Grid-Forming Distributed Photovoltaic Capacity Optimization Method and Device

Abstract

The present invention is applicable to the field of power technology, and provides a method and device for optimizing the capacity of a network-forming distributed photovoltaic system. The method includes: obtaining system parameters of a photovoltaic power station grid-connected system; respectively constructing instability-free conditions for the dominant oscillation modes of the grid-following photovoltaic units and the network-forming photovoltaic units according to the system parameters; determining the capacity constraints of the grid-following photovoltaic units and the network-forming photovoltaic units respectively according to the instability-free conditions for the dominant oscillation modes; and solving a network-forming photovoltaic capacity optimization model according to the capacity constraints of the grid-following photovoltaic units and the network-forming photovoltaic units to obtain the optimal capacity of the network-forming photovoltaic units. The present invention ensures the stability of photovoltaic grid connection while enhancing the frequency active support ability of the photovoltaic power station.

Description

Technical Field

[0001] The present invention belongs to the technical field of electric power, and particularly relates to a method and device for optimizing the capacity of a network-forming distributed photovoltaic system. Background Art

[0002] At present, the power system is gradually showing the characteristics of "dual high" with a high proportion of new energy and a high proportion of power electronic equipment.

[0003] Different from synchronous machines, renewable power sources represented by solar energy need converters to access the AC synchronous grid. Due to the intermittency of these energy sources, the grid-connected control method is usually designed as a current-source type grid-following control with the goal of maximum power tracking. Grid-following control and grid synchronization require a phase-locked loop to measure the phase information of the grid connection point, and there are stability problems in weak grids. Therefore, for the grid with distributed photovoltaic access, the converter should preferably adopt network-forming control. The network-forming converter adopts a power synchronization strategy similar to that of a synchronous generator, can achieve synchronization without relying on a phase-locked loop, and can also provide support for the voltage and frequency of the system, which helps to enhance the stability of the power system. At the same time, in the grid-connected system of a photovoltaic power station with a hybrid of grid-following and network-forming types, the capacity optimization of network-forming distributed photovoltaics is also very important.

[0004] For example, the document with the application number CN202110283493.4 proposes a method for evaluating the limit grid-connected capacity of distributed photovoltaics based on distributionally robust optimization, taking the maximization of the grid-connected capacity of distributed photovoltaics in the distribution network as the objective function, considering constraints such as the operation constraints of distributed photovoltaics, node power balance constraints, power flow constraints, branch transmission capacity constraints, and node voltage constraints, and solving the limit grid-connected capacity of distributed photovoltaics. However, this method has insufficient consideration of the stability of the power system and there are certain risks. Summary of the Invention

[0005] In view of this, the embodiments of the present invention provide a method for optimizing the capacity of a network-forming distributed photovoltaic system, which can improve the frequency active support ability of the photovoltaic power station while ensuring the stability of photovoltaic grid connection.

[0006] In a first aspect, the embodiments of the present invention provide a method for optimizing the capacity of a network-forming distributed photovoltaic system, including:

[0007] Obtain the system parameters of the grid-connected system of the photovoltaic power station;

[0008] According to the system parameters, respectively construct the instability-free conditions of the dominant oscillation modes of the grid-following photovoltaic units and the network-forming photovoltaic units;

[0009] According to the instability-free conditions of the dominant oscillation modes, respectively determine the capacity constraints of the grid-following photovoltaic units and the network-forming photovoltaic units;

[0010] According to the capacity constraints of the grid-following PV units and the grid-forming PV units, solve the grid-forming PV capacity optimization model to obtain the optimal capacity of the grid-forming PV units.

[0011] Combined with the first aspect, in a possible implementation manner of the first aspect, the condition for the dominant oscillation mode of the grid-following PV unit not to become unstable is that the effective short-circuit ratio of the grid-following PV unit is greater than the critical short-circuit ratio of the grid-following PV unit operating in parallel.

[0012] Combined with the first aspect, in a possible implementation manner of the first aspect, the calculation formula for the effective short-circuit ratio of the grid-following PV unit is:

[0013] SCR1 = S ac / E1;

[0014] Then, the capacity constraint of the grid-following PV unit is:

[0015]

[0016] Among them, SCR1 is the effective short-circuit ratio of the grid-following PV unit; S ac is the short-circuit capacity at the grid connection point; E1 is the capacity of the grid-following PV unit; CSCR1 is the critical short-circuit ratio of the grid-following PV unit operating in parallel; CSCR2 is the critical short-circuit ratio of the grid-forming PV unit operating in parallel; E is the total capacity of the grid-following PV unit and the grid-forming PV unit.

[0017] Combined with the first aspect, in a possible implementation manner of the first aspect, the condition for the dominant oscillation mode of the grid-forming PV unit not to become unstable is that the effective short-circuit ratio of the grid-forming PV unit is less than the critical short-circuit ratio of the grid-forming PV unit operating in parallel.

[0018] Combined with the first aspect, in a possible implementation manner of the first aspect, the calculation formula for the effective short-circuit ratio of the grid-forming PV unit is:

[0019] SCR2 = S ac / E2;

[0020] Then, the capacity constraint of the grid-forming PV unit is:

[0021]

[0022] Among them, SCR2 is the effective short-circuit ratio of the grid-forming PV unit; S ac is the short-circuit capacity at the grid connection point; E2 is the capacity of the grid-forming PV unit; CSCR1 is the critical short-circuit ratio of the grid-following PV unit operating in parallel; CSCR2 is the critical short-circuit ratio of the grid-forming PV unit operating in parallel; E is the total capacity of the grid-following PV unit and the grid-forming PV unit.

[0023] In combination with the first aspect, in a possible implementation manner of the first aspect, before solving the network-forming photovoltaic capacity optimization model, it further includes:

[0024] Construct the network-forming photovoltaic capacity optimization model minf = h f + c f ;

[0025] Where h f is the frequency drop risk function; c f is the network-forming photovoltaic unit capacity penalty function.

[0026] In combination with the first aspect, in a possible implementation manner of the first aspect, the frequency drop risk function is:

[0027]

[0028] Where t end is the fault duration; Δf(t) is the frequency deviation.

[0029] In combination with the first aspect, in a possible implementation manner of the first aspect, the network-forming photovoltaic unit capacity penalty function is:

[0030]

[0031] Where E2 is the capacity of the network-forming photovoltaic unit; E limit is the capacity configuration limit.

[0032] In a second aspect, an embodiment of the present invention provides a network-forming distributed photovoltaic capacity optimization device, including:

[0033] An acquisition module, configured to acquire system parameters of a photovoltaic power station grid-connected system;

[0034] A construction module, configured to respectively construct the non-instability conditions of the dominant oscillation modes of the network-following photovoltaic unit and the network-forming photovoltaic unit according to the system parameters;

[0035] A determination module, configured to respectively determine the capacity constraints of the network-following photovoltaic unit and the network-forming photovoltaic unit according to the non-instability conditions of the dominant oscillation modes;

[0036] A calculation module, configured to solve the network-forming photovoltaic capacity optimization model according to the capacity constraints of the network-following photovoltaic unit and the network-forming photovoltaic unit, and obtain the optimal capacity of the network-forming photovoltaic unit.

[0037] In combination with the second aspect, in a possible implementation manner of the second aspect, the network-forming photovoltaic capacity optimization model is:

[0038] minf = h f + c f ;

[0039] Among them, h f is the frequency drop risk function; c f is the capacity penalty function of the grid-forming photovoltaic unit.

[0040] The beneficial effects of the embodiments of the present invention compared with the prior art are as follows:

[0041] The embodiments of the present invention propose a calculation principle for the proportion configuration of grid-forming photovoltaic units in a photovoltaic power station grid connection system with a combination of grid-following and grid-forming types, that is, respectively constructing the instability-free conditions of the dominant oscillation modes of grid-following photovoltaic units and grid-forming photovoltaic units. According to the instability-free conditions of the dominant oscillation modes, the capacity constraints of grid-following photovoltaic units and grid-forming photovoltaic units are respectively determined, and then the grid-forming photovoltaic capacity optimization model is solved to obtain the optimal capacity of the grid-forming photovoltaic units, which improves the frequency active support ability of the photovoltaic power station while ensuring the stable grid connection of the photovoltaic power station. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0043] Figure 1 is a schematic structural diagram of the photovoltaic power station grid connection system provided by the embodiments of the present invention;

[0044] Figure 2 is a schematic implementation flow diagram of the grid-forming distributed photovoltaic capacity optimization method provided by the embodiments of the present invention Figure 1 ;

[0045] Figure 3 is a schematic implementation flow diagram of the grid-forming distributed photovoltaic capacity optimization method provided by the embodiments of the present invention Figure 2 ;

[0046] Figure 4 is a schematic diagram of the simulation results provided by the embodiments of the present invention Figure 1 ;

[0047] Figure 5 is a schematic diagram of the simulation results provided by the embodiments of the present invention Figure 2 ;

[0048] Figure 6 is a schematic diagram of the grid-forming distributed photovoltaic capacity optimization device provided by the embodiments of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0049] In the following description, specific details such as specific system structures and technologies are presented for the purpose of illustration rather than limitation, so as to thoroughly understand the embodiments of the present invention. However, those skilled in the art should clearly understand that the present invention can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid unnecessary details from interfering with the description of the present invention.

[0050] To illustrate the technical solutions described in the present invention, the following will be described through specific embodiments.

[0051] The converter control mode can be divided into grid-following type and grid-forming type. With the joint support of a large number of synchronous motors with inertia, the AC system connected to the PV grid-connected equipment can be considered a "strong" grid, and the fluctuation range of the grid voltage amplitude and frequency is very small. In this case, the grid-following type converter only needs to closely follow the voltage of the connected AC bus and inject the set current to achieve the power generation goal. At this time, the grid-connected equipment does not have the power and power angle equation constraints of a synchronous motor, its power is decoupled from the system frequency, and it cannot actively provide inertia support for the grid under active power disturbances, nor does it have the instantaneous power sharing ability and primary frequency regulation ability. Over time, as the PV proportion increases, the system inertia will gradually decrease, and a small disturbance will cause large fluctuations and deviations in the grid frequency, and even grid collapse.

[0052] To overcome the limitations of the grid-following type, the grid-forming type converter came into being. It simulates the synchronization process of a synchronous machine through a control strategy, directly controls the amplitude and phase angle of the inverter output voltage, presents a voltage source characteristic similar to that of a synchronous machine, can actively provide support for the voltage and frequency of the system, and can operate independently. Therefore, for the grid with PV access, grid-forming type equipment is an inevitable choice.

[0053] This embodiment proposes a grid-forming type distributed PV capacity optimization method for active frequency support. According to the active power three-stage transient response characteristics of grid-forming and grid-following PV units, a multi-objective optimization method is used to obtain the optimal capacity selection scheme of grid-forming PV units, which can improve the active frequency support ability of the power station while ensuring the stable grid connection of the PV power station. To make the purpose, technical solutions, and advantages of the present invention clearer, the following will be described through specific embodiments with reference to the accompanying drawings.

[0054] Figure 1 It is a schematic structural diagram of the PV power station grid connection system provided in this embodiment. The PV power station includes grid-following type PV units and grid-forming type PV units, and the grid connection methods of the two types of units are different.

[0055] See Figure 2 and Figure 3Schematic diagram of the implementation process of the grid-forming distributed photovoltaic capacity optimization method shown, the method comprising:

[0056] Step S201, obtaining the system parameters of the photovoltaic power station grid-connected system.

[0057] In this embodiment, the system parameters are used to calculate and construct the optimization model and constraint conditions. Here, the system parameters may include voltage, current, power operation data, etc.

[0058] Step S202, respectively constructing the non-instability conditions of the dominant oscillation modes of the grid-following photovoltaic units and the grid-forming photovoltaic units according to the system parameters.

[0059] The sub-synchronous oscillation accidents frequently occurring in the new energy grid-connected system seriously affect the consumption of new energy. Previous research on the sub-synchronous oscillation problem of the new energy power generation grid-connected system mainly focused on the wind power grid-connected system, and there was less research on the photovoltaic grid-connected system. Although there is no report on the sub-synchronous oscillation accident of the photovoltaic power station at present, there are certain similarities between photovoltaic power generation and wind power generation. Both are connected to the AC grid via converters, and their control structures and strategies are similar. The dominant oscillation mode of the photovoltaic power generation grid-connected system with a static var generator is mainly caused by the dynamic interaction between the photovoltaic power station and the AC system. In addition, the state variables of the inner loop control of the photovoltaic inverter have a high participation degree in the oscillation mode, indicating that this link has a greater impact on the dominant sub-synchronous oscillation mode.

[0060] Assume that the capacities of the grid-following and grid-forming photovoltaic units in the photovoltaic power station are E1 and E2 respectively, the total capacity is E (E = E1 + E2), and the short-circuit capacity at the connection point is S ac , then:

[0061] The effective short-circuit ratio of the grid-following photovoltaic unit is SCR1 = S ac / E1;

[0062] The effective short-circuit ratio of the grid-forming photovoltaic unit is SCR2 = S ac / E!.

[0063] The short-circuit ratio (SCR) refers to the system short-circuit capacity divided by the equipment capacity. So when the short-circuit ratio is large, it means that this equipment is connected to a strong system, indicating that the switching of the equipment has little impact on the system. And the short-circuit capacity is numerically equal to the system admittance value under the unit voltage condition, which is the reciprocal of the Thevenin equivalent impedance of the system. The larger the short-circuit capacity, the smaller the Thevenin equivalent resistance of the system, and the switching of the load, shunt capacitor or reactor will not cause large changes in the voltage amplitude. Therefore, the system is relatively strong.

[0064] The damping ratio of the subsynchronous oscillation mode of the grid-following grid-connected system increases with the increase of the short-circuit ratio, while the damping ratio of the low-frequency oscillation mode of the grid-forming grid-connected system decreases with the increase of the short-circuit ratio. Therefore, the conditions for maintaining the stability of the dominant oscillation modes corresponding to the two types of photovoltaic units in the photovoltaic power station are constructed as follows:

[0065]

[0066] Among them, CSCR1 and CSCR2 are the critical short-circuit ratios for the grid-following photovoltaic unit and the grid-forming photovoltaic unit to be connected to the grid, respectively, and can be obtained by analyzing and calculating using the eigenvalue root locus method. The calculation process can be briefly described as follows: If the entire root locus is located in the left half-plane, it means that no matter how the gain changes, all the characteristic roots of the system have negative real parts, and the system is stable; if the root locus is on the imaginary axis, the system is in a critically stable state, which means that the system may oscillate continuously. At this time, the intersection point of the root locus and the imaginary axis is the critical short-circuit ratio CSCR; if the root locus is completely located in the right half-plane, it means that no matter what parameters are selected, the system is unstable.

[0067] Step S203: According to the conditions for the stability of the dominant oscillation mode, determine the capacity constraints of the grid-following photovoltaic unit and the grid-forming photovoltaic unit, respectively.

[0068] According to the conditions for the stability of the dominant oscillation modes corresponding to the two types of photovoltaic units in step S202, the capacity value ranges of the grid-following photovoltaic unit and the grid-forming photovoltaic unit can be solved.

[0069] Among them, the capacity of the grid-following photovoltaic unit satisfies:

[0070]

[0071] The capacity of the grid-forming photovoltaic unit satisfies:

[0072]

[0073] Step S204: According to the capacity constraints of the grid-following photovoltaic unit and the grid-forming photovoltaic unit, solve the grid-forming photovoltaic capacity optimization model to obtain the optimal capacity of the grid-forming photovoltaic unit.

[0074] In the synchronous machine power grid, active power disturbances (such as short circuits and load increases) will cause the system to have unbalanced active power, which is considered to be the internal driving force, that is, the essential reason for causing low-frequency oscillations in the power grid. Therefore, to suppress low-frequency oscillations, it is necessary to suppress active power, and the power grid is required to actively provide power support to suppress the unbalanced active power of the system. By coupling the synchronous machine rotor speed with active or reactive power support devices (such as photovoltaic and energy storage), active power support can be provided for the power grid.

[0075] Convert the capacity of the distributed photovoltaic units in step S203 into the number of units. When this constraint relationship is satisfied, theoretically, the dominant oscillation mode can be kept stable. Based on this, with other parameters unchanged, set the same working conditions, analyze the change of the frequency dynamic response of different numbers of grid-forming photovoltaic units, and comprehensively consider the frequency active support ability and economic requirements of the grid-forming photovoltaic units, and propose to establish an objective function considering the frequency drop risk to determine the optimal capacity selection scheme of the grid-forming photovoltaic units.

[0076] Specifically, construct an optimization model for the capacity of grid-forming photovoltaic:

[0077] min f = h f + c f ;

[0078] Among them, h f is the frequency drop risk function; c f is the capacity penalty function of the grid-forming photovoltaic units.

[0079] Optionally, the frequency drop risk function is:

[0080]

[0081] Among them, t end is the fault duration; Δf(t) is the frequency deviation, that is, the difference between the rated power and the lowest point of the frequency drop.

[0082] Optionally, the capacity penalty function of the grid-forming photovoltaic units is:

[0083]

[0084] Among them, E2 is the capacity of the grid-forming photovoltaic units; E limit is the capacity configuration limit.

[0085] In the embodiment of the present invention, for the grid-connected system of a photovoltaic power station with a hybrid of grid-following and grid-forming types, a calculation principle for the proportion configuration of grid-forming photovoltaic units in the photovoltaic power station considering the oscillation stability constraint is proposed, that is, the dominant oscillation mode instability conditions of the grid-following photovoltaic units and the grid-forming photovoltaic units are respectively constructed. According to the dominant oscillation mode instability conditions, the capacity constraints of the grid-following photovoltaic units and the grid-forming photovoltaic units are respectively determined, and then the optimization model for the capacity of the grid-forming photovoltaic is solved to obtain the optimal capacity of the grid-forming photovoltaic units, which improves the frequency active support ability of the photovoltaic power station while ensuring the stable grid connection of the photovoltaic power station.

[0086] In a more specific embodiment, the capacity of the distributed photovoltaic system is 50 MW, the short-circuit capacity of the grid connection point is 80 MVA, and the CSCR1 and CSCR2 are determined to be 2.2 and 5.0 respectively by the eigenvalue root locus method. The approximate capacity ranges of the two types of units are determined as follows: the grid-following type E1 < 34 MW, and the grid-forming type E2 > 16 MW.

[0087] Figure 4 is the frequency characteristic curve under faults without optimization. When a fault occurs in the system, the valley value of the frequency drop is 49.3 Hz. Figure 5 is the frequency characteristic curve under faults optimized by the method of the present invention. When a fault occurs in the system, the valley value of the frequency drop is 49.6 Hz. The results show that the present invention can accurately configure the capacity of the grid-forming photovoltaic units in the distributed photovoltaic system on the basis of meeting the oscillation stability constraints, while reducing the frequency drop risk and enhancing the frequency active support ability of the power station. The correctness and effectiveness of the proposed configuration method are verified by simulation examples. The results show that it can improve the frequency active support ability of the power station while ensuring the stable grid connection of the photovoltaic power station, and has good engineering application value.

[0088] Therefore, the grid-forming distributed photovoltaic capacity optimization method for frequency active support of the present invention has the following beneficial effects: (1) For the grid connection system of a photovoltaic power station with a mixture of grid-following type and grid-forming type, a calculation principle for the proportion configuration of the grid-forming photovoltaic units in the photovoltaic power station considering the oscillation stability constraints is proposed, which can ensure the stable operation of the power station connected to the grid; (2) For the three-stage transient response characteristics of the active power of the grid-following photovoltaic units and the grid-forming photovoltaic units, a coordinated optimization configuration method considering the frequency drop risk is proposed. The results show that it can improve the frequency active support ability of the photovoltaic power station.

[0089] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.

[0090] Figure 6 is a schematic structural diagram of the grid-forming distributed photovoltaic capacity optimization device 60 provided by the embodiment of the present invention. Refer to Figure 6 As shown, the device includes:

[0091] An acquisition module 61, configured to acquire the system parameters of the grid connection system of the photovoltaic power station.

[0092] A construction module 62, configured to respectively construct the non-instability conditions of the dominant oscillation modes of the grid-following photovoltaic units and the grid-forming photovoltaic units according to the system parameters.

[0093] A determination module 63, configured to determine the capacity constraints of the grid-connected PV units and the grid-forming PV units respectively according to the condition that the dominant oscillation mode is stable.

[0094] A calculation module 64, configured to solve the grid-forming PV capacity optimization model according to the capacity constraints of the grid-connected PV units and the grid-forming PV units, and obtain the optimal capacity of the grid-forming PV units.

[0095] As a possible implementation, the condition for the dominant oscillation mode of the grid-connected PV units to be stable is that the effective short-circuit ratio of the grid-connected PV units is greater than the critical short-circuit ratio of the grid-connected PV units operating in parallel.

[0096] As a possible implementation, the calculation formula for the effective short-circuit ratio of the grid-connected PV units is:

[0097] SCR1 = S ac / E1;

[0098] Then, the capacity constraint of the grid-connected PV units is:

[0099]

[0100] Wherein, SCR1 is the effective short-circuit ratio of the grid-connected PV units; S ac is the short-circuit capacity at the grid connection point; E1 is the capacity of the grid-connected PV units; CSCR1 is the critical short-circuit ratio of the grid-connected PV units operating in parallel; CSCR2 is the critical short-circuit ratio of the grid-forming PV units operating in parallel; E is the total capacity of the grid-connected PV units and the grid-forming PV units.

[0101] As a possible implementation, the condition for the dominant oscillation mode of the grid-forming PV units to be stable is that the effective short-circuit ratio of the grid-forming PV units is less than the critical short-circuit ratio of the grid-forming PV units operating in parallel.

[0102] As a possible implementation, the calculation formula for the effective short-circuit ratio of the grid-forming PV units is:

[0103] SCR2 = S ac / E2;

[0104] Then, the capacity constraint of the grid-forming PV units is:

[0105]

[0106] Wherein, SCR2 is the effective short-circuit ratio of the grid-forming PV units; S acThe short-circuit capacity at the grid connection point; E2 is the capacity of the grid-forming PV unit; CSCR1 is the critical short-circuit ratio for the grid-following PV unit to operate in parallel; CSCR2 is the critical short-circuit ratio for the grid-forming PV unit to operate in parallel; E is the total capacity of the grid-following PV unit and the grid-forming PV unit.

[0107] As a possible implementation, the grid-forming PV capacity optimization model is:

[0108] min f = h f + c f ;

[0109] where h f is the frequency drop risk function; c f is the capacity penalty function of the grid-forming PV unit.

[0110] As a possible implementation, the frequency drop risk function is:

[0111]

[0112] where t end is the fault duration; Δf(t) is the frequency deviation.

[0113] As a possible implementation, the capacity penalty function of the grid-forming PV unit is:

[0114]

[0115] where E2 is the capacity of the grid-forming PV unit; E limit is the capacity configuration limit.

[0116] In the embodiments of the present invention, for the grid connection system of a PV power station with a mixture of grid-following and grid-forming types, a calculation principle for the proportion configuration of grid-forming PV units in the PV power station considering oscillation stability constraints is proposed, that is, the non-instability conditions of the dominant oscillation modes of the grid-following PV units and the grid-forming PV units are respectively constructed. According to the non-instability conditions of the dominant oscillation modes, the capacity constraints of the grid-following PV units and the grid-forming PV units are respectively determined, and then the grid-forming PV capacity optimization model is solved to obtain the optimal capacity of the grid-forming PV units, which improves the frequency active support ability of the PV power station while ensuring the stable grid connection of the PV power station.

[0117] In the above embodiments, the descriptions of the respective embodiments have their own focuses. For parts not detailed or recorded in a certain embodiment, reference may be made to the relevant descriptions of other embodiments.

[0118] Those of ordinary skill in the art can realize that the templates, units, and algorithm steps of the examples described in combination with the embodiments disclosed herein can be implemented by electronic hardware or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods for each specific application to implement the described functions, but such implementation should not be considered to exceed the scope of the present invention.

[0119] If a module / unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, to implement all or part of the processes in the methods of the above embodiments of the present invention, it can also be completed by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above embodiments of the various network-constructing distributed photovoltaic capacity optimization method can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file, or some intermediate form, etc. The computer-readable medium can include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disc, computer memory, read-only memory, random access memory, electrical carrier signal, telecommunication signal, and software distribution medium, etc.

[0120] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that: they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A method for optimizing the capacity of a network-forming distributed photovoltaic system, characterized in that, Including: Obtain the system parameters of the grid-connected system of the photovoltaic power station; According to the system parameters, respectively construct the instability-free conditions of the dominant oscillation modes of the grid-following photovoltaic units and the grid-forming photovoltaic units; According to the instability-free conditions of the dominant oscillation modes, respectively determine the capacity constraints of the grid-following photovoltaic units and the grid-forming photovoltaic units; According to the capacity constraints of the grid-following photovoltaic units and the grid-forming photovoltaic units, solve the grid-forming photovoltaic capacity optimization model to obtain the optimal capacity of the grid-forming photovoltaic units; The network-constructing type photovoltaic capacity optimization model is: minf = h f + c f ; Among them, h f is the frequency drop risk function; c f is the capacity penalty function of the network-forming photovoltaic unit; The frequency drop risk function is: where t end is the fault duration; Δf(t) is the frequency deviation; The grid-forming photovoltaic unit capacity penalty function is: Among them, E2 is the capacity of the network-forming photovoltaic unit; E limit is the capacity configuration limit value.

2. The grid-forming distributed photovoltaic capacity optimization method according to claim 1, wherein The instability-free condition of the dominant oscillation mode of the grid-following photovoltaic unit is that the effective short-circuit ratio of the grid-following photovoltaic unit is greater than the critical short-circuit ratio of the grid-following photovoltaic unit operating in parallel; 3. The network-constructing type distributed photovoltaic capacity optimization method according to claim 2, characterized in that, The calculation formula for the effective short-circuit ratio of the grid-following photovoltaic unit is: SCR1 = S ac / E1; Then, the capacity constraint of the grid-following photovoltaic unit is: Among them, SCR1 is the effective short-circuit ratio of the network-following PV unit; S ac is the short-circuit capacity at the point of common coupling; E1 is the capacity of the network-following PV unit; CSCR1 is the critical short-circuit ratio for the network-following PV unit to operate in parallel; CSCR2 is the critical short-circuit ratio for the network-forming PV unit to operate in parallel; E is the total capacity of the network-following PV unit and the network-forming PV unit.

4. The grid-forming distributed photovoltaic capacity optimization method according to claim 1, characterized in that The instability-free condition of the dominant oscillation mode of the grid-forming photovoltaic unit is that the effective short-circuit ratio of the grid-forming photovoltaic unit is less than the critical short-circuit ratio of the grid-forming photovoltaic unit operating in parallel; 5. The grid-forming distributed photovoltaic capacity optimization method according to claim 4, wherein The calculation formula for the effective short-circuit ratio of the grid-forming photovoltaic unit is: SCR2 = S ac / E2; Then, the capacity constraint of the grid-forming photovoltaic unit is: Among them, SCR2 is the effective short-circuit ratio of the grid-forming photovoltaic unit; S ac is the short-circuit capacity at the grid connection point; E2 is the capacity of the grid-forming photovoltaic unit; CSCR1 is the critical short-circuit ratio for the grid-following photovoltaic unit to operate in parallel; CSCR2 is the critical short-circuit ratio for the grid-forming photovoltaic unit to operate in parallel; E is the total capacity of the grid-following photovoltaic unit and the grid-forming photovoltaic unit.

6. A network-constructing distributed photovoltaic capacity optimization device, characterized in that, Including: An acquisition module, configured to obtain the system parameters of the grid-connected system of the photovoltaic power station; A construction module, configured to respectively construct the instability-free conditions of the dominant oscillation modes of the grid-following photovoltaic units and the grid-forming photovoltaic units according to the system parameters; A determination module, configured to respectively determine the capacity constraints of the grid-following photovoltaic units and the grid-forming photovoltaic units according to the instability-free conditions of the dominant oscillation modes; A calculation module, configured to solve the grid-forming photovoltaic capacity optimization model according to the capacity constraints of the grid-following photovoltaic units and the grid-forming photovoltaic units to obtain the optimal capacity of the grid-forming photovoltaic units; The grid-forming PV capacity optimization model is: minf = h f + c f ; Among them, h f is the frequency drop risk function; c f is the capacity penalty function of the grid-forming photovoltaic unit; The frequency drop risk function is: where t end is the fault duration; Δf(t) is the frequency deviation; The grid-forming photovoltaic unit capacity penalty function is: wherein, E2 is the capacity of the network-forming photovoltaic unit; E limit is the capacity configuration limit value.

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