Energy storage power station oscillation risk monitoring method and device based on impedance network aggregation

Abstract

The invention discloses an energy storage power station oscillation risk monitoring method and device based on impedance network aggregation, and belongs to the field of power systems, and the method comprises the steps: obtaining impedance information and a first network topology structure of each device in an energy storage power station; obtaining a first impedance network framework by adopting a hierarchical calculation method; based on the framework and the impedance information, an impedance network aggregation method is adopted to calculate impedance characteristics of all frequency points to form full-frequency-domain impedance characteristics, and the oscillation risk of the energy storage power station is monitored according to the full-frequency-domain impedance characteristics and actual impedance data. The problem that it is difficult to accurately monitor the oscillation risk of the energy storage power station while guaranteeing the calculation efficiency in the prior art can be solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of power systems, in particular to a kind of energy storage power station oscillation risk monitoring method and device based on impedance network aggregation. BACKGROUND

[0002] In modern power system, with the continuous improvement of wind power, photovoltaic and other new energy power generation penetration rate, a large number of new energy is connected to the grid through power electronic converter, so that the mixed energy storage power station with grid-connected type and network-constructed type energy storage as the core becomes the key link to maintain system stability, the impedance characteristics of internal single machine, transformer, collection line and other equipment of the mixed energy storage power station show significant wideband frequency dependence, and the impedance parameters of different frequency bands directly affect the excitation and propagation of oscillation mode, so the oscillation risk monitoring of energy storage power station becomes an important prerequisite to ensure the safe operation of power station.

[0003] In the prior art, the judgment of the oscillation risk of the mixed energy storage power station mainly depends on full detailed modeling or equivalent simplified modeling method. Since full detailed modeling needs to model all devices in detail, the calculation complexity increases exponentially with the scale of the power station, which is difficult to meet the real-time requirements of engineering; And equivalent simplified modeling ignores the single machine topology difference and multi-frequency band coupling effect, which leads to distortion of impedance characteristics and cannot accurately capture the oscillation risk boundary of sub-synchronous frequency band and super-synchronous frequency band, so there is a problem that the modeling efficiency and evaluation accuracy cannot be considered at the same time, and the oscillation risk monitoring is not accurate. SUMMARY

[0004] The present application provides a kind of energy storage power station oscillation risk monitoring method and device based on impedance network aggregation, which can solve the problem that it is difficult to ensure calculation efficiency while accurately monitoring the oscillation risk of energy storage power station in the prior art.

[0005] In the first aspect, the present application embodiment provides a kind of energy storage power station oscillation risk monitoring method based on impedance network aggregation, comprising: Obtain the impedance information corresponding to each device in the energy storage power station and the first network topology structure of the energy storage power station;Wherein, the impedance information corresponding to any device includes the impedance characteristics corresponding to the device at each frequency point; According to the first network topology structure and the devices, a hierarchical calculation method is used to obtain the first impedance network framework of the energy storage power station; Based on the first impedance network framework and the impedance information corresponding to each device, the impedance network aggregation method is used to calculate the impedance characteristics corresponding to the energy storage power station at each frequency point in turn, and the impedance characteristics of all frequency points are combined to form the full frequency domain impedance characteristics of the energy storage power station; Obtain the actual impedance data of the energy storage power station, and monitor the oscillation risk of the energy storage power station according to the full frequency domain impedance characteristics of the energy storage power station and the actual impedance data.

[0006] This application, by acquiring the impedance characteristics of each device in an energy storage power station at different frequency points and fully understanding the first network topology of the power station, provides a comprehensive data foundation for subsequent impedance network calculations. Based on this, this application employs a hierarchical calculation method to construct the first impedance network framework. Within this framework, each device is divided into different levels, connected by specific nodes. This not only fully considers the hierarchical structure and complex relationships of the devices in the energy storage power station but also provides a clear computational logic for subsequent impedance characteristic calculations. Subsequently, based on this impedance network framework and the impedance information of each device, the impedance network aggregation method is used to sequentially calculate the impedance characteristics of the power station at each frequency point and form a full-frequency domain impedance characteristic. This comprehensively covers all frequency ranges that the system may involve, avoiding the omission of potential oscillation risk factors due to missing frequency points, thus forming a complete characterization of the overall impedance characteristics of the power station. Furthermore, this processing method eliminates the need to construct a detailed model of the energy storage power station, saving computational resources. Finally, the oscillation risk of the energy storage power station is monitored by combining the actual impedance data of the energy storage power station. Therefore, this application solves the problem in the prior art of accurately monitoring the oscillation risk of energy storage power stations while ensuring computational efficiency.

[0007] As a preferred example of the first aspect, the energy storage power station includes several energy storage converter devices and several auxiliary devices. The acquisition of impedance information corresponding to each device in the energy storage power station specifically involves: For any energy storage converter device, the voltage time-domain signal and current time-domain signal of the energy storage converter device are acquired, and the impedance information corresponding to the energy storage converter device is obtained based on the voltage time-domain signal and the current time-domain signal; wherein, the voltage time-domain signal and the current time-domain signal are obtained by injecting positive and negative sequence disturbance signals within a preset frequency range into the grid connection point of the energy storage converter through the voltage disturbance method; For any auxiliary device, the impedance information corresponding to the auxiliary device is obtained by using the electromagnetic equivalent reduction method according to the first network topology.

[0008] In this preferred embodiment, positive and negative sequence disturbance signals within a preset frequency range are injected into the grid connection point of the energy storage converter using a voltage perturbation method. This allows for the acquisition of voltage and current time-domain signals and their impedance information. This ensures that the converter's impedance information accurately reflects its actual electrical characteristics within that frequency range, avoiding omissions due to limitations in signal acquisition methods. For auxiliary equipment, impedance information is obtained using an electromagnetic equivalent reduction method based on the first network topology. This method fully integrates the connection relationships of the equipment within the network for equivalent processing, ensuring that the impedance information of the auxiliary equipment is compatible with the overall network structure and reducing deviations caused by neglecting correlations in individual calculations. These two methods, targeting the energy storage converter and auxiliary equipment respectively, comprehensively improve the accuracy and adaptability of impedance information for each device, providing reliable foundational data for subsequent analysis of the overall impedance characteristics of the energy storage power station.

[0009] As a preferred example of the first aspect, the step of obtaining the first impedance network framework of the energy storage power station based on the first network topology and the various devices using a hierarchical calculation method specifically includes: Extract all nodes from the first network topology and form a node set; The devices are sequentially divided into hierarchical levels based on the node set, and the first impedance network framework is obtained based on all the divided devices and the node set.

[0010] In this preferred example, by extracting all nodes of the first network topology to form a set, the network connection nodes can be fully covered, providing a complete reference for device hierarchy division. Based on this, the hierarchy of each device can be divided in sequence, so that the division result fits the actual structure and clearly presents the relationship between devices. Then, by combining the divided set of devices and nodes, the first impedance network framework can be obtained, so that the framework structure is clear and the relationship is accurate, providing a reliable foundation for subsequent impedance calculation.

[0011] As a preferred example of the first aspect, the node set includes grid connection points, several main transformer nodes, several collection line nodes, and several generator unit nodes. The step of hierarchically dividing the equipment according to the node set, and obtaining the first impedance network framework based on all the divided equipment and the node set, specifically involves: The devices are hierarchically divided according to the node set to obtain the devices corresponding to each level; wherein, the devices between the grid connection point and each main transformer node are divided into the first level, the devices between each main transformer node and each collection line node are divided into the second level, the devices between each collection line node and each generator node are divided into the third level, and the devices after each generator node are divided into the fourth level. The devices and node sets corresponding to each level are connected according to the first network topology to obtain the first impedance network framework.

[0012] In this preferred example, Tonghua clearly defines the node set as including grid connection points, main transformer nodes, etc., and classifies the equipment into corresponding levels according to these nodes. This allows the equipment division to conform to the actual structure and functional logic, clearly presenting the relationships and hierarchical architecture, and avoiding arbitrary and ambiguous division. Furthermore, by combining the network topology to connect the equipment and node sets at each level, the first impedance network framework is obtained, which makes the framework structure clear and provides an accurate and reliable foundation for subsequent impedance calculations.

[0013] As a preferred example of the first aspect, the impedance characteristics of the energy storage power station at each frequency point are calculated sequentially using an impedance network aggregation method based on the first impedance network framework and the impedance information corresponding to each device, and the impedance characteristics of all frequency points are combined to form the full-frequency domain impedance characteristics of the energy storage power station. Specifically: The impedance characteristics of each device under the same unit node at the same frequency point are processed by series and parallel connection to obtain the impedance of each first branch network. The impedance of each first branch network is then connected in series with the corresponding third-level device to obtain the impedance of each second branch network. The second branch network impedances under the same aggregation line node in each second branch network impedance are connected in parallel to obtain the equivalent impedance of each first aggregation line node, and the equivalent impedance of each first aggregation line node is connected in series with the corresponding second-level device to obtain the equivalent impedance of each second aggregation line node. The equivalent impedances of each second collection line node under the same main transformer node are connected in parallel to obtain the equivalent impedance of each first main transformer node. The equivalent impedances of each first main transformer node are then connected in series with the corresponding first-level equipment to obtain the equivalent impedance of each second main transformer node. The equivalent impedances of each of the second main transformer nodes are connected in parallel to obtain the first impedance characteristic. The first impedance characteristic is then connected in series with the preset line impedance of the grid-connected substation to obtain the impedance characteristic of the energy storage power station at that frequency point. The impedance characteristics generated at all frequency points are combined to form the full-frequency domain impedance characteristic of the energy storage power station.

[0014] In this preferred example, by processing the impedances of the same unit node equipment in series and parallel and combining them with third-level equipment, the overall electrical characteristics of that level can be integrated; by combining the relevant impedances under the line node in parallel and in series with second-level equipment, the impedance information of that level can be aggregated; by integrating the relevant impedances of the main transformer node and in series with first-level equipment, its overall impedance can be presented; finally, the impedances at each frequency point are obtained by combining the equivalent impedance of the main transformer node in parallel and the impedance of the grid-connected line in series, forming the full-frequency domain characteristics. This impedance network aggregation method not only saves computational resources but also comprehensively reflects the overall impedance of the energy storage power station, providing a reliable basis for judging oscillation risk.

[0015] As a preferred example of the first aspect, obtaining the impedance information corresponding to each device in the energy storage power station and the first network topology of the energy storage power station specifically includes: Obtain the original network topology of the energy storage power station. If there is a triangular structure in the original network topology, convert the triangular structure in the original network topology into a star structure through star-triangular transformation to obtain the first network topology.

[0016] In this preferred example, after obtaining the original network topology of the energy storage power station, if a delta structure exists, it is transformed into a star structure through star-delta transformation to obtain the first network topology. This can eliminate the network complexity caused by the delta structure, making the topology simpler and clearer, which is convenient for subsequent work such as hierarchical division of each device, construction of impedance network framework, and calculation of impedance characteristics.

[0017] Secondly, the present invention provides an energy storage power station oscillation risk monitoring device based on impedance network aggregation, comprising: a data acquisition module, a first calculation module, a second calculation module, and a result output module; The data acquisition module is used to acquire the impedance information of each device in the energy storage power station and the first network topology of the energy storage power station; wherein, the impedance information of any device includes the impedance characteristics of the device at each frequency point. The first calculation module is used to obtain the first impedance network framework of the energy storage power station by using a hierarchical calculation method based on the first network topology and each device. The second calculation module is used to calculate the impedance characteristics of the energy storage power station at each frequency point in sequence using the impedance network aggregation method based on the first impedance network framework and the impedance information corresponding to each device, and to combine the impedance characteristics of all frequency points into the full-frequency domain impedance characteristics of the energy storage power station. The result output module is used to acquire the actual impedance data of the energy storage power station, and to monitor the oscillation risk of the energy storage power station based on the full-frequency impedance characteristics of the energy storage power station and the actual impedance data.

[0018] As a preferred example of the second aspect, the energy storage power station includes several energy storage converter devices and several auxiliary devices, and the data acquisition module includes a first acquisition unit and a second acquisition unit; The first acquisition unit is used to acquire, for any energy storage converter device, the voltage time-domain signal and the current time-domain signal of the energy storage converter device, and obtain the impedance information corresponding to the energy storage converter device based on the voltage time-domain signal and the current time-domain signal; wherein, the voltage time-domain signal and the current time-domain signal are obtained by injecting positive and negative sequence disturbance signals within a preset frequency range into the grid connection point of the energy storage converter through a voltage disturbance method; The second acquisition unit is used to obtain the impedance information of any auxiliary device by using an electromagnetic equivalent reduction method based on the first network topology.

[0019] As a preferred example of the second aspect, the first computing module includes a first computing unit and a second computing unit; The first computing unit is used to extract all nodes in the first network topology and form a node set; The second calculation unit performs hierarchical division of each device according to the node set, and obtains the first impedance network framework based on all the divided devices and the node set.

[0020] As a preferred example of the second aspect, the node set includes grid connection points, several main transformer nodes, several collection line nodes and several generator nodes, and the second computing unit includes a first computing subunit and a second computing subunit. The first calculation subunit is used to divide the devices into hierarchical levels according to the node set to obtain the devices corresponding to each level; wherein, the devices between the grid connection point and each main transformer node are divided into the first level, the devices between each main transformer node and each collection line node are divided into the second level, the devices between each collection line node and each generator node are divided into the third level, and the devices after each generator node are divided into the fourth level. The second calculation subunit is used to connect the devices and node sets corresponding to each level according to the first network topology to obtain the first impedance network framework.

[0021] As a preferred example of the second aspect, the second computing module includes a third computing unit, a fourth computing unit, a fifth computing unit, and a sixth computing unit; The third calculation unit is used to process the impedance characteristics of each device under the same unit node in each device in series and parallel at the same frequency point to obtain the impedance of each first branch network, and to connect the impedance of each first branch network in series with the corresponding third-level device to obtain the impedance of each second branch network. The fourth calculation unit is used to connect the second branch network impedances under the same collection line node in parallel to obtain the equivalent impedance of each first collection line node, and connect the equivalent impedance of each first collection line node in series with the corresponding second-level device to obtain the equivalent impedance of each second collection line node. The fifth calculation unit is used to connect the equivalent impedances of each second collection line node under the same main transformer node in parallel to obtain the equivalent impedance of each first main transformer node, and connect the equivalent impedances of each first main transformer node in series with the corresponding first-level equipment to obtain the equivalent impedance of each second main transformer node. The sixth calculation unit is used to connect the equivalent impedances of each second main transformer node in parallel to obtain the first impedance characteristic, and connect the first impedance characteristic in series with the preset grid-connected substation line impedance to obtain the impedance characteristic of the energy storage station at that frequency point, and combine the impedance characteristics generated at all frequency points to form the full-frequency domain impedance characteristic of the energy storage station.

[0022] As a preferred example of the second aspect, the data acquisition module further includes a third acquisition unit; The third acquisition unit is used to acquire the original network topology of the energy storage power station. If there is a triangular structure in the original network topology, the triangular structure in the original network topology is converted into a star structure through star-triangular transformation to obtain the first network topology.

[0023] In summary, this application, by acquiring the impedance characteristics of each device in the energy storage power station at different frequency points and fully understanding the first network topology of the power station, provides a comprehensive data foundation for subsequent impedance network calculations. Based on this, this application employs a hierarchical calculation method to construct the first impedance network framework. Within this framework, each device is divided into different levels, connected by specific nodes. This not only fully considers the hierarchical structure and complex relationships of the devices in the energy storage power station but also provides a clear computational logic for subsequent impedance characteristic calculations. Subsequently, based on this impedance network framework and the impedance information of each device, the impedance network aggregation method is used to sequentially calculate the impedance characteristics of the power station at each frequency point and form a full-frequency domain impedance characteristic. This comprehensively covers all frequency ranges that the system may involve, avoiding the omission of potential oscillation risk factors due to missing frequency points, thus forming a complete characterization of the overall impedance characteristics of the power station. Furthermore, this processing method eliminates the need to construct a detailed model of the energy storage power station, saving computational resources. Finally, the oscillation risk of the energy storage power station is monitored by combining the actual impedance data of the energy storage power station. Therefore, this application can solve the problem in the prior art that it is difficult to accurately monitor the oscillation risk of energy storage power stations while ensuring computational efficiency.

[0024] Another embodiment of the present invention provides a terminal device, including: a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the steps of the energy storage power station oscillation risk monitoring method based on impedance network aggregation of the present invention.

[0025] Another embodiment of the present invention provides a computer-readable storage medium item, including: a stored computer program, which, when the computer program is running, controls the device where the computer-readable storage medium is located to perform the steps of the energy storage power station oscillation risk monitoring method based on impedance network aggregation of the present invention. Attached Figure Description

[0026] To more clearly illustrate the technical solutions of this application, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1 This is a flowchart illustrating an embodiment of an energy storage power station oscillation risk monitoring method based on impedance network aggregation provided by the present invention. Figure 2 A star-angle transformation diagram of an embodiment of an energy storage power station oscillation risk monitoring method based on impedance network aggregation provided by the present invention; Figure 3 A schematic diagram illustrating the impedance network framework construction process of an embodiment of the oscillation risk monitoring method for energy storage power stations based on impedance network aggregation provided by the present invention. Figure 4 A schematic diagram of the impedance network framework for an embodiment of an energy storage power station oscillation risk monitoring method based on impedance network aggregation provided by the present invention; Figure 5 This is a flowchart illustrating an embodiment of an energy storage power station oscillation risk monitoring method based on impedance network aggregation provided by the present invention. Figure 6 The flowchart illustrates the calculation of impedance characteristics for an embodiment of an energy storage power station oscillation risk monitoring device based on impedance network aggregation, provided by the present invention. Detailed Implementation

[0028] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings of the embodiments. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0029] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0030] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0031] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0032] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0033] In the description of the embodiments of this application, the term "multiple" refers to two or more (including two), similarly, "multiple sets" refers to two or more (including two sets), and "multiple pieces" refers to two or more (including two pieces).

[0034] In the description of the embodiments of this application, unless otherwise expressly specified and limited, technical terms such as "installation," "connection," "joining," and "fixing" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; 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 components or the interaction between two components. For those skilled in the art, the specific meaning of the above terms in the embodiments of this application can be understood according to the specific circumstances.

[0035] Example 1 See Figure 1To address the challenge of accurately monitoring the oscillation risk of energy storage power stations while ensuring computational efficiency in existing technologies, this application provides a method for monitoring the oscillation risk of energy storage power stations based on impedance network aggregation, comprising: S1. Obtain the impedance information of each device in the energy storage power station and the first network topology of the energy storage power station; wherein, the impedance information of any device includes the impedance characteristics of the device at each frequency point. In some embodiments of this application, the energy storage power station includes several energy storage converter devices and several auxiliary devices. The acquisition of impedance information corresponding to each device in the energy storage power station specifically involves: For any energy storage converter device, the voltage time-domain signal and current time-domain signal of the energy storage converter device are acquired, and the impedance information corresponding to the energy storage converter device is obtained based on the voltage time-domain signal and the current time-domain signal; wherein, the voltage time-domain signal and the current time-domain signal are obtained by injecting positive and negative sequence disturbance signals within a preset frequency range into the grid connection point of the energy storage converter through the voltage disturbance method; For any auxiliary device, the impedance information corresponding to the auxiliary device is obtained by using the electromagnetic equivalent reduction method according to the first network topology.

[0036] In some optional embodiments of this application, obtaining the impedance information corresponding to each device in the energy storage power station specifically includes: The energy storage converter equipment may include grid-connected energy storage converters and network-connected energy storage converters. Grid-connected energy storage converters require limiting their rated current to avoid PLL instability caused by excessive disturbance amplitude. Network-connected energy storage converters, due to their stronger dynamic response capability, can appropriately increase the amplitude. Through electromagnetic mode transient simulation or hardware-in-the-loop simulation, a voltage disturbance method is used to sequentially inject small positive and negative sequence disturbance signals within a certain frequency range at the grid connection point of a single unit. Taking the positive sequence as an example, the specific response current includes the current response at the same frequency and the current response at the coupled frequency. The two output currents will generate corresponding voltage disturbances in the system. These two voltage disturbances, in turn, generate two response currents through the control loop and the main circuit, respectively, ultimately forming a closed loop. After processing and calculation, instantaneous data such as the disturbance voltage and its response current components at each frequency point of the single unit are obtained.

[0037] The Fast Fourier Transform (FFT) algorithm was used to perform Discrete Fourier Analysis on the acquired voltage and current time-domain signals. Transient waveform data during device operation was captured by using sampling points at least twice the highest frequency of the signal and a sufficient number of sampling points. After preprocessing such as denoising filtering and adding a Hanning window, the non-stationary time-domain signal was converted into a frequency-domain analytical expression using FFT, and the complex amplitudes of each harmonic component were extracted. Based on the Thevenin equivalent circuit principle and Kirchhoff's voltage law, a system of equations was established to finally calculate the impedance information corresponding to different frequency points.

[0038] For example, the calculation process of positive sequence impedance will be used as an example to illustrate: Injecting a voltage disturbance at the grid connection point of the energy storage converter will generate a current response with the same frequency f0 and a current response with a coupling frequency f1. These two output currents will in turn generate corresponding voltage disturbances in the system. These two voltage disturbances will then generate two response currents through the control loop and the main circuit, respectively, ultimately forming a closed loop. Considering the coupling effect, the coupling admittance matrix is: in, and for The positive-sequence admittance represents the small-signal response of a positive-sequence current at frequency f0. The positive-sequence coupling admittance represents the negative-sequence current small-signal response at frequency f1 under a positive-sequence voltage small-signal disturbance at frequency f0. The negative-sequence admittance represents the small-signal response of the negative-sequence current at frequency f1 under a small-signal disturbance of the negative-sequence voltage at frequency f1. The negative-sequence coupling admittance represents the positive-sequence current small-signal response at frequency f0 under a negative-sequence voltage small-signal disturbance at frequency f1.

[0039] The inverse of the admittance yields the corresponding impedance, and the specific calculation formula is as follows: in, Indicates positive sequence impedance; Indicates the positive-sequence coupling impedance; Indicates negative sequence coupling impedance; Indicates negative sequence impedance; It is the coupling matrix of Park variation and control loop derivation, including the cross term of f0 and f1; s is the frequency shift operator.

[0040] The effect of the coupling term is equivalently factored into the output impedance, and the expression for the equivalent positive-sequence output impedance Z+ is: Based on the conversion relationship between positive and negative sequence impedances, the negative sequence impedance considering frequency coupling effects can be obtained, i.e.: In some embodiments of this application, obtaining the impedance information corresponding to each device in the energy storage power station and the first network topology of the energy storage power station specifically involves: Obtain the original network topology of the energy storage power station. If there is a triangular structure in the original network topology, convert the triangular structure in the original network topology into a star structure through star-triangular transformation to obtain the first network topology.

[0041] For example, the following case illustrates the process of converting the angled structure in the original network topology into a star structure using star-angle transformation: like Figure 2 As shown, this illustrates the process of transforming a triangle (Δ) connected impedance network into an equivalent star (Y) connected impedance network, known as the star-angle transformation. The impedance of each star branch is equal to the product of the impedances of the two sides adjacent to its vertex in the triangle, divided by the sum of all three impedances of the triangle. S2. Based on the first network topology and each device, the first impedance network framework of the energy storage power station is obtained by using a hierarchical calculation method. In some embodiments of this application, the step of obtaining the first impedance network framework of the energy storage power station using a hierarchical calculation method based on the first network topology and the devices specifically includes: Extract all nodes from the first network topology and form a node set; The devices are sequentially divided into hierarchical levels based on the node set, and the first impedance network framework is obtained based on all the divided devices and the node set.

[0042] In some embodiments of this application, the node set includes a grid connection point, several main transformer nodes, several collection line nodes, and several generator unit nodes. The step of hierarchically dividing the devices according to the node set and obtaining the first impedance network framework based on all the divided devices and the node set specifically involves: The devices are hierarchically divided according to the node set to obtain the devices corresponding to each level; wherein, the devices between the grid connection point and each main transformer node are divided into the first level, the devices between each main transformer node and each collection line node are divided into the second level, the devices between each collection line node and each generator node are divided into the third level, and the devices after each generator node are divided into the fourth level. The devices and node sets corresponding to each level are connected according to the first network topology to obtain the first impedance network framework.

[0043] For example, the construction process of the first impedance network framework is described below: like Figure 3 The diagram illustrates the construction process of the first impedance network framework. It extends from the grid connection point, constructing hierarchically with series connections between levels and parallel connections within the same level. The impedance network framework is constructed hierarchically according to the order of grid connection point, main transformer node, collection line node, and unit node. If a delta structure exists at any level, it is transformed into a star structure according to the star-delta transformation principle.

[0044] For example, to illustrate the structure of the first impedance network framework, such asFigure 4 The diagram shown is a schematic of the first impedance network framework, which includes the impedance of the energy storage converter equipment (ZG) and the transformer substation (ZG). G ), Line (Z) L ), main variable (Z) I-III ), submarine cable (Z) V ), high-voltage shunt reactor (Z) X ) and grid-connected substation lines (Z L0 The energy storage converter device in the first impedance network framework is a grid-type energy storage converter device.

[0045] S3. Based on the first impedance network framework and the impedance information corresponding to each device, the impedance network aggregation method is used to calculate the impedance characteristics of the energy storage power station at each frequency point in sequence, and the impedance characteristics of all frequency points are combined to form the full-frequency domain impedance characteristics of the energy storage power station. In some embodiments of this application, the step of calculating the impedance characteristics of the energy storage power station at each frequency point sequentially using an impedance network aggregation method based on the first impedance network framework and the impedance information corresponding to each device, and then combining the impedance characteristics of all frequency points to form the full-frequency domain impedance characteristics of the energy storage power station, specifically involves: The impedance characteristics of each device under the same unit node at the same frequency point are processed by series and parallel connection to obtain the impedance of each first branch network. The impedance of each first branch network is then connected in series with the corresponding third-level device to obtain the impedance of each second branch network. The second branch network impedances under the same aggregation line node in each second branch network impedance are connected in parallel to obtain the equivalent impedance of each first aggregation line node, and the equivalent impedance of each first aggregation line node is connected in series with the corresponding second-level device to obtain the equivalent impedance of each second aggregation line node. The equivalent impedances of each second collection line node under the same main transformer node are connected in parallel to obtain the equivalent impedance of each first main transformer node. The equivalent impedances of each first main transformer node are then connected in series with the corresponding first-level equipment to obtain the equivalent impedance of each second main transformer node. The equivalent impedances of each of the second main transformer nodes are connected in parallel to obtain the first impedance characteristic. The first impedance characteristic is then connected in series with the preset line impedance of the grid-connected substation to obtain the impedance characteristic of the energy storage power station at that frequency point. The impedance characteristics generated at all frequency points are combined to form the full-frequency domain impedance characteristic of the energy storage power station.

[0046] For example, the following scheme illustrates the process of calculating the impedance characteristics of the energy storage power station at each frequency point using the impedance network aggregation method: like Figure 5The diagram shows the calculation process for the impedance characteristics at any given frequency. The specific process is as follows: ① The structure of any branch network can be adjusted. Taking branch network 1 as an example, the slave end impedance is the single-machine impedance Z. G Initially, the series box changes to Z. T Line Z L The equivalent impedance forms branch elements, and multiple branch elements connected in parallel form branch network 1, with an equivalent impedance of Z. 1∑ (That is, the impedance of the first branch network), and the other branch networks are similar; ② The branch network is connected in parallel and then connected to the main transformer. After being connected in series and parallel with the main transformer impedances ZⅠ, ZⅡ, and ZⅢ, it forms the main transformer branch with an equivalent impedance of Z. Ⅰ-Ⅱ-Ⅲ∑ (That is, the equivalent impedance of each first main transformer node); ③ Combine and connect the main transformer branches in parallel, and then connect other components in series and parallel to obtain the equivalent impedance Z. V∑ (That is, the first impedance characteristic); ④ Finally, the line impedance ZL0 of the grid-connected substation is used to obtain the final total impedance, which is the equivalent impedance Z at the grid connection point of the hybrid energy storage power station. ∑ (That is, the impedance characteristics of the energy storage power station at this frequency point).

[0047] S4. Obtain the actual impedance data of the energy storage power station, and monitor the oscillation risk of the energy storage power station based on the full-frequency impedance characteristics of the energy storage power station and the actual impedance data.

[0048] In some optional embodiments of this application, the monitoring of the oscillation risk of the energy storage power station based on the full-frequency impedance characteristics of the energy storage power station and the actual impedance data specifically includes: After obtaining the full-frequency impedance characteristics of the energy storage power station, the actual impedance data of the power grid (generally a resistive-inductive system) is combined with methods such as Nyquist stability to monitor whether the energy storage power station has an oscillation risk.

[0049] In summary, this application, by acquiring the impedance characteristics of each device in the energy storage power station at different frequency points and fully understanding the first network topology of the power station, provides a comprehensive data foundation for subsequent impedance network calculations. Based on this, this application employs a hierarchical calculation method to construct the first impedance network framework. Within this framework, each device is divided into different levels, connected by specific nodes. This not only fully considers the hierarchical structure and complex relationships of the devices in the energy storage power station but also provides a clear computational logic for subsequent impedance characteristic calculations. Subsequently, based on this impedance network framework and the impedance information of each device, the impedance network aggregation method is used to sequentially calculate the impedance characteristics of the power station at each frequency point and form a full-frequency domain impedance characteristic. This comprehensively covers all frequency ranges that the system may involve, avoiding the omission of potential oscillation risk factors due to missing frequency points, thus forming a complete characterization of the overall impedance characteristics of the power station. Furthermore, this processing method eliminates the need to construct a detailed model of the energy storage power station, saving computational resources. Finally, the oscillation risk of the energy storage power station is monitored by combining the actual impedance data of the energy storage power station. Therefore, this application can solve the problem in the prior art that it is difficult to accurately monitor the oscillation risk of energy storage power stations while ensuring computational efficiency.

[0050] Example 2 like Figure 6 As shown, based on the above method embodiments, corresponding device embodiments are provided; An embodiment of the present invention provides an oscillation risk monitoring device for an energy storage power station based on impedance network aggregation, comprising: a data acquisition module 61, a first calculation module 62, a second calculation module 63, and a result output module 64; the data acquisition module 61 is used to acquire impedance information corresponding to each device in the energy storage power station and a first network topology of the energy storage power station; wherein, the impedance information corresponding to any device includes the impedance characteristics of the device at each frequency point; the first calculation module 62 is used to obtain a first impedance network framework of the energy storage power station using a hierarchical calculation method based on the first network topology and each device; the second calculation module 63 is used to calculate the impedance characteristics of the energy storage power station at each frequency point sequentially using an impedance network aggregation method based on the first impedance network framework and the impedance information corresponding to each device, and to form the full-frequency domain impedance characteristics of the energy storage power station; the result output module 64 is used to acquire the actual impedance data of the energy storage power station, and to monitor the oscillation risk of the energy storage power station based on the full-frequency domain impedance characteristics of the energy storage power station and the actual impedance data.

[0051] In some embodiments of this application, the energy storage power station includes several energy storage converter devices and several auxiliary devices, and the data acquisition module 61 includes a first acquisition unit and a second acquisition unit; The first acquisition unit is used to acquire, for any energy storage converter device, the voltage time-domain signal and the current time-domain signal of the energy storage converter device, and obtain the impedance information corresponding to the energy storage converter device based on the voltage time-domain signal and the current time-domain signal; wherein, the voltage time-domain signal and the current time-domain signal are obtained by injecting positive and negative sequence disturbance signals within a preset frequency range into the grid connection point of the energy storage converter using a voltage disturbance method; the second acquisition unit is used to acquire, for any auxiliary device, the impedance information corresponding to the auxiliary device using an electromagnetic equivalent reduction method based on the first network topology.

[0052] In some embodiments of this application, the first calculation module 62 includes a first calculation unit and a second calculation unit; the first calculation unit is used to extract all nodes in the first network topology and form a node set; the second calculation unit is used to perform hierarchical division of each device according to the node set, and obtain the first impedance network framework according to all the divided devices and the node set.

[0053] In some embodiments of this application, the node set includes a grid connection point, several main transformer nodes, several collection line nodes, and several generator nodes. The second calculation unit includes a first calculation subunit and a second calculation subunit. The first calculation subunit is used to sequentially divide the devices into hierarchical levels according to the node set to obtain the devices corresponding to each level. Specifically, the devices between the grid connection point and each main transformer node are divided into the first level, the devices between each main transformer node and each collection line node are divided into the second level, the devices between each collection line node and each generator node are divided into the third level, and the devices after each generator node are divided into the fourth level. The second calculation subunit is used to connect the devices corresponding to each level and the node set according to the first network topology to obtain the first impedance network framework.

[0054] In some embodiments of this application, the second calculation module 63 includes a third calculation unit, a fourth calculation unit, a fifth calculation unit, and a sixth calculation unit. The third calculation unit is used to perform series-parallel processing on the impedance characteristics of each device under the same unit node at the same frequency point to obtain the impedance of each first branch network, and then connects the impedances of each first branch network in series with the corresponding third-level devices to obtain the impedances of each second branch network. The fourth calculation unit is used to perform parallel processing on the impedances of each second branch network under the same collecting line node to obtain the equivalent impedance of each first collecting line node, and then connect the equivalent impedances of each first collecting line node in series with the corresponding second-level devices. The equipment obtains the equivalent impedance of each second collection line node; the fifth calculation unit is used to connect the equivalent impedances of each second collection line node under the same main transformer node in parallel to obtain the equivalent impedance of each first main transformer node, and connect the equivalent impedances of each first main transformer node in series with the corresponding first-level equipment to obtain the equivalent impedance of each second main transformer node; the sixth calculation unit is used to connect the equivalent impedances of each second main transformer node in parallel to obtain the first impedance characteristic, and connect the first impedance characteristic in series with the preset grid-connected substation line impedance to obtain the impedance characteristic of the energy storage power station at that frequency point, and combine the impedance characteristics generated at all frequency points to form the full-frequency domain impedance characteristic of the energy storage power station.

[0055] In some embodiments of this application, the data acquisition module 61 further includes a third acquisition unit; The third acquisition unit is used to acquire the original network topology of the energy storage power station. If there is a triangular structure in the original network topology, the triangular structure in the original network topology is converted into a star structure through star-triangular transformation to obtain the first network topology.

[0056] For more detailed steps and working principles of this embodiment, please refer to the relevant description in Embodiment 1, but not limited to these descriptions.

[0057] In summary, compared with existing technologies, the above embodiments have the following beneficial effects: By acquiring the impedance characteristics of each device in the energy storage power station at different frequency points and fully understanding the first network topology of the power station, the embodiments of this application can provide a comprehensive data foundation for subsequent impedance network calculations. Based on this, this application employs a hierarchical calculation method to construct the first impedance network framework. In this framework, each device is divided into different levels, and each level is connected by specific nodes. This not only fully considers the hierarchical structure and complex relationships of each device in the energy storage power station but also provides a clear calculation logic for subsequent impedance characteristic calculations. Subsequently, based on this impedance network framework and the impedance information of each device, the impedance network aggregation method is used to sequentially calculate the impedance characteristics of the power station at each frequency point and form a full-frequency domain impedance characteristic. This comprehensively covers all frequency ranges that the system may involve, avoiding the omission of potential oscillation risk factors due to missing frequency points, thus forming a complete characterization of the overall impedance characteristics of the power station. Furthermore, this processing method eliminates the need to construct a detailed model of the energy storage power station, saving computational resources. Finally, the oscillation risk of the energy storage power station is monitored by combining the actual impedance data of the energy storage power station. Therefore, this application can solve the problem in the prior art that it is difficult to accurately monitor the oscillation risk of energy storage power stations while ensuring computational efficiency.

[0058] It is understood that the above-described device embodiments correspond to the method embodiments of the present invention, and can realize the oscillation risk monitoring method for energy storage power stations based on impedance network aggregation provided by any of the above-described method embodiments of the present invention.

[0059] It should be noted that the device embodiments described above are merely illustrative, and some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Furthermore, in the accompanying drawings of the device embodiments provided by this invention, the connection relationships between modules indicate that they have communication connections, which can specifically be implemented as one or more communication buses or signal lines. Those skilled in the art can understand and implement this without any creative effort.

[0060] Example 3 Based on the above embodiments of the energy storage power station oscillation risk monitoring method based on impedance network aggregation, another embodiment of the present invention provides a terminal device, which includes a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor. When the processor executes the computer program, it implements the energy storage power station oscillation risk monitoring method based on impedance network aggregation of any embodiment of the present invention.

[0061] For example, in this embodiment, the computer program can be divided into one or more modules, which are stored in the memory and executed by the processor to complete the present invention. The one or more modules may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in the terminal device.

[0062] The terminal device may be a desktop computer, laptop, handheld computer, or cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0063] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the terminal device, connecting all parts of the terminal device via various interfaces and lines.

[0064] Example 4 Based on the above-described method embodiments, another embodiment of the present invention provides a computer-readable storage medium including a stored computer program, wherein, when the computer program is executed, it controls the device where the computer-readable storage medium is located to execute the oscillation risk monitoring method for energy storage power stations based on impedance network aggregation as described in any of the above-described method embodiments of the present invention.

[0065] The modules / units integrated in the device / terminal equipment, if implemented as software functional units and sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium, etc.

[0066] The above description is a preferred embodiment of the present invention. It should be noted that, for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications are also considered to be within the scope of protection of the present invention.

Claims

1. A method for monitoring oscillation risk in energy storage power stations based on impedance network aggregation, characterized in that, include: Obtain the impedance information of each device in the energy storage power station and the first network topology of the energy storage power station; wherein, the impedance information of any device includes the impedance characteristics of the device at each frequency point; Based on the first network topology and each device, the first impedance network framework of the energy storage power station is obtained by using a hierarchical calculation method. Based on the first impedance network framework and the impedance information corresponding to each device, the impedance network aggregation method is used to calculate the impedance characteristics of the energy storage power station at each frequency point in sequence, and the impedance characteristics of all frequency points are combined to form the full-frequency domain impedance characteristics of the energy storage power station. The actual impedance data of the energy storage power station is obtained, and the oscillation risk of the energy storage power station is monitored based on the full-frequency impedance characteristics of the energy storage power station and the actual impedance data.

2. The method for monitoring oscillation risk in energy storage power stations based on impedance network aggregation as described in claim 1, characterized in that, The energy storage power station includes several energy storage converter devices and several auxiliary devices. The acquisition of impedance information for each device in the energy storage power station specifically involves: For any energy storage converter device, the voltage time-domain signal and current time-domain signal of the energy storage converter device are acquired, and the impedance information corresponding to the energy storage converter device is obtained based on the voltage time-domain signal and the current time-domain signal; wherein, the voltage time-domain signal and the current time-domain signal are obtained by injecting positive and negative sequence disturbance signals within a preset frequency range into the grid connection point of the energy storage converter through the voltage disturbance method; For any auxiliary device, the impedance information corresponding to the auxiliary device is obtained by using the electromagnetic equivalent reduction method according to the first network topology.

3. The method for monitoring oscillation risk in energy storage power stations based on impedance network aggregation as described in claim 1, characterized in that, The first impedance network framework of the energy storage power station is obtained by using a hierarchical calculation method based on the first network topology and each device, specifically as follows: Extract all nodes from the first network topology and form a node set; The devices are sequentially divided into hierarchical levels based on the node set, and the first impedance network framework is obtained based on all the divided devices and the node set.

4. The method for monitoring oscillation risk in energy storage power stations based on impedance network aggregation as described in claim 3, characterized in that, The node set includes grid connection points, several main transformer nodes, several collection line nodes, and several generator unit nodes. The process involves hierarchically dividing the equipment according to the node set, and obtaining the first impedance network framework based on all the divided equipment and the node set, specifically as follows: The devices are hierarchically divided according to the node set to obtain the devices corresponding to each level; wherein, the devices between the grid connection point and each main transformer node are divided into the first level, the devices between each main transformer node and each collection line node are divided into the second level, the devices between each collection line node and each generator node are divided into the third level, and the devices after each generator node are divided into the fourth level. The devices and node sets corresponding to each level are connected according to the first network topology to obtain the first impedance network framework.

5. The method for monitoring oscillation risk in energy storage power stations based on impedance network aggregation as described in claim 4, characterized in that, Based on the first impedance network framework and the impedance information corresponding to each device, the impedance network aggregation method is used to sequentially calculate the impedance characteristics of the energy storage power station at each frequency point, and the impedance characteristics of all frequency points are combined to form the full-frequency domain impedance characteristics of the energy storage power station. Specifically: The impedance characteristics of each device under the same unit node at the same frequency point are processed by series and parallel connection to obtain the impedance of each first branch network. The impedance of each first branch network is then connected in series with the corresponding third-level device to obtain the impedance of each second branch network. The second branch network impedances under the same aggregation line node in each second branch network impedance are connected in parallel to obtain the equivalent impedance of each first aggregation line node, and the equivalent impedance of each first aggregation line node is connected in series with the corresponding second-level device to obtain the equivalent impedance of each second aggregation line node. The equivalent impedances of each second collection line node under the same main transformer node are connected in parallel to obtain the equivalent impedance of each first main transformer node. The equivalent impedances of each first main transformer node are then connected in series with the corresponding first-level equipment to obtain the equivalent impedance of each second main transformer node. The equivalent impedances of each of the second main transformer nodes are connected in parallel to obtain the first impedance characteristic. The first impedance characteristic is then connected in series with the preset line impedance of the grid-connected substation to obtain the impedance characteristic of the energy storage power station at that frequency point. The impedance characteristics generated at all frequency points are combined to form the full-frequency domain impedance characteristic of the energy storage power station.

6. The method for monitoring oscillation risk in energy storage power stations based on impedance network aggregation as described in claim 1, characterized in that, The specific steps for obtaining the impedance information corresponding to each device in the energy storage power station and the first network topology of the energy storage power station are as follows: Obtain the original network topology of the energy storage power station. If there is a triangular structure in the original network topology, convert the triangular structure in the original network topology into a star structure through star-triangular transformation to obtain the first network topology.

7. A device for monitoring the oscillation risk of an energy storage power station based on impedance network aggregation, characterized in that, include: The system comprises a data acquisition module, a first calculation module, a second calculation module, and a result output module. The data acquisition module is used to acquire the impedance information of each device in the energy storage power station and the first network topology of the energy storage power station; wherein, the impedance information of any device includes the impedance characteristics of the device at each frequency point. The first calculation module is used to obtain the first impedance network framework of the energy storage power station by using a hierarchical calculation method based on the first network topology and each device. The second calculation module is used to calculate the impedance characteristics of the energy storage power station at each frequency point in sequence using the impedance network aggregation method based on the first impedance network framework and the impedance information corresponding to each device, and to combine the impedance characteristics of all frequency points into the full-frequency domain impedance characteristics of the energy storage power station. The result output module is used to acquire the actual impedance data of the energy storage power station, and to monitor the oscillation risk of the energy storage power station based on the full-frequency impedance characteristics of the energy storage power station and the actual impedance data.

8. The energy storage power station oscillation risk monitoring device based on impedance network aggregation as described in claim 7, characterized in that, The energy storage power station includes several energy storage converter devices and several auxiliary devices, and the data acquisition module includes a first acquisition unit and a second acquisition unit; The first acquisition unit is used to acquire, for any energy storage converter device, the voltage time-domain signal and the current time-domain signal of the energy storage converter device, and obtain the impedance information corresponding to the energy storage converter device based on the voltage time-domain signal and the current time-domain signal; wherein, the voltage time-domain signal and the current time-domain signal are obtained by injecting positive and negative sequence disturbance signals within a preset frequency range into the grid connection point of the energy storage converter through a voltage disturbance method; The second acquisition unit is used to obtain the impedance information of any auxiliary device by using an electromagnetic equivalent reduction method based on the first network topology.

9. The energy storage power station oscillation risk monitoring device based on impedance network aggregation as described in claim 7, characterized in that, The first computing module includes a first computing unit and a second computing unit; The first computing unit is used to extract all nodes in the first network topology and form a node set; The second calculation unit performs hierarchical division of each device according to the node set, and obtains the first impedance network framework based on all the divided devices and the node set.

10. The energy storage power station oscillation risk monitoring device based on impedance network aggregation as described in claim 9, characterized in that, The node set includes grid connection points, several main transformer nodes, several collection line nodes, and several generator unit nodes; the second calculation unit includes a first calculation subunit and a second calculation subunit. The first calculation subunit is used to divide the devices into hierarchical levels according to the node set to obtain the devices corresponding to each level; wherein, the devices between the grid connection point and each main transformer node are divided into the first level, the devices between each main transformer node and each collection line node are divided into the second level, the devices between each collection line node and each generator node are divided into the third level, and the devices after each generator node are divided into the fourth level. The second calculation subunit is used to connect the devices and node sets corresponding to each level according to the first network topology to obtain the first impedance network framework.

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