Power system dominant oscillation section identification method, device and equipment and storage medium

Abstract

The application provides a power system dominant oscillation section identification method, device and equipment and a storage medium, and belongs to the technical field of power systems. The method comprises the following steps: constructing a regional equivalent model of a target power system; obtaining phasor measurement data of equivalent generators of each regional power subsystem based on the regional equivalent model; performing multi-channel singular spectrum analysis on the phasor measurement data to obtain regional inter-area oscillation mode signals of each equivalent generator; and performing dissipation energy analysis on the regional inter-area oscillation mode signals to identify a dominant oscillation section of the target power system based on the dissipation energy. The multi-channel singular spectrum analysis is used to quickly and effectively extract regional inter-area oscillation mode signals in data, has good anti-noise capability, and can retain more useful information. The dissipation energy analysis method is used to calculate the dissipation energy of the regional inter-area oscillation mode signals, and the energy can reflect the influence of time-varying factors on the oscillation behavior of the power system, so that the dominant oscillation section can be accurately identified.

Description

Technical Field

[0001] This invention relates to the field of power system technology, and in particular to a method, apparatus, equipment and storage medium for identifying the dominant oscillation section of a power system. Background Technology

[0002] In recent years, wide-area measurement methods based on synchronous phasor technology have become widespread. Deploying high-sampling-rate phasor measurement units (PMUs) at the transmission and distribution levels of the power system to record digital signals enables dynamic real-time assessment of the entire power system. Inter-regional oscillation modes can be extracted from wide-area data such as acquired frequency, phase angle, and active power; this analysis method is called measurement-based oscillation behavior analysis. Wide-area data is divided into noise-like data aggregated from the system under small disturbances and post-fault data resulting from changes in motor tripping under large disturbances. Analysis of post-fault data generally involves hysteresis analysis of the fault event. Therefore, the analysis of inter-regional oscillation modes often uses noise-like data caused by changes in system load, which enables real-time estimation of the system state. However, the measurement signals contain a lot of interference noise, which directly affects the accuracy of the analysis results.

[0003] Inertia plays a crucial role in maintaining the frequency stability of a power system. Currently, the inertia of a power system can be estimated using the eigenvalues ​​and eigenvectors extracted from the oscillation power and frequency signals measured by the power management unit (PMU). Inertia can serve as an indicator for identifying the dominant oscillation profile between power system regions. However, inertia cannot reflect the influence of time-varying factors on the system's oscillation behavior. Therefore, the identification of the dominant oscillation profile has a significant error, affecting the accuracy of its identification. Summary of the Invention

[0004] This invention provides a method, apparatus, device, and storage medium for identifying the dominant oscillation section of a power system, which solves the defect in the prior art that it cannot accurately identify the dominant oscillation section, and realizes the ability to accurately identify the dominant oscillation section between regions of the power system, thereby improving the identification accuracy of the dominant oscillation section.

[0005] This invention provides a method for identifying the dominant oscillation section of a power system, comprising:

[0006] Construct a regional equivalent model of the target power system; wherein the target power system includes multiple regional power subsystems;

[0007] Based on the regional equivalent model, obtain the phasor measurement data of the equivalent generators corresponding to each regional power subsystem;

[0008] Multichannel singular spectrum analysis is performed on the phasor measurement data to obtain the inter-regional oscillation mode signal of each equivalent generator;

[0009] Dissipated energy analysis is performed on the inter-regional oscillation mode signals, and the dominant oscillation section of the target power system is identified based on the dissipated energy of the inter-regional oscillation mode signals.

[0010] According to the present invention, a method for identifying the dominant oscillation profile of a power system includes performing multi-channel singular spectrum analysis on the phasor measurement data to obtain the inter-regional oscillation mode signal of each equivalent generator, comprising:

[0011] Based on the phasor measurement data, multiple common oscillation mode signals are obtained by decomposition.

[0012] Extract all inter-regional common oscillation mode signals from multiple common oscillation mode signals;

[0013] The inter-regional oscillation mode signal of each equivalent generator is obtained by reconstructing the inter-regional common oscillation mode signal with the original phasor measurement signal of each equivalent generator.

[0014] According to a method for identifying the dominant oscillation profile of a power system provided by the present invention, the step of performing dissipative energy analysis on the inter-regional oscillation mode signals and identifying the dominant oscillation profile of the target power system based on the dissipative energy of the inter-regional oscillation mode signals includes:

[0015] The dissipated energy function is used to calculate and process the inter-regional oscillation mode signal to obtain the dissipated energy of each equivalent generator;

[0016] The state of each equivalent generator is determined based on the dissipated energy.

[0017] Based on the aforementioned state, the location of the dominant oscillation section in the target power system is identified.

[0018] According to the method for identifying the dominant oscillation section of a power system provided by the present invention, the expression for the dissipated energy function is as follows:

[0019]

[0020] Among them, F DE This represents the dissipated energy of the equivalent large motor. V is the total reactance of the transmission path between region i and region j. i Let V be the voltage in region i. j Let θ be the voltage in region j. ij Let θ be the voltage phase angle of the transmission path between region i and region j. i Let θ be the voltage phase angle of region i. j Let be the voltage phase angle of region j.

[0021] The method for identifying the dominant oscillation section of a power system according to the present invention further includes:

[0022] When it is identified that there is more than one dominant oscillation section in the target power system based on the state, the energy of the common oscillation mode signal between each region is obtained.

[0023] Based on the energy of the common oscillation mode signal between each region, the dominant common oscillation mode between regions is determined;

[0024] Obtain the mode shape of each of the equivalent generators under the common oscillation mode in the dominant regions;

[0025] The location of the dominant oscillation section in the target power system is finally determined by combining the location and the mode shape.

[0026] According to the method for identifying the dominant oscillation section of a power system provided by the present invention, the energy of the common oscillation mode signal between each region is calculated by the following formula:

[0027]

[0028] Among them, E k,∞ The energy of the common oscillation mode signal between the regions, representing a time series of length T. This represents the common oscillating mode signal of the nth eigenvector in the region of channel l.

[0029] According to the method for identifying the dominant oscillation section of a power system provided by the present invention, the construction of a regional equivalent model of the target power system includes:

[0030] An initial equivalent model is constructed based on the target power system; wherein, the initial equivalent model includes equivalent generators of the regional power subsystem, the equivalent generators with connection relationships are connected through a bus, and each of the equivalent generators is equipped with a phasor measurement unit;

[0031] Based on the phasor measurement data collected by the phasor measurement unit, model parameters are obtained; wherein, the model parameters include the reactance between the buses, the internal reactance of the equivalent generator, the equivalent inertia, and the damping factor;

[0032] Based on the initial equivalent model and the model parameters, the regional equivalent model is constructed.

[0033] The present invention also provides a device for identifying inter-regional oscillation modes in a power system, comprising:

[0034] A construction module is used to construct a regional equivalent model of the target power system; wherein the target power system includes multiple regional power subsystems;

[0035] The first acquisition module is used to acquire phasor measurement data of the equivalent generators corresponding to each regional power subsystem based on the regional equivalent model;

[0036] The second acquisition module is used to perform multi-channel singular spectrum analysis on the phasor measurement data to acquire the inter-regional oscillation mode signal of each equivalent generator;

[0037] The identification module is used to perform dissipated energy analysis on the inter-regional oscillation mode signal and identify the dominant oscillation section of the target power system based on the dissipated energy of the inter-regional oscillation mode signal.

[0038] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the power system dominant oscillation section identification method as described above.

[0039] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the power system dominant oscillation section identification method as described above.

[0040] The present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the power system dominant oscillation section identification method as described above.

[0041] The present invention provides a method, apparatus, device, and storage medium for identifying the dominant oscillation section of a power system. By constructing a regional equivalent model of the target power system, each regional power subsystem in the target power system is equivalently represented as an equivalent generator. Phasor measurement data of the equivalent generators are obtained. Multi-channel singular spectrum analysis is used to quickly and effectively extract inter-regional oscillation mode signals from the phasor measurement data. The extracted inter-regional oscillation mode signals have good noise immunity and can retain more useful inter-regional oscillation information. Furthermore, dissipative energy analysis is used to calculate the dissipated energy of the inter-regional oscillation mode signals, thereby identifying the dominant oscillation section of the target power system from an energy perspective. Since the energy perspective can reflect the influence of time-varying factors on the oscillation behavior of the power system, the dominant oscillation section can be accurately identified, improving the identification accuracy. Attached Figure Description

[0042] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0043] Figure 1 This is a flowchart illustrating the method for identifying the dominant oscillation section of a power system provided by the present invention;

[0044] Figure 2 This is a wiring diagram of the IEEE 68-node system;

[0045] Figure 3 This is a schematic diagram of the regional equivalent model of the IEEE 68-node system;

[0046] Figure 4 These are frequency measurement data of the five equivalent generators in the regional equivalent model of the IEEE 68-bus system.

[0047] Figure 5 (a) to (i) are schematic diagrams of the common oscillation components obtained by multi-channel singular spectrum analysis of PMU data from the IEEE 68-node system.

[0048] Figure 6 (a) to (e) are schematic diagrams of the inter-regional oscillation mode signals of the five-region equivalent generator in the regional equivalent model of the IEEE 68-node system;

[0049] Figure 7 This is a schematic diagram of the energy dissipation curves of the five-region equivalent generator in the regional equivalent model of the IEEE 68-node system.

[0050] Figure 8 This is a schematic diagram of the transmission power angle curve between Region 2 and Region 3 of the IEEE 68-node system.

[0051] Figure 9 This is a schematic diagram of the energy curves of the common oscillation components RC3 to RC5 of the IEEE 68-node system.

[0052] Figure 10 This is a schematic diagram of the mode shapes of the five-region equivalent generator in the regional equivalent model of the IEEE 68-bus system.

[0053] Figure 11 This is a schematic diagram of the motor slip compass of the five-region equivalent generator in the regional equivalent model of the IEEE 68-node system.

[0054] Figure 12This is a schematic diagram of the original measurement signal waveforms before and after the addition of noise to the IEEE 68-node system;

[0055] Figure 13 This is a schematic diagram of the inter-regional oscillation mode signal waveforms before and after the addition of noise to the IEEE 68-node system.

[0056] Figure 14 This is a schematic diagram of the structure of the power system dominant oscillation section identification device provided by the present invention;

[0057] Figure 15 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0058] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0059] It should be noted that in the description of the embodiments of the present invention, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element. The terms "upper," "lower," etc., indicating orientation or positional relationships based on the orientation or positional relationships shown in the accompanying drawings, are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the present invention. Unless otherwise expressly specified and limited, the terms "installed," "connected," and "linked" should be interpreted broadly, for example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two elements. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0060] The terms "first," "second," etc., used in this invention are used to distinguish similar objects, not to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention can be implemented in orders other than those illustrated or described herein, and the objects distinguished by "first," "second," etc., are generally of the same class, without limiting the number of objects; for example, a first object can be one or more. Furthermore, "and / or" indicates at least one of the connected objects, and the character " / " generally indicates that the preceding and following objects are in an "or" relationship.

[0061] The following is combined Figures 1-15 The present invention describes a method, apparatus, electronic device, and storage medium for identifying the dominant oscillation section of a power system.

[0062] like Figure 1 As shown, the present invention provides a method for identifying the dominant oscillation section of a power system, comprising:

[0063] Step 110: Construct a regional equivalent model of the target power system; wherein the target power system includes multiple regional power subsystems.

[0064] Specifically, the target power system refers to a cross-regional power system, which includes power systems in multiple regions (i.e., regional power subsystems). These regional power subsystems are interconnected to achieve interconnected power transmission. Here, "cross-regional" can refer to inter-city or even inter-country / regional connections. Before analyzing the cross-regional power system, a reduced-order regional equivalent model is constructed. Specifically, a regional power subsystem can be represented as an equivalent generator.

[0065] In one embodiment, step 110 may specifically include the following steps:

[0066] An initial equivalent model is constructed based on the target power system; wherein, the initial equivalent model includes equivalent generators of the regional power subsystem, the equivalent generators with connection relationships are connected through a bus, and each of the equivalent generators is equipped with a phasor measurement unit;

[0067] Based on the phasor measurement data collected by the phasor measurement unit, model parameters are obtained; wherein, the model parameters include the reactance between the buses, the internal reactance of the equivalent generator, the equivalent inertia, and the damping factor;

[0068] Based on the initial equivalent model and the model parameters, the regional equivalent model is constructed.

[0069] Specifically, each regional power subsystem is equivalent to a regional equivalent generator. Based on the interconnections between regional power subsystems, the connections between regions are equivalent to a transmission bus (or equivalent tie line). That is, each region's outgoing line is connected to a transmission bus. Each equivalent generator is equipped with a phasor measurement unit (PMU), specifically, the PMU is installed on the transmission bus, and each equivalent generator has one PMU. At this point, the initial equivalent model is complete. Using the PMU data measured by the PMU, specific model parameters can be obtained. Based on the initial equivalent model and model parameters, the regional equivalent model of the target power system is then constructed.

[0070] This invention takes the IEEE 68-node system as an example, such as... Figure 2 The diagram shows the wiring diagram of the IEEE 68-node system, which includes 16 generators and 5 areas. Area 1 is the New England Test System (NETS), and Area 2 is the New York Power System (NYPS). It can be seen that NETS and NYPS contain multiple generators. When constructing the equivalent model of the areas, NETS and NYPS are aggregated into one equivalent generator each. The remaining three areas (AREA3, AREA4, and AREA5) each have only one generator, so the remaining three areas are approximated by equivalent generators. Figure 2 As shown, the connections between NETS and NYPS, NYPS and AREA 3, AREA 3 and AREA 4, AREA 4 and AREA 5, and the connections between areas are equivalent to a single transmission bus.

[0071] It should be noted that the regional equivalent generator can be viewed as a collection of all slow-coherent generators within the region. Regions within the region are strongly connected and synchronized on a fast timescale, while regions between the region are weakly connected and synchronized on a relatively slow timescale.

[0072] Therefore, the regional equivalent model of the aforementioned IEEE 68-node system is as follows: Figure 3 As shown, each area's outgoing line is connected to a transmission bus, and the PMU is installed on this transmission bus. Assuming the transmission line between buses is lossless, the reactance is expressed as jx. ij Let the inertia of the equivalent generator be H. i The voltage phase V of the bus i ∠θ i and current phase I i ∠α i These can all be directly measured from PMU data. Relatedly, the bus current phase I... i ∠α iThis is the difference between the voltage flowing into and out of the bus. The electromotive force of the equivalent generator's internal voltage source is expressed as E. i ∠δ i Thevenin reactance x inside the equivalent motor in the region i Represented as:

[0073] x i =j(x Ti +x di );

[0074] Where, x Ti x represents the equivalent transformer reactance. di This represents the open-circuit transient reactance of the generator. It should be noted that the Thevenin reactance inside the equivalent generator in the region is represented as x. i , not r i +x i The latter would render the entire system unrecognizable. Therefore, the total reactance of the transmission path between region i and region j is obtained. for:

[0075]

[0076] Where, x i Let x represent the Thevenin reactance within region i. j This represents the Thevenin reactance within region j.

[0077] Bus voltage phase V i ∠θ i and current phase I i ∠α i The reactance x between the busbars can be directly measured using a PMU. ij It can be calculated using the following formula:

[0078]

[0079] In stability analysis, the rotor angle δ inside the generator can be used to replace the voltage phase angle θ of the regional transmission bus, and the internal electromotive force E can be used to replace the voltage V of the transmission bus. Then the power transmission between regions P... e It can be represented as:

[0080]

[0081] Among them, E i E represents the electromotive force within region i. j δ represents the electromotive force within region j. i δ represents the rotor angle within region i. j This represents the rotor angle within region j.

[0082] The generator in the classical model is a salient-pole machine with a constant internal electromotive force. Let X be the sum of the generator reactance and the external reactance, and δ be the phase difference between E and V. To make the dynamic equations of the power system correspond to the power flow equations, it is desirable to use power dimensions instead of torque dimensions on the right-hand side of the generator's equations of motion. Therefore, the equations of motion and the power-rotation (P-δ) function expression of the simplest classical model of a one-machine infinite-bus (OMIB) system are as follows:

[0083]

[0084] Among them, the maximum power M / ω0 is the inertial time constant, with dimensions in s (rad / s). -1 =s 2 / rad, for ease of writing, let M replace M / ω0, then the equation of motion can be expressed as:

[0085]

[0086] Based on the OMIB system, considering the damping effect, the dynamic electromechanical model of the i-th equivalent generator is:

[0087]

[0088] Where δ=δ1-δ2,

[0089] The study found that the virtual nature of the equivalent generator makes it impossible to use high-order models for analysis. The reactance x of the regional tie line was mentioned above. ij The mathematical formula is calculated using PMU measurement data, and the remaining parameters can also be indirectly derived using PMU measurement data. In other words, the equivalent generator internal reactance x is calculated using PMU data. i Equivalent inertia H and damping factor D.

[0090] In one embodiment, the estimated value of the equivalent inertia H can be obtained using PMU data and the least squares approximation method. Specifically, the calculation expression for the equivalent inertia H is as follows:

[0091]

[0092] Thus, the model parameters such as the reactance between the busbars, the internal reactance of the equivalent generator, the equivalent inertia, and the damping factor are obtained based on the PMU data. Based on the model parameters and the initial equivalent model, a regional equivalent model of the target power system is constructed.

[0093] It should be noted that constructing a reduced-order model requires specifying the parameters of each aggregated model, which is difficult for actual power system analysis. The regional equivalent model constructed in this invention includes a PMU, which enables the identification of the equivalent generator parameters to rely solely on PMU data. In other words, the model parameters of the regional equivalent model can be directly measured by the PMU or indirectly calculated based on the PMU data.

[0094] Step 120: Obtain phasor measurement data of the equivalent generators corresponding to each regional power subsystem based on the regional equivalent model.

[0095] Specifically, after constructing the regional equivalent model of the target power system, the PMU data of each equivalent generator is obtained based on the PMU in the regional equivalent model.

[0096] In one embodiment, the data type of PMU data can be frequency, instantaneous real power, phase angle, and other wide-area measurement data.

[0097] Step 130: Perform multi-channel singular spectrum analysis on the phasor measurement data to obtain the inter-regional oscillation mode signal of each equivalent generator.

[0098] Specifically, inter-regional oscillations in interconnected power systems increase system risks, particularly affecting the stability of the dominant oscillation profile. Therefore, analyzing regional oscillation information is crucial for locating the dominant oscillation profile and improving the stable operation of inter-regional power grids. Power monitoring units (PMUs) facilitate the monitoring and analysis of large-area interconnected power systems. When using PMU data to search for the dominant oscillation profile of the power grid, it is necessary to exclude intra-regional oscillation modes.

[0099] Specifically, a PMU signal can be clustered as follows:

[0100]

[0101] Where y0(t) is the DC mode signal, y s (t) represents the inter-regional oscillation mode signal, y f (t) represents the oscillating mode signal within the region. If all regional modes are less than 1, the value of r must be ω. i ∈(0,2π]rad / s. This indicates that to determine the dominant oscillation section between the study areas, it is necessary to extract y from the PMU data. s (t) Inter-regional oscillation mode component. The types of PMU data may include, but are not limited to, frequency, instantaneous real power, phase angle, and other wide-area measurement data.

[0102] Multi-channel singular spectrum analysis (MSSA) can be used to identify and extract the synchronous oscillation behavior of multivariate signals. It can extract the low-frequency resonance components of multivariate signals and is less affected by interference signals during processing. Especially for long-term nonlinear signals, MSSA performs better than single-channel singular spectrum analysis (SSA).

[0103] The process of multichannel singular spectral analysis (MSA) includes decomposition and reconstruction. It is similar to SSA in generating time-series trajectory matrices. Therefore, for a multivariate original signal with a time series scale of N and L channels, generating its trajectory matrix with a time delay of 1 yields a covariance matrix. The trajectory matrix is:

[0104]

[0105] Trajectory matrix X N The covariance matrix is ​​then:

[0106]

[0107] For X N Performing Singular Value Decomposition (SVD) yields the following:

[0108]

[0109] in,

[0110]

[0111] Where, in the formula and Representation matrix S N The eigenvalues ​​and corresponding eigenvectors are assigned. The assignment process is the same as MSSA and SSA, following the... Calculate the state vector In the eigenvector The orthogonal projection coefficients on are:

[0112]

[0113] Where 'l' represents the channel number. It is the component of the nth eigenvector at time lag j in channel l, and is a spatial-temporal empirical orthogonal function (ST-EOF). express In the original sequence X NiThe weights on the nth spatial-temporal principal component (ST-PC) are then called the reconstructed part of the MSSA:

[0114]

[0115] By selecting the first H terms to reconstruct the measurement signal, we obtain:

[0116]

[0117] In one embodiment, step 130 may specifically include the following steps: decomposing the phasor measurement data to obtain multiple common oscillation mode signals; extracting all inter-regional common oscillation mode signals from the multiple common oscillation mode signals; and reconstructing the inter-regional common oscillation mode signals based on the inter-regional common oscillation mode signals and the original phasor measurement signals of each equivalent generator to obtain the inter-regional oscillation mode signal of each equivalent generator.

[0118] Specifically, by performing MSSA decomposition on the PMU data, the measured signal can be decomposed into multiple common oscillation components, multiple common oscillation mode signals can be obtained, all inter-regional common oscillation mode signals can be extracted from the common oscillation mode signals, DC mode and intra-regional common oscillation mode signals can be excluded, and the signal can be reconstructed by using the long-term variation trend of the inter-regional common oscillation mode signals and the original signal to obtain new inter-regional oscillation mode signals for each equivalent generator.

[0119] Compared to SSA, MSSA has a significant advantage in extracting the common oscillation components of multivariate signals and can retain more useful information when extracting and analyzing interregional oscillation modes.

[0120] Taking the aforementioned IEEE 68-node system's equivalent regional model as an example, PMUs are used to collect interconnection transmission data between regions (PMU data), with a sampling rate of 0.02. It includes 5 regions using 5 frequency measurement channels, such as... Figure 4 The figure shows frequency measurement data for equivalent generators in five regions of the IEEE 68-bus system's regional equivalent model. In the figure, Area 1 represents the New England Test System (NETS), and Area 2 represents the New York Power System (NYPS).

[0121] MSSA analysis of the PMU data yielded the waveforms of the corresponding common oscillation components, as shown below. Figure 5As shown in (a) to (i), RC1 and RC2 are high-amplitude variations generated by generator control, representing long-term frequency fluctuations, i.e., DC modes. RC7, RC8, and RC9 have relatively small amplitudes and are common oscillation modes within the region. RC3 contains some high-amplitude modes, which may be caused by local system noise, measurement errors, and local oscillations caused by high damping ratios. RC4, RC5, and RC6 are common oscillation modes between regions, including the dominant oscillation mode.

[0122] y in the frequency measurement data of the five-region equivalent generator s (t) Inter-regional oscillation mode extraction: The long-term variation trend of all inter-regional common oscillation mode signals containing the dominant oscillation mode is selected and used to reconstruct the signal. The resulting new inter-regional oscillation mode signals for each equivalent generator are as follows: Figure 6 As shown in (a) to (e).

[0123] Step 140: Perform dissipative energy analysis on the inter-regional oscillation mode signal, and identify the dominant oscillation section of the target power system based on the dissipative energy of the inter-regional oscillation mode signal.

[0124] Specifically, energy functions can be used to analyze stability problems caused by disturbances in power systems. Previous methods employed eigenvalue analysis to analyze system oscillation behavior from an amplitude perspective; however, this method is ineffective in analyzing highly time-varying and highly nonlinear power systems. This invention uses PMU measurement data for energy analysis, enabling accurate determination of the system's oscillation characteristics.

[0125] Step 140 may specifically include the following steps: using the dissipated energy function to calculate and process the inter-regional oscillation mode signal to obtain the dissipated energy of each equivalent generator; determining the state of each equivalent generator based on the dissipated energy; and identifying the location of the dominant oscillation section in the target power system based on the state.

[0126] It should be noted that energy analysis using PMU measurement data requires certain assumptions to fit actual oscillation conditions. Assuming the load is uniformly distributed across the power system, the PMU is installed on the transmission bus, and the construction process of the aggregated equivalent generator will generate a small equivalent transformer and mechanical reactance, then:

[0127] V i ≈E i ;

[0128] ω≈ω i -ω s ≈ω i -ω j ;

[0129] θ≈δ;

[0130] Where, ω i and ω j This represents the measured values ​​on the i-th and j-th buses. The measured voltage in the aggregated equivalent generator bus contains the corresponding components of the modes within the region, which can be filtered out using the aforementioned MSSA method. The oscillation energy function F of the OMIB system... E It can be represented as kinetic energy F KE and potential energy F PE and dissipated energy F DE The sum, that is:

[0131] F E =F KE +F PE +F DE .

[0132] Specifically, the formulas for calculating kinetic energy, potential energy, and dissipated energy are expressed as follows:

[0133]

[0134]

[0135]

[0136] Where, θ q F is the phase angle of the system voltage after the disturbance; DE This represents the dissipated energy of the equivalent large motor. V is the total reactance of the transmission path between region i and region j. i Let V be the voltage in region i. j Let θ be the voltage in region j. ij Let θ be the voltage phase angle of the transmission path between region i and region j. i Let θ be the voltage phase angle of region i. j Let be the voltage phase angle of region j.

[0137] Dissipated energy can be used to determine the location of the dominant oscillation section of a system. Its value is mainly related to the system's active power increment and phase angle difference. A positive dissipated energy value indicates that the system is in a dissipated state, suggesting that the system is in a state of recovery to stability. Conversely, the system requires energy injection, indicating that the system is in a state unfavorable to recovery to stability.

[0138] Based on the above formula for calculating dissipated energy, the oscillating dissipated energy of the equivalent motor in each region can be used to determine the state of the equivalent generator in each region. The example of the regional equivalent model constructed using the IEEE 68-node system above shows the calculated results of the dissipated energy of the equivalent motor in each region as follows: Figure 7 As shown. From Figure 7The dissipation energy curves show that regions 1 and 2 are in a dissipation state, while regions 3, 4, and 5 are in a state unfavorable for restoring stability. Combined with... Figure 3 The diagram shows the equivalent regional model. The system is radially connected, thus determining that the dominant regional oscillation section is the connecting line between regions 2 and 3. Figure 8 As shown, it presents a schematic diagram of the transmission power angle curves of regions 2 and 3 fitted from PMU data using the least squares approximation method, which confirms that the dominant oscillation section is the connecting line between regions 2 and 3.

[0139] The dominant oscillation section identification method for power systems provided by this invention constructs a regional equivalent model of the target power system, equating each regional power subsystem of the target power system to an equivalent generator, and obtains phasor measurement data of the equivalent generator. Using a multi-channel singular spectrum analysis method, the inter-regional oscillation mode signals in the phasor measurement data can be extracted quickly and effectively. Furthermore, the extracted inter-regional oscillation mode signals have good noise resistance and can retain more useful inter-regional oscillation information. The dissipated energy analysis method is used to calculate the dissipated energy of the inter-regional oscillation mode signals, thereby identifying the dominant oscillation section of the target power system from an energy perspective. Since the energy perspective can reflect the influence of time-varying factors on the oscillation behavior of the power system, the dominant oscillation section can be accurately identified, improving the identification accuracy.

[0140] To verify the dominant oscillation profile determination results of the example regional equivalent model constructed by the IEEE 68-node system, the inter-regional common oscillation modes from the multiple common oscillation components decomposed by MSSA were separated, and the dominant inter-regional common oscillation mode was determined by calculating the energy of each inter-regional common oscillation mode signal. The inter-regional common oscillation modes of the above five regional equivalent models are RC4, RC5, and RC6. For reference, RC3, which may be caused by local system noise, measurement errors, and high damping ratio, was also calculated. The energy curves of RC3 to RC5 are shown in the figure. Figure 9 As shown. From Figure 9 It can be seen that RC3 and RC5 have relatively high overall energy trends. Since RC3 includes local oscillations caused by system noise and measurement errors, RC5 is determined to be the dominant oscillation mode. The system oscillation frequency is a regional oscillation of 0.31Hz, and the system damping ratio is 13.54%.

[0141] Furthermore, the dominant oscillation mode components can be analyzed, specifically the mode shape diagrams of each equivalent generator under the common oscillation modes in the dominant regions, such as... Figure 10 As shown. Furthermore, a schematic diagram of the motor slip compass for each equivalent generator under the common oscillation mode in the dominant regions is also given, as shown. Figure 11 As shown. From Figure 10 , 11 It can be seen that under this dominant oscillation mode, the system oscillation is characterized by oscillations in region 1-2 compared to region 3-5, which is consistent with the results of the dissipative energy analysis. Therefore, in this oscillation event, the dominant oscillation section of the target power system is the tie line between region 2 and region 3.

[0142] It should be noted that regional measurement signals often contain a lot of noise, which can significantly affect the observability of oscillation behavior. This necessitates that multi-channel analysis methods based on measurement data possess a certain degree of noise robustness. Taking the example of the regional equivalent model constructed using the IEEE 68-node system mentioned above, a stable segment of the original measurement signal was extracted, and interference noise with a signal-to-noise ratio of 5 was added. The waveforms of the original measurement signal before and after adding noise are shown in the diagram below. Figure 12 As shown. The inter-regional oscillation mode signal obtained by signal reconstruction using the MSSA method of this invention is then subjected to interference noise with the same signal-to-noise ratio of 5. The waveforms of the inter-regional oscillation mode signal before and after the addition of noise are illustrated in the diagram. Figure 13 As shown, even in high-noise environments, the method can still smoothly reconstruct the signal. This indicates that the method of the present invention is applicable to practically measured noise-like data.

[0143] It should be noted that when each regional power subsystem in the target power system is connected to only one or two other regional power subsystems, the dissipated energy of the inter-regional oscillation mode signal is analyzed, and the state of each equivalent generator is determined based on the dissipated energy of each equivalent generator. The position of the dominant oscillation section in the target power system can be directly identified from the state.

[0144] However, for a star-connected target power system—that is, at least one regional power subsystem connecting three or more other regional power subsystems—energy dissipation analysis of the inter-regional oscillation mode signals may reveal the possible locations of multiple dominant oscillation sections within the target power system. In this case, it is necessary to further combine the determination of the common oscillation mode between the dominant regions. Based on the mode shape under the common oscillation mode between the dominant regions of each equivalent generator, the location of the dominant oscillation section within the target power system can be ultimately identified.

[0145] In one embodiment, the method further includes:

[0146] When it is identified that there is more than one dominant oscillation section in the target power system based on the state, the energy of the common oscillation mode signal between each region is obtained.

[0147] Based on the energy of the common oscillation mode signal between each region, the dominant common oscillation mode between regions is determined;

[0148] Obtain the mode shape of each of the equivalent generators under the common oscillation mode in the dominant regions;

[0149] The location of the dominant oscillation section in the target power system is finally determined by combining the location and the mode shape.

[0150] In one embodiment, the energy of the common oscillation mode signal between each region is calculated using the following formula:

[0151]

[0152] Among them, E k,∞ The energy of the common oscillation mode signal between the regions, representing a time series of length T. This represents the common oscillating mode signal of the nth eigenvector in the region of channel l.

[0153] The dominant oscillation section identification method for power systems provided by this invention constructs a regional equivalent model of the target power system, equating each regional power subsystem of the target power system to an equivalent generator, and obtains phasor measurement data of the equivalent generator. Using multi-channel singular spectrum analysis, the inter-regional oscillation mode signals in the phasor measurement data can be extracted quickly and effectively, and the extracted inter-regional oscillation mode signals have good noise resistance, retaining more useful inter-regional oscillation information. Furthermore, the dissipated energy analysis method is used to calculate the dissipated energy of the inter-regional oscillation mode signals, thereby identifying the dominant oscillation section of the target power system from an energy perspective. Since the energy perspective can reflect the influence of time-varying factors on the oscillation behavior of the power system, the dominant oscillation section can be accurately identified, improving the identification accuracy. For star-connected target power systems, the method further combines the determination of the dominant inter-regional common oscillation mode, and based on the mode shape under the dominant inter-regional common oscillation mode of each equivalent generator, the location of the dominant oscillation section in the target power system is finally identified.

[0154] The dominant oscillation section identification device for power systems provided by the present invention is described below. The dominant oscillation section identification device for power systems described below can be referred to in correspondence with the dominant oscillation section identification method for power systems described above.

[0155] like Figure 14 As shown, the present invention provides a power system dominant oscillation section identification device, specifically comprising:

[0156] Construction module 1410 is used to construct a regional equivalent model of the target power system; wherein the target power system includes multiple regional power subsystems;

[0157] The first acquisition module 1420 is used to acquire phasor measurement data of the equivalent generators corresponding to each regional power subsystem based on the regional equivalent model;

[0158] The second acquisition module 1430 is used to perform multi-channel singular spectrum analysis on the phasor measurement data to acquire the inter-regional oscillation mode signal of each equivalent generator.

[0159] The identification module 1440 is used to perform dissipated energy analysis on the inter-regional oscillation mode signal and identify the dominant oscillation section of the target power system based on the dissipated energy of the inter-regional oscillation mode signal.

[0160] Figure 15 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 15 As shown, the electronic device may include a processor 1510, a communication interface 1520, a memory 1530, and a communication bus 1540, wherein the processor 1510, the communication interface 1520, and the memory 1530 communicate with each other through the communication bus 1540. The processor 1510 can call logical instructions in the memory 1530 to execute a method for identifying the dominant oscillation section of a power system. This method includes: constructing a regional equivalent model of a target power system; wherein the target power system includes multiple regional power subsystems; obtaining phasor measurement data of equivalent generators corresponding to each regional power subsystem based on the regional equivalent model; performing multi-channel singular spectrum analysis on the phasor measurement data to obtain the inter-regional oscillation mode signal of each equivalent generator; performing dissipated energy analysis on the inter-regional oscillation mode signal; and identifying the dominant oscillation section of the target power system based on the dissipated energy of the inter-regional oscillation mode signal.

[0161] Furthermore, the logical instructions in the aforementioned memory 1530 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0162] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the power system dominant oscillation section identification method provided by the above methods. The method includes: constructing a regional equivalent model of a target power system; wherein the target power system includes multiple regional power subsystems; obtaining phasor measurement data of equivalent generators corresponding to each regional power subsystem based on the regional equivalent model; performing multi-channel singular spectrum analysis on the phasor measurement data to obtain inter-regional oscillation mode signals of each equivalent generator; performing dissipated energy analysis on the inter-regional oscillation mode signals; and identifying the dominant oscillation section of the target power system based on the dissipated energy of the inter-regional oscillation mode signals.

[0163] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the method for identifying the dominant oscillation profile of a power system provided by the methods described above. This method includes: constructing a regional equivalent model of a target power system; wherein the target power system includes multiple regional power subsystems; obtaining phasor measurement data of equivalent generators corresponding to each regional power subsystem based on the regional equivalent model; performing multi-channel singular spectrum analysis on the phasor measurement data to obtain inter-regional oscillation mode signals of each equivalent generator; performing dissipative energy analysis on the inter-regional oscillation mode signals; and identifying the dominant oscillation profile of the target power system based on the dissipative energy of the inter-regional oscillation mode signals.

[0164] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0165] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0166] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for identifying the dominant oscillation section of a power system, characterized in that, include: Construct a regional equivalent model of the target power system; wherein the target power system includes multiple regional power subsystems; Based on the regional equivalent model, obtain the phasor measurement data of the equivalent generators corresponding to each regional power subsystem; Multichannel singular spectrum analysis is performed on the phasor measurement data to obtain the inter-regional oscillation mode signal of each equivalent generator; The dissipation energy function is used to analyze the dissipation energy of the inter-regional oscillation mode signal, and the dominant oscillation section of the target power system is identified based on the dissipation energy of the inter-regional oscillation mode signal; the expression of the dissipation energy function is: ； in, The energy dissipated by the equivalent generator is For the region With the region The total reactance of the transmission path between them For the region voltage, For the region voltage, For the region With the region Voltage phase angle of the transmission path between them For the region voltage phase angle, For the region The voltage phase angle.

2. The method for identifying the dominant oscillation section of a power system according to claim 1, characterized in that, The step of performing multi-channel singular spectrum analysis on the phasor measurement data to obtain the inter-regional oscillation mode signal of each equivalent generator includes: Based on the phasor measurement data, multiple common oscillation mode signals are obtained by decomposition. Extract all inter-regional common oscillation mode signals from multiple common oscillation mode signals; The inter-regional oscillation mode signal of each equivalent generator is obtained by reconstructing the inter-regional common oscillation mode signal with the original phasor measurement signal of each equivalent generator.

3. The method for identifying the dominant oscillation section of a power system according to claim 2, characterized in that, The method of performing dissipative energy analysis on the inter-regional oscillation mode signal using a dissipative energy function, and identifying the dominant oscillation section of the target power system based on the dissipative energy of the inter-regional oscillation mode signal, includes: The dissipated energy function is used to calculate and process the inter-regional oscillation mode signal to obtain the dissipated energy of each equivalent generator; The state of each equivalent generator is determined based on the dissipated energy. Based on the aforementioned state, the location of the dominant oscillation section in the target power system is identified.

4. The method for identifying the dominant oscillation section of a power system according to claim 3, characterized in that, Also includes: When it is identified that there is more than one dominant oscillation section in the target power system based on the state, the energy of the common oscillation mode signal between each region is obtained. Based on the energy of the common oscillation mode signal between each region, the dominant common oscillation mode between regions is determined; Obtain the mode shape of each of the equivalent generators under the common oscillation mode in the dominant regions; The location of the dominant oscillation section in the target power system is finally determined by combining the location and the mode shape.

5. The method for identifying the dominant oscillation section of a power system according to claim 4, characterized in that, The energy of the common oscillation mode signal between each region is calculated using the following formula: ； in, The length of the time series is represented as The energy of the inter-regional common oscillation mode signal, Representative at the Each feature vector in the channel Interregional common oscillation mode signal.

6. The method for identifying the dominant oscillation section of a power system according to claim 1, characterized in that, The construction of the regional equivalent model of the target power system includes: An initial equivalent model is constructed based on the target power system; wherein, the initial equivalent model includes equivalent generators of the regional power subsystem, the equivalent generators with connection relationships are connected through a bus, and each of the equivalent generators is equipped with a phasor measurement unit; Based on the phasor measurement data collected by the phasor measurement unit, model parameters are obtained; wherein, the model parameters include the reactance between the buses, the internal reactance of the equivalent generator, the equivalent inertia, and the damping factor; Based on the initial equivalent model and the model parameters, the regional equivalent model is constructed.

7. A device for identifying inter-regional oscillation modes in a power system, characterized in that, include: A construction module is used to construct a regional equivalent model of the target power system; wherein the target power system includes multiple regional power subsystems; The first acquisition module is used to acquire phasor measurement data of the equivalent generators corresponding to each regional power subsystem based on the regional equivalent model; The second acquisition module is used to perform multi-channel singular spectrum analysis on the phasor measurement data to acquire the inter-regional oscillation mode signal of each equivalent generator; The identification module is used to perform dissipative energy analysis on the inter-regional oscillation mode signal using a dissipative energy function, and to identify the dominant oscillation section of the target power system based on the dissipative energy of the inter-regional oscillation mode signal; the expression of the dissipative energy function is: ； in, The energy dissipated by the equivalent generator is For the region With the region The total reactance of the transmission path between them For the region voltage, For the region voltage, For the region With the region Voltage phase angle of the transmission path between them For the region voltage phase angle, For the region The voltage phase angle.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the power system dominant oscillation section identification method as described in any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the power system dominant oscillation section identification method as described in any one of claims 1 to 6.

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