Frequency and voltage support control method, device and equipment for new energy base

Abstract

The embodiment of the application provides a frequency and voltage support control method, device and equipment of a new energy base, and belongs to the technical field of new energy and energy storage. The method comprises the following steps: calculating a frequency and voltage dynamic support factor of a power resource corresponding to a power resource category; if the power resource category is a controllable power resource category, calculating a reference sensitivity transfer matrix corresponding to the power resource according to the frequency and voltage dynamic support factor and a pre-acquired frequency and voltage support control matrix of the new energy base to the power grid; constructing a frequency and voltage support mechanism control model according to the reference sensitivity transfer matrix; solving the frequency and voltage support mechanism control model to obtain a frequency and voltage support control strategy of the power resource; and performing frequency and voltage support control on the power resource according to the frequency and voltage support control strategy. The embodiment of the application can provide active safe and stable voltage and frequency support for the power grid by the new energy base, and improve the operation stability of the power grid.

Description

Technical Field

[0001] This application relates to the fields of new energy and energy storage technology, and in particular to a frequency and voltage support control method, device, and equipment for a new energy base. Background Technology

[0002] With the rapid development and continuous growth of new energy sources such as wind and solar power, which have significant uncertainties, the safe and stable operation of the power system (especially voltage and frequency) faces increasingly severe challenges. Increased fluctuations in power system frequency and voltage frequently lead to grid disconnection incidents caused by voltage exceeding limits at new energy bases. The deployment of energy storage in clean energy bases offers hope for solving these problems and plays a crucial role in promoting the safe and stable operation of the new power system. On the one hand, the installed capacity and power generation of new energy sources will far exceed those of traditional power sources such as thermal power, gas power, and hydropower. Relying solely on traditional generator units cannot accomplish the tasks of safe and stable frequency and voltage control; active support from new energy sources and energy storage is required. On the other hand, clean energy systems such as wind power, solar power, hydropower, and energy storage have different dynamic characteristics and response time scales, resulting in varying and time-varying capabilities in actively supporting grid frequency and voltage, making coordination difficult. Therefore, how to coordinate the control of wind, solar, hydro, and energy storage resources in clean energy bases is a key challenge in achieving active support for grid safety and stability from clean energy bases.

[0003] Current research primarily focuses on the design and analysis of model-based root network and network control strategies, failing to consider the grid's dynamic response requirements under frequency and voltage fluctuations. It also neglects issues such as the difficulty in accurately obtaining model dynamics and time-varying uncertainties in real-world systems. These shortcomings limit the potential of clean energy bases with energy storage to actively support grid security and stability, and hinder the improvement of the electricity ancillary services market. There is a need to research methods and systems that can directly utilize multi-type resource input and output data for collaborative control to provide proactive security and stability support for the grid, even when the model is unknown or time-varying, or when model information is partially known, thereby enhancing system security and stability. Summary of the Invention

[0004] The main objective of this application is to propose a frequency and voltage support control method, device, equipment, and storage medium for a new energy base, which aims to coordinate the control of various resources in the new energy base, thereby providing active, safe, and stable voltage and frequency support control for the power grid.

[0005] To achieve the above objectives, a first aspect of this application proposes a frequency and voltage support control method for a new energy base, the method comprising:

[0006] Determine the power resource category of the new energy base, and calculate the frequency and voltage dynamic support factors of the power resources corresponding to the power resource category;

[0007] If the power resource category is a controllable power resource category, then based on the frequency and voltage dynamic support factors and the pre-acquired frequency and voltage support control matrix of the new energy base for the power grid, the reference sensitivity transfer matrix corresponding to the power resource is calculated; wherein, the reference sensitivity transfer matrix is ​​used to indicate the mapping relationship between the output active power, output reactive power and frequency fluctuation and voltage fluctuation of the power resource corresponding to the controllable power resource category.

[0008] A frequency and voltage support mechanism control model is constructed based on the reference sensitivity transfer matrix;

[0009] Solve the frequency and voltage support mechanism control model to obtain the frequency and voltage support control strategy for the power resources;

[0010] The power resources are subjected to frequency and voltage support control according to the frequency and voltage support control strategy.

[0011] In some embodiments, the power resource category includes an uncontrollable power resource category, and the calculation of the frequency and voltage dynamic support factors of the power resources corresponding to the power resource category includes:

[0012] Obtain the expected sensitivity transfer matrix of the power resource corresponding to the uncontrollable power resource category; wherein, the expected sensitivity transfer matrix is ​​used to indicate the mapping relationship between the output active power, output reactive power and frequency fluctuation and voltage fluctuation of the power resource corresponding to the uncontrollable power resource category;

[0013] Based on the pre-acquired frequency and voltage support control matrix of the new energy base for the power grid and the expected sensitivity transfer matrix, the frequency and voltage dynamic support factor of the power resources is calculated.

[0014] In some embodiments, the power resource category includes a controllable power resource category, and the calculation of the frequency and voltage dynamic support factors of the power resources corresponding to the power resource category includes:

[0015] Obtain the time scale for the frequency and voltage support provided by the power resources corresponding to the controllable power resource category;

[0016] Determine the filter model based on the time scale;

[0017] The frequency and voltage dynamic support factors of the power resources are determined based on the filter model.

[0018] In some embodiments, after determining the frequency and voltage dynamic support factors of the power resource according to the filter model, the method further includes:

[0019] Obtain historical operating data of the new energy base; wherein, the historical operating data includes dynamic input and output response time series of power resources;

[0020] Data fitting is performed on the dynamic input and output response time series to obtain the dynamic support factor time constant;

[0021] If the filter model is a bandpass filter, then the frequency and voltage dynamic support factors are optimized according to the dynamic support factor time constant;

[0022] If the filter model is a low-pass filter, a dynamic support factor gain optimization model is constructed, and the dynamic support factor gain is obtained by solving the dynamic support factor gain optimization model. The frequency and voltage dynamic support factors are then optimized based on the dynamic support factor time constant and the dynamic support factor gain.

[0023] In some embodiments, constructing the frequency and voltage support mechanism control model based on the reference sensitivity transfer matrix includes:

[0024] Based on the reference sensitivity transfer matrix, construct a frequency and voltage support control reference state space model for power resources and a frequency and voltage support control state space model containing a current control loop;

[0025] An augmented state space model is constructed based on the frequency and voltage supported control reference state space model and the frequency and voltage supported control state space model;

[0026] The frequency and voltage support mechanism control model is constructed based on the augmented state space model.

[0027] In some embodiments, constructing an augmented state space model based on the frequency and voltage supported control reference state space model and the frequency and voltage supported control state space model includes:

[0028] Based on the frequency and voltage support control reference state space model and the frequency and voltage support control state space model, the control deviation variables are determined;

[0029] The state variables are determined based on the frequency and voltage support control reference state space model and the frequency and voltage support control state space model.

[0030] The system matrix is ​​determined based on the frequency and voltage supported control reference state space model and the frequency and voltage supported control state space model.

[0031] The augmented state-space model is constructed based on the control deviation variable, the state variable, and the system matrix.

[0032] In some embodiments, solving the frequency and voltage support mechanism control model to obtain the frequency and voltage support control strategy for the power resources includes:

[0033] Obtain the sample frequency and voltage to support the control strategy and sample control deviation;

[0034] A data matrix is ​​constructed based on the sample frequency and voltage support control strategy and the sample control deviation;

[0035] The frequency and voltage support mechanism control model is converted into a deterministic data control model based on the data matrix.

[0036] The deterministic data control model is converted into a distributed bar data control model;

[0037] Solve the sub-bar data control model to obtain the frequency and voltage support control strategy.

[0038] To achieve the above objectives, a second aspect of this application provides a frequency and voltage support control device for a new energy base, the device comprising:

[0039] The determination module is used to determine the power resource category of the new energy base and calculate the frequency and voltage dynamic support factors of the power resources corresponding to the power resource category;

[0040] The calculation module is used to calculate the reference sensitivity transfer matrix corresponding to the power resource if the power resource category is a controllable power resource category, based on the frequency and voltage dynamic support factor and the pre-acquired frequency and voltage support control matrix of the new energy base to the power grid; wherein, the reference sensitivity transfer matrix is ​​used to indicate the mapping relationship between the output active power, output reactive power and frequency fluctuation and voltage fluctuation of the power resource corresponding to the controllable power resource category.

[0041] The module is used to construct a frequency and voltage support mechanism control model based on the reference sensitivity transfer matrix;

[0042] The solution module is used to solve the frequency and voltage support mechanism control model to obtain the frequency and voltage support control strategy of the power resources.

[0043] The control module is used to perform frequency and voltage support control on the power resources according to the frequency and voltage support control strategy.

[0044] To achieve the above objectives, a third aspect of this application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the method described in the first aspect.

[0045] To achieve the above objectives, a fourth aspect of the present application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method described in the first aspect.

[0046] The frequency and voltage support control method, device, electronic equipment, and computer-readable storage medium for new energy bases proposed in this application determine the power resource category of the new energy base. Considering the heterogeneous characteristics of power resources such as response time and support capacity, the method calculates the dynamic support factor of the power resources corresponding to the power resource category, thereby achieving frequency and voltage support based on the collaborative control of heterogeneous resources. If the power resource category is a controllable power resource category, a reference sensitivity transfer matrix of the power resources is calculated based on the dynamic support factor of the frequency and voltage and the pre-acquired frequency and voltage support control matrix of the new energy base to the power grid. This matrix constrains the frequency and voltage support of each power resource of the new energy base to the power grid, achieving collaborative control of each power resource and improving the operational stability of the power grid. A frequency and voltage support mechanism control model is constructed based on the reference sensitivity transfer matrix. The model is solved to obtain the frequency and voltage support control strategy of the power resources. The power resources are then controlled according to the frequency and voltage support control strategy to promote the active support capability of the new energy base to the power grid frequency and voltage, thereby improving the operational stability of the power grid. Attached Figure Description

[0047] Figure 1 This is a system schematic diagram of the new energy base provided in the embodiments of this application;

[0048] Figure 2 This is a flowchart of the frequency and voltage support control method for a new energy base provided in an embodiment of this application;

[0049] Figure 3 yes Figure 2 The flowchart of step S210 in the middle;

[0050] Figure 4 yes Figure 2 Another flowchart of step S210 in the process;

[0051] Figure 5 This is another flowchart of the frequency and voltage support control method for a new energy base provided in the embodiments of this application;

[0052] Figure 6 yes Figure 2 The flowchart of step S230 in the text;

[0053] Figure 7 yes Figure 6 The flowchart of step S620 in the middle;

[0054] Figure 8 yes Figure 2 The flowchart of step S240 in the text;

[0055] Figure 9 This is a illustrative example diagram showing the frequency and voltage support control effect of the new energy base provided in the embodiments of this application;

[0056] Figure 10 This is a schematic diagram of the frequency and voltage support control device for a new energy base provided in an embodiment of this application;

[0057] Figure 11 This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0058] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0059] It should be noted that although functional modules are divided in the device schematic diagram and a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart. The terms "first," "second," etc., in the specification, claims, and the aforementioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0060] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0061] In related technologies, it is necessary to integrate renewable energy bases into the power system to transmit electricity to the power system through these bases. With the rapid development and continuous growth of renewable energy sources such as wind and solar power, which have significant uncertainties, the safe and stable operation of the power system faces increasingly severe challenges. Increased frequency and voltage fluctuations in the power system can disrupt the grid connection conditions of renewable energy bases, leading to frequent grid disconnections due to voltage exceeding limits, thus affecting the stable operation of the power system.

[0062] Based on this, embodiments of this application provide a frequency and voltage support control method, a frequency and voltage support control device, an electronic device, and a computer-readable storage medium for a new energy base, aiming to enhance the safety and stability of the power system.

[0063] The frequency and voltage support control method, device, electronic equipment, and computer-readable storage medium for new energy bases provided in this application are specifically described through the following embodiments. First, the frequency and voltage support control method for new energy bases in this application embodiment is described.

[0064] The frequency and voltage support control method for a new energy base provided in this application relates to the fields of new energy and energy storage technology. This method can be applied to a terminal, a server, or software running on either a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, etc.; the server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms; the software can be an application implementing the frequency and voltage support control method for the new energy base, but is not limited to the above forms.

[0065] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0066] The new energy base provides energy storage for wind, solar, and hydropower energy bases. Figure 1This is a schematic diagram of a wind, solar, and hydropower energy base with energy storage system provided in this application embodiment, including power resources such as wind power generation, photovoltaic power generation, hydropower generation, and energy storage. The electrical energy transmitted from the wind, solar, and hydropower energy base with energy storage can be converted into high-voltage direct current (HVDC) and then transmitted to the power grid.

[0067] Figure 2 This is an optional flowchart of the frequency and voltage support control method for a new energy base provided in the embodiments of this application. Figure 2 The method may include, but is not limited to, steps S210 to S250.

[0068] Step S210: Determine the power resource category of the new energy base and calculate the frequency and voltage dynamic support factors of the power resources corresponding to the power resource category;

[0069] Step S220: If the power resource category is a controllable power resource category, then calculate the reference sensitivity transfer matrix corresponding to the power resource based on the frequency and voltage dynamic support factors and the pre-acquired frequency and voltage support control matrix of the new energy base to the power grid; wherein, the reference sensitivity transfer matrix is ​​used to indicate the mapping relationship between the output active power, output reactive power and frequency fluctuation and voltage fluctuation of the power resource corresponding to the controllable power resource category.

[0070] Step S230: Construct a frequency and voltage support mechanism control model based on the reference sensitivity transfer matrix;

[0071] Step S240: Solve the frequency and voltage support mechanism control model to obtain the frequency and voltage support control strategy for power resources;

[0072] Step S250: Perform frequency and voltage support control on the power resources according to the frequency and voltage support control strategy.

[0073] In step S210 of some embodiments, the power resources of the new energy base are classified according to the response and support characteristics of the power resources' frequency and voltage. These power resource categories include uncontrollable power resource categories and controllable power resource categories. Uncontrollable power resource categories include synchronous resources such as hydropower and electricity, where the impact of frequency and voltage fluctuations on their output active and reactive power is fixed and uncontrollable. Controllable power resource categories include new resources such as wind power, photovoltaic power generation, and energy storage connected to the grid through power converters, where the impact of frequency and voltage fluctuations on their output active and reactive power can be adjusted by changing the control strategy, and this impact is controllable. Hydropower can provide frequency and voltage support over a longer timescale; wind power, photovoltaic power, and energy storage can provide rapid frequency and voltage support over a shorter timescale; depending on the energy storage technology and capacity, energy storage can also provide frequency and voltage support over a longer timescale between hydropower, wind power, and photovoltaic power.

[0074] The overall control requirements of power system operators for renewable energy bases to provide voltage and frequency support to the grid are obtained, including delay time, response time, duration, response and recovery rate, and support capacity. These overall control requirements characterize the impact of frequency and voltage fluctuations on the overall output active and reactive power of renewable energy bases, and can be described in the frequency domain using mathematical expressions based on transfer functions.

[0075] ,

[0076] in, Represents the frequency domain; and These are the frequency domain representations of frequency fluctuations and voltage fluctuations, respectively. and These are the frequency domain representations of the total active and reactive power output of the new energy bases as expected by power system operators; This is the transfer function matrix expression of the overall control requirements of power system operators for the voltage and frequency support provided by new energy bases to the power grid, namely, the frequency and voltage support control matrix of new energy bases to the power grid. and These represent the effects of frequency fluctuations and voltage fluctuations on the output active power, respectively. and The effects of frequency fluctuations and voltage fluctuations on the output reactive power are respectively shown.

[0077] Dynamic support factors are provided for the design of frequency and voltage for each power resource in the new energy base, resulting in the dynamic support factors for frequency and voltage of each power resource. Specifically, dynamic support factors for frequency and voltage are allocated to power resources corresponding to uncontrollable and controllable power resource categories. This can be described using a mathematical expression based on the transfer function:

[0078] ,

[0079] in, For the expected frequency and voltage fluctuations on power resources The transfer function matrix expression for the influence of output active power and output reactive power. and The impact of frequency fluctuations and voltage fluctuations on power resources, respectively. The impact of output active power. and The impact of frequency fluctuations and voltage fluctuations on power resources, respectively. The impact of reactive power output; For power resources The dynamic support factor matrix, which consists of frequency and voltage dynamic support factors; , , , These represent the dynamic support factors for the impact of frequency fluctuations on active power, the dynamic support factors for the impact of reactive power on active power, the dynamic support factors for the impact of active power on reactive power, and the dynamic support factors for the impact of voltage fluctuations on reactive power, respectively.

[0080] To construct dynamic support factors that meet the overall control requirements of power system operators for new energy bases to provide voltage and frequency support to the power grid, the following conditions must be met, based on the above-mentioned requirements for power resources. Based on the mathematical expression of the transfer function and the overall frequency and voltage support control objectives of the new energy base, the following mathematical expression can be obtained:

[0081] ,

[0082] in, For the impact of frequency fluctuations and voltage fluctuations on power resources The transfer function matrix expression for the influence of output active and reactive power. and It is a collection consisting of uncontrollable power resources and controllable power resources, respectively.

[0083] Based on the above The mathematical expression for determining the conditions that the dynamic support factor must satisfy to fully meet the overall control requirements of the new energy base in providing voltage and frequency support to the power grid is:

[0084] ,

[0085] .

[0086] Please see Figure 3 In some embodiments, step S210 may include, but is not limited to, steps S310 to S320:

[0087] Step S310: Obtain the expected sensitivity transfer matrix of the power resources corresponding to the uncontrollable power resource category; wherein, the expected sensitivity transfer matrix is ​​used to indicate the mapping relationship between the output active power, output reactive power and frequency fluctuation and voltage fluctuation of the power resources corresponding to the uncontrollable power resource category.

[0088] Step S320: Calculate the frequency and voltage dynamic support factor of power resources based on the pre-acquired frequency and voltage support control matrix and expected sensitivity transfer matrix of the new energy base to the power grid.

[0089] In step S310 of some embodiments, a dynamic support factor transfer function model that satisfies the above conditions is designed for the power resources corresponding to the uncontrollable power resource category. The dynamic support factor transfer function model for uncontrollable power resources is fixed, and its calculation formula is expressed as:

[0090] ,

[0091] Right now:

[0092] ,

[0093] ,

[0094] ,

[0095] ,

[0096] in, and Represent the transfer function matrix respectively The first and second columns of the inverse matrix; This represents a set of uncontrollable electrical resources; , , , These represent the dynamic support factors for the impact of frequency fluctuations on active power, the dynamic support factors for the impact of reactive power on active power, the dynamic support factors for the impact of active power on reactive power, and the dynamic support factors for the impact of voltage fluctuations on reactive power, respectively.

[0097] Referring to the calculation formula of the dynamic support factor transfer function model, the power resources corresponding to the uncontrollable power resource category are obtained. The expected sensitivity transfer matrix is ​​used to indicate uncontrollable power resources. The mapping relationship between output active power, output reactive power, and frequency and voltage fluctuations. Power Resources The desired sensitivity transfer matrix is ​​expressed as .

[0098] In step S320 of some embodiments, for uncontrollable power resources Calculate the frequency and voltage support control matrix The inverse matrix of the matrix will transfer the desired sensitivity to the matrix. and inverse matrix Multiplying them together yields uncontrollable electrical resources. Frequency and voltage dynamic support factors.

[0099] Through the above steps S310 to S320, the frequency and voltage dynamic support factors of uncontrollable power resources can be obtained, so as to provide stable frequency and voltage support for the power grid based on the frequency and voltage dynamic support factors.

[0100] Please see Figure 4 In some embodiments, step S210 may include, but is not limited to, steps S410 to S430:

[0101] Step S410: Obtain the time scale for the frequency and voltage support of the power resources corresponding to the controllable power resource category;

[0102] Step S420: Determine the filter model based on the time scale;

[0103] Step S430: Determine the frequency and voltage dynamic support factors of the power resources based on the filter model.

[0104] In step S410 of some embodiments, to design a dynamic support factor transfer function model for controllable power resources, the time scale for providing frequency and voltage support corresponding to the controllable power resource category is obtained. The time scale includes long time scales, medium time scales, and short time scales. A frequency and voltage support control duration greater than or equal to 30 seconds can be considered a long time scale, a frequency and voltage support control duration greater than or equal to 2 seconds and less than 30 seconds can be considered a medium time scale, and a frequency and voltage support control duration less than 2 seconds can be considered a short time scale.

[0105] In step S420 of some embodiments, a dynamic support factor for the controllable power resource is set based on the response characteristics and frequency and voltage support capabilities of the power resource. The dynamic support factor for controllable power resources (a portion of energy storage, such as compressed air energy storage) capable of providing frequency and voltage support over a longer timescale is designed as a low-pass filter model. That is, if the timescale is a long timescale, the filter model is a low-pass filter, which is represented as:

[0106] ,

[0107] in, The time constant representing the dynamic support factor; This represents the gain of the dynamic support factor; This represents the set of electrical resources that provide frequency and voltage support over a long time scale; * represents any parameter in the set, fp represents the parameter that affects active power due to frequency fluctuations, qp represents the parameter that affects active power due to reactive power, pq represents the parameter that affects reactive power due to active power, and vq represents the parameter that affects reactive power due to voltage fluctuations.

[0108] The dynamic support factor for controllable power resources (another part of energy storage, such as large-capacity battery energy storage) that can provide frequency and voltage support at a medium time scale is designed as a bandpass filter model. That is, if the time scale is medium, the filter model is a bandpass filter, which is expressed as:

[0109] ,

[0110] in, The time constant representing the dynamic support factor; This refers to the collection of electrical resources that provide frequency and voltage support for a medium time scale; Indicates an index.

[0111] The dynamic support factor for controllable power resources (wind power, photovoltaics, and another part of energy storage, such as small-capacity battery energy storage) that can provide frequency and voltage support on a short timescale is designed as a high-pass filter model. That is, if the timescale is short, the filter model is a high-pass filter, expressed as:

[0112] ,

[0113] in, Indicates the bandwidth constant; This refers to the collection of electrical resources that provide frequency and voltage support on a short timescale. .

[0114] In step S430 of some embodiments, the filter model is used as a frequency and voltage dynamic support factor for the power resources.

[0115] Through the above steps S410 to S430, the frequency and voltage dynamic support factors of controllable power resources can be obtained, so as to provide stable frequency and voltage support for the power grid based on the frequency and voltage dynamic support factors.

[0116] Please see Figure 5 In some embodiments, after step S430, the frequency and voltage support control method for the new energy base may include, but is not limited to, steps S510 to S540:

[0117] Step S510: Obtain historical operating data of the new energy base; wherein, the historical operating data includes the dynamic input and output response time series of power resources;

[0118] Step S520: Perform data fitting on the dynamic input and output response time series to obtain the dynamic support factor time constant;

[0119] Step S530: If the filter model is a bandpass filter, optimize the frequency and voltage dynamic support factors based on the dynamic support factor time constant.

[0120] Step S540: If the filter model is a low-pass filter, construct a dynamic support factor gain optimization model and solve the dynamic support factor gain optimization model to obtain the dynamic support factor gain. Optimize the frequency and voltage dynamic support factors based on the dynamic support factor time constant and the dynamic support factor gain.

[0121] In step S510 of some embodiments, historical operating data of the new energy base is obtained, and dynamic input and output response time series of power resources are obtained from the historical operating data.

[0122] In step S520 of some embodiments, data fitting is performed on the dynamic input and output response time series to determine the dynamic response characteristics of power resources. An appropriate dynamic support factor time constant is selected based on these characteristics. The dynamic input and output response time series include an input time series and an output response time series. Linear regression is used to fit the input and output time series to obtain the mapping relationship between them, i.e., the dynamic response characteristics of power resources. This mapping relationship is then used as the dynamic support factor time constant.

[0123] In step S530 of some embodiments, if the filter model is a bandpass filter, the time constants in the frequency and voltage dynamic support factors are updated according to the dynamic support factor time constants calculated in step S520 to optimize the frequency and voltage dynamic support factors.

[0124] In step S540 of some embodiments, if the filter model is a low-pass filter, a dynamic support factor gain optimization model for any time period t is constructed in the time domain based on the maximum output prediction data of active and reactive power of uncontrollable power resources and controllable power resources that can provide frequency and voltage support over a longer time scale, as well as the frequency and voltage support control objectives. The dynamic support factor gain optimization model is a convex optimization model, and a general solver is used to solve the gain optimization model to obtain the optimal solution, thus obtaining the dynamic support factor gain. The time constants of the frequency and voltage dynamic support factors are updated based on the dynamic support factor time constants calculated in step S520, and the gains of the frequency and voltage dynamic support factors are updated based on the dynamic support factor gains calculated in step S540 to optimize the frequency and voltage dynamic support factors.

[0125] The dynamic support factor gain optimization model for any time period t is expressed as:

[0126] ,

[0127] in, and These represent the maximum output active power and maximum output reactive power of controllable electrical resources that provide frequency and voltage support over a long time scale, respectively. and Both represent the dynamic support factor gain. The dynamic support factor gain represents the effect of frequency fluctuations on active power or the dynamic support factor gain represents the effect of voltage fluctuations on reactive power. This refers to the dynamic support factor gain that represents the influence of active power on reactive power, or the dynamic support factor gain that represents the influence of reactive power on active power. and The frequency and voltage dynamic support factors that constitute uncontrollable power resource j.

[0128] Through the above steps S510 to S540, the frequency and voltage dynamic support factors can be optimized.

[0129] In step S220 of some embodiments, if the power resource category is a controllable power resource category, the frequency and voltage dynamic support factors are multiplied by the pre-acquired frequency and voltage support control matrix of the new energy base to the power grid to obtain the reference sensitivity transfer matrix corresponding to the power resource. The reference sensitivity transfer matrix is ​​used to indicate the mapping relationship between the output active power, output reactive power and frequency fluctuations and voltage fluctuations of the power resource corresponding to the controllable power resource category.

[0130] Please see Figure 6 In some embodiments, step S230 may include, but is not limited to, steps S610 to S630:

[0131] Step S610: Construct a frequency and voltage support control reference state space model and a frequency and voltage support control state space model containing a current control loop for power resources based on the reference sensitivity transfer matrix.

[0132] Step S620: Construct an augmented state space model based on the frequency and voltage supported control reference state space model and the frequency and voltage supported control state space model;

[0133] Step S630: Construct frequency and voltage support mechanism control models based on the augmented state space model.

[0134] In step S610 of some embodiments, a state-space described control model is established, specifically, based on the expected frequency and voltage fluctuations of the power resources. The transfer function matrix that influences the output active power and output reactive power. That is, referencing the sensitivity transfer matrix to establish a system for power resources. The frequency and voltage support control reference state-space model, the reference state-space model is:

[0135] ,

[0136] in, Indicates the variable The first derivative; Represents the state of the reference state-space model; This represents the perturbation of the reference state-space model, i.e., frequency fluctuation. and voltage fluctuations ; This represents the output of the reference state-space model, i.e. and ; , , , This represents the system matrix of the reference state-space model, which depends on the frequency and voltage dynamic support factors.

[0137] Based on the expected frequency and voltage fluctuations, the power resources The transfer function matrix that influences the output active power and output reactive power. That is, referencing the sensitivity transfer matrix, to establish power resources including a typical current control loop. The control state-space model is represented as follows:

[0138] ,

[0139] in, and Electricity resources The state vector and the output vector, the output vector is composed of active power and reactive power; This is the disturbance vector composed of voltage fluctuations and frequency fluctuations; This is the control input vector, i.e., the reference input for the current control loop; , , , , , For power resources The system matrix.

[0140] It should be noted that the matrix parameters of the control state space model in this embodiment are all unknown.

[0141] In step S620 of some embodiments, a control deviation variable is defined based on the frequency and voltage support control reference state space model and the frequency and voltage support control state space model. Variable dynamics and state variables Based on control deviation variables, variable dynamics, and state variables, power resources are established. The frequency and voltage-supported control are represented by an augmented state-space model. The augmented state-space model is expressed as:

[0142] ,

[0143] in,

[0144] ,

[0145] ,

[0146] ,

[0147] ,

[0148] ,

[0149] ,

[0150] in, , , , , and The system matrix for the augmented state-space model; Represents a zero matrix.

[0151] In step S630 of some embodiments, the controller is designed This allows the frequency and voltage to support the deviation of the control target. To minimize and satisfy the augmented state-space model, the inputs and outputs are constrained within the allowable operating range. Simultaneously, the augmented state-space model is discretized, and predictive control using a rolling optimization approach is employed to obtain controllable power resources. The frequency and voltage support mechanism control model is expressed as follows:

[0152] ,

[0153] in, , , , , , This represents the system matrix obtained after discretizing the augmented state-space model; Indicates the predicted duration. and These represent the input allowed operating range and the output allowed operating range, respectively. Indicates the first That moment.

[0154] Through the above steps S610 to S630, a frequency and voltage support mechanism control model can be obtained, and frequency and voltage support control can be performed based on the frequency and voltage support mechanism control model, thereby enabling the power grid to operate stably.

[0155] Please see Figure 7 In some embodiments, step S620 may include, but is not limited to, steps S710 to S740:

[0156] Step S710: Determine the control deviation variables based on the frequency and voltage supported control reference state space model and the frequency and voltage supported control state space model;

[0157] Step S720: Determine the state variables based on the frequency and voltage supported control reference state space model and the frequency and voltage supported control state space model;

[0158] Step S730: Determine the system matrix based on the frequency and voltage supported control reference state space model and the frequency and voltage supported control state space model;

[0159] Step S740: Construct an augmented state-space model based on the control deviation variables, state variables, and system matrix.

[0160] In step S710 of some embodiments, a control deviation variable is defined based on the frequency and voltage support control reference state space model and the frequency and voltage support control state space model. The control deviation variable is represented as... .

[0161] In step S720 of some embodiments, state variables are determined based on the frequency and voltage support control reference state space model and the frequency and voltage support control state space model. The state variables are represented as follows: .

[0162] In step S730 of some embodiments, referring to step S620, the system matrix is ​​determined based on the frequency and voltage support control reference state space model and the frequency and voltage support control state space model.

[0163] In step S740 of some embodiments, referring to step S620, an augmented state-space model is constructed based on the control deviation variable, state variable, and system matrix.

[0164] Through the above steps S710 to S740, an augmented state-space model can be obtained, which can be used for frequency and voltage support control.

[0165] Solve the frequency and voltage support mechanism control model to obtain the values ​​of the control input vector of the power resources, and obtain the frequency and voltage support control strategy, so as to carry out frequency and voltage support control of the power resources according to the frequency and voltage support control strategy.

[0166] Please see Figure 8 In some embodiments, step S240 may include, but is not limited to, steps S810 to S850:

[0167] Step S810: Obtain the sample frequency, voltage support control strategy, and sample control deviation;

[0168] Step S820: Construct a data matrix based on the sample frequency, voltage support control strategy, and sample control deviation;

[0169] Step S830: Convert the frequency and voltage support mechanism control model into a deterministic data control model based on the data matrix;

[0170] Step S840: Convert the deterministic data control model into a distributed bar data control model;

[0171] Step S850: Solve the split-bar data control model to obtain the frequency and voltage support control strategy.

[0172] In step S810 of some embodiments, considering that the matrix parameters in the frequency and voltage-supported control state-space model are unknown, i.e., the matrix... , , , , , Medium dynamic support factor gain It varies over time and may differ at different times; the matrix , , , , and The parameters in the data are difficult to obtain accurately in actual power resources, and there are difficulties in measuring some intermediate states generated during the transformation of the transfer function into a state-space expression. This application addresses these challenges by establishing a data control model based on behavioral system theory. Specifically, it collects input control data and output data of trajectory length T offline. The input control data serves as the sample frequency and voltage to support the control strategy, and the output data serves as the sample control deviation. The collected data of trajectory length T includes power resources obtained from N identical repeated trials. Historical trajectory data and , and the latest input and output measurement data and . and These represent input control data and output data, respectively.

[0173] The collected data can be preprocessed, including removing bad data and completing missing data.

[0174] In step S820 of some embodiments, the prediction duration is determined based on the sample frequency of trajectory length T and the voltage support control strategy. and sample control deviation Establish a trajectory with length T and prediction duration of... Depth is The order is Data matrix and The data matrix includes blocks used to estimate the state and output. row matrix ( ) and blocks used to predict future states and outputs row matrix ( The data matrix is ​​represented as follows:

[0175] ,

[0176] ,

[0177] Among them, data matrix and They are respectively:

[0178] ,

[0179] .

[0180] In step S830 of some embodiments, according to behavioral systems theory, the discrete state-space model in the frequency and voltage support mechanism control model is replaced by a data matrix, collected sample frequency and voltage support control strategy, and sample control deviation, eliminating the dependence on model parameters, so as to transform the frequency and voltage support mechanism control model into a deterministic data control model, that is:

[0181] ,

[0182] in, These are the variables to be optimized.

[0183] In step S840 of some embodiments, considering the uncertainties of frequency, voltage, and new energy sources such as wind and solar power, the prediction of the future output trajectory obtained from the deterministic data control model has uncertainty, and the initial condition constraints used to obtain the future trajectory are also considered. This may not hold true due to the randomness of the system. In this embodiment, a penalty term is added to the objective function of the deterministic data control model, and the predicted output trajectory constraint is constructed as a conditional risk value constraint, resulting in a sub-Bruker data control model. This model achieves the optimal control strategy under the worst-case empirical distribution of the random variable. The sub-Bruker data control model is expressed as:

[0184] ,

[0185] in, This indicates that the Wasserstein radius does not exceed empirical distribution The fuzzy set formed; Represents the worst distribution in a fuzzy set; Indicates distribution The following expectations; Indicates the confidence parameter; Indicates distribution The lower confidence parameter is Conditional risk value at time; sup represents supremacy; and These represent the row matrices to be optimized in the data matrix.

[0186] Conditional risk value is expressed as:

[0187] ,

[0188] Where inf represents the infimum; + represents a positive number; Represents the constraint function; Represent the space of real numbers; The time constant represents the dynamic support factor.

[0189] In step S850 of some embodiments, the sub-Blu-ray bar data control model is solved to obtain a sub-Blu-ray bar data-driven predictive control strategy that provides frequency and power support from controllable power resources, thus obtaining a frequency and voltage support control strategy. The frequency and voltage support control strategy is expressed as follows:

[0190] ,

[0191] in, To find the optimal solution for the split-bar data control model; Frequency and voltage-supported control strategies, including current and future ones. The optimal control strategy at time t is:

[0192] .

[0193] Considering the untraceability of the model generated by the sup and inf functions in the sub-Bruker data control model, this application embodiment reconstructs the sub-Bruker data control model into a traceable data control model in the following form when solving the sub-Bruker data control model, namely:

[0194] ,

[0195] in, The confidence region parameter is selected; N is the number of independent repeated trials; the superscript k indicates the data trajectory collected in the k-th independent repeated trial; Lobj and Lcon are both positive Lipschitz constants; Represents a random variable; Denotes the order of the norm; Indicates the error parameter; and the optimal solution same.

[0196] The reconstructed data control model is solved using a typical solver to obtain the optimal control strategy, namely, the frequency and voltage-supported control strategy. The calculated optimal control strategy is then assigned to the controller to update the control strategy.

[0197] ,

[0198] ,

[0199] And update the time at the same time. and the latest input / output measurement data and T represents the transpose operation.

[0200] Through the above steps S810 to S850, the optimal control strategy can be obtained, and frequency and voltage support control can be performed based on the optimal control strategy.

[0201] In step S250 of some embodiments, the power resources are subjected to frequency and voltage support control according to the frequency and voltage support control strategy, thereby enabling the power grid to operate stably.

[0202] This application's embodiments directly utilize power resource input and output data to design control methods, eliminating the need for dynamic models of power resources and related system identification. Considering the heterogeneous characteristics of power resources, such as response time and support capabilities, it can be used for collaborative control of heterogeneous resources to achieve frequency and voltage support, demonstrating strong versatility. It also provides robust stability guarantees against uncertainties in new energy sources like wind and solar power and other systems. This is of significant importance and practical value in promoting the configuration of energy storage in clean energy bases for wind, solar, and hydropower to enhance their active support capabilities for grid frequency and voltage, and in improving the safety and stability of new power systems. It can be widely applied in the fields of new energy and energy storage technologies.

[0203] Please see Figure 9 , Figure 9 This example demonstrates the voltage and frequency control effects of power resources (wind power, photovoltaic, energy storage) in embodiments of this application (active power and reactive power response characteristics). Active power is measured in MW (megawatts), and reactive power is measured in MVAr (megavars). The active power response of wind power is shown below. A fluctuation occurs at 5s, with an amplitude not exceeding 2MW and a duration not exceeding 0.1s. After the fluctuation, its change with time t is relatively stable. (Photovoltaic active power response) Active power response of energy storage The change with time t is relatively stable. Total active power response Similarly, a fluctuation occurs at 5 seconds, but it recovers to a stable state within a short time of no more than 0.2 seconds, achieving second-level stable support control. The total active power response is the sum of the active power responses of wind power, photovoltaic power, and energy storage. The reactive power response of wind power... Reactive power response of photovoltaics Reactive power response of energy storage and total reactive power response The curves show roughly the same trend, with small response fluctuations and short durations of large fluctuations, enabling stable support control at the second level. The total reactive power response is the sum of the reactive power responses of wind power, photovoltaic power, and energy storage. The voltage and frequency dynamic support resources in the embodiments of this application can accurately and quickly provide support services for new power systems. This is of great significance for promoting the participation of new regulation resources such as new energy and energy storage in the ancillary service market such as rapid frequency regulation and voltage regulation, and for improving the safety and stability of new power systems. It has high practical value and can be widely applied in the fields of new power systems and new energy technologies.

[0204] Please see Figure 10 This application also provides a frequency and voltage support control device for a new energy base, which can implement the above-mentioned frequency and voltage support control method for a new energy base. The frequency and voltage support control device for the new energy base includes:

[0205] The determination module 1010 is used to determine the power resource category of the new energy base and calculate the frequency and voltage dynamic support factors of the power resources corresponding to the power resource category;

[0206] The calculation module 1020 is used to calculate the reference sensitivity transfer matrix corresponding to the power resource if the power resource category is a controllable power resource category, based on the frequency and voltage dynamic support factor and the pre-acquired frequency and voltage support control matrix of the new energy base to the power grid; wherein, the reference sensitivity transfer matrix is ​​used to indicate the mapping relationship between the output active power, output reactive power and frequency fluctuation and voltage fluctuation of the power resource corresponding to the controllable power resource category.

[0207] Construction module 1030 is used to construct a frequency and voltage support mechanism control model based on the reference sensitivity transfer matrix;

[0208] Solver module 1040 is used to solve the frequency and voltage support mechanism control model to obtain the frequency and voltage support control strategy of the power resources;

[0209] The control module 1050 is used to perform frequency and voltage support control on the power resources according to the frequency and voltage support control strategy.

[0210] The specific implementation method of the frequency and voltage support control device of the new energy base is basically the same as the specific implementation method of the frequency and voltage support control method of the new energy base mentioned above, and will not be repeated here.

[0211] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the aforementioned frequency and voltage support control method for the new energy base. This electronic device can be any smart terminal, including tablet computers, in-vehicle computers, etc.

[0212] Please see Figure 11 , Figure 11 The hardware structure of an electronic device according to another embodiment is illustrated. The electronic device includes:

[0213] The processor 1110 can be implemented using a general-purpose central processing unit (CPU), microprocessor, application specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application.

[0214] The memory 1120 can be implemented as a read-only memory (ROM), static storage device, dynamic storage device, or random access memory (RAM). The memory 1120 can store the operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 1120 and is called and executed by the processor 1110 to execute the frequency and voltage support control method for the new energy base of this application embodiment.

[0215] The input / output interface 1130 is used to implement information input and output;

[0216] The communication interface 1140 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, network cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0217] Bus 1150 transmits information between various components of the device (e.g., processor 1110, memory 1120, input / output interface 1130, and communication interface 1140);

[0218] The processor 1110, memory 1120, input / output interface 1130 and communication interface 1140 are connected to each other within the device via bus 1150.

[0219] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the aforementioned frequency and voltage support control method for a new energy base.

[0220] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0221] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0222] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0223] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0224] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or appropriate combinations thereof.

[0225] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0226] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0227] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0228] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0229] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0230] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0231] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A frequency and voltage support control method for a new energy base, characterized in that, The method includes: Determine the power resource category of the new energy base, and calculate the frequency and voltage dynamic support factors of the power resources corresponding to the power resource category; If the power resource category is a controllable power resource category, then based on the frequency and voltage dynamic support factors and the pre-acquired frequency and voltage support control matrix of the new energy base for the power grid, the reference sensitivity transfer matrix corresponding to the power resource is calculated; wherein, the reference sensitivity transfer matrix is ​​used to indicate the mapping relationship between the output active power, output reactive power and frequency fluctuation and voltage fluctuation of the power resource corresponding to the controllable power resource category. A frequency and voltage support mechanism control model is constructed based on the reference sensitivity transfer matrix; Solve the frequency and voltage support mechanism control model to obtain the frequency and voltage support control strategy for the power resources; The power resources are subjected to frequency and voltage support control according to the frequency and voltage support control strategy. The construction of the frequency and voltage support mechanism control model based on the reference sensitivity transfer matrix includes: Based on the reference sensitivity transfer matrix, construct a frequency and voltage support control reference state space model and a frequency and voltage support control state space model including a current control loop for power resources; construct an augmented state space model based on the frequency and voltage support control reference state space model and the frequency and voltage support control state space model; construct the frequency and voltage support mechanism control model based on the augmented state space model. The construction of the augmented state space model based on the frequency and voltage supported control reference state space model and the frequency and voltage supported control state space model includes: Based on the frequency and voltage supported control reference state space model and the frequency and voltage supported control state space model, determine the control deviation variable; based on the frequency and voltage supported control reference state space model and the frequency and voltage supported control state space model, determine the state variable; based on the frequency and voltage supported control reference state space model and the frequency and voltage supported control state space model, determine the system matrix; construct the augmented state space model based on the control deviation variable, the state variable, and the system matrix. The solution to the frequency and voltage support mechanism control model yields the frequency and voltage support control strategy for the power resources, including: Obtain the sample frequency and voltage support control strategy and sample control deviation; construct a data matrix based on the sample frequency and voltage support control strategy and the sample control deviation; convert the frequency and voltage support mechanism control model into a deterministic data control model based on the data matrix; convert the deterministic data control model into a sub-Bruker data control model; solve the sub-Bruker data control model to obtain the frequency and voltage support control strategy.

2. The method according to claim 1, characterized in that, The power resource category includes uncontrollable power resource categories, and the calculation of the frequency and voltage dynamic support factors of the power resources corresponding to the power resource category includes: Obtain the expected sensitivity transfer matrix of the power resource corresponding to the uncontrollable power resource category; wherein, the expected sensitivity transfer matrix is ​​used to indicate the mapping relationship between the output active power, output reactive power and frequency fluctuation and voltage fluctuation of the power resource corresponding to the uncontrollable power resource category; Based on the pre-acquired frequency and voltage support control matrix of the new energy base for the power grid and the expected sensitivity transfer matrix, the frequency and voltage dynamic support factor of the power resources is calculated.

3. The method according to claim 1, characterized in that, The power resource category includes controllable power resource categories, and the calculation of the frequency and voltage dynamic support factors of the power resources corresponding to the power resource category includes: Obtain the time scale for the frequency and voltage support provided by the power resources corresponding to the controllable power resource category; Determine the filter model based on the time scale; The frequency and voltage dynamic support factors of the power resources are determined based on the filter model.

4. The method according to claim 3, characterized in that, After determining the frequency and voltage dynamic support factors of the power resource based on the filter model, the method further includes: Obtain historical operating data of the new energy base; wherein, the historical operating data includes dynamic input and output response time series of power resources; Data fitting is performed on the dynamic input and output response time series to obtain the dynamic support factor time constant; If the filter model is a bandpass filter, then the frequency and voltage dynamic support factors are optimized according to the dynamic support factor time constant; If the filter model is a low-pass filter, a dynamic support factor gain optimization model is constructed, and the dynamic support factor gain is obtained by solving the dynamic support factor gain optimization model. The frequency and voltage dynamic support factors are then optimized based on the dynamic support factor time constant and the dynamic support factor gain.

5. A frequency and voltage support control device for a new energy base, characterized in that, The device includes: The determination module is used to determine the power resource category of the new energy base and calculate the frequency and voltage dynamic support factors of the power resources corresponding to the power resource category; The calculation module is used to calculate the reference sensitivity transfer matrix corresponding to the power resource if the power resource category is a controllable power resource category, based on the frequency and voltage dynamic support factor and the pre-acquired frequency and voltage support control matrix of the new energy base to the power grid; wherein, the reference sensitivity transfer matrix is ​​used to indicate the mapping relationship between the output active power, output reactive power and frequency fluctuation and voltage fluctuation of the power resource corresponding to the controllable power resource category. The module is used to construct a frequency and voltage support mechanism control model based on the reference sensitivity transfer matrix; The solution module is used to solve the frequency and voltage support mechanism control model to obtain the frequency and voltage support control strategy of the power resources. The control module is used to perform frequency and voltage support control on the power resources according to the frequency and voltage support control strategy; The construction of the frequency and voltage support mechanism control model based on the reference sensitivity transfer matrix includes: Based on the reference sensitivity transfer matrix, construct a frequency and voltage support control reference state space model and a frequency and voltage support control state space model including a current control loop for power resources; construct an augmented state space model based on the frequency and voltage support control reference state space model and the frequency and voltage support control state space model; construct the frequency and voltage support mechanism control model based on the augmented state space model. The construction of the augmented state space model based on the frequency and voltage supported control reference state space model and the frequency and voltage supported control state space model includes: Based on the frequency and voltage supported control reference state space model and the frequency and voltage supported control state space model, determine the control deviation variable; based on the frequency and voltage supported control reference state space model and the frequency and voltage supported control state space model, determine the state variable; based on the frequency and voltage supported control reference state space model and the frequency and voltage supported control state space model, determine the system matrix; construct the augmented state space model based on the control deviation variable, the state variable, and the system matrix. The solution to the frequency and voltage support mechanism control model yields the frequency and voltage support control strategy for the power resources, including: Obtain the sample frequency and voltage support control strategy and sample control deviation; construct a data matrix based on the sample frequency and voltage support control strategy and the sample control deviation; convert the frequency and voltage support mechanism control model into a deterministic data control model based on the data matrix; convert the deterministic data control model into a sub-Bruker data control model; solve the sub-Bruker data control model to obtain the frequency and voltage support control strategy.

6. An electronic device, characterized in that, The electronic device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method according to any one of claims 1 to 4.

7. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method described in any one of claims 1 to 4.

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