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

Abstract

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

Description

Technical Field

[0001] The present application relates to the technical field of virtual power plants, and in particular to a method and device for evaluating the second-level frequency support performance and cost of virtual power plants. Background Art

[0002] At present, the evaluation and description of the minute-level and hour-level output performance and cost of the aggregated distributed resources of virtual power plants has been studied in depth. The existing technologies are mainly divided into two schools: first, a bottom-up strategy is adopted to first determine the feasible domain of each distributed resource, and then integrate and accumulate these feasible domains to obtain the overall output performance and cost description; second, the direct search technology is used to directly explore the extreme points of the aggregated feasible domain, and then obtain the global output performance and cost description.

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

[0004] In the method of solving the global output performance and cost description by direct search, the prior art four uses the direct search method to analyze multiple critical operating points and extreme operating points of the virtual power plant, and then approximates the overall performance feasible interval of the virtual power plant by its convex hull. The proposed method utilizes the geometric characteristics of the performance feasible interval; the prior art five uses projection to identify the effective boundary conditions that act in the time domain coupled feasible domain, and uses the outer approximation algorithm to characterize the extreme points of the dual space of the feasible domain, thereby obtaining the feasible domain of the time-series coupled output performance of the virtual power plant.

[0005] Based on the above analysis, current technologies mainly focus on describing the regulation performance range of virtual power plants at the hourly and minute levels, and are committed to solving the optimal feasible domain of their output descriptions. Moreover, these studies mainly serve the demand response before the day and before the hour. However, these studies generally ignore the in-depth discussion of the second-level output characteristics of virtual power plants, and fail to accurately describe the output curve characteristics of virtual power plants in the emergency frequency support service within 0-10 seconds, making it difficult to accurately evaluate the substantial contribution of virtual power plants to the emergency support of the system in a very short time. In addition, the existing technology also fails to cover the cost analysis of virtual power plants under different second-level response performance, resulting in the inability of the power grid to determine the most economical and effective virtual power plant emergency support frequency backup plan. This defect limits the participation and development of virtual power plants in the field of fast and reliable rapid response services. Summary of the invention

[0006] The present application aims to solve one of the technical problems in the related art at least to some extent.

[0007] To this end, the first purpose of this application is to propose a method for evaluating the second-level frequency support performance and cost of a virtual power plant, which effectively solves the problem faced by the power system and power grid of being unable to accurately evaluate its support performance and support cost when the virtual power plant aggregates distributed resources to participate in the second-level frequency service.

[0008] The second object of the present application is to provide a computer device.

[0009] A third object of the present application is to provide a non-transitory computer-readable storage medium.

[0010] A fourth object of the present application is to provide a computer program product.

[0011] To achieve the above-mentioned objectives, the first aspect of the present application proposes a method for evaluating the performance and cost of second-level frequency support of a virtual power plant, including: 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 responds; using the minimum frequency value to obtain the first-order power curve parameter value that forms a similar frequency minimum 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 can be provided by the virtual power plant; 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; 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 virtual power plant second-level frequency support performance and cost evaluation method of the embodiment of the present application realizes the accurate description of the second-level output characteristics of the virtual power plant, depicts the dynamic characteristics of the output curve of the virtual power plant's aggregate response within 0-10 seconds, and finely characterizes the support effect and role of the virtual power plant within the extreme time scale, so that the power grid can determine the most economical and effective virtual power plant emergency support frequency backup plan, thereby significantly promoting the in-depth participation and sustainable development of virtual power plants in the field of fast and reliable fast 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, they can find out the weak links in the response and improve them, thereby improving the safety, reliability and economy of the operation of virtual power plants. Therefore, this application has important practical significance and broad application prospects.

[0013] Optionally, in one embodiment of the present 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 of the frequency derivative component of distributed resource i is:

[0016]

[0017] Where i = {1, 2, ..., I}, i∈L represents a generalized ramp-type resource, i∈D represents a generalized switch-type resource, time t∈[0, T], U[t] is a unit step function, p i is the reserved capacity of distributed resource i, τ i is the response delay of distributed resource i, T i is the time constant of the first-order process,

[0018]

[0019] in, is the factorized representation of the transfer function of the entire system, which is of order m, q m is the system pole, α m is the corresponding coefficient, q m and α m are all complex numbers, D is the damping, H is the grid inertia, s is the Laplace operator, R -1 is the external primary frequency modulation characteristic, EX(s) is the pull-type transformation function of the external power grid power response characteristic.

[0020] Optionally, in one embodiment of the present application, calculating the minimum frequency value after the virtual power plant responds 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 moment of minimum frequency value and the corresponding minimum frequency value after the virtual power plant responds are solved.

[0023] Optionally, in one embodiment of the present application, the time domain expressions of the frequency component and the frequency derivative component caused by the system disturbance are:

[0024]

[0025] Among them, p φ is the system disturbance power;

[0026] Solve the nonlinear equation to determine the moment of the lowest frequency value. The nonlinear equation is expressed as:

[0027]

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

[0029]

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

[0031] Optionally, in one embodiment of the present application, the time domain expressions of the frequency component and the frequency derivative component caused by the first-order power curve are:

[0032]

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

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

[0035]

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

[0037]

[0038] Among them, σ is the penalty factor.

[0039] Optionally, in one embodiment of the present 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 response amplitude sequence considered. Representative The power is the interval, 0 is the starting point, is the amplitude sequence of the end point, T is the response time constant sequence considered, Representative The time constant is the interval, As a starting point, is the time constant sequence of the end point, is the first-order power curve parameter value that forms the lowest point of similar frequency determined by the optimization problem.

[0040] Optionally, in one embodiment of the present application, let the elements in the feasible performance parameter combination P×T be j=1,...,J, let the jth element of the feasible performance parameter combination P×T be For the jth element The corresponding optimal cost of the virtual power plant is C j , and the corresponding cost optimization problem of the virtual power plant second-level frequency support is expressed as:

[0041]

[0042] The goal of the optimization problem is to minimize the total cost Indicates that the reserved capacity of distributed resource i is The cost at this 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, represents the frequency derivative component when changing the reserved capacity of distributed resource i, ε1 and ε2 are trust region parameters, and y i is a binary 01 variable, representing the discrete switching state of a generalized switch-type resource. is the lowest frequency value caused by the power curve corresponding to the jth element, τ j is the moment when the frequency of the jth element reaches its lowest value.

[0043] To achieve the above-mentioned purpose, the second aspect of the embodiment of the present invention 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, the above-mentioned virtual power plant second-level frequency support performance and cost evaluation method is implemented.

[0044] In order to achieve the above objectives, the third aspect of the present invention proposes a non-temporary computer-readable storage medium. When the instructions in the storage medium are executed by a processor, the above-mentioned virtual power plant second-level frequency support performance and cost evaluation method can be executed.

[0045] In order to achieve the above-mentioned objectives, a fourth aspect of the present invention proposes a computer program product, which, when an instruction processor in the computer program product executes, executes the above-mentioned virtual power plant second-level frequency support performance and cost evaluation method.

[0046] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0048] Figure 1 A flow chart of a method for evaluating the second-level frequency support performance and cost of a virtual power plant provided in Example 1 of the present application. DETAILED DESCRIPTION

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

[0050] The following describes the method and device for evaluating the second-level frequency support performance and cost of a virtual power plant in an embodiment of the present application with reference to the accompanying drawings.

[0051] Figure 1 A flow chart of a method for evaluating the second-level frequency support performance and cost of a virtual power plant provided in Example 1 of the present application.

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

[0053] Step 101, calculating the second-level frequency response of the distributed resources of the virtual power plant and the lowest 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 distributed resource port to the outward input power is defined as the positive direction of the electric power.

[0055] In some embodiments, type information, second-level regulation performance parameter information, and cost information of distributed resources within the region of the virtual power plant are obtained;

[0056] Specifically, the types of distributed resources include generalized switch resources and generalized ramp resources. Generalized switch resources refer to distributed resources similar to switch control, which can switch states or adjust output very quickly after receiving adjustment instructions. Typical generalized switch resources include directly controlled flexible interruptible loads, etc. The time domain response characteristics and pull transfer function of the power response of generalized switch resources are expressed as:

[0057]

[0058] In the formula, p i Reserve capacity for steady state, τ i The response delay. and Represent the time domain and pull domain response characteristics of resource i respectively. e is the natural exponential, and function U[t] is the unit step function. If the distributed resource i is a generalized switch type resource, it is recorded as i∈D.

[0059] Generalized ramping resources refer to distributed resources that need to perform short-term ramping to a new power set point after receiving a control command. Typical generalized ramping resources include most distributed resources controlled by power electronic power supplies, including distributed photovoltaic / wind power, distributed energy storage, electric vehicles, etc. The time domain response characteristics and pull transfer function of the power response of generalized ramping resources are expressed as:

[0060]

[0061] In the formula, p i Reserve capacity for steady state, τ i is the response delay, T i is the time constant of the first-order process, and the other functions and symbols have the same meaning as generalized switch-type resources. If the distributed resource i is a generalized ramp-type resource, it is recorded as i∈L.

[0062] In the step of obtaining the second-level regulation performance parameter information of the 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 parameter information of the generalized ramp-type resource is the maximum steady-state reserved capacity p i , response delay τ i , time constant T i .

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

[0064] Specifically, the frequency response characteristic information includes the grid inertia H and damping D, the external primary frequency modulation characteristics R -1 And the pull-type transformation function EX(s) of the external grid power supply response characteristics, this part as a whole represents the total dynamic response characteristics of the external grid power supply from the virtual power plant to the grid connection port.

[0065] In some embodiments, frequency response characteristic information at a common connection point between the virtual power plant and the power grid is obtained;

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

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

[0068] Step 102, using the lowest frequency value, obtaining a first-order power curve parameter value that forms a similar lowest frequency point, and using the first-order power curve parameter value as a performance parameter evaluation value of the virtual power plant;

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

[0070] Step 104, for each feasible performance parameter combination, solve the cost optimization problem of the second-level frequency support of the corresponding virtual power plant to obtain the optimal cost of the corresponding virtual power plant;

[0071] Step 105: The performance parameter evaluation value and the optimal cost of the virtual power plant under each feasible performance parameter combination are used as the evaluation result of the virtual power plant.

[0072] The virtual power plant second-level frequency support performance and cost evaluation method of the embodiment of the present application realizes the accurate description of the second-level output characteristics of the virtual power plant, depicts the dynamic characteristics of the output curve of the virtual power plant's aggregate response within 0-10 seconds, and finely characterizes the support effect and role of the virtual power plant within the extreme time scale, so that the power grid can determine the most economical and effective virtual power plant emergency support frequency backup plan, thereby significantly promoting the in-depth participation and sustainable development of virtual power plants in the field of fast and reliable fast 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, they can find out the weak links in the response and improve them, thereby improving the safety, reliability and economy of the operation of virtual power plants. Therefore, this application has important practical significance and broad application prospects.

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

[0074]

[0075] in, is the factorized representation of the transfer function of the entire system. The transfer function is of order m, q m is the system pole, α m is the corresponding coefficient, which can be solved by the residue method; q m and α m All are plural.

[0076] Then, according to the pull transfer function of distributed resource i, write the frequency component ω of distributed resource i i Pull-type expression for (s):

[0077]

[0078] In the formula, ω i (s) is the Laplace expression of the frequency component of distributed resource i. Through the inverse Laplace transform, the time domain expression of the frequency component of distributed resource i can be calculated:

[0079]

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

[0081]

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

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

[0084] First, solve the frequency component and frequency derivative component caused by the system disturbance. Let the system disturbance power be p φ , in emergency events, disturbances are usually regarded as step signals, and their Latent domain expressions can be regarded as generalized switching power responses with a response delay of 0. Therefore, the time domain expressions of the frequency components and frequency derivative components caused by system disturbances are:

[0085]

[0086] In the formula, ω φ (t) and They are the time domain expressions of the frequency component and frequency derivative component caused by system disturbance. Further, solve the following nonlinear equation to obtain the moment of minimum frequency value:

[0087]

[0088] The solution of the above nonlinear equation is denoted as t min Finally, the minimum frequency value after the virtual power plant responds is ω min Calculated as:

[0089]

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

[0091]

[0092] In the formula, ω0(t) and are the time domain expressions of the frequency component and frequency derivative component caused by this first-order power curve. and the total frequency derivative Denoted as:

[0093]

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

[0095]

[0096] Where σ is the penalty factor, which is usually between 0.01 and 1. min is the solution of the nonlinear equation. The optimization problem can be solved by the gradient descent method. They are the performance parameter evaluation values ​​of the virtual power plant, which are the equivalent response amplitude and equivalent response time constant of the virtual power plant.

[0097] Optionally, in one embodiment of the present application, the solution to the optimization problem is As the benchmark, the interval is divided into and where P represents the response amplitude sequence under consideration, Representative The power is the interval, 0 is the starting point, is the amplitude sequence of the end point; T represents the response time constant sequence considered, Representative The time constant is the interval, As a starting point, The final feasible performance parameter combination is P×T, where × represents the Cartesian product between the sequences.

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

[0099]

[0100] In the formula, ω j (t) and The jth element The time domain expression of the frequency component and frequency derivative component caused by the corresponding power curve. The total frequency derivative generated by this first-order power response curve is In the form of nonlinear equation, it can be expressed as:

[0101]

[0102] Solve the nonlinear equation and record its solution as t = τ j , and find the jth element as follows The minimum frequency value caused by its corresponding power curve is:

[0103]

[0104] In the formula, is the jth element The frequency minimum value caused by the corresponding power curve. At this time, the jth element The corresponding cost optimization problem of the virtual power plant's second-level frequency support is shown in the following table:

[0105]

[0106]

[0107] In the formula, the goal of the optimization problem is to minimize the total cost Indicates that the reserved capacity of distributed resource i is The decision variable is the reserved capacity of each distributed resource Ω i (t) represents the frequency component when changing the reserved capacity of distributed resource i, represents the frequency derivative component when the reserved capacity of distributed resource i is changed, ε1 and ε2 are trust region parameters, which are generally 10 -4 to 0.01, y i is a binary 01 variable, representing the discrete switching state of the generalized switch resource i∈D. The meanings of the remaining parameters are the same as in the previous steps. The optimal objective function value of the cost optimization problem of the corresponding virtual power plant second-level frequency support is C j , repeat the above steps for each element of the feasible performance parameter combination P×T, and obtain the optimal cost of the virtual power plant under each feasible performance parameter combination, which is C1,...,C j ,...,C J .

[0108] In order to implement the above embodiments, the present invention further 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, the method described in the above embodiments is implemented.

[0109] In order to implement the above embodiments, the present invention further proposes a non-transitory computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the method of the above embodiments is implemented.

[0110] In order to implement the above embodiments, the present invention further provides a computer program product. When an instruction processor in the computer program product executes, the method of the above embodiments is executed.

[0111] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example" or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0112] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of the features. In the description of this application, the meaning of "plurality" is at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0113] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0114] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute the instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purpose of this specification, "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or more wires (electronic device), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways if necessary, and then stored in a computer memory.

[0115] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one of the following technologies known in the art or their combination: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0116] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0117] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0118] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for evaluating the performance and cost of second-level frequency support of 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 responds; Using the lowest frequency value, obtaining a first-order power curve parameter value that forms a similar lowest frequency point, and using the first-order power curve parameter value as a performance parameter evaluation value of the virtual power plant; Dividing the performance parameter evaluation values ​​into intervals to obtain feasible performance parameter combinations that can be provided by the virtual power plant; For each feasible performance parameter combination, solve the cost optimization problem of the corresponding virtual power plant second-level frequency support and obtain the optimal cost of the corresponding virtual power plant; The performance parameter evaluation value and the optimal cost of the virtual power plant under each feasible performance parameter combination are taken as the evaluation result of the virtual power plant.

2. The method according to claim 1, characterized in that The second-level frequency response of distributed resources includes the frequency component and frequency derivative component of distributed resources. The time domain expression of the frequency component of distributed resource i is: The time domain expression of the frequency derivative component of distributed resource i is: Where i = {1, 2, ..., I}, i∈L represents a generalized ramp-type resource, i∈D represents a generalized switch-type resource, time t∈[0, T], U[t] is a unit step function, p i is the reserved capacity of distributed resource i, τ i is the response delay of distributed resource i, T i is the time constant of the first-order process, in, is the factorized representation of the transfer function of the entire system, which is of order m, q m is the system pole, α m is the corresponding coefficient, q m and α m are all complex numbers, D is the damping, H is the grid inertia, s is the Laplace operator, R -1 is the external primary frequency modulation characteristic, EX(s) is the pull-type transformation function of the external power grid power response characteristic.

3. The method according to claim 2, characterized in that Calculate the frequency floor after the virtual power plant response, including: 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 moment of minimum frequency value and the corresponding minimum frequency value after the virtual power plant responds are solved.

4. The method according to claim 3, characterized in that The time domain expressions of the frequency component and frequency derivative component caused by system disturbance are: Among them, p φ is the system disturbance power; Solve the nonlinear equation to determine the moment of the lowest frequency value. The nonlinear equation is expressed as: The minimum frequency value after the virtual power plant responds is: Among them, t min is the moment when the frequency is at its lowest value.

5. The method according to claim 4, characterized in that The time domain expressions of the frequency component and frequency derivative component caused by the first-order power curve are: Among them, p0 and T0 represent the response amplitude and time constant of the first-order power curve respectively; The total frequency and total frequency derivative generated by the first-order power response curve are expressed as: The optimization problem is solved by the gradient descent method to determine the first-order power curve parameter value p0, T0 that forms the lowest point of similar frequency, wherein the optimization problem is expressed as: Among them, σ is the penalty factor.

6. The method according to claim 5, characterized in that The feasible performance parameter combination that a virtual power plant can provide is P×T, where × represents the Cartesian product between sequences and P represents the response amplitude sequence considered. Representative The power is the interval, 0 is the starting point, is the amplitude sequence of the end point, T is the response time constant sequence considered, Representative The time constant is the interval, As a starting point, is the time constant sequence of the end point, is the first-order power curve parameter value that forms the lowest point of similar frequency determined by the optimization problem.

7. The method according to claim 6, characterized in that Let the elements in the feasible performance parameter combination P×T be j=1,...,J, and let the jth element of the feasible performance parameter combination P×T be For the jth element The corresponding optimal cost of the virtual power plant is C j , and the corresponding cost optimization problem of the virtual power plant second-level frequency support is expressed as: The goal of the optimization problem is to minimize the total cost Indicates that the reserved capacity of distributed resource i is The cost at this 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, represents the frequency derivative component when changing the reserved capacity of distributed resource i, ε1 and ε2 are trust region parameters, and y i is a binary 01 variable, representing the discrete switching state of a generalized switch-type resource. is the lowest frequency value caused by the power curve corresponding to the jth element, τ j is the moment when the frequency of the jth element reaches its lowest value.

8. A computer device, characterized in that: The method comprises 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, the method according to any one of claims 1 to 7 is implemented.

9. 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, the method according to any one of claims 1 to 7 is implemented.

10. A computer program product, when instructions in the computer program product are executed by a processor, performs the method according to any one of claims 1 to 7.

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