of the second frequency drop and the average rate of change of frequency Three indicators were used to evaluate the frequency characteristics; Specifically: 4.1) Evaluation of the lowest point of frequency characteristics: When calculated , All are less than the minimum allowable frequency threshold of the system. When the system frequency is at its lowest point, the system frequency regulation requirement is met, and proceed to 4.2); otherwise, it is not met. 4.2) Evaluation of frequency change rate: When calculated Less than the system's allowable average rate of change critical value When the system frequency average rate of change is within a certain range, it meets the system frequency regulation requirements; otherwise, it does not.

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