Evaluation method and system for improving transmission capacity of key sections by grid-connected energy storage

Abstract

The present invention provides an evaluation method and system for improving the transmission capacity of a key section by using a grid-type energy storage, and relates to the technical field of safety analysis of a grid-type energy storage power system, including: considering the influence of the grid-type energy storage on the Thevenin equivalent impedance of the system after the grid-type energy storage is connected and the virtual synchronous generator control adopted by the grid-type energy storage, changing the connection position of the grid-type energy storage and the relevant parameters of the virtual synchronous generator control, respectively calculating and obtaining the grid voltage support strength characteristics and the grid frequency support strength characteristics under different change scenarios; inputting the grid operation characteristics, grid voltage support strength characteristics and grid frequency support strength characteristics under different change scenarios into a rapid evaluation model of the maximum transmission capacity of a key section for sending new energy power, obtaining the change of the maximum transmission capacity of the section before and after the grid-type energy storage is connected, and rapidly evaluating the effect of the grid-type energy storage on improving the transmission capacity of the key section for sending new energy power.

Description

Technical Field

[0001] The present disclosure relates to the technical field of safety analysis of grid-type energy storage power systems, and in particular to an evaluation method and system for improving the transmission capacity of key sections by grid-type energy storage. Background Art

[0002] The statements in this section merely provide background information related to the present disclosure and do not necessarily constitute prior art.

[0003] For traditional power systems dominated by synchronous generators, synchronous generators can independently establish voltage and provide voltage and frequency regulation and support capabilities for the power system to support the safe and stable operation of the system. With the rapid development and large-scale access of renewable energy power generation, a large number of synchronous generators have been replaced by renewable energy power generation. Renewable energy power generation is connected to the power system through power electronic converters, which lack the voltage and frequency support capabilities of synchronous generators. In order to ensure the safe and stable operation of high-proportion renewable energy power generation systems, grid-type energy storage has received increasing attention. It has the advantages of energy storage and rapid power response, and can provide voltage and frequency support capabilities for the power grid through grid-type control technologies such as virtual synchronous generators, supporting the effective delivery of renewable energy power through key transmission sections.

[0004] After the grid-type energy storage is connected to the power system, it can provide voltage and frequency support capabilities for the system, improve the safe operation level of the power grid, and then improve the maximum transmission capacity of key sections such as the power transmission section of new energy generation. In terms of the support capacity analysis of grid-type energy storage, there is a method that uses the short-circuit ratio index to measure the voltage support strength of the power system at a certain node after the grid-type energy storage is connected, and uses the equivalent inertia improvement factor and the steady-state frequency deviation reduction factor to measure the frequency support strength of the power grid after the grid-type energy storage is connected, but the equivalent inertia improvement factor and the steady-state frequency deviation reduction factor need to be simulated in the time domain when calculating. There is also a method that uses the virtual inertia coefficient and the primary frequency modulation coefficient to measure the frequency support strength of the power grid after the grid-type energy storage is connected. In terms of the transmission capacity calculation of the key sections of the power grid, there is a method that calculates the transmission capacity of the key sections based on power flow calculation and time domain simulation, but the calculation takes a long time. In order to improve the calculation speed of the transmission capacity, there is a method that uses machine learning technologies such as neural networks to construct a rapid evaluation model of the maximum transmission capacity.

[0005] However, the existing evaluation methods for the role of grid-type energy storage in improving the transmission capacity of key sections still have the following shortcomings:

[0006] (1) Existing research mainly analyzes the supporting role of grid-connected energy storage on voltage and frequency from the perspective of the entire system. There is still a lack of in-depth research on the role of grid-connected energy storage in improving the transmission capacity of key sections for the transmission of new energy power, and no specific evaluation indicators for improving the role have been proposed.

[0007] (2) In the existing machine learning-based rapid assessment methods for section transmission capacity, the operating characteristics of the power grid are mainly considered when constructing the input feature set. In the process of transmission capacity assessment, it is difficult to consider the role of different grid-connected energy storage access and configuration schemes in improving the safe operation level of the system. Summary of the invention

[0008] In order to solve the above problems, the present disclosure proposes an evaluation method and system for improving the transmission capacity of key sections by using grid-type energy storage, constructs evaluation indicators for the voltage support strength and the frequency support strength of the power grid, and constructs a total transfer capability (TTC) evaluation model for key sections that can consider the voltage and frequency support effects of the grid-type energy storage based on the evaluation indicators; for different grid-type energy storage access and configuration schemes, the change in section transmission capacity is calculated, and evaluation indicators are constructed to evaluate the effect of grid-type energy storage on improving the transmission capacity of key sections for sending out new energy power.

[0009] According to some embodiments, the present disclosure adopts the following technical solutions:

[0010] The evaluation method of grid-type energy storage to improve the transmission capacity of key sections includes:

[0011] Obtain the maximum transmission capacity of the grid for the key section of new energy power transmission before access to the grid-building energy storage as a benchmark reference value;

[0012] Establish a maximum transmission capacity assessment model for key sections of new energy power transmission;

[0013] Based on the typical output scenario set of new energy stations, the grid operation characteristics are obtained;

[0014] By changing the access location of the grid-connected energy storage and the relevant parameters of the virtual synchronous generator control, the grid voltage support strength characteristics and grid frequency support strength characteristics under different change scenarios are calculated and obtained respectively;

[0015] The grid operation characteristics, grid voltage support strength characteristics, and grid frequency support strength characteristics under different change scenarios are input into the maximum transmission capacity assessment model for key sections of renewable energy power delivery. Combined with the benchmark reference value, the changes in the maximum transmission capacity of the section before and after the access of grid-connected energy storage are obtained to evaluate the effect of grid-connected energy storage on improving the transmission capacity of key sections of renewable energy power delivery.

[0016] According to some embodiments, the present disclosure adopts the following technical solutions:

[0017] The evaluation system for grid-type energy storage to improve the transmission capacity of key sections includes:

[0018] An initialization module is used to obtain the maximum transmission capacity of the power grid for the key section of new energy power transmission before the grid-building energy storage is connected, as a benchmark reference value;

[0019] Model building module, used to establish a maximum transmission capacity assessment model for key sections of new energy power transmission;

[0020] The voltage support strength evaluation index and frequency support strength evaluation index calculation module are used to obtain the grid operation characteristics for the typical output scenario set of new energy stations; the access location of the grid-type energy storage and the relevant parameters of the virtual synchronous generator control are changed to calculate the grid voltage support strength characteristics and the grid frequency support strength characteristics under different change scenarios;

[0021] The maximum transmission capacity rapid assessment module is used to input the grid operation characteristics, grid voltage support strength characteristics and grid frequency support strength characteristics under different change scenarios into the maximum transmission capacity assessment model of the key section for the transmission of new energy power, and combine the benchmark reference value to obtain the changes in the maximum transmission capacity of the section before and after the grid-connected energy storage;

[0022] The grid-type energy storage effect evaluation module is used to evaluate the effect of grid-type energy storage on improving the transmission capacity of key sections for the transmission of new energy power.

[0023] According to some embodiments, the present disclosure adopts the following technical solutions:

[0024] A computer program product includes a computer program, and when the computer program is executed by a processor, the evaluation method for improving the power transmission capacity of key sections by grid-type energy storage is implemented.

[0025] According to some embodiments, the present disclosure adopts the following technical solutions:

[0026] A non-transitory computer-readable storage medium is used to store computer instructions. When the computer instructions are executed by a processor, the evaluation method for improving the power transmission capacity of key sections by using grid-type energy storage is implemented.

[0027] According to some embodiments, the present disclosure adopts the following technical solutions:

[0028] An electronic device comprises: a processor, a memory and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory, so that the electronic device executes the evaluation method for improving the power transmission capacity of key sections by implementing the grid-type energy storage.

[0029] Compared with the prior art, the present invention has the following beneficial effects:

[0030] The present invention discloses an evaluation method for improving the transmission capacity of a key section by using a grid-type energy storage. The method considers the influence of the grid-type energy storage on the Thevenin equivalent impedance of the system after the grid-type energy storage is connected, and uses the short-circuit ratio as an evaluation index of the voltage support strength of the grid; considers the typical virtual synchronous generator control, and uses the virtual inertia and the primary frequency modulation coefficient as the evaluation index of the frequency support strength of the grid; on the basis of the voltage and frequency support strength evaluation index, a critical section maximum transmission capacity (total transfer capability, TTC) evaluation model that can consider the voltage and frequency support role of the grid-type energy storage is constructed; for different grid-type energy storage access and configuration schemes, the change of the section transmission capacity is calculated, the evaluation index is constructed, the improvement effect of the grid-type energy storage on the transmission capacity of the key section of the new energy power transmission is evaluated, and the transmission capacity evaluation model of the key section of the new energy power transmission is established. When constructing the input feature set, the evaluation index of the voltage and frequency support role of the grid-type energy storage is considered, which can effectively take into account the improvement effect of the grid-type energy storage on the safe operation level of the system, and realize the rapid calculation of the maximum transmission capacity.

[0031] The present invention discloses an evaluation method for improving the transmission capacity of key sections by using grid-type energy storage. The proposed evaluation method for the effect of grid-type energy storage on improving the transmission capacity of key sections can comprehensively consider the voltage and frequency support provided by the grid-type energy storage, establish quantitative evaluation indicators for the effect of improving the transmission capacity, and realize accurate evaluation of the effect of grid-type energy storage on improving the transmission capacity of sections. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] The accompanying drawings constituting a part of the present disclosure are used to provide a further understanding of the present disclosure. The illustrative embodiments of the present disclosure and their descriptions are used to explain the present disclosure and do not constitute an improper limitation on the present disclosure.

[0033] Figure 1 It is a block diagram of active power-frequency control of a virtual synchronous generator control according to an embodiment of the present disclosure;

[0034] Figure 2 A flow chart for generating a maximum power transmission capacity evaluation training sample provided by an embodiment of the present disclosure;

[0035] Figure 3 A rapid assessment model for the maximum power transmission capacity of a key section provided in an embodiment of the present disclosure;

[0036] Figure 4 Schematic diagram of an evaluation system for improving the power transmission capacity of key sections by grid-connected energy storage provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0037] The present disclosure is further described below in conjunction with the accompanying drawings and embodiments.

[0038] It should be noted that the following detailed descriptions are all illustrative and are intended to provide further explanation of the present disclosure. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present disclosure belongs.

[0039] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present disclosure. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0040] Example 1

[0041] In one embodiment of the present disclosure, a method for evaluating the improvement of power transmission capacity of key sections by grid-connected energy storage is provided, comprising:

[0042] Step 1: Obtain the maximum transmission capacity of the power grid for the key section of new energy power transmission before connecting to the grid-connected energy storage, as a benchmark reference value;

[0043] Step 2: Establish a rapid assessment model for the maximum transmission capacity of key sections for new energy power transmission;

[0044] Step 3: Obtain the grid operation characteristics for the typical output scenario set of new energy stations; consider the impact of the grid-connected energy storage on the system's Thevenin equivalent impedance and the virtual synchronous generator control adopted by the grid-connected energy storage, change the connection location of the grid-connected energy storage and the relevant parameters of the virtual synchronous generator control, and calculate and obtain the grid voltage support strength characteristics and grid frequency support strength characteristics under different change scenarios;

[0045] Step 4: Input the grid operation characteristics, grid voltage support strength characteristics and grid frequency support strength characteristics under different change scenarios into the rapid assessment model of the maximum transmission capacity of the key section of new energy power delivery, and combine with the benchmark reference value to obtain the change of the maximum transmission capacity of the section before and after the grid-connected energy storage;

[0046] Step 5: Evaluate the effect of grid-connected energy storage on improving the transmission capacity of key sections for the delivery of new energy power.

[0047] As an embodiment, the specific implementation process of the evaluation method of the grid-type energy storage disclosed in the present invention for improving the transmission capacity of key sections is as follows:

[0048] S1: Considering the impact of grid-connected energy storage on the system's Thevenin equivalent impedance, the short-circuit ratio at the grid connection point of the new energy power station is calculated, and the short-circuit ratio is used as an evaluation indicator of the strength of grid-connected energy storage's support for grid voltage;

[0049] In power systems, the short-circuit ratio is usually used to characterize the voltage support strength at a certain node. It represents the ratio of the three-phase short-circuit capacity at the node to the capacity of the connected equipment. The larger the short-circuit ratio, the stronger the voltage support capacity at the node. The calculation expression of the short-circuit ratio is,

[0050]

[0051] Where: SCR i For Node i The short circuit ratio; S ti For Node i Three-phase short-circuit capacity; S ni For Node i The capacity of the equipment connected to the premises, such as the rated capacity of a renewable energy power station.

[0052] The short-circuit ratio can also be calculated by the Thevenin equivalent impedance from the node to the grid, that is,

[0053]

[0054] Where: U ni For Node i Rated voltage; Z i For slave nodes i Thevenin equivalent impedance looking toward the grid; Z ipu is the per-unit value of the Thevenin equivalent impedance.

[0055] Renewable energy generation represented by wind power and photovoltaic power generation can also use grid-connected converters, but their output is random and volatile, making it difficult to provide stable and continuous support for the system. Compared with renewable energy generation, energy storage has the advantage of stable energy reserves and can provide stable support for the power grid for a longer period of time. Therefore, energy storage is a more ideal target for grid-connected control. From a system level, grid-connected energy storage and renewable energy generation exhibit voltage source characteristics, while grid-connected energy storage and renewable energy generation exhibit current source characteristics.

[0056] Furthermore, the short-circuit ratio at the grid connection point of the new energy power station is used to measure the voltage support provided by the grid-connected energy storage. After considering the impact of the grid-connected and grid-connected energy storage and the new energy power generation access system, the grid voltage support strength characteristics are used as the evaluation index of the grid voltage support strength of the grid-connected energy storage. The grid voltage support strength characteristics are specifically the short-circuit ratio at the grid connection point of the new energy power station. After considering the impact of the grid-connected energy storage on the system's Thevenin equivalent impedance, the calculation steps of the short-circuit ratio are as follows:

[0057] (1) Set the synchronous generator power supply in the system to zero. The synchronous generator is represented by an impedance branch to ground, and the impedance value is the sub-transient reactance.

[0058] (2) The grid-connected energy storage and renewable energy generation in the system are represented by the short-circuit branches to the ground at their grid connection points;

[0059] (3) The grid-connected energy storage and renewable energy generation in the system are represented by the open branch to the ground at their grid connection point;

[0060] (4) After completing the above operations, the Thevenin equivalent impedance at the grid connection point of the renewable energy power station is calculated using circuit transformation theory, and then the short-circuit ratio index is calculated.

[0061] S2: Considering the virtual synchronous generator control technology used by the grid-connected energy storage, the virtual inertia coefficient and primary frequency modulation coefficient set in the virtual synchronous generator control are used as evaluation indicators of the grid-connected energy storage's support strength for the grid frequency, and the primary frequency modulation coefficient is verified to be within the range allowed by the converter capacity;

[0062] In step S2, virtual synchronous generator control is the mainstream grid-type control strategy adopted by grid-type energy storage and new energy power generation. Taking this control strategy as an example, the frequency support capability provided by grid-type energy storage after access is analyzed. The active power-frequency control block diagram of virtual synchronous generator control is shown in Figure 1 As shown, the corresponding active power-frequency control equation is,

[0063]

[0064]

[0065] Where: ω and θ are the frequency and angle of the virtual synchronous generator control, respectively; J and D p are the virtual inertia coefficient and damping coefficient of virtual synchronous generator control respectively; P 0 and P e They are respectively the active setting value and actual active output value of the grid-building energy storage; ω 0 is the rated frequency.

[0066] Virtual synchronous generator control can also simulate the primary frequency regulation characteristics of synchronous generators to provide frequency support capabilities for the system. The control equation for simulating the primary frequency regulation characteristics is:

[0067]

[0068] Where: P 0ref It is the active power setting value in the initial state; K f is the primary frequency modulation coefficient.

[0069] Although setting a larger primary frequency modulation coefficient can have a better frequency support effect, it is necessary to ensure that the power output of the grid-type energy storage does not exceed the capacity limit of its converter. Therefore, it is necessary to verify the rationality of the setting of the primary frequency modulation coefficient. The relationship that the primary frequency modulation coefficient needs to satisfy is:

[0070]

[0071] Where: Δ f max is the maximum frequency drop deviation that may occur in the system; S es is the capacity of the energy storage converter; Q es is the reactive power output by the energy storage.

[0072] The frequency support capability of the power grid can be measured mainly from two aspects. One aspect is the inertia support capability of the system, which can directly affect the frequency change rate of the system after a fault occurs. The larger the system inertia, the slower the frequency change rate and the stronger the frequency support capability. The other aspect is the primary frequency regulation capability of the system, which can directly affect the frequency deviation of the system after a fault occurs. The stronger the primary frequency regulation capability of the system, the smaller the frequency deviation and the stronger the frequency support capability. For grid-type energy storage, its inertia support capability and primary frequency regulation capability can be directly reflected by the virtual inertia coefficient and primary frequency regulation coefficient in the control parameters, respectively. Based on the above analysis, the virtual inertia coefficient and primary frequency regulation coefficient set in the grid-type energy storage grid-connected control strategy are used to measure the frequency support function provided by the grid-type energy storage after access.

[0073] S3: For a typical set of output scenarios of new energy stations, change the access location of the grid-type energy storage and the relevant parameters of the virtual synchronous generator control, generate a large number of training samples, calculate the maximum transmission capacity of the key section of new energy power delivery as the sample label, and construct a training sample set;

[0074] The generation process of the maximum transmission capacity evaluation training sample set is as follows: Figure 2 As shown, the specific process is:

[0075] (1) Based on the long-term forecast data of renewable energy power generation, a set of typical output scenarios of renewable energy power generation sites is generated. This is combined with the load forecast data and power generation scheduling plan of the power grid to generate a set of typical operating modes of the system.

[0076] (2) Based on the above typical operation mode set, grid-connected energy storage is added. The capacity of the grid-connected energy storage is kept unchanged, and the location of the grid-connected energy storage, as well as the virtual inertia coefficient and primary frequency modulation coefficient in the virtual synchronous generator control are changed to generate a large number of training sample scenarios.

[0077] (3) The power delivery section of the renewable energy power station is taken as the key transmission section of concern, and the maximum transmission capacity of the section is calculated as the training sample label considering the static and dynamic safety constraints. The specific steps for calculating the maximum transmission capacity are:

[0078] 1) Set a fixed power increase step size to continuously increase the power of renewable energy power stations and grid load power on both sides of the transmission section;

[0079] 2) After each power increase, the system is verified through power flow calculation and time domain simulation to see whether it can meet the static and dynamic safety constraints set after the expected fault occurs, including voltage limit, power flow overload, transient voltage safety and frequency safety constraints;

[0080] 3) If the safety constraint check passes, continue to increase the cross-section transmission power. Otherwise, the current cross-section transmission power minus one power transmission step is the maximum cross-section transmission capacity of the current sample scenario.

[0081] S4: Taking the grid operation characteristics, voltage support strength evaluation index and frequency support strength evaluation index as input features, constructing an input feature set, and establishing a maximum transmission capacity evaluation model for key sections of new energy power delivery based on deep learning technology;

[0082] In step S4, a maximum transmission capacity evaluation model for key sections of new energy power transmission is established based on deep learning technology. The schematic diagram of the evaluation model is as follows: Figure 3 As shown, it mainly includes input feature set construction, convolutional neural network feature extraction and feedforward neural network regression.

[0083] The input characteristics of the maximum transmission capacity assessment model for key sections of renewable energy power delivery mainly include: active and reactive power of synchronous generators in the system, active and reactive power of loads, active and reactive power of DC transmission, active and reactive power of renewable energy generation, and active and reactive power of energy storage. The above characteristics are used to characterize the operating mode of the system. In order to better reflect the supporting role of grid-connected energy storage on system voltage and frequency, the short-circuit ratio at the grid connection point of renewable energy power generation stations, the virtual inertia coefficient of grid-connected energy storage, and the primary frequency regulation coefficient are also selected as input characteristics of the assessment model.

[0084] Since the features such as short circuit ratio, virtual inertia coefficient and primary frequency modulation coefficient have clear physical meanings, and the active and reactive features that characterize the operation mode of the power grid contain information closely related to the safety and stability of the power grid. Therefore, when using convolutional neural networks for feature extraction, only the active and reactive features that characterize the operation mode of the power grid are used as the input of the convolutional neural network, and the convolutional neural network is used to extract high-order abstract features closely related to the safety and stability of the power grid. Finally, the high-order feature map extracted by the convolutional neural network is flattened and merged with the features that characterize the voltage and frequency support capacity such as short circuit ratio, virtual inertia coefficient and primary frequency modulation coefficient, and used as the input features of the feedforward neural network. The feedforward neural network is used to establish a nonlinear mapping relationship between these input features and the maximum transmission capacity of the key section of new energy power transmission.

[0085] The loss function used in the training of the maximum transmission capacity evaluation model is:

[0086]

[0087] Where: L s is the loss function; Y t is the real label vector of the maximum transmission capacity of the key section; Y The evaluation results output by the maximum transmission capacity evaluation model; λ a is the L2 regularization term coefficient, which is used to prevent the model from overfitting; w a is the weight vector for evaluating the model.

[0088] S5: For different grid-connected energy storage access and control parameter setting schemes, the corresponding voltage and frequency support strength evaluation indicators are calculated respectively, and then the change in the maximum transmission capacity of the section before and after the grid-connected energy storage is calculated to evaluate the effect of the grid-connected energy storage on improving the transmission capacity of key sections.

[0089] In step S5, for different grid-type energy storage access locations and control parameter setting schemes, combined with the established key section maximum transmission capacity evaluation model, the effect of grid-type energy storage on improving the transmission capacity of key sections for sending new energy power is quickly evaluated to support the optimization configuration analysis of grid-type energy storage access to the power grid. The specific evaluation process is:

[0090] (1) For the power grid before connecting to the grid-building energy storage, the maximum transmission capacity of the key section for sending out new energy power is calculated as a benchmark reference value. For the process of calculating the maximum transmission capacity of the key section for sending out new energy power for the power grid before connecting to the grid-building energy storage, please refer to the specific steps of calculating the maximum transmission capacity in the above step S3.

[0091] (2) Based on the access location of the new energy power generation station and the characteristics of the access grid, the capacity of the grid-connected energy storage is kept unchanged, and various configuration schemes of the access location and control parameters of the grid-connected energy storage are set.

[0092] (3) After the grid-connected energy storage is connected according to the configuration plan, the active and reactive characteristics that characterize the operation mode of the power grid are obtained through power flow calculation, the characteristics that characterize the voltage support capacity are obtained through short-circuit ratio calculation, and the virtual inertia coefficient and primary frequency regulation coefficient of the grid-connected energy storage are obtained as characteristics that characterize the frequency support capacity.

[0093] (4) According to different grid-connected energy storage access locations and control parameter configuration schemes, the established key section maximum transmission capacity assessment model is used to quickly assess the maximum transmission capacity of the key section for the transmission of new energy power after the grid-connected energy storage is connected.

[0094] (5) For different grid-type energy storage access locations and control parameter configuration schemes, the corresponding key section transmission capacity improvement evaluation index is calculated. The calculation formula of the evaluation index is:

[0095]

[0096] Where: η To evaluate the effect of grid-type energy storage on improving the transmission capacity of key sections; T e The maximum transmission capacity of the section after the grid-type energy storage is connected; T n The maximum transmission capacity of the section before the grid-type energy storage is connected; S e To construct the capacity of the grid-type energy storage itself.

[0097] The above-mentioned evaluation index of the role of improving the transmission capacity of key sections can clearly show the role of grid-type energy storage in improving the maximum transmission capacity of key sections for the transmission of new energy power. The larger the index, the stronger the role of grid-type energy storage in improving the transmission capacity of sections. Based on the evaluation results of this index, the effects of different grid-type energy storage access locations and control parameter configuration schemes can be analyzed to support the optimization configuration analysis and decision-making of grid-type energy storage access to the power grid.

[0098] Example 2

[0099] In one embodiment of the present disclosure, a system for evaluating grid-type energy storage for improving the transmission capacity of key sections is provided, comprising:

[0100] An initialization module is used to obtain the maximum transmission capacity of the power grid for the key section of new energy power transmission before the grid-building energy storage is connected, as a benchmark reference value;

[0101] Model building module, used to establish a rapid assessment model for the maximum transmission capacity of key sections for the transmission of new energy power;

[0102] The voltage support strength evaluation index and frequency support strength evaluation index calculation module are used to obtain the grid operation characteristics for the typical output scenario set of new energy stations; the access location of the grid-type energy storage and the relevant parameters of the virtual synchronous generator control are changed to calculate the grid voltage support strength characteristics and the grid frequency support strength characteristics under different change scenarios;

[0103] The maximum transmission capacity rapid assessment module is used to input the grid operation characteristics, grid voltage support strength characteristics and grid frequency support strength characteristics under different change scenarios into the rapid assessment model of the maximum transmission capacity of the key section for the transmission of new energy power, and combine the benchmark reference value to obtain the change of the maximum transmission capacity of the section before and after the grid-connected energy storage;

[0104] The grid-type energy storage effect evaluation module is used to quickly evaluate the effect of grid-type energy storage on improving the transmission capacity of key sections for the transmission of new energy power.

[0105] Example 3

[0106] In one embodiment of the present disclosure, a computer program product is provided, including a computer program, which, when executed by a processor, implements the method for evaluating the use of grid-connected energy storage to improve power transmission capacity at key sections.

[0107] Example 4

[0108] In one embodiment of the present disclosure, a non-transitory computer-readable storage medium is provided, wherein the non-transitory computer-readable storage medium is used to store computer instructions. When the computer instructions are executed by a processor, the evaluation method of improving the transmission capacity of key sections by grid-type energy storage is implemented.

[0109] Example 5

[0110] In one embodiment of the present disclosure, an electronic device is provided, including: a processor, a memory, and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory, so that the electronic device executes the evaluation method for improving the power transmission capacity of key sections by grid-type energy storage.

[0111] The present disclosure is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present disclosure. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of the processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0112] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0113] Although the above describes the specific implementation methods of the present disclosure in conjunction with the accompanying drawings, it is not intended to limit the scope of protection of the present disclosure. Technical personnel in the relevant field should understand that on the basis of the technical solution of the present disclosure, various modifications or variations that can be made by those skilled in the art without creative work are still within the scope of protection of the present disclosure.

Claims

1. An evaluation method for improving the transmission capacity of key sections by using grid-connected energy storage, characterized in that: include: Obtain the maximum transmission capacity of the grid for the key section of new energy power transmission before access to the grid-building energy storage as a benchmark reference value; Establish a maximum transmission capacity assessment model for key sections of new energy power transmission; The input of the maximum transmission capacity assessment model for the key section of new energy power delivery is the grid operation characteristics, grid voltage support strength characteristics and grid frequency support strength characteristics. The grid operation characteristics are the active and reactive characteristics that characterize the grid operation mode, specifically: the active and reactive power of the synchronous generator in the system, the active and reactive power of the load, the active and reactive power of the direct current transmission, the active and reactive power of the new energy power generation, and the active and reactive power of the energy storage; Convert it into a high-order feature map, flatten the high-order feature map, merge it with the short-circuit ratio, virtual inertia coefficient and primary frequency modulation coefficient features, and use them together as input features of the feedforward neural network. The feedforward neural network is used to establish a nonlinear mapping relationship between these input features and the maximum transmission capacity of the key section of new energy power transmission; The loss function used in the maximum transmission capacity assessment model for key sections of renewable energy power delivery is: Where: L s is the loss function; Y t is the real label vector of the maximum transmission capacity of the key section; Y The evaluation results output by the maximum transmission capacity evaluation model; λ a is the L2 regularization term coefficient, which is used to prevent the model from overfitting; w a is the weight vector of the evaluation model; Based on the typical output scenario set of new energy stations, the grid operation characteristics are obtained; By changing the access location of the grid-connected energy storage and the relevant parameters of the virtual synchronous generator control, the grid voltage support strength characteristics and grid frequency support strength characteristics under different change scenarios are calculated and obtained respectively; The grid operation characteristics, grid voltage support strength characteristics, and grid frequency support strength characteristics under different change scenarios are input into the maximum transmission capacity assessment model for key sections of renewable energy power delivery. Combined with the benchmark reference value, the changes in the maximum transmission capacity of the section before and after the grid-forming energy storage is connected are obtained to evaluate the effect of grid-forming energy storage on improving the transmission capacity of key sections of renewable energy power delivery. According to different grid-type energy storage access locations and control parameter configuration schemes, the corresponding key section transmission capacity improvement evaluation index is calculated. The calculation formula of the evaluation index is: Where: η To evaluate the effect of grid-type energy storage on improving the transmission capacity of key sections; T e The maximum transmission capacity of the section after the grid-type energy storage is connected; T n The maximum transmission capacity of the section before the grid-type energy storage is connected; S e To construct the capacity of the grid-type energy storage itself; The calculation steps for the maximum transmission capacity of the power grid for the key section of new energy power transmission before access to the grid-connected energy storage are as follows: 1) Set a fixed power increase step size to increase the power of renewable energy power stations and grid load power on both sides of the transmission section; 2) After each power increase, the system is verified through power flow calculation and time domain simulation to see whether it can meet the static and dynamic safety constraints set after the expected fault occurs, including voltage limit, power flow overload, transient voltage safety and frequency safety constraints; 3) If the safety constraint check passes, continue to increase the cross-section transmission power. Otherwise, the current cross-section transmission power minus one power transmission step is the maximum cross-section transmission capacity of the current sample scenario.

2. The evaluation method for improving the transmission capacity of key sections by grid-type energy storage as claimed in claim 1 is characterized in that: Considering the impact of grid-connected energy storage on the system's Thevenin equivalent impedance and the virtual synchronous generator control adopted by the grid-connected energy storage, the connection location of the grid-connected energy storage and the relevant parameters of the virtual synchronous generator control are changed, and the grid voltage support strength characteristics and grid frequency support strength characteristics under different change scenarios are calculated respectively; The grid voltage support strength characteristic is used as an evaluation index of the grid voltage support strength of the grid-connected energy storage. The grid voltage support strength characteristic is specifically the short-circuit ratio at the grid connection point of the new energy power station. After considering the impact of the grid-connected energy storage on the system's Thevenin equivalent impedance, the calculation steps of the short-circuit ratio are as follows: (1) Set the synchronous generator power supply in the system to zero. The synchronous generator is represented by an impedance branch to ground, and the impedance value is the sub-transient reactance. (2) The grid-connected energy storage and renewable energy generation in the system are represented by the short-circuit branches to the ground at their grid connection points; (3) The grid-connected energy storage and renewable energy generation in the system are represented by the open branch to the ground at their grid connection point; (4) After completing the above operations, the Thevenin equivalent impedance at the grid connection point of the renewable energy power station is calculated using circuit transformation theory, and then the short-circuit ratio is calculated.

3. The evaluation method for improving the transmission capacity of key sections by grid-type energy storage as claimed in claim 1 is characterized in that: The grid frequency support strength characteristics are used as evaluation indicators of grid-connected energy storage for grid frequency support strength. The grid frequency support strength characteristics are specifically the virtual inertia coefficient and primary frequency regulation coefficient set in the virtual synchronous generator control, and the rationality of the primary frequency regulation coefficient setting needs to be verified.

4. The evaluation method for improving the transmission capacity of key sections by grid-type energy storage as claimed in claim 1 is characterized in that: Based on deep learning technology, a maximum transmission capacity assessment model for key sections of renewable energy power transmission is established. The assessment steps of the maximum transmission capacity assessment model for key sections of renewable energy power transmission mainly include input feature set construction, convolutional neural network feature extraction and feedforward neural network regression.

5. An evaluation system for improving the transmission capacity of key sections by using grid-type energy storage, using the evaluation method for improving the transmission capacity of key sections by using grid-type energy storage as claimed in claim 1, characterized in that: include: An initialization module is used to obtain the maximum transmission capacity of the power grid for the key section of new energy power transmission before the grid-building energy storage is connected, as a benchmark reference value; Model building module, used to establish a maximum transmission capacity assessment model for key sections of new energy power transmission; The voltage support strength evaluation index and frequency support strength evaluation index calculation module are used to obtain the grid operation characteristics for the typical output scenario set of new energy stations; the access location of the grid-type energy storage and the relevant parameters of the virtual synchronous generator control are changed to calculate the grid voltage support strength characteristics and the grid frequency support strength characteristics under different change scenarios; The maximum transmission capacity rapid assessment module is used to input the grid operation characteristics, grid voltage support strength characteristics and grid frequency support strength characteristics under different change scenarios into the maximum transmission capacity assessment model of the key section for the transmission of new energy power, and combine the benchmark reference value to obtain the changes in the maximum transmission capacity of the section before and after the grid-connected energy storage; The grid-type energy storage role evaluation module is used to evaluate the effect of grid-type energy storage on improving the transmission capacity of key sections for the transmission of new energy power.

6. The evaluation system for improving the transmission capacity of key sections by grid-type energy storage as claimed in claim 5 is characterized in that: The grid voltage support strength characteristic is used as an evaluation index of the grid voltage support strength of the grid-connected energy storage. The grid voltage support strength characteristic is specifically the short-circuit ratio at the grid connection point of the new energy power station. After considering the impact of the grid-connected energy storage on the system's Thevenin equivalent impedance, the calculation steps of the short-circuit ratio are as follows: (1) Set the synchronous generator power supply in the system to zero. The synchronous generator is represented by an impedance branch to ground, and the impedance value is the sub-transient reactance. (2) The grid-connected energy storage and renewable energy generation in the system are represented by the short-circuit branches to the ground at their grid connection points; (3) The grid-connected energy storage and renewable energy generation in the system are represented by the open branch to the ground at their grid connection point; (4) After completing the above operations, the Thevenin equivalent impedance at the grid connection point of the renewable energy power station is calculated using circuit transformation theory, and then the short-circuit ratio is calculated.

7. The evaluation system for improving the transmission capacity of key sections by grid-type energy storage as claimed in claim 5, characterized in that: The grid frequency support strength characteristics are used as evaluation indicators of grid-connected energy storage for grid frequency support strength. The grid frequency support strength characteristics are specifically the virtual inertia coefficient and primary frequency regulation coefficient set in the virtual synchronous generator control, and the rationality of the primary frequency regulation coefficient setting needs to be verified.

8. The evaluation system for improving the transmission capacity of key sections by grid-type energy storage as claimed in claim 5, characterized in that: The loss function used in the maximum transmission capacity assessment model for key sections of renewable energy power delivery is: Where: L s is the loss function; Y t is the real label vector of the maximum transmission capacity of the key section; Y The evaluation results output by the maximum transmission capacity evaluation model; λ a is the L2 regularization term coefficient, which is used to prevent the model from overfitting; w a is the weight vector for evaluating the model.

9. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the evaluation method for improving the transmission capacity of key sections by grid-connected energy storage as described in any one of claims 1 to 4 is implemented.

10. A non-transitory computer-readable storage medium, characterized in that: The non-transitory computer-readable storage medium is used to store computer instructions. When the computer instructions are executed by the processor, the evaluation method for improving the transmission capacity of key sections by grid-type energy storage as described in any one of claims 1 to 4 is implemented.

11. An electronic device, characterized in that: include: A processor, a memory and a computer program; wherein the processor is connected to the memory, the computer program is stored in the memory, and when the electronic device is running, the processor executes the computer program stored in the memory so that the electronic device executes the evaluation method for improving the transmission capacity of key sections of grid-type energy storage as described in any one of claims 1 to 4.

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