Rapid frequency response control method and system for photovoltaic power station

Abstract

The embodiment of the invention provides a photovoltaic power station fast frequency response control method and system, and belongs to the field of photovoltaic power station fast frequency response control. The method comprises the following steps: calculating a dynamic response threshold value by using preprocessed operation data of the photovoltaic power station; performing dynamic priority self-organization control to obtain a response sequence list; distributing an active power target value needing to be adjusted; and performing automatic power generation control interlocking mechanism check on the active power target value needing to be adjusted, and issuing the active power target value needing to be adjusted, which passes the automatic power generation control interlocking mechanism check, to a power adjusting device so as to control the power adjusting device to adjust the frequency of a power grid and complete rapid frequency response control. According to the invention, through dynamic response threshold hierarchical calculation and self-organizing priority iteration, rapid frequency adjustment of the photovoltaic power station is realized, and the response speed and precision are improved; and a double-signal interlocking mechanism ensures reliable execution of a control instruction.

Description

Technical Field

[0001] The present invention relates to the field of fast frequency response control of photovoltaic power stations, and in particular to a fast frequency response control method and system for photovoltaic power stations. Background Art

[0002] With the continuous increase in renewable energy penetration, photovoltaic power plants, as a vital component of the power system, are becoming increasingly important. Their ability to actively participate in grid frequency regulation is crucial for ensuring stable system operation. Traditional frequency response technologies for photovoltaic power plants primarily rely on automatic generation control (AGC) systems, which trigger active power regulation using preset fixed thresholds or employ strategies such as droop control and virtual synchronous generators to simulate the inertia characteristics of synchronous generators. In recent years, some research has attempted to introduce dynamic threshold adjustment mechanisms and multi-objective optimization algorithms to improve regulation accuracy and response speed. For example, a dynamic threshold division method based on fuzzy logic can partially adapt to grid frequency fluctuations, while a distributed collaborative control framework implements local unit prioritization through a multi-agent system. However, existing technologies generally lack adaptability in priority allocation strategies, making it difficult to meet the demand for rapid frequency support, particularly when dealing with complex frequency disturbances caused by a high proportion of renewable energy integration. Summary of the Invention

[0003] The purpose of the embodiments of the present invention is to provide a fast frequency response control method and system for a photovoltaic power station, which integrates dynamic response threshold calculation, self-organizing priority iteration and dual-signal interlocking verification, and can improve the frequency regulation speed, regulation accuracy and reliability of control instructions of the photovoltaic power station.

[0004] To achieve the above objectives, an embodiment of the present invention provides a method for controlling rapid frequency response of a photovoltaic power station, comprising: collecting and preprocessing photovoltaic power station operating data, and calculating a dynamic response threshold using the preprocessed photovoltaic power station operating data; performing dynamic priority self-organizing control based on the preprocessed photovoltaic power station operating data and the dynamic response threshold to obtain a response sequence list; and allocating an active power target value to be adjusted based on the dynamic response threshold and the response sequence list; The active power target value that needs to be adjusted is checked by the automatic power generation control interlocking mechanism, and the active power target value that needs to be adjusted that passes the check by the automatic power generation control interlocking mechanism is sent to the power regulation device to control the power regulation device to adjust the grid frequency and complete fast frequency response control.

[0005] Optionally, the calculation of the dynamic response threshold includes: calculating the frequency deviation between the rated frequency of the power grid and the current average frequency of the power grid; dividing the power grid frequency state according to the absolute value of the frequency deviation; selecting a corresponding frequency deviation response model according to the divided power grid frequency state; and calculating the dynamic response threshold based on the frequency deviation response model.

[0006] Optionally, the division of the grid frequency state includes dividing the grid operating frequency state into a reference state, an offset state and an emergency state according to a set first deviation threshold and a second deviation threshold. When the absolute value of the frequency deviation is less than the first deviation threshold, the grid frequency state is divided into a reference state. When the first deviation threshold ≤ the absolute value of the frequency deviation < the second deviation threshold, the grid frequency state is divided into an offset state. When the absolute value of the frequency deviation is greater than or equal to the second deviation threshold, the grid frequency state is divided into an emergency state.

[0007] Optionally, the frequency deviation response model includes a reference state model, an offset state model and an emergency state model.

[0008] Optionally, the dynamic priority self-organizing control is performed to obtain a response order list, including: calculating the initial response priority; calculating the threshold sensitivity factor based on the dynamic response threshold; performing self-organizing iterative update according to the initial response priority and the threshold sensitivity factor to obtain an iterative convergence priority; sorting the iterative convergence priority to obtain a response order list.

[0009] Optionally, the self-organizing iterative update is performed according to the initial response priority and the threshold sensitivity factor to obtain the iterative convergence priority, including: calculating the neighborhood interaction correction term and the threshold sensitivity correction term, the calculating the neighborhood interaction correction term includes calculating the initial response priority difference between the neighborhood unit and the current power generation unit, and summing the initial response priority differences of all neighborhood units.

[0010] Optionally, the allocation of the active power target value that needs to be adjusted based on the dynamic response threshold and the response sequence list includes: initializing the cumulative allocation amount; calculating the current cumulative allocation power of each power generation unit in order of iterative convergence priority from high to low in the response sequence list; if the sum of the current cumulative allocation power and the current available capacity of the power generation unit does not exceed the dynamic response threshold, then using the current available capacity as the active power target value that needs to be adjusted, and updating the cumulative allocation amount; if the sum of the current cumulative allocation power and the current available capacity of the power generation unit exceeds the dynamic response threshold, then calculating the remaining required power value, using the remaining required power value as the active power target value that needs to be adjusted, and terminating subsequent allocation after updating the cumulative allocation amount.

[0011] Optionally, the automatic power generation control interlocking mechanism check of the active power target value that needs to be adjusted includes: simultaneously monitoring the hard-wired signal and the communication signal, if either the hard-wired signal or the communication signal is 1, it is determined that the active power target value that needs to be adjusted has not passed the automatic power generation control interlocking mechanism check; if the monitored hard-wired signal and the communication signal are both 0, it is determined that the active power target value that needs to be adjusted has passed the automatic power generation control interlocking mechanism check.

[0012] Optionally, sending the active power target value that needs to be adjusted checked by the automatic power generation control interlocking mechanism to the power regulation device includes: encapsulating the active power target value that needs to be adjusted checked by the automatic power generation control interlocking mechanism to obtain a formatted instruction frame, and sending the formatted instruction frame to the power regulation device.

[0013] On the other hand, the present invention provides a photovoltaic power station fast frequency response control system for implementing a photovoltaic power station fast frequency response control method. The system includes a control module, the control module includes a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor executes the computer program to implement the photovoltaic power station fast frequency response control method.

[0014] The above technical solution significantly improves the frequency response speed and regulation accuracy of photovoltaic power stations through dynamic response threshold calculation and priority self-organizing control. Based on a frequency deviation response model with frequency deviation classification (reference state, offset state, and emergency state), it implements a refined power regulation strategy, thereby enhancing grid state adaptability. It optimizes the resource allocation sequence through a dynamic priority iteration mechanism, combined with threshold constraints for cumulative power allocation to ensure that the regulation amount is precisely controllable and avoids overload. The automatic power generation control interlocking mechanism effectively prevents command conflicts through dual-signal monitoring, ensuring the safe and reliable execution of control commands. This solution balances response speed and stability, can quickly coordinate the power output of multiple devices when the grid frequency fluctuates, improves the grid frequency recovery efficiency and the system's anti-disturbance capabilities, and is suitable for frequency emergency support needs under complex operating conditions.

[0015] Other features and advantages of the embodiments of the present invention will be described in detail in the subsequent detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The accompanying drawings are used to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the following detailed description, they are used to explain the embodiments of the present invention, but do not constitute a limitation of the embodiments of the present invention. In the accompanying drawings: Figure 1 It is a flow chart of the fast frequency response control method of photovoltaic power station.

[0017] Figure 2 It is the flow chart of dynamic response threshold calculation. DETAILED DESCRIPTION

[0018] The following is combined with Figure 1 -Attached Figure 2The specific implementation of the embodiment of the present invention is described in detail. It should be understood that the specific implementation described here is only used to illustrate and explain the embodiment of the present invention, and is not used to limit the embodiment of the present invention.

[0019] It should be noted that the acquisition, transmission, storage, use, and processing of data in the technical solution of this application are in compliance with the relevant provisions of national laws and regulations. In the embodiments of this application, certain software, components, models, and other existing solutions in the industry may be mentioned. These should be considered as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of this application, but it does not mean that the applicant has or will necessarily use such solutions.

[0020] In the process of realizing the present invention, the inventors of the present application discovered that the fixed response threshold adopted in the prior art cannot adapt to the dynamic changes of the power grid, resulting in adjustment lag or overload risk; priority sorting relies on static preset parameters and lacks real-time working condition perception capability, affecting response efficiency; the interlocking mechanism relies on single signal verification and has the risk of false operation; the use of a unified response model makes it difficult to match the rapid fluctuation characteristics of the power grid frequency, resulting in insufficient control accuracy.

[0021] Example 1 Reference Figure 1-Figure 2 , which is the first embodiment of the present invention, provides a photovoltaic power station fast frequency response control method, comprising: S100: Collecting and preprocessing photovoltaic power station operation data, and calculating a dynamic response threshold using the preprocessed photovoltaic power station operation data.

[0022] Specifically, data from individual PV power stations, regional power generation data, and grid indicators are collected. This data includes active power, reactive power, voltage, current, and temperature. The collected PV power station operating data is preprocessed, including applying a sliding average filter to the frequency and power flow data.

[0023] Furthermore, the available capacity of each individual generating unit and the total available capacity of all generating units are calculated based on the preprocessed PV power station operating data. Available capacity of each generating unit = maximum allowable output power of the generating unit - actual active power output of the generating unit; total available capacity = the sum of the available capacities of all individual units.

[0024] It should be noted that the available capacity of a single machine and the total available capacity are recalculated in each data collection cycle. When an inverter failure, communication interruption, or sudden environmental change (such as a sudden temperature rise) is detected, the available capacity of a single machine and the total available capacity are immediately recalculated.

[0025] Preferably, by calculating the available capacity of a single machine, the regulation potential can be accurately quantified. The available capacity of a single machine and the total available capacity are updated in each collection cycle, which can ensure the timeliness of the capacity data and quickly respond to emergencies such as inverter failures.

[0026] Furthermore, calculating the dynamic response threshold includes calculating the frequency deviation between the rated frequency of the power grid and the current average frequency of the power grid; dividing the power grid frequency state according to the absolute value of the frequency deviation; selecting the corresponding frequency deviation response model according to the divided power grid frequency state; and calculating the dynamic response threshold based on the frequency deviation response model.

[0027] It should be noted that the dynamic response threshold is a dynamically calculated power regulation constraint value and is also the active power target value that needs to be adjusted. It is used to limit the total amount of power regulation to ensure that the regulation process not only meets the grid demand but also avoids equipment overload.

[0028] Specifically, the calculation formula for frequency deviation is as follows:

[0029] in, Indicates the frequency deviation, is the rated frequency of the grid, Indicates the average value of the current grid frequency after preprocessing.

[0030] Furthermore, the frequency deviation The absolute value of , according to the absolute value of the frequency deviation , dividing the grid frequency state. Dividing the grid frequency state includes dividing the grid operating frequency state into a reference state, an offset state, and an emergency state according to a set first deviation threshold (0.1Hz) and a second deviation threshold (0.3Hz). When the absolute value of the frequency deviation is less than the first deviation threshold, the grid frequency state is divided into a reference state. When the first deviation threshold ≤ the absolute value of the frequency deviation < the second deviation threshold, the grid frequency state is divided into an offset state. When the absolute value of the frequency deviation is greater than or equal to the second deviation threshold, the grid frequency state is divided into an emergency state. The frequency deviation response model includes a reference state model, an offset state model, and an emergency state model.

[0031] (1) When the absolute value of the frequency deviation is less than the first deviation threshold, that is, when the grid frequency state is the reference state, the reference state model in the frequency deviation response model is used to calculate the dynamic response threshold. The expression of the reference state model is as follows:

[0032] in, represents the dynamic response threshold, represents the exponential coefficient of the baseline model, represents the capacity proportional coefficient of the baseline model, represents the total available capacity of all generating units, It represents the total power generation of all power generation units, that is, the algebraic sum of the active power of all power generation units.

[0033] (2) When the first deviation threshold ≤ the absolute value of the frequency deviation < the second deviation threshold, that is, when the grid frequency state is in the offset state, the offset state model in the frequency offset response model is used to calculate the dynamic response threshold. The expression of the offset state model is as follows:

[0034] in, represents the dynamic response threshold, represents the logarithmic coefficient of the offset state model, represents the frequency deviation coefficient of the offset state model, Indicates the absolute value of the frequency deviation.

[0035] (3) When the absolute value of the frequency deviation is ≥ the second deviation threshold, that is, when the grid frequency state is in an emergency state, the emergency state model in the frequency deviation response model is used to calculate the dynamic response threshold. The expression of the emergency state model is as follows:

[0036] in, represents the dynamic response threshold, represents the square root coefficient of the emergency model, Indicates the absolute value of the frequency deviation, Indicates the maximum frequency deviation reference value, which is 0.5Hz.

[0037] It should be noted that the coefficients in the frequency deviation response model are determined by fitting historical data or a preset parameter table, and are dynamically calibrated according to the characteristics of the power grid.

[0038] Optimally, a hierarchical dynamic response threshold design is employed. In the baseline state, an exponential model is used to balance capacity utilization and regulation intensity. In the offset state, a logarithmic model is used to achieve a progressive response. In the emergency state, a square root model is used to trigger rapid and strong intervention. By combining real-time capacity updates with dynamic mathematical models, resource allocation efficiency is optimized, balancing equipment stability with grid response speed. This effectively improves the frequency regulation accuracy and anti-disturbance capabilities of photovoltaic power stations, reduces equipment losses during minor fluctuations, prioritizes grid security during large deviations, and achieves faster response and shorter frequency recovery times.

[0039] S200: Based on the pre-processed photovoltaic power station operation data and the dynamic response threshold, dynamic priority self-organizing control is performed to obtain a response sequence list.

[0040] Furthermore, dynamic priority self-organization control is performed to obtain a response order list, including calculating the initial response priority; calculating the threshold sensitivity factor based on the dynamic response threshold; performing self-organization iterative update according to the initial response priority and the threshold sensitivity factor to obtain the iterative convergence priority; sorting the iterative convergence priority to obtain a response order list.

[0041] Specifically, the initial response priority is calculated as follows:

[0042] in, Indicates the initial response priority, 、 、 are weight coefficients, Indicates the available capacity of a single machine. represents the total available capacity of all generating units, represents the stability score, , Indicates the absolute value of the frequency deviation, To prevent zero constant.

[0043] Preferably, the calculation formula for the initial response priority adopts a dynamic weighting method to balance capacity efficiency, equipment stability and frequency sensitivity, give priority to scheduling high-availability capacity units to improve regulation efficiency, and introduce temperature and voltage fluctuation scores to suppress the participation of unstable equipment to ensure operational safety; combined with the frequency deviation dynamic adjustment strategy weight, when the deviation is small, focus on fine-tuning to reduce equipment loss, and when the deviation is large, strengthen capacity dominance to achieve rapid power support; the configurability of the weight coefficient supports flexible strategy adjustment (such as focusing on economy or reliability), and the real-time data-driven capacity update and frequency deviation feedback mechanism can adapt to grid fluctuations, taking into account both response speed and regulation accuracy.

[0044] It should be noted that The stability score indicates the degree of temperature deviation from 25℃ and the standard deviation of voltage fluctuation. If the temperature is close to 25℃ and the voltage fluctuation is small, then If it approaches 1, the stability score is high; if the temperature deviates significantly from 25°C or the voltage fluctuates violently, Approaching 0, the stability score is low.

[0045]

[0046] in, represents the stability score, Indicates the real-time component temperature, represents the standard deviation of voltage fluctuation, Indicates the maximum allowed standard deviation; is the temperature deviation weight, is the voltage fluctuation weight, Indicates the maximum allowable temperature difference.

[0047] Furthermore, the threshold sensitivity factor is calculated as follows:

[0048] in, Represents the threshold sensitivity factor; reflects the degree of matching between the available capacity of a single machine and the dynamic response threshold, and , The higher it is, the more sufficient the adjustable capacity is at the current threshold; Indicates the available capacity of a single machine; represents the dynamic response threshold; To prevent zero constant.

[0049] A self-organizing iterative update is performed according to the initial response priority and the threshold sensitivity factor to obtain an iterative convergence priority, including: calculating a neighborhood interaction correction term and a threshold sensitivity correction term. The calculated neighborhood interaction correction term includes calculating the difference in initial response priority between the neighborhood unit and the current power generation unit, and summing the initial response priority differences of all neighborhood units. The neighborhood here refers to the electrical topology proximity.

[0050] Specifically, the calculation formula of the neighborhood interaction correction term is as follows:

[0051] in, represents the neighborhood weight adjustment rate, represents the priority after the tth iteration, It represents the priority of the neighboring power generation unit j adjacent to the current power generation unit i after the tth iteration, Represents the neighborhood set of power generation unit i, i is the current power generation unit, and j is the power generation unit adjacent to i.

[0052] Furthermore, the threshold sensitivity correction term is calculated as follows:

[0053] in, represents the weighted coefficient of the threshold sensitivity factor, Represents the threshold sensitivity factor, with 0.5 being the base threshold.

[0054] Furthermore, the expression for self-organizing iterative update according to the initial response priority and the threshold sensitivity factor is as follows:

[0055] in, represents the priority after the t+1th iteration, Indicates the priority after the tth iteration, which is obtained based on the dynamic iteration of the initial response priority. It represents the priority of the neighboring power generation unit j adjacent to the current power generation unit i after the tth iteration, represents the neighborhood weight adjustment rate, Represents the neighborhood set of power generation unit i, i is the current power generation unit, j is the power generation unit adjacent to i, represents the weighted coefficient of the threshold sensitivity factor, Represents the threshold sensitivity factor.

[0056] Preferably, the neighborhood interaction correction term is used to achieve collaborative optimization of inter-unit priorities, avoid local regulation conflicts, and improve global resource coordination efficiency. A threshold-sensitive correction term is introduced to quantify the matching relationship between the available capacity of a single unit and the dynamic response threshold, dynamically adapt to the current regulation needs, and ensure that the strategy is synchronized with the real-time grid status. Furthermore, if the available capacity of a single unit is less than 0.2 times the dynamic response threshold, it indicates that the available capacity of the power generation unit is insufficient to support its effective participation in the grid response task. At this time, the priority after the t+1th iteration is attenuated, that is, the capacity shortage attenuation mechanism is implemented. The priority attenuation expression is as follows:

[0057] in, represents the priority after the t+1th iteration, is the priority attenuation factor.

[0058] Preferably, a capacity shortage attenuation mechanism is used to proactively eliminate inefficient units, optimize resource allocation, and prevent resource waste.

[0059] Furthermore, the post-iteration priority is evaluated for convergence. If the convergence criteria are met, the post-iteration priority is used as the iterative convergence priority. The resulting iterative convergence priorities are sorted from high to low to create a response order list. This response order list is dynamically generated to adapt to real-time changes in grid conditions.

[0060] Preferably, the convergence condition is: , is the preset convergence judgment value, when When the value reaches 0, the iteration is stopped to prevent infinite loops caused by numerical oscillation or abnormal disturbances, ensuring the reliable termination of the algorithm. The number of iterations is minimized while meeting the accuracy requirements, reducing the calculation time and meeting the stringent requirements of photovoltaic power stations for real-time response.

[0061] Preferably, the preset frequency is selected according to the grid frequency state (reference state / deviation state / emergency state). By selecting different The value of is used to balance speed and accuracy. For example, in an emergency (large frequency deviation), a relaxed preset is selected. value to speed up the response. In the reference state (small frequency deviation), select the tightened preset value to improve the adjustment accuracy.

[0062] S300: Allocate an active power target value that needs to be adjusted based on the dynamic response threshold and the response order list.

[0063] Furthermore, based on the dynamic response threshold and the response sequence list, the active power target value that needs to be adjusted is allocated, including: initializing the cumulative allocation amount; calculating the current cumulative allocation power of each power generation unit in order of iterative convergence priority from high to low in the response sequence list; if the sum of the current cumulative allocation power and the current available capacity of the power generation unit does not exceed the dynamic response threshold, the current available capacity is used as the active power target value that needs to be adjusted, and the cumulative allocation amount is updated; if the sum of the current cumulative allocation power and the current available capacity of the power generation unit exceeds the dynamic response threshold, the remaining required power value is calculated, the remaining required power value is used as the active power target value that needs to be adjusted, and after updating the cumulative allocation amount, subsequent allocation is terminated.

[0064] Specifically, initialize the cumulative allocation amount and set the cumulative allocation amount , process each power generation unit in order from high to low according to the response order list. If the sum of the current cumulative allocated power and the current power generation unit available capacity does not exceed the dynamic response threshold, that is , the current available capacity is used as the active power target value that needs to be adjusted ( ),Right now , and update the cumulative allocation, the cumulative allocation , if the sum of the current cumulative allocated power and the current available capacity of the power generation unit exceeds the dynamic response threshold, that is, , then calculate the remaining required power value and use the remaining required power value as the active power target value that needs to be adjusted, that is, , update the cumulative allocation , after updating the cumulative allocation amount, terminate the subsequent allocation.

[0065] Furthermore, record the , forming a list of active power distribution results.

[0066] Preferably, efficient and accurate allocation of active power is achieved through dynamic response thresholds and priority sorting. Power generation units are called in sequence according to priority, and the available capacity is quickly saturated to improve response speed. At the same time, the dynamic cutoff mechanism immediately terminates the allocation when the dynamic response threshold is reached, reducing computational complexity. The precise allocation and full recording of the remaining power enhance the robustness and traceability of the system. Large-capacity units can be quickly called to achieve strong intervention in an emergency, and multiple units can be fine-tuned in coordination to reduce equipment losses in the baseline state. While ensuring the stability of the grid frequency, resource utilization is optimized, ultimately achieving a dual improvement in safety and economy.

[0067] S400: Perform an automatic power generation control interlocking mechanism check on the active power target value that needs to be adjusted, and send the active power target value that needs to be adjusted that passes the automatic power generation control interlocking mechanism check to the power regulation device to control the power regulation device to adjust the grid frequency and complete fast frequency response control.

[0068] Furthermore, the automatic power generation control interlocking mechanism check of the active power target value that needs to be adjusted includes: simultaneously monitoring the hard-wired signal and the communication signal; if either the hard-wired signal or the communication signal is 1, it is determined that the active power target value that needs to be adjusted has not passed the automatic power generation control interlocking mechanism check; if the monitored hard-wired signal and the communication signal are both 0, it is determined that the active power target value that needs to be adjusted has passed the automatic power generation control interlocking mechanism check.

[0069] Furthermore, the hard-wired signal (0 / 1) here is a physical switch signal indicating the current state of the AGC (Automatic Generation Control); the communication signal (0 / 1) is the AGC status flag received via the communication network. Both the hard-wired signal and the communication signal are binary signals, indicating whether the signal is inactive or active. For both signals, 0 indicates inactive, and 1 indicates active. Hard-wired signals are typically implemented via hard wiring (such as relay contacts or dry contacts) or level signals (such as a 24V DC level). For example, if the AGC is active, the physical switch is closed, and the output is 1 (high level); if the AGC is inactive, the physical switch is open, and the output is 0 (low level). The communication signal is the status flag received from the AGC via a communication network (such as Modbus TCP / IP).

[0070] Furthermore, the hard-wired signal and the communication signal are read in real time. If either signal is 1, indicating that the AGC is active, the current FFR (Fast Frequency Response) instruction is discarded to avoid conflict with the AGC instruction. Only when the hard-wired signal and the communication signal are both 0 is the FFR instruction allowed to be issued.

[0071] Preferably, double verification of hard-wired signals (physical level) and communication signals (protocol level) is performed to prevent erroneous operation caused by abnormality of a single signal, and to ensure that when the FFR system and the AGC system work together, the grid frequency regulation will not fail due to command conflicts.

[0072] Furthermore, sending the active power target value that needs to be adjusted checked by the automatic power generation control interlocking mechanism to the power regulation device includes: encapsulating the active power target value that needs to be adjusted checked by the automatic power generation control interlocking mechanism to obtain a formatted instruction frame, and sending the formatted instruction frame to the power regulation device.

[0073] Specifically, based on the power generation unit corresponding to the active power target value to be adjusted, the inverter's IP address or Modbus device ID is obtained. According to the Modbus protocol specification, the target register address for setting active power in the target inverter is located. The target active power value to be adjusted is converted into a data format supported by the Modbus protocol, and a checksum is appended to the end of the instruction to obtain a formatted instruction frame. A connection is established with the target inverter via an independent Modbus TCP / IP channel. According to the Modbus TCP / IP protocol specification, the instruction frame is sent to the target inverter over the network. The response signal returned by the target inverter (such as a write success / failure flag) is monitored and logged. If no response is received from the target inverter or the check fails, the instruction frame is retried according to the preset strategy (up to three retries). The target inverter receives and executes the instruction frame, adjusts the output power, and achieves rapid response and stable control of the grid frequency.

[0074] Preferably, through multi-level interlocking and standardized control links, conflict-free coordination between FFR and AGC can be achieved under complex working conditions, ensuring the accurate execution of grid frequency regulation instructions and stable system operation; the preset retry strategy (up to 3 retries) automatically handles network anomalies, which can effectively reduce the probability of regulation interruption caused by transient faults.

[0075] The present invention also provides a photovoltaic power station fast frequency response control system for implementing a photovoltaic power station fast frequency response control method. The system includes a control module, the control module includes a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor executes the computer program to implement the photovoltaic power station fast frequency response control method.

[0076] An embodiment of the present invention provides a storage medium having a program stored thereon. When the program is executed by a processor, the photovoltaic power station fast frequency response control method is implemented.

[0077] An embodiment of the present invention provides a processor, which is configured to run a program, wherein the photovoltaic power station fast frequency response control method is executed when the program is run.

[0078] An embodiment of the present invention provides a device comprising a processor, a memory, and a program stored in the memory and executable on the processor. When the processor executes the program, it implements a method for controlling the rapid frequency response of a photovoltaic power plant. The device herein may be a server, a PC, a PAD, a mobile phone, or the like.

[0079] The present application also provides a computer program product, which, when executed on a data processing device, is suitable for implementing the following photovoltaic power station fast frequency response control method.

[0080] Those skilled in the art will appreciate that the embodiments of the present application may provide methods, systems, or computer program products. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0081] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0082] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0083] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps for the function specified in one or more boxes.

[0084] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0085] Memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0086] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can be implemented using any method or technology for information storage. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change RAM (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media, such as modulated data signals and carrier waves.

[0087] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0088] The above are merely embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should be included within the scope of the claims of the present application.

Claims

1. A photovoltaic power station fast frequency response control method, characterized in that: include: Collecting and preprocessing photovoltaic power station operation data, and calculating a dynamic response threshold using the preprocessed photovoltaic power station operation data; Based on the pre-processed photovoltaic power station operation data and the dynamic response threshold, dynamic priority self-organizing control is performed to obtain a response order list; Allocating an active power target value that needs to be adjusted based on the dynamic response threshold and the response order list; The active power target value that needs to be adjusted is checked by the automatic power generation control interlocking mechanism, and the active power target value that needs to be adjusted that passes the check by the automatic power generation control interlocking mechanism is sent to the power regulation device to control the power regulation device to adjust the grid frequency and complete fast frequency response control.

2. The photovoltaic power station fast frequency response control method according to claim 1, characterized in that: The calculating of the dynamic response threshold comprises: Calculate the frequency deviation between the rated grid frequency and the current average grid frequency; classifying a power grid frequency state according to an absolute value of the frequency deviation; Selecting a corresponding frequency deviation response model according to the divided grid frequency state; Dynamic response thresholds are calculated based on the frequency offset response model.

3. The photovoltaic power station fast frequency response control method according to claim 2, characterized in that: The division of the grid frequency state includes dividing the grid frequency state into a reference state, an offset state and an emergency state according to a set first deviation threshold and a second deviation threshold. When the absolute value of the frequency deviation is less than the first deviation threshold, the grid frequency state is classified as the reference state. When the first deviation threshold ≤ the absolute value of the frequency deviation < the second deviation threshold, the grid frequency state is classified as the offset state. When the absolute value of the frequency deviation is greater than or equal to the second deviation threshold, the grid frequency state is classified as an emergency state.

4. The photovoltaic power station fast frequency response control method according to claim 2, characterized in that: The frequency deviation response model includes a reference state model, an offset state model and an emergency state model.

5. The photovoltaic power station fast frequency response control method according to claim 1, characterized in that: The dynamic priority self-organizing control is performed to obtain a response sequence list, including: Calculate initial response priority; Calculate threshold sensitivity factor based on dynamic response threshold; Performing self-organizing iterative update according to the initial response priority and the threshold sensitivity factor to obtain an iterative convergence priority; Sort the iterative convergence priorities to obtain a response order list.

6. The photovoltaic power station fast frequency response control method according to claim 5, characterized in that: The self-organizing iterative update is performed according to the initial response priority and the threshold sensitivity factor to obtain an iterative convergence priority, including: Calculate the neighborhood interaction correction term and the threshold sensitivity correction term, The calculation of the neighborhood interaction correction term includes calculating the difference in initial response priority between the neighborhood unit and the current power generation unit, and summing the initial response priority differences of all neighborhood units.

7. The photovoltaic power station fast frequency response control method according to claim 1, characterized in that: The allocating the active power target value to be adjusted based on the dynamic response threshold and the response order list includes: Initialize the cumulative allocation amount; Calculate the current cumulative allocated power of each power generation unit according to the order of iterative convergence priority from high to low in the response sequence list; If the sum of the current cumulative allocated power and the current available capacity of the power generation unit does not exceed the dynamic response threshold, the current available capacity is used as the active power target value that needs to be adjusted, and the cumulative allocated amount is updated; If the sum of the current cumulative allocated power and the current available capacity of the power generation unit exceeds the dynamic response threshold, the remaining required power value is calculated and used as the active power target value that needs to be adjusted. After updating the cumulative allocated amount, subsequent allocation is terminated.

8. The photovoltaic power station fast frequency response control method according to claim 1, characterized in that: The automatic power generation control interlocking mechanism check on the active power target value that needs to be adjusted includes: Simultaneously monitor hard-wired signals and communication signals, If either the hard-wired signal or the communication signal is 1, it is determined that the active power target value that needs to be adjusted has not passed the automatic power generation control interlocking mechanism check; If the monitoring hard-wired signal and the communication signal are both 0, it is determined that the active power target value that needs to be adjusted passes the automatic power generation control interlocking mechanism check.

9. The photovoltaic power station fast frequency response control method according to claim 1, characterized in that: The step of sending the active power target value that needs to be adjusted checked by the automatic power generation control interlocking mechanism to the power regulation device includes: encapsulating the active power target value that needs to be adjusted checked by the automatic power generation control interlocking mechanism to obtain a formatted instruction frame, and sending the formatted instruction frame to the power regulation device.

10. A photovoltaic power station fast frequency response control system, characterized in that: The system includes a control module, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor executes the computer program to implement the photovoltaic power station fast frequency response control method according to any one of claims 1 to 9.

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