A method and system for analyzing characteristics of cascading failure transient evolution of a power system

Abstract

The application belongs to the technical field of power systems, and provides a characteristic analysis method and system for transient evolution of power system cascading failures, comprising: acquiring a dynamic model of power system cascading failures containing new energy; based on the acquired dynamic model of cascading failures, considering the transient evolution process of power system cascading failures under different operation modes, constructing a power system cascading failure scenario; extracting the electrical quantity characteristics of the safety and stability events of cascading failures in the constructed power system cascading failure scenario; using the Spearman correlation coefficient method to analyze the correlation of the extracted electrical quantity characteristics of the safety and stability events, determining the electrical quantity characteristic change law of the transient evolution of the safety and stability events, judging the evolution direction of the cascading failures, and completing the characteristic analysis of the transient evolution of the power system cascading failures.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of power systems, and particularly relates to a feature analysis method and system for transient evolution of cascading faults of a power system. BACKGROUND

[0002] The statements in this section merely provide background information related to the application and do not necessarily constitute prior art.

[0003] With large-scale grid connection of wind power, photovoltaic power and other new energy sources, the scale of direct current long-distance power transmission continues to grow, and conventional generating units at the sending and receiving ends are largely replaced, so that the form and operating characteristics of the power grid change significantly. Compared with the traditional power system, the power grid structure of the new type of power system is more complex, and with the increasing proportion of power electronic equipment, the uncertainty of the equipment operating state increases, and the cascading fault process becomes more complex. At the same time, the low disturbance resistance, weak support and low inertia response characteristics of new energy power generation make it more affected than synchronous generating units after a fault occurs, and the cascading reaction time is shorter, further increasing the risk of system instability.

[0004] According to the inventors' understanding, the transient evolution process of cascading faults has highly nonlinear, uncertain and complex time sequence characteristics. The complexity and uncertainty of this cascading fault transient evolution process pose a great challenge to the safe and stable operation of the power system.

[0005] For the complex AC / DC hybrid power grid structure under the condition of high proportion of new energy, the cascading fault deduction model driven by steady-state overload is difficult to cover the diversity of events in the new type of power system, and the cascading fault analysis method based on steady-state power flow is no longer applicable to the weakly supported power electronic power grid. The uncertainty of new energy and the significant influence of conventional power generation dispatching on the operating mode of the power system cause a sharp increase in cascading fault samples, detailed simulation analysis is time-consuming, and it is difficult to meet the requirements of online application. SUMMARY

[0006] To solve the above problems, the application provides a feature analysis method and system for transient evolution of cascading faults of a power system, which extracts the characteristics of security and stability events in the transient evolution process of cascading faults to realize fast evaluation of the security and stability of the power system, greatly improve the evaluation efficiency of cascading faults of the power system, help system operation and maintenance personnel to make decisions quickly after a fault occurs, and reduce the impact of cascading faults on the operation of the power system.

[0007] According to some embodiments, the first aspect of the application provides a feature analysis method for transient evolution of cascading faults of a power system, which adopts the following technical scheme:

[0008] A feature analysis method for transient evolution of cascading faults of a power system, comprising:

[0009] Obtaining a cascading failure dynamic model of a power system containing new energy

[0010] Based on the obtained cascading failure dynamic model, considering the transient evolution process of the cascading failure of the power system under different operation modes, a cascading failure scenario of the power system is constructed.

[0011] Extracting the electrical quantity characteristics of the security and stability event of the cascading failure in the constructed cascading failure scenario of the power system.

[0012] The correlation of the extracted electrical quantity characteristics of the security and stability event is analyzed by using the Spearman correlation coefficient method, the variation law of the electrical quantity characteristics of the transient evolution of the security and stability event is determined, the evolution direction of the cascading failure is judged, and the characteristic analysis of the transient evolution of the cascading failure of the power system is completed.

[0013] As a further technical limitation, the obtained cascading failure dynamic model of the power system containing new energy at least includes generator / converter models, electrical control models and high / low voltage ride-through protection logic of wind power and photovoltaic; the active power control of the wind power adopts a control mode of superimposed frequency and speed, the active power control of the photovoltaic adopts a control mode of superimposed active power and frequency, and the reactive power control of the wind power and the photovoltaic adopts a constant voltage control mode.

[0014] As a further technical limitation, the obtaining process of the cascading failure dynamic model of the power system containing new energy is: based on the AC / DC hybrid model and the AC / DC alternating iteration calculation of AC power flow, the admittance matrix is generated; when the obtained AC power flow result converges, the power system state variable is initialized based on the AC power flow calculation result, otherwise the power system state variable cannot be initialized, and the dynamic simulation process is ended; the generated admittance matrix is updated according to the initialized power system state variable and the initial fault, and the algebraic differential equations are solved; if the algebraic differential equations converge, the device operation state is updated according to the power system device protection logic and the system operation state, otherwise the dynamic simulation of the cascading failure of the power system is ended; the current time is updated, if the initial fault is cleared at the current time, the power system device operation state is updated, otherwise the device operation state is updated and the initial fault is re-judged whether it is cleared; if the current time is greater than the preset dynamic simulation termination time, the cascading failure simulation of the power system is completed, and the dynamic simulation simulation result of the cascading failure of the power system containing new energy is obtained, otherwise the current time is updated and the algebraic differential equations are solved.

[0015] As a further technical limitation, the constructed cascading failure scenario of the power system at least includes cascading failure scenarios of different power grid topologies containing line faults, cascading failure scenarios under different new energy output conditions, and cascading failure scenarios under different load states.

[0016] As a further technical limitation, the safety and stability event at least includes a short circuit fault, a direct current commutation failure, a new energy low voltage ride through, and a new energy off-grid.

[0017] As a further technical limitation, the correlation coefficient between different electrical quantity characteristics extracted in the safety and stability event is calculated by the Spearman correlation coefficient method, the electrical quantity characteristics with an absolute value of the correlation coefficient greater than a correlation coefficient threshold are removed, and the safety and stability event electrical quantity characteristics are obtained; the correlation between each electrical quantity in different safety and stability events is calculated by the Spearman correlation coefficient method, a correlation coefficient data set between the pre-fault and post-fault events under different initial fault and operation scenarios is obtained, the correlation coefficient is used to represent the causal relationship between the safety and stability events, the electrical quantity characteristic change rule of the transient evolution of the safety and stability event is determined, the interaction between the initial fault equipment and the cascading fault equipment is obtained, the evolution direction of the cascading fault is judged, and the cascading fault transient evolution characteristics of the power system are analyzed.

[0018] According to some embodiments, the second aspect of the present application provides a characteristic analysis system for transient evolution of cascading faults in a power system, which adopts the following technical solution:

[0019] A characteristic analysis system for transient evolution of cascading faults in a power system, comprising:

[0020] An acquisition module configured to acquire a cascading fault dynamic model of a power system containing new energy;

[0021] A construction module configured to construct a cascading fault scenario of the power system based on the acquired cascading fault dynamic model, considering the transient evolution process of the cascading fault of the power system under different operation modes;

[0022] An extraction module configured to extract safety and stability event electrical quantity characteristics of the cascading fault in the constructed cascading fault scenario of the power system;

[0023] An analysis module configured to analyze the correlation of the extracted safety and stability event electrical quantity characteristics by the Spearman correlation coefficient method, determine the electrical quantity characteristic change rule of the transient evolution of the safety and stability event, judge the evolution direction of the cascading fault, and complete the characteristic analysis of the transient evolution of the cascading fault in the power system.

[0024] As a further technical limitation, in the acquisition module, the acquired cascading fault dynamic model of the power system containing new energy at least includes a generator / converter model, an electrical control model, and a high / low voltage ride through protection logic of wind power and photovoltaic; the active power control of the wind power adopts a frequency and speed superimposed control mode, the active power control of the photovoltaic adopts an active power and frequency superimposed control mode, and the reactive power control of the wind power and the photovoltaic both adopts a constant voltage control mode.

[0025] As a further technical limitation, in the acquisition module, the acquisition process of the new energy-containing power system cascading failure dynamic model is: based on the AC-DC hybrid model and the AC-DC alternating iterative calculation of AC power flow, a conductance matrix is generated; when the obtained AC power flow result converges, the power system state variable is initialized based on the AC power flow calculation result, otherwise the power system state variable cannot be initialized, and the dynamic simulation process is ended; the generated conductance matrix is updated according to the initialized power system state variable and the initial fault, and an algebraic differential equation set is solved; if the algebraic differential equation set converges, the device operating state is updated according to the power system device protection logic and the system operating state, otherwise the dynamic simulation of the power system cascading failure is ended; the current time is updated, and if the initial fault is cleared at the current time, the power system device operating state is updated, otherwise the device operating state is updated and the initial fault is re-judged whether it is cleared; if the current time is greater than the preset dynamic simulation termination time, the power system cascading failure simulation is completed, and a new energy-containing power system cascading failure dynamic simulation result is obtained, otherwise the current time is updated and the algebraic differential equation set is solved.

[0026] As a further technical limitation, in the construction module, the constructed power system cascading failure scenario at least includes a cascading failure scenario of different power grid topologies containing line faults, a cascading failure scenario under different new energy output conditions, and a cascading failure scenario under different load states.

[0027] As a further technical limitation, in the extraction module, the security and stability event at least includes a short-circuit fault, a DC commutation failure, a new energy low voltage ride-through, and a new energy off-grid.

[0028] As a further technical limitation, in the analysis module, the correlation coefficient between different electrical quantity characteristics extracted in the security and stability event is calculated by the Spearman correlation coefficient method, the electrical quantity characteristics with an absolute value of the correlation coefficient greater than a correlation coefficient threshold are removed, and the security and stability event electrical quantity characteristics are obtained; the correlation between each electrical quantity in different security and stability events is calculated by the Spearman correlation coefficient method, a correlation coefficient data set between the pre-fault event and the post-fault event under different initial fault and operating scenarios is obtained, the causal relationship between the security and stability events is characterized by the correlation coefficient, the electrical quantity characteristic change rule of the security and stability event transient evolution is determined, the interaction between the initial fault device and the cascading failure device is obtained, the evolution direction of the cascading failure is judged, and the power system cascading failure transient evolution characteristics are analyzed.

[0029] According to some embodiments, the third aspect of the present application provides a computer readable storage medium, which adopts the following technical scheme:

[0030] A computer readable storage medium having stored thereon a program which, when executed by a processor, implements the steps of the method for feature analysis of transient evolution of cascading failures of a power system according to the first aspect of the present application.

[0031] According to some embodiments, the fourth aspect of the present application provides an electronic device, which adopts the technical scheme as follows:

[0032] An electronic device comprises a memory, a processor and a program stored in the memory and running on the processor, and the processor implements the steps of the method for feature analysis of transient evolution of cascading failures of a power system according to the first aspect of the present application when executing the program.

[0033] According to some embodiments, the fifth aspect of the present application provides a computer program product, which adopts the technical scheme as follows:

[0034] A computer program product comprises software codes, and the program in the software codes implements the steps of the method for feature analysis of transient evolution of cascading failures of a power system according to the first aspect of the present application.

[0035] Compared with the prior art, the present application has the beneficial effects as follows:

[0036] The present application can better simulate the influence of various uncertain factors on cascading failures and cover more comprehensive security and stability events and obtain more comprehensive data under various operating modes of a power system.

[0037] The device control interaction under security and stability events makes cascading failures more complex. BRIEF DESCRIPTION OF DRAWINGS

[0038] The accompanying drawings, which form a part of this specification, are included to provide a further understanding of the embodiments of the present application and are incorporated in and constitute a part of this specification.

[0039] Figure 1 Flow chart of a characteristic analysis method of transient evolution of power system cascading faults in embodiment one of the present application;

[0040] Figure 2 New energy dynamic model diagram for cascading faults in embodiment one of the present application;

[0041] Figure 3 Simplified generator / converter model diagram in embodiment one of the present application;

[0042] Figure 4 New energy low voltage ride through tripping protection curve diagram in embodiment one of the present application;

[0043] Figure 5 New energy high voltage ride through tripping protection curve diagram in embodiment one of the present application;

[0044] Figure 6 Power system cascading fault dynamic model algorithm flow chart with new energy in embodiment one of the present application;

[0045] Figure 7 Short circuit fault electrical quantity characteristic change curve diagram in embodiment one of the present application;

[0046] Figure 8 Commutation failure electrical quantity characteristic change curve diagram in embodiment one of the present application;

[0047] Figure 9 New energy low voltage ride through electrical quantity characteristic change curve diagram in embodiment one of the present application;

[0048] Figure 10 New energy off-grid electrical quantity characteristic change curve diagram in embodiment one of the present application;

[0049] Figure 11 Structure block diagram of a characteristic analysis system of transient evolution of power system cascading faults in embodiment two of the present application. DETAILED DESCRIPTION

[0050] The present application will be further described below with reference to the accompanying drawings and embodiments.

[0051] It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the present application. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which the present application belongs.

[0052] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0053] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0054] Example 1

[0055] Embodiment 1 of this invention introduces a characteristic analysis method for transient evolution of cascading faults in power systems.

[0056] like Figure 1 The method for characterizing the transient evolution of cascading faults in a power system, as shown, includes:

[0057] Obtain a dynamic model of cascading failures in a power system containing new energy sources;

[0058] Based on the obtained dynamic model of cascading failures, the transient evolution process of cascading failures in the power system under different operating modes is considered, and a cascading failure scenario of the power system is constructed.

[0059] Extract the electrical quantity characteristics of the safety and stability events of cascading failures in the constructed power system cascading failure scenario;

[0060] The Spearman correlation coefficient method is used to analyze the correlation of the extracted electrical quantity characteristics of safety and stability events, determine the change law of electrical quantity characteristics in the transient evolution of safety and stability events, judge the evolution direction of cascading faults, and complete the characteristic analysis of the transient evolution of cascading faults in the power system.

[0061] This embodiment is based on a dynamic model of cascading faults in a power system including new energy sources. It constructs a large number of cascading fault scenarios covering different operating states such as line faults, new energy output fluctuations, and load changes, obtaining simulation data for these scenarios. For typical safety and stability events during the transient evolution of cascading faults, relevant electrical quantity features are extracted through mechanism analysis and data mining. Analysis of these extracted electrical quantity features reveals the changing patterns of electrical quantities during the transient evolution of safety and stability events. The Spearman correlation coefficient method is used to extract the correlation relationships between electrical quantities, and the correlation coefficient is used to characterize the causal relationships between safety and stability events during the transient evolution of cascading faults.

[0062] The existing cascading failure sample size is relatively limited, and the characteristic events covered have certain limitations and incompleteness. It is necessary to use simulation means to obtain sufficient cascading failure samples and data to provide strong support for the research of cascading failure. In order to describe the regulation capacity of the power grid after the disturbance occurs and meet the simulation needs of cascading failure, on the basis of considering the transmission line, conventional unit, double-end DC transmission and other devices, a cascading failure dynamic model of power system containing new energy is established to depict the interaction of different device links in the fault propagation process.

[0063] The new energy dynamic model for cascading failure in the embodiment is as shown in Figure 2 , wherein the generator / converter model and the electrical control model are applicable to wind turbines and photovoltaic devices, the red part represents the photovoltaic model, and the blue part represents the wind turbine model. The generator / converter model is the interface of wind turbine, photovoltaic device and network, and has a more flexible control mode and a faster response speed compared with the traditional generator model.

[0064] The wind turbine and the photovoltaic device in the embodiment both adopt the simplified current source model as shown in Figure 3 , which realizes the decoupling control of active and reactive power by cooperating with the phase-locked loop to track the phase angle of the terminal voltage; the electrical control model is divided into active control and reactive control two parts, which respectively provide the active current instruction I pcmd and the reactive current instruction I qcmd for the converter model. In the embodiment, the active control of the wind turbine adopts the frequency and speed superimposed control mode, the active control of the photovoltaic device adopts the active and frequency superimposed control mode, and the reactive control of the wind turbine and the photovoltaic device both adopt the constant voltage control mode.

[0065] New energy units have strict grid connection requirements, but their disturbance capacity is still lower than that of conventional units. When the disturbance exceeds its bearing capacity, there is a risk of large-scale disconnection. When the system fails and the voltage at the new energy end fluctuates, the new energy will enter the voltage ride-through state and have the ability to operate without disconnection within a certain voltage range and time. When the voltage at the grid connection point of the new energy drops to 0.2pu, it must be ensured that it does not disconnect within 625ms, and when the voltage at the grid connection point is restored to 0.9pu within 2s, the new energy can ensure that it does not disconnect. When the voltage is not higher than 1.3pu, the new energy device has the ability to continuously operate for 500ms, and when the voltage is not higher than 1.2pu, it has the ability to continuously operate for 10s. The new energy high and low voltage ride-through trip protection curves are as shown in Figure 4 and Figure 5 .

[0066] Combined with the dynamic model and protection logic of the new energy device, the embodiment adopts the method as shown in Figure 6 to construct the cascading failure dynamic model of the power system containing new energy, and the specific steps are as follows:

[0067] Step 1): Power flow calculation

[0068] Import the power flow model data and generate the admittance matrix. The model is a hybrid AC / DC system model, and the AC / DC alternating iteration method is used in power flow calculation, that is, the AC power flow is solved according to the injection power of the unit and the power of the load, and then the DC is solved using the results of the AC power flow and is equivalent to an AC load. If the power flow converges, go to step 2), if not, end the model.

[0069] Step 2): System state initialization

[0070] Initialize the state variables of the differential equation set according to the power flow calculation results, and ensure that the initial values of the state variables are reasonable and do not exceed the limit, otherwise the system will not be able to maintain a steady state. Initialize the current time t to 0s and the dynamic simulation step to 0.005s.

[0071] Step 3): Initial fault selection

[0072] The initial fault mainly considers the short-circuit fault of the transmission line, and since the three-phase short-circuit fault is more serious than the single-phase and two-phase short-circuit faults, the short-circuit fault type is considered to be three-phase short-circuit.

[0073] Step 4): Update the admittance matrix of the current system and solve the algebraic equation set

[0074] When a short-circuit fault occurs in the system, first process the short-circuit point using Y-Δ transformation, and then update the system admittance matrix.

[0075] Step 5): Solve the algebraic differential equation set

[0076] Solve the algebraic differential equation set using the implicit trapezoidal method, and if it converges, go to step 6); otherwise, end the simulation.

[0077] Step 6): Update the device operating state according to the device protection logic and system operating state.

[0078] Step 7): Update the current time t = t + dt

[0079] Determine whether a short-circuit fault clearing or protection action has occurred. If so, update the corresponding device state and go to step 4).

[0080] Step 8): If the current t is greater than the pre-set dynamic simulation termination time t max , go to step 9), otherwise go to step 5.

[0081] Step 9): End the cascading fault simulation and output the simulation results.

[0082] Power systems may be in normal, light load, heavy load and other operating states in actual operation. In the heavy load operating state, the line power flow is close to the transmission limit, and the system operating margin is small. At this time, if a short-circuit fault or other disturbance event occurs, the system instability risk is significantly increased compared to the normal operating state. In the light load operating state, although the overall system load demand is low, when the new energy unit output ratio is large, the shutdown of conventional units may significantly reduce the system inertia, thereby weakening the system's resistance to disturbances. In this case, even a slight initial fault can trigger new energy unit off-grid and other serious consequences, and may further evolve into a large-scale cascading failure.

[0083] When a short-circuit fault occurs in an AC power grid, the stability of a DC power transmission system will be severely tested. In the case of strong system voltage support capability, after the short-circuit fault is cleared, the commutation bus voltage and DC power can quickly recover, thereby avoiding the occurrence of DC blocking. However, in the case of weak system grid structure and insufficient voltage support capability, the DC system may experience continuous commutation failure after the first commutation failure, ultimately leading to DC blocking, thereby exacerbating the stability problem of the system.

[0084] Considering that the transient evolution process of cascading failures under different operating modes has significant differences, the present embodiment systematically constructs a large number of operating scenarios based on a cascading failure dynamic model of a power system containing new energy. For the transmission lines in the system, N-1, N-2, N-3 and other fault scenarios are set, and various changes in new energy penetration rate from low to high are considered, as well as different distributions of load ratio (such as light load, normal, heavy load and other load levels). Through the above multi-dimensional scenario combination, a large number of operating scenario sets are constructed, covering line faults, new energy output fluctuations and load changes. On this basis, the initial line fault is set based on the cascading failure dynamic model of the power system containing new energy, and a large number of cascading failure scenarios are simulated.

[0085] The large number of cascading failure scenarios constructed in the present embodiment can comprehensively cover the transient evolution process of cascading failures under multiple uncertain factors such as power grid topology, new energy output fluctuation and load change, and can also generate a large number of cascading failure data with statistical significance, providing reliable data support for subsequent feature extraction.

[0086] The transient evolution process of cascading failure is closely related to many factors such as power grid operation mode and device grid protection, and has strong uncertainty. High-dimensional uncertainty will lead to curse of dimensionality, reducing the efficiency of cascading failure risk assessment. The occurrence and transient evolution process of new-type power system cascading failure essentially have causal relationship, so the key event features can be extracted through mechanism analysis and data mining. The event that has causal relationship, promotes the evolution process of cascading failure and affects the security and stability of power system is defined as security and stability event. The electrical quantity features in typical security and stability events such as short-circuit fault, DC commutation failure, new energy low voltage ride-through and new energy off-grid are analyzed based on the massive cascading failure scenarios obtained by simulation.

[0087] The electrical quantity features in typical security and stability events are defined by mechanism analysis in this embodiment. When short-circuit fault occurs in the system, the voltage at the short-circuit point and surrounding area decreases and the current increases, so the electrical quantity features defined by short-circuit fault are the voltage and current at the short-circuit point.

[0088] When the voltage at the DC inversion side bus falls due to short-circuit fault of AC power grid, it will lead to decrease of DC voltage and increase of DC current, further leading to decrease of turn-off angle and triggering of commutation failure. The DC power transmission capacity decreases after commutation failure, and the active power of inversion station decreases accordingly, while the commutation failure will lead to increase of reactive power absorbed by inversion station. Therefore, the electrical quantity features defined by commutation failure event are the voltage at AC bus on inversion side, DC voltage, DC current, DC power, turn-off angle, active power of inversion station and reactive power of inversion station.

[0089] When the threshold voltage at the terminal of new energy device is lower than the threshold voltage caused by voltage drop due to short-circuit fault of AC power grid, the new energy enters fault ride-through state, at this time the control loop under normal operation is bypassed, and the active current command and reactive current command are determined by the control strategy in fault ride-through process. The reactive power will fluctuate in a large range after DC commutation failure, thereby causing voltage change around, and it is also possible to trigger the new energy to enter fault ride-through state. The active current command and reactive current command control strategies during low voltage ride-through period and low voltage ride-through recovery period of new energy are shown in formula (1), formula (2), formula (3) and formula (4) respectively:

[0090] I p_LVRT =K 1_Ip_LV V t +K 2_Ip_LV I p0 +I pset_LV (1)

[0091] Wherein, I p_LVRT is the active current command during low voltage ride-through period, K 1_Ip_LV , K 2_Ip_LV , I pset_LV are active current calculation coefficients, Vt is the terminal voltage amplitude, I p0 is the initial active current.

[0092] I q_LVRT = K 1_Iq_LV (0.9-V t ) + K 2_Iq_LV I q0 + I qset_LV (2)

[0093] wherein I q_LVRT is the reactive current instruction during low voltage ride through, K 1_Iq_LV , K 2_Iq_LV , I qset_LV are reactive current calculation coefficients, I q0 is the initial reactive current.

[0094]

[0095] wherein I p_LVRT2 is the active current instruction during low voltage ride through recovery, I p_LVRT0 is the active current instruction value when entering the recovery state, T p is the active current recovery time.

[0096]

[0097] wherein I q_LVRT2 is the reactive current instruction during low voltage ride through recovery, I q_LVRT0 is the reactive current instruction value when entering the recovery state, T q is the reactive current recovery time.

[0098] Therefore, in the embodiment, the electrical quantity characteristics defined by the new energy low voltage ride through event are terminal voltage, active current instruction, reactive current instruction, active current, reactive current, terminal current, active power and reactive power.

[0099] When the voltage support capability is insufficient, the new energy low voltage ride through failure leads to new energy off-grid. Therefore, the electrical quantity characteristics defined by the new energy off-grid event are the same as those of the new energy low voltage ride through event, i.e. terminal voltage, active current instruction, reactive current instruction, active current, reactive current, terminal current, active power and reactive power.

[0100] In the embodiment, the electrical quantity characteristic data corresponding to typical security and stability events is extracted from the obtained cascading failure scenario simulation data, the electrical quantity characteristics extracted are analyzed, the electrical quantity change law in the transient evolution process of the security and stability event is revealed, and thus the evolution direction of the cascading failure is judged.

[0101] The short-circuit fault occurs in the embodiment, and the change curve of the electrical quantity characteristics is as shown in Figure 7 The short-circuit fault occurs in the system, the voltage at the short-circuit point suddenly drops, and the current suddenly rises. After the short-circuit line is cut off, the voltage at the short-circuit point gradually recovers, and the current becomes 0.

[0102] The change curve of the electrical quantity characteristics when the direct current occurs commutation failure is as shown in Figure 8 The direct current voltage is lower than the threshold value, the direct current itself related electrical quantity becomes 0 when the commutation failure occurs, the active power and the reactive power of the inverter station also become 0, and the turn-off angle becomes 90°. After the commutation failure lasts for 0.2 s, the recovery state is entered, the trigger angle of the inverter side is adjusted to make the direct current voltage linearly recover from a certain value, the trigger angle is reduced accordingly, and the power factor is increased. At the same time, the direct current power gradually recovers, so that the reactive power demand of the inverter station increases, and the direct current will absorb the reactive power from the receiving end power grid for a long time, causing the voltage of the inverter side alternating current bus to drop.

[0103] The change curve of the electrical quantity characteristics when the new energy occurs low voltage ride through is as shown in Figure 9 When the machine end voltage drops to the threshold value 0.9pu, the new energy enters the low voltage ride through state, the active current instruction is reduced, the reactive current instruction is increased, the active current and the active power are reduced, and the reactive current and the reactive power are increased. After the machine end voltage is increased after the fault is cut off, the new energy enters the recovery state from the ride through state, the active current instruction is increased, the reactive current instruction is reduced, the active current and the active power are increased, and the reactive current and the reactive power are reduced. The active power gradually increases before the new energy enters the recovery state at 1.1 s because the voltage jumps at 1.1 s when the fault is cleared. After the active current instruction and the reactive current instruction recover to the initial value, the new energy enters the normal operation state from the recovery state.

[0104] The change curve of the electrical quantity characteristics when the new energy is off-grid is as shown in Figure 10 The electrical quantity change trend in the low voltage ride through state before the new energy is off-grid is the same as that described above, and the electrical quantity is 0 except the machine end voltage after the new energy is off-grid.

[0105] The embodiment can accurately determine the fault type and infer the evolution direction of the cascading failure by analyzing the change rule of the electrical quantity characteristics in the cascading failure safety and stability event. The short-circuit fault can be determined by the maximum voltage drop at the short-circuit point and the zero current after the fault line is cut off; the commutation failure is determined by the DC voltage being lower than the threshold value, and the recovery of the commutation failure into the recovery state is determined according to the recovery of the DC voltage, and the recovery of the commutation failure is completed when the DC voltage and the DC current recover to the set value; the determination of the low-voltage ride-through state is based on the drop of the terminal voltage of the new energy and the rise of the reactive current command according to the control strategy, and when the reactive current command begins to drop, it indicates that the new energy enters the recovery state; when the active current command and the reactive current command recover to the initial value, the system enters the normal state; the new energy off-grid can be determined by the electrical quantity being zero.

[0106] The Spearman correlation coefficient method is not disturbed by the data dimension, does not depend on the data distribution and is not sensitive to abnormal values, and can be used for correlation analysis of any two groups of data with the same length, and the calculation method is:

[0107]

[0108] wherein, ρ is the Spearman correlation coefficient, N is the total number of variables, X i and Y i are the rank of the i th observation value of two variables, respectively, and X and Y are the average rank.

[0109] The calculation result of the Spearman correlation coefficient ρ ranges from -1 to 1, a positive value indicates that the two variables are positively correlated, and a negative value indicates that the two variables are negatively correlated, and the absolute value of the calculation result can be used to represent the correlation degree between the two variables. 0.8-1.0 represents a strong correlation, 0.6-0.8 represents a strong correlation, 0.4-0.6 represents a moderate correlation, 0.2-0.4 represents a weak correlation, and 0-0.2 represents a weak or no correlation.

[0110] There are many electrical quantity characteristics in the extraction of typical safety and stability events, and there is a feature redundancy problem, and high-dimensional electrical quantity characteristics will affect the calculation and analysis speed and accuracy. The embodiment calculates the correlation coefficient between different electrical quantities extracted in the safety and stability event by the Spearman correlation coefficient method, and when the absolute value of the coefficient is greater than the threshold value C, it is considered that the two are redundant. After removing the redundant electrical quantity characteristics according to the correlation coefficient between different electrical quantities, the key electrical quantity characteristics representing the safety and stability events such as short-circuit fault, DC commutation failure, new energy low-voltage ride-through, and new energy off-grid are obtained.

[0111] The occurrence and transient evolution of cascading faults in new power systems are essentially causally related. After obtaining the key electrical quantity characteristics that characterize safety and stability events such as short-circuit faults, DC commutation failures, low-voltage ride-through of new energy sources, and new energy source disconnection from the grid, the Spearman correlation coefficient method is used to calculate the correlation between various electrical quantities in different safety and stability events. This yields a set of correlation coefficient data between preceding and subsequent fault events under different initial faults and operating scenarios. By characterizing the causal relationship between safety and stability events through correlation coefficients, the interaction between initial fault equipment and cascading fault equipment can be further obtained, enabling the identification of key events and evolution processes that lead to cascading faults.

[0112] This embodiment constructs a massive cascading failure scenario under various operating modes of the power system, which can better simulate the impact of various uncertainties on cascading failures, covering more comprehensive safety and stability events and obtaining more comprehensive data. The Spearman correlation coefficient method is used to perform correlation analysis on the electrical quantity features extracted from safety and stability events, which can eliminate redundant features and accelerate the accuracy and speed of power system safety and stability assessment. The electrical quantity features are used to characterize safety and stability events, and the correlation between key electrical quantity features is used to reveal the causal relationship between different safety and stability events, which can accelerate the identification of key events and evolution processes of power system cascading failures.

[0113] Example 2

[0114] Embodiment 2 of the present invention introduces a feature analysis system for transient evolution of cascading faults in power systems.

[0115] like Figure 11 The system shown is a feature analysis system for transient evolution of cascading faults in a power system, comprising:

[0116] The acquisition module is configured to acquire dynamic models of cascading faults in power systems containing new energy sources;

[0117] The module is configured to construct power system cascading failure scenarios based on the acquired dynamic model of cascading failures, taking into account the transient evolution process of power system cascading failures under different operating modes.

[0118] The extraction module is configured to extract the electrical quantity characteristics of the safety and stability events of cascading failures in the constructed power system cascading failure scenario;

[0119] The analysis module is configured to use the Spearman correlation coefficient method to analyze the correlation of the extracted electrical quantity characteristics of safety and stability events, determine the change law of electrical quantity characteristics in the transient evolution of safety and stability events, judge the evolution direction of cascading faults, and complete the characteristic analysis of the transient evolution of cascading faults in the power system.

[0120] As one or more implementations, in the obtaining module, the obtained power system cascading failure dynamic model with new energy includes at least generator / converter models, electrical control models and high / low voltage ride-through protection logics of wind power and photovoltaic power; the wind power active control adopts a control mode of frequency and speed superposition, the photovoltaic active control adopts a control mode of active power and frequency superposition, and the wind power and the photovoltaic reactive control both adopt a control mode of constant voltage.

[0121] As one or more implementations, in the obtaining module, the obtaining process of the power system cascading failure dynamic model with new energy is as follows: based on AC / DC hybrid model and AC / DC alternating iteration calculation of AC power flow, a conductance matrix is generated; when the obtained AC power flow result converges, power system state variables are initialized based on the AC power flow calculation result, otherwise the power system state variables cannot be initialized, and the dynamic simulation process is ended; the generated conductance matrix is updated according to the initialized power system state variables and initial fault, and algebraic differential equations are solved; if the algebraic differential equations converge, the device operating state is updated according to the power system device protection logic and system operating state, otherwise the dynamic simulation of power system cascading failure is ended; the current time is updated, if the initial fault is cleared at the current time, the power system device operating state is updated, otherwise the device operating state is updated and the initial fault is re-judged whether it is cleared; if the current time is greater than the preset dynamic simulation termination time, the power system cascading failure simulation is completed, and the dynamic simulation simulation result of the power system cascading failure with new energy is obtained, otherwise the current time is updated and the algebraic differential equations are solved.

[0122] As one or more implementations, in the constructing module, the constructed power system cascading failure scenario includes at least cascading failure scenarios of different power grid topologies with line fault, cascading failure scenarios under different new energy output conditions and cascading failure scenarios under different load states.

[0123] As one or more implementations, in the extracting module, the safety and stability event includes at least short-circuit fault, DC commutation failure, new energy low voltage ride-through and new energy off-grid.

[0124] As one or more implementations, in the analysis module, the correlation coefficients between different electrical quantity features extracted in the safety and stability event are calculated by the Spearman correlation coefficient method, the electrical quantity features with the absolute value of the correlation coefficient greater than a correlation coefficient threshold are removed, and the safety and stability event electrical quantity features are obtained; the correlation between each electrical quantity in different safety and stability events is calculated by the Spearman correlation coefficient method, the correlation coefficient data set between the pre-fault event and the post-fault event under different initial faults and operation scenarios is obtained, the correlation coefficient is used to represent the causal relationship between the safety and stability events, the change rule of the electrical quantity features in the transient evolution of the safety and stability event is determined, the interaction between the initial fault equipment and the cascading fault equipment is obtained, the evolution direction of the cascading fault is judged, and the transient evolution characteristics of the cascading fault of the power system are analyzed.

[0125] The detailed steps are the same as those of the power system cascading fault transient evolution characteristic analysis method provided in Embodiment 1, and will not be described here.

[0126] Embodiment 3

[0127] The embodiment 3 of the present application provides a computer readable storage medium.

[0128] A computer readable storage medium has a program stored thereon, and the program is executed by a processor to implement the steps in the power system cascading fault transient evolution characteristic analysis method according to the embodiment 1 of the present application.

[0129] The detailed steps are the same as those of the power system cascading fault transient evolution characteristic analysis method provided in Embodiment 1, and will not be described here.

[0130] Embodiment 4

[0131] The embodiment 4 of the present application provides an electronic device.

[0132] An electronic device includes a memory, a processor, and a program stored in the memory and running on the processor, and the processor executes the program to implement the steps in the power system cascading fault transient evolution characteristic analysis method according to the embodiment 1 of the present application.

[0133] The detailed steps are the same as those of the power system cascading fault transient evolution characteristic analysis method provided in Embodiment 1, and will not be described here.

[0134] Embodiment 5

[0135] The embodiment 5 of the present application provides a computer program product.

[0136] A computer program product includes software code, and a program in the software code executes the steps in the power system cascading fault transient evolution characteristic analysis method according to the embodiment 1 of the present application.

[0137] The detailed steps are the same as those of the method for analyzing the characteristics of the transient evolution of power system cascading faults provided in Embodiment 1, which will not be repeated here.

[0138] Those skilled in the art should understand that the embodiments of the present application can be provided as a method, a system, or a computer program product. Therefore, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROMs, optical storage devices, etc.) containing computer-usable program code. The solutions in the embodiments of the present application can be implemented in various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0139] The present application is described with reference to flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowcharts and / or block diagrams, as well as combinations of flows and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing apparatus to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing apparatus generate a means for implementing the functions specified in the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 means for carrying out the functions specified in the flowcharts and / or block diagrams.

[0140] These computer program instructions can also be stored in a computer-readable memory that can direct the computer or other programmable data processing apparatus to work in a specific manner, so that the instructions stored in the computer-readable memory produce a product including instruction means, which implement the functions specified in the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 means for carrying out the functions specified in the flowcharts and / or block diagrams.

[0141] These computer program instructions can also be loaded onto a computer or other programmable data processing apparatus, so that a series of operation steps are performed on the computer or other programmable data processing apparatus to produce a computer-implemented process, so that the instructions executed on the computer or other programmable data processing apparatus provide a means for implementing the functions specified in the flowcharts and / or block diagrams. Figure 1 one or more flows and / or blocks Figure 1 means for carrying out the functions specified in the flowcharts and / or block diagrams.

[0142] While the preferred embodiments of the application have been described, additional variations and modifications can be made to the embodiments without departing from the spirit and scope of the application. Therefore, it is intended that the appended claims cover all such modifications and variations as fall within the scope of the application.

[0143] It is apparent that many modifications and variations of this application can be effected although only a few are specified and described herein. No limitation is intended by the detailed description herein, which can be read as encompassing the exemplary designs described and all equivalent variations and modifications.

[0144] The above description is only preferred embodiments of the present application, and is not intended to limit the present application. The present application can be variously changed and modified by those skilled in the art without departing from the spirit and scope of the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the present application.

Claims

1. A method of analyzing the characteristics of a cascading failure transient evolution of an electric power system, characterized in that, The application relates to a method for analyzing the transient evolution characteristics of a new-energy-containing power system cascading failure. The method comprises the following steps: acquiring a new-energy-containing power system cascading failure dynamic model; based on the acquired cascading failure dynamic model, considering the transient evolution process of the power system cascading failure under different operation modes, constructing a power system cascading failure scenario; extracting the electrical quantity characteristics of the safety and stability events in the constructed power system cascading failure scenario; using the Spearman correlation coefficient method to analyze the correlation of the extracted safety and stability event electrical quantity characteristics, determining the electrical quantity characteristic change rule of the transient evolution of the safety and stability events, judging the evolution direction of the cascading failure, and completing the characteristic analysis of the transient evolution of the power system cascading failure; the acquisition process of the new-energy-containing power system cascading failure dynamic model is as follows: based on an AC / DC hybrid model and AC / DC alternating iteration calculation of AC power flow, a conductance matrix is generated; when the obtained AC power flow result converges, the AC power flow calculation result is used to initialize the power system state variable, otherwise the power system state variable cannot be initialized, and the dynamic simulation process is ended; the generated conductance matrix is updated according to the initialized power system state variable and the initial fault, and an algebraic differential equation set is solved; if the algebraic differential equation set converges, the device operation state is updated according to the power system device protection logic and the system operation state, otherwise the dynamic simulation of the power system cascading failure is ended; the current time is updated, if the initial fault is cleared at the current time, the power system device operation state is updated, otherwise the device operation state is updated and the initial fault is rejudged after the device operation state is updated; if the current time is greater than the preset dynamic simulation termination time, the power system cascading failure simulation is completed, and the new-energy-containing power system cascading failure dynamic simulation result is obtained, otherwise the current time is updated and the algebraic differential equation set is solved; 2. A method of feature analysis of power system cascading failure transient evolution as claimed in claim 1, wherein, the correlation coefficients between different electrical quantity characteristics extracted in the safety and stability events are calculated by using the Spearman correlation coefficient method, the electrical quantity characteristics with the correlation coefficient absolute value greater than the correlation coefficient threshold value are removed, and the safety and stability event electrical quantity characteristics are obtained; the correlation between each electrical quantity in different safety and stability events is calculated by using the Spearman correlation coefficient method, the correlation coefficient data set between the front and rear fault events under different initial faults and operation scenarios is obtained, the causality between the safety and stability events is represented by the correlation coefficient, the electrical quantity characteristic change rule of the transient evolution of the safety and stability events is determined, the interaction between the initial fault device and the cascading failure device is obtained, the evolution direction of the cascading failure is judged, and the transient evolution characteristics of the power system cascading failure are analyzed.

3. A method of feature analysis of power system cascading failure transient evolution as claimed in claim 1, wherein, The acquired new-energy-containing power system cascading failure dynamic model at least comprises a wind power generator / converter model, an electrical control model and high and low voltage ride-through protection logic of the wind power generator / converter; the active power control of the wind power generator adopts a frequency and speed superposition control mode, the active power control of the photovoltaic power generator adopts an active power and frequency superposition control mode, and the reactive power control of the wind power generator and the photovoltaic power generator both adopts a constant voltage control mode. The constructed power system cascading failure scenario at least comprises a cascading failure scenario of different power grid topological structures containing line faults, a cascading failure scenario under different new energy output conditions and a cascading failure scenario under different load states.

4. A method of feature analysis of power system cascading failure transient evolution as claimed in claim 1, wherein, The security and stability event at least includes a short circuit fault, a direct current commutation failure, a new energy low voltage ride through, and a new energy off-grid.

5. A system for characterizing cascading failure transient evolution in power systems, the system comprising: The method comprises the following steps: an acquisition module configured to acquire a new energy-containing power system cascading failure dynamic model; a construction module configured to construct a power system cascading failure scenario based on the acquired cascading failure dynamic model and considering transient evolution processes of power system cascading failures under different operating modes; an extraction module configured to extract security and stability event electrical quantity characteristics of cascading failures in the constructed power system cascading failure scenario; an analysis module configured to analyze correlations of the extracted security and stability event electrical quantity characteristics by using a Spearman correlation coefficient method, determine electrical quantity characteristic change rules of security and stability event transient evolution, judge an evolution direction of cascading failures, and complete characteristic analysis of power system cascading failure transient evolution; In the acquisition module, the acquisition process of the new energy-containing power system cascading failure dynamic model is as follows: based on an alternating current (AC) power flow calculation of an alternating current-direct current (AC-DC) hybrid model and an AC-DC alternating iteration, a conductance matrix is generated; when the obtained AC power flow result converges, power system state variables are initialized based on the AC power flow calculation result, otherwise the power system state variables cannot be initialized, and the dynamic simulation process is ended; the generated conductance matrix is updated according to the initialized power system state variables and an initial fault, and algebraic differential equations are solved; if the algebraic differential equations converge, device operating states are updated according to power system device protection logic and system operating states, otherwise the dynamic simulation of power system cascading failures is ended; the current time is updated, if the initial fault is cleared at the current time, the power system device operating states are updated, otherwise the device operating states are updated and the initial fault is re-judged whether it is cleared; if the current time is greater than a preset dynamic simulation termination time, the power system cascading failure simulation is completed, and a new energy-containing power system cascading failure dynamic simulation result is obtained, otherwise the current time is updated and the algebraic differential equations are solved; In the analysis module, a correlation coefficient between different electrical quantity characteristics extracted in the security and stability event is calculated by using the Spearman correlation coefficient method, an electrical quantity characteristic with an absolute value of the correlation coefficient greater than a correlation coefficient threshold value is eliminated, and a security and stability event electrical quantity characteristic is obtained; correlations between electrical quantities in different security and stability events are calculated by using the Spearman correlation coefficient method, a correlation coefficient data set between front and rear fault events under different initial faults and operating scenarios is obtained, a causal relationship between security and stability events is represented by the correlation coefficient, electrical quantity characteristic change rules of security and stability event transient evolution are determined, interactive influences of initial fault devices and cascading failure devices are obtained, an evolution direction of cascading failures is judged, and power system cascading failure transient evolution characteristics are analyzed.

6. A system for characterizing the transient evolution of a cascading failure in a power system as claimed in claim 5, wherein, In the acquisition module, the acquired power system cascading failure dynamic model includes at least generator / converter models, electrical control models and high / low voltage ride-through protection logic of wind power and photovoltaic power; the active power control of the wind power adopts a control mode of frequency and speed superposition, the active power control of the photovoltaic power adopts a control mode of active power and frequency superposition, and the reactive power control of the wind power and the photovoltaic power both adopts a constant voltage control mode.

7. A system for characterizing the transient evolution of a cascading failure in a power system as recited in claim 5, wherein, In the construction module, the constructed power system cascading failure scene includes at least cascading failure scenes of different power grid topologies with line faults, cascading failure scenes under different new energy output conditions and cascading failure scenes under different load conditions.

8. A system for characterizing the transient evolution of a cascading failure in a power system as recited in claim 5, wherein, In the extraction module, the safety and stability event includes at least short-circuit fault, direct current commutation failure, new energy low voltage ride-through and new energy off-grid.

9. A computer-readable storage medium having stored thereon a computer program, characterized in that, The program is executed by the processor to realize the steps of the characteristic analysis method of the power system cascading failure transient evolution according to any one of claims 1-4.

10. An electronic device comprising a memory, a processor, and a computer program stored on the memory and running on the processor, characterized in that, The processor executes the program to realize the steps of the characteristic analysis method of the power system cascading failure transient evolution according to any one of claims 1-4.

11. A computer program product comprising software code, characterized in that, The program in the software code executes the steps of the characteristic analysis method of the power system cascading failure transient evolution according to any one of claims 1-4.

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