Power system transient instability identification method, system and medium based on energy function

Abstract

The present invention discloses a method, system and medium for identifying transient instability of a power system based on an energy function, and relates to the field of transient analysis of a power system. The method includes: determining an energy equivalent model of a generator, a transmission network and a load contained in a power system based on Kirchhoff's current law; obtaining the fault time of a fault in the power system; determining the energy accumulated by the generator, the transmission network and the load at the fault time according to the energy equivalent model of the generator, the transmission network and the load; determining the weight value corresponding to the energy accumulated by the generator, the transmission network and the load by using a hierarchical analysis method; calculating an identification factor of transient instability of the power system according to the energy accumulated by the generator, the transmission network and the load and the weight value corresponding to the accumulated energy; determining the dominant mode of transient instability of the power system according to the identification factor. When transient coupled instability occurs in the power system, the identification factor provided by the present invention can better identify the transient dominant instability mode.

Description

Technical Field

[0001] The present invention relates to the field of power system transient analysis, and more specifically, to a method, system and medium for identifying transient instability of a power system based on an energy function. Background Art

[0002] The transient stability problems of power systems mainly include power angle stability, voltage stability, frequency stability, etc. Among them, frequency instability is relatively easy to directly judge. The judgment of power angle instability and voltage instability usually relies on identification indicators. In actual engineering applications, a relatively complete engineering experience judgment has been formed, but this type of judgment can only identify a single instability mode. When the power angle instability phenomenon is intertwined with the voltage instability phenomenon, other methods are needed to judge the dominant instability mode of the system.

[0003] At present, there are many methods for identifying the dominant modes of transient power angle instability and transient voltage instability. Among them, the energy function method is a direct method. It does not need to solve a set of nonlinear equations. The analysis process can take into account the nonlinear components of the system and has a fast calculation speed. The classical theory of the energy function method is based on the principle of dynamics. By solving the differential algebraic equations of the power system, the operating equilibrium point of the system can be obtained. The stable equilibrium point of the power system is located at the lowest point of the potential energy well. When the power system is unstable, the potential energy well escapes from the unstable equilibrium point. Using the energy function method, the overall transient stability of the power system can be well evaluated.

[0004] In practical applications, the structure-preserving modulus energy function method is used in most cases. This method retains the structural model of each part of the power system and uses the response information of the power system to calculate the transient energy. However, the existing technologies are all aimed at traditional power systems and do not consider the impact of the addition of new energy and dynamic loads in the current power system on transient stability and energy function values, resulting in errors in the existing technology in judging transient instability of the power system. Summary of the invention

[0005] In order to solve the deficiencies of the above-mentioned prior art, the present invention provides a method, system and medium for identifying transient instability of an electric power system based on an energy function. The present invention utilizes energy equivalence models of the generator, transmission network and load of the electric power system to determine the energy accumulated by the generator part, the transmission network part and the load part during the fault period, evaluates the influence of the generator part, the transmission network part and the load part on the transient instability mode of the electric power system, calculates the weight value of the energy accumulated by the three parts using a judgment matrix established by a hierarchical analysis method, calculates the identification factor of transient instability of the electric power system based on the weight value and the energy, and when transient coupled instability occurs in the electric power system, the identification factor can be used to better identify the transient dominant instability mode to assist in making decisions on more effective control measures for the electric power system.

[0006] The above technical objectives of the present invention are achieved through the following technical solutions:

[0007] In a first aspect of the present application, a method for identifying transient instability of a power system based on an energy function is provided, the method comprising:

[0008] Determine the energy equivalent model of the generator, transmission network and load included in the power system based on Kirchhoff's current law;

[0009] Obtain the fault time when the power system fails;

[0010] Determine the energy accumulated by the generator, transmission network and load during the fault time according to the energy equivalent model of the generator, transmission network and load;

[0011] The weight values ​​corresponding to the energy accumulated by the generator, transmission network and load are determined by using the analytic hierarchy process;

[0012] According to the energy accumulated by the generator, the transmission network and the load and the weight value corresponding to the accumulated energy, the identification factor of the transient instability of the power system is calculated;

[0013] The dominant mode of transient instability of the power system is determined based on the identification factors, where the transient instability is power angle instability or voltage instability.

[0014] In one implementation, the fault time includes the total time that the fault occurs at a bus node or a branch of the power system.

[0015] In one implementation scheme, the energy accumulated by the generator, the transmission network and the load during the fault time is determined based on the energy equivalent models of the generator, the transmission network and the load. Specifically, the energy equivalent models of the generator, the transmission network and the load are integrated during the fault time to obtain the energy accumulated by the generator, the transmission network and the load during the fault time.

[0016] In one implementation, the calculation of the recognition factor is specifically as follows:

[0017] The energy accumulated by the generator, the transmission network and the load during the fault time is summed with the product of the weight values ​​corresponding to the energy accumulated by the generator, the transmission network and the load, respectively, to obtain a first summation result;

[0018] The energy accumulated by the generator, the transmission network and the load during the fault time is summed to obtain a second summation result;

[0019] The ratio of the first summation result to the second summation result is used as an identification factor of the transient instability mode of the power system.

[0020] In one implementation scheme, the dominant mode of transient instability of the power system is determined based on the identification factor, specifically: when the identification factor is greater than or equal to a preset identification threshold, the dominant mode of transient instability of the power system is determined to be voltage instability; or, when the identification factor is less than the preset identification threshold, the dominant mode of transient instability of the power system is determined to be power angle instability.

[0021] In a second aspect of the present application, a power system transient instability identification system based on energy function is provided, the system comprising:

[0022] An energy equivalent model determination module is used to determine energy equivalent models of generators, transmission networks and loads included in the power system based on Kirchhoff's current law;

[0023] A time acquisition module is used to obtain the fault time when a fault occurs in the power system;

[0024] An energy calculation module, used to determine the energy accumulated by the generator, the transmission network and the load during the fault time according to the energy equivalent model of the generator, the transmission network and the load;

[0025] A weight determination module is used to determine the weight values ​​corresponding to the energy accumulated by the generator, the transmission network and the load using the hierarchical analysis method;

[0026] An identification factor calculation module is used to calculate the identification factor of transient instability of the power system according to the energy accumulated by the generator, the transmission network and the load and the weight value corresponding to the accumulated energy;

[0027] The identification module is used to determine the dominant mode of transient instability of the power system according to the identification factor, wherein the transient instability is power angle instability or voltage instability.

[0028] In one implementation, the time acquisition module is specifically used to acquire the total time that a fault occurs at a bus node or a branch of the power system.

[0029] In one implementation, the energy calculation module is specifically used to integrate the energy equivalent models of the generator, the transmission network and the load during the fault time to obtain the energy accumulated by the generator, the transmission network and the load during the fault time.

[0030] In one implementation, the identification factor calculation module includes:

[0031] A first calculation module is used to sum the energy accumulated by the generator, the transmission network and the load during the fault time and the product of the weight values ​​corresponding to the energy accumulated by the generator, the transmission network and the load, respectively, to obtain a first summation result;

[0032] A second calculation module is used to sum the energy accumulated by the generator, the transmission network and the load during the fault time to obtain a second summation result;

[0033] The third calculation module is used to use the ratio of the first summation result to the second summation result as an identification factor of the transient instability mode of the power system.

[0034] In one implementation scheme, the identification module is specifically used to: when the identification factor is greater than or equal to a preset identification threshold, determine that the dominant mode of transient instability of the power system is voltage instability; or when the identification factor is less than the preset identification threshold, determine that the dominant mode of transient instability of the power system is power angle instability.

[0035] The third aspect of the present application further provides a computer-readable storage medium, on which a computer program is stored, wherein when the computer program is executed by a processor, the steps of the method for identifying transient instability of a power system based on an energy function as described in any one of the first aspect of the present application are implemented.

[0036] Compared with the prior art, the present invention has the following beneficial effects:

[0037] The present invention provides a method for identifying transient instability of an electric power system based on an energy function. The method uses energy equivalent models of generators, transmission networks and loads of an electric power system to determine the energy accumulated by a generator part, a transmission network part and a load part during a fault period, evaluates the influence of the generator part, the transmission network part and the load part on the transient instability mode of the electric power system, calculates the weight values ​​of the energy accumulated by the three parts using a judgment matrix established by a hierarchical analysis method, calculates an identification factor of transient instability of the electric power system based on the weight value and the energy, and when transient coupled instability occurs in the electric power system, the identification factor can be used to better identify the transient dominant instability mode, so as to assist in making decisions on more effective control measures for the electric power system.

[0038] In addition, the second and third aspects of the present application also provide an energy function-based power system transient instability identification system and medium, which have the same beneficial effects as the above-mentioned energy function-based power system transient instability identification method, so they are not repeated here. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] The drawings described herein are used to provide a further understanding of the embodiments of the present invention, constitute a part of this application, and do not constitute a limitation of the embodiments of the present invention. In the drawings:

[0040] Figure 1 A schematic diagram of a flow chart of a method for identifying transient instability of a power system based on an energy function provided in an embodiment of the present application is shown;

[0041] Figure 2A flowchart of the hierarchical analysis method provided by an embodiment of the present application is shown;

[0042] Figure 3 A structural diagram of a power simulation system provided in an embodiment of the present application is shown;

[0043] Figure 4 An energy curve diagram of each part of the synchronous machine system provided by an embodiment of the present application is shown;

[0044] Figure 5 It shows a 0.40 second simulation curve diagram of a receiving end fault under the same-inductive working condition provided by an embodiment of the present application;

[0045] Figure 6 A 0.25 second simulation curve diagram of a sending end fault under the same operating condition provided by an embodiment of the present application is shown;

[0046] Figure 7 A factor importance hierarchy diagram provided by an embodiment of the present application is shown;

[0047] Figure 8 An energy curve diagram of each part of the doubly-fed wind turbine system provided in an embodiment of the present application is shown;

[0048] Fig. 9 A 0.30 second simulation curve diagram of a receiving end failure in a wind-sensing working condition provided in an embodiment of the present application is shown;

[0049] Fig.10 A 0.23 second simulation curve diagram of a sending end fault under wind-sensing working conditions provided in an embodiment of the present application is shown; DETAILED DESCRIPTION

[0050] In order to make the purpose, technical scheme and advantages of the present invention clearer, the present invention is further described in detail below in conjunction with the embodiments and drawings. The schematic implementation mode of the present invention and its description are only used to explain the present invention and are not intended to limit the present invention. It should be understood that the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features.

[0051] Traditional resources such as thermal power, hydropower, and nuclear power can no longer meet the requirements of the times, so the development of renewable energy, mainly wind power and solar power generation, has been vigorously promoted, among which doubly fed wind turbines are widely used. However, due to the transient characteristics of doubly fed wind turbines that are different from synchronous generators, they may affect the transient stability of traditional synchronous machines in the system. At the same time, in modern power systems, induction motor loads are also the most important dynamic load. In the simulation of large-scale power system accidents, it is found that in addition to considering static loads, the characteristics of electrical equipment such as induction motors must also be considered. At this time, the simulation results are consistent with the fault records, indicating that the impact of induction motor loads on the transient stability of power systems cannot be ignored. It is of great significance to study the mechanism of transient stability problems caused by induction motors.

[0052] In practical applications, the structure-preserving modulus energy function method is used in most cases. This method retains the structural model of each part of the power system and uses the response information of the power system to calculate the transient energy. However, the existing technologies are all aimed at traditional power systems and do not consider the impact of the addition of new energy and dynamic loads in the current power system on transient stability and energy function values, resulting in errors in the existing technology in judging transient instability of the power system.

[0053] Therefore, this embodiment provides a method for identifying transient instability of a power system based on an energy function, which takes into account the impact of the addition of new energy and dynamic loads in the current power system on transient stability and the value of the energy function, and proposes an identification factor for the dominant mode of transient instability with good compatibility. When transient coupled instability occurs in the power system (i.e., it contains both voltage instability and power angle instability), the dominant mode of transient instability can be better identified by using the identification factor to assist in deciding more effective power system control measures.

[0054] It should be noted that the method provided in this embodiment is applied to a power system including a doubly-fed wind turbine and an induction motor, so as to determine the dominant mode of transient instability of the power system currently connected to new energy sources and dynamic loads.

[0055] The method provided in this embodiment will be described in detail below with reference to the accompanying drawings. Figure 1 , Figure 1 The flowchart of the method for identifying transient instability of a power system based on an energy function provided in an embodiment of the present application is shown as follows: Figure 1 As shown, the method includes:

[0056] S110, based on Kirchhoff's current law, determine the energy equivalent model of the generator, transmission network and load included in the power system. According to Kirchhoff's current law, for a system with n nodes, m generators and p loads, its bus current equation can be expressed as: Where Y Bis the n-order node admittance matrix, V B is the n-dimensional node voltage column vector, and the current is based on outflow as the reference direction. gen Refers to the current vector of the generator bus, I load Refers to the current vector of the load bus, I net Refers to the current vector of all buses in the system.

[0057] For equation (1), the voltage vector complex line integral is performed on the current along the system trajectory and the imaginary part is taken. Ignoring the loss in the system, the expression of the energy function E of the system can be obtained: E = ∫Im[-∑I gen +∑I load +∑Y B V B * ] T dV jθ (2), where V is the voltage amplitude of each bus, θ is the bus voltage phase angle, and j is the imaginary unit.

[0058] Total energy of the generator part E gen Energy equivalent model (ignoring the damping loss of the generator):

[0059] Where P Gi , Q Gi are the active power and reactive power output from the port of the i-th generator, is the conjugate of the output current vector of the i-th generator port, V i is the voltage vector of the i-th bus where the generator is located, (V0,θ0) is the voltage parameter of the system under stable operation, and (V,θ) is the voltage parameter of the system at a certain moment in the transient state after the fault occurs.

[0060] Total energy of load part E load Energy equivalent model:

[0061] Where P Li , Q Li are the active power and reactive power of the i-th load port respectively, is the conjugate of the output current vector of the i-th load port, V i is the voltage vector of the i-th bus where the load is located.

[0062] Total energy E of the transmission network net Energy equivalent model:

[0063] In the formula Corresponding to the conjugate of the admittance parameter between busbars i and j.

[0064] If the energy of a certain part is positive, it means that this part of the transient process injects unbalanced energy into the system, aggravating the instability phenomenon.

[0065] S120, obtaining the fault time when the power system fails.

[0066] It should be noted that the failure time refers to the total time when failures occur in the power system in a historical period of time.

[0067] S130, determining the energy accumulated by the generator, the transmission network and the load during the fault time according to the energy equivalent model of the generator, the transmission network and the load.

[0068] In this embodiment, the method is implemented based on the PSASP simulation software. However, since the output parameters in the PSASP are time-varying values, the energy calculations in equations (3) to (5) are the integration of the power system trajectory. Therefore, if the energy calculation is performed based on the output parameters of the PSASP, the energy value obtained is the energy value of the system at each moment, that is, the left side of the energy expression in equations (3) to (5) is actually written as E(t). To obtain the energy accumulated or consumed by the power system over a period of time, it is necessary to integrate the energy over a period of time.

[0069] S140, using the analytic hierarchy process to determine weight values ​​corresponding to the energy accumulated by the generator, the transmission network and the load.

[0070] Specifically, in order to evaluate the values ​​of k1, k2, and k3, where k1 is the weight of the energy accumulated by the generator, k2 is the weight of the energy accumulated by the load, and k3 is the weight of the energy accumulated by the transmission network, this embodiment introduces the Analytic Hierarchy Process (AHP). AHP is a structured decision-making method.

[0071] Using the AHP process Figure 2 After constructing the hierarchical evaluation model, it is necessary to establish a judgment matrix. The process of establishing the judgment matrix is ​​to compare the elements in it two by two, and use the 1-9 scale method proposed by Saaty to judge the importance of the two elements, as shown in Table 1. If the scale is 1, it means that the importance of the two elements is the same. If the scale is greater than 1, it means that the latter is more important than the former, and the larger the scale, the greater the importance; on the contrary, if the scale is less than 1, it means that the former is more important than the latter.

[0072] Table 1 Relative importance scale

[0073]

[0074]

[0075] Hierarchical single sorting will determine the weight of each factor. After hierarchical single sorting, the consistency index CI (Consistency Index) is used to test whether the judgment matrix meets the consistency: In the formula, λ max is the maximum eigenvalue of the judgment matrix, and n is the matrix dimension (number of factors). CI = 0 means that the judgment matrix is ​​completely consistent. The larger the CI, the more serious the inconsistency of the judgment matrix. Then use the ratio of CI and the average random consistency index RI to calculate CR for consistency test:

[0076] Among them, RI is a fixed matrix [0, 0, 0.58, 0.89, 1.12, 1.26, 1.36, 1.41, 1.46, 1.49], and the specific value is obtained by looking up the table according to the judgment matrix dimension.

[0077] S150, calculating an identification factor of transient instability of the power system according to the energy accumulated by the generator, the transmission network and the load and the weight value corresponding to the accumulated energy.

[0078] In this embodiment, the calculation of the identification factor is specifically as follows: summing the energy accumulated by the generator, the transmission network and the load during the fault time and the product of the weight values ​​corresponding to the energy accumulated by the generator, the transmission network and the load to obtain a first summation result; summing the energy accumulated by the generator, the transmission network and the load during the fault time to obtain a second summation result; and using the ratio of the first summation result to the second summation result as the identification factor of the transient instability mode of the power system. The identification factor is a display expression of the influence of each part of the energy on the instability mode under different dominant instability modes.

[0079] The calculation formula of the recognition factor determined according to the first summation result and the second summation result is:

[0080] Where k1G+k2L+k3N represents the first summation result, G+L+N represents the second summation result, which represents the total energy accumulated in the power system during the fault period, which is equivalent to normalizing the first summation result. DI represents the identification factor, and the energy accumulated by the generator, load, and transmission network during the fault period is recorded as G, L, and N, respectively.

[0081] As can be understood by those skilled in the art, k1, k2, and k3 satisfy the following relationship: k1+k2+k3=1.

[0082] After analyzing the weights of k1, k2, and k3 by AHP according to the above embodiment, the energy value and the weight value are substituted into the above formula (9). The discrimination range of the identification factor DI proposed in the present invention may change with the experimental system, and the analysis results of the range are based on the above process.

[0083] The dominant mode of transient instability of the power system is determined based on the identification factors, where the transient instability is power angle instability or voltage instability.

[0084] In this embodiment, since the calculated recognition factor is a specific value, a recognition threshold is determined by experiment.

[0085] In the system, the constant impedance load is replaced by the induction motor load to simulate the situation where the power angle instability and voltage instability occur simultaneously, and multiple sets of simulation experiments are carried out. In the experiment, by setting different generator types, load types and fault locations, and calculating multiple sets of energy change curves, the energy change trends corresponding to different simulation results are analyzed, and the relationship between the dominant mode of transient instability and energy is summarized.

[0086] The relationship between the energy changes of each part of the system and the dominant mode of transient instability is weighed and considered, the specific values ​​of the AHP judgment matrix are evaluated, and the weights k1, k2, and k3 in the identification factors are calculated.

[0087] Based on the experimental and analytical results, the values ​​of the identification factors under different instability modes are calculated, the values ​​of the identification factors are classified into two cases: power angle instability-dominated and voltage instability-dominated, and the general identification thresholds are summarized.

[0088] The dominant mode of transient instability of the power system is determined based on the relationship between the identification factor and the identification threshold.

[0089] The identification factor and identification threshold proposed in this embodiment have been verified to be effective in a power system where a doubly-fed wind turbine replaces part of the synchronous generator output.

[0090] It can be seen that the identification method provided in this embodiment uses the energy equivalence model of the generator, transmission network and load of the power system to determine the energy accumulated by the generator part, the transmission network part and the load part during the fault period, evaluates the influence of the generator part, the transmission network part and the load part on the transient instability mode of the power system, and calculates the weight value of the energy accumulated by the three parts using the judgment matrix established by the hierarchical analysis method. The identification factor of the transient instability of the power system is calculated based on the weight value and the energy. When the power system suffers from transient coupled instability, the identification factor can be used to better identify the transient dominant instability mode, so as to assist in making decisions on more effective power system control measures.

[0091] In one embodiment, the fault time includes the total time that the fault occurs at a bus node or a branch of the power system.

[0092] Specifically, when a fault occurs at a bus node or a branch, the capacity equivalence model of the three parts of the power system described in step S110 can be used to observe the energy change of the power system and analyze the system stability.

[0093] In one implementation scheme, the energy accumulated by the generator, the transmission network and the load during the fault time is determined based on the energy equivalent models of the generator, the transmission network and the load. Specifically, the energy equivalent models of the generator, the transmission network and the load are integrated during the fault time to obtain the energy accumulated by the generator, the transmission network and the load during the fault time.

[0094] Taking the fault time as [t1, t2], integrating equations (3) to (5) provided in the above embodiment during the fault time period, we obtain equations (6) to (8) which are the energy accumulated by the generator, load, and transmission network during the fault period.

[0095] The energy accumulated by the generator, load, and transmission network during the fault period is denoted as G, L, and N, respectively, as follows:

[0096]

[0097] In one embodiment, the calculation of the identification factor is specifically as follows: summing the products of the energy accumulated by the generator, the transmission network and the load during the fault time and the weight values ​​corresponding to the energy accumulated by the generator, the transmission network and the load, respectively, to obtain a first summation result; summing the energy accumulated by the generator, the transmission network and the load during the fault time to obtain a second summation result; and using the ratio of the first summation result to the second summation result as the identification factor of the transient instability mode of the power system.

[0098] In this embodiment, the calculation of the identification factor has been described in detail in the above step S150, so it will not be repeated here.

[0099] In one embodiment, the dominant mode of transient instability of the power system is determined based on the identification factor, specifically: when the identification factor is greater than or equal to a preset identification threshold, the dominant mode of transient instability of the power system is determined to be voltage instability; or, when the identification factor is less than the preset identification threshold, the dominant mode of transient instability of the power system is determined to be power angle instability.

[0100] Here, it should be understood that, in this embodiment, based on the occurrence of coupled instability in the power system, it is determined whether voltage instability is the main mode or power angle instability is the main mode under coupled instability.

[0101] It should be noted that in the above formula (1-11), the bold ones are matrix or vector parameters, and the non-bold ones are scalar values.

[0102] This embodiment also provides a simulation of the identification method, including a power system including a synchronous machine and a power system including a double-fed wind turbine, as follows:

[0103] The system using the simulation software PSASP for the experiment is as follows Figure 3 As shown in the figure, the bus voltage parameters and steady-state power flow parameters are marked in the figure, S B = 100. In the system, Gen1 and Gen3 are always constant synchronous generator models, and Load2 is always constant impedance load model. There is a replacement of electrical equipment models at B2 and B5 buses.

[0104] The experiment is divided into 4 working conditions, named synchronous-constant, synchronous-inductive, wind-constant, and wind-inductive. The description of the working conditions is only for the power generation equipment connected to the B2 bus and the load equipment at the B5 bus. For example, the synchronous-constant condition means that the B2 bus is connected to the synchronous generator Gen2, and the Load1 at the B5 bus is a constant impedance load model; the wind-inductive condition means that the synchronous generator at the B2 bus is replaced by a DFIG with equal capacity, and the Load1 at the B5 bus replaces the induction motor load model.

[0105] The synchronous-constant and synchronous-sensing operating conditions are collectively referred to as synchronous machine systems, and the wind-constant and wind-sensing operating conditions are collectively referred to as doubly fed wind turbine systems.

[0106] The identification factors of transient modes are analyzed in synchronous machine systems and applied to doubly-fed wind turbine systems.

[0107] 1. Synchronous machine system

[0108] Table 2 records the transient conditions of two fault locations in the synchronous machine system.

[0109] Table 2 Synchronous machine system fault duration and system transient instability

[0110]

[0111]

[0112] The relationship curves between the energy of the system generator, load and network and time calculated by formula (1) to formula (3) are as follows: Figure 4 As shown, the figure magnifies the energy changes during the fault.

[0113] Depend on Figure 4 (a) It can be seen that the energy change curve under coupled instability has a similar trend to the energy change curve under single power angle or single voltage instability under the same conditions. In the case of single power angle instability, the energy has obvious high-frequency fluctuations after the fault is removed; in the case of single voltage instability, the energy fluctuates slowly after the fault is removed.

[0114] Figure 4 The positive and negative energy of (b) clearly reflects the impact of the induction motor on transient stability. When the same-inductance system is set at the B5 busbar, the load energy continues to rise after the fault occurs and is always positive, indicating that the load continuously transmits unbalanced energy to the system; when the fault is set at line B3-B4, the energy of the load part is positive for a short time, and then it is always negative, indicating that the load does not provide unbalanced energy in the system at this time. The energy change of the load part represents the instability of the load part of the system, especially the instability of the induction motor. The above phenomenon shows that when a fault occurs near the receiving end of the induction motor load, the induction motor dominates the instability.

[0115] Figure 4 The network energy in (c) is always positive. Since the fault in this paper is set in the network, the experimental results do not involve the positive and negative changes of the energy of the network part.

[0116] The coupled instability simulation curves under receiving-end fault and sending-end fault are shown as follows: Figure 5 and Figure 6 shown.

[0117] Figure 5 (a) Figure 5 (c) are the synchronous machine power angle and bus voltage curves of the system under the same-sensing end fault 0.25s, and the coupling instability phenomenon is obvious. Analysis shows that the system is in a coupled instability state dominated by voltage instability. The system power angle and voltage curves after taking the load shedding control measures of 780MW and 195Mvar at 1.26s are as follows Figure 5 (b) Figure 5 As shown in (d), the generator power angle and bus voltage tend to be stable, indicating that the control measures are effective.

[0118] Figure 6 is the same-sensing condition sending end fault simulation curve, Figure 6 (a) Figure 6 (c) are the system synchronous machine power angle and bus voltage curves for the case of a synchronous-sensing sending-end fault at 0.40s. It is judged that the system is in a coupled instability state dominated by power angle instability. The system power angle and voltage curves after taking the control measure of cutting off 855.3MW at 1.41s are shown in Figure 6 (b) Figure 6 As shown in (d), the generator power angle and bus voltage tend to be stable, indicating that the control measures are effective.

[0119] Combining the energy change curve and the system simulation curve, especially the load part energy curve, it can be judged that when a fault occurs at the receiving end close to the induction motor load, the induction motor is the dominant instability. The coupling instability when a fault occurs at the sending end of the system is actually the overall reduction of transient voltage caused by transient power angle instability, which in turn affects the transient stability of the induction motor.

[0120] The coupled instability energies of two different dominant modes are used to perform weighted evaluation on the generator energy, load energy, and network energy to obtain the values ​​of k1, k2, and k3, and then determine the discrimination value range of the discrimination index DI.

[0121] The method of weighing the importance of factors in the present invention is to set the scale according to whether the power generation part includes a fan, whether the load part includes an induction motor, and the influence of the fault location on the energy size and change trend. Since the energy of the network part is always positive in the experiment of the present invention, N is used as a reference factor to compare the importance of G and L relative to N. According to the situation of the experiment of the present invention, the hierarchical structure diagram of the three factors G, L, and N is as follows: Figure 7 shown.

[0122] Through the comparison of the accumulated energy values ​​during the fault period and after discussion with an expert, the judgment matrix for factors N, L, and G was established as shown in Table 3.

[0123] Table 3 Main factor judgment matrix

[0124] factor N L G N 1 0.3333 0.5 L 3 1 3.0003 G 2 0.3333 1

[0125] Solving for the matrix λ max =3.055, and the corresponding eigenvectors are normalized to become the normalized weights of each factor, see Table 4.

[0126] Table 4 Normalized weights of main factors

[0127] factor N L G Weight 0.1592 0.5900 0.2508

[0128] The judgment matrix is ​​tested for consistency, n = 3, and RI = 0.52 is obtained by table lookup. CI = 0.028 and CR = 0.053 are calculated by equations (10) and (11), indicating that the matrix meets the consistency requirements.

[0129] According to the weight values ​​determined in Table 4, substitute k1=0.2508, k2=0.5900, k3=0.1592 in the above formula (9). Set the fault duration to 0.1-0.9 seconds, and calculate the values ​​of the identification factor DI under 9 groups of fault time, with an interval of 0.1 seconds between groups. When the receiving end fails, DI increases with the increase of the fault duration; when the sending end fails, DI decreases with the increase of the fault duration. This change is mainly due to the large k2 and the negative load energy in the case of the sending end fault, which dominates the size of the positive DI.

[0130] In order to obtain the DI value range for judging the dominant instability mode, the average values ​​of 9 groups of DI are recorded in Table 5. The calculation results in Table 5 show that the DI when the system is dominated by voltage instability is always greater than the DI when the system is dominated by power angle instability.

[0131] Table 5 Mean range of indicators in synchronous machine system

[0132]

[0133]

[0134] Final Definition Figure 3 The value range of the identification factor DI in the system is:

[0135]

[0136] 2. Double-fed fan system

[0137] Based on the value range of the identification factor proposed in the synchronous machine system, this embodiment verifies the value range of the dominant instability mode identification factor DI in the doubly-fed wind turbine system.

[0138] The system simulation results under wind-constant and wind-sensing conditions are recorded in Table 6. Similar to the same-sensing case, the wind-sensing system also undergoes a transformation in the form of instability when the receiving end of the system fails.

[0139] Table 6 Fault duration of doubly-fed wind turbine system and system transient instability

[0140]

[0141] Similarly, the weight values ​​determined in Table 4 are substituted, and a certain fault duration is set under the wind-constant and wind-sensing conditions. The index DI is calculated using formula (9) and the dominant mode of transient instability is identified. The results are recorded in Table 7.

[0142] Table 7 Calculation results of indicators in double-fed wind turbine system

[0143]

[0144] When the receiving end of the wind-sensing system fails, DI>0.3 exists, and the dominant instability mode at this time is judged to be voltage instability.

[0145] Using equations (3) to (5), the three-part energy curve under the wind power system condition is calculated as follows: Figure 8 As shown, the overall energy curve changes with Figure 4 similar.

[0146] Fig. 9 is the fault simulation curve of the receiving end under wind-sensing condition, Fig. 9 (a) Fig. 9 (c) are the synchronous machine power angle and bus voltage curves of the system under the same-sensing end fault 0.30s, and the coupling instability phenomenon is obvious. According to the above analysis, the system is in a coupled instability state dominated by voltage instability. The system power angle and voltage curves after taking the load shedding control measures of 600MW and 150Mvar at 1.31s are as follows Fig. 9 (b) Fig. 9 (d) The generator power angle and bus voltage tend to be stable, indicating that the load shedding control measures are effective.

[0147] Fig.10 is the same-sensing condition sending end fault simulation curve, Fig.10 (a) Fig.10 (c) are the system synchronous machine power angle and bus voltage curves at 0.23s when the same-sensor sending end fails. The above analysis shows that the system is in a coupled instability state dominated by power angle instability. The system power angle and voltage curves after the control measure of cutting off 610.9MW at 1.24s are shown in Figure 2. Fig.10 (b) Fig.10 (d) The generator power angle and bus voltage tend to be stable, indicating that the generator tripping control measures are effective.

[0148] In summary, the simulation examples illustrate that the identification method provided by the embodiment of the present invention is also applicable to the system containing induction motor loads under DFIG and other capacity replacements in the value range of the identification factor DI proposed based on the synchronous machine system.

[0149] Corresponding to the method for identifying transient instability of a power system based on an energy function provided in the above embodiment, the present application, in one embodiment, also provides an identification system for transient instability of a power system based on an energy function. The explanation of the system can be found in the same part of the above method, which will not be repeated here. The identification system includes: an energy equivalent model determination module, which is used to determine the energy equivalent model of the generator, transmission network and load contained in the power system based on Kirchhoff's current law; a time acquisition module, which is used to obtain the fault time of the fault of the power system; an energy calculation module, which is used to determine the energy accumulated by the generator, transmission network and load at the fault time according to the energy equivalent model of the generator, transmission network and load; a weight determination module, which is used to determine the weight value corresponding to the energy accumulated by the generator, transmission network and load using the hierarchical analysis method; an identification factor calculation module, which is used to calculate the identification factor of transient instability of the power system according to the energy accumulated by the generator, transmission network and load and the weight value corresponding to the accumulated energy; an identification module, which is used to determine the dominant mode of transient instability of the power system according to the identification factor, wherein the transient instability is power angle instability or voltage instability.

[0150] Accordingly, the present embodiment provides an energy function-based power system transient instability identification system, which uses energy equivalence models of the power system's generators, transmission networks and loads to determine the energy accumulated by the generator part, the transmission network part and the load part during the fault period, evaluates the degree of influence of the generator part, the transmission network part and the load part on the transient instability mode of the power system, calculates the weight values ​​of the energy accumulated by the three parts using a judgment matrix established using a hierarchical analysis method, and calculates the identification factor of the power system transient instability based on the weight value and the energy. When transient coupled instability occurs in the power system, the identification factor can be used to better identify the transient dominant instability mode, so as to assist in making decisions on more effective power system control measures.

[0151] In one embodiment, the time acquisition module is specifically used to acquire the total time when the fault occurs at the bus node or branch of the power system.

[0152] In one embodiment, the energy calculation module is specifically used to integrate the energy equivalent models of the generator, the transmission network and the load during the fault time to obtain the energy accumulated by the generator, the transmission network and the load during the fault time.

[0153] In one embodiment, the identification factor calculation module includes:

[0154] A first calculation module is used to sum the energy accumulated by the generator, the transmission network and the load during the fault time and the product of the weight values ​​corresponding to the energy accumulated by the generator, the transmission network and the load, respectively, to obtain a first summation result;

[0155] A second calculation module is used to sum the energy accumulated by the generator, the transmission network and the load during the fault time to obtain a second summation result;

[0156] The third calculation module is used to use the ratio of the first summation result to the second summation result as an identification factor of the transient instability mode of the power system.

[0157] In one embodiment, the identification module is specifically used to: when the identification factor is greater than or equal to a preset identification threshold, determine that the dominant mode of transient instability of the power system is voltage instability; or when the identification factor is less than a preset identification threshold, determine that the dominant mode of transient instability of the power system is power angle instability.

[0158] The power system transient instability identification system based on the energy function in the embodiment of the present application is different from the above Figure 1 The method for identifying transient instability of a power system based on the energy function shown is an invention based on the same concept. Through the detailed description of the method for identifying transient instability of a power system based on the energy function above, those skilled in the art can clearly understand the implementation process of the system for identifying transient instability of a power system based on the energy function in this embodiment. Therefore, for the sake of brevity of the specification, it will not be repeated here.

[0159] Based on the same inventive concept as the method for identifying transient instability of a power system based on an energy function in the aforementioned embodiment, in another embodiment of the present invention, an electronic device is further provided, the electronic device comprising one or more processors; a memory coupled to the processor for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors implement the steps of the method for identifying transient instability of a power system based on an energy function in the aforementioned embodiment. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), off-the-shelf programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc., which are the computing core and control core of the terminal, which are suitable for implementing one or more instructions, and are specifically suitable for loading and executing one or more instructions in a computer storage medium to implement the corresponding method flow or corresponding function; the processor described in the embodiment of the present invention can be used to perform the operation of the method for identifying transient instability of a power system based on an energy function.

[0160] Based on the same inventive concept as the method for identifying transient instability of a power system based on an energy function in the aforementioned embodiment, in another embodiment of the present invention, the present invention further provides a computer-readable storage medium, which is a memory device in a computer device for storing programs and data. It can be understood that the computer-readable storage medium here can include both a built-in storage medium in a computer device and an extended storage medium supported by the computer device. The computer-readable storage medium provides a storage space, which stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by a processor are also stored in the storage space, and these instructions can be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the corresponding steps of the method for identifying transient instability of a power system based on an energy function in the above embodiment. 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 complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. 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 codes.

[0161] The specific implementation methods described above further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above description is only a specific implementation method of the present invention and is not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for identifying transient instability of power systems based on energy function, characterized in that: Methods include: Determine the energy equivalent model of the generator, transmission network and load included in the power system based on Kirchhoff's current law; Obtain the fault time when the power system fails; Determine the energy accumulated by the generator, transmission network and load during the fault time according to the energy equivalent model of the generator, transmission network and load; The weight values ​​corresponding to the energy accumulated by the generator, transmission network and load are determined by using the analytic hierarchy process; According to the energy accumulated by the generator, the transmission network and the load and the weight value corresponding to the accumulated energy, the identification factor of the transient instability of the power system is calculated; wherein the calculation of the identification factor is specifically as follows: summing the products of the energy accumulated by the generator, the transmission network and the load during the fault time and the weight values ​​corresponding to the energy accumulated by the generator, the transmission network and the load, respectively, to obtain a first summation result; summing the energy accumulated by the generator, the transmission network and the load during the fault time to obtain a second summation result; and taking the ratio of the first summation result to the second summation result as the identification factor of the transient instability mode of the power system; Determine the dominant mode of transient instability of the power system according to the identification factor, wherein the transient instability is power angle instability or voltage instability; determine the dominant mode of transient instability of the power system, specifically: when the identification factor is greater than or equal to a preset identification threshold, determine that the dominant mode of transient instability of the power system is voltage instability; or, when the identification factor is less than a preset identification threshold, determine that the dominant mode of transient instability of the power system is power angle instability.

2. The method for identifying transient instability of a power system based on energy function according to claim 1, characterized in that: Fault time includes the total time that the fault occurs at the bus node or branch of the power system.

3. The method for identifying transient instability of a power system based on energy function according to claim 1, characterized in that: The energy accumulated by the generator, transmission network and load during the fault time is determined according to the energy equivalent model of the generator, transmission network and load. Specifically, the energy equivalent model of the generator, transmission network and load is integrated during the fault time to obtain the energy accumulated by the generator, transmission network and load during the fault time.

4. The power system transient instability identification system based on energy function is characterized by: The system includes: An energy equivalent model determination module is used to determine energy equivalent models of generators, transmission networks and loads included in the power system based on Kirchhoff's current law; A time acquisition module is used to obtain the fault time when a fault occurs in the power system; An energy calculation module, used to determine the energy accumulated by the generator, the transmission network and the load during the fault time according to the energy equivalent model of the generator, the transmission network and the load; A weight determination module is used to determine the weight values ​​corresponding to the energy accumulated by the generator, the transmission network and the load using the hierarchical analysis method; An identification factor calculation module is used to calculate the identification factor of transient instability of the power system according to the energy accumulated by the generator, the transmission network and the load and the weight value corresponding to the accumulated energy; wherein the identification factor calculation module includes: a first calculation module, which is used to sum the products of the energy accumulated by the generator, the transmission network and the load during the fault time and the weight value corresponding to the energy accumulated by the generator, the transmission network and the load, respectively, to obtain a first summation result; a second calculation module, which is used to sum the energy accumulated by the generator, the transmission network and the load during the fault time to obtain a second summation result; a third calculation module, which is used to use the ratio of the first summation result to the second summation result as the identification factor of the transient instability mode of the power system; An identification module is used to determine the dominant mode of transient instability of the power system according to an identification factor, wherein the transient instability is power angle instability or voltage instability; determine the dominant mode of transient instability of the power system, specifically: when the identification factor is greater than or equal to a preset identification threshold, determine that the dominant mode of transient instability of the power system is voltage instability; or, when the identification factor is less than a preset identification threshold, determine that the dominant mode of transient instability of the power system is power angle instability.

5. The power system transient instability identification system based on energy function according to claim 4 is characterized in that: The time acquisition module is specifically used to obtain the total time when the fault occurs at the bus node or branch of the power system.

6. The power system transient instability identification system based on energy function according to claim 4 is characterized in that: The energy calculation module is specifically used to integrate the energy equivalent models of the generator, transmission network and load during the fault time to obtain the energy accumulated by the generator, transmission network and load during the fault time.

7. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, wherein when the computer program is executed by a processor, the steps of the method for identifying transient instability of a power system based on an energy function as claimed in any one of claims 1 to 3 are implemented.

Images