Dynamic equivalent modeling method and system for induction motors in new energy power systems

Abstract

This invention discloses a dynamic equivalent modeling method and system for induction motors in new energy power systems. First, induction motors are grouped based on their eigenvalue distance and the dynamic similarity of their port voltages. The initial number of induction motor groups and the grouping results are obtained by combining the intersection of these two grouping results. Second, the operating status of nearby new energy sources within the same group is analyzed. If some new energy sources enter a low-voltage ride-through state, the voltage drop depth at the induction motor port is used as a further grouping criterion. The final grouping result is determined by combining the initial grouping results. Finally, a capacity-weighted method is used to aggregate the parameters of the induction motors grouped within the same group. The induction motor equivalent modeling method proposed in this invention has higher equivalent accuracy compared to existing grouping methods that only consider the eigenvalue distance of induction motors; it is also suitable for the dynamic equivalent modeling of induction motors in high-proportion new energy power systems.

Description

Technical Field

[0001] This invention relates to the field of power system modeling, specifically to a dynamic equivalent modeling method for induction motors in new energy power systems, and also to a dynamic equivalent modeling system for induction motors in new energy power systems. Background Technology

[0002] Power system analysis and control primarily rely on simulation calculations, and the accuracy of these calculations depends on the model used. Loads are among the key components affecting the dynamic characteristics of power systems, and accurate load models are fundamental to power system simulation analysis. Induction motors account for over 60% of the electricity consumption in power loads, and even exceed 90% in industrial loads; therefore, equivalent modeling of induction motors is an important aspect of power system modeling. Currently, with the continuous integration of new energy sources into the grid, load characteristics have changed significantly, and existing load models are no longer suitable for the needs of modern power system simulation analysis, necessitating the research of new modeling methods and techniques.

[0003] Currently, equivalent modeling methods for induction motors in traditional power grids are relatively mature. However, with the increasing proportion and scale of renewable energy grid connection, the inherently nonlinear control mechanisms of renewable energy units, such as amplitude limiting and switching, affect the dynamic characteristics of nearby induction motors. Therefore, when there are many renewable energy units in the vicinity of induction motors, it is necessary to consider the dynamic interaction between renewable energy and induction motors to improve the accuracy of equivalent modeling. Currently, no literature reports on the impact of renewable energy on the dynamic equivalent modeling of induction motors has been found. Summary of the Invention

[0004] The purpose of this invention is to provide a dynamic equivalent modeling method and system for induction motors in new energy power systems. Based on the existing equivalent modeling of induction motors based on small disturbance similarity, this invention proposes an equivalent modeling clustering method that takes into account the dynamic similarity of the terminal voltage. At the same time, for high-proportion new energy power systems, this invention proposes a dynamic clustering method that further considers the voltage drop depth of the induction motor terminal. This invention has high equivalent accuracy and strong adaptability.

[0005] To achieve the above functions, this invention designs a dynamic equivalent modeling method for induction motors in a new energy power system, executing the following steps S1-S5: grouping each induction motor into groups, and aggregating the parameters of induction motors within the same group to obtain the model parameters of the equivalent induction motors:

[0006] Step S1: Establish a dynamic model for each induction motor and linearize it. Based on the linearized dynamic model of the induction motor, calculate the eigenvalues ​​of each induction motor, construct the eigenvalue distance between each induction motor, and group the induction motors according to the eigenvalue distance.

[0007] Step S2: Based on the disturbance trajectory of the port voltage of each induction motor under the preset type of disturbance, construct the similarity distance of voltage fluctuation after the induction motor is disturbed, and group each induction motor according to the similarity distance of voltage fluctuation;

[0008] Step S3: Based on the intersection of the grouping results of each induction motor obtained in steps S1 and S2, divide each intersection of the grouping results of each induction motor into the same group, and divide the other induction motors into the same group, to obtain the preliminary number of groups and grouping results of each induction motor.

[0009] Step S4: For each generator group obtained in Step S3, based on the operating characteristics of each induction motor near the new energy generator group, determine whether any part of the new energy generator group has entered the low voltage ride-through state. If so, further group the generator groups according to the voltage drop depth of each induction motor port in each generator group. Otherwise, maintain the initial group number and grouping result of each induction motor unchanged.

[0010] Step S5: For each machine group obtained in Step S4, the capacity weighting method is used to aggregate the parameters of the induction motors in the same machine group to obtain the model parameters of each equivalent induction motor.

[0011] As a preferred technical solution of the present invention, the specific steps of step S1 are as follows:

[0012] Step S11: Establish the dynamic model of the induction motor as follows:

[0013]

[0014] In the formula, E m δ and φ represent the amplitude and angle of the internal electromotive force of the induction motor, respectively; U and θ represent the amplitude and angle of the port voltage of the induction motor, respectively; s is the slip; ω is the rotor angular velocity; X is the stator reactance; X′ is the transient reactance; T′ d0 T represents the rotor winding time constant; m Represents mechanical torque, f0 = 50Hz, ω s T represents the stator angular velocity. j The rotor's inertia time constant;

[0015] Step S12: Linearize the dynamic model of the induction motor into the following equation:

[0016]

[0017] In the formula, X = [E m ,δ,s] T Let A be the column vector of state variables of the induction motor, and let A be the coefficient matrix.

[0018] Step S13: Define the eigenvalue distance d between induction motors E The following formula is used to group the induction motors according to their eigenvalue distance. Induction motors with eigenvalue distances higher than a preset threshold are grouped into one group, while induction motors with eigenvalue distances lower than the preset threshold are grouped into another group:

[0019]

[0020]

[0021] In the formula, i and j represent the i-th and j-th induction motors, respectively; λ li Let λ represent the l-th characteristic value of the induction motor i. lj Let j represent the l-th characteristic value of induction motor j, and n be the total number of induction motors;

[0022] Step S14: Define the two induction motor groups as C eqm C eqn The shortest distance method is used to calculate the group C of induction motors. eqm and induction motor group C eqn The distance between the two nearest points is calculated using the following formula:

[0023]

[0024] In the formula, D L (C eqm C eqn ) represents the group of induction motors C eqm and C eqn The distance between the two closest points.

[0025] As a preferred technical solution of the present invention, the specific steps of step S2 are as follows:

[0026] Step S21: The voltage at node k after the induction motor is disturbed is expressed by the following formula:

[0027]

[0028] In the formula, and These represent the stable and fluctuating values ​​of the voltage at node k, respectively.

[0029] Step S22: Construct the similarity distance of voltage fluctuations of the induction motor after disturbance as follows:

[0030]

[0031] In the formula, Here, K represents the fluctuation value of the voltage at node h, and K represents the total number of points within the simulation duration.

[0032] Step S23: Based on the voltage fluctuation similarity distance obtained in step S22, the induction motors are grouped using the average method. Induction motors with voltage fluctuation similarity distances higher than a preset threshold are grouped into one group, and induction motors with voltage fluctuation similarity distances not higher than the preset threshold are grouped into another group, as shown in the following formula:

[0033]

[0034] In the formula, D V (C eqm C eqn ) represents the group of induction motors C eqm and C eqn The similarity distance of voltage fluctuations between the groups, M and N, represent the induction motor group C, respectively. eqm and C eqn The number of induction motors.

[0035] As a preferred embodiment of the present invention, the preliminary grouping method of each induction motor in step S3 is as follows:

[0036] Based on the grouping method in step S1, m induction motor groups are obtained. Based on the grouping method in step S2, n induction motor groups are obtained. Starting from the first group among the m induction motor groups in step S1, each induction motor in this group is compared with each induction motor in the first to nth induction motor groups in step S2. Induction motors that are the same in the induction motor groups in steps S1 and S2 are grouped into the same group, and induction motors that are different are grouped into another group. Starting from the second group among the m induction motor groups in step S1, the above steps are repeated until all induction motors in all the induction motor groups in steps S1 and S2 have been compared, and the preliminary number of groups and grouping results of each induction motor are obtained.

[0037] As a preferred technical solution of the present invention, the specific method of step S4 is as follows:

[0038] Step S41: For each generator group obtained in step S3, determine the voltage threshold value U for each induction motor near-field renewable energy unit in the same generator group to enter the low-voltage ride-through state. th Determine whether any of the new energy units have entered the low-voltage ride-through state; if so, proceed to step S42; otherwise, proceed to step S43.

[0039] Step S42: Set the voltage at the induction motor port higher than U. thThe induction motors are grouped into the same group, and the remaining induction motors are grouped into another group. The intersection of the preliminary grouping result obtained in step S3 and the above grouping result is compared. The induction motors in the intersection are grouped into the same group, and the different induction motors are grouped into another group, so as to obtain the final number of groups and the grouping result.

[0040] Step S43: If all induction motor near-area renewable energy units either enter or do not enter the low-voltage ride-through state, further grouping is not required.

[0041] As a preferred technical solution of the present invention, the specific method of step S5 is as follows:

[0042] For each machine group obtained in step S4, the induction motors within the same machine group are aggregated using a capacity-weighted method. The parameter aggregation method is as follows:

[0043]

[0044] In the formula, x i Let x be the parameter of the i-th induction motor. eq Here are the parameters for the equivalent induction motor, where f is the number of induction motors in the same group, and S... i Let S be the capacity of the i-th induction motor. eq It is the sum of the capacities of all induction motors in the machine group.

[0045] This invention also designs a dynamic equivalent modeling system for induction motors in a new energy power system, including an acquisition unit, a simulation unit, a clustering unit, and a calculation unit, to realize the aforementioned dynamic equivalent modeling method for induction motors in a new energy power system.

[0046] The acquisition unit is used to establish a dynamic model of the induction motor.

[0047] The simulation unit constructs a simulation system based on the power system analysis and synthesis program, performs simulations for preset types of disturbances, and obtains the disturbance trajectory of the port voltage of each induction motor and the disturbance trajectory of the outlet voltage of each new energy unit.

[0048] The grouping unit is used to perform the linearization of the induction motor dynamic model described in step S1. Based on the linearized induction motor dynamic model, it calculates the eigenvalues ​​of each induction motor, constructs the eigenvalue distance between each induction motor, and groups the induction motors according to the eigenvalue distance. Step S2 describes constructing the voltage fluctuation similarity distance of each induction motor after disturbance based on the port voltage disturbance trajectory of each induction motor under a preset type of disturbance, and groups the induction motors according to the voltage fluctuation similarity distance. Step S3 describes grouping the induction motors based on the grouping results obtained in steps S1 and S2 respectively. The intersection of the grouping results of each induction motor is divided into the same group, and the other induction motors are divided into the same group to obtain the initial number of groups and the grouping results of each induction motor. In step S4, for each group obtained in step S3, based on the operating characteristics of the near-field new energy units of each induction motor in the same group, it is determined whether a part of each new energy unit has entered the low voltage ride-through state. If so, further grouping is performed according to the voltage drop depth of each induction motor port in each group. Otherwise, the initial number of groups and the grouping results of each induction motor remain unchanged.

[0049] The calculation unit is used to aggregate the parameters of each induction motor in the same group using the capacity weighting method to obtain the model parameters of the equivalent induction motor.

[0050] Beneficial effects: Compared with the prior art, the advantages of the present invention include:

[0051] This invention designs a dynamic equivalent modeling method and system for induction motors in new energy power systems. It comprehensively considers the dynamic characteristics of induction motors under small disturbances, the dynamic similarity of terminal voltage after disturbance, and the degree of voltage drop during disturbance, effectively improving the accuracy of equivalent modeling for induction motors. Especially in high-proportion new energy power systems, considering the impact of the terminal voltage drop depth can account for the influence of the operating characteristics of new energy units, resulting in high accuracy for the dynamic equivalent modeling of induction motors in high-proportion new energy power systems. Attached Figure Description

[0052] Figure 1 This is a flowchart of a dynamic equivalent modeling method for induction motors in a new energy power system according to an embodiment of the present invention;

[0053] Figure 2 This is a schematic diagram of a 10-machine, 39-node system provided according to an embodiment of the present invention;

[0054] Figure 3 This is a schematic diagram of the induction motor clustering results based on feature value similarity according to an embodiment of the present invention;

[0055] Figure 4This is a clustering diagram of induction motors based on dynamic voltage similarity provided in an embodiment of the present invention;

[0056] Figure 5 This is a photovoltaic bus voltage disturbance trajectory diagram provided according to an embodiment of the present invention;

[0057] Figures 6a-6c This is a schematic diagram of the equivalent error of boundary nodes and lines after considering the voltage drop depth, provided according to an embodiment of the present invention. Detailed Implementation

[0058] The present invention will be further described below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and should not be used to limit the scope of protection of the present invention.

[0059] Reference Figure 1 The present invention provides a dynamic equivalent modeling method for induction motors in a new energy power system, which performs the following steps S1-S5: grouping each induction motor into groups, and aggregating the parameters of induction motors within the same group to obtain the model parameters of the equivalent induction motors.

[0060] Step S1: Establish a dynamic model for each induction motor and linearize it. Based on the linearized dynamic model of the induction motor, calculate the eigenvalues ​​of each induction motor, construct the eigenvalue distance between each induction motor, and group the induction motors according to the eigenvalue distance.

[0061] In one embodiment, the new energy power system is a New England 10-machine 39-bus system, as referenced. Figure 2 In the diagram, numbers 1-39 represent node numbers. In this embodiment, photovoltaic power sources are added to the load nodes {5,6,13,14,16,21} of the original system. To maintain the power balance of the original nodes, constant impedance loads with the same power are added to the corresponding nodes. The synchronous generator nodes {33,35} are replaced with photovoltaic power sources with the same active power output, and the reactive power output of the original nodes is kept unchanged through parallel capacitors. The simulation platform is Power System Analysis and Synthesis Program (PSASP), where the area above the dashed line is the study area, and the area below the dashed line is the area to be equalized. For the needs of the problem study, the static load nodes {4,7,8,12,15,20,23,24} in the original system are set as comprehensive loads including induction motors. The static loads are all constant impedance loads, and others remain unchanged. Table 1 gives the parameters of each induction motor, where P mp K represents the initial load proportion of the induction motor. L This indicates the load rate.

[0062] Table 1

[0063]

[0064] The specific steps of step S1 are as follows:

[0065] Step S11: Establish the dynamic model of the induction motor as follows:

[0066]

[0067] In the formula, E m δ and φ represent the amplitude and angle of the internal electromotive force of the induction motor, respectively; U and θ represent the amplitude and angle of the port voltage of the induction motor, respectively; s is the slip; ω is the rotor angular velocity; X is the stator reactance; X′ is the transient reactance; T′ d0 T represents the rotor winding time constant; m Represents mechanical torque, f0 = 50Hz, ω s T represents the stator angular velocity. j The rotor's inertia time constant;

[0068] Step S12: Linearize the dynamic model of the induction motor into the following equation:

[0069]

[0070] In the formula, x = [E m ,δ,s] T Let A be the column vector of state variables of the induction motor, and let A be the coefficient matrix. Since the dynamic model of the induction motor adopts a third-order model, the three characteristic values ​​of the induction motor can be obtained from A. The characteristic values ​​of each induction motor in the embodiment are shown in Table 2.

[0071] Table 2

[0072]

[0073] Step S13: Define the eigenvalue distance d between induction motors E The following formula is used to group the induction motors according to their eigenvalue distance. Induction motors with eigenvalue distances higher than a preset threshold are grouped into one group, while induction motors with eigenvalue distances lower than the preset threshold are grouped into another group. The preset threshold is obtained based on engineering experience:

[0074]

[0075]

[0076] In the formula, i and j represent the i-th and j-th induction motors, respectively; λ li Let λ represent the l-th characteristic value of the induction motor i. lj Let j represent the l-th characteristic value of induction motor j, and n be the total number of induction motors;

[0077] The characteristic value distances of each induction motor in the embodiments are shown in Table 3:

[0078] Table 3

[0079]

[0080] Step S14: Define the two induction motor groups as C eqm C eqn The shortest distance method is used to calculate the group C of induction motors. eqm and induction motor group C eqn The distance between the two nearest points is calculated using the following formula:

[0081]

[0082] In the formula, D L (C eqm C eqn ) represents the group of induction motors C eqm and C eqn The distance between the two closest points.

[0083] Based on Table 3, the induction motor grouping results based on eigenvalue distance are obtained, and D is selected. L =0.3 is the grouping threshold. Induction motors {7, 8} are grouped into one group, and the remaining induction motors {4, 12, 15, 20, 23, 24} are grouped into another group. See the diagram for the grouping results. Figure 3 .

[0084] Step S2: Based on the disturbance trajectory of the port voltage of each induction motor under the preset type of disturbance, construct the similarity distance of voltage fluctuation after the induction motor is disturbed, and group each induction motor according to the similarity distance of voltage fluctuation;

[0085] The specific steps of step S2 are as follows:

[0086] Step S21: The disturbance is set as follows: at t=1s, a three-phase short circuit with a grounding reactance of 0.004pu occurs at node 39. The fault lasts for 0.1s and then disappears. Based on this disturbance, the voltage disturbance trajectory of each node in the system is obtained.

[0087] The voltage at node k of the induction motor after being disturbed is expressed by the following formula:

[0088]

[0089] In the formula, and These represent the stable and fluctuating values ​​of the voltage at node k, respectively.

[0090] Step S22: Construct the similarity distance of voltage fluctuations of the induction motor after disturbance as follows:

[0091]

[0092] In the formula, Here, K represents the fluctuation value of the voltage at node h, and K represents the total number of points within the simulation duration.

[0093] Step S23: Based on the voltage fluctuation similarity distance obtained in step S22, the induction motors are grouped using the average method. Induction motors with voltage fluctuation similarity distances higher than a preset threshold are grouped into one group, and induction motors with voltage fluctuation similarity distances not higher than the preset threshold are grouped into another group. The preset threshold is obtained based on engineering experience and is specifically calculated as follows:

[0094]

[0095] In the formula, D V (C eqm C eqn ) represents the group of induction motors C eqm and C eqn The similarity distance of voltage fluctuations between the groups, M and N, represent the induction motor group C, respectively. eqm and C eqn The number of induction motors.

[0096] The similarity distance of voltage fluctuations of each induction motor in the embodiments is shown in Table 4.

[0097] Table 4

[0098]

[0099] Based on the voltage fluctuation similarity distance, the induction motor grouping results can be obtained, see... Figure 4 By selecting DV = 0.002 as the grouping threshold, induction motors {4, 7, 8, 12} can be grouped into one group, and the remaining induction motors {15, 20, 23, 24} can be grouped into another group.

[0100] Step S3: Based on the intersection of the grouping results of each induction motor obtained in steps S1 and S2, divide each intersection of the grouping results of each induction motor into the same group, and divide the other induction motors into the same group, to obtain the preliminary number of groups and grouping results of each induction motor.

[0101] The preliminary grouping method for each induction motor in step S3 is as follows:

[0102] Based on the grouping method in step S1, m induction motor groups are obtained. Based on the grouping method in step S2, n induction motor groups are obtained. Starting from the first group among the m induction motor groups in step S1, each induction motor in this group is compared with each induction motor in the first to nth induction motor groups in step S2. Induction motors that are the same in the induction motor groups in steps S1 and S2 are grouped into the same group, and induction motors that are different are grouped into another group. Starting from the second group among the m induction motor groups in step S1, the above steps are repeated until all induction motors in all the induction motor groups in steps S1 and S2 have been compared, and the preliminary number of groups and grouping results of each induction motor are obtained.

[0103] In this embodiment, step S1 results in two clusters: cluster 1 consists of induction motors {7,8}, and cluster 2 consists of induction motors {4,12,15,20,23,24}. Step S2 also results in two clusters: cluster 1 consists of induction motors {4,7,8,12}, and cluster 2 consists of induction motors {15,20,23,24}. Combining the intersection of steps S1 and S2, the final cluster result is three clusters: cluster 1 {7,8}, cluster 2 {4,12}, and cluster 3 {15,20,23,24}.

[0104] Step S4: For each generator group obtained in Step S3, based on the operating characteristics of each induction motor near-field new energy generator unit in the same generator group, determine whether any part of each new energy generator unit has entered the low voltage ride-through state (LVRT). If so, further group the generators according to the voltage drop depth of each induction motor port in each generator group; otherwise, maintain the initial group number and grouping result of each induction motor unchanged.

[0105] The specific method for step S4 is as follows:

[0106] Step S41: For each generator group obtained in step S3, determine the voltage threshold value U for each induction motor near-field renewable energy unit in the same generator group to enter the low-voltage ride-through state. th Determine if any of the new energy generating units have entered the low-voltage ride-through state; if so, proceed to step S42; otherwise, proceed to step S43; where the voltage threshold value U... th These are preset values, provided by the new energy unit manufacturers;

[0107] The disturbance trajectories of the voltages at each photovoltaic power supply port during the disturbance period in the embodiment are shown in the figure. Figure 5 As shown.

[0108] from Figure 5 It can be seen that the voltage of photovoltaic power sources {5,6,13,14} is less than 0.9U during the fault period.n (Voltage threshold U for photovoltaic power to enter low-voltage ride-through state) th Therefore, photovoltaic power sources {5,6,13,14} entered low-voltage ride-through mode during the fault, while the remaining photovoltaic power sources {16,21,33,35} did not enter low-voltage ride-through mode. Based on this, it is determined that the induction motors need to be regrouped.

[0109] Step S42: Set the voltage at the induction motor port higher than U. th The induction motors are grouped into the same group, and the remaining induction motors are grouped into another group. The intersection of the preliminary grouping result obtained in step S3 and the above grouping result is compared. The induction motors in the intersection are grouped into the same group, and the different induction motors are grouped into another group, so as to obtain the final number of groups and the grouping result.

[0110] The port voltages of induction motors {7,8} in group 1 and {4,12} in group 2 are both less than 0.9U. n They are grouped together. However, in group 3, among the induction motors {15,20,23,24}, the terminal voltage of unit {20,23,24} is higher than 0.9U. n However, the voltage of the induction motor {15} is below 0.9U. n Meanwhile, there are a large number of photovoltaic power sources in the vicinity of group 3 induction motors. Therefore, after further considering the voltage drop depth, the final grouping result of the induction motors is: group 1 {7,8}, group 2 {4,12}, group 3 {15}, group 4 {20,23,24}.

[0111] Step S43: If all induction motor near-area renewable energy units either enter or do not enter the low-voltage ride-through state, further grouping is not required.

[0112] Step S5: For each machine group obtained in Step S4, the capacity weighting method is used to aggregate the parameters of the induction motors in the same machine group to obtain the model parameters of each equivalent induction motor.

[0113] The specific method for step S5 is as follows:

[0114] For each machine group obtained in step S4, the induction motors within the same machine group are aggregated using a capacity-weighted method. The parameter aggregation method is as follows:

[0115]

[0116] In the formula, x i Let x be the parameter of the i-th induction motor. eq Here are the parameters for the equivalent induction motor, r is the number of induction motors in the same group, and S is... i Let S be the capacity of the i-th induction motor. eqIt is the sum of the capacities of all induction motors in the machine group.

[0117] The aggregated parameters of the equivalent induction motor are shown in Table 5. Figure 6a A comparison of the voltage disturbance trajectories at boundary node 27 before and after the equivalent voltage values ​​are presented. Figure 6a This is a comparison of the active power disturbance trajectories of lines 17-27 before and after the equivalent values. Figure 6c This is a comparison of the reactive power disturbance trajectories of lines 17-27 before and after the equivalent values.

[0118] Table 5

[0119]

[0120] The model error is defined using the root mean square error E1 and the absolute error E2, as follows:

[0121]

[0122] E2(n)=|y(n)-y′(n)|

[0123] In the formula, y and y′ represent the disturbed trajectories before and after the equalization, respectively;

[0124] Table 6 shows the accuracy of the equivalent model for the method of the present invention and the grouping method that does not consider the voltage drop depth at the induction motor port.

[0125] Table 6

[0126]

[0127]

[0128] This invention also provides a dynamic equivalent modeling system for induction motors in a new energy power system, including an acquisition unit, a simulation unit, a clustering unit, and a calculation unit, to realize the aforementioned dynamic equivalent modeling method for induction motors in a new energy power system.

[0129] The acquisition unit is used to establish a dynamic model of the induction motor.

[0130] The simulation unit constructs a simulation system based on the power system analysis and synthesis program, performs simulations for preset types of disturbances, and obtains the disturbance trajectory of the port voltage of each induction motor and the disturbance trajectory of the outlet voltage of each new energy unit.

[0131] The grouping unit is used to perform the linearization of the induction motor dynamic model described in step S1. Based on the linearized induction motor dynamic model, it calculates the eigenvalues ​​of each induction motor, constructs the eigenvalue distance between each induction motor, and groups the induction motors according to the eigenvalue distance. Step S2 describes constructing the voltage fluctuation similarity distance of each induction motor after disturbance based on the port voltage disturbance trajectory of each induction motor under a preset type of disturbance, and groups the induction motors according to the voltage fluctuation similarity distance. Step S3 describes grouping the induction motors based on the grouping results obtained in steps S1 and S2 respectively. The intersection of the grouping results of each induction motor is divided into the same group, and the other induction motors are divided into the same group to obtain the initial number of groups and the grouping results of each induction motor. In step S4, for each group obtained in step S3, based on the operating characteristics of the near-field new energy units of each induction motor in the same group, it is determined whether a part of each new energy unit has entered the low voltage ride-through state. If so, further grouping is performed according to the voltage drop depth of each induction motor port in each group. Otherwise, the initial number of groups and the grouping results of each induction motor remain unchanged.

[0132] The calculation unit is used to aggregate the parameters of each induction motor in the same group using the capacity weighting method to obtain the model parameters of the equivalent induction motor.

[0133] In summary, this invention proposes a novel method for dynamic equivalent modeling of induction motors in new energy power systems. It comprehensively considers the dynamic characteristics of induction motors under small disturbances, the dynamic similarity of terminal voltage after disturbance, and the degree of voltage drop during the disturbance period, effectively improving the accuracy of equivalent modeling of induction motors. Especially in high-proportion new energy power systems, considering the impact of the depth of voltage drop at the terminals allows for the inclusion of the operating characteristics of new energy units, resulting in high accuracy for the dynamic equivalent modeling of induction motors in such systems.

[0134] The embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the present invention is not limited to the above embodiments. Within the scope of knowledge possessed by those skilled in the art, various changes can be made without departing from the spirit of the present invention.

Claims

1. A dynamic equivalent modeling method for induction motors in a new energy power system, characterized in that, Perform the following steps S1-S5 to group each induction motor and aggregate the parameters of the induction motors within the same group to obtain the model parameters of the equivalent induction motor: Step S1: Establish a dynamic model for each induction motor and linearize it. Based on the linearized dynamic model of the induction motor, calculate the eigenvalues ​​of each induction motor, construct the eigenvalue distance between each induction motor, and group the induction motors according to the eigenvalue distance. The specific steps of step S1 are as follows: Step S11: Establish the dynamic model of the induction motor as follows: In the formula, and These represent the amplitude and angle of the electromotive force within the induction motor, respectively. and These represent the amplitude and angle of the induction motor port voltage, respectively. For slip; This refers to the rotor angular velocity; For stator reactance, Transient reactance; Indicates the rotor winding time constant; Represents mechanical torque. , Indicates the stator angular velocity. The rotor's inertia time constant; Step S12: Linearize the dynamic model of the induction motor into the following equation: In the formula, Let A be the column vector of state variables of the induction motor, and let A be the coefficient matrix. Step S13: Define the characteristic distance between induction motors The following formula is used to group the induction motors according to their eigenvalue distance. Induction motors with eigenvalue distances higher than a preset threshold are grouped into one group, while induction motors with eigenvalue distances lower than the preset threshold are grouped into another group: In the formula, i and j They represent the first i Taiwan and the j Taiwan induction motor; Indicating an induction motor i The 1 eigenvalue, Indicating an induction motor j The 1 eigenvalue, n This represents the total number of induction motors. Step S14: Define the two induction motor groups as follows: , The shortest distance method is used to calculate the induction motor group. and induction motor group The distance between the two nearest points is calculated using the following formula: In the formula, Indicating a group of induction motors and The distance between the two closest points; Step S2: Based on the disturbance trajectory of the port voltage of each induction motor under the preset type of disturbance, construct the similarity distance of voltage fluctuation after the induction motor is disturbed, and group each induction motor according to the similarity distance of voltage fluctuation; Step S3: Based on the intersection of the grouping results of each induction motor obtained in steps S1 and S2, divide each intersection of the grouping results of each induction motor into the same group, and divide the other induction motors into the same group, to obtain the preliminary number of groups and grouping results of each induction motor. Step S4: For each generator group obtained in Step S3, based on the operating characteristics of each induction motor near the new energy generator group, determine whether any part of the new energy generator group has entered the low voltage ride-through state. If so, further group the generator groups according to the voltage drop depth of each induction motor port in each generator group. Otherwise, maintain the initial group number and grouping result of each induction motor unchanged. The specific method for step S4 is as follows: Step S41: For each generator group obtained in step S3, determine the voltage threshold value for each induction motor near-field renewable energy unit in the same generator group to enter the low-voltage ride-through state. Determine whether any of the new energy units have entered the low-voltage ride-through state; if so, proceed to step S42; otherwise, proceed to step S43. Step S42: Set the voltage at the induction motor port higher than... The induction motors are grouped into the same group, and the remaining induction motors are grouped into another group. The intersection of the preliminary grouping result obtained in step S3 and the above grouping result is compared. The induction motors in the intersection are grouped into the same group, and the different induction motors are grouped into another group, so as to obtain the final number of groups and the grouping result. Step S43: If all induction motor near-area renewable energy units either enter or do not enter the low-voltage ride-through state, further grouping is not required; Step S5: For each machine group obtained in Step S4, the capacity weighting method is used to aggregate the parameters of the induction motors in the same machine group to obtain the model parameters of each equivalent induction motor.

2. The dynamic equivalent modeling method for induction motors in a new energy power system according to claim 1, characterized in that, The specific steps of step S2 are as follows: Step S21: Node after the induction motor is disturbed k The voltage is expressed as follows: In the formula, and They are nodes k Stable and fluctuating voltage values; Step S22: Construct the similarity distance of voltage fluctuations of the induction motor after disturbance as follows: In the formula, For nodes h Voltage fluctuation value, K This represents the total number of points within the simulation duration; Step S23: Based on the voltage fluctuation similarity distance obtained in step S22, the induction motors are grouped using the average method. Induction motors with voltage fluctuation similarity distances higher than a preset threshold are grouped into one group, and induction motors with voltage fluctuation similarity distances not higher than the preset threshold are grouped into another group, as shown in the following formula: In the formula, Indicating a group of induction motors and Similarity distance of voltage fluctuations between regions M and N Representing induction motor groups and The number of induction motors.

3. The dynamic equivalent modeling method for induction motors in a new energy power system according to claim 1, characterized in that, The preliminary grouping method for each induction motor in step S3 is as follows: Based on the clustering method in step S1, obtain m A group of induction motors, based on the grouping method in step S2, obtains n A group of induction motors, divided from step S1 m Starting with the first group of induction motor groups, each induction motor in that group is sequentially compared with the first to the second group as defined in step S2. n The induction motors in each induction motor group are compared. The induction motors that are the same in the induction motor groups divided in steps S1 and S2 are grouped into the same group, and the induction motors that are different are grouped into another group. Then from the division in step S1 m Starting with the second group of induction motors in each group, repeat the above steps until all induction motors in all groups divided in steps S1 and S2 have been compared, and obtain the preliminary number of groups and grouping results for each induction motor.

4. The dynamic equivalent modeling method for induction motors in a new energy power system according to claim 1, characterized in that, The specific method for step S5 is as follows: For each machine group obtained in step S4, the induction motors within the same machine group are aggregated using a capacity-weighted method. The parameter aggregation method is as follows: In the formula, For the first i Taiwan induction motor parameters These are the parameters of an equivalent induction motor. r This refers to the number of induction motors within the same machine group. For the first The capacity of the induction motor, It is the sum of the capacities of all induction motors in the machine group.

5. A dynamic equivalent modeling system for induction motors in a new energy power system, characterized in that, It includes an acquisition unit, a simulation unit, a clustering unit, and a calculation unit to realize a dynamic equivalent modeling method for induction motors in a new energy power system as described in any one of claims 1-4; The acquisition unit is used to establish a dynamic model of the induction motor. The simulation unit constructs a simulation system based on the power system analysis and synthesis program, performs simulations for preset types of disturbances, and obtains the disturbance trajectory of the port voltage of each induction motor and the disturbance trajectory of the outlet voltage of each new energy unit. The grouping unit is used to perform the linearization of the induction motor dynamic model described in step S1. Based on the linearized induction motor dynamic model, it calculates the eigenvalues ​​of each induction motor, constructs the eigenvalue distance between each induction motor, and groups the induction motors according to the eigenvalue distance. Step S2 describes constructing the voltage fluctuation similarity distance of each induction motor after disturbance based on the port voltage disturbance trajectory of each induction motor under a preset type of disturbance, and groups the induction motors according to the voltage fluctuation similarity distance. Step S3 describes grouping the induction motors based on the grouping results obtained in steps S1 and S2 respectively. The intersection of the grouping results of each induction motor is divided into the same group, and the other induction motors are divided into the same group to obtain the initial number of groups and the grouping results of each induction motor. In step S4, for each group obtained in step S3, based on the operating characteristics of the near-field new energy units of each induction motor in the same group, it is determined whether a part of each new energy unit has entered the low voltage ride-through state. If so, further grouping is performed according to the voltage drop depth of each induction motor port in each group. Otherwise, the initial number of groups and the grouping results of each induction motor remain unchanged. The calculation unit is used to aggregate the parameters of each induction motor in the same group using the capacity weighting method to obtain the model parameters of the equivalent induction motor.

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