Virtual power plant second-level frequency support performance and cost evaluation method

Abstract

The application provides a virtual power plant second-level frequency support performance and cost evaluation method, which comprises the following steps: calculating the second-level frequency response of distributed resources of the virtual power plant and the lowest frequency value after the response of the virtual power plant; using the lowest frequency value to obtain the first-order power curve parameter value forming a similar lowest frequency point, and taking the first-order power curve parameter value as the performance parameter evaluation value of the virtual power plant; performing interval division on the performance parameter evaluation value to obtain feasible performance parameter combinations that can be provided by the virtual power plant; for each feasible performance parameter combination, solving the cost optimization problem of the corresponding second-level frequency support of the virtual power plant to obtain the optimal cost of the virtual power plant; and taking the performance parameter evaluation value and the optimal cost of the virtual power plant under each feasible performance parameter combination as the evaluation result of the virtual power plant. The application adopting the above scheme can accurately evaluate the support performance and support cost of the virtual power plant when the virtual power plant aggregates the distributed resources to participate in the second-level frequency support service.

Description

Technical Field

[0001] This application relates to the field of virtual power plant technology, and in particular to a method and apparatus for evaluating the performance and cost of virtual power plant at the second-level frequency support level. Background Technology

[0002] Currently, there has been considerable in-depth research on the evaluation and description of output performance and cost at the minute and hourly levels for virtual power plants aggregating distributed resources. Existing technologies mainly fall into two categories: First, a bottom-up strategy is adopted, which first determines the feasible region of operation for each distributed resource, and then integrates and accumulates these feasible regions to obtain an overall description of output performance and cost; Second, a direct search technique is used to directly explore the extreme points of the aggregated feasible regions, thereby obtaining a global description of output performance and cost.

[0003] In bottom-up technical solutions for evaluating the hourly and minute-level output performance and cost of virtual power plants, existing technology one classifies virtual power plants into semi-controlled and controllable resources based on their different internal resource characteristics, and proposes a spatial aggregation method for adjustable performance of virtual power plants; existing technology two considers network topology constraints and three-phase network imbalance when describing aggregated performance, and the effective performance feasible range obtained by this method can guarantee that there is at least one feasible instruction decomposition scheme at any point; existing technology three gradually sorts and classifies distributed resources based on price and energy as indicators, and obtains multi-level aggregated performance and cost results.

[0004] In methods for solving global output performance and cost descriptions through direct search, Existing technology four uses a direct search method to analyze multiple critical and extreme operating points of a virtual power plant, and then approximates the overall performance feasible range of the virtual power plant using its convex hull. The proposed method utilizes the geometric characteristics of the performance feasible range. Existing technology five identifies effective boundary conditions that play a role in the temporal coupled feasible region through projection, and uses an external approximation algorithm to characterize the extreme points of the dual space of the feasible region, thereby obtaining the temporal coupled output performance feasible region of the virtual power plant.

[0005] In summary, current technologies primarily focus on describing the regulation performance range of virtual power plants (VPS) at the hourly and minute levels, aiming to solve the optimal feasible region of their output description. These studies mainly serve day-ahead and hour-ahead demand response. However, these studies generally neglect in-depth exploration of the second-level output characteristics of VPS, failing to accurately depict the output curve characteristics of VPS aggregated response within 0-10 seconds during emergency frequency support services. This makes it difficult to accurately assess the substantial contribution of VPS to system emergency support in extremely short periods. Furthermore, existing technologies also fail to cover cost analysis of VPS under different second-level response performances, preventing the power grid from determining the most economical and effective VPS emergency support frequency backup scheme. This deficiency limits the participation and development of VPS in the field of rapid and reliable fast response services. Summary of the Invention

[0006] This application aims to at least partially address one of the technical problems in the related art.

[0007] Therefore, the first objective of this application is to propose a method for evaluating the performance and cost of virtual power plants at the second level of frequency support, which effectively solves the problem faced by power systems and grids in accurately evaluating the support performance and support cost when virtual power plants aggregate distributed resources to participate in second-level frequency services.

[0008] The second objective of this application is to propose a computer device.

[0009] The third objective of this application is to provide a non-transitory computer-readable storage medium.

[0010] The fourth objective of this application is to provide a computer program product.

[0011] To achieve the above objectives, the first aspect of this application proposes a method for evaluating the performance and cost of a virtual power plant's second-level frequency support, comprising: calculating the second-level frequency response of the distributed resources of the virtual power plant and the minimum frequency value after the virtual power plant's response; using the minimum frequency value, obtaining the first-order power curve parameter value that forms a similar minimum frequency point, and using the first-order power curve parameter value as the performance parameter evaluation value of the virtual power plant; dividing the performance parameter evaluation value into intervals to obtain feasible performance parameter combinations that the virtual power plant can provide; for each feasible performance parameter combination, solving the corresponding cost optimization problem of the virtual power plant's second-level frequency support to obtain the corresponding optimal cost of the virtual power plant; and using the performance parameter evaluation value and the optimal cost of the virtual power plant under each feasible performance parameter combination as the evaluation result of the virtual power plant.

[0012] The method for evaluating the second-level frequency support performance and cost of virtual power plants in this application provides a precise description of the second-level output characteristics of virtual power plants. It characterizes the dynamic features of the output curve of the aggregated response of a virtual power plant within 0-10 seconds, and finely represents the support effect and role of the virtual power plant in extreme time scales. This allows the power grid to determine the most economical and effective emergency frequency backup plan for virtual power plants, thereby significantly promoting the in-depth participation and continuous development of virtual power plants in the field of fast and reliable rapid response services. This application can also serve as a basis for virtual power plants to improve their own response capabilities. By evaluating their own response capabilities, weak links in the response can be identified and improved, thereby enhancing the safety, reliability, and economy of virtual power plant operation. Therefore, this application has significant practical implications and broad application prospects.

[0013] Optionally, in one embodiment of this application, the second-level frequency response of the distributed resource includes the frequency component and the frequency derivative component of the distributed resource, and the time-domain expression of the frequency component of the distributed resource i is:

[0014]

[0015] The time-domain expression for the frequency derivative component of distributed resource i is:

[0016]

[0017] Where i = {1, 2, ..., I}, i ∈ L indicates that i is a generalized climbing resource, i ∈ D indicates a generalized switching resource, time t ∈ [0, T], U[t] is a unit step function, p i τ is the reserved capacity for distributed resource i. i Let T be the response latency of distributed resource i. i The time constant of the first-order process,

[0018]

[0019] in, This is the factorization representation of the transfer function of the entire system, which is of order m and q. m For the system poles, α m For the corresponding coefficient, q m and α m All are complex numbers, D is damping, H is grid inertia, s is the Laplace operator, and R is... -1 Let EX(s) be the external primary frequency regulation characteristic, and let EX(s) be the Laplace transform function of the external grid power supply response characteristic.

[0020] Optionally, in one embodiment of this application, calculating the minimum frequency value after the virtual power plant response includes:

[0021] Calculate the frequency components and frequency derivative components caused by system disturbances;

[0022] Based on the second-level frequency response of distributed resources and the frequency components and frequency derivative components caused by system disturbances, the time of the minimum frequency after the virtual power plant response and the corresponding minimum frequency value are solved.

[0023] Optionally, in one embodiment of this application, the time-domain expressions for the frequency components and frequency derivative components caused by system disturbances are as follows:

[0024]

[0025] Where, p φ This refers to the system disturbance power;

[0026] Solve the nonlinear equation to determine the time of minimum frequency. The nonlinear equation is expressed as:

[0027]

[0028] The minimum frequency after the virtual power plant response is:

[0029]

[0030] Among them, t min This is the moment when the frequency is at its lowest.

[0031] Optionally, in one embodiment of this application, the time-domain expressions for the frequency components and frequency derivative components caused by the first-order power curve are as follows:

[0032]

[0033] Where p0 and T0 represent the response amplitude and time constant of the first-order power curve, respectively;

[0034] The total frequency and the total frequency derivative generated by the first-order power response curve are expressed as follows:

[0035]

[0036] The optimization problem is solved using gradient descent to determine the parameter values ​​p0, T0 of the first-order power curve that forms the lowest similar frequency point. The optimization problem is expressed as:

[0037]

[0038] Where σ is the penalty factor.

[0039] Optionally, in one embodiment of this application, the feasible performance parameter combination that the virtual power plant can provide is P×T, where × represents the Cartesian product between sequences, and P represents the considered response amplitude sequence. Representative with The power is the interval, with 0 as the starting point. The magnitude sequence at the stop point, where T represents the sequence of response time constants under consideration. Representative with The time constant is the interval. Starting from, The time constant sequence at the stop point These are the parameter values ​​for the first-order power curves that form the lowest similar frequency points, determined through the optimization problem.

[0040] Optionally, in one embodiment of this application, the elements in the feasibility parameter combination P×T are denoted as j = 1,...,J, and the j-th element of the feasibility parameter combination P×T is... For the j-th element The optimal cost of the corresponding virtual power plant is C. j The corresponding cost optimization problem for virtual power plants supporting second-level frequencies is expressed as:

[0041]

[0042] The objective of the optimization problem is to minimize the total cost. This indicates that the reserved capacity of distributed resource i is... The cost at that time, the decision variable is the reserved capacity of distributed resource i. Ω i (t) represents the frequency component when the reserved capacity of distributed resource i is changed. This represents the frequency derivative component when the reserved capacity of distributed resource i is changed, where ε1 and ε2 are trust region parameters, and y i This is a binary 0-1 variable, representing the discrete switching state of a generalized switching resource. τ is the lowest frequency caused by the power curve corresponding to the j-th element. j The moment when the frequency of the j-th element is at its lowest value.

[0043] To achieve the above objectives, a second aspect of the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the above-mentioned method for evaluating the second-level frequency support performance and cost of a virtual power plant.

[0044] To achieve the above objectives, a third aspect of the present invention provides a non-transitory computer-readable storage medium that, when the instructions in the storage medium are executed by a processor, can perform the above-described virtual power plant second-level frequency support performance and cost assessment method.

[0045] To achieve the above objectives, a fourth aspect of the present invention provides a computer program product that, when executed by an instruction processor, performs the aforementioned virtual power plant second-level frequency support performance and cost evaluation method.

[0046] Additional aspects and advantages of this application 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 this application. Attached Figure Description

[0047] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0048] Figure 1 This is a flowchart illustrating a method for evaluating the performance and cost of a virtual power plant at the second-level frequency support level, as provided in Embodiment 1 of this application. Detailed Implementation

[0049] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0050] The following describes, with reference to the accompanying drawings, a method and apparatus for evaluating the performance and cost of virtual power plant second-level frequency support according to embodiments of this application.

[0051] Figure 1 This is a flowchart illustrating a method for evaluating the performance and cost of a virtual power plant at the second-level frequency support level, as provided in Embodiment 1 of this application.

[0052] like Figure 1 As shown, the method for evaluating the performance and cost of second-level frequency support in this virtual power plant includes the following steps:

[0053] Step 101: Calculate the second-level frequency response of the distributed resources of the virtual power plant and the minimum frequency value after the virtual power plant responds;

[0054] In some embodiments, the set of distributed resources of the virtual power plant is defined as i = {1,2,...,I}, time is defined as t∈[0,T], the Laplace operator is defined as s, and the power flow direction of the power input to the distributed resource port is defined as the positive direction of the power.

[0055] In some embodiments, information on the type of distributed resources, second-level regulation performance parameters, and cost information within the virtual power plant area is obtained.

[0056] Specifically, distributed resource types include generalized switching resources and generalized ramping resources. Generalized switching resources refer to distributed resources that function similarly to switch control, capable of rapidly switching states or adjusting output upon receiving adjustment commands. Typical generalized switching resources include directly controlled flexible interruptible loads. The time-domain response characteristics and Lagrange transfer function of the power response of generalized switching resources are expressed as follows:

[0057]

[0058] In the formula, p i To reserve capacity for steady state, τ i For response delay. and Let represent the time-domain and Laplace-domain response characteristics of resource i, respectively. e is the natural exponent, and U[t] is the unit step function. If the distributed resource i is a generalized switching resource, then it is denoted as i∈D.

[0059] Generalized ramp-up resources refer to distributed resources that require a short-term ramp-up to reach a new power setpoint after receiving a control command. Typical generalized ramp-up resources include most distributed resources controlled by power electronic power sources, such as distributed photovoltaic / wind power, distributed energy storage, and electric vehicles. The time-domain response characteristics and Laplace transfer function of the power response of generalized ramp-up resources are expressed as follows:

[0060]

[0061] In the formula, p i To reserve capacity for steady state, τ i In response to latency, T i Let be the time constant of the first-order process; the meanings of the remaining functions and symbols are the same as those for generalized switch-type resources. If distributed resource i is a generalized ramp-type resource, then it is denoted as i∈L.

[0062] In the step of obtaining the second-level regulation performance parameter information of distributed resources within the virtual power plant area, the second-level regulation performance parameter information of the generalized switch-type resources is the maximum steady-state reserved capacity p. i Response delay τ i The second-level adjustment performance parameters of generalized climbing-type resources are the maximum steady-state reserved capacity p. i Response delay τ i Time constant T i .

[0063] In the step of obtaining cost information of distributed resources within the virtual power plant area, the cost information includes the cost function C of distributed resource i. i (p i ), which represents the reserved capacity of distributed resource i as p. i The cost.

[0064] Specifically, the frequency response characteristic information includes the grid inertia H and damping D, and the external primary frequency regulation characteristic R. -1 The Laplace transform function EX(s) of the response characteristics of the external grid power source represents the overall dynamic response characteristics of the external grid power source from the virtual power plant to the grid connection port.

[0065] In some embodiments, frequency response characteristics at the point of common connection between the virtual power plant and the power grid are obtained;

[0066] In some embodiments, a second-level frequency response calculation module is established to establish a mapping from the response power curve to the frequency response;

[0067] In some embodiments, the minimum frequency value after the virtual power plant responds is calculated using the established second-level frequency response calculation module.

[0068] Step 102: Using the lowest frequency value, obtain the first-order power curve parameter value that forms the similar lowest frequency point, and use the first-order power curve parameter value as the performance parameter evaluation value of the virtual power plant.

[0069] Step 103: Divide the performance parameter evaluation values ​​into intervals to obtain the feasible performance parameter combinations that the virtual power plant can provide;

[0070] Step 104: For each combination of feasible performance parameters, solve the cost optimization problem of the virtual power plant's second-level frequency support to obtain the corresponding optimal cost of the virtual power plant.

[0071] Step 105: The performance parameter evaluation values ​​and the optimal cost of the virtual power plant under each combination of feasible performance parameters are taken as the evaluation results of the virtual power plant.

[0072] The method for evaluating the second-level frequency support performance and cost of virtual power plants in this application provides a precise description of the second-level output characteristics of virtual power plants. It characterizes the dynamic features of the output curve of the aggregated response of a virtual power plant within 0-10 seconds, and finely represents the support effect and role of the virtual power plant in extreme time scales. This allows the power grid to determine the most economical and effective emergency frequency backup plan for virtual power plants, thereby significantly promoting the in-depth participation and continuous development of virtual power plants in the field of fast and reliable rapid response services. This application can also serve as a basis for virtual power plants to improve their own response capabilities. By evaluating their own response capabilities, weak links in the response can be identified and improved, thereby enhancing the safety, reliability, and economy of virtual power plant operation. Therefore, this application has significant practical implications and broad application prospects.

[0073] Optionally, in one embodiment of this application, the total system transfer function from power change to system frequency is first calculated and factored, as follows:

[0074]

[0075] in, This is the factorization representation of the transfer function of the entire system. The transfer function is of order m, q m For the system poles, α m The corresponding coefficients can be solved using the residue method; q m and α m All are plural numbers.

[0076] Based on the Laplace transfer function of distributed resource i, write out the frequency component ω of distributed resource i. i The Laplace expression of (s):

[0077]

[0078] In the formula, ω i (s) represents the Laplace expression for the frequency components of distributed resource i. The time-domain expression for the frequency components of distributed resource i can be calculated using the inverse Laplace transform:

[0079]

[0080] In the formula, ω i (t) is the time-domain expression for the frequency component of distributed resource i. Similarly, the expression for the frequency derivative component of distributed resource i is given as follows:

[0081]

[0082] In the formula, The time-domain expression for the frequency derivative component of distributed resource i is given by ω. i (t) and That is, the second-level frequency response of distributed resource i.

[0083] Optionally, in one embodiment of this application, calculating the minimum frequency value after the virtual power plant response includes:

[0084] First, we solve for the frequency components and frequency derivative components caused by the system disturbance. Let the magnitude of the system disturbance power be p. φ In emergency situations, disturbances are typically treated as step signals, and their Laplace domain expression can be considered as a generalized switching power response with zero time delay. Therefore, the time-domain expressions for the frequency components and frequency derivative components caused by the system disturbance are:

[0085]

[0086] In the formula, ω φ (t) and These are the time-domain expressions for the frequency components and frequency derivative components caused by the system disturbance, respectively. Further, the following nonlinear equation is solved to find the time of the minimum frequency:

[0087]

[0088] Let the solution to the above nonlinear equation be denoted as t. min Ultimately, the lowest frequency value ω after the virtual power plant's response. min The calculation is as follows:

[0089]

[0090] Optionally, in one embodiment of this application, the parameters of the first-order power curve are first denoted as p0 and T0, representing the response amplitude and time constant of the first-order power curve, respectively, which are unknown variables to be determined. Then, the frequency component ω0(t) and the frequency derivative component caused by this first-order power curve are... The expression is:

[0091]

[0092] In the formula, ω0(t) and These are the time-domain expressions for the frequency components and frequency derivative components caused by this first-order power curve, respectively. The total frequency response curve generated by this first-order power response curve... and the derivative of total frequency Recorded as:

[0093]

[0094] At this point, the parameter values ​​p0 and T0 of the first-order power curve that form the lowest similar frequency point are determined by the following optimization problem:

[0095]

[0096] In the formula, σ is the penalty factor, which is generally taken as 0.01 to 1, and t min This is a solution to a nonlinear equation. Optimization problems can be solved using the gradient descent method. These are the performance parameter evaluation values ​​of the virtual power plant, namely the equivalent response amplitude and the equivalent response time constant of the virtual power plant.

[0097] Optionally, in one embodiment of this application, a solution to the problem is optimized. Based on the baseline, the interval is divided into: and Where P represents the sequence of response amplitudes considered. Representative with The power is the interval, with 0 as the starting point. The magnitude sequence at the stop point; T represents the sequence of response time constants under consideration. Representative with The time constant is the interval. Starting from, The time constant sequence is the stop point. The final feasible performance parameter combination is P×T, where × represents the Cartesian product between sequences.

[0098] Optionally, in one embodiment of this application, the elements in the feasibility parameter combination P×T are j = 1,...,J, where J is the total number of feasibility parameter combination elements. Let the j-th element of the feasibility parameter combination P×T be... For the j-th element is The frequency component ω caused by its corresponding power curve j (t) and frequency derivative components The expression is:

[0099]

[0100] In the formula, ω j (t) and The j-th element The time-domain expressions for the frequency components and frequency derivative components caused by the corresponding power curve. The total frequency derivative generated by this first-order power response curve. It is in the form of a nonlinear equation, denoted as:

[0101]

[0102] Solve the nonlinear equation, and denote the solution as t = τ. j And find the j-th element as follows. The lowest frequency caused by its corresponding power curve is:

[0103]

[0104] In the formula, For the j-th element The minimum frequency caused by its corresponding power curve. At this time, the j-th element The cost optimization problem for the corresponding virtual power plant's second-level frequency support is shown in the table below:

[0105]

[0106]

[0107] In the formula, the objective of the optimization problem is to minimize the total cost. This indicates that the reserved capacity of distributed resource i is... The cost at that time. The decision variable is the reserved capacity for each distributed resource. Ω i (t) represents the frequency component when the reserved capacity of distributed resource i is changed. The frequency derivative components represent the changes in the reserved capacity of distributed resource i, and ε1 and ε2 are trust region parameters, typically taken as 10. -4 up to 0.01, y i This is a binary 0-1 variable, representing the discrete switching state of the generalized switch-type resource i∈D. The meanings of the remaining parameters are the same as in the previous steps. Let the j-th element be... The optimal objective function value for the cost optimization problem supported by the second-level frequency of the corresponding virtual power plant is C. j For each element of the feasibility parameter combination P×T, repeat the above steps to obtain the optimal cost of the virtual power plant under each feasibility parameter combination, denoted as C1,...,C j ,...,C J .

[0108] To implement the above embodiments, the present invention also proposes a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, it implements the methods described in the above embodiments.

[0109] To implement the above embodiments, the present invention also proposes a non-transitory computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the method of the above embodiments.

[0110] To implement the above embodiments, the present invention also proposes a computer program product that, when the instruction processor in the computer program product is executed, performs the method of the above embodiments.

[0111] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. 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.

[0112] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0113] Any process or method description in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or more executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0114] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically, for example, by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0115] It should be understood that various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0116] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0117] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0118] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A method for evaluating the performance and cost of second-level frequency support in a virtual power plant, characterized in that, include: Calculate the second-level frequency response of the distributed resources of the virtual power plant and the minimum frequency value after the virtual power plant response. The second-level frequency response of the distributed resources includes the frequency components and frequency derivative components of the distributed resources. Using the lowest frequency value, the first-order power curve parameter value that forms a similar lowest frequency point is obtained, and the first-order power curve parameter value is used as the performance parameter evaluation value of the virtual power plant. The performance parameter evaluation values ​​are divided into intervals to obtain feasible performance parameter combinations that the virtual power plant can provide; For each combination of feasible performance parameters, solve the cost optimization problem of the virtual power plant's second-level frequency support to obtain the corresponding optimal cost of the virtual power plant. The evaluation results of the virtual power plant are the performance parameter evaluation values ​​and the optimal cost of the virtual power plant under each combination of feasible performance parameters. The calculation of the minimum frequency after the virtual power plant response includes: Calculate the frequency components and frequency derivative components caused by system disturbances; Based on the second-level frequency response of distributed resources and the frequency components and frequency derivative components caused by system disturbances, the time of the minimum frequency after the virtual power plant response and the corresponding minimum frequency value are solved. The time-domain expressions for the frequency components and frequency derivative components caused by the first-order power curve are as follows: Among them, time is defined. The transfer function of the entire system is of order m. For the system poles, For the corresponding coefficients, and All are plural numbers. For unit step function, , These represent the response amplitude and time constant of the first-order power curve, respectively. The total frequency and the total frequency derivative generated by the first-order power response curve are expressed as follows: The optimization problem is solved using the gradient descent method to determine the parameter values ​​of the first-order power curve that forms the lowest point of similar frequency. The optimization problem is expressed as: in, The moment with the lowest frequency. This represents the lowest frequency value after the virtual power plant responds. As a penalty factor; The combination of feasible performance parameters that a virtual power plant can provide are: , Represents the Cartesian product between sequences. This represents the sequence of response amplitudes under consideration. , Representative with The power is the interval. Starting from, The magnitude sequence at the stop point This represents the sequence of response time constants under consideration. , Representative with The time constant is the interval. Starting from, The time constant sequence at the stop point , These are the parameter values ​​for the first-order power curves that form the lowest similar frequency points, determined through the optimization problem.

2. The method as described in claim 1, characterized in that, Distributed resources The time-domain expression for the frequency component is: Distributed resources The time-domain expression for the frequency derivative component is: Among them, the set of distributed resources that define the virtual power plant. , express For a broad sense, climbing-type resources This represents a generalized switching resource. For distributed resources Reserved capacity, For distributed resources Response latency, The time constant of the first-order process, in, The factorization representation of the transfer function of the entire system. For damping, Due to the inertia of the power grid, For the Laplace operator, For external primary frequency modulation characteristics, This is the Laplace transform function of the external power grid response characteristics.

3. The method as described in claim 1, characterized in that, The time-domain expressions for the frequency components and frequency derivative components caused by system disturbances are as follows: in, This refers to the system disturbance power; Solve the nonlinear equation to determine the time of minimum frequency. The nonlinear equation is expressed as: The minimum frequency after the virtual power plant response is: 。 4. The method as described in any one of claims 2-3, characterized in that, Combining feasible performance parameters The elements in are Combining feasible performance parameters The The elements are For the first element The optimal cost of the corresponding virtual power plant is The corresponding cost optimization problem for virtual power plants supporting second-level frequencies is expressed as: The objective of the optimization problem is to minimize the total cost. , Represents distributed resources Reserved capacity is The cost at that time, the decision variable is distributed resources The reserved capacity is , Indicates changing distributed resources Frequency components when reserving capacity Indicates changing distributed resources Frequency derivative components when reserving capacity, , For trust region parameters, This is a binary 0-1 variable, representing the discrete switching state of a generalized switching resource. For the first The lowest frequency value caused by the power curve corresponding to each element. For the first The moment when the frequency of each element is at its lowest value.

5. A computer device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, it implements the method as described in any one of claims 1-4.

6. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1-4.

7. A computer program product, wherein, when instructions in the computer program product are executed by a processor, the method described in any one of claims 1-4 is performed.

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