A method and system for constructing a distributed photovoltaic equivalent model

Abstract

The present invention discloses a method and system for constructing a distributed photovoltaic equivalent model, which belongs to the technical field of distributed photovoltaic equivalent model simulation. The method of the present invention includes: obtaining parameters of distributed photovoltaics in the distribution network; calculating electrical parameters of the equivalent model of the original distributed photovoltaics based on the parameters of the distributed photovoltaics; calculating conventional control parameters of the equivalent model of the original distributed photovoltaics based on the electrical parameters; in the control strategy of the equivalent model of the original distributed photovoltaics, according to the conventional control parameters, introducing a capacity weighting method and a piecewise slope recovery method to calculate the equivalent parameters of the control during the low-voltage ride-through of the distributed photovoltaics; and constructing an equivalent model of the distributed photovoltaics based on the equivalent parameters of the control during the low-voltage ride-through of the distributed photovoltaics. The present invention realizes high-precision dynamic equivalent modeling of distributed photovoltaics.

Description

Technical Field

[0001] The present invention relates to the technical field of distributed photovoltaic equivalent model simulation, and more particularly, to a method and system for constructing a distributed photovoltaic equivalent model. Background Art

[0002] As the global energy system transitions toward a clean, low-carbon, safe, and efficient future, my country's energy and power development faces a critical strategic opportunity, and the energy supply and demand landscape continues to evolve rapidly. By the end of 2023, installed renewable energy power generation capacity will reach 1.1 billion kilowatts, accounting for 37% of total installed power generation capacity. Renewable energy power generation is gradually shifting from supplementing incremental energy and electricity consumption to becoming the primary driver of incremental energy and electricity consumption. Compared to traditional power generation methods such as generators, renewable energy power generation utilizes a large number of new power electronics devices, which differ significantly in physical structure, control methods, dynamic response, and interaction with other devices. This widespread integration will significantly alter the operational characteristics of the power system.

[0003] The scale of distributed photovoltaic (DPV) installations within the installed capacity of renewable energy is growing rapidly. By the end of 2023, the cumulative installed capacity of distributed photovoltaics will exceed 250 million kilowatts, accounting for approximately 42% of the total installed capacity of photovoltaic power generation. Distributed photovoltaics are increasingly being required to design new control strategies to improve transient performance, especially low voltage ride through (LVRT) capability. The active distribution network that carries distributed photovoltaics has an increasingly profound impact on the dynamics of the entire power system. The design and operation of the power system heavily rely on the accuracy of the system simulation model. Developing a dynamic simulation model that effectively characterizes the transient characteristics of the power system is of great significance.

[0004] Studying the patterns, dynamic characteristics, and impact of large-scale distributed photovoltaic integration on grid security and stability requires a high-precision distributed photovoltaic model. Establishing a detailed distributed photovoltaic model is the most direct approach. However, large power grids typically include hundreds or thousands of distributed photovoltaic models. Simulating these models significantly increases the scale and time of grid dynamic simulations, making detailed modeling of each distributed photovoltaic impractical. Establishing a distributed photovoltaic equivalent model that balances computational accuracy and efficiency while ensuring the greatest possible consistency in external characteristics is a key issue that needs to be addressed in transient simulations of high-penetration distributed photovoltaic integration into power systems.

[0005] Existing distributed photovoltaic equivalent models typically assume uniform transient characteristics. However, a thorough investigation of manufacturer data reveals significant diversity and differences in device type and converter transient characteristics, particularly between manufacturers. These differences are crucial for accurately modeling distributed photovoltaic behavior in the grid, but due to manufacturer confidentiality agreements, obtaining these key parameters is extremely difficult. Summary of the Invention

[0006] In response to the above problems, the present invention proposes a method for constructing a distributed photovoltaic equivalent model, comprising:

[0007] Obtain parameters of distributed photovoltaics in the distribution network;

[0008] Based on the distributed photovoltaic parameters, calculating the electrical parameters of the equivalent model of the original distributed photovoltaic;

[0009] Based on the electrical parameters, calculating conventional control parameters of the equivalent model of the original distributed photovoltaic system;

[0010] In the control strategy of the equivalent model of the original distributed photovoltaic, based on the conventional control parameters, a capacity weighting method and a piecewise slope recovery method are introduced to calculate the equivalent parameters of the distributed photovoltaic control during the low voltage ride-through period;

[0011] Based on the equivalent parameters controlled during the distributed photovoltaic low voltage ride-through period, an equivalent model of distributed photovoltaic is constructed.

[0012] Optionally, calculate the electrical parameters of the equivalent model of the original distributed photovoltaic system, specifically:

[0013] The circuit parameter aggregation for distributed photovoltaics is as follows:

[0014]

[0015] Among them, C deq 、C feq , L feq are the DC capacitance, AC capacitance and AC reactance of distributed photovoltaics after equalization, S Deq is the capacity of distributed photovoltaic after equalization, C d,i 、C f,i For L f,i are the ith DC capacitance, AC capacitance and AC reactance before the distributed photovoltaic equalization, S D,i is the capacity of the i-th distributed photovoltaic.

[0016] Optionally, conventional control parameters of the equivalent model of the original distributed photovoltaic system are calculated, specifically:

[0017] The conventional control parameters of distributed photovoltaics are aggregated, and the formula is as follows:

[0018]

[0019] Among them, N D,i It represents the ratio of the capacity of the i-th distributed photovoltaic unit to the capacity of the distributed photovoltaic equivalent unit, K is the conventional control / ride-through control parameter, K eq is the control parameter after distributed photovoltaic equalization, K i is the control parameter of the i-th distributed photovoltaic.

[0020] Optionally, the capacity weighting method and the segmented slope recovery method are introduced to calculate the equivalent parameters for distributed photovoltaic control during low voltage ride-through, specifically:

[0021] Introducing the capacity weighting method and the piecewise slope recovery method, constructing the control strategy mathematical model and the piecewise rate recovery control strategy model;

[0022] Based on the control strategy mathematical model and the segmented rate recovery control strategy model, the equivalent parameters of the distributed photovoltaic low voltage ride-through control period are calculated;

[0023] The mathematical model of the control strategy is as follows:

[0024] I d_R =g1I d_R_C1 +g2I d_R_C2 (6)

[0025] Among them, I d_R is the mathematical model of the control strategy, g1 and g2 are the weight coefficients of the recovery control strategy, I d_R_C1 and I d_R_C2 The current reference command of the recovery control strategy corresponding to g1 and g2;

[0026] The segmented rate recovery control strategy model is as follows:

[0027]

[0028] Among them, I d_R (t) is the segmented rate recovery control strategy model, n is the number of distributed photovoltaics in the active distribution network, h i 、k i are the weight coefficients and recovery rates of different distributed photovoltaics, I n_i is the current reference instruction of different distributed photovoltaics under normal operation, t r is the initial recovery time, t j+1 is the recovery time of the jth distributed photovoltaic unit, t nis the recovery start time of the nth distributed photovoltaic unit, t is the operating time, and j is the number of the distributed photovoltaic unit.

[0029] Optional, distributed photovoltaic equivalent model, the formula is as follows:

[0030]

[0031] Among them, g i Equivalent model of distributed photovoltaics, S Di,j is the capacity of the jth unit in the i-th distributed photovoltaic system.

[0032] In another aspect, the present invention further provides a system for constructing a distributed photovoltaic equivalent model, comprising:

[0033] Parameter acquisition unit, used to obtain parameters of distributed photovoltaic in the distribution network;

[0034] A first calculation unit is configured to calculate electrical parameters of an equivalent model of an original distributed photovoltaic system based on the parameters of the distributed photovoltaic system;

[0035] A second calculation unit is configured to calculate conventional control parameters of the equivalent model of the original distributed photovoltaic system based on the electrical parameters;

[0036] a third calculation unit, configured to introduce a capacity weighting method and a piecewise slope recovery method into the control strategy of the equivalent model of the original distributed photovoltaic system according to the conventional control parameters, so as to calculate equivalent parameters for control of the distributed photovoltaic system during the low voltage ride-through period;

[0037] The model building unit is used to build an equivalent model of distributed photovoltaics based on equivalent parameters controlled during the distributed photovoltaic low voltage ride-through period.

[0038] Optionally, calculate the electrical parameters of the equivalent model of the original distributed photovoltaic system, specifically:

[0039] The circuit parameter aggregation for distributed photovoltaics is as follows:

[0040]

[0041] Among them, C deq 、C feq , L feq are the DC capacitance, AC capacitance and AC reactance of distributed photovoltaics after equalization, S Deq is the capacity of distributed photovoltaic after equalization, C d,i 、C f,i For L f,i are the ith DC capacitance, AC capacitance and AC reactance before the distributed photovoltaic equalization, S D,i is the capacity of the i-th distributed photovoltaic.

[0042] Optionally, conventional control parameters of the equivalent model of the original distributed photovoltaic system are calculated, specifically:

[0043] The conventional control parameters of distributed photovoltaics are aggregated, and the formula is as follows:

[0044]

[0045] Among them, N D,i It represents the ratio of the capacity of the i-th distributed photovoltaic unit to the capacity of the distributed photovoltaic equivalent unit, K is the conventional control / ride-through control parameter, K eq is the control parameter after distributed photovoltaic equalization, K i is the control parameter of the i-th distributed photovoltaic.

[0046] Optionally, the capacity weighting method and the segmented slope recovery method are introduced to calculate the equivalent parameters for distributed photovoltaic control during low voltage ride-through, specifically:

[0047] Introducing the capacity weighting method and the piecewise slope recovery method, constructing the control strategy mathematical model and the piecewise rate recovery control strategy model;

[0048] Based on the control strategy mathematical model and the segmented rate recovery control strategy model, the equivalent parameters of the distributed photovoltaic low voltage ride-through control period are calculated;

[0049] The mathematical model of the control strategy is as follows:

[0050] I d_R =g1I d_R_C1 +g2I d_R_C2 (6)

[0051] Among them, I d_R is the mathematical model of the control strategy, g1 and g2 are the weight coefficients of the recovery control strategy, I d_R_C1 and I d_R_C2 The current reference command of the recovery control strategy corresponding to g1 and g2;

[0052] The segmented rate recovery control strategy model is as follows:

[0053]

[0054] Among them, I d_R (t) is the segmented rate recovery control strategy model, n is the number of distributed photovoltaics in the active distribution network, h i 、k i are the weight coefficients and recovery rates of different distributed photovoltaics, I n_i is the current reference instruction of different distributed photovoltaics under normal operation, tr is the initial recovery time, t j+1 is the recovery time of the jth distributed photovoltaic unit, t n is the recovery start time of the nth distributed photovoltaic unit, t is the operating time, and j is the number of the distributed photovoltaic unit.

[0055] Optional, distributed photovoltaic equivalent model, the formula is as follows:

[0056]

[0057] Among them, g i Equivalent model of distributed photovoltaics, S Di,j is the capacity of the jth unit in the i-th distributed photovoltaic system.

[0058] In yet another aspect, the present invention further provides a computing device comprising: one or more processors;

[0059] a processor for executing one or more programs;

[0060] When the one or more programs are executed by the one or more processors, the above-described method is implemented.

[0061] In another aspect, the present invention further provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed, the method described above is implemented.

[0062] Compared with the prior art, the present invention has the following beneficial effects:

[0063] The present invention provides a method for constructing a distributed photovoltaic equivalent model, comprising: obtaining parameters of distributed photovoltaics in a distribution network; calculating electrical parameters of an original distributed photovoltaic equivalent model based on the distributed photovoltaic parameters; calculating conventional control parameters of the original distributed photovoltaic equivalent model based on the electrical parameters; introducing a capacity weighting method and a piecewise slope recovery method into the control strategy of the original distributed photovoltaic equivalent model based on the conventional control parameters to calculate equivalent parameters for distributed photovoltaic control during low-voltage ride-through; and constructing a distributed photovoltaic equivalent model based on the equivalent parameters for distributed photovoltaic control during low-voltage ride-through. The present invention achieves high-precision dynamic equivalent modeling of distributed photovoltaics. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 is a flow chart of the method of the present invention;

[0065] Figure 2 is a general distributed photovoltaic control strategy diagram;

[0066] Figure 3This is a control strategy diagram of the distributed photovoltaic equivalent model during the low-voltage penetration period of the present invention;

[0067] Figure 4 A structural diagram of a system in an example of the method of the present invention;

[0068] Figure 5 Schematic diagram of fitting under various control strategies in the embodiment of the method of the present invention;

[0069] Figure 6 It is a structural diagram of the system of the present invention. DETAILED DESCRIPTION

[0070] Exemplary embodiments of the present invention will now be described with reference to the accompanying drawings. However, the present invention may be embodied in many different forms and is not limited to the embodiments described herein. These embodiments are provided to provide a thorough and complete disclosure of the present invention and to fully convey the scope of the present invention to those skilled in the art. The terminology used in the exemplary embodiments shown in the accompanying drawings is not intended to limit the present invention. In the accompanying drawings, identical elements are denoted by the same reference numerals.

[0071] Unless otherwise specified, the terms used herein (including technical terms) have the meanings commonly understood by those skilled in the art. In addition, it is understood that terms defined in commonly used dictionaries should be understood to have the same meanings as those in the context of the relevant fields, and should not be understood as idealized or overly formal meanings.

[0072] Example 1:

[0073] The present invention proposes a method for constructing a distributed photovoltaic equivalent model, such as Figure 1 As shown, including:

[0074] Step 1: Obtain the parameters of distributed photovoltaics in the distribution network;

[0075] Step 2: Calculate the electrical parameters of the equivalent model of the original distributed photovoltaic system based on the parameters of the distributed photovoltaic system;

[0076] Step 3: Calculate conventional control parameters of the equivalent model of the original distributed photovoltaic system based on the electrical parameters;

[0077] Step 4: In the control strategy of the equivalent model of the original distributed photovoltaic system, based on the conventional control parameters, a capacity weighting method and a piecewise slope recovery method are introduced to calculate the equivalent parameters of the distributed photovoltaic system during the low voltage ride-through period;

[0078] Based on the equivalent parameters controlled during the distributed photovoltaic low voltage ride-through period, an equivalent model of distributed photovoltaic is constructed.

[0079] Among them, the electrical parameters of the equivalent model of the original distributed photovoltaic are calculated as follows:

[0080] The circuit parameter aggregation for distributed photovoltaics is as follows:

[0081]

[0082] Among them, C deq 、C feq , L feq are the DC capacitance, AC capacitance and AC reactance of distributed photovoltaics after equalization, S Deq is the capacity of distributed photovoltaic after equalization, C d,i 、C f,i For L f,i are the ith DC capacitance, AC capacitance and AC reactance before the distributed photovoltaic equalization, S D,i is the capacity of the i-th distributed photovoltaic.

[0083] The conventional control parameters of the equivalent model of the original distributed photovoltaic system are calculated as follows:

[0084] The conventional control parameters of distributed photovoltaics are aggregated, and the formula is as follows:

[0085]

[0086] Among them, N D,i It represents the ratio of the capacity of the i-th distributed photovoltaic unit to the capacity of the distributed photovoltaic equivalent unit, K is the conventional control / ride-through control parameter, K eq is the control parameter after distributed photovoltaic equalization, K i is the control parameter of the i-th distributed photovoltaic.

[0087] Among them, the capacity weighted method and the segmented slope recovery method are introduced to calculate the equivalent parameters of distributed photovoltaic control during low voltage ride-through, specifically:

[0088] Introducing the capacity weighting method and the piecewise slope recovery method, constructing the control strategy mathematical model and the piecewise rate recovery control strategy model;

[0089] Based on the control strategy mathematical model and the segmented rate recovery control strategy model, the equivalent parameters of the distributed photovoltaic low voltage ride-through control period are calculated;

[0090] The mathematical model of the control strategy is as follows:

[0091] I d_R =g1I d_R_C1 +g2I d_R_C2 (6)

[0092] Among them, Id_R is the mathematical model of the control strategy, g1 and g2 are the weight coefficients of the recovery control strategy, I d_R_C1 and I d_R_C2 The current reference command of the recovery control strategy corresponding to g1 and g2;

[0093] The segmented rate recovery control strategy model is as follows:

[0094]

[0095] Among them, I d_R (t) is the segmented rate recovery control strategy model, n is the number of distributed photovoltaics in the active distribution network, h i 、k i are the weight coefficients and recovery rates of different distributed photovoltaics, I n_i is the current reference instruction of different distributed photovoltaics under normal operation, t r is the initial recovery time, t j+1 is the recovery time of the jth distributed photovoltaic unit, t n is the recovery start time of the nth distributed photovoltaic unit, t is the operating time, and j is the number of the distributed photovoltaic unit.

[0096] Among them, the equivalent model of distributed photovoltaics is as follows:

[0097]

[0098] Among them, g i Equivalent model of distributed photovoltaics, S Di,j is the capacity of the jth unit in the i-th distributed photovoltaic system.

[0099] The present invention will be further described below with reference to embodiments and specific examples:

[0100] The embodiment steps include:

[0101] Step 1: Obtain the parameters of distributed photovoltaics in the distribution network.

[0102] Step 2: Calculate the electrical parameters of the distributed photovoltaic equivalent model. For distributed photovoltaics, perform circuit parameter aggregation as shown in the following formula:

[0103]

[0104] In the above formula, C deq 、C feq , L feq They represent the DC capacitance, AC capacitance and AC reactance of distributed photovoltaics respectively; S Deq Indicates the capacity of distributed photovoltaic after equalization.

[0105] Step 3: Calculate the conventional control parameters of the distributed photovoltaic equivalent model; for the conventional control parameters of distributed photovoltaics, the aggregation is as shown in the following formula:

[0106]

[0107] Where N D,i It represents the ratio of the capacity of the i-th distributed photovoltaic unit to the capacity of the distributed photovoltaic equivalent unit; K represents the conventional control and ride-through control parameters.

[0108] Step 4: Introduce the capacity weighting method and the segmented slope recovery method into the control strategy of the distributed photovoltaic equivalent model. To achieve the aggregate equivalent characteristics of the distributed photovoltaic system under various control characteristics, the capacity weighting method control is added in the recovery phase. First, different recovery controls are established and corresponding interface models are added to process the outputs. The processed multiple outputs are superimposed and fed into the current limiting model. The mathematical model of the control strategy is:

[0109] I d_R =g1I d_R_C1 +g2I d_R_C2 (27)

[0110] Where g represents the weight coefficient of the recovery control strategy; I d_R_C Indicates the current reference command for the recovery control strategy.

[0111] Affected by the capacity, output and recovery rate of the distributed photovoltaic system, the time it takes for the distributed photovoltaic system to restore its pre-fault power is different. When the power recovery of the distributed photovoltaic equivalent model is restored at a fixed rate, it will cause a large accuracy error. Therefore, the recovery control strategy of the equivalent model needs to be redesigned.

[0112] Design the following segmented rate recovery control strategy:

[0113]

[0114] Where n represents the number of distributed photovoltaics in the active distribution network; h i 、k i Represent the weight coefficient and recovery rate of different distributed photovoltaics; I n_i Indicates the current reference instructions of different distributed photovoltaic systems under normal operation.

[0115] From formula (7), we can know that the active current recovery instruction of the distributed photovoltaic equivalent model is r ~t1 period according to the rate ∑h i k i , i=1,…,n recovery; in the time period t1~t2, according to the rate ∑h i k i, i=2,…,n recovery; in the time period t2~t3, according to the rate ∑h i k i ,i=3,…,n is restored; and so on until t n At the rate k n Restore to the steady-state output of distributed photovoltaics.

[0116] Step 5: Calculate the equivalent parameters of distributed photovoltaic control during low voltage ride-through according to step 4 and build an equivalent model of distributed photovoltaic. The parameters in ride-through control are determined using the following equations:

[0117]

[0118] Where S Di,j Represents the capacity of the jth unit in the i-th distributed photovoltaic system.

[0119] Figure 2 It is the control strategy of the general model of distributed photovoltaic, including conventional control and low-throughput control. Figure 3 The low penetration control strategy used in the present invention is carried out according to the following steps:

[0120] Step 1: Obtain the parameters of distributed photovoltaic in the distribution network. Figure 4 Electrical parameters of the four distributed photovoltaic systems in China;

[0121] Step 2: Calculate the electrical parameters of the distributed photovoltaic equivalent model. Figure 4 The four distributed photovoltaic units are equivalent to one distributed photovoltaic unit. The electrical parameters of the distributed photovoltaic equivalent model are calculated. deq =0.04032F, C feq =8×10 -4 F, L feq =2.5×10 -4 H;

[0122] Step 3: Calculate the conventional control parameters of the distributed photovoltaic equivalent model and calculate the conventional control parameters separately according to the capacity weighted method.

[0123] Step 4: Introduce the capacity weighting method and the piecewise slope recovery method into the control strategy of the distributed photovoltaic equivalent model.

[0124] Step 5: Calculate the equivalent parameters for distributed PV control during low voltage ride-through based on step 4 and construct an equivalent model for distributed PV. The control parameters for low voltage ride-through in the equivalent model are g1 = 0.2, g2 = 0.4, g3 = 0.6, and g4 = 0.8.

[0125] According to the above implementation steps, the equivalent model of the present invention considering the transient characteristics of distributed photovoltaic aggregation is established, and high-precision dynamic equivalent modeling of distributed photovoltaic is achieved.

[0126] Set voltage drop fault, Figure 5 The responses of the distributed photovoltaic detailed model and the equivalent model are shown. Under large disturbances, the transient curve of the single-unit equivalent model established by the present invention is essentially consistent with the transient curve of the aggregated multiple distributed photovoltaic units. The distributed photovoltaic equivalent model of the present invention not only has high curve tracking performance under different control strategies, but also has good accuracy under different power distributions.

[0127] Example 2:

[0128] The present invention also provides a system 200 for constructing a distributed photovoltaic equivalent model, such as Figure 6 As shown, including:

[0129] The parameter acquisition unit 201 is used to obtain the parameters of distributed photovoltaic in the distribution network;

[0130] A first calculation unit 202 is configured to calculate electrical parameters of an equivalent model of an original distributed photovoltaic system based on the parameters of the distributed photovoltaic system;

[0131] A second calculation unit 203 is configured to calculate conventional control parameters of the equivalent model of the original distributed photovoltaic system based on the electrical parameters;

[0132] The third calculation unit 204 is configured to introduce a capacity weighting method and a piecewise slope recovery method into the control strategy of the original distributed photovoltaic equivalent model according to the conventional control parameters to calculate equivalent parameters for the distributed photovoltaic control during the low voltage ride-through period;

[0133] The model building unit 205 is configured to build an equivalent model of distributed photovoltaics based on equivalent parameters controlled during the distributed photovoltaic low voltage ride-through period.

[0134] Among them, the electrical parameters of the equivalent model of the original distributed photovoltaic are calculated as follows:

[0135] The circuit parameter aggregation for distributed photovoltaics is as follows:

[0136]

[0137] Among them, C deq 、C feq , L feq are the DC capacitance, AC capacitance and AC reactance of distributed photovoltaics after equalization, S Deq is the capacity of distributed photovoltaic after equalization, C d,i 、C f,iFor L f,i are the ith DC capacitance, AC capacitance and AC reactance before the distributed photovoltaic equalization, S D,i is the capacity of the i-th distributed photovoltaic.

[0138] The conventional control parameters of the equivalent model of the original distributed photovoltaic system are calculated as follows:

[0139] The conventional control parameters of distributed photovoltaics are aggregated, and the formula is as follows:

[0140]

[0141] Among them, N D,i It represents the ratio of the capacity of the i-th distributed photovoltaic unit to the capacity of the distributed photovoltaic equivalent unit, K is the conventional control / ride-through control parameter, K eq is the control parameter after distributed photovoltaic equalization, K i is the control parameter of the i-th distributed photovoltaic.

[0142] Among them, the capacity weighted method and the segmented slope recovery method are introduced to calculate the equivalent parameters of distributed photovoltaic control during low voltage ride-through, specifically:

[0143] Introducing the capacity weighting method and the piecewise slope recovery method, constructing the control strategy mathematical model and the piecewise rate recovery control strategy model;

[0144] Based on the control strategy mathematical model and the segmented rate recovery control strategy model, the equivalent parameters of the distributed photovoltaic low voltage ride-through control period are calculated;

[0145] The mathematical model of the control strategy is as follows:

[0146] I d_R =g1I d_R_C1 +g2I d_R_C2 (6)

[0147] Among them, I d_R is the mathematical model of the control strategy, g1 and g2 are the weight coefficients of the recovery control strategy, I d_R_C1 and I d_R_C2 The current reference command of the recovery control strategy corresponding to g1 and g2;

[0148] The segmented rate recovery control strategy model is as follows:

[0149]

[0150] Among them, I d_R (t) is the segmented rate recovery control strategy model, n is the number of distributed photovoltaics in the active distribution network, h i 、ki are the weight coefficients and recovery rates of different distributed photovoltaics, I n_i is the current reference instruction of different distributed photovoltaics under normal operation, t r is the initial recovery time, t j+1 is the recovery time of the jth distributed photovoltaic unit, t n is the recovery start time of the nth distributed photovoltaic unit, t is the operating time, and j is the number of the distributed photovoltaic unit.

[0151] Among them, the equivalent model of distributed photovoltaics is as follows:

[0152]

[0153] Among them, g i Equivalent model of distributed photovoltaics, S Di,j is the capacity of the jth unit in the i-th distributed photovoltaic system.

[0154] The present invention realizes high-precision dynamic equivalent modeling of distributed photovoltaics.

[0155] Example 3:

[0156] Based on the same inventive concept, the present invention also provides a computer device, which includes a processor and a memory, wherein the memory is used to store a computer program, the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or may be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions in the computer storage medium to implement the corresponding method flow or corresponding function, so as to implement the steps of the method in the above embodiment.

[0157] Example 4:

[0158] Based on the same inventive concept, the present invention also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a computer device for storing programs and data. It can be understood that the computer-readable storage medium here can include both built-in storage media in the computer device and, of course, extended storage media supported by the computer device. The computer-readable storage medium provides a storage space that stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by the processor are also stored in the storage space. These instructions can be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory. The processor can load and execute one or more instructions stored in the computer-readable storage medium to implement the steps of the method in the above embodiment.

[0159] It will be understood by those skilled in the art that the embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code. The solutions in the embodiments of the present invention may be implemented in various computer languages, for example, the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0160] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0161] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0162] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0163] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0164] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A method for constructing a distributed photovoltaic equivalent model, characterized in that: The method comprises: Obtain parameters of distributed photovoltaics in the distribution network; Based on the distributed photovoltaic parameters, calculating the electrical parameters of the equivalent model of the original distributed photovoltaic; Based on the electrical parameters, calculating conventional control parameters of the equivalent model of the original distributed photovoltaic system; In the control strategy of the equivalent model of the original distributed photovoltaic, based on the conventional control parameters, a capacity weighting method and a piecewise slope recovery method are introduced to calculate the equivalent parameters of the distributed photovoltaic control during the low voltage ride-through period; Based on the equivalent parameters controlled during the distributed photovoltaic low voltage ride-through period, an equivalent model of distributed photovoltaic is constructed; The capacity weighted method and the segmented slope recovery method are introduced to calculate the equivalent parameters of distributed photovoltaic control during low voltage ride-through, specifically: Introducing the capacity weighting method and the piecewise slope recovery method, constructing the control strategy mathematical model and the piecewise rate recovery control strategy model; Based on the control strategy mathematical model and the segmented rate recovery control strategy model, the equivalent parameters of the distributed photovoltaic low voltage ride-through control period are calculated; The mathematical model of the control strategy is as follows: I d_R =g1I d_R_C1 +g2I d_R_C2 (1) Among them, I d_R is the mathematical model of the control strategy, g1 and g2 are the weight coefficients of the recovery control strategy, I d_R_C1 and I d_R_C2 The current reference command of the recovery control strategy corresponding to g1 and g2; The segmented rate recovery control strategy model is as follows: Among them, I d_R (t) is the segmented rate recovery control strategy model, n is the number of distributed photovoltaics in the active distribution network, h i 、k i are the weight coefficients and recovery rates of different distributed photovoltaics, I n_i is the current reference instruction of different distributed photovoltaics under normal operation, t r is the initial recovery time, t j+1 is the recovery time of the jth distributed photovoltaic unit, t n is the recovery start time of the nth distributed photovoltaic unit, t is the operating time, and j is the number of the distributed photovoltaic unit; The equivalent model of distributed photovoltaics is as follows: Among them, g i Equivalent model of distributed photovoltaics, S Di,j is the capacity of the jth unit in the i-th distributed photovoltaic system.

2. The method according to claim 1, characterized in that The electrical parameters of the equivalent model of the original distributed photovoltaic system are calculated as follows: The circuit parameter aggregation for distributed photovoltaics is as follows: Among them, C deq 、C feq , L feq are the DC capacitance, AC capacitance and AC reactance of distributed photovoltaics after equalization, S Deq is the capacity of distributed photovoltaic after equalization, C d,i 、C f,i For L f,i are the ith DC capacitance, AC capacitance and AC reactance before the distributed photovoltaic equalization, S D,i is the capacity of the i-th distributed photovoltaic.

3. The method according to claim 1, characterized in that The conventional control parameters of the equivalent model of the original distributed photovoltaic system are calculated as follows: The conventional control parameters of distributed photovoltaics are aggregated, and the formula is as follows: Among them, N D,i It represents the ratio of the capacity of the i-th distributed photovoltaic unit to the capacity of the distributed photovoltaic equivalent unit, K is the conventional control / ride-through control parameter, K eq is the control parameter after distributed photovoltaic equalization, K i is the control parameter of the i-th distributed photovoltaic.

4. A system for constructing a distributed photovoltaic equivalent model, characterized in that: The system comprises: Parameter acquisition unit, used to obtain parameters of distributed photovoltaic in the distribution network; A first calculation unit is configured to calculate electrical parameters of an equivalent model of an original distributed photovoltaic system based on the parameters of the distributed photovoltaic system; A second calculation unit is configured to calculate conventional control parameters of the equivalent model of the original distributed photovoltaic system based on the electrical parameters; a third calculation unit, configured to introduce a capacity weighting method and a piecewise slope recovery method into the control strategy of the equivalent model of the original distributed photovoltaic system according to the conventional control parameters, so as to calculate equivalent parameters for control of the distributed photovoltaic system during the low voltage ride-through period; A model building unit is used to build an equivalent model of distributed photovoltaics based on equivalent parameters controlled during the distributed photovoltaic low voltage ride-through period; The capacity weighted method and the segmented slope recovery method are introduced to calculate the equivalent parameters of distributed photovoltaic control during low voltage ride-through, specifically: Introducing the capacity weighting method and the piecewise slope recovery method, constructing the control strategy mathematical model and the piecewise rate recovery control strategy model; Based on the control strategy mathematical model and the segmented rate recovery control strategy model, the equivalent parameters of the distributed photovoltaic low voltage ride-through control period are calculated; The mathematical model of the control strategy is as follows: I d_R =g1I d_R_C1 +g2I d_R_C2 (1) Among them, I d_R is the mathematical model of the control strategy, g1 and g2 are the weight coefficients of the recovery control strategy, I d_R_C1 and I d_R_C2 The current reference command of the recovery control strategy corresponding to g1 and g2; The segmented rate recovery control strategy model is as follows: Among them, I d_R (t) is the segmented rate recovery control strategy model, n is the number of distributed photovoltaics in the active distribution network, h i 、k i are the weight coefficients and recovery rates of different distributed photovoltaics, I n_i is the current reference instruction of different distributed photovoltaics under normal operation, t r is the initial recovery time, t j+1 is the recovery time of the jth distributed photovoltaic unit, t n is the recovery start time of the nth distributed photovoltaic unit, t is the operating time, and j is the number of the distributed photovoltaic unit; The equivalent model of distributed photovoltaics is as follows: Among them, g i Equivalent model of distributed photovoltaics, S Di,j is the capacity of the jth unit in the i-th distributed photovoltaic system.

5. The system according to claim 4, characterized in that The electrical parameters of the equivalent model of the original distributed photovoltaic system are calculated as follows: The circuit parameter aggregation for distributed photovoltaics is as follows: Among them, C deq 、C feq , L feq are the DC capacitance, AC capacitance and AC reactance of distributed photovoltaics after equalization, S Deq is the capacity of distributed photovoltaic after equalization, C d,i 、C f,i For L f,i are the ith DC capacitance, AC capacitance and AC reactance before the distributed photovoltaic equalization, S D,i is the capacity of the i-th distributed photovoltaic.

6. The system according to claim 4, characterized in that The conventional control parameters of the equivalent model of the original distributed photovoltaic system are calculated as follows: The conventional control parameters of distributed photovoltaics are aggregated, and the formula is as follows: Among them, N D,i It represents the ratio of the capacity of the i-th distributed photovoltaic unit to the capacity of the distributed photovoltaic equivalent unit, K is the conventional control / ride-through control parameter, K eq is the control parameter after distributed photovoltaic equalization, K i is the control parameter of the i-th distributed photovoltaic.

7. A computer device, characterized in that: include: one or more processors; a processor for executing one or more programs; When the one or more programs are executed by the one or more processors, the method according to any one of claims 1 to 3 is implemented.

8. A computer-readable storage medium, characterized in that A computer program is stored thereon, and when the computer program is executed, the method according to any one of claims 1 to 3 is implemented.

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