A method and system for evaluating the support capability of a network-constructed energy storage

Abstract

The application discloses a kind of network construction type energy storage's support ability evaluation method and system, belong to network construction type energy storage evaluation technical field.The application obtains the virtual impedance control parameter and virtual synchronous machine control parameter of network construction type energy storage, and constructs virtual impedance model and virtual inertia model in combination with node operation data;Then, with virtual impedance model and node operation data network construction type energy storage's voltage stability index;With virtual inertia model and node operation data determine the frequency dynamic equation of power system;Based on the frequency dynamic equation determines the frequency response energy index and frequency change rate index of network construction type energy storage;Finally, voltage stability index, frequency response energy index and frequency change rate index are analyzed, and the support ability evaluation result of network construction type energy storage is obtained, improve the accuracy of network construction type energy storage support ability evaluation.

Description

Technical Field

[0001] This invention belongs to the field of grid-type energy storage assessment technology, and particularly relates to a method and system for assessing the support capacity of grid-type energy storage. Background Technology

[0002] With the continuous expansion of new energy grid connection in the power system, problems such as declining system inertia and weakened voltage support capacity are becoming increasingly prominent. Grid-based energy storage devices, due to their ability to actively construct voltage and frequency, can provide effective inertia, frequency, and voltage support for weak power grids, and have become key technological equipment for improving the stability of high-proportion new energy power systems. However, the stability support capability of grid-based energy storage devices is affected by multiple factors such as their control parameters, connection location, and capacity configuration. Therefore, evaluating the support capability of grid-based energy storage can better ensure the stable and sustainable operation of the power system.

[0003] Currently, most assessments of the support capabilities of grid-based energy storage are conducted within the framework of the power system. For example, they assess the voltage and frequency data of the power system to determine the support capacity of grid-based energy storage. However, this approach ignores the unique virtual impedance and virtual inertia characteristics of grid-based energy storage, making it difficult to accurately reflect its actual support capabilities for the power system. Furthermore, most current assessment methods rely on a single dimension, which further reduces the accuracy of the assessment of the support capabilities of grid-based energy storage under actual power system operating conditions. Summary of the Invention

[0004] The present invention aims to provide a method and system for assessing the support capacity of grid-type energy storage, so as to solve the above-mentioned technical problems and improve the accuracy of assessing the support capacity of grid-type energy storage.

[0005] To address the aforementioned technical problems, embodiments of the present invention provide a method for assessing the support capacity of grid-type energy storage, comprising: Acquire node operation data in the power system and connect the grid-type energy storage to be evaluated into the power system; Obtain the virtual impedance control parameters and virtual synchronous machine control parameters of the grid-type energy storage, and construct a virtual impedance model and a virtual inertial model based on the virtual impedance control parameters, virtual synchronous machine control parameters and node operation data; Based on the virtual impedance model and node operation data, the node mutual impedance data of the power system are determined, and the voltage stability index of the grid-type energy storage is determined based on the node mutual impedance data. The frequency dynamic equation of the power system is determined based on the virtual inertial model and node operation data; the frequency response energy index and frequency change rate index of the grid-type energy storage are determined based on the frequency dynamic equation. The voltage stability index, frequency response energy index, and frequency change rate index are analyzed to obtain the evaluation results of the support capacity of the grid-type energy storage.

[0006] Understandably, compared to existing technologies, this invention obtains the virtual impedance control parameters and virtual synchronous machine control parameters of grid-connected energy storage, and constructs virtual impedance models and virtual inertia models respectively by combining node operation data. The virtual impedance model reflects the active voltage support characteristics of grid-connected energy storage, while the virtual inertia model accurately simulates the inertial response behavior of grid-connected energy storage under frequency disturbances. Next, the node mutual impedance data of the power system is determined using the virtual impedance model and node operation data, and the voltage stability index of the grid-connected energy storage is determined based on the node mutual impedance data. The frequency dynamic equation of the power system is determined using the virtual inertia model and node operation data. Based on the frequency dynamic equation, the frequency response energy index and frequency change rate index of the grid-connected energy storage are determined. Finally, the voltage stability index, frequency response energy index, and frequency change rate index are analyzed, and the support capability assessment result of the grid-connected energy storage is obtained through multi-dimensional evaluation, significantly improving the accuracy of the support capability assessment of grid-connected energy storage.

[0007] As a preferred embodiment, the step of obtaining the virtual impedance control parameters and virtual synchronous machine control parameters of the grid-type energy storage, and constructing a virtual impedance model and a virtual inertial model based on the virtual impedance control parameters, virtual synchronous machine control parameters, and node operation data includes: The virtual impedance control parameters and virtual synchronous machine control parameters of the grid-type energy storage are obtained, wherein the virtual impedance control parameters include: grid-type converter potential, grid-type converter access voltage and grid-type converter current; The potential difference of the grid converter is determined based on the grid converter potential and the grid converter input voltage; A virtual impedance model is constructed based on the ratio of the potential difference of the grid converter to the current of the grid converter; Based on the control parameters of the virtual synchronous machine and the node operation data, the rotor motion equation and electromagnetic equation are constructed, and a virtual inertial model is constructed based on the rotor motion equation and electromagnetic equation.

[0008] The above scheme utilizes the potential, input voltage, and current of the grid-connected converter as virtual impedance control parameters. A virtual impedance model is constructed by calculating the ratio of the potential difference to the current of the grid-connected converter. This virtual impedance model accurately describes the output impedance characteristics of the grid-connected energy storage, avoiding model distortion caused by using fixed impedance values. This allows for accurate reflection of the active voltage support characteristics of the grid-connected energy storage. Simultaneously, based on the virtual synchronous machine control parameters and operating data, rotor motion equations and electromagnetic equations are constructed to form a virtual inertial model. This virtual inertial model synchronously reflects the electromechanical transient processes and electromagnetic transient characteristics of the grid-connected energy storage, accurately simulating the inertial response behavior of the grid-connected energy storage under frequency disturbances. This improves the accuracy of subsequent assessments of the grid-connected energy storage's support capabilities.

[0009] As a preferred embodiment, the virtual synchronous machine control parameters include: virtual inertia coefficient, virtual damping coefficient, virtual mechanical power, and grid interaction power; the node operation data includes: real-time frequency, phase angle transformation rate, frequency change rate, and rated frequency of the grid-connected energy storage node; the construction of rotor motion equations and electromagnetic equations based on the virtual synchronous machine control parameters and node operation data, and the construction of a virtual inertial model based on the rotor motion equations and electromagnetic equations, includes: Electromagnetic equations are constructed based on the real-time frequency and phase angle transformation rate of the network-type energy storage access node. The virtual inertial torque is determined based on the virtual inertial coefficient and the frequency change rate of the grid-type energy storage access node; The frequency change value of the grid-type energy storage access node is determined based on the real-time frequency and the rated frequency of the grid-type energy storage access node. The virtual damping torque is determined based on the frequency variation value of the grid-type energy storage access node and the virtual damping coefficient. The virtual acceleration power is determined based on the virtual mechanical power, the power grid interaction power, and the virtual damping torque. The rotor motion equations are constructed based on the virtual inertial torque and virtual acceleration power. A virtual inertial model is constructed based on the rotor motion equations and electromagnetic equations.

[0010] The above scheme introduces virtual inertia coefficient, virtual damping coefficient, virtual mechanical power, and grid interaction power when constructing the virtual inertial model. It combines the real-time frequency, phase angle change rate, frequency change rate, and rated frequency of the grid-connected energy storage nodes to sequentially determine the virtual inertial torque, frequency change value, virtual damping torque, and virtual acceleration power. Finally, it constructs the rotor motion equation and electromagnetic equation. Through hierarchical parameter transformation, the virtual inertial torque characterizes the physical effect of grid-connected energy storage resisting frequency changes, and the virtual damping torque reflects the ability of grid-connected energy storage to suppress frequency oscillations. This completely maps the virtual synchronous machine control of grid-connected energy storage into a computable mathematical model, enabling the virtual inertial model to accurately simulate the rotor dynamic characteristics of a synchronous generator. Consequently, the frequency response energy index and frequency change rate index calculated based on the virtual inertial model can truly reflect the actual response capability of grid-connected energy storage under different frequency disturbance scenarios, thereby improving the accuracy of subsequent assessments of the support capability of grid-connected energy storage.

[0011] As a preferred embodiment, the node operation data includes: the impedance value between any two power nodes, the impedance value between any power node and a grid-connected energy storage node, the self-impedance value of the grid-connected energy storage node, the node capacity of the power nodes and the base value of the AC grid capacity, and the reactance value between the grid-connected energy storage and the grid-connected energy storage node; the step of determining the node mutual impedance data of the power system based on the virtual impedance model and the operation data, and determining the voltage stability index of the grid-connected energy storage based on the node mutual impedance data, includes: The virtual impedance value of the grid-type energy storage is determined based on the virtual impedance model. The total equivalent impedance of the grid-type energy storage access node is determined based on the virtual impedance value, the self-impedance value, and the reactance value of the grid-type energy storage access node. The coupling impedance between any two power nodes is determined based on the impedance value between any power node and the grid-type energy storage access node. The impedance correction term between any two power nodes is determined based on the ratio of the coupling impedance value between any two power nodes to the total equivalent impedance of the grid-type energy storage access node. The impedance value between any two power nodes is corrected based on the impedance correction term between any two power nodes to obtain the corrected impedance value between any two power nodes. The voltage stability index of the grid-type energy storage is determined based on the corrected impedance value between any two power nodes, the node capacity of the power nodes, and the base value of the AC grid capacity.

[0012] The above scheme, when determining voltage stability indicators, first outputs virtual impedance values ​​based on the virtual impedance model. Then, based on the virtual impedance values, the self-impedance values, and reactance values ​​of the grid-type energy storage access nodes, it obtains the total equivalent impedance of the grid-type energy storage access nodes. Next, it uses the impedance values ​​between each power node and the grid-type energy storage access node, combined with the impedance values ​​between any two power nodes, to determine the coupling impedance value. Then, it calculates the ratio of the coupling impedance value to the total equivalent impedance as an impedance correction term, and uses this impedance correction term to obtain the corrected impedance value. By using the total equivalent impedance and the coupling impedance between nodes, it quantitatively characterizes the reshaping effect of the virtual impedance introduced by grid-type energy storage on the impedance distribution of the power system. This allows the voltage stability indicators to accurately reflect the actual voltage support effect of grid-type energy storage, thereby improving the accuracy of subsequent assessments of the support capacity of grid-type energy storage.

[0013] As a preferred embodiment, the step of determining the frequency dynamic equation of the power system based on the virtual inertial model and node operation data; and determining the frequency response energy index and frequency change rate index of the grid-type energy storage based on the frequency dynamic equation, includes: The virtual inertia matrix and virtual damping matrix of the power system are determined based on the virtual inertia model. Based on the virtual inertia matrix, virtual damping matrix, and pre-acquired node admittance matrix of the power system, the frequency dynamic equation of the power system is constructed by combining the phase angle transformation rate and frequency change rate of the grid-type energy storage access node. An evaluation equation is constructed based on the virtual inertia matrix of the power system; Solving the frequency dynamic equation and the evaluation equation yields the frequency response energy index of the grid-type energy storage. The virtual inertia time constant of the grid-type energy storage is constructed based on the virtual inertia matrix of the power system, and the total inertia time constant of the power system is determined based on the virtual inertia time constant and the pre-acquired inertia time constant of the power equipment. The power change rate of the power system is obtained, and the frequency change rate of the power system is determined based on the power change rate, the AC grid capacity base value and the total inertial time constant. The frequency change rate of the power system is used as the frequency change rate index of the grid-type energy storage.

[0014] The above scheme, when determining the frequency response energy index, constructs frequency dynamic equations and evaluation equations based on the power system virtual inertia matrix and virtual damping matrix output by the virtual inertia model, combined with the pre-acquired nodal admittance matrix, and obtains the frequency response energy index by solving them. When determining the frequency change rate index, the power system virtual inertia matrix is ​​converted into a virtual inertia time constant, and then combined with the inertia time constants of the power equipment to obtain the total system inertia time constant. Finally, the frequency change rate index is determined by combining the power change rate. This dual index system characterizes frequency stability from different dimensions: the frequency response energy index is determined by combining the frequency dynamic equations and evaluation equations. The joint solution of the equations can quantify the output energy response of grid-type energy storage under white noise or small disturbance excitation, thus reflecting the ability of grid-type energy storage to suppress random disturbances. The frequency change rate index focuses on the inertial response at the moment of high power disturbance. Through the calculation relationship between the total inertial time constant and the power change rate, it directly reflects the buffering effect of grid-type energy storage on the frequency drop rate. It not only captures the frequency stability margin of grid-type energy storage under small disturbance scenarios, but also evaluates its inertial support strength under severe disturbances, thereby comprehensively improving the accuracy of frequency and inertial support capability assessment, and thus improving the accuracy of subsequent grid-type energy storage support capability assessment.

[0015] As a preferred embodiment, the analysis of the voltage stability index, frequency response energy index, and frequency change rate index to obtain the evaluation results of the support capability of the grid-type energy storage includes: The voltage stability index, frequency response energy index, and frequency change rate index are normalized respectively to obtain normalized voltage stability index, normalized frequency response energy index, and normalized frequency change rate index. An index layer is constructed based on the normalized voltage stability index, the normalized frequency response energy index, and the normalized frequency change rate index. The preset stability support capability is used as the target layer, and the preset voltage support capability, preset frequency support capability, and preset inertia support capability are used as the criteria layer. Construct a first judgment matrix of the criterion layer relative to the target layer, and construct several second judgment matrices of the indicator layer relative to the criterion layer; Consistency checks are performed on the first judgment matrix and the second judgment matrix respectively, so as to obtain the first weight vector corresponding to the first judgment matrix and the second weight vector corresponding to each of the second judgment matrices based on the consistency check results; Based on the normalized voltage stability index, normalized frequency response energy index, and normalized frequency change rate index, the voltage support capability assessment score, frequency support capability assessment score, and inertia support capability assessment score of the grid-type energy storage are determined by combining the second weight vector corresponding to each second judgment matrix. Based on the voltage support capability assessment score, frequency support capability assessment score, and inertia support capability assessment score, the support capability score of the grid-type energy storage is determined by combining the first weight vector, and the support capability score is used as the support capability assessment result of the grid-type energy storage.

[0016] The above scheme employs the Analytic Hierarchy Process (AHP) to comprehensively analyze voltage stability, frequency response energy, and frequency change rate indices. First, these indices are normalized to eliminate dimensional differences, and then an index layer is constructed. Next, stability support capability is used as the target layer, and preset voltage support capability, preset frequency support capability, and preset inertia support capability are used as the criteria layer. Based on this, a first and second judgment matrix are constructed, and after consistency verification, a first and second weight vector are obtained. Then, the voltage support capability assessment score, frequency support capability assessment score, and inertia support capability assessment score of the grid-type energy storage are calculated, ultimately yielding the support capability score. By constructing a three-layer evaluation architecture, the multi-dimensional support capability problem, which is difficult to comprehensively evaluate with a single index, is transformed into a hierarchical, multi-criteria decision-making problem. This avoids the shortcomings of traditional methods that can only evaluate from a single dimension or simply weight the data without reflecting physical meaning. The support capability evaluation results possess both the advantages of multi-dimensional comprehensiveness and the ability to adapt to different operating scenarios, thereby improving the accuracy of the grid-type energy storage support capability evaluation.

[0017] Accordingly, embodiments of the present invention provide a support capability assessment system for grid-type energy storage, including: a data acquisition module, a grid-type energy storage model construction module, a voltage stability index acquisition module, a frequency index acquisition module, and a support capability assessment module; The data acquisition module is used to acquire node operation data in the power system and to connect the grid-type energy storage to be evaluated into the power system. The grid-type energy storage model construction module is used to obtain the virtual impedance control parameters and virtual synchronous machine control parameters of the grid-type energy storage, and to construct a virtual impedance model and a virtual inertial model based on the virtual impedance control parameters, virtual synchronous machine control parameters and node operation data. The voltage stability index acquisition module is used to determine the node mutual impedance data of the power system based on the virtual impedance model and node operation data, and to determine the voltage stability index of the grid-type energy storage based on the node mutual impedance data. The frequency index acquisition module is used to determine the frequency dynamic equation of the power system based on the virtual inertial model and node operation data; and to determine the frequency response energy index and frequency change rate index of the grid-type energy storage based on the frequency dynamic equation. The support capability assessment module is used to analyze the voltage stability index, frequency response energy index, and frequency change rate index to obtain the support capability assessment results of the grid-type energy storage.

[0018] As a preferred embodiment, the grid-type energy storage model construction module includes: a grid-type energy storage model construction unit; The grid-type energy storage model construction unit is used to obtain the virtual impedance control parameters and virtual synchronous machine control parameters of the grid-type energy storage. The virtual impedance control parameters include: grid-type converter potential, grid-type converter access voltage, and grid-type converter current. The potential difference of the grid converter is determined based on the grid converter potential and the grid converter input voltage; A virtual impedance model is constructed based on the ratio of the potential difference of the grid converter to the current of the grid converter; Based on the control parameters of the virtual synchronous machine and the node operation data, the rotor motion equation and electromagnetic equation are constructed, and a virtual inertial model is constructed based on the rotor motion equation and electromagnetic equation.

[0019] As a preferred embodiment, the grid-type energy storage model construction unit includes: a virtual inertial model construction subunit; In the virtual inertial model construction subunit, the virtual synchronous machine control parameters include: virtual inertia coefficient, virtual damping coefficient, virtual mechanical power, and grid interaction power; the node operation data includes: real-time frequency, phase angle transformation rate, frequency change rate, and rated frequency of the grid-type energy storage access node. The virtual inertial model construction subunit is used to construct electromagnetic equations based on the real-time frequency and phase angle transformation rate of the grid-type energy storage access node; The virtual inertial torque is determined based on the virtual inertial coefficient and the frequency change rate of the grid-type energy storage access node; The frequency change value of the grid-type energy storage access node is determined based on the real-time frequency and the rated frequency of the grid-type energy storage access node. The virtual damping torque is determined based on the frequency variation value of the grid-type energy storage access node and the virtual damping coefficient. The virtual acceleration power is determined based on the virtual mechanical power, the power grid interaction power, and the virtual damping torque. The rotor motion equations are constructed based on the virtual inertial torque and virtual acceleration power. A virtual inertial model is constructed based on the rotor motion equations and electromagnetic equations.

[0020] As a preferred embodiment, the voltage stability index acquisition module includes: a voltage stability index acquisition unit; In the voltage stability index acquisition unit, the node operation data includes: the impedance value between any two power nodes, the impedance value between any power node and the grid-type energy storage access node, the self-impedance value of the grid-type energy storage access node, the node capacity of the power node and the AC grid capacity base value, and the reactance value between the grid-type energy storage and the grid-type energy storage access node. The voltage stability index acquisition unit is used to determine the virtual impedance value of the grid-type energy storage according to the virtual impedance model; The total equivalent impedance of the grid-type energy storage access node is determined based on the virtual impedance value, the self-impedance value, and the reactance value of the grid-type energy storage access node. The coupling impedance between any two power nodes is determined based on the impedance value between any power node and the grid-type energy storage access node. The impedance correction term between any two power nodes is determined based on the ratio of the coupling impedance value between any two power nodes to the total equivalent impedance of the grid-type energy storage access node. The impedance value between any two power nodes is corrected based on the impedance correction term between any two power nodes to obtain the corrected impedance value between any two power nodes. The voltage stability index of the grid-type energy storage is determined based on the corrected impedance value between any two power nodes, the node capacity of the power nodes, and the base value of the AC grid capacity.

[0021] Understandably, compared to existing technologies, this system acquires the virtual impedance control parameters and virtual synchronous machine control parameters of the grid-type energy storage, and constructs virtual impedance and virtual inertia models respectively by combining node operation data. The virtual impedance model reflects the active voltage support characteristics of the grid-type energy storage, while the virtual inertia model accurately simulates the inertial response behavior of the grid-type energy storage under frequency disturbances. Next, the system determines the node mutual impedance data of the power system using the virtual impedance model and node operation data, and determines the voltage stability index of the grid-type energy storage based on the node mutual impedance data. It then determines the frequency dynamic equation of the power system using the virtual inertia model and node operation data, and determines the frequency response energy index and frequency change rate index of the grid-type energy storage based on the frequency dynamic equation. Finally, the system analyzes the voltage stability index, frequency response energy index, and frequency change rate index, obtaining the support capability assessment result of the grid-type energy storage through multi-dimensional evaluation, significantly improving the accuracy of the grid-type energy storage support capability assessment. Attached Figure Description

[0022] Figure 1 A flowchart illustrating the steps of a method for assessing the support capacity of grid-type energy storage according to an embodiment of the present invention; Figure 2A schematic diagram of a power node in a power system provided as an embodiment of the present invention; Figure 3 This is a schematic diagram of a support capacity assessment system for grid-type energy storage provided in an embodiment of the present invention. Detailed Implementation

[0023] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0024] Example 1 Please refer to Figure 1 , Figure 1 The flowchart of a method for evaluating the support capacity of grid-type energy storage provided in an embodiment of the present invention includes steps S101 to S105.

[0025] Step S101: Obtain node operation data in the power system and connect the grid-type energy storage to be evaluated into the power system.

[0026] Step S102: Obtain the virtual impedance control parameters and virtual synchronous machine control parameters of the grid-type energy storage, and construct a virtual impedance model and a virtual inertial model based on the virtual impedance control parameters, virtual synchronous machine control parameters and node operation data.

[0027] Step S103: Determine the node mutual impedance data of the power system based on the virtual impedance model and node operation data, and determine the voltage stability index of the grid-type energy storage based on the node mutual impedance data.

[0028] Step S104: Determine the frequency dynamic equation of the power system based on the virtual inertial model and node operation data; determine the frequency response energy index and frequency change rate index of the grid-type energy storage based on the frequency dynamic equation.

[0029] Step S105: Analyze the voltage stability index, frequency response energy index, and frequency change rate index to obtain the evaluation results of the support capacity of the grid-type energy storage.

[0030] This embodiment acquires the virtual impedance control parameters and virtual synchronous machine control parameters of the grid-type energy storage, and constructs virtual impedance and virtual inertia models respectively by combining node operation data. The virtual impedance model reflects the active voltage support characteristics of the grid-type energy storage, while the virtual inertia model accurately simulates the inertial response behavior of the grid-type energy storage under frequency disturbances. Next, the node mutual impedance data of the power system is determined using the virtual impedance model and node operation data, and the voltage stability index of the grid-type energy storage is determined based on the node mutual impedance data. The frequency dynamic equation of the power system is determined using the virtual inertia model and node operation data. Based on the frequency dynamic equation, the frequency response energy index and frequency change rate index of the grid-type energy storage are determined. Finally, the voltage stability index, frequency response energy index, and frequency change rate index are analyzed to obtain the support capability assessment result of the grid-type energy storage through multi-dimensional evaluation, which significantly improves the accuracy of the support capability assessment of the grid-type energy storage.

[0031] In one optional embodiment, a number of power nodes are distributed in the power system. The grid-type energy storage being added to the power system refers to the grid-type energy storage being integrated into a certain power node, and at this time, the power node is marked as the grid-type energy storage access node.

[0032] In this embodiment, obtaining the virtual impedance control parameters and virtual synchronous machine control parameters of the grid-type energy storage, and constructing a virtual impedance model and a virtual inertial model based on the virtual impedance control parameters, virtual synchronous machine control parameters, and node operation data, includes: The virtual impedance control parameters and virtual synchronous machine control parameters of the grid-type energy storage are obtained, wherein the virtual impedance control parameters include: grid-type converter potential, grid-type converter access voltage and grid-type converter current; The potential difference of the grid converter is determined based on the grid converter potential and the grid converter input voltage; A virtual impedance model is constructed based on the ratio of the potential difference of the grid converter to the current of the grid converter; Based on the control parameters of the virtual synchronous machine and the node operation data, the rotor motion equation and electromagnetic equation are constructed, and a virtual inertial model is constructed based on the rotor motion equation and electromagnetic equation.

[0033] The above embodiments utilize the grid-connected converter potential, grid-connected converter voltage, and grid-connected converter current as virtual impedance control parameters. A virtual impedance model is constructed by calculating the ratio of the grid-connected converter potential difference to the grid-connected converter current. This virtual impedance model accurately describes the output impedance characteristics of the grid-connected energy storage, avoiding model distortion caused by using fixed impedance values. Furthermore, it accurately reflects the active voltage support characteristics of the grid-connected energy storage. Simultaneously, based on the virtual synchronous machine control parameters and operating data, rotor motion equations and electromagnetic equations are constructed to form a virtual inertial model. This virtual inertial model synchronously reflects the electromechanical transient processes and electromagnetic transient characteristics of the grid-connected energy storage, accurately simulating the inertial response behavior of the grid-connected energy storage under frequency disturbances, thereby improving the accuracy of subsequent assessments of the grid-connected energy storage support capabilities.

[0034] In one optional embodiment, virtual impedance is a power electronic control technology based on the impedance relationship between voltage and current. It simulates a regulation effect similar to actual impedance by embedding a corresponding algorithm in the control loop, without increasing additional system losses. In grid-connected energy storage, the grid-connected converter can exhibit voltage source characteristics, stabilizing node voltages by adjusting the virtual impedance. In this embodiment, the virtual impedance control parameters include: the grid-connected converter potential... Grid-type converter input voltage and grid-type converter current ; the potential of the grid-type converter Grid-type converter input voltage The difference is used as the potential difference value of the grid-type converter. Then, a virtual impedance model is constructed using the ratio of the potential difference of the grid-type converter to the current of the grid-type converter. The virtual impedance model is expressed as: ;in, This represents the virtual impedance value of grid-connected energy storage. Specifically, it represents the current of the grid-connected converter. The capacity of grid-connected energy storage is positively correlated with the capacity of grid-connected energy storage; therefore, the larger the capacity of grid-connected energy storage, the larger the current of the grid-connected converter. Thus, the integration of large-capacity grid-connected energy storage can provide virtual impedance to ground for the grid-connected energy storage nodes, thereby affecting the power system impedance matrix and enhancing the voltage stability of the power system.

[0035] In this embodiment, the virtual synchronous machine control parameters include: virtual inertia coefficient, virtual damping coefficient, virtual mechanical power, and grid interaction power; the node operation data includes: real-time frequency, phase angle transformation rate, frequency change rate, and rated frequency of the grid-connected energy storage node; the construction of rotor motion equations and electromagnetic equations based on the virtual synchronous machine control parameters and node operation data, and the construction of a virtual inertial model based on the rotor motion equations and electromagnetic equations, includes: Electromagnetic equations are constructed based on the real-time frequency and phase angle transformation rate of the network-type energy storage access node. The virtual inertial torque is determined based on the virtual inertial coefficient and the frequency change rate of the grid-type energy storage access node; The frequency change value of the grid-type energy storage access node is determined based on the real-time frequency and the rated frequency of the grid-type energy storage access node. The virtual damping torque is determined based on the frequency variation value of the grid-type energy storage access node and the virtual damping coefficient. The virtual acceleration power is determined based on the virtual mechanical power, the power grid interaction power, and the virtual damping torque. The rotor motion equations are constructed based on the virtual inertial torque and virtual acceleration power. A virtual inertial model is constructed based on the rotor motion equations and electromagnetic equations.

[0036] In one optional embodiment, virtual synchronous machine control involves embedding a mathematical model of a synchronous generator, particularly the rotor motion equations and electromagnetic equations, into the upper-level control algorithm of the grid-connected converter. This enables the grid-connected converter in the grid-connected energy storage system to exhibit inertial and damping characteristics similar to a traditional synchronous generator during grid-connected operation, thereby providing virtual inertial support for the power system. Therefore, this embodiment constructs a virtual inertial model to reflect the actual response capability of the grid-connected energy storage system under different frequency disturbance scenarios.

[0037] Among them, the virtual inertia coefficient is defined. Virtual damping coefficient Virtual mechanical power Power interaction with the power grid Power grid interaction This refers to the interaction power between grid-connected energy storage and the power system; subsequently, node operation data can be obtained by monitoring each node in the power system, including: the real-time frequency of the grid-connected energy storage access node. Phase angle transformation rate Rate of change of frequency and rated frequency ; Next, using the real-time frequency of the grid-type energy storage access node. and phase angle transformation rate Construct the electromagnetic equations, which are expressed as follows: ; Virtual inertia coefficient Frequency variation rate of grid-connected energy storage nodes The product of these is used as the virtual moment of inertia. Virtual inertial torque The physical effects of grid-based energy storage resisting frequency variations were characterized; the real-time frequency of the grid-based energy storage access node was used. and rated frequency The difference determines the frequency variation value of the grid-type energy storage access node. Next, the frequency variation value of the grid-type energy storage access node will be... and the virtual damping coefficient Multiplying them yields the virtual damping torque. The virtual damping torque reflects the ability of the grid-type energy storage to suppress frequency oscillations; finally, the virtual mechanical power... Subtract grid interaction power in sequence and virtual damping torque Determine virtual acceleration power The rotor motion equation is obtained by using the equation relating virtual inertial torque and virtual acceleration power; the rotor motion equation is expressed as: The rotor motion equations and electromagnetic equations together form a virtual inertial model. The larger the grid-type energy storage capacity, the greater the virtual inertia it can provide to the power system.

[0038] In constructing the virtual inertial model, the above embodiments introduce virtual inertia coefficients, virtual damping coefficients, virtual mechanical power, and grid interaction power. Combined with the real-time frequency, phase angle change rate, frequency change rate, and rated frequency of the grid-connected energy storage nodes, the virtual inertial torque, frequency change value, virtual damping torque, and virtual acceleration power are determined sequentially. Finally, the rotor motion equation and electromagnetic equation are constructed. Through hierarchical parameter transformation, the virtual inertial torque characterizes the physical effect of grid-connected energy storage resisting frequency changes, and the virtual damping torque reflects the ability of grid-connected energy storage to suppress frequency oscillations. This completely maps the virtual synchronous machine control of grid-connected energy storage into a computable mathematical model, enabling the virtual inertial model to accurately simulate the rotor dynamic characteristics of a synchronous generator. Consequently, the frequency response energy index and frequency change rate index calculated based on the virtual inertial model can truly reflect the actual response capability of grid-connected energy storage under different frequency disturbance scenarios, thereby improving the accuracy of subsequent assessments of the support capability of grid-connected energy storage.

[0039] In this embodiment, the node operation data includes: the impedance value between any two power nodes, the impedance value between any power node and a grid-connected energy storage node, the self-impedance value of the grid-connected energy storage node, the node capacity of the power nodes and the base value of the AC grid capacity, and the reactance value between the grid-connected energy storage and the grid-connected energy storage node; the step of determining the node mutual impedance data of the power system based on the virtual impedance model and the operation data, and determining the voltage stability index of the grid-connected energy storage based on the node mutual impedance data, includes: The virtual impedance value of the grid-type energy storage is determined based on the virtual impedance model. The total equivalent impedance of the grid-type energy storage access node is determined based on the virtual impedance value, the self-impedance value, and the reactance value of the grid-type energy storage access node. The coupling impedance between any two power nodes is determined based on the impedance value between any power node and the grid-type energy storage access node. The impedance correction term between any two power nodes is determined based on the ratio of the coupling impedance value between any two power nodes to the total equivalent impedance of the grid-type energy storage access node. The impedance value between any two power nodes is corrected based on the impedance correction term between any two power nodes to obtain the corrected impedance value between any two power nodes. The voltage stability index of the grid-type energy storage is determined based on the corrected impedance value between any two power nodes, the node capacity of the power nodes, and the base value of the AC grid capacity.

[0040] In an optional embodiment, after completing the virtual impedance model construction, the voltage stability index is further calculated. The multi-infeed short circuit ratio (MSCR) is an important indicator for evaluating the voltage stability of an AC power grid with multiple renewable energy power plants or DC system connections, as it considers the coupling relationship between multiple connection points. Therefore, this embodiment uses the MSCR as the voltage stability index. To calculate the MSCR after connecting grid-type energy storage, it is necessary to calculate the impedance between each node after connecting the grid-type energy storage. Since connecting grid-type energy storage will affect the impedance between nodes in the power system, this embodiment first corrects the original impedance.

[0041] Specifically, in this embodiment, any two power nodes are defined as... and Define the grid-type energy storage access node as Therefore, the impedance between any two power nodes is expressed as... It refers to the impedance value between two power nodes before they are connected to the grid-connected energy storage system; the impedance value between any power node and the grid-connected energy storage node is defined as... and , Indicates the first Power nodes and grid-type energy storage access nodes The impedance values ​​between; Indicates the first Power nodes and grid-type energy storage access nodes The impedance values ​​between; the self-impedance value of the grid-type energy storage access node is defined as... It represents the node's own impedance value due to the integration of grid-type energy storage; the node capacity of a power node is defined as... It refers to the first The capacity of new energy power plants in each power node; the baseline value of AC power grid capacity is defined as follows: It refers to the total capacity of new energy power stations in the entire power system; the reactance value between grid-connected energy storage and grid-connected energy storage access nodes is defined as... ; As described above, the virtual impedance value of the grid-type energy storage is determined from the virtual impedance model. Then, the virtual impedance value was... Self-impedance value of grid-type energy storage access node and reactance value The total equivalent impedance of the grid-type energy storage access node is obtained by summing the results. For any two power nodes, multiply the impedance values ​​between the power nodes and the grid-connected energy storage nodes to obtain the coupling impedance value between the two power nodes. The coupling impedance value between any two power nodes and the total equivalent impedance of the grid-type energy storage access node The ratio of these two values, used as the impedance correction term between any two power nodes, is expressed as: Finally, the impedance value between any two power nodes is... Subtract its corresponding impedance correction term Obtain the corrected impedance value between any two power nodes. ; After obtaining the actual corrected impedance values ​​of each power node after grid-connected energy storage, the multi-infeed short-circuit ratio is calculated. The formula for calculating the multi-infeed short-circuit ratio is as follows: The multi-infeed short-circuit ratio is used as a voltage stability indicator for grid-type energy storage. When voltage stability is poor, the power system is called a weak system. When the voltage stability is good, the power system is called a strong system.

[0042] In determining the voltage stability index, the above embodiment first outputs the virtual impedance value based on the virtual impedance model. Then, based on the virtual impedance value, the self-impedance value, and the reactance value of the grid-type energy storage access node, the total equivalent impedance of the grid-type energy storage access node is obtained. Next, using the impedance values ​​between each power node and the grid-type energy storage access node, combined with the impedance values ​​between any two power nodes, the coupling impedance value is determined. Then, the ratio of the coupling impedance value to the total equivalent impedance is calculated as an impedance correction term, and the corrected impedance value is obtained by correcting with the impedance correction term. By using the total equivalent impedance and the coupling impedance between nodes, the reshaping effect of the virtual impedance introduced by the grid-type energy storage on the impedance distribution of the power system is quantitatively characterized, so that the voltage stability index can accurately reflect the actual voltage support effect of the grid-type energy storage, thereby improving the accuracy of the subsequent assessment of the support capability of the grid-type energy storage.

[0043] In this embodiment, determining the frequency dynamic equation of the power system based on the virtual inertial model and node operation data; and determining the frequency response energy index and frequency change rate index of the grid-type energy storage based on the frequency dynamic equation, includes: The virtual inertia matrix and virtual damping matrix of the power system are determined based on the virtual inertia model. Based on the virtual inertia matrix, virtual damping matrix, and pre-acquired node admittance matrix of the power system, the frequency dynamic equation of the power system is constructed by combining the phase angle transformation rate and frequency change rate of the grid-type energy storage access node. An evaluation equation is constructed based on the virtual inertia matrix of the power system; Solving the frequency dynamic equation and the evaluation equation yields the frequency response energy index of the grid-type energy storage. The virtual inertia time constant of the grid-type energy storage is constructed based on the virtual inertia matrix of the power system, and the total inertia time constant of the power system is determined based on the virtual inertia time constant and the pre-acquired inertia time constant of the power equipment. The power change rate of the power system is obtained, and the frequency change rate of the power system is determined based on the power change rate, the AC grid capacity base value and the total inertial time constant. The frequency change rate of the power system is used as the frequency change rate index of the grid-type energy storage.

[0044] In an alternative embodiment, in order to evaluate frequency support capability, this embodiment first calculates the frequency response energy index. The norm is an important performance indicator in control system theory that measures the overall energy of the output response of a linear time-invariant system under external input signal excitation. It quantifies the average suppression capability of a power system against typical random disturbances or impulse disturbances. A smaller norm indicates better power system interference suppression performance and a more stable output response. Therefore, this embodiment will... The norm serves as an indicator of frequency response energy.

[0045] The admittance matrix of a node in a power system refers to the linear relationship between the injected current and the node voltage. It can be obtained from data between power systems. The mutual admittance matrix is ​​the admittance matrix after removing the diagonal. In a power system, nodes connected to generators, synchronous condensers, and grid-connected energy storage can be called inertial nodes. Therefore, this embodiment simplifies non-inertial nodes (nodes other than inertial nodes) to further simplify subsequent calculations. Specifically, this embodiment uses Karon's reduction method to process the initial node admittance matrix. Karon's reduction method is a classic method for reducing the order of admittance matrices in power systems, and its simplified calculation formula is expressed as: ;in, The admittance matrix represents the inertial node; This represents the mutual admittance matrix from inertial nodes to non-inertial nodes; Represents the admittance matrix of non-inertial nodes; Represents the mutual admittance matrix from non-inertial nodes to inertial nodes; Represents the nodal admittance matrix; After obtaining the nodal admittance matrix, use the nodal admittance matrix Determine the auxiliary computation matrix Auxiliary calculation matrix The elements in are represented as: , : Indicates the first Admittance value of each power node; Indicates the first Auxiliary calculation values ​​for each power node; Indicates the first The power node and the first The admittance value of each power node; Indicates the first The power node and the first Auxiliary calculation values ​​for each power node; Extracting the virtual inertial matrix of the power system from the virtual inertial model and the virtual damping matrix of the power system Then, using the nodal admittance matrix The auxiliary calculation matrix is ​​determined. Phase angle transformation rate of grid-type energy storage access nodes and the rate of change of frequency The frequency dynamic equations of the power system are constructed as shown in the following formula. ; In the frequency dynamic equation, Represents the identity matrix; This represents the injected power disturbance term. This indicates the distribution of the injected power disturbance term; This indicates the real-time phase angle of the grid-connected energy storage node; This indicates the real-time frequency of the grid-connected energy storage node; and Both represent matrices generated by constructing the frequency dynamic equation, where, ; In particular, the injected power disturbance term can be set according to actual needs, which will not be explained in detail in this embodiment.

[0046] Furthermore, the constructed evaluation equation is expressed as: ;in, This represents the matrix generated by constructing the evaluation equation. ; This represents an intermediate variable in the time domain, used to calculate... Norm; therefore, at this time The norm can be expressed as: ; In general solutions, The norm is obtained by constructing and solving the Lyapunov equation. Specifically, the Lyapunov equation can be derived through the frequency dynamic equation and the evaluation equation, which includes: and ; Represents the trace of a matrix. The observation matrix is ​​given; therefore, the frequency response energy index of the grid-type energy storage can be obtained by solving the Lyapunov equation.

[0047] After obtaining the frequency response energy index, this embodiment also sets a frequency change rate index, which is a key dynamic characteristic for quantifying the inertial support capability of a power system. When a power system experiences power disturbances, its frequency change rate directly reflects the overall inertia of the power system: the larger the change rate, the weaker the power system's ability to resist frequency abrupt changes, i.e., insufficient inertial support from grid-based energy storage; the smaller the change rate, the more sufficient the power system's rotational inertia, which can effectively buffer the impact of power imbalance. Specifically, the virtual inertial time constant of the grid-based energy storage is constructed based on the virtual inertia matrix of the power system, and the virtual inertial time constant is expressed as: The pre-acquired inertial time constant of the power equipment refers to the inertial time constant of traditional synchronous generators, synchronous condensers, and other power equipment in the power system. This inertial time constant can be obtained using conventional methods, which will not be elaborated upon in this embodiment. Next, the virtual inertial time constant and the power equipment inertial time constant are summed to obtain the total inertial time constant of the power system. The total inertial time constant of the power system The sum of the inertial time constants of the inertial nodes in the power system was characterized; then the power change rate of the power system was obtained. The rate of change of frequency in a power system can be expressed as: .

[0048] In determining the frequency response energy index, the above embodiments construct frequency dynamic equations and evaluation equations based on the power system virtual inertia matrix and power system virtual damping matrix output by the virtual inertia model, combined with the pre-acquired node admittance matrix, and obtain the frequency response energy index by solving them. In determining the frequency change rate index, the power system virtual inertia matrix is ​​converted into a virtual inertia time constant, and then combined with the power equipment inertia time constant to obtain the system's total inertia time constant. Finally, the frequency change rate index is determined by combining the power change rate. This dual index system characterizes frequency stability from different dimensions: the frequency response energy index is determined by analyzing the frequency dynamic equations and evaluation equations. The joint solution of the valence equations can quantify the output energy response of grid-type energy storage under white noise or small disturbance excitation, thus reflecting the ability of grid-type energy storage to suppress random disturbances. The frequency change rate index focuses on the inertial response at the moment of high power disturbance. Through the calculation relationship between the total inertial time constant and the power change rate, it directly reflects the buffering effect of grid-type energy storage on the frequency drop rate. It not only captures the frequency stability margin of grid-type energy storage under small disturbance scenarios, but also evaluates its inertial support strength under severe disturbances, thereby comprehensively improving the accuracy of frequency and inertial support capability assessment, and thus improving the accuracy of subsequent grid-type energy storage support capability assessment.

[0049] In this embodiment, the analysis of the voltage stability index, frequency response energy index, and frequency change rate index to obtain the evaluation result of the supporting capacity of the grid-type energy storage includes: The voltage stability index, frequency response energy index, and frequency change rate index are normalized respectively to obtain normalized voltage stability index, normalized frequency response energy index, and normalized frequency change rate index. An index layer is constructed based on the normalized voltage stability index, the normalized frequency response energy index, and the normalized frequency change rate index. The preset stability support capability is used as the target layer, and the preset voltage support capability, preset frequency support capability, and preset inertia support capability are used as the criteria layer. Construct a first judgment matrix of the criterion layer relative to the target layer, and construct several second judgment matrices of the indicator layer relative to the criterion layer; Consistency checks are performed on the first judgment matrix and the second judgment matrix respectively, so as to obtain the first weight vector corresponding to the first judgment matrix and the second weight vector corresponding to each of the second judgment matrices based on the consistency check results; Based on the normalized voltage stability index, normalized frequency response energy index, and normalized frequency change rate index, the voltage support capability assessment score, frequency support capability assessment score, and inertia support capability assessment score of the grid-type energy storage are determined by combining the second weight vector corresponding to each second judgment matrix. Based on the voltage support capability assessment score, frequency support capability assessment score, and inertia support capability assessment score, the support capability score of the grid-type energy storage is determined by combining the first weight vector, and the support capability score is used as the support capability assessment result of the grid-type energy storage.

[0050] In an optional embodiment, to perform a unified quantitative comparison of the three indicators, this embodiment employs the Analytic Hierarchy Process (AHP) for comprehensive evaluation. The AHP is a multi-criteria decision-making method that combines qualitative and quantitative approaches, suitable for handling complex decision problems that are difficult to analyze entirely using quantitative methods. This method decomposes complex problems into multiple levels and factors, determines the relative importance of each factor through pairwise comparisons, and ultimately derives a weighted ranking.

[0051] Specifically, to avoid the influence of different indicator dimensions, each indicator is first normalized. For the voltage stability indicator (multi-feed short-circuit ratio), which is an extremely large indicator, the normalization process is expressed as follows: ; This represents the normalized voltage stability index. This represents the minimum voltage stability index; This represents the maximum voltage stability index; in particular, since the practical significance is diminished when the multi-infeed short-circuit ratio is too large, therefore when At this time, set The maximum value of 1 is reached. This embodiment sets... , For the frequency response energy index, which is a very small index, the normalization process is expressed as follows: ; This represents the normalized frequency response energy index; This indicates the frequency response energy index; This represents the maximum frequency response energy index; This represents the minimum frequency response energy index; when Afterwards, the power system stability is poor, and it is set at this time. The minimum value of 0 is reached. This embodiment sets... , For the rate of change of frequency index, which is a very small index, the normalization process is expressed as follows: ; This represents the normalized frequency change rate index. Indicators representing the rate of change of frequency; Indicator representing the maximum rate of change of frequency; Indicates the minimum frequency change rate index; when Afterwards, the power system has poor inertia, so it is set at this time. The minimum value of 0 is reached. The time constant of traditional generating units in a power system can be calculated, and this embodiment is set accordingly. , .

[0052] The Analytic Hierarchy Process (AHP) includes a target layer, a criterion layer, and an index layer. Therefore, this embodiment uses the normalized voltage stability index, the normalized frequency response energy index, and the normalized frequency change rate index as the index layer, with stability support capability as the target layer, and voltage support capability, frequency support capability, and inertia support capability as the criterion layer. Specifically, stability support capability reflects the overall support capability of grid-type energy storage; voltage support capability reflects the support capability of grid-type energy storage in the voltage dimension; frequency support capability reflects the support capability of grid-type energy storage in the frequency dimension; and inertia support capability reflects the support capability of grid-type energy storage in the inertia dimension.

[0053] After constructing the target layer, criterion layer, and indicator layer, the Analytic Hierarchy Process (AHP) still needs to use judgment matrices to determine the importance of each indicator layer relative to each criterion layer, and each criterion layer relative to the target layer. Specifically, a first judgment matrix is ​​constructed relative to the target layer, where the rows and columns represent voltage support capability, frequency support capability, and inertia support capability. This first judgment matrix includes the judgment matrix from the criterion layer (voltage support capability, frequency support capability, inertia support capability) to the target layer (stability support capability). Construct several second judgment matrices for the index layer relative to the criterion layer; the rows and columns of each second judgment matrix represent the normalized voltage stability index, the normalized frequency response energy index, and the normalized frequency change rate index; the second judgment matrix includes: a judgment matrix from the index layer (normalized voltage stability index, normalized frequency response energy index, and normalized frequency change rate index) to voltage support capability. From the indicator layer (normalized voltage stability index, normalized frequency response energy index, and normalized frequency change rate index) to the judgment matrix of frequency support capability. The judgment matrix from the index layers (normalized voltage stability index, normalized frequency response energy index, and normalized frequency change rate index) to inertial support capability. The contents of the first and second judgment matrices can be set according to actual needs, and will not be elaborated on in this embodiment.

[0054] In the judgment matrix, the judgment matrix elements in The value ranges from 1 to 9, where 1 represents the th _____. The factor relative to the first All factors are equally important; 9 indicates that the 9th factor is... The factor relative to the first Each factor is strongly important; diagonal elements And satisfy After obtaining the judgment matrix, it is necessary to perform a consistency check on it by calculating the largest eigenvalue of the judgment matrix. Consistency index can be obtained and consistency ratio ;in, Indicates the number of factors; The random consistency index is determined by the number of factors, as shown in this embodiment. , .if If the consistency of the judgment matrix is ​​satisfactory, then the consistency of the judgment matrix is ​​acceptable; otherwise, the judgment matrix is ​​contradictory and needs to be re-evaluated. After obtaining the judgment matrix that has passed the consistency check, the judgment matrix is ​​calculated... Eigenvector corresponding to the largest eigenvalue It can calculate the weights of each factor. ;in, Indicates the first The weights of each factor are determined; ultimately, these weights form the weight vector for the judgment matrix. .

[0055] Therefore, the first judgment matrix can be obtained. The corresponding first weight vector In the second judgment matrix, the judgment matrix The corresponding second weight vector Judgment matrix The corresponding second weight vector Judgment matrix The corresponding second weight vector .

[0056] Finally, based on the normalized voltage stability index, normalized frequency response energy index, and normalized frequency change rate index, and combined with the second weight vector corresponding to each of the second judgment matrices, the voltage support capability assessment score, frequency support capability assessment score, and inertia support capability assessment score of the grid-type energy storage are determined, wherein the voltage support capability assessment score is expressed as: The frequency support capability assessment score is expressed as follows: The inertial support capacity assessment score is expressed as follows: Finally, the support capability score is expressed as: The support capability score will be used as the evaluation result of the support capability of the grid-type energy storage.

[0057] In one alternative embodiment, please refer to Figure 2 , Figure 2 A schematic diagram of a power node in a power system is provided as an embodiment of the present invention; for example... Figure 2 As shown, this embodiment selects a traditional power system with 14 power nodes to verify the method proposed in this embodiment. Figure 2 middle, This refers to a traditional synchronous generator. , and All three schemes refer to Renewable Energy Sources, each with a capacity of 30MW. This embodiment sets up three grid-connected energy storage access schemes: the first scheme connects 50MW of high-voltage direct-connected grid-connected energy storage at power node 1; the second scheme connects 100MW of high-voltage direct-connected grid-connected energy storage at power node 1; and the third scheme connects 50MW (totaling 100MW) of high-voltage direct-connected grid-connected energy storage at both power node 1 and power node 8.

[0058] As described above, the voltage stability index, frequency response energy index, and frequency change rate index are calculated in the following ways: the first scheme yields a voltage stability index of 1.78, a frequency response energy index of 1.96, and a frequency change rate index of 0.00195; the second scheme yields a voltage stability index of 1.86, a frequency response energy index of 1.90, and a frequency change rate index of 0.00171; and the third scheme yields a voltage stability index of 3.23, a frequency response energy index of 1.71, and a frequency change rate index of 0.00171.

[0059] At the same time, based on the relevant descriptions of the first and second judgment matrices above, the following can be calculated: , , , ; The consistency index is 0, the consistency ratio is 0, and it can pass the consistency check. The consistency index is 0, the consistency ratio is 0, and it can pass the consistency check. The consistency index is 0.0109, and the consistency ratio is 0.0209, which means it passes the consistency check. The consistency index is 0.0268 and the consistency ratio is 0.0516, which means it can pass the consistency check.

[0060] Therefore, based on the first judgment matrix and the second judgment matrix, the first judgment matrix is ​​obtained. The corresponding first weight vector Judgment Matrix The corresponding second weight vector Judgment Matrix The corresponding second weight vector Judgment Matrix The corresponding second weight vector ; Ultimately, for the first scheme, the calculated voltage support capability assessment score is... Frequency support capability assessment score Inertial support capacity assessment score Support capability score For the second scheme, the calculated voltage support capability assessment score is... Frequency support capability assessment score Inertial support capacity assessment score Support capability score For the third scheme, the calculated voltage support capability assessment score is... Frequency support capability assessment score Inertial support capacity assessment score Support capability score Therefore, the third option has better grid-based energy storage support capabilities.

[0061] The above embodiments employ the Analytic Hierarchy Process (AHP) to comprehensively analyze voltage stability, frequency response energy, and frequency change rate indices. First, these indices are normalized to eliminate dimensional differences, and then an index layer is constructed. Next, stability support capability is used as the target layer, and preset voltage support capability, preset frequency support capability, and preset inertia support capability are used as the criteria layer. Based on this, a first judgment matrix and a second judgment matrix are constructed. After consistency verification, a first weight vector and a second weight vector are obtained. Then, the voltage support capability evaluation score, frequency support capability evaluation score, and inertia support capability evaluation score of the grid-type energy storage are calculated, ultimately yielding the support capability score. By constructing a three-layer evaluation architecture, the multi-dimensional support capability problem, which is difficult to comprehensively evaluate with a single index, is transformed into a hierarchical multi-criteria decision-making problem. This avoids the shortcomings of traditional methods that can only evaluate from a single dimension or whose simple weighting fails to reflect physical meaning. The support capability evaluation results possess both the advantages of multi-dimensional comprehensiveness and the ability to adapt to different operating scenarios, thereby improving the accuracy of the grid-type energy storage support capability evaluation.

[0062] Example 2 Please refer to Figure 3 , Figure 3 A schematic diagram of a support capability assessment system for grid-type energy storage provided in an embodiment of the present invention includes: a data acquisition module 201, a grid-type energy storage model construction module 202, a voltage stability index acquisition module 203, a frequency index acquisition module 204, and a support capability assessment module 205; The data acquisition module 201 is used to acquire node operation data in the power system and to connect the grid-type energy storage to be evaluated into the power system. The grid-type energy storage model construction module 202 is used to obtain the virtual impedance control parameters and virtual synchronous machine control parameters of the grid-type energy storage, and construct a virtual impedance model and a virtual inertial model based on the virtual impedance control parameters, virtual synchronous machine control parameters and node operation data; The voltage stability index acquisition module 203 is used to determine the node mutual impedance data of the power system based on the virtual impedance model and node operation data, and to determine the voltage stability index of the grid-type energy storage based on the node mutual impedance data. The frequency index acquisition module 204 is used to determine the frequency dynamic equation of the power system based on the virtual inertial model and node operation data; and to determine the frequency response energy index and frequency change rate index of the grid-type energy storage based on the frequency dynamic equation. The support capability assessment module 205 is used to analyze the voltage stability index, frequency response energy index, and frequency change rate index to obtain the support capability assessment results of the grid-type energy storage.

[0063] In this embodiment, the grid-type energy storage model construction module 202 includes: a grid-type energy storage model construction unit; The grid-type energy storage model construction unit is used to obtain the virtual impedance control parameters and virtual synchronous machine control parameters of the grid-type energy storage. The virtual impedance control parameters include: grid-type converter potential, grid-type converter access voltage, and grid-type converter current. The potential difference of the grid converter is determined based on the grid converter potential and the grid converter input voltage; A virtual impedance model is constructed based on the ratio of the potential difference of the grid converter to the current of the grid converter; Based on the control parameters of the virtual synchronous machine and the node operation data, the rotor motion equation and electromagnetic equation are constructed, and a virtual inertial model is constructed based on the rotor motion equation and electromagnetic equation.

[0064] In this embodiment, the grid-type energy storage model construction unit includes: a virtual inertial model construction subunit; In the virtual inertial model construction subunit, the virtual synchronous machine control parameters include: virtual inertia coefficient, virtual damping coefficient, virtual mechanical power, and grid interaction power; the node operation data includes: real-time frequency, phase angle transformation rate, frequency change rate, and rated frequency of the grid-type energy storage access node. The virtual inertial model construction subunit is used to construct electromagnetic equations based on the real-time frequency and phase angle transformation rate of the grid-type energy storage access node; The virtual inertial torque is determined based on the virtual inertial coefficient and the frequency change rate of the grid-type energy storage access node; The frequency change value of the grid-type energy storage access node is determined based on the real-time frequency and the rated frequency of the grid-type energy storage access node. The virtual damping torque is determined based on the frequency variation value of the grid-type energy storage access node and the virtual damping coefficient. The virtual acceleration power is determined based on the virtual mechanical power, the power grid interaction power, and the virtual damping torque. The rotor motion equations are constructed based on the virtual inertial torque and virtual acceleration power. A virtual inertial model is constructed based on the rotor motion equations and electromagnetic equations.

[0065] In this embodiment, the voltage stability index acquisition module 203 includes: a voltage stability index acquisition unit; In the voltage stability index acquisition unit, the node operation data includes: the impedance value between any two power nodes, the impedance value between any power node and the grid-type energy storage access node, the self-impedance value of the grid-type energy storage access node, the node capacity of the power node and the AC grid capacity base value, and the reactance value between the grid-type energy storage and the grid-type energy storage access node. The voltage stability index acquisition unit is used to determine the virtual impedance value of the grid-type energy storage according to the virtual impedance model; The total equivalent impedance of the grid-type energy storage access node is determined based on the virtual impedance value, the self-impedance value, and the reactance value of the grid-type energy storage access node. The coupling impedance between any two power nodes is determined based on the impedance value between any power node and the grid-type energy storage access node. The impedance correction term between any two power nodes is determined based on the ratio of the coupling impedance value between any two power nodes to the total equivalent impedance of the grid-type energy storage access node. The impedance value between any two power nodes is corrected based on the impedance correction term between any two power nodes to obtain the corrected impedance value between any two power nodes. The voltage stability index of the grid-type energy storage is determined based on the corrected impedance value between any two power nodes, the node capacity of the power nodes, and the base value of the AC grid capacity.

[0066] In this embodiment, the frequency index acquisition module 204 includes: a frequency index acquisition unit; The frequency index acquisition unit is used to determine the power system virtual inertia matrix and the power system virtual damping matrix based on the virtual inertia model. Based on the virtual inertia matrix, virtual damping matrix, and pre-acquired node admittance matrix of the power system, the frequency dynamic equation of the power system is constructed by combining the phase angle transformation rate and frequency change rate of the grid-type energy storage access node. An evaluation equation is constructed based on the virtual inertia matrix of the power system; Solving the frequency dynamic equation and the evaluation equation yields the frequency response energy index of the grid-type energy storage. The virtual inertia time constant of the grid-type energy storage is constructed based on the virtual inertia matrix of the power system, and the total inertia time constant of the power system is determined based on the virtual inertia time constant and the pre-acquired inertia time constant of the power equipment. The power change rate of the power system is obtained, and the frequency change rate of the power system is determined based on the power change rate, the AC grid capacity base value and the total inertial time constant. The frequency change rate of the power system is used as the frequency change rate index of the grid-type energy storage.

[0067] In this embodiment, the support capability assessment module 205 includes: a support capability assessment unit; The support capability assessment unit is used to normalize the voltage stability index, frequency response energy index, and frequency change rate index respectively to obtain normalized voltage stability index, normalized frequency response energy index, and normalized frequency change rate index. An index layer is constructed based on the normalized voltage stability index, the normalized frequency response energy index, and the normalized frequency change rate index. The preset stability support capability is used as the target layer, and the preset voltage support capability, preset frequency support capability, and preset inertia support capability are used as the criteria layer. Construct a first judgment matrix of the criterion layer relative to the target layer, and construct several second judgment matrices of the indicator layer relative to the criterion layer; Consistency checks are performed on the first judgment matrix and the second judgment matrix respectively, so as to obtain the first weight vector corresponding to the first judgment matrix and the second weight vector corresponding to each of the second judgment matrices based on the consistency check results; Based on the normalized voltage stability index, normalized frequency response energy index, and normalized frequency change rate index, the voltage support capability assessment score, frequency support capability assessment score, and inertia support capability assessment score of the grid-type energy storage are determined by combining the second weight vector corresponding to each second judgment matrix. Based on the voltage support capability assessment score, frequency support capability assessment score, and inertia support capability assessment score, the support capability score of the grid-type energy storage is determined by combining the first weight vector, and the support capability score is used as the support capability assessment result of the grid-type energy storage.

[0068] This embodiment acquires the virtual impedance control parameters and virtual synchronous machine control parameters of the grid-type energy storage, and constructs virtual impedance and virtual inertia models respectively by combining node operation data. The virtual impedance model reflects the active voltage support characteristics of the grid-type energy storage, while the virtual inertia model accurately simulates the inertial response behavior of the grid-type energy storage under frequency disturbances. Next, the node mutual impedance data of the power system is determined using the virtual impedance model and node operation data, and the voltage stability index of the grid-type energy storage is determined based on the node mutual impedance data. The frequency dynamic equation of the power system is determined using the virtual inertia model and node operation data. Based on the frequency dynamic equation, the frequency response energy index and frequency change rate index of the grid-type energy storage are determined. Finally, the voltage stability index, frequency response energy index, and frequency change rate index are analyzed to obtain the support capability assessment result of the grid-type energy storage through multi-dimensional evaluation, which significantly improves the accuracy of the support capability assessment of the grid-type energy storage.

[0069] In summary, this embodiment of the invention acquires the virtual impedance control parameters and virtual synchronous machine control parameters of grid-connected energy storage, and constructs virtual impedance and virtual inertia models respectively by combining node operation data. The virtual impedance model reflects the active voltage support characteristics of grid-connected energy storage, while the virtual inertia model accurately simulates the inertial response behavior of grid-connected energy storage under frequency disturbances. Next, the node mutual impedance data of the power system is determined using the virtual impedance model and node operation data, and the voltage stability index of the grid-connected energy storage is determined based on the node mutual impedance data. The frequency dynamic equation of the power system is determined using the virtual inertia model and node operation data. Based on the frequency dynamic equation, the frequency response energy index and frequency change rate index of the grid-connected energy storage are determined. Finally, the voltage stability index, frequency response energy index, and frequency change rate index are analyzed, and the support capability assessment result of the grid-connected energy storage is obtained through multi-dimensional evaluation, significantly improving the accuracy of the support capability assessment of grid-connected energy storage.

[0070] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. In particular, it should be noted that any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention for those skilled in the art.

Claims

1. A method for assessing the supporting capacity of grid-type energy storage, characterized in that, include: Acquire node operation data in the power system and connect the grid-type energy storage to be evaluated into the power system; Obtain the virtual impedance control parameters and virtual synchronous machine control parameters of the grid-type energy storage, and construct a virtual impedance model and a virtual inertial model based on the virtual impedance control parameters, virtual synchronous machine control parameters and node operation data; Based on the virtual impedance model and node operation data, the node mutual impedance data of the power system are determined, and the voltage stability index of the grid-type energy storage is determined based on the node mutual impedance data. The frequency dynamic equation of the power system is determined based on the virtual inertial model and node operation data; the frequency response energy index and frequency change rate index of the grid-type energy storage are determined based on the frequency dynamic equation. The voltage stability index, frequency response energy index, and frequency change rate index are analyzed to obtain the evaluation results of the support capacity of the grid-type energy storage.

2. The method for assessing the supporting capacity of grid-type energy storage as described in claim 1, characterized in that, The process of obtaining the virtual impedance control parameters and virtual synchronous machine control parameters of the grid-type energy storage, and constructing a virtual impedance model and a virtual inertial model based on the virtual impedance control parameters, virtual synchronous machine control parameters, and node operation data includes: The virtual impedance control parameters and virtual synchronous machine control parameters of the grid-type energy storage are obtained, wherein the virtual impedance control parameters include: grid-type converter potential, grid-type converter access voltage and grid-type converter current; The potential difference of the grid converter is determined based on the grid converter potential and the grid converter input voltage; A virtual impedance model is constructed based on the ratio of the potential difference of the grid converter to the current of the grid converter; Based on the control parameters of the virtual synchronous machine and the node operation data, the rotor motion equation and electromagnetic equation are constructed, and a virtual inertial model is constructed based on the rotor motion equation and electromagnetic equation.

3. The method for assessing the supporting capacity of grid-type energy storage as described in claim 2, characterized in that, The virtual synchronous machine control parameters include: virtual inertia coefficient, virtual damping coefficient, virtual mechanical power, and grid interaction power; the node operation data includes: real-time frequency, phase angle transformation rate, frequency change rate, and rated frequency of the grid-connected energy storage node; the construction of rotor motion equations and electromagnetic equations based on the virtual synchronous machine control parameters and node operation data, and the construction of a virtual inertial model based on the rotor motion equations and electromagnetic equations, includes: Electromagnetic equations are constructed based on the real-time frequency and phase angle transformation rate of the network-type energy storage access node. The virtual inertial torque is determined based on the virtual inertial coefficient and the frequency change rate of the grid-type energy storage access node; The frequency change value of the grid-type energy storage access node is determined based on the real-time frequency and the rated frequency of the grid-type energy storage access node. The virtual damping torque is determined based on the frequency variation value of the grid-type energy storage access node and the virtual damping coefficient. The virtual acceleration power is determined based on the virtual mechanical power, the power grid interaction power, and the virtual damping torque. The rotor motion equations are constructed based on the virtual inertial torque and virtual acceleration power. A virtual inertial model is constructed based on the rotor motion equations and electromagnetic equations.

4. The method for assessing the supporting capacity of grid-type energy storage as described in claim 2, characterized in that, The node operation data includes: the impedance value between any two power nodes, the impedance value between any power node and a grid-connected energy storage node, the self-impedance value of the grid-connected energy storage node, the node capacity of the power nodes and the base value of the AC grid capacity, and the reactance value between the grid-connected energy storage and the grid-connected energy storage node; the step of determining the node mutual impedance data of the power system based on the virtual impedance model and the operation data, and determining the voltage stability index of the grid-connected energy storage based on the node mutual impedance data, includes: The virtual impedance value of the grid-type energy storage is determined based on the virtual impedance model. The total equivalent impedance of the grid-type energy storage access node is determined based on the virtual impedance value, the self-impedance value, and the reactance value of the grid-type energy storage access node. The coupling impedance between any two power nodes is determined based on the impedance value between any power node and the grid-type energy storage access node. The impedance correction term between any two power nodes is determined based on the ratio of the coupling impedance value between any two power nodes to the total equivalent impedance of the grid-type energy storage access node. The impedance value between any two power nodes is corrected based on the impedance correction term between any two power nodes to obtain the corrected impedance value between any two power nodes. The voltage stability index of the grid-type energy storage is determined based on the corrected impedance value between any two power nodes, the node capacity of the power nodes, and the base value of the AC grid capacity.

5. The method for assessing the supporting capacity of grid-type energy storage as described in claim 4, characterized in that, The frequency dynamic equations of the power system are determined based on the virtual inertial model and node operation data. The frequency response energy index and frequency change rate index of the grid-type energy storage are determined based on the aforementioned frequency dynamic equation, including: The virtual inertia matrix and virtual damping matrix of the power system are determined based on the virtual inertia model. Based on the virtual inertia matrix, virtual damping matrix, and pre-acquired node admittance matrix of the power system, the frequency dynamic equation of the power system is constructed by combining the phase angle transformation rate and frequency change rate of the grid-type energy storage access node. An evaluation equation is constructed based on the virtual inertia matrix of the power system; Solving the frequency dynamic equation and the evaluation equation yields the frequency response energy index of the grid-type energy storage. The virtual inertia time constant of the grid-type energy storage is constructed based on the virtual inertia matrix of the power system, and the total inertia time constant of the power system is determined based on the virtual inertia time constant and the pre-acquired inertia time constant of the power equipment. The power change rate of the power system is obtained, and the frequency change rate of the power system is determined based on the power change rate, the AC grid capacity base value and the total inertial time constant. The frequency change rate of the power system is used as the frequency change rate index of the grid-type energy storage.

6. The method for assessing the supporting capacity of grid-type energy storage as described in claim 5, characterized in that, The analysis of the voltage stability index, frequency response energy index, and frequency change rate index yields the assessment results of the support capability of the grid-type energy storage, including: The voltage stability index, frequency response energy index, and frequency change rate index are normalized respectively to obtain normalized voltage stability index, normalized frequency response energy index, and normalized frequency change rate index. An index layer is constructed based on the normalized voltage stability index, the normalized frequency response energy index, and the normalized frequency change rate index. The preset stability support capability is used as the target layer, and the preset voltage support capability, preset frequency support capability, and preset inertia support capability are used as the criteria layer. Construct a first judgment matrix of the criterion layer relative to the target layer, and construct several second judgment matrices of the indicator layer relative to the criterion layer; Consistency checks are performed on the first judgment matrix and the second judgment matrix respectively, so as to obtain the first weight vector corresponding to the first judgment matrix and the second weight vector corresponding to each of the second judgment matrices based on the consistency check results; Based on the normalized voltage stability index, normalized frequency response energy index, and normalized frequency change rate index, the voltage support capability assessment score, frequency support capability assessment score, and inertia support capability assessment score of the grid-type energy storage are determined by combining the second weight vector corresponding to each second judgment matrix. Based on the voltage support capability assessment score, frequency support capability assessment score, and inertia support capability assessment score, the support capability score of the grid-type energy storage is determined by combining the first weight vector, and the support capability score is used as the support capability assessment result of the grid-type energy storage.

7. A support capacity assessment system for grid-type energy storage, characterized in that, include: The system includes a data acquisition module, a grid-type energy storage model construction module, a voltage stability index acquisition module, a frequency index acquisition module, and a support capability assessment module. The data acquisition module is used to acquire node operation data in the power system and to connect the grid-type energy storage to be evaluated into the power system. The grid-type energy storage model construction module is used to obtain the virtual impedance control parameters and virtual synchronous machine control parameters of the grid-type energy storage, and to construct a virtual impedance model and a virtual inertial model based on the virtual impedance control parameters, virtual synchronous machine control parameters and node operation data. The voltage stability index acquisition module is used to determine the node mutual impedance data of the power system based on the virtual impedance model and node operation data, and to determine the voltage stability index of the grid-type energy storage based on the node mutual impedance data. The frequency index acquisition module is used to determine the frequency dynamic equation of the power system based on the virtual inertial model and node operation data; and to determine the frequency response energy index and frequency change rate index of the grid-type energy storage based on the frequency dynamic equation. The support capability assessment module is used to analyze the voltage stability index, frequency response energy index, and frequency change rate index to obtain the support capability assessment results of the grid-type energy storage.

8. The support capacity assessment system for grid-type energy storage as described in claim 7, characterized in that, The grid-type energy storage model construction module includes: a grid-type energy storage model construction unit; The grid-type energy storage model construction unit is used to obtain the virtual impedance control parameters and virtual synchronous machine control parameters of the grid-type energy storage. The virtual impedance control parameters include: grid-type converter potential, grid-type converter access voltage, and grid-type converter current. The potential difference of the grid converter is determined based on the grid converter potential and the grid converter input voltage; A virtual impedance model is constructed based on the ratio of the potential difference of the grid converter to the current of the grid converter; Based on the control parameters of the virtual synchronous machine and the node operation data, the rotor motion equation and electromagnetic equation are constructed, and a virtual inertial model is constructed based on the rotor motion equation and electromagnetic equation.

9. The support capacity assessment system for grid-type energy storage as described in claim 8, characterized in that, The grid-type energy storage model construction unit includes: a virtual inertial model construction subunit; In the virtual inertial model construction subunit, the virtual synchronous machine control parameters include: virtual inertia coefficient, virtual damping coefficient, virtual mechanical power, and grid interaction power; the node operation data includes: real-time frequency, phase angle transformation rate, frequency change rate, and rated frequency of the grid-type energy storage access node. The virtual inertial model construction subunit is used to construct electromagnetic equations based on the real-time frequency and phase angle transformation rate of the grid-type energy storage access node; The virtual inertial torque is determined based on the virtual inertial coefficient and the frequency change rate of the grid-type energy storage access node; The frequency change value of the grid-type energy storage access node is determined based on the real-time frequency and the rated frequency of the grid-type energy storage access node. The virtual damping torque is determined based on the frequency variation value of the grid-type energy storage access node and the virtual damping coefficient. The virtual acceleration power is determined based on the virtual mechanical power, the power grid interaction power, and the virtual damping torque. The rotor motion equations are constructed based on the virtual inertial torque and virtual acceleration power. A virtual inertial model is constructed based on the rotor motion equations and electromagnetic equations.

10. The support capacity assessment system for grid-type energy storage as described in claim 9, characterized in that, The voltage stability index acquisition module includes: a voltage stability index acquisition unit; In the voltage stability index acquisition unit, the node operation data includes: the impedance value between any two power nodes, the impedance value between any power node and the grid-type energy storage access node, the self-impedance value of the grid-type energy storage access node, the node capacity of the power node and the AC grid capacity base value, and the reactance value between the grid-type energy storage and the grid-type energy storage access node. The voltage stability index acquisition unit is used to determine the virtual impedance value of the grid-type energy storage according to the virtual impedance model; The total equivalent impedance of the grid-type energy storage access node is determined based on the virtual impedance value, the self-impedance value, and the reactance value of the grid-type energy storage access node. The coupling impedance between any two power nodes is determined based on the impedance value between any power node and the grid-type energy storage access node. The impedance correction term between any two power nodes is determined based on the ratio of the coupling impedance value between any two power nodes to the total equivalent impedance of the grid-type energy storage access node. The impedance value between any two power nodes is corrected based on the impedance correction term between any two power nodes to obtain the corrected impedance value between any two power nodes. The voltage stability index of the grid-type energy storage is determined based on the corrected impedance value between any two power nodes, the node capacity of the power nodes, and the base value of the AC grid capacity.

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