A method, apparatus, equipment, and storage medium for low voltage ride-through control of a photovoltaic power plant.

Abstract

This application discloses a low-voltage ride-through control method, apparatus, equipment, and storage medium for photovoltaic power plants, relating to the field of photovoltaic technology. The method includes: acquiring a multi-dimensional state dataset of the photovoltaic power plant's grid connection point and inverter in period t; determining a low-voltage ride-through control command judgment value for period t based on the multi-dimensional state dataset and a correction factor for period t; generating a low-voltage ride-through termination command if the low-voltage ride-through control command judgment value for period t is greater than or equal to a first threshold; generating a delayed low-voltage ride-through termination command if the low-voltage ride-through control command judgment value for period t is greater than or equal to a second threshold and less than the first threshold; generating a sustained low-voltage ride-through command if the low-voltage ride-through control command judgment value for period t is less than the second threshold; and executing the control command. This method can improve the accuracy of control commands and reduce the deviation in determining the timing of ride-through exit.

Description

Technical Field

[0001] This application relates to the field of photovoltaic technology, and in particular to a low voltage ride-through control method, device, equipment and storage medium for a photovoltaic power station. Background Technology

[0002] With the ongoing global energy transition, photovoltaic (PV) power generation has become an important renewable energy source. As the penetration rate of PV power plants continues to increase, their coupling with the power grid becomes increasingly close. Voltage dips caused by grid faults (such as short circuits and grounding) are becoming more prominent. Low voltage ride-through (LVRT) capability has become a core requirement for the grid-connected operation of PV power plants and is a key technical support for ensuring the safety and stability of the power grid, avoiding cascading failures caused by PV power plant disconnection, and reducing power generation losses.

[0003] However, traditional low-voltage ride-through (LVRT) control schemes for photovoltaic power plants have significant limitations, including inaccurate control commands and large deviations in determining the timing of ride-through exit. Summary of the Invention

[0004] This application provides a low-voltage ride-through control method, apparatus, equipment, and storage medium for photovoltaic power plants, which can improve the accuracy of control commands and reduce the deviation in determining the timing of ride-through exit.

[0005] To achieve the above objectives, this application adopts the following technical solution: In a first aspect, this application provides a low-voltage ride-through control method for a photovoltaic power plant, comprising: Obtain a multi-dimensional state dataset of the grid connection point and inverter of a photovoltaic power plant in period t. Based on the multi-dimensional state dataset of period t and the correction factor of period t, determine the low-voltage ride-through control command judgment value of period t. If the low-voltage ride-through control command determination value in period t is greater than or equal to the first threshold, then a control command to end low-voltage ride-through is generated. If the low-voltage ride-through control command determination value in period t is greater than or equal to the second threshold, and the low-voltage ride-through control command determination value in period t is less than the first threshold, then a control command to delay the end of low-voltage ride-through is generated. If the low-voltage ride-through control command determination value in period t is less than the second threshold, then a control command to maintain low-voltage ride-through is generated. Execute control commands.

[0006] Optionally, after executing the control command, the method further includes: Obtain the multi-dimensional state dataset of the grid connection point and inverter of the photovoltaic power plant in the (t+1)th period; Based on the multi-dimensional state datasets of the photovoltaic power plant grid connection point and inverter in period t and period t+1, evaluate the control score of the control command in period t.

[0007] Optionally, the method further includes: If the control score of the control instruction in period t is less than the score threshold in period t, then the correction factor in period t is updated to obtain the correction factor in period t+1.

[0008] Optionally, the fraction threshold for the t-th period is determined in the following way: Obtain the baseline score; Based on the grid impedance adjustment coefficient, the grid equivalent impedance in period t, the voltage drop depth adjustment coefficient, and the standardized value of the voltage drop depth in period t, the fractional reference value is corrected to obtain the fractional threshold in period t.

[0009] Optionally, updating the correction factor for period t includes: The correction factor for the t-th period is updated based on the control score of the control command in the t-th period, the score threshold of the t-th period, and the correction step size coefficient.

[0010] Optionally, obtaining the multi-dimensional state dataset of the photovoltaic power plant's grid connection point and inverter in period t includes: Obtain the multi-dimensional initial state dataset of the grid connection point and inverter of the photovoltaic power plant in period t; The multidimensional initial state dataset of period t is standardized to obtain the multidimensional state dataset of period t.

[0011] Secondly, this application provides a low-voltage ride-through control device for a photovoltaic power plant, comprising: The acquisition module is used to acquire the multi-dimensional state dataset of the grid connection point and inverter of the photovoltaic power station in period t. The determination module is used to determine the low-voltage ride-through control command judgment value for the t-th period based on the multi-dimensional state dataset of the t-th period and the correction factor of the t-th period. The generation module is used to generate a control command to end low-voltage crossing if the low-voltage crossing control command determination value of the t-th period is greater than or equal to a first threshold; generate a control command to delay the end of low-voltage crossing if the low-voltage crossing control command determination value of the t-th period is greater than or equal to a second threshold and the low-voltage crossing control command determination value of the t-th period is less than the first threshold; and generate a control command to maintain low-voltage crossing if the low-voltage crossing control command determination value of the t-th period is less than the second threshold. The control module is used to execute control commands.

[0012] Thirdly, this application provides a computing device, including a memory and a processor; The memory stores one or more computer programs, the one or more computer programs including instructions; when the instructions are executed by the processor, the computing device performs the method as described in any one of the first aspects.

[0013] Fourthly, this application provides a computer-readable storage medium for storing a computer program for performing the method as described in any one of the first aspects.

[0014] As can be seen from the above technical solution, this application has at least the following beneficial effects: In this application, by collecting multi-dimensional state data of the grid connection point of the photovoltaic power station and the inverter in the t-th cycle, and combining the correction factor to calculate the low voltage ride-through control command judgment value, the three types of control commands—end, delayed end, and maintenance of low voltage ride-through—are accurately distinguished. This fundamentally solves the problems of inaccurate control commands and large deviations in the timing of ride-through exit in traditional schemes, and effectively avoids secondary grid disturbances, inverter disconnection, or delayed active power recovery caused by improper exit timing during the voltage recovery phase.

[0015] Meanwhile, this invention achieves closed-loop quantitative verification of control effectiveness by collecting state data in the (t+1)th cycle and evaluating the control command in the tth cycle. It dynamically adjusts the score threshold based on operating parameters such as grid equivalent impedance and voltage sag depth, enabling the judgment criteria to adapt to grid strength and fault severity, significantly improving the accuracy and robustness of judgment results under different operating scenarios. When the control score does not meet the requirements, the correction factor is updated in real time based on the control deviation, forming a complete closed-loop control logic of data acquisition, command generation, execution control, effect evaluation, and parameter iteration. This allows for continuous self-optimization of control parameters without relying on complex network models. While ensuring computational efficiency and engineering feasibility, it improves the stability, accuracy, and grid adaptability of the low-voltage ride-through process, enhances the safety and reliability of photovoltaic power plant grid-connected operation, and reduces power generation loss and equipment failure risks.

[0016] It should be understood that the descriptions of technical features, technical solutions, beneficial effects, or similar language in this application do not imply that all features and advantages can be achieved in any single embodiment. Rather, it is understood that the description of a feature or beneficial effect means that a specific technical feature, technical solution, or beneficial effect is included in at least one embodiment. Therefore, the descriptions of technical features, technical solutions, or beneficial effects in this specification do not necessarily refer to the same embodiment. Furthermore, the technical features, technical solutions, and beneficial effects described in this embodiment can be combined in any suitable manner. Those skilled in the art will understand that embodiments can be implemented without one or more specific technical features, technical solutions, or beneficial effects of a particular embodiment. In other embodiments, additional technical features and beneficial effects may be identified in specific embodiments that do not embody all embodiments. Attached Figure Description

[0017] Figure 1 A flowchart illustrating a low-voltage ride-through control method for a photovoltaic power plant, provided as an embodiment of this application; Figure 2 A schematic diagram of a low voltage ride-through control device for a photovoltaic power station provided in an embodiment of this application; Figure 3 This is a schematic diagram of a computing device provided in an embodiment of this application. Detailed Implementation

[0018] The terms "first," "second," and "third," etc., used in this application specification and accompanying drawings are used to distinguish different objects, not to limit a specific order.

[0019] In the embodiments of this application, the terms "exemplary" or "for example" are used to indicate that something is an example, illustration, or description. Any embodiment or design that is described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design. Specifically, the use of the terms "exemplary" or "for example" is intended to present the relevant concepts in a specific manner.

[0020] To ensure clarity and conciseness in the description of the following embodiments, a brief introduction to the related technologies is given first: Low voltage ride-through (LVRT) refers to the ability of a photovoltaic power plant to maintain grid-connected operation within a specified voltage range and time frame when the grid voltage drops due to faults such as short circuits or grounding. At the same time, it provides necessary reactive power support to the grid and smoothly switches back to normal operation after the grid voltage recovers. It is a performance requirement for photovoltaic power plants to meet grid connection standards and ensure grid stability.

[0021] The technical problem this application aims to solve is that traditional photovoltaic power plant low voltage ride-through control schemes generally suffer from inaccurate control commands and large deviations in determining the timing of low voltage ride-through exit. During the voltage drop and recovery process in the power grid, it is easy to issue incorrect commands to immediately end low voltage ride-through, delay the end of low voltage ride-through, or maintain low voltage ride-through, which can lead to operational risks such as secondary disturbances in the power grid, inverter disconnection, delayed active power recovery, and equipment overload, making it difficult to meet the requirements for stable grid connection of photovoltaic power plants under high penetration rates.

[0022] The main reason for the above technical problems is that traditional control schemes only use a single operating parameter as the basis for judgment, without comprehensively considering the impact of multi-dimensional operating condition information on control decisions. At the same time, they lack a quantitative evaluation and closed-loop verification mechanism for the execution effect of control commands, and cannot identify control deviations in a timely manner. In addition, the judgment threshold and control parameters are all set in a fixed manner, and cannot be adaptively adjusted according to actual operating conditions such as the equivalent impedance of the power grid and the voltage drop depth. There is also no mechanism to dynamically correct control parameters based on the control effect, which leads to a mismatch between the control logic and the nonlinear and time-varying characteristics of the power grid fault. Ultimately, this results in low accuracy of low voltage ride-through command judgment and poor adaptability to operating conditions.

[0023] In view of this, embodiments of this application provide a low-voltage ride-through control method for a photovoltaic power plant, which can be executed by a processing device. This processing device can be a terminal or a server. Terminals include, but are not limited to, smartphones, tablets, laptops, personal digital assistants, or smart wearable devices. Servers can be cloud servers, such as central servers in a central cloud computing cluster or edge servers in an edge cloud computing cluster. Alternatively, servers can be located in a local data center. A local data center refers to a data center directly controlled by the user.

[0024] This application addresses the technical problems of inaccurate control commands and large deviations in the timing of low-voltage ride-through (LVRT) in traditional photovoltaic (PV) power plants. First, it collects multi-dimensional operational status data from the PV power plant's grid connection point and inverters, and standardizes this data to eliminate the impact of dimensional differences on control decisions. Then, it introduces a correction factor and calculates the control command decision value based on the standardized status data, thus distinguishing between three control commands: termination, delayed termination, and maintenance of LVRT, achieving accurate control of the ride-through process. After command execution, a control score is quantified by comparing status data from adjacent cycles to evaluate the control effect. The score threshold is dynamically adjusted based on the grid's equivalent impedance and voltage drop depth to adapt the decision criteria to different grid conditions. When the control effect does not meet requirements, the correction factor is updated in real time, forming a closed-loop control logic encompassing data acquisition, command generation, control execution, effect evaluation, and parameter iteration. This improves the accuracy and adaptability of LVRT control without relying on complex network models, fundamentally solving the problems of inaccurate exit timing and misjudgment of control commands.

[0025] To make the technical solution of this application clearer and easier to understand, the following description, in conjunction with the accompanying drawings, introduces a low-voltage ride-through control method for a photovoltaic power station provided in an embodiment of this application. Figure 1 As shown, this figure is a flowchart of a low-voltage ride-through control method for a photovoltaic power station provided in an embodiment of this application. The method includes: S201. The processing equipment acquires the multi-dimensional state dataset of the photovoltaic power station grid connection point and inverter in period t.

[0026] The grid connection point of a photovoltaic power station refers to the node where the photovoltaic power station's step-up system connects to the public power grid. It is the location for monitoring electrical quantities such as grid voltage and phase.

[0027] An inverter is a power electronic device that converts the DC power of photovoltaic modules into AC power and enables grid-connected control. It is the main device for performing low-voltage ride-through control.

[0028] The t-th cycle refers to the t-th control cycle set during the low voltage ride-through control process. The control cycle has a fixed duration, and the entire control process is executed cyclically.

[0029] A multi-dimensional state dataset refers to a collection of various electrical parameters that can comprehensively reflect the operating conditions of the power grid and the operating status of the inverter, including parameters such as grid connection point voltage, voltage phase transition, grid equivalent impedance, active power, reactive power, DC side voltage, peak current, and voltage sag depth.

[0030] The process of obtaining the multi-dimensional state dataset for period t is as follows: First, the processing equipment acquires the multi-dimensional initial state dataset of the photovoltaic power plant grid connection point and inverter in period t; then, the multi-dimensional initial state dataset in period t is standardized to obtain the multi-dimensional state dataset in period t.

[0031] A multidimensional initial state dataset refers to a set of original electrical parameters with original dimensions and numerical values ​​directly collected by the processing equipment, such as measured values ​​of voltage, power, impedance, and current.

[0032] Standardization refers to the process of converting initial data with different units and numerical ranges into a unified range using mathematical methods. The purpose is to eliminate the impact of differences in dimensions and numerical values ​​on subsequent calculations.

[0033] First, during the t-th control cycle, the processing device, as the computing unit of the entire control system, directly collects the original electrical operating parameters of the photovoltaic power station's grid connection point and the inverter. These parameters cover multiple dimensions, including grid connection point voltage, current, power, grid equivalent impedance, inverter DC side voltage, output current, active / reactive power, etc. After collection, they are integrated to form a multi-dimensional initial state dataset, which fully captures the real-time operating status of the current power grid and inverter.

[0034] Subsequently, due to the dimensional differences (e.g., voltage is in volts, power in kilowatts) and significant variations in numerical values ​​of the collected raw electrical parameters, direct use in calculations would introduce deviations and affect the accuracy of control commands. Therefore, the processing equipment standardizes this raw data. Through a preset standardization formula, parameters with different dimensions and numerical ranges are uniformly converted into dimensionless, standardized data with consistent value ranges, ultimately yielding a multi-dimensional state dataset that can be used for subsequent control calculations.

[0035] The purpose of this process is to eliminate computational interference caused by the inherent characteristics of the raw data, ensure the accuracy and reliability of subsequent control command judgment values, provide solid data support for the processing equipment to accurately generate low-voltage ride-through control commands (maintain, delay termination, terminate ride-through), and ensure the scientific nature and accuracy of the entire low-voltage ride-through control logic.

[0036] The calculation expression for standardization is:

[0037] in, This represents the standardized value of the i-th dimension state parameter in period t. This represents the original measured value of the i-th dimension of the electrical operating parameters in the t-th period, i.e., the unprocessed data (such as grid connection voltage, inverter DC side current, etc.) directly collected by the processing equipment from the grid connection point or inverter of the photovoltaic power station. This represents the historical minimum value of the i-th dimension electrical operating parameter. It is the lower limit value of this dimension parameter obtained based on the preset operating conditions of the photovoltaic power plant or through statistical analysis of historical operating data, and serves as the benchmark lower limit for standardization. The maximum historical value of the i-th dimension electrical operating parameter is the upper limit of this dimension parameter obtained based on the preset operating conditions of the photovoltaic power plant or through the statistics of historical operating data, and is used as the benchmark upper limit for standardization processing.

[0038] S202. The processing device determines the low-voltage ride-through control command judgment value for the t-th period based on the multi-dimensional state dataset of the t-th period and the correction factor of the t-th period.

[0039] The correction factor for cycle t is an adjustable coefficient used to dynamically adjust the calculation results. It can be updated based on the control effect of the previous cycle to compensate for calculation deviations caused by changes in operating conditions and improve the accuracy of command judgment.

[0040] The low-voltage ride-through control command determination value is a quantitative value calculated by the processing equipment. It is used to determine the current operating status of the power grid and the inverter, and is the basis for the final decision to output the command to end low-voltage ride-through, delay the end of low-voltage ride-through, or maintain low-voltage ride-through.

[0041] The processing equipment is based on standardized multi-dimensional state data within the t-th control cycle. At the same time, a correction factor for the t-th cycle is introduced to dynamically adjust the calculation process. A quantified judgment value is obtained through a preset calculation method. This judgment value is used to distinguish and generate corresponding low voltage ride-through control commands, so that the control decision not only fits the real-time operating conditions but also has adaptive correction capabilities, thereby improving the accuracy of command judgment.

[0042] The expression for calculating the low-voltage ride-through control command determination value is as follows:

[0043] in, This represents the low-voltage ride-through control command determination value for period t. This represents the correction factor for period t. This represents the static weight coefficient of the i-th dimension state parameter. This represents the standardized value of the i-th dimension state parameter in period t. This represents the coupling term adjustment coefficient, used to quantify the impact of the coupling effect between multi-dimensional state parameters on the control command determination value. This represents the standardized value of the grid connection point voltage in period t. This represents the standardized value of the equivalent impedance of the power grid in period t. This represents the standardized value of the inverter's output active power in period t. This represents the standardized value of the inverter's output reactive power in period t. This represents the standardized value of the voltage drop depth in period t. The standardized value represents the phase jump of the grid-connected voltage at the t-th cycle.

[0044] S203. If the low-voltage ride-through control command determination value of the t-th period is greater than or equal to the first threshold, then generate a control command to end the low-voltage ride-through.

[0045] The first threshold is a preset judgment threshold, representing the critical condition that the state of the power grid and the inverter has recovered to meet the condition of safely exiting the low-voltage ride-through mode. When the judgment value reaches or exceeds the first threshold, the command to end the low-voltage ride-through can be triggered.

[0046] The control command to end low-voltage ride-through is a control command issued by the processing equipment to the inverter. It is used to instruct the inverter to immediately exit the low-voltage ride-through operation mode and return to the normal grid-connected control state, including restoring active power closed-loop control and canceling reactive power current limiting constraints.

[0047] When the low-voltage ride-through control command judgment value calculated by the processing equipment for cycle t reaches or exceeds the preset first threshold, it means that the current grid fault has been effectively mitigated, the grid voltage has returned to a stable level, and all operating parameters meet the conditions for safely exiting the low-voltage ride-through mode. At this time, the processing equipment will generate and issue a control command to end the low-voltage ride-through, instructing the inverter to complete the switching of operating modes.

[0048] Upon receiving this command, the inverter will smoothly switch from fault-support mode back to normal grid-connected operation mode. Specific actions include exiting reactive power current limiting constraints, restoring active power closed-loop control, adjusting the DC-side voltage to its rated value, and gradually restoring normal power generation and grid connection. The purpose of this control strategy is to avoid prolonged maintenance of low-voltage ride-through mode, which could lead to delayed active power recovery and affect the photovoltaic power plant's power generation efficiency. Simultaneously, it prevents prolonged fault-support mode from causing inverter overload and extends equipment lifespan.

[0049] The first threshold, serving as the boundary between immediate termination of cross-connection and delayed termination, is set in accordance with the standards for stable grid operation, ensuring precise timing of command triggering. In summary, this logic not only guarantees the normal operation of the photovoltaic power station after the grid stabilizes but also avoids equipment or grid risks caused by improper control, further improving the operational reliability and economy of the photovoltaic grid-connected system, and keeping it within a reasonable logical closed loop.

[0050] S204. If the low-voltage ride-through control command determination value of the t-th cycle is greater than or equal to the second threshold, and the low-voltage ride-through control command determination value of the t-th cycle is less than the first threshold, then a control command to delay the end of low-voltage ride-through is generated.

[0051] The second threshold is a preset judgment threshold, representing the critical condition when the grid and inverter are in the transition recovery phase. This second threshold is lower than the first threshold and is used to distinguish the boundary between maintaining low-voltage ride-through and delaying the end of low-voltage ride-through.

[0052] The control command to delay the end of low-voltage ride-through is a control command sent by the processing equipment to the inverter. It is used to instruct the inverter to gradually restore active power output at a controllable rate while maintaining reactive power support. After the operating conditions are reassessed in the next control cycle, a decision will be made on whether to completely exit the low-voltage ride-through mode to achieve a smooth transition.

[0053] When the low-voltage ride-through control command judgment value calculated by the processing equipment for cycle t is between the second threshold and the first threshold, it indicates that the current power grid operating condition is in the transition recovery phase. The grid voltage has shown a recovery trend, and the fault has been alleviated, but it has not yet reached a stable state where it can safely and immediately exit the low-voltage ride-through mode. At this time, the processing equipment will generate and issue a control command to delay the end of the low-voltage ride-through, guiding the inverter to execute the corresponding control strategy.

[0054] Upon receiving this instruction, the inverter will neither immediately exit the fault support mode nor continue to maintain a complete fault state. Instead, it will gradually restore active power output at a preset, controllable rate, prioritizing the reactive power support of the grid. This strategy avoids secondary disturbances caused by prematurely exiting the low-voltage ride-through mode, which could lead to insufficient reactive power support from the grid and a subsequent voltage drop. It also prevents the problem of delayed active power recovery and reduced photovoltaic power plant efficiency caused by excessively maintaining the fault ride-through state.

[0055] In summary, this control logic enables a smooth transition during grid fault recovery, ensuring grid stability while also considering the operational efficiency of photovoltaic power plants. It ensures that the entire low-voltage ride-through control process is scientific and controllable, further enhancing the stability and reliability of the photovoltaic grid-connected system.

[0056] The first and second thresholds are preset according to the grid connection standards of photovoltaic power plants and the rated parameters of inverters. Under normal operating conditions, the first threshold is set to 0.8~0.9 and the second threshold is set to 0.5~0.6. Under weak grid conditions or deep voltage drop conditions, the threshold values ​​can be appropriately reduced according to the actual operating conditions to improve the adaptability and reliability of the low-voltage ride-through control strategy to complex grid environments.

[0057] S205. If the low-voltage ride-through control command determination value of the t-th period is less than the second threshold, then generate a control command to maintain low-voltage ride-through.

[0058] The control command to maintain low-voltage ride-through is a control command issued by the processing equipment to the inverter. It is used to instruct the inverter to continue to maintain the low-voltage ride-through operation mode, prioritize the provision of reactive power support to the grid, limit active power output, suppress DC side overvoltage and bridge arm overcurrent, until the operating conditions are reassessed in the next control cycle.

[0059] When the low-voltage ride-through control command judgment value calculated by the processing equipment in cycle t is less than the second threshold, it indicates that the current grid fault has not been alleviated, the voltage drop is significant, and the grid operating condition remains unstable. At this time, the processing equipment will generate and issue a control command to maintain low-voltage ride-through, enabling the inverter to continue in fault support mode, prioritizing the grid's reactive power support needs, limiting active power output to avoid equipment overload, ensuring the photovoltaic power station continues to operate connected to the grid during the fault, and preventing grid disconnection from triggering a cascading grid fault.

[0060] The purpose of this judgment logic is that the second threshold serves as the boundary between maintaining low-voltage ride-through and delaying the termination of low-voltage ride-through. When the judgment value is lower than this second threshold, it indicates that the power grid is still in a fault state. If the grid abruptly exits the ride-through mode, it will lead to insufficient reactive power support capacity, further exacerbating voltage drops and even causing large-scale power outages. Therefore, the inverter needs to continue to maintain fault support mode, stabilizing the grid voltage by prioritizing reactive current output, while limiting active power output within a safe threshold to prevent the inverter from disconnecting from the grid due to overload.

[0061] Through this control strategy, photovoltaic power plants can continue to connect to the grid during faults, providing necessary reactive power support to the grid, effectively reducing the risk of fault expansion, and ensuring the stable operation of the entire power system.

[0062] S206, Execute control instructions.

[0063] Control commands are commands generated by the processing equipment after comparing the low-voltage ride-through control command judgment value of the t-th cycle with the threshold. They include three types: end low-voltage ride-through, delay end low-voltage ride-through, and maintain low-voltage ride-through. They are commands used to control the inverter's operating mode.

[0064] The processing device will calculate the low voltage ride-through control command judgment value based on the multi-dimensional state data and correction factor of the t-th period, and combine it with the preset threshold range to complete the logical judgment, generate the control command to end the low voltage ride-through, delay the end of the low voltage ride-through, or maintain the low voltage ride-through, and send the command to the photovoltaic inverter through the high-speed communication link.

[0065] Upon receiving the command, the inverter will immediately activate the corresponding control strategy: if the command is to terminate the low-voltage ride-through, it will quickly exit the reactive power current limiting mode, restore the active power closed-loop control, and adjust the DC side voltage to the rated value, thereby achieving a smooth switch from fault support mode to normal grid-connected mode. If the low-voltage ride-through command is to be terminated later, active power output will be gradually increased at a preset rate while maintaining reactive power support, so as to reserve a transition window for the grid voltage to stabilize and recover. To maintain the low-voltage ride-through command, reactive current will continue to be output first, active power will be limited within the safe threshold, DC side overvoltage and bridge arm overcurrent will be suppressed, and grid connection will be ensured during the fault.

[0066] Through this complete instruction transmission and execution process, photovoltaic power plants can respond to changes in grid operating conditions, effectively avoiding risks such as secondary disturbances, inverter disconnection, or equipment overload caused by improper control. At the same time, it provides a stable operating foundation and reliable data support for the processing equipment to collect multi-dimensional status data in the t+1 cycle, quantitatively evaluate the execution effect of control instructions, and dynamically correct control parameters.

[0067] After executing the control instructions, the method further includes: First, the processing equipment acquires a multi-dimensional state dataset of the photovoltaic power plant's grid connection point and inverter in the t+1th cycle.

[0068] The (t+1)th cycle refers to the next control cycle immediately following the tth control cycle. It is used to collect the system status after the control command in the tth cycle has been executed.

[0069] After generating and executing the low-voltage ride-through control command in cycle t, in order to evaluate the effect of this control, the processing equipment will collect multiple operating parameters of the photovoltaic power station grid connection point and inverter again in the next control cycle t+1 to form a multi-dimensional state dataset for cycle t+1, so as to compare it with the data of cycle t and realize the quantitative evaluation of the effect of the control command.

[0070] Then, the processing device evaluates the control score of the control command in the t-th period based on the multi-dimensional state dataset of the photovoltaic power plant grid connection point and inverter in the t-th period and the multi-dimensional state dataset in the t+1-th period.

[0071] The multi-dimensional state dataset of the t+1th cycle refers to the set of multi-dimensional parameters that reflect the system's operating state after the execution of the control command, collected and standardized within the t+1th control cycle after the control command in the tth cycle is executed.

[0072] The control command for cycle t refers to the low-voltage ride-through control command generated by the processing device in cycle t after comparing the judgment value with the threshold. It includes three types: ending low-voltage ride-through, delaying the end of low-voltage ride-through, and maintaining low-voltage ride-through.

[0073] The control score is an evaluation index obtained by the processing equipment through quantitative calculation by comparing the state data before and after control. It is used to objectively measure the execution effect and accuracy of the control command in cycle t.

[0074] After completing the execution of the low voltage ride-through control command in cycle t, the processing equipment will enter the closed-loop effect evaluation stage: First, the multi-dimensional operating status data of the grid connection point and the inverter in cycle t+1 will be collected synchronously to form a snapshot of the system status after the execution of the control command. Subsequently, the snapshot is precisely compared with the multi-dimensional state data of the t-th cycle before the execution of the control command. The focus is on analyzing the deviation between the actual changes of each dimension parameter (such as grid connection point voltage, reactive power support capability, active power recovery rate, DC side voltage stability, etc.) and the expected target of the command. Based on this, the deviations of each dimension are weighted and normalized through a preset quantitative evaluation formula to finally obtain the control score of the control command in the t-th cycle.

[0075] This process not only enables an objective and quantitative assessment of the control effect, but also provides a reliable quantitative basis for the dynamic updating of subsequent correction factors, enabling the entire low-voltage ride-through control system to have self-optimization capabilities and effectively improving the accuracy of control decisions under different operating conditions.

[0076] The expression for calculating the control fraction of the control instruction in cycle t is:

[0077] in, The control score represents the control command in cycle t. It is an indicator for quantitatively evaluating the control effect, with a value range of [0,1]. The closer the value is to 1, the better the control effect and the higher the matching degree between the command and the operating condition. This represents the evaluation weight coefficient of the i-th dimension state parameter, used to characterize the importance of this dimension parameter to the evaluation of control effectiveness. , This represents the standardized measured value of the i-th dimension state parameter in the (t+1)-th period, reflecting the actual state of the system after the control command is executed. This represents the standardized target reference value of the i-th dimension state parameter corresponding to the t-th cycle control command. It is the ideal state that the control command expects to achieve and is set differently according to the command type (end / delayed end / maintain low-voltage ride-through). Represents an infinitesimal quantity, with values ​​ranging from 1 to 10. This is used to avoid calculation errors caused by a denominator of 0.

[0078] If the control score of the control instruction in period t is less than the score threshold in period t, then the correction factor in period t is updated to obtain the correction factor in period t+1.

[0079] The fraction threshold for period t is a threshold for judging the effect of dynamic adjustment based on real-time operating conditions such as grid equivalent impedance and voltage drop depth, rather than a fixed value. It is used to determine whether the control fraction has reached the expected accuracy requirements and is the critical condition for triggering the update of the correction factor.

[0080] The fraction threshold for period t is determined in the following way: First, the processing device obtains the baseline score.

[0081] The score baseline value is a fixed reference value that is set in advance and used as the basis for evaluating the control effect. It is the initial basis for calculating the score threshold of the t-th period. It does not change with the real-time operating conditions and represents the basic requirements that the control score needs to achieve under normal and standard operating conditions.

[0082] Before calculating the current periodic dynamic fraction threshold, the processing device first reads or calls a pre-set fixed reference value from its own storage area, which is the fraction baseline value. This serves as the basis and starting point for subsequent correction based on real-time operating conditions such as grid impedance and voltage drop depth to obtain the final usable dynamic fraction threshold.

[0083] Then, the processing equipment corrects the fractional reference value based on the grid impedance adjustment coefficient, the grid equivalent impedance in period t, the voltage drop depth adjustment coefficient, and the voltage drop depth standardization value in period t to obtain the fractional threshold in period t.

[0084] The grid impedance adjustment coefficient is a preset fixed coefficient used to quantify the influence of the grid equivalent impedance on the fractional threshold. It is determined by the mechanism analysis of the photovoltaic grid-connected system, and its value determines the adjustment range of the fractional threshold when the grid impedance changes.

[0085] The equivalent impedance of the grid in period t refers to the equivalent impedance value of the grid side at the grid connection point of the photovoltaic power station within the control period t. It reflects the current strength and weakness of the grid (the greater the impedance, the weaker the grid) and is a real-time operating parameter that affects the criteria for judging the control effect.

[0086] The voltage sag depth adjustment coefficient is a preset fixed coefficient used to quantify the impact of voltage sag depth on the fractional threshold. In conjunction with the grid impedance adjustment coefficient, it enables the fractional threshold to adaptively adapt to different fault levels.

[0087] The standardized value of voltage drop depth in cycle t refers to the dimensionless value (range [0,1]) of the voltage drop depth at the grid connection point of the photovoltaic power station within the control cycle t after standardization, which accurately reflects the severity of the current grid voltage drop.

[0088] After obtaining the fractional reference value, the processing equipment calls upon preset grid impedance adjustment coefficients and voltage sag depth adjustment coefficients. Simultaneously, it extracts two real-time operating parameters: the grid equivalent impedance in period t and the standardized voltage sag depth in period t. Using a preset correction formula, the real-time operating parameters are combined with the fixed adjustment coefficients to dynamically correct the fractional reference value. Specifically, the larger the grid equivalent impedance (weaker grid) and the higher the standardized voltage sag depth (more severe fault), the more the corrected fractional threshold will be adjusted accordingly to lower the judgment standard for control effectiveness and adapt to complex operating conditions such as weak grids and deep faults. Conversely, the more stable the grid condition and the less severe the voltage sag, the closer the fractional threshold will be to the fractional reference value, raising the judgment standard and ensuring control accuracy.

[0089] The expression for calculating the fraction threshold in period t is:

[0090] in, The threshold value for the t-th period is a real-time judgment threshold obtained after dynamic correction. It is used to determine whether the control score for the t-th period meets the standard and is adaptively adjusted according to the power grid operating conditions. The baseline value represents a pre-set, fixed reference value that serves as the initial basis for calculating the dynamic score threshold, representing the judgment standard under normal operating conditions. This represents the grid impedance adjustment coefficient, a preset fixed coefficient used to quantify the influence of the grid's equivalent impedance on the fractional threshold, and determines the adjustment range of the threshold when the grid impedance changes. This represents the standardized value of the equivalent impedance of the power grid in period t. This represents the reference point for the standardized value of the power grid's equivalent impedance, signifying the critical condition of a medium-strength power grid and used to determine whether the current power grid is excessively strong or weak. This represents the voltage sag depth adjustment coefficient, a preset fixed coefficient used to quantify the impact of voltage sag depth on the fractional threshold. Together with the grid impedance adjustment coefficient, it enables adaptive adjustment of the threshold. This represents the standardized value of the voltage drop depth in period t.

[0091] Through this correction process, the originally fixed score benchmark value is transformed into a dynamic score threshold that fits the actual operating conditions of the t-th cycle. This enables the judgment criteria for control effect to adapt to different power grid strengths and fault degrees, avoiding judgment distortion caused by fixed thresholds. It provides a scientific and reasonable critical basis for subsequent comparison of control scores and updating of correction factors, further improving the adaptability and accuracy of low voltage ride-through control.

[0092] The correction factor for cycle t+1 is a new coefficient obtained by updating the correction factor for cycle t when the control effect in cycle t is not up to standard. It will be used as the input for calculating the control command judgment value in cycle t+1 to achieve adaptive optimization of the control logic.

[0093] The specific process for updating the correction factor in period t is as follows: The processing device updates the correction factor for the t-th period based on the control score of the control command for the t-th period, the score threshold for the t-th period, and the correction step size coefficient.

[0094] The correction step size coefficient is a preset fixed coefficient used to control the update amplitude of the correction factor, avoid control logic oscillation due to excessive single correction amplitude, and ensure that the correction process is smooth and controllable. Its value determines the response speed of the correction factor to the deviation of the control effect.

[0095] When the control score in period t falls below the score threshold, the processing device will initiate the correction factor update process: First, the deviation between the control score and the score threshold is calculated. The larger the deviation, the worse the adaptability of the current control command judgment value to the actual working condition. Then, the deviation value is combined with the preset correction step size coefficient, and the correction factor of the t-th period is corrected by the preset update formula.

[0096] If the control score is significantly lower than the score threshold, the correction factor will be adjusted substantially to quickly correct the control deviation; if the control score is slightly lower than the score threshold, it will be finely adjusted in smaller steps to avoid oscillations in the control logic.

[0097] The expression for updating the correction factor in period t is:

[0098] in, This indicates that the updated correction factor for the (t+1)th cycle will be used as input for calculating the control command decision value in the next cycle, thereby achieving adaptive optimization of the control logic. This represents the correction factor for period t. This represents the correction step size coefficient, a preset fixed coefficient used to control the update magnitude of the correction factor. This prevents control logic oscillations caused by excessively large single correction magnitudes, ensuring a smooth and controllable correction process. This represents the fractional threshold for the t-th period. This represents the control fraction of the control instruction in cycle t.

[0099] Add boundary constraints during the correction factor update process, if the calculated... ,Pick ;like ,Pick When the control effect meets the target, directly order... The current correction factor will be used in the next cycle.

[0100] Through this update process, the original correction factor is optimized into a new coefficient that better reflects the actual operating conditions of the t-th cycle, so that the calculation of the control command judgment value for the next cycle can more accurately reflect the operating status of the power grid and the inverter, thereby improving the accuracy and adaptability of subsequent control decisions, effectively avoiding control failure or misjudgment caused by fixed parameters, and ensuring that the entire low voltage ride-through control system always maintains the optimal operating state under complex operating conditions.

[0101] Based on the above description, this application has the following beneficial effects: In this application, by collecting multi-dimensional state data of the grid connection point of the photovoltaic power station and the inverter in the t-th cycle, and combining the correction factor to calculate the low voltage ride-through control command judgment value, the three types of control commands—end, delayed end, and maintenance of low voltage ride-through—are accurately distinguished. This fundamentally solves the problems of inaccurate control commands and large deviations in the timing of ride-through exit in traditional schemes, and effectively avoids secondary grid disturbances, inverter disconnection, or delayed active power recovery caused by improper exit timing during the voltage recovery phase.

[0102] Meanwhile, this invention achieves closed-loop quantitative verification of control effectiveness by collecting state data in the (t+1)th cycle and evaluating the control command in the tth cycle. It dynamically adjusts the score threshold based on operating parameters such as grid equivalent impedance and voltage sag depth, enabling the judgment criteria to adapt to grid strength and fault severity, significantly improving the accuracy and robustness of judgment results under different operating scenarios. When the control score does not meet the requirements, the correction factor is updated in real time based on the control deviation, forming a complete closed-loop control logic of data acquisition, command generation, execution control, effect evaluation, and parameter iteration. This allows for continuous self-optimization of control parameters without relying on complex network models. While ensuring computational efficiency and engineering feasibility, it improves the stability, accuracy, and grid adaptability of the low-voltage ride-through process, enhances the safety and reliability of photovoltaic power plant grid-connected operation, and reduces power generation loss and equipment failure risks.

[0103] The above text combined Figure 1 The low voltage ride-through control method for photovoltaic power plants provided in the embodiments of this application has been described in detail. The apparatus and equipment provided in the embodiments of this application will be described below with reference to the accompanying drawings.

[0104] like Figure 2 As shown in the figure, this is a schematic diagram of a low-voltage ride-through control device for a photovoltaic power station provided in an embodiment of this application. The device includes: Module 301 is used to acquire the multi-dimensional state dataset of the grid connection point and inverter of the photovoltaic power station in period t. The determination module 302 is used to determine the low-voltage ride-through control command judgment value for the t-th period based on the multi-dimensional state dataset of the t-th period and the correction factor of the t-th period. The generation module 303 is used to generate a control command to end low-voltage crossing if the low-voltage crossing control command determination value of the t-th period is greater than or equal to a first threshold; generate a control command to delay the end of low-voltage crossing if the low-voltage crossing control command determination value of the t-th period is greater than or equal to a second threshold and the low-voltage crossing control command determination value of the t-th period is less than the first threshold; and generate a control command to maintain low-voltage crossing if the low-voltage crossing control command determination value of the t-th period is less than the second threshold. Control module 304 is used to execute control commands.

[0105] Optionally, the generation module 303 is also used to obtain the multi-dimensional state dataset of the photovoltaic power plant grid connection point and inverter in the t+1 period; and to evaluate the control score of the control command in the t period based on the multi-dimensional state dataset of the photovoltaic power plant grid connection point and inverter in the t period and the multi-dimensional state dataset in the t+1 period.

[0106] Optionally, the determining module 302 is further configured to update the correction factor of the t-th period if the control score of the control instruction in the t-th period is less than the score threshold of the t-th period, so as to obtain the correction factor of the (t+1)-th period.

[0107] Optionally, module 302 is used to obtain the score baseline value; Based on the grid impedance adjustment coefficient, the grid equivalent impedance in period t, the voltage drop depth adjustment coefficient, and the standardized value of the voltage drop depth in period t, the fractional reference value is corrected to obtain the fractional threshold in period t.

[0108] Optionally, the determining module 302 is specifically used to update the correction factor for the t-th period based on the control score of the control instruction for the t-th period, the score threshold for the t-th period, and the correction step size coefficient.

[0109] Optionally, module 302 is specifically used to obtain a multi-dimensional initial state dataset of the photovoltaic power plant grid connection point and inverter in period t. The multidimensional initial state dataset of period t is standardized to obtain the multidimensional state dataset of period t.

[0110] The low-voltage ride-through control device for a photovoltaic power plant according to the embodiments of this application can correspond to the execution of the method described in the embodiments of this application, and the other operations and / or functions of each module / unit of the low-voltage ride-through control device for the photovoltaic power plant are respectively for realizing Figure 1 For the sake of brevity, the corresponding processes of each method in the illustrated embodiments will not be described in detail here.

[0111] This application also provides a computing device. For example... Figure 3 As shown in the figure, this is a schematic diagram of a computing device provided in an embodiment of this application. The computing device 700 includes a bus 701, a processor 702, a communication interface 703, and a memory 704. The processor 702, the memory 704, and the communication interface 703 communicate with each other via the bus 701.

[0112] The 701 bus can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, Figure 3 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0113] The processor 702 can be any one or more of the following processors: central processing unit (CPU), graphics processing unit (GPU), microprocessor (MP), or digital signal processor (DSP).

[0114] The communication interface 703 is used for external communication.

[0115] Memory 704 may include volatile memory, such as random access memory (RAM). Memory 704 may also include non-volatile memory, such as read-only memory (ROM), flash memory, hard disk drive (HDD), or solid state drive (SSD).

[0116] The memory 704 stores executable code, and the processor 702 executes the executable code to perform the aforementioned low voltage ride-through control method for the photovoltaic power plant.

[0117] Specifically, in achieving Figure 2 In the case of the illustrated embodiment, and Figure 2In the case where the modules or units of the low-voltage ride-through control device for the photovoltaic power plant described in the embodiment are implemented through software, the following steps are executed: Figure 2 The software or program code required for the functions of each module / unit can be partially or entirely stored in the memory 704. The processor 702 executes the program code corresponding to each unit stored in the memory 704 to execute the aforementioned low-voltage ride-through control method for photovoltaic power plants.

[0118] This application also provides a computer-readable storage medium. The computer-readable storage medium can be any available medium capable of being stored by a computing device, or a data storage device such as a data center containing one or more available media. The available medium can be a magnetic medium (e.g., floppy disk, hard disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., solid-state drive). The computer-readable storage medium includes instructions that instruct a computing device to execute the aforementioned low-voltage ride-through control method for a photovoltaic power plant.

[0119] This application also provides a computer program product comprising one or more computer instructions. When the computer instructions are loaded and executed on a computing device, all or part of the processes or functions described in this application are generated.

[0120] The computer instructions may be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions may be transmitted from one website, computer, or data center to another website, computer, or data center via wired (e.g., coaxial cable, fiber optic, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means.

[0121] When the computer program product is executed by a computer, the computer executes any of the aforementioned low-voltage ride-through control methods for photovoltaic power plants. The computer program product can be a software installation package; when any of the aforementioned low-voltage ride-through control methods for photovoltaic power plants needs to be used, the computer program product can be downloaded and executed on the computer.

[0122] The descriptions of the processes or structures corresponding to the above figures each have their own emphasis. For parts of a process or structure that are not described in detail, please refer to the relevant descriptions of other processes or structures.

[0123] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions within the technical scope disclosed in this application should be covered within the scope of protection of this application.

Claims

1. A low-voltage ride-through control method for a photovoltaic power station, characterized in that, The method includes: Obtain a multi-dimensional state dataset of the grid connection point and inverter of a photovoltaic power plant in period t. Based on the multi-dimensional state dataset of period t and the correction factor of period t, determine the low-voltage ride-through control command judgment value of period t. The correction factor for period t is an adjustable coefficient used to dynamically adjust the calculation results. It can be updated based on the control effect of the previous period to compensate for calculation deviations caused by changes in operating conditions. The expression for calculating the low-voltage ride-through control command determination value is as follows: in, This represents the low-voltage ride-through control command determination value for period t. This represents the correction factor for period t. This represents the static weight coefficient of the i-th dimension state parameter. This represents the standardized value of the i-th dimension of the state parameter in period t. This represents the adjustment coefficient for the coupling term. This represents the standardized value of the grid connection point voltage in period t. This represents the standardized value of the equivalent impedance of the power grid in period t. This represents the standardized value of the inverter's output active power in period t. This represents the standardized value of the inverter's output reactive power in period t. This represents the standardized value of the voltage drop depth in period t. The standardized value representing the phase jump of the grid-connected voltage at the t-th period; If the low-voltage ride-through control command determination value in period t is greater than or equal to the first threshold, then a control command to end low-voltage ride-through is generated. If the low-voltage ride-through control command determination value in period t is greater than or equal to the second threshold, and the low-voltage ride-through control command determination value in period t is less than the first threshold, then a control command to delay the end of low-voltage ride-through is generated. If the low-voltage ride-through control command determination value in period t is less than the second threshold, then a control command to maintain low-voltage ride-through is generated. Execute control commands.

2. The method according to claim 1, characterized in that, After executing the control instructions, the method further includes: Obtain the multi-dimensional state dataset of the grid connection point and inverter of the photovoltaic power plant in the (t+1)th period; Based on the multi-dimensional state datasets of the photovoltaic power plant grid connection point and inverter in period t and period t+1, evaluate the control score of the control command in period t.

3. The method according to claim 2, characterized in that, The method further includes: If the control score of the control instruction in period t is less than the score threshold in period t, then the correction factor in period t is updated to obtain the correction factor in period t+1.

4. The method according to claim 3, characterized in that, The fraction threshold for the t-th period is determined in the following way: Obtain the baseline score; Based on the grid impedance adjustment coefficient, the grid equivalent impedance in period t, the voltage drop depth adjustment coefficient, and the standardized value of the voltage drop depth in period t, the fractional reference value is corrected to obtain the fractional threshold in period t.

5. The method according to claim 3, characterized in that, The update of the correction factor for period t includes: The correction factor for the t-th period is updated based on the control score of the control command in the t-th period, the score threshold of the t-th period, and the correction step size coefficient.

6. The method according to claim 1, characterized in that, The acquisition of the multi-dimensional state dataset of the photovoltaic power plant grid connection point and inverter in period t includes: Obtain the multi-dimensional initial state dataset of the grid connection point and inverter of the photovoltaic power plant in period t; The multidimensional initial state dataset of period t is standardized to obtain the multidimensional state dataset of period t.

7. A low-voltage ride-through control device for a photovoltaic power station, characterized in that, The device includes: The acquisition module is used to acquire the multi-dimensional state dataset of the grid connection point and inverter of the photovoltaic power station in period t. The determination module is used to determine the low-pressure ride-through control command judgment value for period t based on the multi-dimensional state dataset of period t and the correction factor of period t. The correction factor of period t is an adjustable coefficient used to dynamically adjust the calculation results, which can be updated according to the control effect of the previous period to compensate for calculation deviations caused by changes in operating conditions. The calculation expression for the low-pressure ride-through control command judgment value is as follows: in, This represents the low-voltage ride-through control command determination value for period t. This represents the correction factor for period t. This represents the static weight coefficient of the i-th dimension state parameter. This represents the standardized value of the i-th dimension of the state parameter in period t. This represents the adjustment coefficient for the coupling term. This represents the standardized value of the grid connection point voltage in period t. This represents the standardized value of the equivalent impedance of the power grid in period t. This represents the standardized value of the inverter's output active power in period t. This represents the standardized value of the inverter's output reactive power in period t. This represents the standardized value of the voltage drop depth in period t. The standardized value representing the phase jump of the grid-connected voltage at the t-th period; The generation module is used to generate a control command to end low-voltage crossing if the low-voltage crossing control command determination value of the t-th period is greater than or equal to a first threshold; generate a control command to delay the end of low-voltage crossing if the low-voltage crossing control command determination value of the t-th period is greater than or equal to a second threshold and the low-voltage crossing control command determination value of the t-th period is less than the first threshold; and generate a control command to maintain low-voltage crossing if the low-voltage crossing control command determination value of the t-th period is less than the second threshold. The control module is used to execute control commands.

8. The apparatus according to claim 7, characterized in that, The generation module is also used to obtain a multi-dimensional state dataset of the photovoltaic power plant grid connection point and inverter in the (t+1)th cycle; and to evaluate the control score of the control command in the (t)th cycle based on the multi-dimensional state dataset of the photovoltaic power plant grid connection point and inverter in the (t+1)th cycle.

9. A computing device, characterized in that, Including memory and processor; The memory stores one or more computer programs, the one or more computer programs including instructions; when the instructions are executed by the processor, the computing device performs the method as described in any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium is used to store a computer program for performing the method as described in any one of claims 1 to 6.

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