Photovoltaic power station grid-connected adjustment method and system for large-scale power grid safety guarantee

Abstract

The invention discloses a photovoltaic power station grid-connected adjustment method and system for large-scale power grid safety guarantee, and relates to the related field of power system adjustment, and the method comprises the steps: building a grid-connected topological structure of a photovoltaic power station in a preset region and a conventional power grid; a first grid-connected node is extracted, photovoltaic output grid-connected current monitoring and traditional power grid grid-connected current monitoring are carried out, photovoltaic inverter current fluctuation suppression adaptability analysis is carried out according to a first double-path current monitoring result, and a first photovoltaic suppression adaptation index is generated; if the adaptive index is smaller than the preset adaptive index, bidirectional current fluctuation suppression balance optimization of the photovoltaic inverter and the traditional power grid is executed, and a first bidirectional suppression strategy is determined; and grid-connected adjustment of the first grid-connected node is carried out according to the first bidirectional suppression strategy. The technical problem that existing photovoltaic power station grid-connected adjustment is insufficient in adjustment accuracy and effectiveness is solved, and the technical effect of improving the photovoltaic power station grid-connected adjustment accuracy and effectiveness is achieved.

Description

Technical Field

[0001] The present application relates to fields related to power system regulation, and in particular to a photovoltaic power station grid-connected regulation method and system for large-scale power grid security assurance. Background Art

[0002] In the field of power systems, large-scale power grid security is a key issue to ensure stable energy supply and maintain stable social and economic operation. Among them, the grid-connected regulation of photovoltaic power stations is crucial to ensure the security of large-scale power grids. Usually, when photovoltaic power stations are connected to the grid, they mainly rely on inverters to cooperate with the frequency, voltage and other parameters of the traditional power grid to achieve grid-connected operation. However, since photovoltaic power generation is affected by many factors such as light intensity and weather conditions, the power generation data fluctuates greatly, and the inverter's own regulation ability is limited. When faced with such complex and greatly fluctuating power generation data, it is easy for the photovoltaic power station to be out of sync with the grid frequency, which will not only affect the quality of electricity, but also may threaten the safe and stable operation of the power grid.

[0003] Among the current related technologies, the grid-connected regulation of photovoltaic power stations has technical problems such as insufficient regulation accuracy and effectiveness. Summary of the invention

[0004] The present application provides a photovoltaic power station grid-connected regulation method and system for large-scale power grid security, adopts a grid-connected topology structure of building a photovoltaic power station in a preset area and a traditional power grid, extracts a first grid-connected node, performs dual-path current monitoring, analyzes and generates a first photovoltaic suppression adaptation index, and if the index is less than a preset value, performs bidirectional current fluctuation suppression balance optimization, determines a first bidirectional suppression strategy, and performs grid-connected regulation of the first grid-connected node according to this strategy, etc., thereby solving the technical problem of insufficient regulation accuracy and effectiveness of the existing photovoltaic power station grid-connected regulation, and achieving the technical effect of improving the accuracy and effectiveness of the photovoltaic power station grid-connected regulation.

[0005] The present application provides a photovoltaic power station grid-connected regulation method for large-scale power grid security, including: building a grid-connected topology structure of a photovoltaic power station and a traditional power grid in a preset area; extracting a first grid-connected node based on the grid-connected topology structure, performing photovoltaic output grid-connected current monitoring and traditional power grid grid-connected current monitoring at the first grid-connected node, performing a photovoltaic inverter current fluctuation suppression adaptability analysis based on a first dual-path current monitoring result, and generating a first photovoltaic suppression adaptability index; if the first photovoltaic suppression adaptability index is less than a preset adaptability index, performing a bidirectional current fluctuation suppression balance optimization of the photovoltaic inverter and the traditional power grid based on the first dual-path current monitoring result, and determining a first bidirectional suppression strategy; and performing grid-connected regulation of the first grid-connected node using the first bidirectional suppression strategy.

[0006] In a possible implementation, photovoltaic output grid-connected current monitoring and traditional power grid grid-connected current monitoring are performed at the first grid connection node, and the following processing is executed: at the first grid connection node, current characteristic monitoring is performed on the photovoltaic output circuit through a pre-deployed current sensor to generate first photovoltaic grid-connected current data; at the first grid connection node, current characteristic monitoring is performed on the traditional power grid grid-connected circuit through a pre-deployed current sensor to generate first traditional power grid grid-connected current data; the first dual-channel current monitoring result is generated based on the first photovoltaic grid-connected current data and the first traditional power grid grid-connected current data.

[0007] In a possible implementation, the following processing is executed: the photovoltaic output circuit is a circuit in which power generated by a photovoltaic power generation unit in the photovoltaic power station flows into a first photovoltaic inverter, and the first photovoltaic inverter is connected to the first grid connection node; the traditional power grid grid-connected circuit is a non-grid-connected circuit in the traditional power grid before the first grid connection node.

[0008] In a possible implementation, adaptive analysis of current fluctuation suppression of the photovoltaic inverter is performed based on the first dual-channel current monitoring result to generate a first photovoltaic suppression adaptation index, and the following processing is executed: a first adjustment target sequence of the first photovoltaic inverter is constructed based on the first traditional power grid grid-connected current data; the service life, maintenance records, and inverter model of the first photovoltaic inverter are collected and used as modeling constraints to collect modeling data for digital modeling to generate a first twin inverter; based on the first adjustment target sequence, the first twin inverter is used to perform a simulation of suppressing the fluctuation of the first photovoltaic grid-connected current data, and an adaptation matching analysis of the current fluctuation suppression adjustment ability and the power grid current fluctuation level is performed to generate the first photovoltaic suppression adaptation index.

[0009] In a possible implementation, an adaptation matching analysis of the current fluctuation suppression adjustment ability and the power grid current fluctuation level is performed to generate the first photovoltaic suppression adaptation index, and the following processing is executed: the first fluctuation suppression sequence output by the first twin inverter is read; the consistent proportion coefficient of the fluctuation suppression result in the first fluctuation suppression sequence and the corresponding adjustment target in the first adjustment target sequence is analyzed to generate the first photovoltaic suppression adaptation index.

[0010] In a possible implementation manner, based on the first dual-channel current monitoring result, perform two-way current fluctuation suppression balance optimization on the photovoltaic inverter and the traditional power grid, determine the first two-way suppression strategy, and perform the following processing: Determine the traditional generator connected to the traditional power grid, and collect the historical power grid fluctuation suppression record library based on the traditional generator; Screen multiple power grid fluctuation suppression records that match the first traditional power grid grid-connected current data in the first dual-channel current monitoring result from the historical power grid fluctuation suppression record library, and obtain multiple fluctuation suppression characteristics and multiple suppression cost indicators; Based on the multiple suppression cost indicators, extract the fluctuation suppression characteristic with the minimum cost, update the first dual-channel current monitoring result, and then call the first twin inverter to perform the fluctuation suppression simulation of the first photovoltaic grid-connected current data; If the updated photovoltaic suppression adaptation index is greater than or equal to the preset adaptation index, determine the traditional power grid side fluctuation suppression decision and the fluctuation suppression simulation decision of the first twin inverter based on the power grid fluctuation suppression record corresponding to the fluctuation suppression characteristic with the minimum cost to generate the first two-way suppression strategy.

[0011] In a possible implementation manner, perform the following processing: If the updated photovoltaic suppression adaptation index is less than the preset adaptation index, continue to extract the fluctuation suppression characteristic corresponding to the second smallest suppression cost index among the multiple suppression cost indicators, and perform iterative update simulation until the iteratively updated photovoltaic suppression adaptation index is greater than or equal to the preset adaptation index to generate the first two-way suppression strategy.

[0012] In a possible implementation manner, perform the following processing: The fluctuation suppression characteristic corresponding to any one of the multiple power grid fluctuation suppression records is the power grid current characteristic after fluctuation suppression, and the corresponding suppression cost index is determined based on the degree of increased burden on the frequency modulation generator.

[0013] In a possible implementation manner, after determining the first two-way suppression strategy, the following processing is also performed: Read the respective power grid side fluctuation suppression decisions in the two-way suppression strategies corresponding to each grid-connected node in the grid-connected topology; Based on the grid-connected topology, analyze the current fluctuation transfer relationship between each grid-connected node; Based on the current fluctuation transfer relationship, analyze the mutual influence of the fluctuation transfer between each power grid side fluctuation suppression decision, perform cancellation optimization of the mutual influence, and generate each power grid side optimization decision; Optimize and adjust the first two-way suppression strategy with each power grid side optimization decision.

[0014] The present application also provides a grid-connected regulation system for a photovoltaic power station for large-scale power grid security guarantee, including: a grid-connected topology construction module for constructing the grid-connected topology of a photovoltaic power station in a preset area and a traditional power grid; a current fluctuation suppression adaptability analysis module for extracting a first grid-connected node based on the grid-connected topology, monitoring the grid-connected current of photovoltaic output and the grid-connected current of the traditional power grid at the first grid-connected node, performing a photovoltaic inverter current fluctuation suppression adaptability analysis based on the first dual-channel current monitoring result, and generating a first photovoltaic suppression adaptation index; a bidirectional current fluctuation suppression balance optimization module for, if the first photovoltaic suppression adaptation index is less than a preset adaptation index, performing a bidirectional current fluctuation suppression balance optimization of the photovoltaic inverter and the traditional power grid based on the first dual-channel current monitoring result, and determining a first bidirectional suppression strategy; and a grid-connected regulation module for performing grid-connected regulation of the first grid-connected node with the first bidirectional suppression strategy.

[0015] It is intended to first construct the grid-connected topology of a photovoltaic power station in a preset area and a traditional power grid through the grid-connected regulation method and system for a photovoltaic power station for large-scale power grid security guarantee proposed in the present application, then extract a first grid-connected node based on the grid-connected topology, monitor the grid-connected current of photovoltaic output and the grid-connected current of the traditional power grid at the first grid-connected node, perform a photovoltaic inverter current fluctuation suppression adaptability analysis based on the first dual-channel current monitoring result, and generate a first photovoltaic suppression adaptation index. Then, if the first photovoltaic suppression adaptation index is less than a preset adaptation index, perform a bidirectional current fluctuation suppression balance optimization of the photovoltaic inverter and the traditional power grid based on the first dual-channel current monitoring result, and determine a first bidirectional suppression strategy. Finally, perform grid-connected regulation of the first grid-connected node with the first bidirectional suppression strategy. The technical effect of improving the accuracy and effectiveness of the grid-connected regulation of the photovoltaic power station is achieved. Brief Description of the Drawings

[0016] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings of the embodiments of the present invention will be briefly introduced below. Flowcharts are used in the present application to illustrate the operations performed by the system according to the embodiments of the present application. It should be understood that the operations in the front or below do not necessarily need to be executed precisely in sequence. On the contrary, according to needs, they can be executed in reverse order or simultaneously. At the same time, other operations can also be added to these processes, or one or several operations can be removed from these processes.

[0017] Figure 1 It is a schematic flowchart of the grid-connected regulation method for a photovoltaic power station for large-scale power grid security guarantee provided by an embodiment of the present application.

[0018] Figure 2 It is a schematic structural diagram of the grid-connected regulation system for a photovoltaic power station for large-scale power grid security guarantee provided by an embodiment of the present application.

[0019] Explanation of the reference numerals: grid-connected topology structure building module 10 , current fluctuation suppression adaptability analysis module 20 , bidirectional current fluctuation suppression balance optimization module 30 , grid-connected regulation module 40 . DETAILED DESCRIPTION

[0020] The above description is only an overview of the technical solution of the present application. In order to more clearly understand the technical means of the present application, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are listed below.

[0021] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limiting the present application. All other embodiments obtained by ordinary technicians in the field without making creative work are within the scope of protection of this application.

[0022] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments, but it is understood that "some embodiments" may be the same subset or different subsets of all possible embodiments, and may be combined with each other without conflict, and the terms "first\second" involved are merely to distinguish similar objects and do not represent a specific ordering of objects. The terms "including" and "having" and any variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products, or devices. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those generally understood by technicians in the technical field of this application. The terms used herein are for the purpose of describing the embodiments of the present application only.

[0023] The present application embodiment provides a photovoltaic power station grid-connected adjustment method for large-scale power grid security, such as Figure 1 As shown, the method includes: Step S100, constructing a grid-connected topology structure of a photovoltaic power station in a preset area and a traditional power grid.

[0024] Specifically, the grid-connected topology refers to the physical structure of the connection between a photovoltaic power station and the traditional power grid, including the connection relationships among devices such as the output terminal of the photovoltaic power station, the inverter, the transformer, the grid-connected switch, and the transmission line. Among them, a photovoltaic power station is built using photovoltaic modules, inverters, transformers, switchgear, cables, etc., and the photovoltaic power station is connected to the traditional power grid through a grid-connected switch, line protection devices, etc. A communication network, such as optical fiber communication, wireless communication, etc., is deployed to transmit data and control commands between the photovoltaic power station and the power grid. A grid-connected control device is installed to achieve the synchronous grid-connected operation of the photovoltaic power station and the power grid. Monitoring devices such as current transformers and voltage transformers are installed at the grid connection point to collect grid-connected current and voltage data in real time.

[0025] For example, it includes the following specific operations: An inverter is installed at the output terminal of the photovoltaic power station to convert the direct current generated by the photovoltaic modules into alternating current with the same frequency and phase as the traditional power grid. The output terminal of the inverter is connected to the low-voltage side of the transformer through a cable, and the high-voltage side of the transformer is connected to the transmission line of the traditional power grid. An intelligent switch is installed at the grid connection point to control the connection and disconnection between the photovoltaic power station and the power grid, and the switch status information is transmitted to the control center through the communication network. High-precision current transformers and voltage transformers are installed at the grid connection point to collect grid-connected current and voltage data in real time, and the data is transmitted to the monitoring system through the communication network.

[0026] Step S200, extract the first grid-connected node based on the grid-connected topology, perform monitoring of the photovoltaic output grid-connected current and the traditional power grid grid-connected current at the first grid-connected node, and conduct an adaptability analysis of the photovoltaic inverter current fluctuation suppression based on the first dual-channel current monitoring results to generate the first photovoltaic suppression adaptation index.

[0027] Specifically, the grid-connected node refers to the electrical node where the photovoltaic power station is connected to the traditional power grid, which is a key position for current and voltage monitoring and regulation. High-precision current sensors, such as Hall current sensors, are used to monitor the photovoltaic output grid-connected current and the traditional power grid grid-connected current respectively. Through a data acquisition module, such as an analog-to-digital converter, the analog signals collected by the current sensor are converted into digital signals and transmitted to the control center through the communication network. Digital signal processing algorithms, such as fast Fourier transform, wavelet transform, etc., are used to analyze the collected current data, calculate parameters such as the amplitude and frequency of the current fluctuation, and generate the first photovoltaic suppression adaptation index according to the preset adaptability index calculation formula. The first photovoltaic suppression adaptation index is a quantitative index used to measure the ability of the photovoltaic inverter to suppress current fluctuations. An adaptability analysis module is set in the control center to judge whether the ability of the photovoltaic inverter to suppress current fluctuations meets the requirements of power grid operation according to the collected current data and the preset adaptability index threshold.

[0028] For example, it includes the following specific operations: Install two Hall current sensors at the first grid connection node, one for monitoring the photovoltaic output grid-connected current and the other for monitoring the traditional grid grid-connected current. Convert the analog current signals collected by the Hall current sensors into digital signals through an analog-to-digital converter and transmit them to the server in the control center through an optical fiber communication network. Run an adaptability analysis algorithm on the server to perform a fast Fourier transform on the collected current data and calculate the amplitudes and phases of the fundamental wave and each harmonic of the current. Calculate the first photovoltaic suppression adaptability index according to the preset adaptability index formula.

[0029] In a possible implementation manner, for photovoltaic output grid-connected current monitoring and traditional grid grid-connected current monitoring at the first grid connection node, step S200 further includes step S210 of performing current characteristic monitoring on the photovoltaic output circuit through a pre-deployed current sensor at the first grid connection node to generate first photovoltaic grid-connected current data. Specifically, install high-precision current sensors (such as Hall current sensors) on the photovoltaic output circuit at the first grid connection node. These sensors can monitor in real time the characteristics such as the amplitude, frequency, and phase of the photovoltaic output current. Convert the analog signals collected by the current sensors into digital signals through an analog-to-digital converter (ADC), store the collected digital signals in a local storage device, and transmit them to the control center through a communication network (such as optical fiber communication or wireless communication).

[0030] For example, it includes the following specific operations: Install a Hall current sensor with an accuracy of 0.1% FS (full scale) on the photovoltaic output circuit at the first grid connection node, which can monitor the current changes in real time. Convert the analog current signals collected by the sensor into digital signals through an analog-to-digital converter, with a sampling frequency of 10 kHz to ensure that the high-frequency fluctuations of the current can be captured. Store the collected digital signals in a local industrial-grade storage device and transmit them to the server in the control center through an optical fiber communication network.

[0031] Step S220, perform current characteristic monitoring on the traditional grid grid-connected circuit through a pre-deployed current sensor at the first grid connection node to generate first traditional grid grid-connected current data. Specifically, install high-precision current sensors (such as Rogowski coil current sensors) on the traditional grid grid-connected circuit at the first grid connection node. These sensors can monitor in real time the characteristics such as the amplitude, frequency, and phase of the traditional grid grid-connected current. Convert the analog signals collected by the current sensors into digital signals through an analog-to-digital converter (ADC), store the collected digital signals in a local storage device, and transmit them to the control center through a communication network (such as optical fiber communication or wireless communication).

[0032] For example, it includes the following specific operations: Install a Rogowski coil current sensor on the grid-connected circuit of the traditional power grid at the first grid connection node, with an accuracy of 0.2% FS, which can monitor the change of current in real time. Convert the analog current signal collected by the sensor into a digital signal through an analog-to-digital converter, with a sampling frequency of 10 kHz, to ensure that the high-frequency fluctuations of the current can be captured. Store the collected digital signal in a local industrial-grade storage device and transmit it to the server of the control center through an optical fiber communication network.

[0033] Step S230: Generate the first dual-channel current monitoring result based on the first photovoltaic grid-connected current data and the first traditional power grid grid-connected current data. Specifically, on the server of the control center, fuse the current data collected from the photovoltaic output circuit and the traditional power grid grid-connected circuit. Ensure the time alignment of the two-channel current data through a time synchronization algorithm. Extract the features of the fused current data, and calculate the characteristic parameters such as the amplitude, frequency, phase, and harmonic content of the current. Organize the extracted characteristic parameters into the first dual-channel current monitoring result and display it in the form of a table or graph.

[0034] By monitoring the current characteristics of the photovoltaic output circuit and the traditional power grid grid-connected circuit respectively at the first grid connection node, the characteristic parameters such as the amplitude, frequency, and phase of the two-channel current can be accurately obtained, providing an accurate data basis for the adaptive analysis of current fluctuation suppression, and formulating a more effective two-way current fluctuation suppression strategy accordingly.

[0035] For example, it includes the following specific operations: Run a time synchronization algorithm on the server of the control center to align the timestamps of the photovoltaic output current data and the traditional power grid grid-connected current data, ensuring that the two-channel data are compared at the same time point. Perform a fast Fourier transform (FFT) on the fused current data to calculate the fundamental amplitude, the harmonic content of each order, and the total harmonic distortion rate (THD) of the current. Organize the calculated characteristic parameters into a table, as shown in Table 1.

[0036] Table 1: Example of the first dual-channel current monitoring result

[0037] In a possible implementation, step S200 further includes: The photovoltaic output circuit is the circuit from the photovoltaic power generation unit in the photovoltaic power station flowing into the first photovoltaic inverter, and the first photovoltaic inverter is connected to the first grid connection node; the traditional power grid grid-connected circuit is the un-grid-connected circuit in the traditional power grid before the first grid connection node.

[0038] Specifically, the photovoltaic output circuit refers to the circuit that flows out from the photovoltaic power generation units (such as solar panels) in a photovoltaic power station, is converted by the first photovoltaic inverter, and finally flows into the first grid connection node. Among them, the photovoltaic power generation unit consists of solar panels and is used to convert solar energy into direct current. The first photovoltaic inverter is used to convert the direct current generated by the photovoltaic power generation unit into alternating current compatible with the power grid, ensuring that the frequency, phase, and amplitude of the current meet the grid connection requirements. The first grid connection node is the electrical node where the photovoltaic power station is connected to the traditional power grid and is a key position for current monitoring and regulation.

[0039] The traditional power grid grid connection circuit refers to the circuit in the traditional power grid that has not been grid-connected before the first grid connection node. This part of the circuit represents the original state of the traditional power grid and the current characteristics not affected by the grid connection of the photovoltaic power station. Before the first grid connection node refers to the current state of the traditional power grid itself before the grid connection operation, which is used for comparative analysis of the current changes after photovoltaic grid connection.

[0040] An example of the layout of the photovoltaic output circuit is as follows: In a photovoltaic power station, multiple photovoltaic power generation units (solar panels) are connected in series or in parallel to form a complete DC power supply system. The DC power supply is connected to the first photovoltaic inverter, and the inverter converts the DC power into AC power, ensuring that its frequency, phase, and amplitude are consistent with the traditional power grid. The output terminal of the inverter is connected to the first grid connection node to complete the construction of the photovoltaic output circuit. For example, a photovoltaic power station consists of multiple 10kW solar panels, which are combined in series and parallel to form a 100kW DC power supply system, connected to the first photovoltaic inverter, and the inverter outputs 220V / 50Hz AC power, which is connected to the first grid connection node.

[0041] An example of the layout of the traditional power grid grid connection circuit is as follows: In the traditional power grid, a suitable access point is selected as the first grid connection node. Before the first grid connection node, current sensors and voltage sensors are installed to monitor the original current and voltage states of the traditional power grid. For example, a suitable access point on a 10kV transmission line is selected as the first grid connection node, and high-precision current transformers and voltage transformers are installed before this node to monitor the current and voltage of the traditional power grid in real time.

[0042] In a possible implementation, the first dual-path current monitoring result is used for the adaptability analysis of the current fluctuation suppression of the photovoltaic inverter to generate the first photovoltaic suppression adaptation index. Step S200 further includes step S240 of constructing a first adjustment target sequence of the first photovoltaic inverter based on the first traditional grid-connected current data. Specifically, based on the first traditional grid-connected current data, through data processing algorithms such as moving average and wavelet transform for smoothing processing, stable current characteristic values such as amplitude, frequency, harmonic content, etc. are extracted and used as the adjustment target sequence of the photovoltaic inverter. These target sequences are used to guide the output current adjustment of the photovoltaic inverter so that it can better adapt to the current fluctuations of the grid.

[0043] For example, it includes the following specific operations: Extract the current amplitude and frequency every 1 second from the traditional grid current data, calculate its moving average value, and generate a stable current characteristic sequence. Use this current characteristic sequence as the adjustment target sequence of the photovoltaic inverter. For example, the target sequence includes a current amplitude target value of 100 A, a frequency target value of 50 Hz, etc. Store these target values as an ordered sequence for subsequent simulation and adjustment.

[0044] Step S250, collect the service life, maintenance records, and inverter model of the first photovoltaic inverter and use them as modeling constraints to collect modeling data for digital modeling to generate the first twin inverter. Specifically, through the monitoring system and maintenance records of the inverter, collect information such as its service life, maintenance records, and inverter model. Use the collected data as constraint conditions, combined with the physical model and performance parameters of the inverter, to construct a digital twin model (the first twin inverter). The digital twin model can simulate the behavior of the inverter under different working conditions. Use professional modeling software such as MATLAB / Simulink, ANSYS, etc. for modeling and simulation.

[0045] For example, it includes the following specific operations: Obtain its service life of 3 years from the monitoring system of the inverter, and the maintenance records show that two regular maintenances have been carried out in the past year. According to the inverter model, obtain its performance parameters such as rated power, conversion efficiency, maximum output current, etc. In MATLAB / Simulink, according to these parameters and constraint conditions, construct a digital twin model of the inverter, including its circuit topology, control algorithm, and dynamic response characteristics. Verify the accuracy of the digital twin model through simulation to ensure that it can truly reflect the actual operating state of the inverter.

[0046] Step S260: Based on the first adjustment target sequence, perform a simulation of suppressing the fluctuations of the first photovoltaic grid-connected current data with the first twin inverter, conduct an adaptive matching analysis of the current fluctuation suppression adjustment ability and the grid current fluctuation level, and generate the first photovoltaic suppression adaptation index. Specifically, input the first photovoltaic grid-connected current data into the first twin inverter model and perform a fluctuation suppression simulation according to the first adjustment target sequence. Through the simulation results, analyze whether the current fluctuation suppression ability of the photovoltaic inverter can adapt to the grid current fluctuation level. Calculate key indicators such as the current fluctuation amplitude and response time. According to the simulation analysis results, generate the first photovoltaic suppression adaptation index for evaluating the adaptability of the inverter's current fluctuation suppression.

[0047] For example, it includes the following specific operations: Input photovoltaic grid-connected current data, such as a current amplitude of 105 A and a frequency of 50.1 Hz, into the digital twin model. Run the simulation according to the adjustment target sequence, such as a target current amplitude of 100 A and a frequency of 50 Hz, and observe the change in the inverter output current. Through the simulation results, calculate indicators such as the current fluctuation amplitude (e.g., the fluctuation amplitude from 105 A to 100 A is 5 A) and the response time (e.g., the time from input to reaching the target current is 0.5 s). According to these indicators, generate the first photovoltaic suppression adaptation index. For example, the adaptation index can be a comprehensive score calculated based on the weighted values of the fluctuation amplitude and response time.

[0048] In a possible implementation, when conducting an adaptive matching analysis of the current fluctuation suppression adjustment ability and the grid current fluctuation level to generate the first photovoltaic suppression adaptation index, step S260 further includes step S261: Read the first fluctuation suppression sequence output by the first twin inverter. Specifically, read the output current fluctuation suppression sequence from the simulation results of the digital twin inverter. This sequence contains the adjustment results of the inverter for the input current fluctuations during the simulation. Store the read fluctuation suppression sequence in a local or cloud database.

[0049] For example, it includes the following specific operations: Run the digital twin inverter model in simulation software (such as MATLAB / Simulink), input the photovoltaic grid-connected current data, and perform a fluctuation suppression simulation according to the first adjustment target sequence. Read the output current fluctuation suppression sequence from the simulation results. For example, record the output current amplitude and frequency per second. Store the read fluctuation suppression sequence as a data file, as shown in Table 2.

[0050] Table 2: Example of the first fluctuation suppression sequence

[0051] Step S262: Analyze the consistency ratio coefficient between the fluctuation suppression results in the first fluctuation suppression sequence and the corresponding adjustment targets in the first adjustment target sequence to generate the first PV suppression adaptation index. Specifically, compare each data point in the first fluctuation suppression sequence with the corresponding target value in the first adjustment target sequence to calculate the degree of consistency between the two. Calculate the proportion of data points where the fluctuation suppression results are consistent with the adjustment targets through statistical methods to generate the consistency ratio coefficient. Generate the first PV suppression adaptation index based on the consistency ratio coefficient, which is used to quantify the current fluctuation suppression ability of the inverter.

[0052] For example, it includes the following specific operations: Compare the first fluctuation suppression sequence with the first adjustment target sequence point by point. Assume that the adjustment target sequence is as shown in Table 3.

[0053] Table 3: Example of the first adjustment target sequence

[0054] Calculate the consistency between the fluctuation suppression results and the adjustment targets at each time point. For example, set the consistency threshold as the current amplitude error not exceeding ±1A and the frequency error not exceeding ±0.01Hz. Count the proportion of data points that meet the consistency conditions. Assume that among 100 time points, the fluctuation suppression results at 85 time points meet the adjustment targets, then the consistency ratio coefficient is 85%. Generate the first PV suppression adaptation index based on the consistency ratio coefficient. For example, the adaptation index can be defined as the percentage value of the consistency ratio coefficient, that is, 85%.

[0055] Through the consistency ratio coefficient, the matching degree between the current fluctuation suppression ability of the PV inverter and the grid current fluctuation level is quantified. This method provides an intuitive index, which is convenient for system operators to quickly evaluate the performance of the inverter.

[0056] Step S300: If the first PV suppression adaptation index is less than the preset adaptation index, perform two-way current fluctuation suppression balance optimization on the PV inverter and the traditional grid based on the first dual-channel current monitoring results to determine the first two-way suppression strategy.

[0057] Specifically, when the first photovoltaic suppression adaptation index is less than the preset adaptation index, it indicates that the current fluctuation suppression ability of the photovoltaic inverter is insufficient to meet the requirements of the safe operation of the power grid. Specifically, the possible problems include: excessive current fluctuation (the fluctuation amplitude of the output current of the photovoltaic inverter exceeds the range allowed by the power grid, which may cause unstable power grid voltage or abnormal operation of equipment), insufficient response speed (the response time of the photovoltaic inverter to current fluctuation is too long, and it cannot adjust the output current in time to adapt to the changes in the power grid), too high harmonic content (the harmonic content of the output current of the photovoltaic inverter is relatively high, affecting the power quality of the power grid), and mismatch with the power grid regulation target (there is a large deviation between the output current of the photovoltaic inverter and the regulation target of the power grid, and it cannot effectively cooperate with the operating state of the power grid). To ensure the safe and stable operation of the power grid after the photovoltaic power station is connected to the grid, it is necessary to perform two-way current fluctuation suppression balance optimization on the photovoltaic inverter and the traditional power grid. By adjusting the operating parameters of the photovoltaic inverter and the power grid, the current fluctuation suppression ability is improved to reach or exceed the preset adaptation index.

[0058] Adopt optimization algorithms, such as particle swarm optimization algorithm, genetic algorithm, etc., to optimize the control parameters of the photovoltaic inverter and the regulation parameters of the power grid. By adjusting parameters such as the output power, reactive power, and modulation mode of the photovoltaic inverter, as well as parameters such as voltage regulation and reactive power compensation of the power grid, to achieve two-way current fluctuation suppression balance.

[0059] Perform simulation verification on the optimized two-way suppression strategy on the simulation platform of the control center to ensure its effectiveness and reliability. Generate control instructions according to the optimization results, and transmit the control instructions to the regulation equipment of the photovoltaic inverter and the power grid through the communication network.

[0060] For example, it includes the following specific operations: Run the particle swarm optimization algorithm in the control center, take the output power of the photovoltaic inverter and the voltage regulation parameters of the power grid as the optimization variables, and take the two-way current fluctuation suppression balance as the objective function for optimization calculation. According to the optimization results, adjust the modulation mode of the photovoltaic inverter, for example, switch from the fixed modulation mode to the dynamic modulation mode to adapt to the current fluctuation of the power grid. At the same time, adjust the input capacity of the reactive power compensation equipment of the power grid, for example, by switching capacitor banks or adjusting the output of the static var compensator (SVC), to improve the voltage quality and current fluctuation characteristics of the power grid. Perform simulation verification on the optimized two-way suppression strategy on the simulation platform, simulate the current fluctuation conditions under different working conditions, and ensure the effectiveness of the optimization strategy. After passing the verification, generate control instructions and transmit the instructions to the regulation equipment of the photovoltaic inverter and the power grid through the communication network.

[0061] In a possible implementation manner, based on the first dual-channel current monitoring result, two-way current fluctuation suppression balance optimization of the photovoltaic inverter and the traditional power grid is performed to determine the first two-way suppression strategy. Step S300 further includes step S310 of determining a traditional generator connected to the traditional power grid and collecting a historical power grid fluctuation suppression record library based on the traditional generator. Specifically, a traditional generator connected to the traditional power grid is determined through a power grid management system (such as a SCADA system). Historical power grid fluctuation suppression records of the traditional generator are collected from the historical database of the power grid, including characteristic parameters (such as current amplitude, frequency, harmonic content, etc.) of each fluctuation suppression and corresponding suppression cost indicators (such as energy consumption, response time, etc.).

[0062] For example, it includes the following specific operations: Multiple traditional generators (such as generator sets A, B, and C) connected to the traditional power grid are identified through the power grid management system. Historical power grid fluctuation suppression records of these generators in the past year are collected from the historical database of the power grid, and the record content is shown in Table 4.

[0063] Table 4: Example of the historical power grid fluctuation suppression record library

[0064] Step S320, screen multiple power grid fluctuation suppression records that match the first traditional power grid grid-connected current data in the first dual-channel current monitoring result from the historical power grid fluctuation suppression record library, and obtain multiple fluctuation suppression characteristics and multiple suppression cost indicators. Specifically, the first traditional power grid grid-connected current data in the first dual-channel current monitoring result is matched with the data in the historical power grid fluctuation suppression record library to screen out similar fluctuation suppression records. Fluctuation suppression characteristics, such as current amplitude, frequency, and harmonic content, and corresponding suppression cost indicators, such as energy consumption and response time, are extracted from the matched records.

[0065] For example, it includes the following specific operations: The first traditional power grid grid-connected current data is: amplitude 100A, frequency 50.0Hz, harmonic content 2%. Records that match the above data are screened out from the historical power grid fluctuation suppression record library. For example: Record 1: amplitude 100A, frequency 50.0Hz, harmonic content 2%, energy consumption 10kWh, response time 0.5s; Record 2: amplitude 101A, frequency 50.0Hz, harmonic content 2.5%, energy consumption 11kWh, response time 0.6s; Record 3: amplitude 100A, frequency 50.1Hz, harmonic content 2%, energy consumption 12kWh, response time 0.7s.

[0066] Step S330: Based on the multiple suppression cost metrics, extract the fluctuation suppression feature with the minimum cost. After updating the first dual-channel current monitoring result, call the first twin inverter to perform the fluctuation suppression simulation on the first photovoltaic grid-connected current data. Specifically, compare the multiple suppression cost metrics and select the fluctuation suppression feature with the minimum cost. Apply the fluctuation suppression feature with the minimum cost to the first dual-channel current monitoring result to update the monitoring data. Call the first twin inverter and use the updated monitoring data to perform the fluctuation suppression simulation.

[0067] For example, it includes the following specific operations: Compare the suppression cost metrics of the above three records and find that Record 1 has the lowest energy consumption (10 kWh) and the shortest response time (0.5 s). Extract the fluctuation suppression feature of Record 1 (amplitude 100 A, frequency 50.0 Hz, harmonic content 2%) and apply it to the first dual-channel current monitoring result to update the monitoring data. Call the first twin inverter and use the updated monitoring data to perform the fluctuation suppression simulation.

[0068] Step S340: If the updated photovoltaic suppression adaptation metric is greater than or equal to the preset adaptation metric, determine the traditional grid-side fluctuation suppression decision and the fluctuation suppression simulation decision of the first twin inverter based on the grid fluctuation suppression record corresponding to the fluctuation suppression feature with the minimum cost, and generate the first two-way suppression strategy. Specifically, according to the simulation result, evaluate whether the updated photovoltaic suppression adaptation metric meets the preset adaptation metric. If the adaptation metric meets the requirements, generate the traditional grid-side fluctuation suppression decision and the fluctuation suppression simulation decision of the first twin inverter based on the grid fluctuation suppression record corresponding to the fluctuation suppression feature with the minimum cost, and form the first two-way suppression strategy.

[0069] For example, it includes the following specific operations: The simulation result shows that the updated photovoltaic suppression adaptation metric is 88%, higher than the preset adaptation metric of 85%. Based on Record 1 (the grid fluctuation suppression record corresponding to the fluctuation suppression feature with the minimum cost), generate the traditional grid-side fluctuation suppression decision (such as adjusting the generator output power, putting into the reactive power compensation device, etc.). At the same time, according to the simulation result of the first twin inverter, generate the fluctuation suppression simulation decision of the inverter (such as adjusting the inverter modulation mode, reactive power output, etc.). Combine the traditional grid-side fluctuation suppression decision and the fluctuation suppression simulation decision of the inverter into the first two-way suppression strategy to guide the actual operation.

[0070] By introducing a historical power grid fluctuation suppression record library of traditional generators, the past operating experience is fully utilized, providing a reference for current fluctuation suppression optimization. This method can avoid blind optimization and improve the reliability of the optimization strategy. By comparing multiple suppression cost indicators and selecting the fluctuation suppression feature with the minimum cost, it can ensure that the optimization strategy is optimal in terms of economy and efficiency. For example, selecting a fluctuation suppression scheme with the lowest energy consumption and the shortest response time can not only save operating costs but also improve the response speed of the system.

[0071] In a possible implementation, step S300 further includes step S350. If the updated photovoltaic suppression adaptation index is less than the preset adaptation index, continue to extract the fluctuation suppression feature corresponding to the second smallest suppression cost index among multiple suppression cost indicators, and perform iterative update simulation until the updated photovoltaic suppression adaptation index is greater than or equal to the preset adaptation index, and generate the first bidirectional suppression strategy.

[0072] Specifically, if the updated photovoltaic suppression adaptation index after the first update still does not reach the preset adaptation index, the system will automatically enter the iterative update process. Extract the fluctuation suppression feature corresponding to the second smallest suppression cost index from multiple suppression cost indicators, and continue to update the first dual-channel current monitoring result. Call the first twin inverter and use the updated monitoring data to re-perform the fluctuation suppression simulation. The iterative update simulation will continue until the updated photovoltaic suppression adaptation index is greater than or equal to the preset adaptation index. Once the condition is met, the system will stop iterating, and based on the fluctuation suppression feature that finally meets the adaptation index, determine the fluctuation suppression decision on the traditional power grid side and the fluctuation suppression simulation decision of the first twin inverter. Combine these decisions into the first bidirectional suppression strategy to guide the actual operation of the photovoltaic power station and the traditional power grid.

[0073] For example, assume that the PV suppression adaptation index after the first update is 82%, which is lower than the preset adaptation index of 85%. The system enters the iterative update process. In the first iteration, the fluctuation suppression feature corresponding to the sub-minimum suppression cost index is extracted from multiple suppression cost indexes. For example, the fluctuation suppression feature with an energy consumption of 11 kWh and a response time of 0.6 s is selected. The first dual-channel current monitoring result is updated, and the first twin inverter is called to re-perform the fluctuation suppression simulation. The simulation result shows that the updated PV suppression adaptation index is 84%, still lower than the preset adaptation index. In the second iteration, the fluctuation suppression feature corresponding to the next sub-minimum suppression cost index is continuously extracted. For example, the fluctuation suppression feature with an energy consumption of 12 kWh and a response time of 0.7 s is selected. The first dual-channel current monitoring result is updated again, and the first twin inverter is called to re-perform the fluctuation suppression simulation. The simulation result shows that the updated PV suppression adaptation index is 86%, meeting the preset adaptation index. Based on the fluctuation suppression feature (energy consumption 12 kWh, response time 0.7 s) that finally meets the adaptation index, the first bi-directional suppression strategy is generated. The fluctuation suppression decisions on the traditional grid side include adjusting the generator output power, putting into reactive power compensation devices, etc. The fluctuation suppression simulation decisions of the PV inverter include adjusting the inverter modulation mode, reactive power output, etc.

[0074] By introducing the iterative update mechanism, the system can be continuously optimized until the PV suppression adaptation index reaches the preset value. This method ensures the thoroughness and effectiveness of the optimization process, and avoids grid connection quality problems caused by insufficient initial optimization strategies.

[0075] In a possible implementation manner, step S320 further includes step S321. The fluctuation suppression feature corresponding to any one of the multiple grid fluctuation suppression records is the grid current feature after fluctuation suppression, and the corresponding suppression cost index is determined based on the degree of increased burden on the frequency modulation generator.

[0076] Specifically, each grid fluctuation suppression record records the grid current features of the frequency modulation generator after the fluctuation suppression operation. These features include parameters such as current amplitude, frequency, and harmonic content, reflecting the actual effect of the fluctuation suppression operation. For example: the grid current feature after fluctuation suppression is: current amplitude 100 A, frequency 50.0 Hz, harmonic content 2%.

[0077] The suppression cost index reflects the additional burden borne by the frequency modulation generator after the fluctuation suppression operation. These indexes include increased energy consumption, increased equipment wear, extended response time, etc. For example: the suppression cost index is: increased energy consumption 10 kWh, increased equipment wear rate 5%, extended response time 0.2 s.

[0078] Collect historical grid fluctuation suppression records of traditional generators from the historical database of the power grid, including the grid current characteristics and corresponding suppression cost indicators after each fluctuation suppression operation. According to the first traditional grid grid-connected current data in the first dual-channel current monitoring results, filter out multiple grid fluctuation suppression records that match it.

[0079] In a possible implementation manner, after determining the first two-way suppression strategy, step S300 further includes: reading each grid-side fluctuation suppression decision in the two-way suppression strategy corresponding to each grid-connected node in the grid-connected topology; analyzing the current fluctuation transfer relationship between each grid-connected node based on the grid-connected topology; based on the current fluctuation transfer relationship, analyzing the mutual influence of fluctuations between each grid-side fluctuation suppression decision, performing cancellation optimization of the mutual influence, and generating each grid-side optimized decision; using each grid-side optimized decision to optimize and adjust the first two-way suppression strategy.

[0080] Specifically, extract the grid-side fluctuation suppression decisions corresponding to each grid-connected node in the grid-connected topology from the first two-way suppression strategy. For example, assume that there are three grid-connected nodes (node D, node E, and node F) in the grid-connected topology, and each node has a corresponding grid-side fluctuation suppression decision: Node D: Adjust the generator output power and put into the reactive power compensation device; Node E: Adjust the transformer tap position and increase the input capacity of the capacitor bank; Node F: Adjust the generator frequency and put into the static var compensator (SVC).

[0081] Based on the grid-connected topology, analyze the transfer path and influence relationship of current between each grid-connected node. For example: The current enters the traditional power grid D2 from the photovoltaic power station D1 through node D. The grid-side decision of node D (adjusting the generator output power) directly affects the current fluctuation situation of the traditional power grid D2. If the traditional power grid D2 is interconnected with other power grids (such as the traditional power grids E2 and F2), the decision of node D2 may affect other nodes through the interconnection line.

[0082] Analyze the mutual influence between each grid-side fluctuation suppression decision, and identify possible conflicts or synergy effects. For example: The grid-side decision of node D (adjusting the generator output power) may cause an increase in the current fluctuation of the traditional power grid D2, which is transmitted to the traditional power grid E2 through the interconnection line and affects the current fluctuation of node E. The grid-side decision of node E (adjusting the transformer tap position) may cause a voltage change in the traditional power grid E2, which is transmitted to the traditional power grid D1 through the interconnection line and affects the voltage and current fluctuation of node D.

[0083] Based on the analysis results, optimize and adjust each grid-side fluctuation suppression decision to offset the mutual influence and improve the overall suppression effect. For example: If the grid-side decision at node D causes an increase in the current fluctuation at node E, adjust the decision at node D (such as reducing the adjustment amplitude of the generator output power) to reduce the impact on node E. If the grid-side decision at node E causes a voltage change at node D, adjust the decision at node E (such as changing the adjustment direction of the transformer tap position) to reduce the impact on node D. If the grid-side decision at node E causes an increase in the current fluctuation at node F, adjust the decision at node E (such as reducing the adjustment amplitude of the transformer tap position) to reduce the impact on node F. If the grid-side decision at node F causes a frequency change at node E, adjust the decision at node F (such as changing the adjustment direction of the generator frequency) to reduce the impact on node E. If the grid-side decision at node D causes an increase in the current fluctuation at node F, adjust the decision at node D (such as reducing the adjustment amplitude of the generator output power) to reduce the impact on node F. If the grid-side decision at node F causes a frequency change at node D, adjust the decision at node F (such as changing the adjustment direction of the generator frequency) to reduce the impact on node D.

[0084] Generate the optimized decision for each grid side according to the result of the cancellation optimization. For example: Optimized decision for node D: Adjust the generator output power of the traditional grid D2 to reduce the impact on the current fluctuation at node E. Invest in a reactive power compensation device to optimize the voltage level. Optimized decision for node E: Adjust the transformer tap position of the traditional grid E2 to ensure coordination with the decision at node F. Increase the input capacity of the capacitor bank to compensate for reactive power and reduce current fluctuations. Optimized decision for node F: Adjust the generator frequency of the traditional grid F2 to ensure coordination with the decision at node E. Invest in a static var compensator (SVC) to further optimize the current quality. Apply the optimized decisions for each grid side to the first two-way suppression strategy and update the strategy content.

[0085] By analyzing the current fluctuation transfer relationship between each grid-connected node in the grid-connected topology, global optimization can be achieved, not just local optimization. This method can ensure that the current fluctuation suppression effect of the entire grid reaches the optimal. By analyzing the mutual influence between each grid-side fluctuation suppression decision and performing cancellation optimization, the conflict between decisions can be reduced and the overall suppression effect can be improved. For example, avoid the decision of one node canceling the effect of another node's decision. By optimizing the fluctuation suppression decision of each grid-connected node, the grid connection quality of the photovoltaic power station can be improved, the impact on the grid can be reduced, and the stable operation of the grid can be guaranteed.

[0086] Step S400, perform grid connection regulation on the first grid-connected node with the first two-way suppression strategy.

[0087] Specifically, after receiving the control instructions, the photovoltaic inverter and the grid regulation equipment adjust their own operating parameters according to the instructions. During the grid connection regulation process, the grid-connected current and voltage data are continuously monitored in real time, and the monitored data is fed back to the control center. According to the real-time monitored data, the control strategy is dynamically adjusted to cope with the dynamic changes in the grid operation. Protection devices such as overcurrent protection and overvoltage protection are set to ensure the safe operation of the equipment during the regulation process.

[0088] For example, it includes the following specific operations: after the photovoltaic inverter receives the control instructions, it adjusts its output power and modulation method. For example, the output power is adjusted from 80% of the rated power to 75%, and the modulation method is switched from fixed modulation to dynamic modulation. After the reactive power compensation equipment of the grid receives the control instructions, it adjusts its input capacity. For example, the input capacity of the capacitor bank is adjusted from 50% to 60%. During the grid connection regulation process, the grid-connected current and voltage data are continuously monitored in real time through current sensors and voltage sensors, and the data is transmitted to the control center. The control center dynamically adjusts the control strategy according to the real-time monitored data. For example, when it is detected that the amplitude of the current fluctuation increases, the output power of the photovoltaic inverter or the reactive power compensation parameters of the grid are further adjusted. An overcurrent protection device is set at the grid connection node. When it is detected that the current exceeds the set overcurrent threshold, the grid connection switch is immediately cut off to protect the equipment from damage.

[0089] The embodiment of the present application adopts technical means such as building a grid connection topology of a preset area photovoltaic power station and a traditional grid, extracting the first grid connection node, performing dual-channel current monitoring, analyzing and generating the first photovoltaic suppression adaptation index. If the index is less than the preset value, bidirectional current fluctuation suppression balance optimization is executed, the first bidirectional suppression strategy is determined, and grid connection regulation of the first grid connection node is performed according to this strategy, solving the technical problem of insufficient accuracy and effectiveness of the existing grid connection regulation of photovoltaic power stations, and achieving the technical effect of improving the accuracy and effectiveness of the grid connection regulation of photovoltaic power stations.

[0090] In the above text, reference is made to Figure 1 The method for grid connection regulation of a photovoltaic power station for large-scale grid security protection according to an embodiment of the present invention is described in detail. Next, reference will be made to Figure 2 Describe a grid connection regulation system for a photovoltaic power station for large-scale grid security protection according to an embodiment of the present invention.

[0091] The grid - connection regulation system of a photovoltaic power station for large - scale power grid security guarantee according to an embodiment of the present invention is used to solve the technical problem of insufficient accuracy and effectiveness of the existing grid - connection regulation of photovoltaic power stations, and achieve the technical effect of improving the accuracy and effectiveness of the grid - connection regulation of photovoltaic power stations. The grid - connection regulation system of a photovoltaic power station for large - scale power grid security guarantee includes: a grid - connection topology construction module 10, a current fluctuation suppression adaptability analysis module 20, a two - way current fluctuation suppression balance optimization module 30, and a grid - connection regulation module 40.

[0092] The grid - connection topology construction module 10 is used to construct the grid - connection topology of the photovoltaic power station in a preset area and the traditional power grid; the current fluctuation suppression adaptability analysis module 20 is used to extract the first grid - connection node based on the grid - connection topology, monitor the photovoltaic output grid - connection current and the traditional power grid grid - connection current at the first grid - connection node, perform the adaptability analysis of the current fluctuation suppression of the photovoltaic inverter based on the first dual - path current monitoring result, and generate the first photovoltaic suppression adaptation index; the two - way current fluctuation suppression balance optimization module 30 is used to, if the first photovoltaic suppression adaptation index is less than the preset adaptation index, perform the two - way current fluctuation suppression balance optimization of the photovoltaic inverter and the traditional power grid based on the first dual - path current monitoring result, and determine the first two - way suppression strategy; the grid - connection regulation module 40 is used to perform the grid - connection regulation of the first grid - connection node with the first two - way suppression strategy.

[0093] Next, the specific configuration of the current fluctuation suppression adaptability analysis module 20 will be described in detail. As described above, the photovoltaic output grid - connection current and the traditional power grid grid - connection current are monitored at the first grid - connection node. The current fluctuation suppression adaptability analysis module 20 may further include: a first photovoltaic grid - connection current data generation unit for monitoring the current characteristics of the photovoltaic output circuit through a pre - arranged current sensor at the first grid - connection node to generate the first photovoltaic grid - connection current data; a first traditional power grid grid - connection current data generation unit for monitoring the current characteristics of the traditional power grid grid - connection circuit through a pre - arranged current sensor at the first grid - connection node to generate the first traditional power grid grid - connection current data; a first dual - path current monitoring result generation unit for generating the first dual - path current monitoring result with the first photovoltaic grid - connection current data and the first traditional power grid grid - connection current data.

[0094] Among them, the current fluctuation suppression adaptability analysis module 20 may further include: the photovoltaic output circuit is the circuit from the photovoltaic power generation unit in the photovoltaic power station flowing into the first photovoltaic inverter, and the first photovoltaic inverter is connected to the first grid - connection node; the traditional power grid grid - connection circuit is the un - grid - connected circuit in the traditional power grid before the first grid - connection node.

[0095] Among them, the first dual-channel current monitoring result is used for the adaptability analysis of the current fluctuation suppression of the photovoltaic inverter to generate the first photovoltaic suppression adaptation index. The current fluctuation suppression adaptability analysis module 20 may further include: a first adjustment target sequence construction unit for constructing a first adjustment target sequence of the first photovoltaic inverter with the first traditional grid-connected current data; a digital modeling unit for collecting the service life, maintenance records, and inverter model of the first photovoltaic inverter and using them as modeling constraints to collect modeling data for digital modeling to generate a first twin inverter; an adaptation matching analysis unit for performing a fluctuation suppression simulation of the first photovoltaic grid-connected current data with the first twin inverter based on the first adjustment target sequence, and performing an adaptation matching analysis of the current fluctuation suppression adjustment ability and the grid current fluctuation level to generate the first photovoltaic suppression adaptation index.

[0096] Among them, for performing an adaptation matching analysis of the current fluctuation suppression adjustment ability and the grid current fluctuation level to generate the first photovoltaic suppression adaptation index, the adaptation matching analysis unit may further include: a first fluctuation suppression sequence reading subunit for reading a first fluctuation suppression sequence output by the first twin inverter; a consistent ratio coefficient obtaining subunit for analyzing the consistent ratio coefficient of the fluctuation suppression result in the first fluctuation suppression sequence and the corresponding adjustment target in the first adjustment target sequence to generate the first photovoltaic suppression adaptation index.

[0097] Next, the specific configuration of the bidirectional current fluctuation suppression balance optimization module 30 will be described in detail. As described above, based on the first dual-channel current monitoring result, the bidirectional current fluctuation suppression balance optimization of the photovoltaic inverter and the traditional grid is performed to determine the first bidirectional suppression strategy. The bidirectional current fluctuation suppression balance optimization module 30 may further include: a historical grid fluctuation suppression record library collection unit for determining a traditional generator connected to the traditional grid and collecting a historical grid fluctuation suppression record library based on the traditional generator; a screening unit for screening multiple grid fluctuation suppression records matching the first traditional grid-connected current data in the first dual-channel current monitoring result in the historical grid fluctuation suppression record library, and obtaining multiple fluctuation suppression characteristics and multiple suppression cost indicators; a fluctuation suppression simulation unit for extracting the fluctuation suppression characteristic with the minimum cost based on the multiple suppression cost indicators, updating the first dual-channel current monitoring result, and then calling the first twin inverter to perform the fluctuation suppression simulation of the first photovoltaic grid-connected current data; a first bidirectional suppression strategy generation unit for, if the updated photovoltaic suppression adaptation index is greater than or equal to the preset adaptation index, determining the traditional grid-side fluctuation suppression decision and the fluctuation suppression simulation decision of the first twin inverter with the grid fluctuation suppression record corresponding to the fluctuation suppression characteristic with the minimum cost to generate the first bidirectional suppression strategy.

[0098] Among them, the bidirectional current fluctuation suppression balance optimization module 30 may further include: an iterative update simulation unit, which is configured to continue to extract the fluctuation suppression features corresponding to the second smallest suppression cost index among multiple suppression cost indexes for iterative update simulation until the updated photovoltaic suppression adaptation index is greater than or equal to the preset adaptation index, and generate the first bidirectional suppression strategy if the updated photovoltaic suppression adaptation index is less than the preset adaptation index.

[0099] Among them, the screening unit may further include: the fluctuation suppression feature corresponding to any one of the multiple grid fluctuation suppression records is the grid current feature after fluctuation suppression, and the corresponding suppression cost index is determined based on the degree of increased burden on the frequency modulation generator.

[0100] Among them, after determining the first bidirectional suppression strategy, the system may further include: each grid-side fluctuation suppression decision reading module is configured to read each grid-side fluctuation suppression decision in the bidirectional suppression strategies corresponding to each grid connection node in the grid connection topology; the current fluctuation transfer relationship analysis module is configured to analyze the current fluctuation transfer relationship between each grid connection node based on the grid connection topology; the cancellation optimization module is configured to analyze the mutual influence of the fluctuation transfer between each grid-side fluctuation suppression decision based on the current fluctuation transfer relationship, perform cancellation optimization of the mutual influence, and generate each grid-side optimization decision; the optimization adjustment module is configured to optimize and adjust the first bidirectional suppression strategy with each grid-side optimization decision.

[0101] The photovoltaic power station grid connection regulation system for large-scale power grid security provided by the embodiments of the present invention can execute the photovoltaic power station grid connection regulation method for large-scale power grid security provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the method.

[0102] Although the present application makes various references to certain modules in the system according to the embodiments of the present application, however, any number of different modules can be used and run on the user terminal and / or the server. The included individual units and modules are only divided according to the functional logic, but are not limited to the above division, as long as the corresponding functions can be realized; in addition, the specific names of the functional units are only for the convenience of mutual distinction and do not limit the protection scope of the present invention.

[0103] The above specific embodiments do not constitute a limitation on the protection scope of the present application. Those skilled in the art should understand that various modifications, combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principle of the present application shall be included within the protection scope of the present application. In some cases, the actions or steps recited in the present application can be executed in a sequence different from that in the embodiments and still achieve the desired results. Additionally, the processes depicted in the drawings do not necessarily require the specific order or consecutive order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

Claims

1. A photovoltaic power station grid-connected regulation method for large-scale power grid security, characterized in that: include: Build the grid-connected topology of the photovoltaic power station in the preset area and the traditional power grid; Extracting a first grid-connected node based on the grid-connected topology structure, performing photovoltaic output grid-connected current monitoring and traditional power grid grid-connected current monitoring at the first grid-connected node, performing photovoltaic inverter current fluctuation suppression adaptability analysis based on the first dual-path current monitoring result, and generating a first photovoltaic suppression adaptability index; If the first photovoltaic suppression adaptation index is less than a preset adaptation index, performing bidirectional current fluctuation suppression balance optimization of the photovoltaic inverter and the traditional power grid based on the first dual-channel current monitoring result, and determining a first bidirectional suppression strategy; The first bidirectional suppression strategy is used to perform grid connection regulation of the first grid-connected node.

2. The photovoltaic power station grid-connected regulation method for large-scale power grid security according to claim 1, characterized in that: The photovoltaic output grid-connected current monitoring and the traditional power grid grid-connected current monitoring are performed at the first grid-connected node, including: At the first grid-connected node, a current sensor pre-deployed is used to monitor the current characteristics of the photovoltaic output circuit to generate first photovoltaic grid-connected current data; At the first grid-connected node, current characteristics of the conventional grid-connected circuit are monitored by a pre-deployed current sensor to generate first conventional grid-connected current data; The first dual-channel current monitoring result is generated using the first photovoltaic grid-connected current data and the first conventional power grid-connected current data.

3. The photovoltaic power station grid-connected regulation method for large-scale power grid security as claimed in claim 2, characterized in that: The photovoltaic output circuit is a circuit in which the photovoltaic power generation unit in the photovoltaic power station flows into the first photovoltaic inverter, and the first photovoltaic inverter is connected to the first grid-connected node; the traditional power grid-connected circuit is a circuit in the traditional power grid that is located before the first grid-connected node and is not connected to the grid.

4. The photovoltaic power station grid-connected regulation method for large-scale power grid security as claimed in claim 2, characterized in that: The first dual-channel current monitoring result is used to perform current fluctuation suppression adaptability analysis of the photovoltaic inverter to generate a first photovoltaic suppression adaptability index, including: Constructing a first adjustment target sequence of a first photovoltaic inverter based on the first conventional power grid-connected current data; Collecting the service time, maintenance record and inverter model of the first photovoltaic inverter and using them as modeling constraints to collect modeling data for digital modeling, and generating a first twin inverter; Based on the first regulation target sequence, the first twin inverter is used to perform fluctuation suppression simulation of the first photovoltaic grid-connected current data, and an adaptation matching analysis between the current fluctuation suppression regulation capability and the grid current fluctuation level is performed to generate the first photovoltaic suppression adaptation index.

5. The photovoltaic power station grid-connected regulation method for large-scale power grid security as claimed in claim 4, characterized in that: Performing an adaptive matching analysis of the current fluctuation suppression and regulation capability and the grid current fluctuation level to generate the first photovoltaic suppression adaptation index includes: Reading a first fluctuation suppression sequence output by the first twin inverter; The first photovoltaic suppression adaptation index is generated by analyzing the consistency ratio of the fluctuation suppression result in the first fluctuation suppression sequence and the corresponding adjustment target in the first adjustment target sequence.

6. The photovoltaic power station grid-connected regulation method for large-scale power grid security as claimed in claim 4, characterized in that: Based on the first two-way current monitoring result, bidirectional current fluctuation suppression balance optimization of the photovoltaic inverter and the traditional power grid is performed to determine a first bidirectional suppression strategy, including: Determine a traditional generator connected to the traditional power grid, and collect a historical power grid fluctuation suppression record library based on the traditional generator; Screening a plurality of power grid fluctuation suppression records matching the first conventional power grid connected current data in the first dual-channel current monitoring result in the historical power grid fluctuation suppression record library, and acquiring a plurality of fluctuation suppression features and a plurality of suppression cost indicators; Based on the multiple suppression cost indicators, extract the fluctuation suppression feature with the minimum cost, update the first dual-channel current monitoring result, and call the first twin inverter to perform the fluctuation suppression simulation of the first photovoltaic grid-connected current data; If the updated photovoltaic suppression adaptation index is greater than or equal to the preset adaptation index, the first bidirectional suppression strategy is generated by determining the traditional grid-side fluctuation suppression decision and the fluctuation suppression simulation decision of the first twin inverter based on the grid fluctuation suppression record corresponding to the fluctuation suppression feature with the lowest cost.

7. The photovoltaic power station grid-connected regulation method for large-scale power grid security as claimed in claim 6, characterized in that: If the updated photovoltaic suppression adaptation index is less than the preset adaptation index, continue to extract the fluctuation suppression characteristics corresponding to the secondary minimum suppression cost index among the multiple suppression cost indicators, and perform iterative update simulation until the iteratively updated photovoltaic suppression adaptation index is greater than or equal to the preset adaptation index, and generate the first bidirectional suppression strategy.

8. The photovoltaic power station grid-connected regulation method for large-scale power grid security as claimed in claim 6, characterized in that: The fluctuation suppression feature corresponding to any one of the plurality of grid fluctuation suppression records is a grid current feature after fluctuation suppression, and the corresponding suppression cost index is determined based on the degree of burden increase of the frequency modulation generator.

9. The photovoltaic power station grid-connected regulation method for large-scale power grid security as claimed in claim 1, characterized in that: After determining the first bidirectional suppression strategy, it also includes: Reading each grid-side fluctuation suppression decision in the bidirectional suppression strategy corresponding to each grid-connected node in the grid-connected topology structure; Based on the grid-connected topology, analyzing the current fluctuation transmission relationship between each grid-connected node; Based on the current fluctuation transmission relationship, analyzing the fluctuation transmission mutual influence between each grid-side fluctuation suppression decision, performing mutual influence offset optimization, and generating each grid-side optimization decision; The first bidirectional suppression strategy is optimized and adjusted based on the respective grid-side optimization decisions.

10. A photovoltaic power station grid-connected regulation system for large-scale power grid security, characterized in that: The system is used to implement the photovoltaic power station grid-connected regulation method for large-scale power grid security according to any one of claims 1 to 9, and the system comprises: The grid-connected topology building module is used to build the grid-connected topology of the photovoltaic power station in the preset area and the traditional power grid; A current fluctuation suppression adaptability analysis module is used to extract a first grid-connected node based on the grid-connected topology structure, perform photovoltaic output grid-connected current monitoring and traditional power grid grid-connected current monitoring at the first grid-connected node, perform photovoltaic inverter current fluctuation suppression adaptability analysis based on the first dual-channel current monitoring result, and generate a first photovoltaic suppression adaptability index; A bidirectional current fluctuation suppression balance optimization module, configured to perform bidirectional current fluctuation suppression balance optimization of the photovoltaic inverter and the traditional power grid based on the first dual-channel current monitoring result and determine a first bidirectional suppression strategy if the first photovoltaic suppression adaptation index is less than a preset adaptation index; A grid-connected regulation module is used to perform grid-connected regulation of the first grid-connected node using the first bidirectional suppression strategy.

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