Characteristic analysis method and system for cascading failure transient evolution of power system

Abstract

The invention belongs to the technical field of power systems, and provides a power system cascading failure transient evolution feature analysis method and system, and the method comprises the steps: obtaining a new energy-containing power system cascading failure dynamic model; based on the obtained cascading failure dynamic model, considering the transient evolution process of the cascading failure of the power system in different operation modes, and constructing a cascading failure scene of the power system; extracting safety and stability event electrical quantity characteristics of the cascading failure in the established power system cascading failure scene; and analyzing the correlation of the extracted electrical quantity characteristics of the safety and stability event by adopting a Spearman correlation coefficient method, determining an electrical quantity characteristic change rule of transient evolution of the safety and stability event, judging an evolution direction of the cascading failure, and completing characteristic analysis of transient evolution of the cascading failure of the power system.

Description

Technical Field

[0001] The present invention belongs to the technical field of power systems, and particularly relates to a method and system for analyzing the characteristics of the transient evolution of cascading faults in a power system. Background Art

[0002] The statements in this part only provide background technical information related to the present invention and do not necessarily constitute prior art.

[0003] With the large-scale grid connection of new energy sources such as wind power and photovoltaic power, the scale of DC long-distance power transmission continues to grow, and a large number of conventional units at the power receiving and sending ends have been replaced, resulting in significant changes in the grid form and operating characteristics. Compared with traditional power systems, the grid structure of new power systems is more complex, and with the increasing proportion of power electronic equipment, the uncertainty of equipment operating states increases, and the process of cascading faults becomes more complex. At the same time, the characteristics of new energy power generation such as low anti-interference, weak support, and low inertia response lead to greater impacts on it after a fault occurs compared with synchronous units and shorter cascading reaction times, further increasing the risk of system instability.

[0004] According to the inventor's understanding, the transient evolution process of cascading faults has highly non-linear, uncertain, and complex time-series characteristics. The complexity and uncertainty of this transient evolution process of cascading faults pose great pressure on the safe and stable operation of power systems.

[0005] For the AC-DC hybrid complex grid structure under the high-proportion new energy form, the cascading fault deduction model driven by steady-state overload is difficult to cover the diverse events in new power systems, and the method for analyzing cascading faults based on steady-state power flow is no longer applicable to weakly supported power electronic grids. The uncertainty of new energy and the significant impact of conventional power generation scheduling on the operation mode of power systems lead to a sharp increase in cascading fault samples, and detailed simulation analysis takes a long time, making it difficult to meet the requirements of online applications. Summary of the Invention

[0006] To solve the above problems, the present invention proposes a method and system for analyzing the characteristics of the transient evolution of cascading faults in a power system, extracting the characteristics of safe and stable events in the transient evolution process of cascading faults to achieve a safe, stable, and rapid assessment of the power system, greatly improving the assessment efficiency of cascading faults in the power system, helping system operation and maintenance personnel make rapid decisions after a fault occurs, and reducing the impact of cascading faults on the operation of the power system.

[0007] According to some embodiments, the first solution of the present invention provides a method for analyzing the characteristics of the transient evolution of cascading faults in a power system, adopting the following technical solutions:

[0008] A method for analyzing the characteristics of the transient evolution of cascading faults in a power system includes:

[0009] Obtain the dynamic model of cascading failures in a power system with new energy;

[0010] Based on the obtained dynamic model of cascading failures, consider the transient evolution process of cascading failures in the power system under different operating modes, and construct the cascading failure scenarios of the power system;

[0011] Extract the electrical quantity characteristics of the security and stability events of cascading failures in the constructed cascading failure scenarios of the power system;

[0012] Use the Spearman correlation coefficient method to analyze the correlation of the extracted electrical quantity characteristics of security and stability events, determine the variation law of the electrical quantity characteristics of the transient evolution of security and stability events, judge the evolution direction of cascading failures, and complete the characteristic analysis of the transient evolution of cascading failures in the power system.

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

[0014] As a further technical limitation, the process of obtaining the dynamic model of cascading failures in the power system with new energy is as follows: based on the AC-DC hybrid model and AC-DC alternating iterative calculation of the AC power flow, generate the admittance matrix; when the obtained AC power flow result converges, initialize the power system state variables based on the AC power flow calculation result, otherwise the power system state variables cannot be initialized and the dynamic simulation process ends; update the generated admittance matrix according to the initialized power system state variables and the initial fault, and solve the algebraic differential equations; if the algebraic differential equations converge, update the equipment operating state according to the power system equipment protection logic and the system operating state, otherwise end the dynamic simulation of the cascading failures in the power system; update the current time, if the initial fault is cleared at the current time, update the power system equipment operating state, otherwise update the equipment operating state and then re-judge whether the initial fault is cleared; if the current time is greater than the preset dynamic simulation termination time, complete the simulation of the cascading failures in the power system and obtain the dynamic simulation and simulation results of the cascading failures in the power system with new energy, otherwise update the current time and solve the algebraic differential equations.

[0015] As a further technical limitation, the constructed cascading failure scenarios of the power system at least include cascading failure scenarios with different 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 security and stability events at least include short - circuit faults, DC commutation failures, new - energy low - voltage ride - through, and new - energy grid disconnection.

[0017] As a further technical limitation, the correlation coefficients between different electrical quantity characteristics extracted from security and stability events are calculated by the Spearman correlation coefficient method, and the electrical quantity characteristics with the absolute value of the correlation coefficient greater than the correlation coefficient threshold are removed to obtain the electrical quantity characteristics of security and stability events; the Spearman correlation coefficient method is used to calculate the correlation between each electrical quantity in different security and stability events, and a correlation coefficient data set between pre - and post - fault events under different initial faults and operating scenarios is obtained. The causal relationship between security and stability events is characterized by the correlation coefficient, the change law of electrical quantity characteristics in the transient evolution of security and stability events is determined, the interaction between the initial fault equipment and the cascading fault equipment is obtained, the evolution direction of cascading faults is judged, and the transient evolution characteristics of power system cascading faults are analyzed.

[0018] According to some embodiments, the second solution of the present invention provides a feature analysis system for the transient evolution of power system cascading faults, adopting the following technical solution:

[0019] A feature analysis system for the transient evolution of power system cascading faults includes:

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

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

[0022] An extraction module configured to extract the electrical quantity characteristics of security and stability events of cascading faults in the constructed power system cascading fault scenarios;

[0023] An analysis module configured to analyze the correlation of the extracted electrical quantity characteristics of security and stability events by the Spearman correlation coefficient method, determine the change law of electrical quantity characteristics in the transient evolution of security and stability events, judge the evolution direction of cascading faults, and complete the feature analysis of the transient evolution of power system cascading faults.

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

[0025] As a further technical limitation, in the obtaining module, the process of obtaining the dynamic model of cascading faults in the power system containing new energy is as follows: Based on the AC-DC hybrid model and AC-DC alternating iteration to calculate the AC power flow, a admittance matrix is generated; when the obtained AC power flow result converges, the 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 ends; the generated admittance matrix is updated according to the initialized power system state variables and the initial fault, and the 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 the system operating state, otherwise the dynamic simulation of the power system cascading faults ends; the current time is updated. If the initial fault is cleared at the current time, the power system device operating state is updated, otherwise after updating the device operating state, it is re-determined whether the initial fault is cleared; if the current time is greater than the preset dynamic simulation termination time, the simulation of the power system cascading faults is completed to obtain the dynamic simulation and simulation result of the cascading faults in the power system containing new energy, otherwise the current time is updated and the algebraic differential equations are solved.

[0026] As a further technical limitation, in the constructing module, the constructed power system cascading fault scenarios at least include cascading fault scenarios with different grid topologies containing line faults, cascading fault scenarios under different new energy output conditions, and cascading fault scenarios under different load states.

[0027] As a further technical limitation, in the extracting module, the security and stability events at least include short-circuit faults, DC commutation failures, new energy low-voltage ride-through, and new energy islanding.

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

[0029] According to some embodiments, the third aspect of the present invention provides a computer-readable storage medium, adopting the following technical solution:

[0030] A computer-readable storage medium stores a program thereon, and when the program is executed by a processor, it implements the steps in a method for analyzing characteristics of transient evolution of cascading faults in a power system as described in the first solution of the present invention.

[0031] According to some embodiments, the fourth solution of the present invention provides an electronic device, adopting the following technical solution:

[0032] An electronic device includes a memory, a processor, and a program stored on the memory and running on the processor. When the processor executes the program, it implements the steps in a method for analyzing characteristics of transient evolution of cascading faults in a power system as described in the first solution of the present invention.

[0033] According to some embodiments, the fifth solution of the present invention provides a computer program product, adopting the following technical solution:

[0034] A computer program product includes software code, and the program in the software code executes the steps in a method for analyzing characteristics of transient evolution of cascading faults in a power system as described in the first solution of the present invention.

[0035] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0036] The present invention constructs a large number of cascading fault scenarios under various operating modes of the power system, can better simulate the influence of various uncertain factors on cascading faults, cover more comprehensive security and stability events, and obtain more comprehensive data; uses the Spearman correlation coefficient method (i.e., the Spearman correlation coefficient method) to analyze the correlation of electrical quantity characteristics extracted from security and stability events, can eliminate redundant characteristics, and accelerate the accuracy and speed of security and stability assessment of the power system; uses electrical quantity characteristics to characterize security and stability events, and uses the correlation relationship between key electrical quantity characteristics to reveal the causal relationship between different security and stability events, can accelerate the identification of key events and evolution processes of cascading faults in the power system.

[0037] The device control interaction under security and stability events makes cascading faults more complex. To determine the evolution direction of key events of cascading faults and subsequent rapid screening and preventive control of cascading faults, it is necessary to study the fault event characteristics in the transient evolution process of cascading faults, identify the key factors promoting cascading faults, analyze the causal relationship between cascading fault events, and provide a basis for the rapid screening and preventive control of cascading faults. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The accompanying drawings forming a part of this embodiment are used to provide a further understanding of this embodiment. The schematic embodiments and descriptions thereof of this embodiment are used to explain this embodiment and do not constitute an improper limitation to this embodiment.

[0039] Figure 1 Flow chart of a method for analyzing characteristics of transient evolution of cascading faults in a power system in the first embodiment of the present invention;

[0040] Figure 2 Schematic diagram of a new energy dynamic model for cascading faults in the first embodiment of the present invention;

[0041] Figure 3 Schematic diagram of a simplified generator / converter model in the first embodiment of the present invention;

[0042] Figure 4 Schematic diagram of a new energy low voltage ride through generator tripping protection curve in the first embodiment of the present invention;

[0043] Figure 5 Schematic diagram of a new energy high voltage ride through generator tripping protection curve in the first embodiment of the present invention;

[0044] Figure 6 Flow chart of an algorithm for a dynamic model of cascading faults in a power system with new energy in the first embodiment of the present invention;

[0045] Figure 7 Schematic diagram of a curve of characteristic changes of electrical quantities in a short circuit fault in the first embodiment of the present invention;

[0046] Figure 8 Schematic diagram of a curve of characteristic changes of electrical quantities in commutation failure in the first embodiment of the present invention;

[0047] Figure 9 Schematic diagram of a curve of characteristic changes of electrical quantities in new energy low voltage ride through in the first embodiment of the present invention;

[0048] Figure 10 Schematic diagram of a curve of characteristic changes of electrical quantities in new energy grid disconnection in the first embodiment of the present invention;

[0049] Figure 11 Block diagram of the structure of a system for analyzing characteristics of transient evolution of cascading faults in a power system in the second embodiment of the present invention. Detailed implementation manners

[0050] The present invention will be further described below in conjunction with 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 invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which the present invention belongs.

[0052] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular forms are also intended to include the plural forms. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they specify the presence of features, steps, operations, devices, components, and / or combinations thereof.

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

[0054] Embodiment 1

[0055] Embodiment 1 of the present invention introduces a method for analyzing the characteristics of the transient evolution of cascading failures in a power system.

[0056] As Figure 1 shown, a method for analyzing the characteristics of the transient evolution of cascading failures in a power system includes:

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

[0058] Based on the obtained dynamic model of cascading failures, consider the transient evolution process of cascading failures in the power system under different operating modes, and construct a cascading failure scenario of the power system;

[0059] Extract the electrical quantity characteristics of the security and stability event of the cascading failure in the constructed cascading failure scenario of the power system;

[0060] Use the Spearman correlation coefficient method to analyze the correlation of the extracted electrical quantity characteristics of the security and stability event, determine the change law of the electrical quantity characteristics of the transient evolution of the security and stability event, and judge the evolution direction of the cascading failure to complete the characteristic analysis of the transient evolution of the cascading failure in the power system.

[0061] Based on the dynamic model of cascading failures in a power system with new energy, this embodiment constructs a large number of cascading failure scenarios under different operating states covering line failures, new energy output fluctuations, and load changes, and obtains cascading failure scenario simulation data. For typical security and stability events in the transient evolution process of cascading failures, relevant electrical quantity characteristics are extracted through mechanism analysis and data mining. By analyzing the extracted electrical quantity characteristics, the change law of electrical quantities in the transient evolution process of security and stability events is revealed; based on the Spearman correlation coefficient method, the electrical quantity correlation relationship is extracted, and the causal relationship between security and stability events in the transient evolution process of cascading failures is characterized by the correlation coefficient.

[0062] The scale of existing cascading failure samples is relatively limited, and there are certain limitations and incompleteness in the characteristic events covered. It is necessary to use simulation means to obtain sufficient cascading failure samples and data to provide strong support for the research of cascading failures. To describe the grid regulation ability after disturbances and meet the requirements of cascading failure simulation, a dynamic model of cascading failures in a power system with new energy is established on the basis of considering equipment such as transmission lines, conventional units, and bipolar DC transmission, so as to depict the interaction of different equipment links during the fault propagation process.

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

[0064] Both the wind turbines and photovoltaics in this embodiment adopt Figure 3 the simplified current source model shown, and cooperate with the phase-locked loop to track the phase angle of the terminal voltage to achieve decoupled control of active and reactive power; the electrical control model is divided into two parts: active power control and reactive power control, which respectively provide the active current command I pcmd and the reactive current command I qcmd for the converter model. In this embodiment, the active power control of the wind turbine adopts the frequency and speed superposition control mode, the active power control of the photovoltaic adopts the active power and frequency superposition control mode, and the reactive power control of both the wind turbine and the photovoltaic adopts the constant voltage control mode.

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

[0066] Combining the dynamic model and protection logic of new energy equipment, this embodiment adopts the method shown in Figure 6 to construct a dynamic model of cascading failures in a power system with new energy. The specific steps are as follows:

[0067] Step 1): Power flow calculation

[0068] Import the power flow model data and generate the admittance matrix. This model is a hybrid AC-DC system model. In the power flow calculation, the AC-DC alternating iteration method is adopted, that is, the AC power flow is solved according to the injection power of the units and the power of the loads, 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 it does not converge, end the model.

[0069] Step 2): System state initialization

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

[0071] Step 3): Selection of initial fault

[0072] The initial fault mainly considers the short-circuit fault of the transmission line. 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 as a three-phase short circuit.

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

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

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

[0076] Use the implicit trapezoidal method to jointly solve the algebraic differential equation system. 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 the system operating state.

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

[0079] Judge whether a short-circuit fault is cleared or a protection action occurs. If so, update the corresponding device state and go to Step 4).

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

[0081] Step 9): The cascading fault simulation ends, and the simulation results are output.

[0082] In actual operation, the power system may be in various operating states such as normal, light load, and heavy load. In the heavy-load operating state, the line power flow approaches the transmission limit, and the system operating margin is small. At this time, if a disturbance event such as a short-circuit fault occurs, compared with the normal operating state, the risk of system instability increases significantly. In the light-load operating state, although the overall load demand of the system is low, when the output of new energy units accounts for a large proportion, the outage of conventional units may lead to a significant reduction in the system inertia, thereby weakening the anti-disturbance ability of the system. In this case, even a slight initial fault may cause serious consequences such as the disconnection of new energy units from the grid and may further evolve into large-scale cascading faults.

[0083] When a short-circuit fault occurs in the AC power grid, the stability of the DC transmission system will be severely tested. When the system voltage support ability is strong, after the short-circuit fault is cleared, the converter bus voltage and DC power can quickly recover, thus avoiding the occurrence of DC blocking. However, when the system grid structure is weak and the voltage support ability is insufficient, the DC system may experience consecutive commutation failures after the first commutation failure, ultimately leading to DC blocking, which further exacerbates the system stability problem.

[0084] Considering that the transient evolution processes of cascading faults under different operating modes are significantly different, in this embodiment, based on the dynamic model of cascading faults in a power system with new energy, a large number of operating scenarios are systematically constructed. For the transmission lines in the system, fault scenarios such as N-1, N-2, N-3, etc. are set, and at the same time, various changes in the new energy penetration rate from low to high are considered, as well as different distributions of the load ratio (such as various load levels such as light load, normal, and heavy load); through the above multi-dimensional scenario combinations, a large number of operating scenario sets covering line faults, new energy output fluctuations, and load changes are constructed. On this basis, based on the dynamic model of cascading faults in a power system with new energy, an initial line fault is set, and a large number of cascading fault scenarios are obtained through simulation.

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

[0086] The transient evolution process of cascading failures is closely related to many factors such as the operation mode of the power grid and the network-related protection of equipment, and there is a strong uncertainty. In addition, high-dimensional uncertainty will lead to the curse of dimensionality and reduce the efficiency of cascading failure risk assessment. The occurrence and transient evolution process of cascading failures in new power systems are essentially causal, so the key event characteristics can be extracted through mechanism analysis and data mining. Events that have causal relationships, promote the evolution of cascading failures, and affect the safety and stability of the power system are defined as safety and stability events. For the massive cascading failure scenarios obtained through simulation, the electrical quantity characteristics in typical safety and stability events such as short-circuit faults, DC commutation failures, new energy low voltage ride-through, and new energy grid disconnection are analyzed.

[0087] This embodiment defines the electrical quantity characteristics in typical safety and stability events through mechanism analysis. When a short circuit fault occurs in the system, the voltage at the short circuit point and the surrounding area drops and the current rises. Therefore, the electrical quantity characteristics defined by the short circuit fault are the voltage and current at the short circuit point.

[0088] When the AC grid short-circuit fault causes the DC inverter-side commutation bus voltage to drop, it will cause the DC voltage to decrease and the DC current to increase, which will further lead to a decrease in the cut-off angle and cause a commutation failure. After the commutation failure, the DC power transmission capacity decreases, and the active power of the inverter station decreases accordingly. At the same time, the commutation failure will cause the inverter station to absorb more reactive power. Therefore, the electrical quantity characteristics defined by the commutation failure event are the AC bus voltage on the inverter side, DC voltage, DC current, DC power, cut-off angle, inverter station active power, and inverter station reactive power.

[0089] When the voltage drop caused by the AC grid short circuit causes the terminal voltage of the new energy equipment to be lower than the threshold, the new energy enters the fault ride-through state. At this time, the control link under normal operation is bypassed, and the active current command and reactive current command are determined by the control strategy during the fault ride-through process. After the DC commutation fails, the reactive power will fluctuate over a large range, causing the surrounding voltage to change, and may also cause the new energy to enter the fault ride-through state. The active current command and reactive current command control strategies of the new energy during the low voltage ride-through period and the low voltage ride-through recovery period 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] Among them, I p_LVRT is the active current command during low voltage ride-through, K 1_Ip_LV , K 2_Ip_LV ,I pset_LV is the active current calculation coefficient, Vt is the terminal voltage amplitude, and 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 command during low - voltage ride - through, K 1_Iq_LV , K 2_Iq_LV , I qset_LV are the reactive current calculation coefficients, and I q0 is the initial reactive current.

[0094]

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

[0096]

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

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

[0099] When the voltage support ability is insufficient, the new - energy low - voltage ride - through fails, resulting in the disconnection of the new - energy power grid. Therefore, the electrical quantity characteristics defined by the new - energy power - grid disconnection event are the same as those of the new - energy low - voltage ride - through event, namely the terminal voltage, active current command, reactive current command, active current, reactive current, terminal current, active power, and reactive power.

[0100] In this embodiment, the electrical quantity characteristic data corresponding to typical safety - stable events are extracted from the obtained simulation data of cascading - fault scenarios. By analyzing the extracted electrical quantity characteristics, the variation law of electrical quantities during the transient evolution process of safety - stable events is revealed, so as to judge the evolution direction of cascading faults.

[0101] After a short-circuit fault occurs in this embodiment, the change curve of the electrical quantity characteristics is as follows Figure 7 shown. That is, when a short-circuit fault occurs in the system, the voltage at the short-circuit point drops suddenly, and the current surges. When the short-circuit line is removed, the voltage at the short-circuit point gradually recovers, and the current becomes 0.

[0102] When commutation failure occurs in the DC of this embodiment, the change curve of the electrical quantity characteristics is as follows Figure 8 shown. That is, commutation failure occurs when the DC voltage is lower than the threshold. When commutation failure occurs, the electrical quantities related to the DC itself become 0, the active power and reactive power of the inverter station also become 0, and the extinction angle becomes 90°; after the commutation failure lasts for 0.2 s, it enters the recovery state. The trigger angle on the inverter side adjusts the DC voltage to linearly recover it from a certain value, and the trigger angle decreases accordingly, and the power factor increases accordingly. At the same time, the DC power gradually recovers, increasing the reactive power demand of the inverter station. The DC will absorb reactive power from the receiving-end power grid for a long time, causing the voltage of the AC bus on the inverter side to drop.

[0103] When low-voltage ride-through occurs in the new energy of this embodiment, the change curve of the electrical quantity characteristics is as follows Figure 9 shown. That is, when the terminal voltage drops to the threshold of 0.9 pu, the new energy enters the low-voltage ride-through state. The active current command decreases, and the reactive current command increases, corresponding to the decrease in active current and active power, and the increase in reactive current and reactive power. When the terminal voltage rises after the fault is removed, the new energy enters the recovery state from the ride-through state. At this time, the active current command increases, and the reactive current command decreases, corresponding to the increase in active current and active power, and the decrease in reactive current and reactive power. The reason why the active power gradually increases before the new energy enters the recovery state at 1.1 s is that the voltage jumps at 1.1 s when the fault is cleared. When the active current command and the reactive current command return to the initial values, the new energy enters the normal operation state from the recovery state.

[0104] When the new energy is disconnected from the grid in this embodiment, the change curve of the electrical quantity characteristics is as follows Figure 10 shown: The change trend of the electrical quantities in the low-voltage ride-through state before the new energy is disconnected from the grid is the same as that of the low-voltage ride-through state described above. After the new energy is disconnected from the grid, all electrical quantities except the terminal voltage become 0.

[0105] In this embodiment, by analyzing the variation law of electrical quantity characteristics in chain fault safety and stability events, the fault type can be accurately determined, and thus the evolution direction of chain faults can be inferred. A short-circuit fault can be judged by the fact that the voltage drop at the short-circuit point is the largest and the current becomes zero after the faulty line is removed; commutation failure is judged by the DC voltage being lower than the threshold, and the recovery state of commutation failure is judged according to the recovery of the DC voltage. When the DC voltage and DC current recover to the set values, the commutation failure recovery is completed; the determination of the low-voltage ride-through state is based on the decline of the terminal voltage of new energy and the rise of its reactive current command according to the control strategy. When the reactive current command starts to decline, it means that the new energy enters the recovery state; when the active current command and reactive current command recover to the initial values, the system enters the normal state; the disconnection of new energy can be judged by the electrical quantity being zero.

[0106] The Spearman correlation coefficient method is not affected by the data dimension, does not depend on the data distribution, and is not sensitive to outliers. It can be used for the correlation analysis of any two sets of data with the same length. Its calculation method is as follows:

[0107]

[0108] where ρ is the Spearman correlation coefficient, N is the total number of variables, X i and Y i are the rank orders of the i-th observations of the two variables, are the average rank orders of X and respectively.

[0109] The calculation result range of the Spearman correlation coefficient ρ is [-1, 1]. A positive value indicates a positive correlation between the two variables, and a negative value indicates a negative correlation between the two variables. The absolute value of its calculation result can be used to characterize the strength of the correlation between the two variables. 0.8 - 1.0 indicates a very strong correlation, 0.6 - 0.8 indicates a strong correlation, 0.4 - 0.6 indicates a medium correlation, 0.2 - 0.4 indicates a weak correlation, and 0 - 0.2 indicates a very weak correlation or no correlation.

[0110] There are a large number of electrical quantity characteristics extracted from typical safety and stability events, and there is a problem of feature redundancy. High-dimensional electrical quantity characteristics will affect the calculation analysis speed and accuracy. In this embodiment, the correlation coefficients between different electrical quantities extracted from safety and stability events are calculated by the Spearman correlation coefficient method. When the absolute value of the coefficient is greater than the threshold C, the two are considered redundant. After removing the redundant electrical quantity characteristics according to the correlation coefficients between different electrical quantities, the key electrical quantity characteristics representing safety and stability events such as short-circuit faults, DC commutation failures, low-voltage ride-through of new energy, and disconnection of new energy are obtained.

[0111] The occurrence and transient evolution process of cascading failures in a new type of power system are essentially causally related. After obtaining the key electrical quantity characteristics representing safety and stability events such as short-circuit faults, DC commutation failures, low-voltage ride-through of new energy, and disconnection of new energy from the grid, the Spearman correlation coefficient method is used to calculate the correlation between electrical quantities in different safety and stability events, obtaining a set of correlation coefficient data between pre-fault and post-fault events under different initial faults and operating scenarios. The causal relationship between safety and stability events is characterized by the correlation coefficient, and further, the interactive influence between the initial fault equipment and cascading fault equipment is obtained to realize the identification of key events and evolution processes leading to cascading failures.

[0112] In this embodiment, a large number of cascading fault scenarios are constructed under various operating modes of the power system, which can better simulate the influence of various uncertain factors on cascading failures, cover more comprehensive safety and stability events, and obtain more comprehensive data. The Spearman correlation coefficient method is used to analyze the correlation of electrical quantity characteristics extracted from safety and stability events, which can eliminate redundant characteristics and accelerate the accuracy and speed of power system safety and stability assessment. Using electrical quantity characteristics to represent safety and stability events and revealing the causal relationship between different safety and stability events through the correlation relationship between key electrical quantity characteristics can accelerate the identification of key events and evolution processes of power system cascading failures.

[0113] Embodiment 2

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

[0115] As Figure 11 shown, a feature analysis system for the transient evolution of power system cascading failures includes:

[0116] An acquisition module configured to acquire a dynamic model of power system cascading failures with new energy;

[0117] A construction module configured to construct power system cascading fault scenarios based on the acquired dynamic model of cascading failures, considering the transient evolution process of power system cascading failures under different operating modes;

[0118] An extraction module configured to extract the electrical quantity characteristics of safety and stability events of cascading failures in the constructed power system cascading fault scenarios;

[0119] An analysis module configured to analyze the correlation of the extracted electrical quantity characteristics of safety and stability events using the Spearman correlation coefficient method, determine the change law of the electrical quantity characteristics of the transient evolution of safety and stability events, judge the evolution direction of cascading failures, and complete the feature analysis of the transient evolution of power system cascading failures.

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

[0121] As one or more embodiments, in the obtaining module, the process of obtaining the dynamic model of cascading faults in a power system with new energy is as follows: Based on the AC-DC hybrid model and AC-DC alternating iteration to calculate the AC power flow, a conductance matrix is generated; when the obtained AC power flow result converges, the 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 ends; the generated conductance matrix is updated according to the initialized power system state variables and the initial fault, and the algebraic differential equations are solved; if the algebraic differential equations converge, the equipment operating states are updated according to the power system equipment protection logics and the system operating states, otherwise the dynamic simulation of cascading faults in the power system ends; the current time is updated. If the initial fault is cleared at the current time, the power system equipment operating states are updated, otherwise the equipment operating states are updated and it is re-determined whether the initial fault is cleared; if the current time is greater than the preset dynamic simulation termination time, the simulation of cascading faults in the power system is completed, and the dynamic simulation simulation result of cascading faults in a power system with new energy is obtained, otherwise the current time is updated and the algebraic differential equations are solved.

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

[0123] As one or more embodiments, in the extracting module, the security and stability events at least include short-circuit faults, DC commutation failures, low voltage ride-through of new energy, and disconnection of new energy from the grid.

[0124] As one or more embodiments, in the analysis module, the correlation coefficients between different electrical quantity features extracted from the security and stability events are calculated by the Spearman correlation coefficient method, and the electrical quantity features with the absolute value of the correlation coefficient greater than the correlation coefficient threshold are removed to obtain the electrical quantity features of the security and stability events; the Spearman correlation coefficient method is used to calculate the correlation between each electrical quantity in different security and stability events, and a set of correlation coefficient data between the pre-fault and post-fault events under different initial faults and operation scenarios is obtained. The causal relationship between the security and stability events is characterized by the correlation coefficient, the change law of the electrical quantity features in the transient evolution of the security and stability events 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 power system cascading fault are analyzed.

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

[0126] Embodiment 3

[0127] Embodiment 3 of the present invention provides a computer-readable storage medium.

[0128] A computer-readable storage medium, on which a program is stored, and when the program is executed by a processor, the steps in the method for analyzing the characteristics of the transient evolution of the power system cascading fault as described in Embodiment 1 of the present invention are implemented.

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

[0130] Embodiment 4

[0131] Embodiment 4 of the present invention provides an electronic device.

[0132] An electronic device includes a memory, a processor, and a program stored on the memory and running on the processor. When the processor executes the program, the steps in the method for analyzing the characteristics of the transient evolution of the power system cascading fault as described in Embodiment 1 of the present invention are implemented.

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

[0134] Embodiment 5

[0135] Embodiment 5 of the present invention provides a computer program product.

[0136] A computer program product includes software code, and the program in the software code executes the steps in the method for analyzing the characteristics of the transient evolution of the power system cascading fault as described in Embodiment 1 of the present invention.

[0137] The detailed steps are the same as those of a method for analyzing the characteristics of the transient evolution of cascading faults in a power system provided in the first embodiment, and will not be elaborated here.

[0138] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention 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-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of the present invention can be implemented in various computer languages. For example, object-oriented programming languages such as Java and interpreted scripting languages such as JavaScript.

[0139] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to the embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram can be implemented by computer program instructions, and the combination of the flows and / or blocks in the flowchart and / or block diagram can also be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the specified functions in one Figure 1 one process or multiple processes and / or blocks Figure 1 or multiple blocks.

[0140] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including instruction means, and the instruction means implements the specified functions in one Figure 1 one process or multiple processes and / or blocks Figure 1 or multiple blocks.

[0141] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for implementing the specified functions in one Figure 1 one process or multiple processes and / or blocks Figure 1 or multiple blocks.

[0142] Although the preferred embodiments of the present invention have been described, additional changes and modifications can be made to these embodiments by those skilled in the art once they learn the basic creative concept. Therefore, the appended claims are intended to be construed to include the preferred embodiments as well as all changes and modifications falling within the scope of the present invention.

[0143] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention is also intended to include these modifications and variations.

[0144] The above description is only the preferred embodiment of this example and is not used to limit this example. For those skilled in the art, this example can have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of this example shall be included within the protection scope of this example.

Claims

1. A method for analyzing the transient evolution of power system cascading faults, characterized in that: include: Obtain a dynamic model of cascading failures in power systems with renewable energy sources; Based on the obtained cascading failure dynamic model, the transient evolution process of power system cascading failures under different operation modes is considered to construct the power system cascading failure scenario; Extract the electrical quantity characteristics of the safety and stability events of the cascading failures in the constructed power system cascading failure scenario; The Spearman correlation coefficient method is used to analyze the correlation of the extracted electrical quantity characteristics of safety and stability events, determine the changing law of the electrical quantity characteristics of the transient evolution of safety and stability events, judge the evolution direction of cascading failures, and complete the characteristic analysis of the transient evolution of cascading failures in the power system.

2. A method for analyzing the transient evolution of power system cascading failures as claimed in claim 1, characterized in that: The obtained dynamic model of chain failure of the power system containing new energy sources includes at least the generator / converter model, electrical control model and high and low voltage ride-through protection logic of wind power and photovoltaic; 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 adopt a constant voltage control mode.

3. A method for analyzing the transient evolution of power system cascading failures as claimed in claim 1, characterized in that: The acquisition process of the dynamic model of the cascading failure of the power system containing new energy is as follows: based on the AC / DC hybrid model and the AC / DC alternating iteration, the AC power flow is calculated to generate an admittance matrix; when the obtained AC power flow result converges, the 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 terminated; according to the initialized power system state variables and the admittance matrix generated by the initial fault update, the algebraic differential equation group is solved; if the algebraic differential equation group converges, the equipment operation status is updated according to the power system equipment protection logic and the system operation status, otherwise the dynamic simulation of the cascading failure of the power system is terminated; Update the current time. If the initial fault is cleared at the current time, update the operating status of the power system equipment. Otherwise, update the equipment operating status and re-judge whether the initial fault is cleared. If the current time is greater than the preset dynamic simulation end time, complete the power system cascading fault simulation and obtain the dynamic simulation results of the power system cascading fault containing new energy. Otherwise, update the current time and solve the algebraic differential equations.

4. A method for analyzing the transient evolution of power system cascading failures as claimed in claim 1, characterized in that: The constructed power system cascading failure scenarios include at least cascading failure scenarios of different power grid topologies including line failures, cascading failure scenarios under different renewable energy output conditions, and cascading failure scenarios under different load conditions.

5. A method for analyzing the transient evolution of power system cascading failures as claimed in claim 1, characterized in that: The safety and stability events include at least short circuit fault, DC commutation failure, new energy low voltage ride-through and new energy grid disconnection.

6. A method for analyzing the transient evolution of power system cascading failures as claimed in claim 1, characterized in that: The Spearman correlation coefficient method is used to calculate the correlation coefficients between different electrical quantity characteristics extracted from safety and stability events, and the electrical quantity characteristics with absolute values ​​of correlation coefficients greater than the correlation coefficient threshold are eliminated to obtain the electrical quantity characteristics of safety and stability events. The Spearman correlation coefficient method is used to calculate the correlation between various electrical quantities in different safety and stability events, and the correlation coefficient data set between the previous and next fault events under different initial faults and operation scenarios is obtained. The causal relationship between safety and stability events is characterized by the correlation coefficient, and the change law of the electrical quantity characteristics of the transient evolution of safety and stability events is determined. The interactive influence of the initial fault equipment and the chain fault equipment is obtained, the evolution direction of the chain fault is determined, and the transient evolution characteristics of the chain fault of the power system are analyzed.

7. A characteristic analysis system for transient evolution of cascading faults in power systems, characterized in that: include: An acquisition module configured to acquire a dynamic model of cascading failures of a power system including new energy sources; A construction module configured to construct a power system cascading failure scenario based on the acquired cascading failure dynamic model and considering the transient evolution process of the power system cascading failure under different operation modes; An extraction module configured to extract electrical quantity characteristics of safety and stability events of cascading failures in the constructed power system cascading failure scenario; The analysis module is configured to use the Spearman correlation coefficient method to analyze the correlation of the extracted electrical quantity characteristics of the safety and stability events, determine the changing law of the electrical quantity characteristics of the transient evolution of the safety and stability events, judge the evolution direction of the cascading failures, and complete the characteristic analysis of the transient evolution of the cascading failures of the power system.

8. A characteristic analysis system for transient evolution of power system cascading failures as claimed in claim 7, characterized in that: In the acquisition module, the acquired dynamic model of chain failure of the power system containing new energy sources includes at least the generator / converter model, electrical control model and high and low voltage ride-through protection logic of wind power and photovoltaics; 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 adopt a constant voltage control mode.

9. A characteristic analysis system for transient evolution of power system cascading failures as claimed in claim 7, characterized in that: In the acquisition module, the acquisition process of the dynamic model of the power system cascading failure containing new energy is as follows: based on the AC / DC hybrid model and the AC / DC alternating iteration, the AC power flow is calculated to generate an admittance matrix; when the obtained AC power flow result converges, the 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 terminated; according to the initialized power system state variables and the admittance matrix generated by the initial fault update, the algebraic differential equation group is solved; if the algebraic differential equation group converges, the equipment operation status is updated according to the power system equipment protection logic and the system operation status, otherwise the dynamic simulation of the power system cascading failure is terminated; Update the current time. If the initial fault is cleared at the current time, update the operating status of the power system equipment. Otherwise, update the equipment operating status and re-judge whether the initial fault is cleared. If the current time is greater than the preset dynamic simulation end time, complete the power system cascading fault simulation and obtain the dynamic simulation results of the power system cascading fault containing new energy. Otherwise, update the current time and solve the algebraic differential equations.

10. A characteristic analysis system for transient evolution of power system cascading failures as claimed in claim 7, characterized in that: In the construction module, the constructed power system cascading failure scenarios include at least cascading failure scenarios of different power grid topologies including line failures, cascading failure scenarios under different renewable energy output conditions, and cascading failure scenarios under different load conditions.

11. A characteristic analysis system for transient evolution of power system cascading failures as claimed in claim 7, characterized in that: In the extraction module, the safety and stability events include at least short circuit fault, DC commutation failure, new energy low voltage ride-through and new energy grid disconnection.

12. A characteristic analysis system for transient evolution of power system cascading failures as claimed in claim 7, characterized in that: In the analysis module, the Spearman correlation coefficient method is used to calculate the correlation coefficients between different electrical quantity characteristics extracted from the safety and stability events, and the electrical quantity characteristics whose absolute values ​​of the correlation coefficients are greater than the correlation coefficient threshold are eliminated to obtain the electrical quantity characteristics of the safety and stability events; the Spearman correlation coefficient method is used to calculate the correlation between the various electrical quantities in different safety and stability events, and a data set of correlation coefficients between the previous and next fault events under different initial faults and operation scenarios is obtained. The causal relationship between the safety and stability events is characterized by the correlation coefficient, and the change law of the electrical quantity characteristics of the transient evolution of the safety and stability events is determined, the interactive influence of the initial fault equipment and the chain fault equipment is obtained, the evolution direction of the chain fault is judged, and the transient evolution characteristics of the chain fault of the power system are analyzed.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of a characteristic analysis method for transient evolution of cascading faults in a power system as described in any one of claims 1-6 are implemented.

14. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the program, the steps of a method for characteristic analysis of transient evolution of cascading faults in a power system as described in any one of claims 1-6 are implemented.

15. A computer program product comprising software code, characterized in that The program in the software code executes the steps of a method for characteristic analysis of transient evolution of cascading faults in a power system as described in any one of claims 1-6.

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