Energy storage optimization configuration method and system considering new energy base voltage support capability improvement

Abstract

The invention discloses an energy storage optimal configuration method and system considering the improvement of the voltage supporting capability of a new energy base, and the method achieves the overall energy storage optimal configuration through the construction of a generalized operation short-circuit ratio index, the setting of a criterion, the building of a model, and the multi-round iteration and verification of a mechanism. The problem of insufficient voltage supporting capability of the new energy base is systematically solved; by introducing a generalized operation short-circuit ratio as a voltage support strength index, constructing a multi-constraint optimization model and adopting a multi-round iterative configuration strategy, accurate determination of energy storage installation nodes, power and capacity is realized, the voltage support capability of a new energy base is remarkably improved, and the energy storage capacity is improved. Technical support is provided for improving the voltage supporting capacity of the new energy base and guaranteeing stable operation of a power system.

Description

Technical Field

[0001] This invention relates to the field of energy storage configuration technology for new energy bases, specifically to an energy storage optimization configuration method and system that takes into account the improvement of voltage support capability of new energy bases. Background Technology

[0002] Driven by the "dual-carbon" strategy, the proportion of new energy power generation capacity in the new power system continues to rise, and the large-scale grid connection of new energy bases has become the core direction of energy structure transformation. However, new energy power generation is characterized by volatility and intermittency, and its grid-connected equipment (such as inverters) has limited dynamic reactive power support capabilities. In addition, there is a structural shortage of grid-side voltage regulation resources, which leads to a gradual weakening of voltage regulation capabilities in areas rich in new energy sources. This significantly increases the risk of transient voltage instability in the system, seriously threatening the safe and reliable operation of the power system.

[0003] Energy storage technology, with its flexible power regulation capabilities, can effectively compensate for insufficient voltage support in renewable energy generation, becoming a key means to improve voltage stability in renewable energy bases. Currently, the industry has developed several typical methods for energy storage configuration and voltage support, such as: synchronous condenser configuration methods based on traditional short-circuit ratio (SCR), multi-objective configuration models for energy storage aimed at maximizing reactive power reserve, and zonal reactive power reserve optimization methods for wind-solar-storage hybrid systems.

[0004] While existing research provides some technical insights, these methods still have significant limitations and shortcomings. These limitations are mainly reflected in the fact that traditional SCR indicators cannot fully characterize the voltage support mechanism of new energy bases with energy storage, and have poor adaptability to various operating conditions. Some methods do not fully consider the dynamic characteristics of the operating conditions of new energy bases, relying solely on fixed formulas or single objectives to construct models, which can easily lead to large deviations between energy storage configuration parameters and actual needs. Furthermore, existing methods often lack a systematic multi-round iterative optimization mechanism, making it difficult to balance the economic efficiency of energy storage configuration with the voltage support effect. Moreover, they fail to adequately reveal the intrinsic mechanism by which energy storage acts on voltage support, further affecting the scientific validity and engineering applicability of configuration schemes.

[0005] Therefore, there is an urgent need in this field for an energy storage optimization configuration method that can accurately characterize voltage support strength, construct a scientific optimization model, and adopt an efficient iterative strategy, so as to fundamentally improve the voltage stability of new energy bases. Summary of the Invention

[0006] The purpose of this invention is to provide an energy storage optimization configuration method and system that takes into account the improvement of voltage support capability of new energy bases, so as to solve the problem that the current energy storage optimization configuration method is prone to causing large deviations between energy storage configuration parameters and actual needs.

[0007] To address the aforementioned technical problems, in a first aspect, the present invention provides an energy storage optimization configuration method considering the improvement of voltage support capability in new energy bases, comprising the following steps:

[0008] S1: Collect power system parameters of the target new energy base;

[0009] S2: Based on the eigenspace perturbation theory, a eigensystem matrix of a new energy base including energy storage is established; combining the dynamic stability characteristics of the inverse matrix of the power system closed-loop transfer function, the generalized operating short-circuit ratio is defined. As a quantitative evaluation index of voltage support strength ;

[0010] S3: By mapping the coupling relationship between the reactive power output of renewable energy power plants and the voltage at grid connection nodes, the critical condition for voltage support capability is derived. And set the voltage support capability criterion as ;

[0011] S4: With the objective function of maximizing the generalized short-circuit ratio of the new energy base, and setting constraints on energy storage charging and discharging power, capacity, and state of charge, an energy storage optimization configuration model is constructed.

[0012] S5: For the original power system under the worst operating condition, energy storage devices are added step by step using a q-round iterative method. In each round, the extended admittance matrix equation of the power system is solved and the node parameters are updated by combining power flow calculations to determine the energy storage installation nodes and configuration parameters, until the preset number of iterations is reached.

[0013] S6: The mechanism of operation of energy storage devices is verified through simulation analysis, clarifying that it adjusts the generalized operating short-circuit ratio by modifying the equivalent network of the power system, but does not change the critical value of the voltage support capability criterion. Configure energy storage.

[0014] Furthermore, the power system parameters of the target new energy base include network structure data, equipment parameter data, and operating status data;

[0015] The network structure data includes the connection relationships of nodes within the base and the impedance of transmission lines;

[0016] The equipment parameter data includes the core parameters of the new energy unit, the inherent parameters of the energy storage device, and the control parameters of the phase-locked loop of the device.

[0017] The operational status data includes real-time voltage data and real-time output active power data of each node under different operating conditions of the base; the different operating conditions include the worst operating condition.

[0018] Furthermore, the expression for the characteristic sub-power system matrix of the new energy base is as follows:

[0019] ;

[0020] in, This is the eigenspace of the original system matrix; This is the inverse matrix of the original system; The right eigenvector matrix; The core dynamic impedance matrix of the characteristic subsystem of a new energy base containing energy storage in the complex frequency domain; It is the smallest positive eigenvalue of the extended admittance matrix of the original system; It is a two-dimensional identity matrix.

[0021] Furthermore, the minimum positive eigenvalue of the extended admittance matrix of the original system The results were obtained through numerical calculations, specifically including:

[0022] The orthogonal decomposition method is used to perform eigenvalue decomposition on the extended admittance matrix of the original system, obtaining all eigenvalues ​​of the extended admittance matrix of the original system. Then, the smallest positive value among all eigenvalues ​​is selected as the smallest positive eigenvalue. .

[0023] Furthermore, the expression for the generalized operating short-circuit ratio is:

[0024] ;

[0025] in, This represents finding the smallest positive eigenvalue of the matrix. Voltage at grid connection nodes of new energy bases; To provide active power to the new energy base; This is the system parameter matrix, and it is positively correlated with the voltage support capability.

[0026] Furthermore, the critical condition for voltage support capability The expression is:

[0027] ;

[0028] in, This represents the unknown generalized operating short-circuit ratio in solving the equation. The principal component at critical stability of the system Derivative eigenvalues;

[0029] When the new energy base relies solely on phase-locked loop control parameters, the critical condition for the voltage support capability is... After simplification, we get:

[0030] ;

[0031] in, This is the proportional gain of the phase-locked loop. These are the integral coefficients of the phase-locked loop;

[0032] When the generalized operating short-circuit ratio Greater than or equal to the critical condition of voltage support capability ,Right now If the voltage support capability of the new energy base is sufficient to ensure the stable operation of the system, then it can be determined that the new energy base can guarantee the stable operation of the system.

[0033] Furthermore, the energy storage optimization configuration model is as follows:

[0034]

[0035] ;

[0036] in, The generalized operating short-circuit ratio of the power system after configuring n energy storage units; , These represent the minimum and maximum energy storage charging power, respectively. , These represent the minimum and maximum energy storage discharge power, respectively. , These represent the energy storage charging and discharging power at time t, respectively. Let t be the energy storage capacity; , These represent the minimum and maximum energy storage capacities, respectively. The energy storage state of charge at time t; , These represent the minimum and maximum states of charge of the energy storage, respectively.

[0037] Further, step S5 includes:

[0038] Iteration initialization: Input the power system parameters collected in step S1, and set the initial value of the iteration number. and preset iteration rounds ;

[0039] Solving for the extended admittance matrix: Based on the closed-loop characteristic equation of the power system, solve for the extended admittance matrix of the power system in the current iteration state. The expression is:

[0040] ;

[0041] in, The system structure matrix configured for round j. This is the node voltage and power parameter matrix after the (j-1)th iteration;

[0042] Node parameter update: Based on power flow calculations, update the node voltage and power parameters using the following expression:

[0043] ;

[0044] in, The operating voltage of node n obtained from power flow calculations after adding the energy storage converter in the (j-1)th round. The power absorbed by the energy storage device in the (j-1)th round, The output power of node μ before the installation of the energy storage device in round j-1. Let be the equivalent net output power of node μ after the (j-1)th iteration;

[0045] Determining energy storage configuration parameters: Calculate the generalized operating short-circuit ratio of the current power system, combine it with the energy storage optimization configuration model constructed in step S4, determine the power and capacity parameters of energy storage in this iteration, and select weak voltage support nodes as energy storage installation nodes;

[0046] Iteration termination judgment: Let ,like If the condition is met, the iteration terminates, and the output includes the energy storage configuration scheme, including the installation node, power, and capacity of each energy storage unit; otherwise, it returns to the extended admittance matrix solution step to continue the iteration.

[0047] Furthermore, the power flow calculation adopts the Newton-Raphson method, and its iterative convergence criterion is: the infinite norm of the node voltage deviation is less than the threshold, or the maximum number of iterations is greater than the threshold; if the number of iterations exceeds the maximum number of iterations and still fails to converge, the initial power injection value of the node is adjusted and the calculation is repeated.

[0048] Secondly, the present invention provides an energy storage optimization configuration system for improving the voltage support capability of new energy bases, comprising:

[0049] The data acquisition module is used to collect power system parameters of the target new energy base;

[0050] A module for constructing voltage support strength characterization indicators is used to establish a characteristic sub-power system matrix for new energy bases containing energy storage based on the characteristic subspace perturbation theory; and to define the generalized operating short-circuit ratio by combining the dynamic stability characteristics of the inverse matrix of the power system closed-loop transfer function. As a quantitative evaluation index of voltage support strength ;

[0051] The voltage support capability determination module is used to derive the critical conditions for voltage support capability by mapping the coupling relationship between the reactive power output of renewable energy power plants and the voltage at grid connection nodes. And set the voltage support capability criterion as ;

[0052] The module for establishing an energy storage optimization configuration model is used to construct an energy storage optimization configuration model with the objective function of maximizing the generalized short-circuit ratio of new energy bases, while setting constraints on energy storage charging and discharging power, capacity, and state of charge.

[0053] The multi-round iterative energy storage configuration execution module is used to gradually add energy storage devices to the original power system under the worst operating conditions using a q-round iterative approach. In each round, the extended admittance matrix equation of the power system is solved and the node parameters are updated by combining power flow calculations to determine the energy storage installation nodes and configuration parameters, until the preset number of iterations is reached.

[0054] The simulation verification module is used to verify energy storage devices through simulation analysis, in order to modify the power system equivalent network to adjust the generalized operating short-circuit ratio without changing the critical value of the voltage support capability criterion. Based on the principle of configuring energy storage for new energy bases, the goal is to achieve this.

[0055] The beneficial effects of this invention are as follows: By constructing a generalized operating short-circuit ratio index, setting criteria, establishing a model, conducting multiple iterations, and verifying the mechanism to complete the overall method for optimizing energy storage configuration, the problem of insufficient voltage support capability in new energy bases is systematically solved; by introducing the generalized operating short-circuit ratio as a voltage support strength index, constructing a multi-constraint optimization model, and adopting a multi-round iterative configuration strategy, the precise determination of energy storage installation nodes, power, and capacity is achieved, significantly improving the voltage support capability of new energy bases and providing technical support for improving the voltage support capability of new energy bases and ensuring the stable operation of the power system. Attached Figure Description

[0056] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, use the same reference numerals to denote the same or similar parts. The illustrative embodiments of this application and their descriptions are used to explain this application and do not constitute an undue limitation of this application. In the drawings:

[0057] Figure 1 This is a flowchart of one embodiment of the present invention. Detailed Implementation

[0058] In a first aspect, this invention discloses an energy storage optimization configuration method that considers improving the voltage support capability of new energy bases, such as... Figure 1 The steps shown are as follows:

[0059] S1: Collect power system parameters of the target new energy base;

[0060] S2: Based on the eigenspace perturbation theory, a eigensystem matrix of a new energy base including energy storage is established; combining the dynamic stability characteristics of the inverse matrix of the power system closed-loop transfer function, the generalized operating short-circuit ratio is defined. As a quantitative evaluation index of voltage support strength ;

[0061] S3: By mapping the coupling relationship between the reactive power output of renewable energy power plants and the voltage at grid connection nodes, the critical condition for voltage support capability is derived. And set the voltage support capability criterion as ;

[0062] S4: With the objective function of maximizing the generalized short-circuit ratio of the new energy base, and setting constraints on energy storage charging and discharging power, capacity, and state of charge, an energy storage optimization configuration model is constructed.

[0063] S5: For the original power system under the worst operating condition, energy storage devices are added step by step using a q-round iterative method. In each round, the extended admittance matrix equation of the power system is solved and the node parameters are updated by combining power flow calculations to determine the energy storage installation nodes and configuration parameters, until the preset number of iterations is reached.

[0064] S6: The mechanism of operation of energy storage devices is verified through simulation analysis, clarifying that it adjusts the generalized operating short-circuit ratio by modifying the equivalent network of the power system, but does not change the critical value of the voltage support capability criterion. Configure energy storage.

[0065] This invention provides a comprehensive method for optimizing energy storage configuration by constructing a generalized operating short-circuit ratio index, setting criteria, establishing a model, conducting multiple iterations, and verifying the mechanism. This systematically solves the problem of insufficient voltage support capacity in new energy bases. By introducing the generalized operating short-circuit ratio as a voltage support strength index, constructing a multi-constraint optimization model, and adopting a multi-round iterative configuration strategy, the invention achieves accurate determination of energy storage installation nodes, power, and capacity, significantly improving the voltage support capacity of new energy bases and providing technical support for enhancing the voltage support capacity of new energy bases and ensuring the stable operation of the power system.

[0066] According to one embodiment of this application, the power system parameters of the target new energy base include network structure data, equipment parameter data, and operating status data;

[0067] The network structure data includes the connection relationships of nodes within the base and the impedance of transmission lines;

[0068] The equipment parameter data includes the core parameters of the new energy unit and the inherent parameters of the energy storage device. and the control parameters (proportional coefficient) of the phase-locked loop of the equipment. Integral coefficient );

[0069] The operational status data includes real-time voltage data of each node at the base under different operating conditions. and output active power real-time data The different operating conditions include worst-case operating conditions, such as full-capacity operation of new energy units and peak load periods, to ensure the effectiveness of the configuration. Real-time voltage data. and output active power real-time data The data sampling frequency should not be less than 1Hz; alternatively, the following methods can be used: The criteria for removing outliers include calculating the average node voltage and average power. and corresponding standard deviation , Eliminate those that meet the requirements , The sample; if there are records of extreme faults (such as unit disconnection from the grid or line tripping) in the new energy base, it is necessary to manually confirm whether the abnormal sample is the worst operating condition data in combination with the fault record to avoid accidental rejection.

[0070] According to one embodiment of this application, the expression for the characteristic sub-power system matrix of the new energy base is as follows:

[0071] ;

[0072] in, This is the eigenspace of the original system matrix; This is the inverse matrix of the original system; The right eigenvector matrix; The core dynamic impedance matrix of the characteristic subsystem of a new energy base containing energy storage in the complex frequency domain; It is the smallest positive eigenvalue of the extended admittance matrix of the original system; It is a two-dimensional identity matrix.

[0073] This embodiment, based on the eigenspace perturbation theory, treats the new energy base containing energy storage as a whole system and establishes an eigensystem matrix that can approximately characterize its stability. This matrix is ​​constructed by integrating parameters such as the eigenspace of the original system matrix, the inverse matrix of the original system, the right eigenvector matrix, and the minimum positive eigenvalue of the extended admittance matrix of the original system. It can accurately reflect the inherent stability characteristics of the power system after the integration of energy storage.

[0074] According to one embodiment of this application, the minimum positive eigenvalue of the original system's extended admittance matrix is... The results were obtained through numerical calculations, specifically including:

[0075] The eigenvalues ​​of the original system's extended admittance matrix are decomposed using the orthogonal decomposition method (QR decomposition method) to obtain all eigenvalues ​​of the original system's extended admittance matrix. Then, the smallest positive value among all eigenvalues ​​is selected as the smallest positive eigenvalue. The QR decomposition method is a mature and reliable algorithm for calculating eigenvalues, ensuring the accuracy of λy calculation. High-precision λy guarantees accurate calculation of the generalized operating short-circuit ratio, thus avoiding misjudgments caused by numerical calculation errors and improving the overall reliability of the method.

[0076] According to one embodiment of this application, the expression for the Generalized Operating Short-Circuit Ratio (GOSCR) is:

[0077] ;

[0078] in, This represents finding the smallest positive eigenvalue of the matrix. Voltage at grid connection nodes of new energy bases; To provide active power to the new energy base; This is the system parameter matrix, and it is positively correlated with the voltage support capability.

[0079] This application innovatively defines the generalized operating short-circuit ratio as a quantitative evaluation index of voltage support strength. By calculating the minimum positive eigenvalue of a specific matrix, the generalized operating short-circuit ratio value is obtained. The generalized operating short-circuit ratio index overcomes the limitations of the traditional short-circuit ratio (SCR) and can more comprehensively and accurately quantify and evaluate the voltage support strength of new energy bases with energy storage. Its positive correlation with voltage support capability provides a clear and reliable quantitative target for optimal configuration.

[0080] According to one embodiment of this application, the voltage support capability critical condition The expression is:

[0081] ;

[0082] in, This represents the unknown generalized operating short-circuit ratio in solving the equation. The dominant eigenvalue when the system is critically stable;

[0083] When the new energy base relies solely on phase-locked loop control parameters, the critical condition for the voltage support capability is... After simplification, we get:

[0084] ;

[0085] in, This is the proportional gain of the phase-locked loop. These are the integral coefficients of the phase-locked loop;

[0086] When the generalized operating short-circuit ratio Greater than or equal to the critical condition of voltage support capability ,Right now If the voltage support capability of the new energy base is sufficient to ensure the stable operation of the system, then it can be determined that the new energy base can guarantee the stable operation of the system.

[0087] The critical condition for voltage support capability This is obtained by solving equations where the determinant of a specific matrix is ​​zero, reflecting the minimum voltage support strength required for the system to maintain voltage stability. When the voltage support of a new energy base depends solely on the phase-locked loop control parameters of the equipment, a simplified critical condition for voltage support capability can be further derived. Its calculation only requires the proportional gain, integral gain, and dominant characteristic value of the phase-locked loop at critical stability. The final voltage support capability criterion is set as "system..." When this condition is met, it is determined that the voltage support capability of the new energy base can ensure the stable operation of the system. This criterion becomes the core standard for whether the subsequent energy storage configuration meets the requirements.

[0088] According to one embodiment of this application, the energy storage optimization configuration model is as follows:

[0089]

[0090] ;

[0091] in, The generalized operating short-circuit ratio of the power system after configuring n energy storage units; , These represent the minimum and maximum energy storage charging power, respectively. , These represent the minimum and maximum energy storage discharge power, respectively. , These represent the energy storage charging and discharging power at time t, respectively. Let t be the energy storage capacity; , These represent the minimum and maximum energy storage capacities, respectively. The energy storage state of charge at time t; , These represent the minimum and maximum states of charge of the energy storage, respectively.

[0092] This embodiment uses maximizing the generalized operating short-circuit ratio of the new energy base as the objective function, ensuring that the core objective of energy storage configuration focuses on improving voltage support capability—through reasonable energy storage configuration, the generalized operating short-circuit ratio of the system is increased as much as possible until the voltage support capability criterion is met. Simultaneously, to ensure the safe and efficient operation of energy storage equipment, three types of constraints are set: firstly, charging and discharging power (… The energy storage system employs three main constraints: first, power limits during charging and discharging to prevent power from exceeding the device's tolerance range; second, capacity (H) constraints to define the energy storage capacity range and ensure that the energy storage can meet the system's energy regulation needs at different times; and third, state of charge (SOC) constraints to control the SOC of the energy storage within a reasonable range to prevent overcharging or over-discharging from adversely affecting the lifespan of the energy storage device. These objective functions and constraints together constitute a complete energy storage optimization configuration model, providing a mathematical framework for determining energy storage parameters.

[0093] According to one embodiment of this application, step S5 includes:

[0094] Iteration initialization: Input the power system parameters collected in step S1, and set the initial value of the iteration number. and preset iteration rounds Based on the scale of the base, large bases are designated as such. Values ​​range from 3 to 5, for small to medium-sized bases. Values ​​range from 1 to 3;

[0095] Solving for the extended admittance matrix: Based on the closed-loop characteristic equation of the power system, solve for the extended admittance matrix of the power system in the current iteration state. The expression is:

[0096] ;

[0097] in, The system structure matrix configured for round j. This is the node voltage and power parameter matrix after the (j-1)th iteration;

[0098] Node parameter update: Based on power flow calculations, update the node voltage and power parameters using the following expression:

[0099] ;

[0100] in, The operating voltage of node n obtained from power flow calculations after adding the energy storage converter in the (j-1)th round. The power absorbed by the energy storage device in the (j-1)th round, The output power of node μ before the installation of the energy storage device in round j-1. Let be the equivalent net output power of node μ after the (j-1)th iteration;

[0101] Determining energy storage configuration parameters: Calculate the generalized short-circuit ratio of the current power system, combine it with the energy storage optimization configuration model constructed in step S4, determine the power and capacity parameters of energy storage in this iteration, and select weak voltage support nodes (nodes with the smallest generalized short-circuit ratio) as energy storage installation nodes;

[0102] Iteration termination judgment: Let ,like If the condition is met, the iteration terminates, and the output includes the energy storage configuration scheme, including the installation node, power, and capacity of each energy storage unit; otherwise, it returns to the extended admittance matrix solution step to continue the iteration.

[0103] This embodiment addresses the original system under worst-case operating conditions by gradually adding energy storage devices through multiple iterations, achieving dynamic optimization of energy storage configuration. Compared to traditional single-stage configuration methods, it can dynamically optimize energy storage parameters based on the system state after each iteration, gradually increasing the generalized short-circuit ratio to meet the voltage support criterion, avoiding parameter redundancy or insufficiency caused by one-time configuration. Simultaneously, the power flow calculation using the Newton-Raphson method can accurately reflect node voltage and power changes, providing a reliable basis for selecting energy storage installation nodes, balancing the economy and effectiveness of configuration.

[0104] According to one embodiment of this application, the power flow calculation adopts the Newton-Raphson method, and its iterative convergence criterion is: the infinity norm of the node voltage deviation is less than a threshold, or the maximum number of iterations is greater than a threshold (10⁻⁻⁶). 5 If the number of iterations exceeds the maximum number of iterations (50) and still does not converge, adjust the initial power injection value of the node (with a deviation of no more than 5%) and recalculate.

[0105] According to one embodiment of this application, step S6 verifies the mechanism by which energy storage enhances the voltage support capability of new energy bases through a combination of theoretical derivation and simulation analysis. It clarifies that the energy storage device improves the voltage support capability by modifying the parameters of the system's equivalent network, thereby adjusting the system's generalized operating short-circuit ratio; simultaneously, the energy storage device does not change the critical value of the voltage support capability criterion determined in step 3. A system model consistent with the actual site was constructed through electromagnetic transient simulation. The generalized operating short-circuit ratio before and after energy storage commissioning was compared with... The changes will verify the correctness of the above mechanism and ensure the theoretical rationality and engineering feasibility of the energy storage configuration scheme.

[0106] Secondly, the present invention provides an energy storage optimization configuration system for improving the voltage support capability of new energy bases, comprising:

[0107] The data acquisition module is used to collect power system parameters of the target new energy base;

[0108] A module for constructing voltage support strength characterization indicators is used to establish a characteristic sub-power system matrix for new energy bases containing energy storage based on the characteristic subspace perturbation theory; and to define the generalized operating short-circuit ratio by combining the dynamic stability characteristics of the inverse matrix of the power system closed-loop transfer function. As a quantitative evaluation index of voltage support strength ;

[0109] The voltage support capability determination module is used to derive the critical conditions for voltage support capability by mapping the coupling relationship between the reactive power output of renewable energy power plants and the voltage at grid connection nodes. And set the voltage support capability criterion as ;

[0110] The module for establishing an energy storage optimization configuration model is used to construct an energy storage optimization configuration model with the objective function of maximizing the generalized short-circuit ratio of new energy bases, while setting constraints on energy storage charging and discharging power, capacity, and state of charge.

[0111] The multi-round iterative energy storage configuration execution module is used to gradually add energy storage devices to the original power system under the worst operating conditions using a q-round iterative approach. In each round, the extended admittance matrix equation of the power system is solved and the node parameters are updated by combining power flow calculations to determine the energy storage installation nodes and configuration parameters, until the preset number of iterations is reached.

[0112] The simulation verification module is used to verify energy storage devices through simulation analysis, in order to modify the power system equivalent network to adjust the generalized operating short-circuit ratio without changing the critical value of the voltage support capability criterion. Based on the principle of configuring energy storage for new energy bases, the goal is to achieve this.

[0113] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for optimizing energy storage configuration considering the improvement of voltage support capability in new energy bases, characterized in that, Includes the following steps: S1: Collect power system parameters of the target new energy base; S2: Based on the perturbation theory of eigenspace, establish the eigensystem matrix of the new energy base with energy storage; combine the dynamic stability characteristics of the inverse matrix of the closed-loop transfer function of the power system, and define the generalized operating short-circuit ratio as a quantitative evaluation index of voltage support strength. S3: By mapping the coupling relationship between the reactive power output of new energy power plants and the voltage of grid-connected nodes, the critical condition for voltage support capability is derived, and the voltage support capability criterion is set as follows; S4: With the objective function of maximizing the generalized short-circuit ratio of the new energy base, and setting constraints on energy storage charging and discharging power, capacity, and state of charge, an energy storage optimization configuration model is constructed. S5: For the original power system under the worst operating conditions, energy storage devices are added step by step in an iterative round. In each round, the extended admittance matrix equation of the power system is solved and the node parameters are updated by combining power flow calculations to determine the energy storage installation nodes and configuration parameters, until the preset number of rounds is reached. S6: Verify the working mechanism of energy storage devices through simulation analysis, and clarify that they adjust the generalized operating short-circuit ratio by modifying the equivalent network of the power system, but do not change the critical value of the voltage support capability criterion, and then configure energy storage.

2. The energy storage optimization configuration method considering the improvement of voltage support capability of new energy bases according to claim 1, characterized in that, The power system parameters of the target new energy base include network structure data, equipment parameter data, and operating status data; The network structure data includes the connection relationships of nodes within the base and the impedance of transmission lines; The equipment parameter data includes the core parameters of the new energy unit, the inherent parameters of the energy storage device, and the control parameters of the phase-locked loop of the device. The operational status data includes real-time voltage data and real-time output active power data of each node under different operating conditions of the base; the different operating conditions include the worst operating condition.

3. The energy storage optimization configuration method considering the improvement of voltage support capability of new energy bases according to claim 1, characterized in that, The expression for the characteristic sub-power system matrix of the new energy base is: ； in, This is the eigenspace of the original system matrix; This is the inverse matrix of the original system; The right eigenvector matrix; The core dynamic impedance matrix of the characteristic subsystem of a new energy base containing energy storage in the complex frequency domain; It is the smallest positive eigenvalue of the extended admittance matrix of the original system; It is a two-dimensional identity matrix.

4. The energy storage optimization configuration method considering the improvement of voltage support capability of new energy bases according to claim 3, characterized in that, The smallest positive eigenvalue of the extended admittance matrix of the original system The results were obtained through numerical calculations, specifically including: The orthogonal decomposition method is used to perform eigenvalue decomposition on the extended admittance matrix of the original system, obtaining all eigenvalues ​​of the extended admittance matrix of the original system. Then, the smallest positive value among all eigenvalues ​​is selected as the smallest positive eigenvalue. .

5. The energy storage optimization configuration method considering the improvement of voltage support capability of new energy bases according to claim 1, characterized in that, The expression for the generalized operating short-circuit ratio is: ； in, This represents finding the smallest positive eigenvalue of the matrix. Voltage at grid connection nodes of new energy bases; To provide active power to the new energy base; This is the system parameter matrix, and it is positively correlated with the voltage support capability.

6. The energy storage optimization configuration method considering the improvement of voltage support capability of new energy bases according to claim 1 or 5, characterized in that, The critical condition of voltage support capability The expression is: ； in, This represents the unknown generalized operating short-circuit ratio in solving the equation. The principal component at critical stability of the system Derivative eigenvalues; When the new energy base relies solely on phase-locked loop control parameters, the critical condition for the voltage support capability is... After simplification, we get: ； in, This is the proportional gain of the phase-locked loop. These are the integral coefficients of the phase-locked loop; When the generalized operating short-circuit ratio Greater than or equal to the critical condition of voltage support capability ,Right now If the voltage support capability of the new energy base is sufficient to ensure the stable operation of the system, then it can be determined that the new energy base can guarantee the stable operation of the system.

7. The energy storage optimization configuration method considering the improvement of voltage support capability of new energy bases according to claim 1, characterized in that, The energy storage optimization configuration model is as follows: ； in, The generalized operating short-circuit ratio of the power system after configuring n energy storage units; , These represent the minimum and maximum energy storage charging power, respectively. , These represent the minimum and maximum energy storage discharge power, respectively. , These represent the energy storage charging and discharging power at time t, respectively. Let t be the energy storage capacity; , These represent the minimum and maximum energy storage capacities, respectively. The energy storage state of charge at time t; , These represent the minimum and maximum states of charge of the energy storage, respectively.

8. The energy storage optimization configuration method considering the improvement of voltage support capability of new energy bases according to claim 1, characterized in that, Step S5 includes: Iteration initialization: Input the power system parameters collected in step S1, and set the initial value of the iteration number. and preset iteration rounds ; Solving for the extended admittance matrix: Based on the closed-loop characteristic equation of the power system, solve for the extended admittance matrix of the power system in the current iteration state. The expression is: ； in, The system structure matrix configured for round j. This is the node voltage and power parameter matrix after the (j-1)th iteration; Node parameter update: Based on power flow calculations, update the node voltage and power parameters using the following expression: ； in, The operating voltage of node n obtained from power flow calculations after adding the energy storage converter in the (j-1)th round. The power absorbed by the energy storage device in the (j-1)th round, The output power of node μ before the installation of the energy storage device in round j-1. Let be the equivalent net output power of node μ after the (j-1)th iteration; Determining energy storage configuration parameters: Calculate the generalized operating short-circuit ratio of the current power system, combine it with the energy storage optimization configuration model constructed in step S4, determine the power and capacity parameters of energy storage in this iteration, and select weak voltage support nodes as energy storage installation nodes; Iteration termination judgment: Let ,like If the condition is met, the iteration terminates, and the output includes the energy storage configuration scheme, including the installation node, power, and capacity of each energy storage unit; otherwise, it returns to the extended admittance matrix solution step to continue the iteration.

9. The energy storage optimization configuration method considering the improvement of voltage support capability of new energy bases according to claim 8, characterized in that, The power flow calculation adopts the Newton-Raphson method, and its iterative convergence criterion is: the infinite norm of the node voltage deviation is less than the threshold, or the maximum number of iterations is greater than the threshold. If convergence is not achieved after exceeding the maximum number of iterations, the initial power injection value of the node is adjusted and the calculation is repeated.

10. An energy storage optimization configuration system considering the improvement of voltage support capability in new energy bases, characterized in that, include: The data acquisition module is used to collect power system parameters of the target new energy base; A module for constructing voltage support strength characterization indicators is used to establish a characteristic sub-power system matrix for new energy bases containing energy storage based on the characteristic subspace perturbation theory; and to define the generalized operating short-circuit ratio by combining the dynamic stability characteristics of the inverse matrix of the power system closed-loop transfer function. As a quantitative evaluation index of voltage support strength ; The voltage support capability determination module is used to derive the critical conditions for voltage support capability by mapping the coupling relationship between the reactive power output of renewable energy power plants and the voltage at grid connection nodes. And set the voltage support capability criterion as ; The module for establishing an energy storage optimization configuration model is used to construct an energy storage optimization configuration model with the objective function of maximizing the generalized short-circuit ratio of new energy bases, while setting constraints on energy storage charging and discharging power, capacity, and state of charge. The multi-round iterative energy storage configuration execution module is used to gradually add energy storage devices to the original power system under the worst operating conditions using a q-round iterative approach. In each round, the extended admittance matrix equation of the power system is solved and the node parameters are updated by combining power flow calculations to determine the energy storage installation nodes and configuration parameters, until the preset number of iterations is reached. The simulation verification module is used to verify energy storage devices through simulation analysis, in order to modify the power system equivalent network to adjust the generalized operating short-circuit ratio without changing the critical value of the voltage support capability criterion. Based on the principle of configuring energy storage for new energy bases, the goal is to achieve this.

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