A virtual synchronous generator adaptive control method and system for centralized photovoltaic power stations

Abstract

The present invention discloses a method and system for adaptively controlling a virtual synchronous generator (VSG) for a centralized photovoltaic power station. This method, based on VSG control, proposes an adaptive virtual inertia control strategy for centralized, grid-connected photovoltaic power stations. During frequency modulation, the photovoltaic power station adaptively adjusts the virtual moment of inertia based on actual grid frequency changes. Compared to traditional VSG control, this method increases or decreases the virtual moment of inertia at different stages of the dynamic grid frequency change process to reduce frequency overshoot and frequency change rate, accelerate frequency recovery, and improve the dynamic performance of the photovoltaic power station participating in primary frequency modulation.

Description

Technical Field

[0001] The present invention belongs to the technical field of grid-connected power generation in photovoltaic power stations, and in particular relates to a method and system for adaptively controlling a virtual synchronous generator for a centralized photovoltaic power station. Background Art

[0002] Because traditional photovoltaic power generation systems lack the inertia and damping of synchronous generators and typically operate in maximum power point tracking (MPPT) mode, they lack frequency regulation capabilities, leading to power fluctuations and frequency stability issues. In recent years, with the continuous increase in photovoltaic installed capacity, power grids have increasingly required photovoltaic power generation to actively participate in grid frequency regulation, providing active power support when the grid frequency fluctuates. Because inertia and frequency regulation support require additional active power, domestic and international research on photovoltaic power stations participating in grid frequency regulation primarily focuses on two methods: installing energy storage devices and providing active backup for photovoltaic units. However, due to the high cost and relatively short lifespan of energy storage equipment, the resulting energy coordination and stability issues remain largely unresolved.

[0003] Virtual synchronous generator (VSG) technology draws on the operating characteristics and control methods of traditional synchronous generators, simulating their external characteristics of moment of inertia and damping, enabling friendly grid connection. Photovoltaic power generation systems using VSG technology can control grid frequency and voltage. Therefore, some researchers have applied VSG technology to photovoltaic grid-connected inverters and proposed a photovoltaic virtual synchronous generator (PV-VSG) control strategy. This strategy operates the photovoltaic power generation system below its maximum power level, leaving a certain amount of active power reserve to enable frequency regulation and prevent DC bus voltage collapse. However, primary frequency regulation performance is affected by VSG control parameters, especially the value of the virtual moment of inertia, which significantly influences the frequency regulation dynamics. Related research in this area has used PV-VSG control based on active load shedding reserve to enable photovoltaic power generation systems to participate in grid frequency regulation. However, due to the fixed value of the virtual moment of inertia, the strategy suffers from large frequency overshoot and slow recovery. Summary of the Invention

[0004] In order to overcome the shortcomings of the above-mentioned prior art, the purpose of the present invention is to provide a virtual synchronous generator adaptive control method and system for a centralized photovoltaic power station, which can effectively solve the technical problems of large frequency overshoot and slow recovery speed caused by the fixed value of virtual rotational inertia.

[0005] In order to achieve the above object, the present invention adopts the following technical solutions:

[0006] The present invention discloses a virtual synchronous generator adaptive control method for a centralized photovoltaic power station, comprising the following steps:

[0007] Step 1: Obtain the maximum power point of each photovoltaic unit in the photovoltaic power station and set the photovoltaic unit to load-shed and standby operation to leave a frequency regulation margin;

[0008] Step 2: Obtain the grid frequency change rate and obtain the corresponding adaptive virtual moment of inertia based on the adaptive control function expression;

[0009] Step 3: Obtain the total frequency modulation power and add it to the total load shedding standby power of the power station at the current moment to obtain the total active output reference value of the PV power station;

[0010] Step 4: Distribute the total active power reference value of the photovoltaic power station obtained in step 3 to each photovoltaic unit in the station, and control each photovoltaic inverter to output the corresponding active power to complete the adaptive control.

[0011] Preferably, in step 1, the maximum power of each photovoltaic unit in the station is obtained by using a particle swarm algorithm, so that the photovoltaic unit is loaded down and operates at 10% of the maximum power.

[0012] Further preferably, the particle swarm algorithm includes:

[0013] First, the initial voltage and step size of each particle are initialized, and the output power of the photovoltaic array is calculated accordingly. The local optimal and global optimal powers of the particles are obtained by comparison.

[0014] Next, the particle step size and voltage are updated, the output power corresponding to each particle voltage is calculated again, and it is determined whether the number of iterations is met. If so, the algorithm ends and the optimal voltage and corresponding output power are output; if not, the algorithm enters the next iterative update until the end condition is met.

[0015] Preferably, in step 2, the grid frequency change rate df / dt is obtained, and the adaptive control function expression of the adaptive virtual moment of inertia J is:

[0016]

[0017] Where J0 is the steady-state value of the virtual inertia; α1 and α2 are the adaptive inertia coefficients; M is the frequency change rate threshold, which is used to avoid frequent changes in the J value caused by frequency fluctuations within a small range; Δf is the difference between the system frequency and the rated frequency.

[0018] Further preferably, J0 is selected according to the method of fixed virtual inertia; the values ​​of α1 and α2 should be determined comprehensively according to the system performance adjustment needs and actual conditions, while ensuring that the J value is within (0, J max ) varies within the range of J max Adjust according to the following formula:

[0019]

[0020] Where, P max The upper limit of the inverter output active power.

[0021] Preferably, in step 3, the total active power reference value of the photovoltaic power station is for:

[0022]

[0023] Where ΔP refs =P inertia +P droop , P inertia is the power simulating the generator rotor inertia, P droop is the power of the simulated generator speed regulator, P ref0 is the initial active power output of the inverter.

[0024] Preferably, in step 4, the active power distribution strategy for distributing the total active power reference value of the photovoltaic power station to each photovoltaic unit in the station is based on the principle of adjustable capacity ratio. According to the constraint of equal adjustable capacity ratio, the power adjustment command of the i-th photovoltaic unit is expressed as:

[0025]

[0026] Where, P zs is the total active power output of the photovoltaic power station before the load disturbance, ΔP s is the total active power change after the disturbance, P maxs is the sum of the maximum power of each photovoltaic unit; P zi is the active power output of the ith photovoltaic unit before the load disturbance, ΔP i is the change in active power borne by the i-th photovoltaic unit after the disturbance.

[0027] Preferably, in step 4, a PQ control strategy is adopted to control the active power outputted by each photovoltaic inverter.

[0028] The present invention also discloses a system for implementing the above-mentioned virtual synchronous generator adaptive control method for a centralized photovoltaic power station, comprising:

[0029] The maximum power point acquisition module is used to obtain the maximum power point of each photovoltaic unit in the photovoltaic power station and enable the photovoltaic unit to reduce load and operate in standby mode to leave a frequency regulation margin;

[0030] The adaptive virtual moment of inertia acquisition module is used to obtain the grid frequency change rate and obtain the virtual moment of inertia corresponding to the grid frequency change rate according to the proposed adaptive control function expression;

[0031] A total active power reference value acquisition module is used to obtain the total active power reference value of the photovoltaic power station by adding the total frequency modulation power obtained and the current output power;

[0032] The active power distribution control module is used to distribute the total active power reference value of the photovoltaic power station to each photovoltaic unit in the station, and control each photovoltaic inverter to output the corresponding active power to complete adaptive control.

[0033] Compared with the prior art, the present invention has the following beneficial effects:

[0034] The present invention discloses an adaptive control method for a virtual synchronous generator for a centralized photovoltaic power station. First, the maximum power of each photovoltaic unit in the station is obtained, and the photovoltaic units are allowed to operate in load-shedding standby mode with a frequency regulation margin. Then, the grid frequency change rate is obtained, and the corresponding virtual moment of inertia is obtained according to the adaptive control process. Then, the total frequency regulation power is obtained and added to the total load-shedding standby power of the current power station to obtain the total active power reference value of the photovoltaic power station. Finally, the total active power reference value is distributed to each photovoltaic unit in the station, and each photovoltaic inverter is controlled to output the corresponding active power. Although existing research on photovoltaic virtual synchronous generator control has achieved a primary frequency regulation function, the control parameters used are mostly fixed values, which cannot take into account the frequency overshoot and recovery speed issues. This patent proposes an adaptive virtual inertia control, which adaptively changes the value of the virtual inertia according to the change of frequency during the frequency regulation process, thereby reducing the frequency overshoot while accelerating the frequency recovery speed. The method of the present invention is based on VSG control. During the frequency modulation process, the photovoltaic power station adaptively adjusts the virtual moment of inertia according to the actual grid frequency changes. Compared with traditional VSG control, this method increases or decreases the virtual moment of inertia at different stages of the dynamic change process of the grid frequency to reduce frequency overshoot and change rate, accelerate the frequency recovery speed, and improve the dynamic performance of the photovoltaic power station participating in primary frequency modulation.

[0035] Furthermore, the present application proposes for the first time an adaptive variation expression of the virtual moment of inertia parameter during the frequency modulation process.

[0036] Furthermore, to further enhance frequency regulation, a particle swarm algorithm is used for maximum power point tracking (MPP) on individual PV units. This accurately locates the global MPP when the PV array is partially shaded, enhancing the plant's participation in primary frequency regulation. Furthermore, a method based on equal adjustable capacity ratios is used to distribute the active power output of each generator within the plant. This ensures that all PV units within the plant have the same frequency regulation power margin when participating in frequency regulation, preventing over-regulation of some units. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 This is the main circuit structure of PV-VSG;

[0038] Figure 2 It is the flow chart of particle swarm optimization MPPT algorithm;

[0039] Figure 3 This is a schematic diagram of load shedding standby control for photovoltaic units;

[0040] Figure 4 It is a dynamic process of grid frequency change after power fluctuation caused by sudden load increase;

[0041] Figure 5 This is the PV-VSG control block diagram;

[0042] Figure 6 It is a 10MW photovoltaic power station simulation model;

[0043] Figure 7 is the system frequency response under different control strategies. DETAILED DESCRIPTION

[0044] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0045] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate, so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0046] The present invention is described in further detail below with reference to the accompanying drawings:

[0047] The present invention provides a virtual synchronous generator adaptive control method for a centralized photovoltaic power station. The purpose is to enable the photovoltaic power station to retain a certain amount of active power reserve to participate in the primary frequency regulation of the power grid, and to improve the frequency regulation performance of the centralized photovoltaic power station by combining virtual inertia adaptive VSG control.

[0048] The main circuit structure of the PV-VSG studied is as follows Figure 1 As shown, a single-stage topology is employed, consisting of a photovoltaic array, a three-phase full-bridge inverter, and an LCL filter. The control system employs the strategy proposed in this invention, generating switching signals through SPWM to control the inverter's output reference voltage, which is then fed through a filter into the AC bus.

[0049] The specific steps of the present invention are as follows:

[0050] Step 1: Obtain the maximum power point of each photovoltaic unit in the station and reduce the load for standby operation.

[0051] First, we use the particle swarm optimization algorithm to implement the maximum power point tracking (MPPT) of the photovoltaic array, which is particularly suitable for partial shadow conditions. The core formula of the algorithm is:

[0052]

[0053] Where k is the number of iterations; i = 1, 2, ..., n, n is the number of particles; are the velocity and position of the i-th particle in the k-th iteration respectively; c1 and c2 are the individual and group learning factors respectively; r1 and r2 are random numbers distributed in the range of (0, 1); is the individual optimal value of the i-th particle at the current moment; is the optimal value found at the current moment in the particle swarm search history; ω is the inertia weight, and ω0 is the initial weight. The adaptive inertia weight is used here mainly to balance the global search and local search capabilities:

[0054] Assuming that the goal of particle swarm optimization is to find the global maximum value, and f is the fitness value that measures the quality of the particle position, then P best and G best The update method is:

[0055]

[0056] When the particle swarm algorithm is applied to photovoltaic MPPT, the particle position corresponds to the DC output voltage of the photovoltaic array, the particle fitness corresponds to the output active power of the photovoltaic array, and the speed corresponds to the voltage step size. This algorithm first initializes the initial voltage and step size of each particle, and calculates the output power of the photovoltaic array accordingly, and compares the local optimal and global optimal powers of the particles. Then, the particle step size and voltage are updated, the output power corresponding to the voltage of each particle is calculated again, and it is determined whether the end condition (usually the number of iterations) is met. If it is met, the algorithm ends and the optimal voltage and corresponding output power are output; if not, it enters the next iterative update until the end condition is met. The algorithm flow chart is as follows Figure 2 shown.

[0057] Load shedding standby control means that after finding the maximum power point of the photovoltaic array, the photovoltaic output voltage is further controlled to operate below the maximum power point, thereby reserving a certain amount of active power so that the photovoltaic unit has the ability to participate in system frequency regulation. Figure 3 This is a schematic diagram of load shedding standby control for a PV generator. Relevant research indicates that the stable operating region for a PV generator is Region 2, meaning that the actual operating voltage of the PV array should be higher than the maximum power point voltage. The detailed principles are omitted here. Load shedding standby control employs a classic hill climbing method, whereby the PV output voltage is incrementally increased until the output power reaches the standby power point by comparing it with the previous PV output power. Regarding the initial load shedding rate, considering curtailment and frequency regulation requirements, a reserve of 10% to 20% of maximum power is generally chosen in engineering practice to achieve a relatively economical level.

[0058] Step 2: Obtain the grid frequency change rate and obtain the corresponding virtual moment of inertia based on the adaptive control process.

[0059] Figure 4 This is the dynamic process of grid frequency change after power fluctuation caused by a sudden increase in load. The entire process can be divided into two intervals: t0~t1 and t1~t2 (interval numbers are 1 and 2 respectively). According to the different corresponding relationships between the frequency change rate and frequency deviation in each interval, the regulation rules of the virtual moment of inertia can be obtained through analysis as shown in Table 1:

[0060] Table 1 Adjustment rules of virtual moment of inertia

[0061]

[0062] Considering the change characteristics of the control target and the exponential function, the quadratic function of the frequency change rate is introduced to establish the adaptive function expression of the virtual moment of inertia:

[0063]

[0064] Where J0 is the steady-state value of virtual inertia; α1 and α2 are the adaptive inertia coefficients; and M is the frequency change rate threshold to avoid frequent changes in the J value caused by frequency fluctuations in a small range.

[0065] Regarding the parameters in the formula, J0 can be selected according to the method of fixed virtual inertia; the values ​​of α1 and α2 should be determined comprehensively according to the system performance adjustment needs and actual conditions, while ensuring that the J value is within (0, J max ) varies within the range. max Adjustment can be performed according to the following formula:

[0066]

[0067] Where, P maxThe upper limit of the inverter output active power.

[0068] Step 3: Obtain the total frequency modulation power and add it to the current output power to obtain the total active power reference value of the PV power station.

[0069] According to VSG related theory, in order to simulate the rotor inertia, VSG provides the power P of the virtual moment of inertia inertia It can be expressed as:

[0070]

[0071] To simulate the speed regulator, VSG is used for the power P of primary frequency regulation. droop Expressed as:

[0072]

[0073] Where m represents the droop coefficient of the synchronous generator active power.

[0074] The present invention takes electromagnetic power as the control target, adds inertia and primary frequency modulation power support, and the active power instruction output by the photovoltaic power station for:

[0075] Where ΔP refs =P inertia +P droop , P ref0 is the initial active power output.

[0076] Step 4: Distribute the total active power reference value to each photovoltaic unit in the station and control each photovoltaic inverter to output the corresponding active power.

[0077] In the frequency regulation mode, the present invention adopts an active power allocation strategy with an equal adjustable capacity ratio considering the standby power. According to the constraint of the equal adjustable capacity ratio, the power adjustment command of the i-th photovoltaic unit can be expressed as:

[0078]

[0079] Where, P zs is the total active power output of the photovoltaic power station before the load disturbance, ΔP s is the total active power change after the disturbance, P maxs is the sum of the maximum power of each photovoltaic unit; P zi is the active power output of the ith photovoltaic unit before the load disturbance, ΔP i is the change in active power borne by the i-th photovoltaic unit after the disturbance.

[0080] The adaptive VSG control block diagram proposed by the present invention is as follows: Figure 5As shown, a particle swarm optimization algorithm is first used to determine the maximum power point voltage of each photovoltaic array. The photovoltaic output voltage is then increased to find the active power reserve point, or load shedding standby operation. Next, adaptive virtual inertia-based VSG control is combined with grid frequency change rate calculation to determine the frequency-modulated power. This frequency-modulated power is superimposed on the active power reserve point to generate the grid-connected active power command for the photovoltaic power station. After the active power distribution process, the active power reference value for each photovoltaic unit is obtained. The corresponding DC voltage at this point becomes the reference signal for the voltage outer loop. Figure 5 In, P ref and Q ref are the active power and reactive power instructions of the inverter respectively. When grid voltage oriented control is adopted, the grid voltage q-axis component u q =0, the active and reactive current instructions of the current inner loop are:

[0081]

[0082] The control equation of the current inner loop is:

[0083]

[0084] Where u d 、u q is the output voltage, i d,qref 、i d,q are the reference value and actual value of d-axis and q-axis current respectively.

[0085] The following describes a specific embodiment of the present invention to illustrate the control effect of a photovoltaic power station participating in the primary frequency modulation of the power grid. In this embodiment, the relevant parameters are set as follows: Figure 6 This is a simulation model of a photovoltaic power station with a rated capacity of 10MW, consisting of five photovoltaic power generation units with a capacity of 2MW. In the figure, PV1 to PV5 are photovoltaic arrays, T1 to T5 are station-based step-up transformers, and Zg is the transmission line impedance connecting the power station to the grid. The grid is simulated by a steam turbine synchronous generator with an AC side rated voltage of 0.27kV and a transformer ratio of 0.27 / 10kV. A sudden load increase is set to simulate the operating scenario of active power fluctuation. The operating effect of the proposed control strategy is verified by comparing it with VSG control that does not participate in frequency regulation and has fixed virtual inertia. The values ​​of the adaptive virtual inertia control parameters are shown in Table 2 below:

[0086] Table 2 Adaptive virtual inertia control parameters

[0087]

[0088] At t = 0s, the load is rated. At t = 20s, the load suddenly increases by 1.415MW (5% load disturbance). The photovoltaic power station does not participate in frequency regulation and uses a fixed virtual inertia (J = 180kg·m 2 and J = 360 kg·m2 ) and the proposed system frequency response results under the adaptive virtual inertia condition are shown in Figure 7 As shown in the figure, when the photovoltaic power station does not participate in frequency regulation, the system frequency change rate, frequency overshoot and steady-state deviation are all large; when the unit adopts J=180kg·m 2 When the fixed virtual inertia control is used, the system frequency recovery speed is faster due to the low virtual inertia, but the overshoot is larger. 2 When using fixed virtual inertia control, the system frequency overshoot is small due to the high virtual inertia, but the recovery speed is slow. The proposed adaptive virtual inertia control reduces frequency overshoot compared to low-inertia systems and speeds up frequency recovery compared to high-inertia systems. This effectively combines the advantages of both, effectively improving the dynamic characteristics of primary frequency regulation and thus enhancing the frequency stability of the power grid.

[0089] In summary, PV power stations participating in grid primary frequency regulation in an active standby mode can fully utilize PV's own resources, reduce the design capacity of the power station's energy storage devices, and thus reduce construction and operating costs. Adaptively optimizing the value of virtual inertia during the frequency regulation process can further improve the dynamic performance of PV participation in grid frequency regulation. Based on VSG control, the present invention enables PV power stations to adaptively adjust virtual rotational inertia according to actual grid frequency changes during the frequency regulation process. Compared to traditional VSG control, the virtual rotational inertia is increased or decreased at different stages of the dynamic change process of the grid frequency to reduce frequency overshoot and change rate, accelerate frequency recovery, and improve the dynamic performance of PV power stations participating in primary frequency regulation.

[0090] The above content is only for explaining the technical idea of ​​the present invention and cannot be used to limit the protection scope of the present invention. Any changes made on the basis of the technical solution in accordance with the technical idea proposed by the present invention shall fall within the protection scope of the claims of the present invention.

Claims

1. A virtual synchronous generator adaptive control method for a centralized photovoltaic power station, characterized in that: The following steps are involved: Step 1: Obtain the maximum power point of each photovoltaic unit in the photovoltaic power station and set the photovoltaic unit to load-shed and standby operation to leave a frequency regulation margin; Step 2: Obtain the grid frequency change rate and obtain the corresponding adaptive virtual moment of inertia according to the adaptive control function expression; wherein, obtain the grid frequency change rate , adaptive virtual moment of inertia The adaptive control function expression is: Where, is the steady-state value of virtual inertia; and is the adaptive inertia coefficient; The frequency change rate threshold is used to avoid frequency fluctuations within a small range. Frequent changes in value, is the difference between the system frequency and the rated frequency; Step 3: Obtain the total frequency modulation power and add it to the total load shedding standby power of the power station at the current moment to obtain the total active output reference value of the PV power station; Step 4: Distribute the total active power reference value of the photovoltaic power station obtained in step 3 to each photovoltaic unit in the station, and control each photovoltaic inverter to output the corresponding active power to complete the adaptive control.

2. The method for adaptive control of a virtual synchronous generator for a centralized photovoltaic power station according to claim 1, characterized in that: In step 1, the maximum power of each photovoltaic unit in the station is obtained through the particle swarm algorithm, so that the photovoltaic unit can reduce the load and operate at 10% of the maximum power.

3. The method for adaptive control of a virtual synchronous generator for a centralized photovoltaic power station according to claim 2, characterized in that: The particle swarm algorithm includes: First, the initial voltage and step size of each particle are initialized, and the output power of the photovoltaic array is calculated accordingly. The local optimal and global optimal powers of the particles are obtained by comparison. Next, the particle step size and voltage are updated, the output power corresponding to each particle voltage is calculated again, and it is determined whether the number of iterations is met. If so, the algorithm ends and the optimal voltage and corresponding output power are output; if not, the algorithm enters the next iterative update until the end condition is met.

4. The method for adaptive control of a virtual synchronous generator for a centralized photovoltaic power station according to claim 1, characterized in that: Select according to the method of fixed virtual inertia; 、 The value of should be determined comprehensively according to the system performance adjustment needs and actual conditions, while ensuring Value in (0, ) varies within the range, Adjust according to the following formula: Where, The upper limit of the inverter output active power.

5. The method for adaptive control of a virtual synchronous generator for a centralized photovoltaic power station according to claim 1, characterized in that: In step 3, the total active power reference value of the photovoltaic power station for: Where, , is the power simulating the generator rotor inertia, To simulate the power of the generator speed regulator, is the initial active power output of the inverter.

6. The method for adaptive control of a virtual synchronous generator for a centralized photovoltaic power station according to claim 1, characterized in that: In step 4, the active power distribution strategy of allocating the total active power reference value of the photovoltaic power station to each photovoltaic unit in the station is based on the principle of adjustable capacity ratio. According to the constraint of equal adjustable capacity ratio, the first i The power adjustment command of each photovoltaic unit is expressed as: Where, is the total active power output of the photovoltaic power station before the load disturbance, is the total active power change after the disturbance, is the sum of the maximum power of each photovoltaic unit; The first i The active power output of each photovoltaic unit, After the disturbance i The change in active power borne by each photovoltaic unit.

7. The method for adaptive control of a virtual synchronous generator for a centralized photovoltaic power station according to claim 1, characterized in that: In step 4, the PQ control strategy is used to control the active power output of each photovoltaic inverter.

8. A system for implementing the adaptive control method of a virtual synchronous generator for a centralized photovoltaic power station according to any one of claims 1 to 7, characterized in that: include: The maximum power point acquisition module is used to obtain the maximum power point of each photovoltaic unit in the photovoltaic power station and enable the photovoltaic unit to reduce load and operate in standby mode to leave a frequency regulation margin; The adaptive virtual moment of inertia acquisition module is used to obtain the grid frequency change rate and obtain the virtual moment of inertia corresponding to the grid frequency change rate according to the proposed adaptive control function expression; A total active power reference value acquisition module is used to obtain the total active power reference value of the photovoltaic power station by adding the total frequency modulation power obtained and the current output power; The active power distribution control module is used to distribute the total active power reference value of the photovoltaic power station to each photovoltaic unit in the station, and control each photovoltaic inverter to output the corresponding active power to complete adaptive control.

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