Photovoltaic power station frequency modulation control method, system and device considering frequency partition and power constraint and medium

Abstract

The invention discloses a photovoltaic power station frequency modulation control method, system and device considering frequency partition and power constraint and a medium, and belongs to the technical field of power system automation control, and the method comprises the steps: monitoring the frequency deviation and frequency change rate of a power grid; dividing the frequency modulation process into a frequency drop stage and a frequency recovery stage; performing differential adaptive adjustment on the virtual inertia control parameter and the virtual droop control parameter of the photovoltaic power station; dynamically constraining a frequency modulation power instruction calculated based on the adjusted parameters according to the real-time available power capability of the photovoltaic power station; actions of the photovoltaic power station are controlled, and power grid frequency recovery is supported. According to the method, the control stages are adaptively divided according to the frequency dynamic process, and the virtual inertia and the droop coefficient are differentially adjusted, so that accurate matching of the control strategy and the frequency change process is realized, and the frequency modulation performance is optimized in two aspects of suppressing frequency drop and guaranteeing stable recovery.

Description

Technical Field

[0001] This invention relates to the field of power system automation control technology, specifically to a method, system, equipment, and medium for frequency regulation control of photovoltaic power plants that considers frequency zoning and power constraints. Background Technology

[0002] Driven by the "dual-carbon" strategic goals, the penetration rate of new energy power generation, represented by wind power and photovoltaics, in the power system has continued to increase rapidly. However, the large-scale replacement of traditional synchronous generator units with rotational inertia by a high proportion of new energy sources connected to the grid through power electronic inverters has led to a significant decrease in the equivalent inertia of the power system and a severe weakening of the system's frequency regulation capability. When power disturbances occur, the dynamic process of the system frequency deteriorates.

[0003] Therefore, how to effectively tap the frequency regulation potential of new resources such as photovoltaics and energy storage, and enable them to participate in system frequency support quickly and safely, has become a key technical challenge to ensure the safe and stable operation of new power systems.

[0004] Currently, the main technical approach to enabling new energy power plants to participate in frequency regulation is to equip their converters with virtual inertial control and virtual droop control. Virtual droop control, by simulating the speed regulation characteristics of a synchronous generator, linearly adjusts the output power according to the frequency deviation, offering the advantage of good steady-state regulation. However, its fixed droop coefficient makes it difficult to adapt to the complex operating conditions caused by fluctuations in wind and solar power output. Virtual inertial control, by introducing frequency change rate feedback, can quickly provide power support to suppress the rate of frequency change, but its fixed inertial coefficient is prone to causing system overshoot or oscillation. To combine the advantages of both, existing research has proposed a synergistic strategy of virtual inertial control and droop control, and has attempted to switch control modes in different frequency ranges.

[0005] However, existing technical solutions still have the following prominent limitations: First, most solutions use constant values ​​for the frequency regulation coefficients (such as droop coefficient and inertia coefficient) or only involve simple switching, failing to fully consider the dynamic differences in power support requirements at different stages of the entire dynamic process from frequency drop to recovery. Especially during the frequency recovery period, inertial control may generate reverse power, which is detrimental to frequency stability. Second, existing solutions mostly focus on the control algorithm itself, treating the actual adjustable power capability of the frequency regulation unit (such as photovoltaic power limited by irradiance and temperature, and energy storage power limited by state of charge) as a static boundary or considering it separately. This fails to deeply couple the power constraints with the adaptive adjustment process of control parameters in the dynamic frequency process. This leads to situations where, under complex operating conditions, control commands may exceed the actual capabilities of the equipment, or the frequency regulation potential may not be fully utilized, making it difficult to achieve optimal frequency regulation while ensuring equipment safety. Summary of the Invention

[0006] In view of the above-mentioned problems, the present invention is proposed.

[0007] Therefore, the technical problem solved by this invention is: how to perform fine-grained partitioning based on the dynamic recovery process of the power grid frequency, and adaptively adjust the control parameters in different partitions, while taking into account the actual power regulation capability of the photovoltaic power station in real time to impose command constraints, so as to achieve fast, stable and efficient coordinated recovery of the power grid frequency while ensuring the safe operation of the frequency regulation equipment.

[0008] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a photovoltaic power plant frequency regulation control method considering frequency zoning and power constraints, comprising, Monitor the frequency deviation and rate of frequency change of the power grid; Based on the dynamic process of frequency deviation and frequency change rate, the frequency modulation process is divided into the frequency drop stage and the frequency recovery stage. During the frequency drop and frequency recovery phases, the virtual inertial control parameters and virtual droop control parameters of the photovoltaic power station are adjusted in a differentiated and adaptive manner. Based on the real-time available power capacity of the photovoltaic power station, the frequency regulation power command calculated based on the adjusted parameters is dynamically constrained. The operation of the photovoltaic power station is controlled according to the constrained power command to support the restoration of the grid frequency.

[0009] As a preferred embodiment of the photovoltaic power plant frequency regulation control method considering frequency zoning and power constraints described in this invention, wherein: the monitoring of the grid frequency deviation and frequency change rate includes, Real-time acquisition of power grid frequency operation status information; The operating status information is processed to extract feature information that characterizes the dynamic changes in frequency; Based on operational status information and changing trends, a basis for determining phase division and parameter adjustment is established.

[0010] As a preferred embodiment of the photovoltaic power plant frequency regulation control method considering frequency zoning and power constraints described in this invention, the step of dividing the frequency regulation process into a frequency drop phase and a frequency recovery phase based on the dynamic process of frequency deviation and frequency change rate includes, Establish the activation conditions for triggering frequency modulation actions; Based on the system dynamic behavior reflected by the characteristic information, the continuous frequency modulation process is analyzed into different time stages; Set corresponding control objectives and control strategy sets for each time period.

[0011] As a preferred embodiment of the photovoltaic power plant frequency regulation control method considering frequency zoning and power constraints described in this invention, the step of differentially and adaptively adjusting the virtual inertial control parameters and virtual droop control parameters of the photovoltaic power plant during the frequency drop phase and frequency recovery phase includes: Based on the control objectives corresponding to the time stage, corresponding adjustment strategies are determined for the virtual inertial control parameters and the virtual droop control parameters, respectively. Based on the real-time values ​​of operating status information and changing trends, an adjustment strategy is executed to determine the specific adjustment amount of each control parameter; The parameters of the corresponding control loop are updated based on the adjustment amount, and a preliminary power command for frequency regulation is generated accordingly.

[0012] This invention achieves precise matching between the control strategy and the frequency dynamic process by adaptively adjusting the virtual inertial control parameters and virtual droop control parameters in a differentiated manner according to the different control objectives of the frequency drop phase and the frequency recovery phase.

[0013] During the frequency drop phase, two types of parameters are adjusted collaboratively. Inertial control is used to quickly suppress the rate of frequency change, while droop control is used to reduce steady-state deviation. During the frequency recovery phase, the droop parameter is mainly adjusted and inertial control is stopped, effectively avoiding the adverse effects of the reverse output of inertial power during the recovery period on the system frequency recovery. This overcomes the shortcomings of fixed coefficients or rigid switching strategies in traditional control, enabling photovoltaic power plants to dynamically adapt to the real-time needs of system frequency regulation, and improving the response speed and control accuracy of frequency regulation.

[0014] As a preferred embodiment of the photovoltaic power plant frequency regulation control method considering frequency zoning and power constraints described in this invention, the step of dynamically constraining the frequency regulation power command calculated based on the adjusted parameters according to the real-time available power capacity of the photovoltaic power plant includes... Assess the maximum adjustable power range of photovoltaic power plants and energy storage under current environmental and operating conditions; The initial power command is compared with the maximum adjustable power range, and the command components that exceed the range are adaptively corrected. Based on the corrected results, the target power command that the photovoltaic power station can actually execute is output.

[0015] As a preferred embodiment of the photovoltaic power plant frequency regulation control method considering frequency zoning and power constraints described in this invention, wherein: controlling the operation of the photovoltaic power plant according to the constrained power command to support grid frequency recovery includes, The operating status information is processed to extract feature information that characterizes the dynamic changes in frequency; The target power command is converted into executable operation commands for each controllable unit within the photovoltaic power plant; Based on executable operation instructions, the power output device of the controllable unit is driven to output the actual power corresponding to the instructions; Based on the actual response of the power grid frequency, assess the frequency regulation effect and decide whether to start a new frequency regulation control cycle.

[0016] As a preferred embodiment of the photovoltaic power plant frequency regulation control method considering frequency zoning and power constraints described in this invention, the differentiated adaptive adjustment of the virtual inertial control parameters and virtual droop control parameters of the photovoltaic power plant includes determining corresponding adjustment strategies for the virtual inertial control parameters and virtual droop control parameters respectively. For virtual droop control parameters, during the frequency drop phase and frequency recovery phase, if the absolute value of the frequency deviation is greater than the preset dead zone threshold, the adjustment amount is positively correlated with the absolute value of the frequency deviation. For virtual inertial control parameters, during the frequency drop phase, the adjustment process is divided into at least two sub-phases based on the trend of the frequency change rate, and different adjustment functions are used in different sub-phases so that the virtual inertial control parameters achieve a peak value when the frequency deviation reaches an extreme value.

[0017] This invention achieves refined and optimized control of inertial power by dividing the adjustment process of inertial control parameters during the frequency drop phase into two sub-stages based on the changing trend of the frequency change rate and employing different adjustment functions. This enables inertial control to rapidly provide strong power support in the early stages of frequency drop to curb the frequency drop trend; and before the frequency drops to its lowest point, the inertial control parameters are designed to reach their peak values ​​in a timely manner, thereby providing maximum support at critical moments.

[0018] This phased and refined adjustment strategy solves the problems of overshoot or insufficient response caused by fixed inertia coefficients, as well as the harmful power generated by traditional inertial control during the frequency recovery phase. It taps into and safely utilizes the potential of inertial control, making the transient process of system frequency more stable, the recovery speed faster, and the overall frequency regulation performance fundamentally improved.

[0019] This invention provides a frequency regulation control system for photovoltaic power plants that takes into account frequency zoning and power constraints.

[0020] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a photovoltaic power plant frequency regulation control system considering frequency zoning and power constraints, comprising: a data collection module, a stage division module, an adjustment module, a calculation module, and an output command module; The data collection module monitors the frequency deviation and frequency change rate of the power grid. The segmentation module divides the frequency modulation process into a frequency drop phase and a frequency recovery phase based on the dynamic process of frequency deviation and frequency change rate. The adjustment module performs differentiated adaptive adjustments to the virtual inertial control parameters and virtual droop control parameters of the photovoltaic power station during the frequency drop and frequency recovery phases. The calculation module dynamically constrains the frequency modulation power command calculated based on the adjusted parameters, according to the real-time available power capacity of the photovoltaic power station. The output command module controls the operation of the photovoltaic power station based on the constrained power command, supporting the restoration of the grid frequency.

[0021] The present invention provides a computer device, including a memory and a processor, wherein the memory stores a computer program, characterized in that the processor executes the computer program to implement the steps of the photovoltaic power plant frequency regulation control method considering frequency zoning and power constraints.

[0022] The present invention provides a computer-readable storage medium having a computer program stored thereon, characterized in that, when the computer program is executed by a processor, it implements the steps of a photovoltaic power plant frequency regulation control method considering frequency zoning and power constraints.

[0023] The beneficial effects of the present invention are as follows: By adaptively dividing the control stages according to the frequency dynamic process and differentially adjusting the virtual inertia and droop coefficient, the present invention achieves precise matching between the control strategy and the frequency change process, thereby optimizing the frequency modulation performance in terms of both suppressing frequency drops and ensuring smooth recovery.

[0024] By making refined, phased adjustments to inertial control based on frequency variation trends, the inertial power support can reach its optimal level at critical moments, fundamentally avoiding the harmful output problem of traditional inertial control during the recovery period.

[0025] By coupling the parameter adjustment process with the real-time power capacity of the photovoltaic power station, it is ensured that all frequency regulation commands are executed within the safe range of the equipment, thus achieving a balance between frequency regulation efficiency and equipment safety. Attached Figure Description

[0026] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1The above is a general flowchart of a photovoltaic power plant frequency regulation control method considering frequency zoning and power constraints, provided as an embodiment of the present invention.

[0028] Figure 2 The diagram shows the frequency and frequency regulation power variation of a photovoltaic power plant frequency regulation control method considering frequency zoning and power constraints, as provided in one embodiment of the present invention.

[0029] Figure 3 This is a diagram illustrating the frequency and its first / second derivative partitioning recovery mechanism of a photovoltaic power plant frequency regulation control method considering frequency partitioning and power constraints, provided as an embodiment of the present invention.

[0030] Figure 4 The diagram shows a system frequency response model of a photovoltaic power plant frequency regulation control method considering frequency zoning and power constraints, provided as an embodiment of the present invention.

[0031] Figure 5 The diagram shows a comparison between the frequency regulation control method of this patented invention, which considers frequency zoning and power constraints, and a method without photovoltaic frequency regulation, provided as an embodiment of the present invention.

[0032] Figure 6 An embodiment of the present invention provides an adaptive variation of the frequency regulation coefficient and output power curve of a photovoltaic and energy storage power station frequency regulation control method that considers frequency zoning and power constraints.

[0033] Figure 7 This invention provides a frequency regulation power diagram of a photovoltaic power plant before and after correction based on actual frequency regulation capability constraints, which is a frequency regulation control method for photovoltaic power plants considering frequency zoning and power constraints, according to an embodiment of the present invention.

[0034] Figure 8 This invention provides a frequency regulation power diagram of an energy storage power station before and after correction based on actual frequency regulation capability constraints, which is a frequency regulation control method for photovoltaic power plants considering frequency zoning and power constraints, according to an embodiment of the present invention. Detailed Implementation

[0035] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of the present invention.

[0036] Example 1, referring to Figure 1 As one embodiment of the present invention, this embodiment provides a frequency regulation control method for photovoltaic power plants considering frequency zoning and power constraints, comprising: Traditional frequency regulation control methods for photovoltaic power plants typically have two main limitations: Firstly, the frequency modulation coefficients (such as virtual droop coefficient and inertia coefficient) are mostly preset fixed values, or can only switch between limited states. They cannot accurately adapt to the different requirements of power support speed and steady state at different stages of the entire dynamic process from frequency drop to recovery, making it difficult to achieve optimal control performance.

[0037] Secondly, the design of the control algorithm is disconnected from the real-time adjustable power capability of the frequency modulation unit (photovoltaic, energy storage). The calculated power command may exceed the safety limit of the equipment under the current operating conditions, or fail to fully utilize its frequency modulation potential, resulting in equipment risks and resource waste.

[0038] To address the aforementioned issues, this embodiment provides a frequency regulation control method for photovoltaic power plants that considers frequency zoning and power constraints. This method abandons the fixed-coefficient approach, achieving differentiated adaptive adjustment of control parameters by real-time sensing of frequency dynamics and dividing the control into stages. Simultaneously, power constraints are deeply embedded in the control closed loop to ensure the feasibility and security of commands.

[0039] S1. Monitor the frequency deviation and frequency change rate of the power grid; S2. Based on the dynamic process of frequency deviation and frequency change rate, the frequency modulation process is divided into the frequency drop stage and the frequency recovery stage. S3. During the frequency drop and frequency recovery phases, the virtual inertial control parameters and virtual droop control parameters of the photovoltaic power station are adjusted in a differentiated adaptive manner. S4. Based on the real-time available power capacity of the photovoltaic power station, dynamically constrain the frequency regulation power command calculated based on the adjusted parameters; S5. Control the operation of the photovoltaic power station according to the constrained power command to support the restoration of grid frequency.

[0040] Example 2, an embodiment of the present invention, provides a photovoltaic power plant frequency regulation control method considering frequency zoning and power constraints based on the previous embodiment, including: S1. Monitoring the frequency deviation and frequency change rate of the power grid includes the following steps: S11. Real-time acquisition of power disturbance and frequency operation status information of the power grid.

[0041] The actual frequency value of the power grid is acquired in real time by sensors and a measurement system, and then compared with the rated frequency standard value to obtain the power grid frequency deviation, which describes the degree of deviation of the system frequency. This deviation is the core input for all subsequent analysis and control in this invention.

[0042] Collect the time constants TCH, TG, and TRH of the turbine, governor, and reheater of the power grid thermal power unit; the reheater gain coefficient FHP of the thermal power unit; the droop coefficient Kgen of the thermal power unit; and the frequency response time constant of the photovoltaic and energy storage units. and .

[0043] This invention divides the dynamic frequency change process into two regions: region 1 is defined as the frequency dropping from a steady state to its lowest point, and region 2 is defined as the frequency recovering from its lowest point to a steady state. Then, it analyzes the rate of change of frequency deviation at the initial moment of the disturbance. and steady-state frequency deviation This determines that region 1 uses a combined inertial and droop control mode, while region 2 uses only a droop control mode.

[0044] like Figure 2 As shown, at time t0, the system is subjected to a positive power disturbance, and the frequency dynamic process exhibits the characteristics of first dropping and then rising. This invention divides it into region 1 and region 2.

[0045] Depend on Figure 2 (a) It can be seen that the frequency drops to its lowest point at time t1, from Figure 2 (b) It can be seen that the droop power reaches its maximum value at this time. Since the frequency change rate is 0 at this time, the inertial power is 0, and only the droop control participates in the frequency modulation power response. Even after time t1, the frequency change rate changes from negative to positive and participates in the inertial power. If the inertial power and droop power are superimposed at this time, it will reduce the output power of the photovoltaic and is not conducive to the rapid recovery of the frequency.

[0046] During the frequency degradation phase (Region 1), a combined inertial and droop control mode is employed. This leverages the superior steady-state performance of droop control to reduce frequency deviation, while inertial control minimizes the rate of change of frequency difference, thus preventing further frequency degradation. During the frequency recovery phase (Region 2), only droop control is used to avoid the adverse effects of inertial power on the frequency. Furthermore, the three frequency modulation resources can be coordinated and controlled by adjusting the inertial and droop coefficients to maximize their respective modulation potential and significantly improve the modulation effect.

[0047] S12. Based on the operating status information and the trend of change, a basis for determining the stage division and parameter adjustment is formed.

[0048] Based on the obtained frequency change rate, its trend is further identified, specifically by identifying the instantaneous direction of change of the frequency change rate, i.e., determining the sign of the second derivative of the frequency. According to this sign information, the frequency drop phase is finely divided into two sub-stages with different control requirements (e.g., when the second derivative is negative, it is classified as the first sub-stage; when it is positive, it is classified as the second sub-stage). This division result directly serves as the basis for selecting the corresponding adaptive adjustment function (e.g., the first adjustment function corresponding to the first sub-stage or the second adjustment function corresponding to the second sub-stage) for the virtual inertial control parameters.

[0049] S2. Based on the dynamic process of frequency deviation and frequency change rate, the frequency modulation process is divided into frequency drop phase region 1 and frequency recovery phase region 2, including the following steps: S21. Establish the start conditions for triggering frequency modulation actions.

[0050] Set a frequency deviation threshold, i.e., a frequency dead zone, for the frequency regulation unit of a photovoltaic power station. During the control process, the absolute value of the grid frequency deviation obtained from real-time monitoring will be used. and Perform a comparison. Only if the judgment condition is met. If a valid frequency disturbance is detected, the system triggers and enters the subsequent frequency modulation control logic; otherwise, the current operating state is maintained. The mathematical condition for setting the frequency modulation dead zone is as follows: S22. Based on the system dynamic behavior reflected by the characteristic information, the continuous frequency modulation process is analyzed into different time stages.

[0051] Execution is performed after the S21 start-up condition is met. During the frequency adjustment process, the system frequency deviation is based on the real-time acquisition in step S11. And the frequency change rate characteristic calculated by differentiating the frequency deviation in step S12. , and make continuous logical judgments on the symbols of the two.

[0052] When frequency deviation With frequency change rate When the signs are the same (e.g., under a power surge disturbance), Negative, Also negative), the analysis system is currently in a frequency drop phase (corresponding to Figure 2 Region 1, from the start of the disturbance to the frequency dropping to its lowest point.

[0053] When frequency deviation With frequency change rate When the signs are opposite (e.g., under a power surge disturbance), It is negative, but (Turns to positive), the analysis system is currently in the frequency recovery phase (corresponding to) Figure 2 Region 2, recovery begins from the lowest frequency point.

[0054] Analysis is a dynamic process, which is essentially the identification of the real-time state of the system's frequency dynamic response curve.

[0055] S23. Set corresponding control objectives and control strategy sets for each time stage.

[0056] 1. For the frequency droop phase, the control objective is set as "rapidly suppressing the rate of frequency change and reducing steady-state deviation." To achieve this objective, the control strategy set adopted is to simultaneously enable virtual inertial control and virtual droop control, allowing them to work in tandem. This strategy corresponds to the fact that during this phase, the frequency regulation power output of the photovoltaic power station should simultaneously include the output of the controlled variable frequency power generated by the frequency droop control system. Contributing inertial power and by The drooping power contributed.

[0057] 2. For the frequency recovery phase, the control objective is set as "smoothly guiding the frequency back to steady state." To achieve this objective, the control strategy set adopted is: only enabling virtual droop control, while setting the contribution of virtual inertial control to zero. This strategy corresponds to the fact that during this phase, the frequency regulation power output of the photovoltaic power station only includes the output from the virtual inertial control. The drooping power contributed, while the inertial power term... It is forced to be set to zero. This directly implements the conclusion in "Step 2" of the disclosure document that "only the droop control mode is used in Zone 2", avoiding the harmful effects of inertial power during the recovery period.

[0058] Summary: Step S21 uses a threshold comparison expression. .

[0059] The analysis in step S22 inherently relies on the dynamic relationship represented by the system frequency deviation and frequency change rate derived by the inventor; the strategy setting in step S23 directly corresponds to the enabling and disabling logic of virtual droop and virtual inertial control components in the frequency regulation power of the photovoltaic power station. Therefore, the entire partitioning process is a complete technical solution based on the specific mathematical model and expressions provided by the inventor.

[0060] S3. During the frequency drop and frequency recovery phases, the virtual droop control parameters and virtual inertial control parameters of the photovoltaic power station are adjusted adaptively and differentially, including the following steps: S31. Based on the control objectives corresponding to the time stage, determine the corresponding adjustment strategies for the virtual droop control parameters and the virtual inertia control parameters respectively; Based on the control objectives corresponding to the time stages, corresponding adjustment strategies are determined for the virtual inertial control parameters and the virtual droop control parameters, respectively. 1) Adaptive adjustment of droop coefficient.

[0061] like Figure 2 As shown in (b), the droop power is beneficial for frequency recovery in both Region 1 and Region 2. In Region 1, the frequency gradually drops from the steady state to the lowest point, and the droop power should also increase to its maximum value at time t1. In Region 2, the frequency recovers from the lowest value to the steady state value at time t2, and the droop power also decreases to its minimum value. Meanwhile, to avoid the photovoltaic storage unit frequently participating in frequency modulation under low-power disturbances, thus damaging its operating life, this invention sets a frequency modulation dead zone, referencing conventional frequency modulation units.

[0062] 2) Adaptive adjustment of inertia coefficient.

[0063] Inertial power is related to the rate of frequency change. It can quickly provide power support in the early stages of a frequency drop, rapidly suppressing the frequency drop. However, due to… Figure 2 It is known that inertial power output has the problem of not matching the system's power requirements, or even outputting power in the opposite direction. To address this, this invention... Figure 1 Based on this, an adaptive adjustment method for the inertia coefficient is established by revealing the partitioning recovery mechanism of frequency and its first / second derivatives. Figure 3 The curves show the changes in frequency and its first / second derivatives under a power surge scenario.

[0064] Depend on Figure 3 It is known that, in order to refine the control of inertial power and optimize the frequency control effect of photovoltaic storage, this invention subdivides the process of restoring stability of the first / second derivative of the frequency into four regions. In region 1', the frequency change rate rapidly drops to its lowest point at time t1. In this region, the frequency change is relatively small, and the frequency modulation output of the photovoltaic storage mainly relies on inertial support to quickly suppress the frequency drop. At this time, the greater the frequency change rate, the greater the inertial output should be. Figure 3 (c) It can be seen that the second derivative of the frequency in region 1' exhibits the characteristic of first falling and then rising back to zero, and its value is always less than 0.

[0065] The rate of change of frequency reaches its minimum at time t1. Figure 3 (b) The frequency change rate of region 2' gradually increases and reaches zero at time t2. However, the frequency is still in region 1 during the period from t1 to t2 and is not in the recovery range of region 2. The frequency in this region gradually drops to the lowest point, and the droop power gradually increases. The optical storage in region 2' should also maintain a certain inertial output and should continue to increase. It should not decrease its output as the frequency change rate approaches 0. The inertial output should also be at its maximum at time t2.

[0066] After time t1, by Figure 3 It can be seen that the frequency and the rate of frequency change have opposite signs in region 2 (region 3' and region 4'). At this time, only the droop control should participate in frequency modulation. The superposition of the two will instead cancel the frequency modulation output of the optical storage.

[0067] S32. Based on the real-time values ​​of the operating status information and changing trends, execute the adjustment strategy and determine the specific adjustment amount of each control parameter.

[0068] This step, based on the real-time feature information (frequency deviation Δf, rate of change df / dt and its trend) monitored in step S1 and the adjustment strategy determined in step S31, performs specific mathematical calculations and outputs precise parameter adjustment amounts.

[0069] The adaptive adjustment process of the droop coefficient in region 1 and region 2 can be expressed as follows: (1) In the formula, * can represent photovoltaic and energy storage units. This is the frequency regulation dead zone for the unit. This is the initial droop coefficient.

[0070] When the frequency is in region 1 and the rate of change of frequency is also in a declining phase (region 1'), the inertia coefficient is similar to the droop coefficient in region 1, and its adaptive adjustment process can be expressed as follows: (2) When the frequency is in region 1 and the rate of frequency change is also in a declining phase (region 2'), the adaptive adjustment process of the inertia coefficient can be expressed as follows: (3) S33. Update the parameters of the corresponding control loop according to the adjustment amount, and generate the initial power command for frequency regulation accordingly.

[0071] This step assigns the specific parameter adjustment amount calculated in step S32 to the corresponding parameter in the control system model, and calculates the theoretical frequency regulation power that the photovoltaic power station needs to provide through the model.

[0072] In an ideal scenario, where real-time photovoltaic and energy storage frequency regulation resources can fully meet the frequency regulation requirements, photovoltaic power plants and energy storage units are considered as three flexible frequency regulation resources. They participate in system frequency regulation through inertial and droop control methods, and the frequency response process can be expressed as: (4) (5) In the formula, and These are the frequency response transfer functions for photovoltaics and energy storage, respectively. and These are the frequency regulation powers of photovoltaic and energy storage, respectively. and These are the frequency response time constants of the photovoltaic and energy storage units, respectively, characterizing their response delay; and These are the droop coefficients for photovoltaics and energy storage, respectively. and These are the inertia coefficients for photovoltaics and energy storage, respectively.

[0073] In the embodiments of this application, the differentiated adaptive adjustment of S3 is a stage based on the dynamic process division of frequency deviation and frequency change rate. The virtual droop control parameters and virtual inertial control parameters are calculated using the adaptive adjustment functions shown in formulas (1) to (3).

[0074] During the frequency drop phase and the frequency recovery phase, the droop coefficient increases with the increase of the absolute value of the frequency deviation according to formula (1); the inertia coefficient is further divided into two sub-phases in the frequency drop phase according to the trend of the frequency change rate (i.e. the sign of the second derivative of the frequency), and is calculated using formula (2) and formula (3) respectively, and is set to zero in the frequency recovery phase.

[0075] In one optional implementation, the differential adaptive adjustment of S3 employs an adaptive adjustment strategy based on a preset rule lookup table method.

[0076] Based on the frequency drop phase and frequency recovery phase divided in step S2, and the frequency change rate trend (second derivative sign) identified in step S13, the current control state code is determined.

[0077] By querying the preset parameter adjustment table based on the status code, the adjustment amount or the target value after adjustment of the virtual droop control parameter and the virtual inertia control parameter can be obtained directly.

[0078] The control loop parameters are updated based on the lookup table results. The parameter adjustment table is pre-designed according to the control objectives under different states, and its design principle is consistent with the implementation method of this application, that is, during the frequency drop phase, the droop and inertia parameters are adjusted simultaneously to quickly suppress frequency changes and reduce deviations, and during the frequency recovery phase, the droop parameter is mainly adjusted and the inertia parameter is set to zero.

[0079] In another alternative implementation, the differentiated adaptive adjustment of S3 employs an adaptive adjustment strategy based on an online optimization algorithm.

[0080] Using the frequency deviation, frequency change rate and system frequency response model (i.e., the model described by equation (5)) at the current moment as the prediction basis, the optimization objective is to optimize the performance index of the system frequency recovery process (such as the integral of the square of the frequency deviation) in the future prediction time domain, and the real-time power capacity of the photovoltaic power station (i.e. the constraint to be considered in step S4) as the constraint condition, the optimal sequence of virtual droop control parameters and virtual inertial control parameters in the future several control cycles is solved online.

[0081] The parameter values ​​corresponding to the current moment from the solved parameter sequence are applied to the control loop to generate an initial power command. This optimization process is performed on a rolling basis in each control cycle, thereby achieving dynamic adaptive adjustment of the parameters.

[0082] This invention addresses the problems of fixed frequency modulation coefficients in traditional methods, which cannot adapt to dynamic frequency processes, and the harmful power generated by inertial control during the recovery period.

[0083] This scheme sets differentiated adaptive adjustment functions for the droop coefficient and the inertia coefficient based on the two stages of frequency drop and recovery. During the frequency drop stage, the trend of the rate of change of frequency (i.e., the sign of the second derivative) is introduced as a criterion to perform a refined two-stage adjustment of the inertia coefficient.

[0084] This enables control parameters to match the actual needs of the system frequency in different stages in real time and with high precision: during the frequency drop period, the synergistic enhancement of inertial control and droop control can quickly suppress the rate of frequency change and reduce steady-state deviation; during the frequency recovery period, the interference of inertial control on the recovery process is avoided by turning off inertial control.

[0085] S4. Based on the real-time available power capacity of the photovoltaic power station, the dynamic constraint on the frequency regulation power command calculated based on the adjusted parameters includes the following steps: S41. Assess the maximum adjustable power range of photovoltaic power plants and energy storage under current environmental and operating conditions; The output power of photovoltaic (PV) units depends not only on solar irradiance but also, due to the temperature sensitivity of semiconductor materials, on the impact of temperature on photoelectric conversion efficiency. This invention, based on the law of conservation of energy and the thermal characteristics of PV devices, constructs an equivalent model of irradiance and temperature in relation to the rated output power of a PV unit through linearization, which can be expressed as: (6) In the formula, This represents the actual irradiation intensity. For the area of ​​the photovoltaic panel, For photoelectric conversion efficiency, For temperature coefficient, The temperature of the photovoltaic panel. This is the standard test temperature.

[0086] Unlike photovoltaic (PV) generators, which use 10%-20% of their output power as frequency regulation reserve, energy storage can use its entire available capacity as frequency regulation reserve. However, energy storage itself has limitations due to overcharging and over-discharging. This invention uses State of Charge (SOC) to characterize the available frequency regulation margin of energy storage, which can be expressed as: (7) In the formula, In the state of energy storage charge, This is the initial frequency modulation time. For the rated capacity of energy storage, Let t be the cumulative charge and discharge energy stored at time t.

[0087] S42. Compare the initial power command with the maximum adjustable power range and make adaptive corrections for command components that exceed the range; The frequency regulation power change of the photovoltaic power station at time t can be expressed as: (8) In the formula, The ratio of photovoltaic frequency modulation power to rated output power. This refers to the number of photovoltaic (PV) units.

[0088] To avoid the energy storage from operating under severe overcharging and over-discharging conditions, this invention constrains the energy storage output power based on the logistic function. By limiting its output, the state of charge (SOC) of the energy storage is maintained. The maximum charging and discharging power changes of the energy storage participating in frequency regulation can be expressed as follows: (9) In the formula: Soc_min, Soc_0, Soc_low, Soc_high, Soc_1, and Soc_max are the minimum, lower, lower middle, higher middle, and maximum values ​​of SOC, respectively, and P0 and n are control function parameters.

[0089] S43. Based on the correction results, output the target power command that the photovoltaic power station can actually execute.

[0090] Receive the preliminary power command from step S33 (i.e., the theoretical frequency modulation power calculated by equations (4) and (5)). and ) and the real-time power limit from step S42 (i.e., the maximum adjustable photovoltaic power calculated from equations (8) and (10) With the maximum charge and discharge power of energy storage ).

[0091] The theoretical requirements are finally matched with the physical limits to generate the final action instructions.

[0092] The components in the initial power command ( and ), respectively with their corresponding real-time power limits ( and The comparison and decision are made. For photovoltaic units, the following is taken: and The value with the smaller absolute value and the same sign is used as the final photovoltaic execution instruction.

[0093] For energy storage units, take and The smaller absolute value and the same sign are selected as the final energy storage execution command. These two final execution commands are encapsulated into a target power command output with a defined timestamp and control cycle.

[0094] In the embodiments of this application, the real-time available power capability of S4 refers to the maximum power increase or decrease that the photovoltaic unit and energy storage unit inside the photovoltaic power station can safely provide after considering the current real-time environmental conditions and equipment operating status.

[0095] For photovoltaic units, based on the real-time collected irradiance and photovoltaic panel temperature, their current maximum available output power is calculated using formula (6), and their maximum adjustable frequency power is determined according to the preset frequency regulation reserve ratio. For energy storage units, based on the real-time monitored state of charge (calculated by formula (7)) and substituted into the constraint function constructed based on the Logistic function (formula (9)), their maximum allowable charging power and maximum discharging power under the current state are calculated respectively. This forms the specific quantified maximum adjustable power range of the entire photovoltaic power station at the current moment.

[0096] In one alternative implementation, the real-time available power capability of S4 refers to the power adjustment boundary dynamically determined by the photovoltaic power station based on the real-time instructions received from the superior dispatch system and the internal energy storage status.

[0097] The controller of a photovoltaic power plant receives power upper and lower limit instructions from the grid dispatch or energy management system in real time. These instructions define the range of total power that the power plant is allowed to output to the grid during the current period.

[0098] The controller monitors the real-time state of charge of the energy storage system. The real-time available power capacity of the power station is determined by two factors: the overall adjustable power range of the power station must not exceed the upper and lower limits of the dispatch command, and the power that the energy storage units can provide must be dynamically narrowed or widened according to whether their current state of charge is close to the safety boundary, forming a comprehensive dynamic power constraint range that takes into account both external dispatch requirements and internal energy storage safety.

[0099] In another alternative implementation, the real-time available power capability of S4 refers to the safe power regulation capability obtained by the photovoltaic power plant after performing derating calculations based on a real-time assessment of the health status of photovoltaic modules and energy storage batteries.

[0100] The system monitors key parameters that reflect equipment aging or performance degradation (such as the output characteristic degradation coefficient of photovoltaic modules, the internal resistance growth or capacity degradation coefficient of energy storage batteries) and calculates a health status coefficient of less than 1 for both photovoltaic and energy storage units.

[0101] When assessing real-time available power capacity, the theoretical maximum output of photovoltaics is calculated based on irradiance and temperature, or its theoretical charge and discharge limits are calculated based on the energy storage SOC. These theoretical values ​​are then multiplied by the corresponding health state coefficient to obtain the derating safety limits after considering the long-term operating life and reliability of the equipment.

[0102] This invention addresses the problem in traditional frequency regulation methods where control commands may exceed the actual physical capabilities of the equipment, leading to overload, damage, or frequency regulation failure. It deeply couples theoretical control algorithms with the real-time physical operating boundaries of the photovoltaic power plant. By real-time evaluation of the maximum safe adjustable power of the photovoltaic units (considering irradiance and temperature) and energy storage units (considering state of charge (SOC), and by strictly dynamic limiting the theoretically calculated frequency regulation power commands, it ensures that the power commands issued at any given time remain within the equipment's currently permissible safe range.

[0103] It fundamentally prevents the risks of overcharging, over-discharging, or overloading of equipment caused by frequency regulation tasks, ensures the operational safety and lifespan of the frequency regulation resources themselves, and enables photovoltaics and energy storage to intelligently complement each other according to their real-time changing capabilities, thereby maximizing the utilization of frequency regulation potential within the safety boundary. Thus, under the premise of ensuring absolute equipment safety, it improves the reliability and actual regulation effect of the joint frequency regulation system.

[0104] S5. Controlling the operation of the photovoltaic power station according to the constrained power command to support grid frequency recovery includes the following steps: S51. Process the operating status information and extract feature information to characterize the dynamic changes in frequency.

[0105] Using a pre-constructed system frequency response model that includes thermal power units, photovoltaic units, and energy storage, the target power command output in step S43 (i.e., the actual power executed by photovoltaic and energy storage) is substituted into the system model as a known input to calculate the system frequency deviation Δ under the action of the frequency regulation power. f g Expected change process This invention takes a large-capacity thermal power unit as a conventional frequency regulating unit. Its dynamic frequency response characteristics can be mainly characterized by the governor and reheat turbine, and the transfer function Ggen can be expressed as follows: (10) In the formula: T CH , T G , T RH These represent the time constants of the steam turbine, governor, and reheater in a thermal power unit, respectively. F HP Δ is the reheater gain coefficient of the thermal power unit; f gThis refers to the power grid frequency deviation. K gen This represents the sag coefficient of the thermal power unit.

[0106] Combining equations (8) to (10), when the system experiences a power disturbance Δ P L At that time, the grid frequency deviation Δ f g It can be represented as: (11) In the formula, Δ P T Power is switched for the tie line; D g and T g' These are the grid damping and inertia coefficient, respectively; This refers to system power disturbance.

[0107] S52. Convert the target power command into executable operation commands for each controllable unit in the photovoltaic power station and energy storage.

[0108] The target power command output in step S43 contains the final executed power values ​​for both the photovoltaic unit and the energy storage unit. Based on the specific configuration, communication protocol, and control interface of each photovoltaic inverter and energy storage converter in the photovoltaic power plant, the target power command at the power plant level is decomposed and mapped into the underlying control commands of each controllable unit.

[0109] For photovoltaic units, the total photovoltaic power output is allocated to the active power setpoints of each inverter according to the capacity and status of each photovoltaic inverter.

[0110] For energy storage units, the energy storage power value is directly used as the active power setpoint of the energy storage converter, and its charging and discharging direction is clearly defined. These low-level control commands are digital or analog signals that can be directly recognized and executed by the actuators of each controllable unit.

[0111] S53. Based on executable operation instructions, drive the power output device of the controllable unit to output the actual power corresponding to the instructions.

[0112] The executable operation commands generated by S52 are sent to each photovoltaic inverter and energy storage converter via the control bus or communication network. Each power conversion device adjusts the duty cycle of its power semiconductor switching devices according to the received commands through internal control algorithms (such as current closed-loop control and power closed-loop control), thereby controlling the active power output on its AC side.

[0113] Photovoltaic inverters adjust the amplitude and phase of the output current to ensure that the active power injected into the grid accurately tracks the command value; energy storage converters control bidirectional energy flow to ensure that the active power absorbed or released accurately tracks the command value.

[0114] The total actual power output of the photovoltaic power station to the grid is consistent with the target power command, thus achieving the actual regulation of the grid frequency.

[0115] S54. Based on the actual response of the power grid frequency, evaluate the frequency regulation effect and decide whether to start a new frequency regulation control cycle.

[0116] After the actual output of frequency regulation power, the system continuously monitors the actual dynamic response of the grid frequency through the method in step S1, and obtains the real-time frequency deviation and frequency change rate. The actual frequency response is compared with the expected target (e.g., whether the frequency deviation has been reduced to within the frequency regulation dead zone, and whether the frequency change rate has approached zero) to evaluate the effect of this frequency regulation action.

[0117] If the evaluation results indicate that the frequency has not yet stabilized (e.g., |Δf|> If |df / dt| is greater than the threshold, then the current frequency modulation cycle is determined to be incomplete, and the process automatically returns to step S2, where a new round of frequency phase division and frequency modulation control is started based on the latest frequency.

[0118] If the evaluation results indicate that the frequency has stabilized (e.g., |Δf| ≤ 0.05), then... If the frequency modulation task is completed (and maintained for a certain period of time), the system exits the current frequency modulation cycle and enters normal monitoring mode or waits for the next disturbance. This feedback decision-making mechanism ensures that frequency modulation control can adaptively continue to operate until the frequency disturbance is completely suppressed.

[0119] Example 3, referring to Figures 4-8 This invention provides a frequency regulation control method for photovoltaic power plants that considers frequency zoning and power constraints. To verify the beneficial effects of this invention, scientific demonstration is carried out through experiments.

[0120] A frequency response model for optical storage is built in MATLAB / Simulink, and the transfer function model is as follows: Figure 4 As shown.

[0121] The thermal power unit consists of a reheat turbine and a governor. The photovoltaic unit adopts a single-plate equivalent model with a total installed capacity of 5MW. All photovoltaic units operate in the MPPT range. The rated power and capacity configuration of energy storage is 1.5MW / 1.5MWh. The values ​​of other parameters are shown in Table 1.

[0122] The simulation analysis is divided into two parts. The first part is used to verify the adaptive adjustment of the optical-storage frequency modulation coefficient in different frequency recovery ranges. The second part is used to verify the adaptive constraint and cooperative process of the optical-storage frequency modulation power.

[0123] Table 1 Model Parameters

[0124] To verify the effectiveness of the proposed photovoltaic-storage coordinated control strategy, the method of this patent was compared and analyzed with that of thermal power plant frequency regulation alone (Method 1). The system frequency was kept in a steady state at 0s, and a load step disturbance of 0.01 pu was set at 5s. The frequency curves under different strategies are shown below. Figure 5 .

[0125] Depend on Figure 5 It can be seen that the maximum frequency deviation and steady-state frequency deviation of Method 1 are relatively large, while the system frequency characteristics under the method of this patent are more stable, and the optimal frequency modulation effect can be maintained throughout the entire frequency recovery range.

[0126] To verify the adaptive adjustment effect of the frequency modulation coefficient of the proposed method, the control effect of the proposed method is demonstrated in different frequency recovery ranges. Figure 6 The adaptive variation of the optical storage frequency modulation coefficient and the output power curve under this method are derived from... Figure 6 It can be seen that the droop coefficient increases with the increase of frequency deviation in the frequency drop range of region 1, and tends to a constant value as the frequency reaches a steady state.

[0127] Compared to the droop coefficient, the inertia coefficient changes rapidly after a sudden change in system power to quickly provide power support. It reaches its maximum value in region 1 and gradually returns to its initial value in region 2 as the frequency change rate approaches 0. This allows the inertia control to maintain a good level of frequency support within the frequency drop range, quickly suppressing frequency drops. As the frequency curve enters region 3, the inertia coefficient becomes 0, effectively preventing the inertia of the optical storage and the droop output from canceling each other out, thus improving the overall frequency control effect.

[0128] To verify the effectiveness of the proposed adaptive constraint method for frequency modulation power of optical storage, it is compared with a method without setting a rated power constraint.

[0129] First, the irradiance and temperature are set to continuously step-change. The frequency regulation power command and actual power output of the photovoltaic power station are respectively as follows: Figure 7 As shown, by Figure 7 It can be seen that the photovoltaic power station's maximum output power and frequency regulation power are constrained by changes in light intensity and temperature in the 5-15s and 25s-35s ranges, respectively.

[0130] Similar to photovoltaic power plants, Figure 8The proposed strategy, which considers the frequency regulation power curve of energy storage, decreases its frequency regulation power to restore SOC as the SOC moves away from 0.5 in the 5-15s range, since the continuous charging of energy storage tends to the charging threshold. After 15s, the system frequency regulation power command requires energy storage to discharge, and the discharge during this period is conducive to the recovery of energy storage SOC, so the frequency regulation power of energy storage increases. In this range, the frequency regulation effect is improved while maintaining the SOC level.

[0131] In summary, the frequency regulation control method for photovoltaic power plants proposed in this invention, which considers frequency zoning and power constraints, fully takes into account the dynamic requirements of each stage of frequency recovery and adaptively adjusts the frequency regulation coefficients of the photovoltaic power plant and energy storage system accordingly. Furthermore, by linking the photovoltaic frequency regulation power constraint with the coefficient adjustment, it can be adapted to actual recovery conditions.

[0132] Example 4 is an embodiment of the present invention. This embodiment provides a photovoltaic power plant frequency regulation control system that considers frequency zoning and power constraints, including a data collection module, a stage division module, an adjustment module, a calculation module, and an output command module. The data collection module monitors the frequency deviation and frequency change rate of the power grid. The segmentation module divides the frequency modulation process into a frequency drop phase and a frequency recovery phase based on the dynamic process of frequency deviation and frequency change rate. The adjustment module performs differentiated adaptive adjustments to the virtual inertial control parameters and virtual droop control parameters of the photovoltaic power station during the frequency drop and frequency recovery phases. The calculation module dynamically constrains the frequency modulation power command calculated based on the adjusted parameters, according to the real-time available power capacity of the photovoltaic power station. The output command module controls the operation of the photovoltaic power station based on the constrained power command, supporting the restoration of the grid frequency.

[0133] This embodiment also provides an electronic device applicable to a photovoltaic power plant frequency regulation control method considering frequency zoning and power constraints, comprising: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the photovoltaic power plant frequency regulation control method considering frequency zoning and power constraints proposed in the above embodiment.

[0134] This embodiment also provides a storage medium storing a computer program that, when executed by a processor, implements a photovoltaic power plant frequency regulation control method considering frequency zoning and power constraints as proposed in the above embodiments.

[0135] The storage medium proposed in this embodiment and the method for implementing a photovoltaic power plant frequency regulation control considering frequency zoning and power constraints proposed in the above embodiments belong to the same inventive concept. Technical details not described in detail in this embodiment can be found in the above embodiments, and this embodiment has the same beneficial effects as the above embodiments.

[0136] Based on the above description of the implementation methods, those skilled in the art can clearly understand that the present invention can be implemented using software and necessary general-purpose hardware, and of course, it can also be implemented using hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory, hard disk, or optical disk, etc., including several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods of the various embodiments of the present invention.

[0137] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A frequency partition and power constraint considering photovoltaic power station frequency modulation control method, characterized in that: include, Monitor the frequency deviation and rate of frequency change of the power grid; Based on the dynamic process of frequency deviation and frequency change rate, the frequency modulation process is divided into the frequency drop stage and the frequency recovery stage. During the frequency drop and frequency recovery phases, the virtual inertial control parameters and virtual droop control parameters of the photovoltaic power station are adjusted in a differentiated and adaptive manner. Based on the real-time available power capacity of the photovoltaic power station, the frequency regulation power command calculated based on the adjusted parameters is dynamically constrained. The operation of the photovoltaic power station is controlled according to the constrained power command to support the restoration of the grid frequency.

2. The photovoltaic power plant frequency regulation control method considering frequency zoning and power constraints as described in claim 1, characterized in that: The frequency deviation and frequency change rate of the monitored power grid include, Real-time acquisition of power grid frequency operation status information; Based on operational status information and changing trends, a basis for determining phase division and parameter adjustment is established.

3. The photovoltaic power plant frequency regulation control method considering frequency zoning and power constraints as described in claim 2, characterized in that: The process of dividing the frequency modulation process into a frequency drop phase and a frequency recovery phase based on the dynamic process of frequency deviation and frequency change rate includes the following: Establish the activation conditions for triggering frequency modulation actions; Based on the system dynamic behavior reflected by the characteristic information, the continuous frequency modulation process is analyzed into different time stages; Set corresponding control objectives and control strategy sets for each time period.

4. The photovoltaic power plant frequency regulation control method considering frequency zoning and power constraints as described in claim 3, characterized in that: The differentiated adaptive adjustment of the virtual inertial control parameters and virtual droop control parameters of the photovoltaic power station during the frequency drop and frequency recovery phases includes, Based on the control objectives corresponding to the time stage, corresponding adjustment strategies are determined for the virtual inertial control parameters and the virtual droop control parameters, respectively. Based on the real-time values ​​of operating status information and changing trends, an adjustment strategy is executed to determine the specific adjustment amount of each control parameter. The parameters of the corresponding control loop are updated based on the adjustment amount, and a preliminary power command for frequency regulation is generated accordingly.

5. The photovoltaic power plant frequency regulation control method considering frequency zoning and power constraints as described in claim 4, characterized in that: The step of dynamically constraining the frequency modulation power command calculated based on the adjusted parameters according to the real-time available power capacity of the photovoltaic power station includes: Assess the maximum adjustable power range of photovoltaic power plants and energy storage under current environmental and operating conditions; The initial power command is compared with the maximum adjustable power range, and the command components that exceed the range are adaptively corrected. Based on the corrected results, the target power command that the photovoltaic power station can actually execute is output.

6. The photovoltaic power plant frequency regulation control method considering frequency zoning and power constraints as described in claim 5, characterized in that: The control of the photovoltaic power station's operation based on the constrained power command, supporting grid frequency recovery, includes... The operating status information is processed to extract feature information that characterizes the dynamic changes in frequency; The target power command is converted into executable operation commands for each controllable unit within the photovoltaic power plant; Based on executable operation instructions, the power output device of the controllable unit is driven to output the actual power corresponding to the instructions; Based on the actual response of the power grid frequency, assess the frequency regulation effect and decide whether to start a new frequency regulation control cycle.

7. A photovoltaic power plant frequency regulation control method considering frequency zoning and power constraints as described in claim 6, characterized in that: The differentiated adaptive adjustment of the virtual inertial control parameters and virtual droop control parameters of the photovoltaic power station includes determining corresponding adjustment strategies for the virtual inertial control parameters and virtual droop control parameters respectively; For virtual droop control parameters, during the frequency drop phase and frequency recovery phase, if the absolute value of the frequency deviation is greater than the preset dead zone threshold, the adjustment amount is positively correlated with the absolute value of the frequency deviation. For virtual inertial control parameters, during the frequency drop phase, the adjustment process is divided into at least two sub-phases based on the trend of the frequency change rate, and different adjustment functions are used in different sub-phases so that the virtual inertial control parameters achieve a peak value when the frequency deviation reaches an extreme value.

8. A photovoltaic power plant frequency regulation control system considering frequency zoning and power constraints, employing the photovoltaic power plant frequency regulation control method considering frequency zoning and power constraints as described in any one of claims 1 to 7, characterized in that, include: The module includes a data collection module, a phase division module, an adjustment module, a calculation module, and an output instruction module. The data collection module monitors the frequency deviation and frequency change rate of the power grid. The segmentation module divides the frequency modulation process into a frequency drop phase and a frequency recovery phase based on the dynamic process of frequency deviation and frequency change rate. The adjustment module performs differentiated adaptive adjustments to the virtual inertial control parameters and virtual droop control parameters of the photovoltaic power station during the frequency drop and frequency recovery phases. The calculation module dynamically constrains the frequency modulation power command calculated based on the adjusted parameters, according to the real-time available power capacity of the photovoltaic power station. The output command module controls the operation of the photovoltaic power station based on the constrained power command, supporting the restoration of the grid frequency.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the frequency regulation control method for a photovoltaic power plant considering frequency zoning and power constraints as described in any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of a photovoltaic power plant frequency regulation control method considering frequency zoning and power constraints as described in any one of claims 1 to 7.

Images