Virtual power plant grid frequency regulation and stabilization method based on energy storage resource aggregation

Abstract

This invention relates to the field of virtual power plants, providing a method for frequency regulation and stabilization of a virtual power plant grid based on energy storage resource aggregation. The method includes constructing a virtual power plant network; collecting mechanical equivalent parameters to obtain a cluster inertia constant expression; determining the cluster inertia constant; calculating the cluster contribution factor using the cluster inertia constant and the system inertia constant; calculating the steady-state frequency deviation and frequency response characteristic parameters; obtaining the cluster steady-state contribution factor based on the steady-state frequency deviation and frequency response characteristic parameters; determining the steady-state factor parameters and obtaining a first power contribution value; obtaining a second power contribution value through a regional control error expression; and performing frequency regulation on the virtual power plant network; obtaining an update of the first power contribution value; performing primary frequency stabilization on the virtual power plant network; and obtaining the rate of change of the second power contribution value through Taylor expansion; and performing secondary frequency stabilization on the virtual power plant network. This invention can effectively improve the operational stability of virtual power plant networks.

Description

Technical Field

[0001] This invention relates to the field of virtual power plant technology, and in particular to a method for grid frequency regulation and stabilization based on energy storage resource aggregation in virtual power plants. Background Technology

[0002] Frequency regulation technology is one of the important means to maintain grid stability in power system operation. In traditional power systems, frequency regulation is mainly provided by synchronous generators. These generators have mechanical inertia and can provide PFC (Primary Frequency Control) through rotor dynamic response, restoring the system frequency by adjusting the output power. These methods are achieved through mechanical load regulation and generally do not depend on external signal input.

[0003] Virtual Power Plant (VPP) technology is used to integrate multiple distributed energy resources (such as wind and solar power) to provide regulation services similar to those of traditional power plants. However, the resources in a VPP are often heterogeneous, and many resources, such as renewable energy resources, are difficult to provide inertial responses in the traditional sense. Therefore, how to effectively utilize these resources to participate in frequency regulation in the power grid has become a research hotspot. Although existing virtual power plant models can dispatch different renewable energy resources and provide power dispatch, these models often lack real-time dynamic response capabilities and cannot effectively handle rapid changes in grid frequency.

[0004] In inverter-based frequency regulation technologies, existing techniques primarily employ methods that mimic inertial response to enhance the inverter's role in frequency regulation. For example, through virtual inertial control, the inverter can simulate the inertial characteristics of a traditional synchronous generator to provide primary frequency control. Furthermore, some solutions utilize strategies such as virtual load response and droop control to adjust the inverter's output power in response to frequency changes. Most of these technologies focus on enabling the inverter to respond quickly to frequency changes through control algorithms; however, due to a lack of real-time dynamic adjustment capabilities, the system may not be able to maintain stability during rapid fluctuations in grid frequency, especially with high renewable energy penetration.

[0005] Some studies use reinforcement learning to optimize frequency regulation services for various resources in virtual power plants. These methods train intelligent algorithms to optimize frequency response strategies and intelligently allocate regulation resources when the grid experiences disturbances. Such techniques typically require large amounts of historical data and training processes, iteratively improving control strategies. However, applying reinforcement learning methods to real-time systems presents significant challenges, particularly in terms of algorithm stability and computational efficiency. Summary of the Invention

[0006] This invention aims to at least solve one of the technical problems existing in related technologies. To this end, this invention provides a method for regulating and stabilizing the grid frequency of a virtual power plant based on energy storage resource aggregation, thereby achieving effective regulation and stabilization of the grid frequency of the virtual power plant.

[0007] This invention provides a method for grid frequency regulation and stabilization based on virtual power plants using energy storage resource aggregation, comprising: S1: Construct a virtual power plant network including power clusters, collect the mechanical equivalent parameters of the power clusters, and construct an expression for the cluster inertia constant based on the mechanical equivalent parameters; S2: Determine the power grid scale and calculate the power frequency characteristic coefficient. Determine the expected rate of frequency change based on the power grid scale. Calculate the system power imbalance based on the power frequency characteristic coefficient. Calculate the system inertia constant using the system power imbalance. Determine the cluster inertia constant based on the expected rate of frequency change and the expression for the cluster inertia constant. Calculate the cluster contribution factor using the cluster inertia constant and the system inertia constant. S3: Construct the power grid parameter expression, calculate the steady-state frequency deviation and frequency response characteristic parameters through the power grid parameter expression, and obtain the cluster steady-state contribution factor based on the steady-state frequency deviation and frequency response characteristic parameters; S4: Determine the steady-state factor parameters based on the cluster contribution factor and the cluster steady-state contribution factor. Obtain the first power contribution value through the steady-state factor parameters. Construct the regional control error expression. Obtain the second power contribution value through the regional control error expression. Perform frequency regulation on the virtual power plant network based on the first power contribution value and the second power contribution value. During frequency regulation, obtain the load change curve, decompose the load change curve to obtain the regulation weight, and perform frequency regulation based on the regulation weight. S5: Obtain the first power contribution value update amount through the expression of the cluster steady-state contribution factor, and perform primary frequency stabilization on the virtual power plant network through the first power contribution value update amount; S6: Obtain the rate of change of the second power contribution value through Taylor expansion, and use the rate of change of the second power contribution value to perform secondary frequency stabilization on the virtual power plant network.

[0008] According to the virtual power plant grid frequency regulation and stabilization method based on energy storage resource aggregation provided by the present invention, step S1 further includes: S11: Construct a virtual power plant network that includes power clusters, wherein the power clusters include new energy power supply equipment; S12: Collect the mechanical equivalent parameters of the power cluster, including the equivalent rotor angle and the equivalent motor running time, and construct the expression for the cluster inertia constant based on the mechanical equivalent parameters.

[0009] According to the virtual power plant grid frequency regulation and stabilization method based on energy storage resource aggregation provided by the present invention, step S2 further includes: S21: Obtain the equivalent grid inertia constant and grid parameter change values, use the grid parameter change values ​​to calculate the power frequency characteristic coefficient, thereby calculating the system power imbalance, and constructing a frequency change rate expression using the system power imbalance and the equivalent grid inertia constant; S22: Determine the power grid scale, and determine the expected rate of frequency change based on the power grid scale; determine the system inertial constant based on the expected rate of frequency change, the expression for the rate of frequency change, and the system power imbalance. S23: Determine the cluster power imbalance, determine the cluster inertia constant constraint condition based on the expected rate of change of frequency and the cluster power imbalance, determine the cluster inertia constant under the constraint condition based on the cluster inertia constant expression, and calculate the cluster contribution factor through the system inertia constant and the cluster inertia constant.

[0010] According to the virtual power plant grid frequency regulation and stabilization method based on energy storage resource aggregation provided by the present invention, step S3 further includes: S31: Construct power grid parameter expressions that include steady-state frequency deviation expressions and frequency response characteristic expressions; S32: Establish an equivalent frequency deviation expression and obtain frequency recovery reserve parameters. Use the equivalent frequency deviation expression and the frequency recovery reserve parameters to calculate the desired steady-state frequency deviation. Obtain the frequency response characteristic parameters through the desired steady-state frequency deviation and the power grid parameter expression. Solve the cluster steady-state contribution factor based on the desired steady-state frequency deviation and the frequency response characteristic parameters.

[0011] According to the virtual power plant grid frequency regulation and stabilization method based on energy storage resource aggregation provided by the present invention, step S4 further includes: S41: Use the maximum value of the cluster contribution factor and the cluster steady-state contribution factor as the steady-state factor parameter, and use the steady-state factor parameter and the frequency recovery reserve parameter to calculate the first power contribution value; S42: Obtain power grid operating parameters, construct the regional control error expression including a first regional control error expression and a second regional control error expression based on the power grid operating parameters, and obtain the second power contribution value through the first regional control error expression and the second regional control error expression; S43: Frequency regulation is performed on the virtual power plant network using the first power contribution value and the second power contribution value. During frequency regulation, a load change curve is acquired, and empirical mode decomposition is performed on the load change curve to obtain multiple decomposed load curves. The frequency and amplitude of the decomposed load curves are analyzed to obtain the regulation weights, and the virtual power plant network is controlled to perform frequency regulation according to the regulation weights.

[0012] According to the method for frequency regulation and stabilization of virtual power plant grid based on energy storage resource aggregation provided by the present invention, in step S5, the expression of the cluster steady-state contribution factor is expanded by Taylor to obtain the steady-state factor parameter expansion formula, and the first power contribution value update amount is obtained according to the steady-state factor parameter expansion formula. The first power contribution value update amount is used to perform primary frequency stabilization of the virtual power plant network.

[0013] This invention also provides a virtual power plant grid frequency regulation and stabilization system based on energy storage resource aggregation, comprising: Cluster inertia constant expression module: used to build a virtual power plant network including power clusters, collect the mechanical equivalent parameters of the power clusters, and construct the cluster inertia constant expression based on the mechanical equivalent parameters; Cluster Contribution Factor Module: Used to determine the grid scale and calculate the power frequency characteristic coefficient, determine the expected rate of frequency change based on the grid scale, calculate the system power imbalance based on the power frequency characteristic coefficient, calculate the system inertia constant using the system power imbalance, determine the cluster inertia constant based on the expected rate of frequency change and the expression for the cluster inertia constant, and calculate the cluster contribution factor using the cluster inertia constant and the system inertia constant. Cluster steady-state contribution factor module: used to construct power grid parameter expressions, calculate steady-state frequency deviation and frequency response characteristic parameters through power grid parameter expressions, and obtain the cluster steady-state contribution factor based on steady-state frequency deviation and frequency response characteristic parameters; Frequency regulation module: It is used to determine the steady-state factor parameters based on the cluster contribution factor and the cluster steady-state contribution factor, obtain the first power contribution value through the steady-state factor parameters, construct the regional control error expression, obtain the second power contribution value through the regional control error expression, and perform frequency regulation on the virtual power plant network based on the first power contribution value and the second power contribution value. During frequency regulation, the load change curve is acquired, the load change curve is decomposed to obtain the regulation weight, and frequency regulation is performed according to the regulation weight. Primary frequency stabilization module: used to obtain the first power contribution value update amount through the expression of the cluster steady-state contribution factor, and to perform primary frequency stabilization on the virtual power plant network through the first power contribution value update amount; Secondary frequency stabilization module: used to obtain the rate of change of the second power contribution value through Taylor expansion, and to perform secondary frequency stabilization on the virtual power plant network using the rate of change of the second power contribution value.

[0014] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the virtual power plant grid frequency regulation and stabilization method based on energy storage resource aggregation as described above.

[0015] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the virtual power plant grid frequency regulation and stabilization method based on energy storage resource aggregation as described above.

[0016] The present invention also provides a computer program product, the computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, and when the program instructions are executed by a computer, the computer is able to perform the steps of any of the above-described methods for virtual power plant grid frequency regulation and stabilization based on energy storage resource aggregation.

[0017] The above-described one or more technical solutions in the embodiments of the present invention have at least one of the following technical effects: The present invention provides a method for regulating and stabilizing grid frequency in a virtual power plant network based on energy storage resource aggregation. This method can quickly adjust the power of each cluster in the virtual power plant network to balance fluctuations when the grid frequency fluctuates or power is unbalanced. Furthermore, the proposed solution does not rely on complex algorithms, thus effectively saving computational resources. It also provides timely responses to fluctuations and imbalances, thereby reducing reaction time and improving grid operating efficiency.

[0018] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0020] Figure 1 This is a flowchart illustrating the method for virtual power plant grid frequency regulation and stabilization based on energy storage resource aggregation provided by the present invention.

[0021] Figure 2 This is a schematic diagram of the structure of the virtual power plant grid frequency regulation and stabilization system based on energy storage resource aggregation provided by the present invention.

[0022] Figure 3 This is a schematic diagram of the structure of the virtual power plant grid frequency regulation and stabilization device based on energy storage resource aggregation provided by the present invention.

[0023] Figure label: 100. Cluster inertia constant expression module; 200. Cluster contribution factor module; 300. Cluster steady-state contribution factor module; 400. Frequency adjustment module; 500. Primary frequency stabilization module; 600. Secondary frequency stabilization module; 810. Processor; 820. Communication interface; 830. Memory; 840. Communication bus. Detailed Implementation

[0024] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention. The following embodiments are used to illustrate this invention but cannot be used to limit the scope of this invention.

[0025] In the description of the embodiments of the present invention, it should be noted that the terms "first", "second" and "third" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0026] In the description of the embodiments of the present invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "connected" and "linked" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium. Those skilled in the art can understand the specific meaning of the above terms in the embodiments of the present invention based on the specific circumstances.

[0027] In embodiments of the present invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can mean that the first feature is in direct contact with the second feature, or that the first feature is in indirect contact with the second feature through an intermediate medium. Furthermore, "above," "on top of," and "over" the second feature can mean that the first feature is directly above or diagonally above the second feature, or simply that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature can mean that the first feature is directly below or diagonally below the second feature, or simply that the first feature is at a lower horizontal level than the second feature.

[0028] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0029] The following is combined Figures 1 to 3 Specific embodiments of the present invention are described below: Figure 1 This is a flowchart illustrating the method for frequency regulation and stabilization of a virtual power plant grid based on energy storage resource aggregation provided by the present invention. First, a virtual power plant network is constructed, mechanical equivalent parameters of the power cluster are collected, and an expression for the cluster inertia constant is built. Next, the expected rate of frequency change is determined, thereby determining the cluster inertia constant. The cluster contribution factor is calculated using the cluster inertia constant and the system inertia constant. Then, the steady-state frequency deviation and frequency response characteristic parameters are calculated using the grid parameter expression, thereby obtaining the cluster steady-state contribution factor. Next, the first power contribution value and the second power contribution value are obtained, thereby performing frequency regulation. Then, the update amount of the first power contribution value is obtained through the expression for the cluster steady-state contribution factor, and primary frequency stabilization is performed using the update amount of the first power contribution value. Finally, the rate of change of the second power contribution value is obtained through Taylor expansion, and secondary frequency stabilization is performed using the rate of change of the second power contribution value.

[0030] This invention provides a method for grid frequency regulation and stabilization based on virtual power plants using energy storage resource aggregation, comprising: S1: Construct a virtual power plant network including power clusters, collect the mechanical equivalent parameters of the power clusters, and construct an expression for the cluster inertia constant based on the mechanical equivalent parameters; Furthermore, the objective of this stage is to construct a virtual power plant network and collect mechanical equivalent parameters to calculate the cluster power imbalance. Specifically, step S1 further includes: S11: Construct a virtual power plant network that includes power clusters, wherein the power clusters include new energy power supply equipment; S12: Collect the mechanical equivalent parameters of the power cluster, including the equivalent rotor angle and the equivalent motor running time, and construct the expression for the cluster inertia constant based on the mechanical equivalent parameters.

[0031] The specific implementation method for the above steps in this embodiment is as follows: First, a virtual power plant network comprising power clusters is constructed. This virtual power plant network is dynamic and connected to the external power grid. It includes multiple power clusters, each composed of multiple renewable energy power supply devices, including wind power, photovoltaic power, and pumped-storage hydroelectric power generation equipment. The virtual power plant network can use information technology and software communication to uniformly aggregate, manage, and coordinate the various power clusters, enabling them to participate in the electricity market and grid operation as specialized power plants.

[0032] Next, when a power imbalance occurs in the virtual power plant network—that is, when there is a significant difference between the external energy demand and the electrical energy provided by the virtual power plant network—each power cluster needs to be treated as a generator and controlled accordingly. The magnitude of the power imbalance is then used as the system power imbalance quantity. For the i-th power cluster, the power imbalance it faces is the cluster power imbalance amount of the i-th power cluster. In conventional power plants, generator rotors possess mechanical parameters such as torque. However, many renewable energy power supply devices lack mechanical components. Therefore, it is necessary to obtain the equivalent rotor angle, including that of the i-th power cluster, based on the status and parameters of the renewable energy power supply devices. The mechanical equivalent parameters of the equivalent motor running time t of the i-th power cluster are used to obtain the cluster inertia constant of the i-th power cluster. The expression for the cluster inertia constant: In addition, when the inertial constant of each new energy power supply device in the power cluster can be obtained, their inertial constant estimates can be summed to obtain the cluster inertial constant.

[0033] Next, Rewritten as the cluster frequency change rate of the i-th power cluster Thus we get: S2: Determine the power grid scale and calculate the power frequency characteristic coefficient. Determine the expected rate of frequency change based on the power grid scale. Calculate the system power imbalance based on the power frequency characteristic coefficient. Calculate the system inertia constant using the system power imbalance. Determine the cluster inertia constant based on the expected rate of frequency change and the expression for the cluster inertia constant. Calculate the cluster contribution factor using the cluster inertia constant and the system inertia constant. Furthermore, the objective of this stage is to determine the power grid scale and calculate the power frequency characteristic coefficient, determine the expected rate of frequency change based on the power grid scale, calculate the system power imbalance based on the power frequency characteristic coefficient, calculate the system inertia constant using the system power imbalance, thereby determining the cluster inertia constant and calculating the cluster contribution factor. Specifically, step S2 further includes: S21: Obtain the equivalent grid inertia constant and grid parameter change values, use the grid parameter change values ​​to calculate the power frequency characteristic coefficient, thereby calculating the system power imbalance, and constructing a frequency change rate expression using the system power imbalance and the equivalent grid inertia constant; S22: Determine the power grid scale, and determine the expected rate of frequency change based on the power grid scale; determine the system inertial constant based on the expected rate of frequency change, the expression for the rate of frequency change, and the system power imbalance. S23: Determine the cluster power imbalance, determine the cluster inertia constant constraint condition based on the expected rate of change of frequency and the cluster power imbalance, determine the cluster inertia constant under the constraint condition based on the cluster inertia constant expression, and calculate the cluster contribution factor through the system inertia constant and the cluster inertia constant.

[0034] The specific implementation method for the above steps in this embodiment is as follows: First, obtain values ​​including the power grid frequency change. and power grid power change value The changes in power grid parameters are used to calculate the droop coefficient. δ : in, The nominal frequency of the power grid is the frequency that the power grid should maintain during operation. The change in power grid frequency is the difference between the actual frequency of the power grid and the nominal frequency. The change in power grid power is the difference between the actual load power of the power grid and the rated power of the power grid. The deviation value.

[0035] Once the droop coefficient is obtained, the power frequency characteristic coefficient can be calculated. : Therefore, the power frequency characteristic coefficient is used to calculate the system power imbalance. : In addition, it is necessary to obtain the equivalent grid inertia constant of the power grid to which the virtual power plant network is connected. Thus, the expression for the rate of change of frequency can be constructed: in, This represents the frequency change rate of the virtual power plant network. When power imbalance occurs, the system inertia constant of the virtual power plant network during balancing also needs to be considered. Therefore, the expression for the rate of change of frequency now becomes: The size of the power grid is determined, and the larger the power grid, the smaller the required frequency change rate. This is because the safe operation of the virtual power plant network requires ensuring that the frequency change rate is lower than the expected frequency change rate determined based on the power grid size. Therefore, we can obtain: Further deformation will yield the following: Thus, the system inertia constant can be obtained based on the constraints of the above formula. During balancing, the cluster inertia constant of each power cluster also needs to satisfy the expected rate of frequency change. Therefore, the cluster power imbalance can be determined based on the grid power change value and the number of power clusters, and the cluster inertia constant constraint condition can be derived by analogy: When the cluster inertia constant does not satisfy this constraint, it is set to the lowest value that satisfies the cluster inertia constant constraint. Thus, under the constraint of the cluster inertia constant, the cluster contribution factor of the i-th power cluster is calculated using the system inertia constant and the cluster inertia constant. : S3: Construct the power grid parameter expression, calculate the steady-state frequency deviation and frequency response characteristic parameters through the power grid parameter expression, and obtain the cluster steady-state contribution factor based on the steady-state frequency deviation and frequency response characteristic parameters; Furthermore, the objective of this stage is to construct the power grid parameter expression, thereby calculating the steady-state frequency deviation and frequency response characteristic parameters, and finally obtaining the cluster steady-state contribution factor. Specifically, step S3 further includes: S31: Construct power grid parameter expressions that include steady-state frequency deviation expressions and frequency response characteristic expressions; S32: Establish an equivalent frequency deviation expression and obtain frequency recovery reserve parameters. Use the equivalent frequency deviation expression and the frequency recovery reserve parameters to calculate the desired steady-state frequency deviation. Obtain the frequency response characteristic parameters through the desired steady-state frequency deviation and the power grid parameter expression. Solve the cluster steady-state contribution factor based on the desired steady-state frequency deviation and the frequency response characteristic parameters.

[0036] The specific implementation method for the above steps in this embodiment is as follows: When power imbalance occurs, the steady-state frequency deviation expression of the virtual power plant network is: in, For steady-state frequency deviation, Given the frequency response characteristics of a known virtual power plant network connected to a power grid, we establish the following expression for the frequency response characteristics: in, The droop characteristic parameters of the power grid connected to the virtual power plant network. This refers to the load damping of the power grid connected to the virtual power plant network. When balancing power imbalances, the frequency response parameters of the virtual power plant network at the time of balancing must be considered. Therefore, based on the steady-state frequency deviation expression, an equivalent frequency deviation expression is established: in, To calculate the desired steady-state frequency deviation of the virtual power plant network under balancing conditions, we can see that the frequency response parameters can be solved using this formula. However, the frequency response parameters are unknown at this point. To solve for the steady-state frequency deviation, we need to obtain the known frequency recovery reserve parameters. After subtracting it, the frequency response parameter can be ignored. Thus, the desired steady-state frequency deviation can be expressed as: This allows us to solve for the desired steady-state frequency deviation, and further, to obtain the frequency response parameters of the virtual power plant network. For each power cluster, the grid parameter expression also holds true; therefore, we replace the parameters in the original grid parameter expression with the parameters of the power cluster to obtain the frequency response parameters of the i-th power cluster. : Finally, the steady-state contribution factor of the i-th power cluster can be calculated based on the steady-state frequency deviation and frequency response parameters. : S4: Determine the steady-state factor parameters based on the cluster contribution factor and the cluster steady-state contribution factor. Obtain the first power contribution value through the steady-state factor parameters. Construct the regional control error expression. Obtain the second power contribution value through the regional control error expression. Perform frequency regulation on the virtual power plant network based on the first power contribution value and the second power contribution value. During frequency regulation, obtain the load change curve, decompose the load change curve to obtain the regulation weight, and perform frequency regulation based on the regulation weight. Furthermore, the objective of this stage is to determine the steady-state factor parameters, thereby obtaining the first power contribution value and the second power contribution value, and to perform frequency regulation on the virtual power plant network. Specifically, step S4 further includes: S41: Use the maximum value of the cluster contribution factor and the cluster steady-state contribution factor as the steady-state factor parameter, and use the steady-state factor parameter and the frequency recovery reserve parameter to calculate the first power contribution value; S42: Obtain power grid operating parameters, construct the regional control error expression including a first regional control error expression and a second regional control error expression based on the power grid operating parameters, and obtain the second power contribution value through the first regional control error expression and the second regional control error expression; S43: Frequency regulation is performed on the virtual power plant network using the first power contribution value and the second power contribution value. During frequency regulation, a load change curve is acquired, and empirical mode decomposition is performed on the load change curve to obtain multiple decomposed load curves. The frequency and amplitude of the decomposed load curves are analyzed to obtain the regulation weights, and the virtual power plant network is controlled to perform frequency regulation according to the regulation weights.

[0037] The specific implementation method for the above steps in this embodiment is as follows: First, the maximum value between the cluster contribution factor and the cluster steady-state contribution factor is used as the steady-state factor parameter of the i-th power cluster. Then, based on the frequency recovery reserve parameters and steady-state factor parameters, the first power contribution value of the i-th power cluster can be calculated. : Subsequently, data including the actual switching power (AIP) of the power grid, the planned switching power (SIP), the frequency offset parameter (B), and the actual frequency are obtained. and nominal frequency The power grid operating parameters are used to construct the first region control error expression, and to calculate the first region control error value ACE: Thus, the actual switching power of the i-th power cluster can be determined based on the power grid operating parameters. The actual frequency of the i-th power cluster The actual frequency of the i-th power cluster and the nominal frequency of the i-th power cluster This allows for the construction of a second-region control error expression to calculate the second-region control error value for the i-th power cluster. : In this way, the second power contribution value of the i-th power cluster can be obtained using the first area control error value and the second area control error value. : In this way, when a power imbalance occurs, the i-th power cluster outputs a first power contribution value during the primary frequency control phase, and then outputs a second power contribution value during the secondary frequency control phase. The virtual power plant network can then be used for frequency regulation to alleviate the power imbalance.

[0038] When performing power regulation, since the virtual power grid includes various new energy power supply devices with different characteristics, it is necessary to first obtain the load change curve of the power grid and then perform empirical mode decomposition on the load change curve to obtain multiple decomposed load curves. The load change curve can be regarded as the superposition of the decomposed load curves. For the load change of the power grid, there are mainly two types: one is a load change with a high fluctuation frequency and a small amplitude change, which is mainly caused by normal power consumption fluctuations in the power grid; the other is a load change with a low fluctuation frequency and a large amplitude change, which is usually caused by high-power loads such as electric locomotives and machine tools with long operating times. By analyzing and statistically analyzing the frequency and amplitude of all decomposed load curves, it is possible to determine which type of load change mainly causes the load change curve, thereby obtaining the regulation weight.

[0039] Adjustment weights are used to regulate the proportion of different renewable energy power supply devices in the virtual power grid during frequency regulation of output power. For example, when the load change curve is mainly caused by load changes with high frequency and small amplitude, renewable energy power supply devices with higher adjustment flexibility but lower power, such as batteries and flywheel energy storage devices, can be given higher adjustment weights, thus allowing them to contribute the main power output. Conversely, renewable energy power supply devices with lower adjustment flexibility but higher power, such as pumped hydro storage and molten salt energy storage devices, can be given higher adjustment weights, thus allowing them to contribute the main power output. By adjusting the weights, the renewable energy power supply devices in the virtual power plant network can select more suitable renewable energy power supply devices based on the characteristics of load changes, thereby improving the stability of regulation.

[0040] S5: Obtain the first power contribution value update amount through the expression of the cluster steady-state contribution factor, and perform primary frequency stabilization on the virtual power plant network through the first power contribution value update amount; Furthermore, the objective of this stage is to perform primary frequency stabilization on the virtual power plant network using the first power contribution value update. Specifically, in step S5, the expression for the cluster steady-state contribution factor is expanded using Taylor to obtain the steady-state factor parameter expansion. The first power contribution value update is obtained based on the steady-state factor parameter expansion, and the first power contribution value update is used to perform primary frequency stabilization on the virtual power plant network.

[0041] The specific implementation method for the above steps in this embodiment is as follows: After frequency regulation, during continuous operation, since both the virtual power plant network and the external power grid are dynamic, the initial power contribution value needs to be continuously updated to cope with these changes. Here, we first perform a Taylor expansion on the expression of the cluster steady-state contribution factor to obtain the steady-state factor parameter expansion: in, The change value of the steady-state factor parameter is given. Since the frequency response parameters and power imbalance of the i-th power cluster can be continuously obtained during the continuous operation of the virtual power plant network, the expansion of the steady-state factor parameter can be calculated to obtain the update value of the first power contribution of the i-th power cluster. : Using the first power contribution value update allows the power cluster to continuously adjust its output power during the subsequent primary frequency control phase to achieve primary frequency stabilization of the virtual power plant network, thus ensuring that power imbalances are continuously stabilized during subsequent operation.

[0042] S6: Obtain the rate of change of the second power contribution value through Taylor expansion, and use the rate of change of the second power contribution value to perform secondary frequency stabilization on the virtual power plant network.

[0043] Furthermore, the objective of this stage is to obtain the rate of change of the second power contribution value, thereby achieving secondary frequency stabilization. Specifically, firstly, the update amount of the second power contribution value of the i-th power cluster can be written as... : in, Let be the rate of change of the second power contribution value of the i-th power cluster. To calculate the rate of change of the second power contribution value, we can perform a Taylor expansion on the expression for the second power contribution value, thereby obtaining the rate of change of the second power contribution value: In this way, the update amount of the second power contribution value can be obtained through the change rate of the second power contribution value, so that the power cluster can continuously adjust the output power in the subsequent secondary frequency control stage to continuously stabilize the secondary frequency of the virtual power plant network, thereby ensuring the smooth operation of the virtual power plant network.

[0044] This invention effectively balances the power imbalance of the virtual power plant network by continuously controlling and stabilizing the frequency, thus ensuring the stable operation of the virtual power plant network.

[0045] The following describes the virtual power plant grid frequency regulation and stabilization device based on energy storage resource aggregation provided by the present invention. The virtual power plant grid frequency regulation and stabilization device based on energy storage resource aggregation described below can be referred to in correspondence with the virtual power plant grid frequency regulation and stabilization method based on energy storage resource aggregation described above.

[0046] Figure 2 A schematic diagram of a virtual power plant grid frequency regulation and stabilization system based on energy storage resource aggregation is shown, such as... Figure 2 As shown, the method for implementing the virtual power plant grid frequency regulation and stabilization method based on energy storage resource aggregation as described above includes: Cluster inertia constant expression module 100: used to construct a virtual power plant network including power clusters, collect the mechanical equivalent parameters of the power clusters, and construct the cluster inertia constant expression based on the mechanical equivalent parameters; Cluster Contribution Factor Module 200: Used to determine the power grid scale and calculate the power frequency characteristic coefficient, determine the expected rate of frequency change based on the power grid scale, calculate the system power imbalance based on the power frequency characteristic coefficient, calculate the system inertia constant using the system power imbalance, determine the cluster inertia constant based on the expected rate of frequency change and the expression for the cluster inertia constant, and calculate the cluster contribution factor using the cluster inertia constant and the system inertia constant. Cluster steady-state contribution factor module 300: Used to construct power grid parameter expressions, calculate steady-state frequency deviation and frequency response characteristic parameters through power grid parameter expressions, and obtain the cluster steady-state contribution factor based on steady-state frequency deviation and frequency response characteristic parameters; Frequency regulation module 400: It is used to determine the steady-state factor parameters based on the cluster contribution factor and the cluster steady-state contribution factor, obtain the first power contribution value through the steady-state factor parameters, construct the regional control error expression, obtain the second power contribution value through the regional control error expression, and perform frequency regulation on the virtual power plant network based on the first power contribution value and the second power contribution value. During frequency regulation, the load change curve is acquired, the load change curve is decomposed to obtain the regulation weight, and frequency regulation is performed based on the regulation weight. Primary frequency stabilization module 500: used to obtain the first power contribution value update amount through the expression of the cluster steady-state contribution factor, and to perform primary frequency stabilization on the virtual power plant network through the first power contribution value update amount; Secondary frequency stabilization module 600: used to obtain the second power contribution value change rate through Taylor expansion, and to perform secondary frequency stabilization on the virtual power plant network using the second power contribution value change rate.

[0047] on the other hand, Figure 3 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 3As shown, the electronic device may include: a processor 810, a communication interface 820, a memory 830, and a communication bus 840, wherein the processor 810, the communication interface 820, and the memory 830 communicate with each other through the communication bus 840. The processor 810 can call logical instructions in the memory 830 to execute a virtual power plant grid frequency regulation and stabilization method based on energy storage resource aggregation, the method including: S1: Construct a virtual power plant network including power clusters, collect the mechanical equivalent parameters of the power clusters, and construct an expression for the cluster inertia constant based on the mechanical equivalent parameters; S2: Determine the power grid scale and calculate the power frequency characteristic coefficient. Determine the expected rate of frequency change based on the power grid scale. Calculate the system power imbalance based on the power frequency characteristic coefficient. Calculate the system inertia constant using the system power imbalance. Determine the cluster inertia constant based on the expected rate of frequency change and the expression for the cluster inertia constant. Calculate the cluster contribution factor using the cluster inertia constant and the system inertia constant. S3: Construct the power grid parameter expression, calculate the steady-state frequency deviation and frequency response characteristic parameters through the power grid parameter expression, and obtain the cluster steady-state contribution factor based on the steady-state frequency deviation and frequency response characteristic parameters; S4: Determine the steady-state factor parameters based on the cluster contribution factor and the cluster steady-state contribution factor. Obtain the first power contribution value through the steady-state factor parameters. Construct the regional control error expression. Obtain the second power contribution value through the regional control error expression. Perform frequency regulation on the virtual power plant network based on the first power contribution value and the second power contribution value. During frequency regulation, obtain the load change curve, decompose the load change curve to obtain the regulation weight, and perform frequency regulation based on the regulation weight. S5: Obtain the first power contribution value update amount through the expression of the cluster steady-state contribution factor, and perform primary frequency stabilization on the virtual power plant network through the first power contribution value update amount; S6: Obtain the rate of change of the second power contribution value through Taylor expansion, and use the rate of change of the second power contribution value to perform secondary frequency stabilization on the virtual power plant network.

[0048] Furthermore, the logical instructions in the aforementioned memory 830 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a 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 several 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 described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0049] On the other hand, the present invention also provides a computer program product, the computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, wherein when the program instructions are executed by a computer, the computer is able to execute the virtual power plant grid frequency regulation and stabilization method based on energy storage resource aggregation provided by the above methods, the method comprising: S1: Construct a virtual power plant network including power clusters, collect the mechanical equivalent parameters of the power clusters, and construct an expression for the cluster inertia constant based on the mechanical equivalent parameters; S2: Determine the power grid scale and calculate the power frequency characteristic coefficient. Determine the expected rate of frequency change based on the power grid scale. Calculate the system power imbalance based on the power frequency characteristic coefficient. Calculate the system inertia constant using the system power imbalance. Determine the cluster inertia constant based on the expected rate of frequency change and the expression for the cluster inertia constant. Calculate the cluster contribution factor using the cluster inertia constant and the system inertia constant. S3: Construct the power grid parameter expression, calculate the steady-state frequency deviation and frequency response characteristic parameters through the power grid parameter expression, and obtain the cluster steady-state contribution factor based on the steady-state frequency deviation and frequency response characteristic parameters; S4: Determine the steady-state factor parameters based on the cluster contribution factor and the cluster steady-state contribution factor. Obtain the first power contribution value through the steady-state factor parameters. Construct the regional control error expression. Obtain the second power contribution value through the regional control error expression. Perform frequency regulation on the virtual power plant network based on the first power contribution value and the second power contribution value. During frequency regulation, obtain the load change curve, decompose the load change curve to obtain the regulation weight, and perform frequency regulation based on the regulation weight. S5: Obtain the first power contribution value update amount through the expression of the cluster steady-state contribution factor, and perform primary frequency stabilization on the virtual power plant network through the first power contribution value update amount; S6: Obtain the rate of change of the second power contribution value through Taylor expansion, and use the rate of change of the second power contribution value to perform secondary frequency stabilization on the virtual power plant network.

[0050] In another aspect, the present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for regulating and stabilizing the grid frequency of a virtual power plant based on energy storage resource aggregation provided by the above methods, the method comprising: S1: Construct a virtual power plant network including power clusters, collect the mechanical equivalent parameters of the power clusters, and construct an expression for the cluster inertia constant based on the mechanical equivalent parameters; S2: Determine the power grid scale and calculate the power frequency characteristic coefficient. Determine the expected rate of frequency change based on the power grid scale. Calculate the system power imbalance based on the power frequency characteristic coefficient. Calculate the system inertia constant using the system power imbalance. Determine the cluster inertia constant based on the expected rate of frequency change and the expression for the cluster inertia constant. Calculate the cluster contribution factor using the cluster inertia constant and the system inertia constant. S3: Construct the power grid parameter expression, calculate the steady-state frequency deviation and frequency response characteristic parameters through the power grid parameter expression, and obtain the cluster steady-state contribution factor based on the steady-state frequency deviation and frequency response characteristic parameters; S4: Determine the steady-state factor parameters based on the cluster contribution factor and the cluster steady-state contribution factor. Obtain the first power contribution value through the steady-state factor parameters. Construct the regional control error expression. Obtain the second power contribution value through the regional control error expression. Perform frequency regulation on the virtual power plant network based on the first power contribution value and the second power contribution value. During frequency regulation, obtain the load change curve, decompose the load change curve to obtain the regulation weight, and perform frequency regulation based on the regulation weight. S5: Obtain the first power contribution value update amount through the expression of the cluster steady-state contribution factor, and perform primary frequency stabilization on the virtual power plant network through the first power contribution value update amount; S6: Obtain the rate of change of the second power contribution value through Taylor expansion, and use the rate of change of the second power contribution value to perform secondary frequency stabilization on the virtual power plant network.

[0051] The device embodiments described above are merely illustrative. The units described 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 modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0052] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus necessary general-purpose hardware platforms, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solutions, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0053] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for virtual power plant grid frequency regulation and stabilization based on energy storage resource aggregation, characterized in that, include: S1: Construct a virtual power plant network including power clusters, collect the mechanical equivalent parameters of the power clusters, and construct an expression for the cluster inertia constant based on the mechanical equivalent parameters; S2: Determine the power grid scale and calculate the power frequency characteristic coefficient. Determine the expected rate of frequency change based on the power grid scale. Calculate the system power imbalance based on the power frequency characteristic coefficient. Calculate the system inertia constant using the system power imbalance. Determine the cluster inertia constant based on the expected rate of frequency change and the expression for the cluster inertia constant. Calculate the cluster contribution factor using the cluster inertia constant and the system inertia constant. S3: Construct the power grid parameter expression, calculate the steady-state frequency deviation and frequency response characteristic parameters through the power grid parameter expression, and obtain the cluster steady-state contribution factor based on the steady-state frequency deviation and frequency response characteristic parameters; S4: Determine the steady-state factor parameters based on the cluster contribution factor and the cluster steady-state contribution factor. Obtain the first power contribution value through the steady-state factor parameters. Construct the regional control error expression. Obtain the second power contribution value through the regional control error expression. Perform frequency regulation on the virtual power plant network based on the first power contribution value and the second power contribution value. During frequency regulation, obtain the load change curve, decompose the load change curve to obtain the regulation weight, and perform frequency regulation based on the regulation weight. S5: Obtain the first power contribution value update amount through the expression of the cluster steady-state contribution factor, and perform primary frequency stabilization on the virtual power plant network through the first power contribution value update amount; S6: Obtain the rate of change of the second power contribution value through Taylor expansion, and use the rate of change of the second power contribution value to perform secondary frequency stabilization on the virtual power plant network.

2. The method for virtual power plant grid frequency regulation and stabilization based on energy storage resource aggregation according to claim 1, characterized in that, Step S1 further includes: S11: Construct a virtual power plant network that includes power clusters, wherein the power clusters include new energy power supply equipment; S12: Collect the mechanical equivalent parameters of the power cluster, including the equivalent rotor angle and the equivalent motor running time, and construct the expression for the cluster inertia constant based on the mechanical equivalent parameters.

3. The method for virtual power plant grid frequency regulation and stabilization based on energy storage resource aggregation according to claim 1, characterized in that, Step S2 further includes: S21: Obtain the equivalent grid inertia constant and grid parameter change values, use the grid parameter change values ​​to calculate the power frequency characteristic coefficient, thereby calculating the system power imbalance, and constructing a frequency change rate expression using the system power imbalance and the equivalent grid inertia constant; S22: Determine the power grid scale, and determine the expected rate of frequency change based on the power grid scale; determine the system inertial constant based on the expected rate of frequency change, the expression for the rate of frequency change, and the system power imbalance. S23: Determine the cluster power imbalance, determine the cluster inertia constant constraint condition based on the expected rate of change of frequency and the cluster power imbalance, determine the cluster inertia constant under the constraint condition based on the cluster inertia constant expression, and calculate the cluster contribution factor through the system inertia constant and the cluster inertia constant.

4. The method for virtual power plant grid frequency regulation and stabilization based on energy storage resource aggregation according to claim 1, characterized in that, Step S3 further includes: S31: Construct power grid parameter expressions that include steady-state frequency deviation expressions and frequency response characteristic expressions; S32: Establish an equivalent frequency deviation expression and obtain frequency recovery reserve parameters. Use the equivalent frequency deviation expression and the frequency recovery reserve parameters to calculate the desired steady-state frequency deviation. Obtain the frequency response characteristic parameters through the desired steady-state frequency deviation and the power grid parameter expression. Solve the cluster steady-state contribution factor based on the desired steady-state frequency deviation and the frequency response characteristic parameters.

5. The method for virtual power plant grid frequency regulation and stabilization based on energy storage resource aggregation according to claim 1, characterized in that, Step S4 further includes: S41: Use the maximum value of the cluster contribution factor and the cluster steady-state contribution factor as the steady-state factor parameter, and use the steady-state factor parameter and the frequency recovery reserve parameter to calculate the first power contribution value; S42: Obtain power grid operating parameters, construct the regional control error expression including a first regional control error expression and a second regional control error expression based on the power grid operating parameters, and obtain the second power contribution value through the first regional control error expression and the second regional control error expression; S43: Frequency regulation is performed on the virtual power plant network using the first power contribution value and the second power contribution value. During frequency regulation, a load change curve is acquired, and empirical mode decomposition is performed on the load change curve to obtain multiple decomposed load curves. The frequency and amplitude of the decomposed load curves are analyzed to obtain the regulation weights, and the virtual power plant network is controlled to perform frequency regulation according to the regulation weights.

6. The method for virtual power plant grid frequency regulation and stabilization based on energy storage resource aggregation according to claim 1, characterized in that, In step S5, the expression of the cluster steady-state contribution factor is expanded using Taylor to obtain the steady-state factor parameter expansion. The first power contribution value update is obtained based on the steady-state factor parameter expansion. The first power contribution value update is used to perform primary frequency stabilization on the virtual power plant network.

7. A virtual power plant grid frequency regulation and stabilization system based on energy storage resource aggregation, used to execute the virtual power plant grid frequency regulation and stabilization method based on energy storage resource aggregation as described in any one of claims 1 to 6, characterized in that, include: Cluster inertia constant expression module: used to build a virtual power plant network including power clusters, collect the mechanical equivalent parameters of the power clusters, and construct the cluster inertia constant expression based on the mechanical equivalent parameters; Cluster Contribution Factor Module: Used to determine the grid scale and calculate the power frequency characteristic coefficient, determine the expected rate of frequency change based on the grid scale, calculate the system power imbalance based on the power frequency characteristic coefficient, calculate the system inertia constant using the system power imbalance, determine the cluster inertia constant based on the expected rate of frequency change and the expression for the cluster inertia constant, and calculate the cluster contribution factor using the cluster inertia constant and the system inertia constant. Cluster steady-state contribution factor module: used to construct power grid parameter expressions, calculate steady-state frequency deviation and frequency response characteristic parameters through power grid parameter expressions, and obtain the cluster steady-state contribution factor based on steady-state frequency deviation and frequency response characteristic parameters; Frequency regulation module: It is used to determine the steady-state factor parameters based on the cluster contribution factor and the cluster steady-state contribution factor, obtain the first power contribution value through the steady-state factor parameters, construct the regional control error expression, obtain the second power contribution value through the regional control error expression, and perform frequency regulation on the virtual power plant network based on the first power contribution value and the second power contribution value. During frequency regulation, the load change curve is acquired, the load change curve is decomposed to obtain the regulation weight, and frequency regulation is performed according to the regulation weight. Primary frequency stabilization module: used to obtain the first power contribution value update amount through the expression of the cluster steady-state contribution factor, and to perform primary frequency stabilization on the virtual power plant network through the first power contribution value update amount; Secondary frequency stabilization module: used to obtain the rate of change of the second power contribution value through Taylor expansion, and to perform secondary frequency stabilization on the virtual power plant network using the rate of change of the second power contribution value.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the virtual power plant grid frequency regulation and stabilization method based on energy storage resource aggregation as described in any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the method for regulating and stabilizing the grid frequency of a virtual power plant based on energy storage resource aggregation as described in any one of claims 1 to 6.

10. A computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions, characterized in that, When the program instructions are executed by the computer, the computer is able to perform the steps of the virtual power plant grid frequency regulation and stabilization method based on energy storage resource aggregation as described in any one of claims 1 to 6.

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