New energy distribution network photovoltaic automation terminal intelligent debugging method and device

Abstract

The invention relates to the technical field of power system automation, and discloses an intelligent debugging method and device for a photovoltaic automation terminal of a new energy distribution network, and the method comprises the steps: firstly, enabling a photovoltaic terminal device to meet the technical standard and safety requirements of a new energy distribution network system through the network access authentication of automation equipment; the method comprises the following steps: acquiring system operation data, automatically matching a corresponding preset debugging strategy under a current working condition according to the acquired system operation data, automatically executing the corresponding preset debugging strategy when a preset working condition is triggered, and dynamically adjusting and optimizing the photovoltaic terminal equipment passing the authentication. Meanwhile, through a unified debugging strategy and real-time data driving, the technical problem that a traditional debugging method depends on manual operation and static rules and is difficult to meet the requirements of a high-dynamic and multi-device cooperative photovoltaic distribution network system is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of power system automation, and particularly to an intelligent debugging method and device for a photovoltaic automation terminal in a new energy distribution network. Background Art

[0002] As an important part of clean energy, the large-scale application of photovoltaic power generation in the distribution network has become a development trend. With the rapid increase in the number of photovoltaic terminal devices (such as photovoltaic modules, inverters, acquisition terminals, etc.), the complexity of their access, debugging, and operation and maintenance has increased significantly. The traditional debugging method relies on manual operation and static rules, and it is difficult to meet the requirements of a highly dynamic and multi-device collaborative photovoltaic distribution network system. Summary of the Invention

[0003] The present invention provides an intelligent debugging method and device for a photovoltaic automation terminal in a new energy distribution network, and solves the technical problem that the traditional debugging method relies on manual operation and static rules and is difficult to meet the requirements of a highly dynamic and multi-device collaborative photovoltaic distribution network system.

[0004] An intelligent debugging method for a photovoltaic automation terminal in a new energy distribution network provided by the first aspect of the present invention includes:

[0005] Performing device network access authentication on a photovoltaic terminal device to be connected to a new energy distribution network system, and obtaining system operation data of the new energy distribution network system, where the photovoltaic terminal device includes a photovoltaic module and an inverter;

[0006] Matching a corresponding preset debugging strategy according to the system operation data, and performing dynamic debugging on the photovoltaic terminal device that passes the authentication.

[0007] Optionally, the system operation data includes solar radiation intensity, load data, load volatility, photovoltaic power generation efficiency, and historical power generation efficiency average value, the preset debugging strategies include a photovoltaic output maximization grid connection strategy, an inverter power hierarchical decreasing adjustment strategy, and a load adjustment strategy, the photovoltaic terminal device further includes an energy storage system, and the matching a corresponding preset debugging strategy according to the system operation data and performing dynamic debugging on the photovoltaic terminal device that passes the authentication includes:

[0008] When the solar radiation intensity is greater than a preset intensity threshold and the load data is less than a preset load threshold, then performing the photovoltaic output maximization grid connection strategy on the photovoltaic module;

[0009] When the load volatility is greater than a preset volatility threshold and the photovoltaic power generation efficiency is lower than the historical power generation efficiency average value, then performing the inverter power hierarchical decreasing adjustment strategy on the inverter;

[0010] When the load data is within the preset system rated capacity range, the load regulation strategy is executed on the photovoltaic module and / or the energy storage system.

[0011] Optionally, it further includes:

[0012] Real-time obtain the device operation data corresponding to the photovoltaic terminal device that has passed authentication and is connected to the new energy distribution network system;

[0013] Wherein, the photovoltaic terminal device accesses the new energy distribution network system through a communication protocol;

[0014] Perform validity verification on the device operation data;

[0015] When the validity verification result is that the data is valid, the device operation data is used as the target device operation data;

[0016] When the validity verification result is that the data is invalid, perform data repair on the device operation data to obtain the target device operation data;

[0017] Based on the target device operation data, perform functional regulation on the photovoltaic terminal device.

[0018] Optionally, the target device operation data includes photovoltaic module power parameters and inverter power parameters. Based on the target device operation data, performing functional regulation on the photovoltaic terminal device includes:

[0019] Perform integrity detection on the photovoltaic module power parameters;

[0020] When the integrity detection result is that the data is not complete, jump to execute the step of performing validity verification on the device operation data;

[0021] When the integrity detection result is that the data is complete, perform temperature compensation calibration and maximum power point tracking on the photovoltaic module respectively based on the photovoltaic module power parameters;

[0022] Based on the inverter power parameters, perform overvoltage and overcurrent detection on the inverter;

[0023] When the overvoltage and overcurrent detection result is that there is an overvoltage or overcurrent phenomenon, perform inverter output power matching on the inverter based on the inverter power parameters.

[0024] Optionally, the photovoltaic module power parameters include photovoltaic module voltage and photovoltaic module current. Based on the photovoltaic module power parameters, performing temperature compensation calibration and maximum power point tracking on the photovoltaic module respectively includes:

[0025] Based on the voltage of the photovoltaic module, temperature compensation calibration is performed using a preset calibration formula to obtain a photovoltaic calibrated voltage;

[0026] The current voltage of the photovoltaic module is adjusted to the photovoltaic calibrated voltage through a preset voltage regulator;

[0027] A multiplication operation is performed using the photovoltaic calibrated voltage and the current of the photovoltaic module to obtain a photovoltaic calibrated power;

[0028] Based on the photovoltaic calibrated power, a maximum power point tracking is performed on the photovoltaic module using a preset MPPT controller.

[0029] Optionally, the inverter power parameters include inverter current and inverter voltage. The matching of the inverter output power based on the inverter power parameters includes:

[0030] A multiplication operation is performed using the inverter current and the inverter voltage to obtain an inverter power;

[0031] When the inverter power is within a preset first power calibration interval, a multiplication operation is performed using the first power calibration coefficient associated with the preset first power calibration interval and the inverter current to obtain a first inverter calibrated current;

[0032] The current of the inverter is adjusted to the first inverter calibrated current;

[0033] When the inverter power is within a preset second power calibration interval, a multiplication operation is performed using the second power calibration coefficient associated with the preset second power calibration interval and the inverter current to obtain a second inverter calibrated current;

[0034] The current of the inverter is adjusted to the second inverter calibrated current;

[0035] When the inverter power is within a preset third power calibration interval, a multiplication operation is performed using the third power calibration coefficient associated with the preset third power calibration interval and the inverter current to obtain a third inverter calibrated current;

[0036] The current of the inverter is adjusted to the third inverter calibrated current.

[0037] Optionally, it further includes:

[0038] Based on the target device operation data, a fault diagnosis is performed on the photovoltaic terminal device;

[0039] Determine the faulty device according to the fault diagnosis result;

[0040] Match with the pre-established standby device priority list input by the faulty device, output the target standby device and perform device switching.

[0041] Optionally, the photovoltaic terminal device further includes a collection terminal, and the target device operation data further includes collection terminal operation parameters. The fault diagnosis of the photovoltaic terminal device based on the target device operation data includes:

[0042] When the power parameters of the photovoltaic module meet the associated preset current-voltage overlimit rule or preset temperature anomaly rule, it is determined that the photovoltaic module is faulty;

[0043] When the power parameters of the inverter meet the associated preset current-voltage overlimit rule or preset temperature anomaly rule, it is determined that the inverter is faulty;

[0044] When the operation parameters of the collection terminal meet the preset communication fault rule, it is determined that the collection terminal is faulty.

[0045] Optionally, it further includes:

[0046] Establish at least two independent communication link paths for the photovoltaic terminal device, and real-time detect the communication delay and packet loss rate associated with the photovoltaic terminal device;

[0047] When the communication delay associated with the main communication link path of the photovoltaic terminal device is greater than the preset delay threshold or the packet loss rate is greater than the preset packet loss rate threshold, switch to the standby communication link path.

[0048] Optionally, it further includes:

[0049] Real-time record the target device operation data of the photovoltaic terminal device from the first preset time point before the fault occurs to the second preset time point after the fault is repaired, and generate a debugging log.

[0050] Optionally, it further includes:

[0051] Calculate the total deviation amount between the actual value of the evaluation dimension associated with the new energy distribution network system after dynamic debugging and the preset evaluation dimension target value;

[0052] Obtain the initial debugging weight coefficient associated with the preset debugging strategy;

[0053] Input the initial debugging weight coefficient, the total deviation amount and the preset evaluation dimension target value into a preset evaluation matrix to determine the target debugging weight coefficient;

[0054] Sort the preset debugging strategies based on the target debugging weight coefficient;

[0055] Jump to the step of matching the corresponding preset debugging strategy according to the system operation data and dynamically debugging the authenticated photovoltaic terminal device based on the sorted preset debugging strategy.

[0056] Optionally, it further includes:

[0057] Conduct a fault simulation test on the new energy power distribution system and generate a self-healing ability evaluation report according to the simulation test results.

[0058] An intelligent debugging device for a new energy power distribution photovoltaic automation terminal provided in the second aspect of the present invention includes:

[0059] An equipment access detection module, configured to perform equipment network access authentication on a photovoltaic terminal device to be connected to the new energy power distribution system and obtain the system operation data of the new energy power distribution system, where the photovoltaic terminal device includes a photovoltaic module and an inverter;

[0060] A debugging strategy generation module, configured to match the corresponding preset debugging strategy according to the system operation data and dynamically debug the authenticated photovoltaic terminal device.

[0061] An electronic device provided in the third aspect of the present invention includes a memory and a processor. When the computer program stored in the memory is executed by the processor, the processor executes the steps of the intelligent debugging method for the new energy power distribution photovoltaic automation terminal as described in any one of the above.

[0062] A computer-readable storage medium provided in the fourth aspect of the present invention stores a computer program, and when the computer program is executed, it implements the intelligent debugging method for the new energy power distribution photovoltaic automation terminal as described in any one of the above.

[0063] A computer program product provided in the fifth aspect of the present invention includes a computer program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions. When the program instructions are executed by a computer, the computer executes the intelligent debugging method for the new energy power distribution photovoltaic automation terminal as described in any one of the above.

[0064] It can be seen from the above technical solutions that the present invention has the following advantages:

[0065] In the present invention, first, the network access authentication is performed through an automated device to ensure that the photovoltaic terminal device meets the technical standards and safety requirements of the new energy distribution network system, avoiding the inefficiency of manual authentication. Then, according to the obtained system operation data, the corresponding preset debugging strategy under the current working condition is automatically matched, solving the limitation that traditional static rules cannot adapt to high dynamic changes. Finally, when the preset working condition is triggered, the corresponding preset debugging strategy is automatically executed to dynamically adjust and optimize the authenticated photovoltaic terminal device, ensuring that the new energy distribution network system can operate efficiently and stably under different working conditions, significantly improving the power generation efficiency and grid stability of the new energy distribution network system. At the same time, through unified debugging strategies and real-time data driving, the collaborative optimization of multiple photovoltaic terminal devices is realized, solving the problem that it is difficult to coordinate the operation of multiple devices in traditional methods and meeting the technical requirements of the power distribution network system. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0067] Figure 1 It is a flowchart of the steps of an intelligent debugging method for a new energy distribution network photovoltaic automation terminal provided in Embodiment 1 of the present invention;

[0068] Figure 2 It is a flowchart of the steps of an intelligent debugging method for a new energy distribution network photovoltaic automation terminal provided in Embodiment 2 of the present invention;

[0069] Figure 3 It is a structural block diagram of an intelligent debugging device for a new energy distribution network photovoltaic automation terminal provided in Embodiment 3 of the present invention;

[0070] Figure 4 It is a structural block diagram of a computer device provided in Embodiment 4 of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0071] Embodiments of the present invention provide an intelligent debugging method and device for a new energy distribution network photovoltaic automation terminal, which are used to solve the technical problem that traditional debugging methods rely on manual operations and static rules and are difficult to meet the requirements of a highly dynamic and multi-device collaborative photovoltaic power distribution network system.

[0072] To make the objectives, features, and advantages of the present invention more obvious and understandable, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the embodiments described below are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative work fall within the scope of protection of the present invention.

[0073] Currently, traditional debugging methods rely on manual operations and static rules, making it difficult to meet the requirements of highly dynamic and multi-device collaborative photovoltaic distribution network systems. Specifically, the following technical bottlenecks exist:

[0074] 1. Low efficiency in device access and status monitoring;

[0075] In the prior art, device access detection mostly uses a single communication protocol (such as only supporting Modbus RTU (Remote Terminal Unit is a serial communication protocol for realizing data exchange between devices)), which cannot adapt to the protocol differences of multi-vendor devices, resulting in the need for manual configuration of communication parameters in the early stage of debugging. At the same time, device identity authentication relies on offline ledger verification, and illegal device access is easily caused by human input errors. In addition, the data collection frequency is low (such as once per minute), making it difficult to capture instantaneous abnormalities in current and voltage in a timely manner, resulting in an increased misjudgment rate of the online status of devices.

[0076] 2. Lack of dynamic optimization ability in debugging strategies;

[0077] Current debugging schemes mostly generate strategies based on fixed thresholds and do not integrate real-time load, meteorological data (such as solar radiation intensity), and historical power generation trends. For example, in scenarios of fluctuating solar radiation intensity or sudden load increase, the photovoltaic output power and grid connection strategy cannot be dynamically adjusted, resulting in low power generation efficiency or the risk of inverter overload. In addition, the debugging strategy is disconnected from the device parameter calibration and fault repair links, making it difficult to form a closed-loop optimization, resulting in repeated debugging and resource waste.

[0078] 3. Imperfect fault diagnosis and system self-healing mechanism;

[0079] The prior art relies on single-threshold alarms (such as current overlimit) for detecting device faults, lacks a multi-dimensional rule base (such as temperature and communication status linkage analysis), has a high false alarm rate, and the repair method is passive (such as only restarting the device). Environmental factors (such as the influence of temperature on output voltage) are not considered during parameter calibration, and the error accumulation after long-term operation exacerbates the degradation of device performance. In addition, the system lacks an automatic switching mechanism for standby devices and a self-healing ability verification function, and fault repair relies on manual intervention, resulting in an extended downtime.

[0080] The above-mentioned defects result in a long commissioning period for the photovoltaic distribution network system, low equipment utilization rate, and insufficient long-term operation stability. There is an urgent need for an automated commissioning technology that can achieve intelligent device access, dynamic strategy optimization, and closed-loop self-healing to improve the reliability and operation and maintenance efficiency of the photovoltaic distribution network system.

[0081] During the implementation of the intelligent commissioning method for the new energy distribution network photovoltaic automation terminal provided by the invention embodiment, each step is organically connected and data flows to ensure the efficient and stable operation of the system. Through intelligent device access, dynamically optimized commissioning strategies, and efficient self-healing capabilities, the above-mentioned technical bottlenecks such as low device access efficiency, fixed commissioning strategies, and insufficient fault diagnosis and self-healing capabilities have been successfully overcome.

[0082] Please refer to Figure 1 , Figure 1 which is the flowchart of the steps of an intelligent commissioning method for a new energy distribution network photovoltaic automation terminal provided in Embodiment 1 of the present invention.

[0083] An intelligent commissioning method for a new energy distribution network photovoltaic automation terminal provided by the present invention includes:

[0084] Step 101: Conduct device network access authentication for the photovoltaic terminal device to be connected to the new energy distribution network system, and obtain the system operation data of the new energy distribution network system. The photovoltaic terminal device includes a photovoltaic module and an inverter;

[0085] Device network access authentication refers to a series of verification and authorization processes that the photovoltaic terminal device needs to go through when accessing the new energy distribution network system to ensure that the device meets the technical standards, safety requirements, and operation specifications of the system. The process of device network access authentication includes, but is not limited to, device identity verification (such as device serial number, etc.), verifying whether the communication protocol of the device is compatible with the system, and verifying whether the device meets relevant safety standards.

[0086] System operation data refers to the key parameters and indicators related to the system operation status, performance, and environment, including, but not limited to, solar radiation intensity, load data, load volatility, photovoltaic power generation efficiency, and historical average power generation efficiency, etc. Among them, for example, the load volatility is obtained by the built-in preset algorithm unit of the device through load data operation. This is a conventional load volatility operation process. Other similar data, such as the historical average power generation efficiency, can also be obtained through conventional algorithms and will not be elaborated here.

[0087] Photovoltaic terminal device is a set of devices used to complete functions such as converting solar energy into electrical energy, electrical energy management, data transmission, and system control in a photovoltaic power generation system. It includes, but is not limited to, photovoltaic modules, inverters, acquisition terminals, etc.

[0088] In an embodiment of the present invention, network access authentication is performed on a photovoltaic terminal device to ensure that the photovoltaic terminal device meets the requirements of a new energy distribution network system, and system operation data of the new energy distribution network system is obtained after the photovoltaic terminal device is connected. The photovoltaic terminal device includes a photovoltaic module and an inverter.

[0089] Step 102: Match corresponding preset debugging strategies according to the system operation data, and perform dynamic debugging on the authenticated photovoltaic terminal device.

[0090] The preset debugging strategy refers to a debugging scheme or rule preset according to the characteristics and operation requirements of the new energy distribution network system, and is used to dynamically adjust the operation state of the photovoltaic terminal device under different working conditions, so as to optimize the performance of the new energy distribution network system, improve the power generation efficiency, and ensure the stable operation of the power grid.

[0091] It should be noted that the debugging strategy is based on the analysis of system operation data and can be automatically executed when a specific condition is triggered. The specific condition refers to when the system operation data meets the preset working condition, and each preset debugging strategy corresponds to at least one set of preset working conditions.

[0092] Dynamic debugging refers to adjusting and optimizing the photovoltaic terminal device according to the system operation data of the new energy distribution network system in the actual operation environment to ensure that it can operate efficiently and stably under different working conditions.

[0093] In an embodiment of the present invention, through the collected system operation data of the new energy distribution network system, the corresponding preset debugging strategy under the working condition where the current new energy distribution network system is located is matched according to the system operation data, and the preset debugging strategy is triggered and executed based on the preset working condition, and dynamic debugging operations are performed on the authenticated photovoltaic terminal device to optimize the performance of the new energy distribution network system, improve the power generation efficiency, and ensure the stable operation of the power grid.

[0094] In the present invention, first, network access authentication is performed through an automated device to ensure that the photovoltaic terminal device meets the technical standards and safety requirements of the new energy distribution network system, avoiding the inefficiency of manual authentication. Then, the corresponding preset debugging strategy under the current working condition is automatically matched according to the obtained system operation data, solving the limitation that traditional static rules cannot adapt to high-dynamic changes. Finally, when the preset working condition is triggered, the corresponding preset debugging strategy is automatically executed, and dynamic adjustment and optimization are performed on the authenticated photovoltaic terminal device to ensure that the new energy distribution network system can operate efficiently and stably under different working conditions, significantly improving the power generation efficiency and power grid stability of the new energy distribution network system; at the same time, through unified debugging strategies and real-time data driving, the collaborative optimization of multiple photovoltaic terminal devices is realized, solving the technical problem that it is difficult to coordinate the operation of multiple devices in the traditional method to meet the requirements of the network system.

[0095] Please refer to Figure 2 ,Figure 2 This is a flowchart of the steps for an intelligent debugging method of a new - energy distribution network photovoltaic automation terminal provided in the second embodiment of the present invention.

[0096] An intelligent debugging method of a new - energy distribution network photovoltaic automation terminal provided by the present invention includes:

[0097] Step 201: Perform device network access authentication on the photovoltaic terminal device to be connected to the new - energy distribution network system, and obtain the system operation data of the new - energy distribution network system. The photovoltaic terminal device includes a photovoltaic module and an inverter.

[0098] In the embodiment of the present invention, the specific implementation process of step 201 is similar to that of step 101, and will not be elaborated here.

[0099] Step 202: Match the corresponding preset debugging strategy according to the system operation data, and perform dynamic debugging on the authenticated photovoltaic terminal device.

[0100] It should be noted that traditional static rules usually only consider a single variable and cannot comprehensively consider the complex relationships among multiple variables. For example, static rules may only execute strategies based on "solar radiation intensity" and ignore the influence of other key parameters such as "load data". In the operating environment of a highly dynamic new - energy distribution network system, a single variable cannot fully reflect the system working conditions, which may lead to inaccurate strategy execution. More specifically, when the solar radiation intensity is high but the load volatility is also high, static rules may still execute the "maximum photovoltaic output grid - connection strategy" while ignoring the impact of load fluctuations on system stability.

[0101] It is worth mentioning that by using the key - value pair matching method, the system operation data is used to match the corresponding preset debugging strategy. The specific matching method is as follows:

[0102] T1: When the solar radiation intensity is greater than the preset intensity threshold and the load data is less than the preset load threshold, generate a first target key using the solar radiation intensity and the load data;

[0103] T2: Query the preset key - value pair strategy library using the first target key to match the corresponding first target value. The first target value is the maximum photovoltaic output grid - connection strategy;

[0104] T3: When the load volatility is greater than the preset volatility threshold and the photovoltaic power generation efficiency is lower than the historical power generation efficiency average value, generate a second target key using the load volatility and the photovoltaic power generation efficiency;

[0105] T4: Query the preset key - value pair strategy library using the second target key to match the corresponding second target value. The second target value is the inverter power hierarchical decreasing adjustment strategy;

[0106] T5. When the load data is within the preset system rated capacity range, the third target key is generated using the load ratio.

[0107] T6. Query the preset key-value pair policy library using the third target key to match the corresponding third target value, which is the load regulation strategy.

[0108] It should be noted that the preset debugging strategies in the preset key-value pair policy library are generated through a scheduling algorithm and include debugging solutions for load regulation strategies, inverter power hierarchical decreasing regulation strategies, and photovoltaic output maximization grid connection strategies, and output specific debugging steps, equipment lists, and parameter setting instructions. Dynamically adjust the operating state of the system based on specific conditions to optimize the collaborative working efficiency of the power grid and photovoltaic terminal equipment. The implementation of these debugging strategies can effectively improve the economy and stability of photovoltaic power generation through precise condition determination and strategy application.

[0109] The preset key-value pair policy library refers to a key-value pair database established based on the associations between solar radiation intensity, load data, load volatility, photovoltaic power generation efficiency, and load ratio and the preset debugging strategies. Among them, one or two data combinations of solar radiation intensity, load data, load volatility, photovoltaic power generation efficiency, and load ratio are used as keys, and the preset debugging strategies are used as values.

[0110] Furthermore, the system operation data includes solar radiation intensity, load data, load volatility, photovoltaic power generation efficiency, and historical power generation efficiency average value. The preset debugging strategies include photovoltaic output maximization grid connection strategies, inverter power hierarchical decreasing regulation strategies, and load regulation strategies. The photovoltaic terminal equipment also includes an energy storage system. Step 202 may include the following sub-steps:

[0111] It should be noted that after the access detection of the photovoltaic terminal equipment is completed, the system generates preset debugging strategies by collecting the system operation data of the distribution network system in real time using a scheduling algorithm. The preset debugging strategies include photovoltaic output maximization grid connection strategies, inverter power hierarchical decreasing regulation strategies, and load regulation strategies, and dynamically generate the most suitable debugging solution according to the real-time environmental data. The debugging solution outputs specific debugging steps, equipment lists, and parameter setting instructions to guide subsequent operations. This step can optimize the debugging strategy according to the real-time load and solar radiation intensity, ensure that the grid connection debugging of the new energy distribution network system and the power adjustment of the inverter are most in line with the current conditions, improve the flexibility and adaptability of the debugging process, and avoid over-debugging or ineffective operations.

[0112] S11. When the solar radiation intensity is greater than the preset intensity threshold and the load data is less than the preset load threshold, the photovoltaic output maximization grid connection strategy is executed for the photovoltaic module.

[0113] In an embodiment of the present invention, the solar radiation intensity and load data are monitored in real time. When the solar radiation intensity exceeds a preset intensity threshold (i.e., ≥800W / m²) and the load data is lower than a preset load threshold (i.e., the carrying capacity of the new energy distribution network system), the new energy distribution network system will start the photovoltaic output maximization grid-connected strategy.

[0114] In the specific implementation, the two factors of solar radiation intensity and load data are collected and analyzed in real time by the system to determine whether the debugging strategy needs to be started. When the solar radiation intensity reaches the preset threshold and the grid load is low, the system will enable the strategy of maximizing photovoltaic output, which can ensure that the power generation is maximized under suitable lighting conditions. The specific operation process includes:

[0115] Send instructions to all online inverters to fix the power factor to 1.0 (pure active output) and remove the power limit threshold to allow the inverters to operate at maximum capacity;

[0116] The sampling frequency of the maximum power point tracking (MPPT) algorithm is increased to 5 times per second, and combined with real-time irradiance data, the working point of the photovoltaic module array is dynamically adjusted to ensure that the global maximum power is locked within 10 seconds.

[0117] At this time, the new energy distribution network system will output the maximum power as much as possible to make full use of the abundant sunlight and improve the power generation efficiency. Carrying capacity refers to the maximum load capacity of the power grid. The new energy distribution network system will monitor the load of the power grid in real time. If the load is low, more photovoltaic power can be connected to the grid to reduce the burden on the power grid and optimize energy use.

[0118] S12. When the load fluctuation rate is greater than the preset fluctuation rate threshold and the photovoltaic power generation efficiency is lower than the historical power generation efficiency average, the inverter power graded decreasing adjustment strategy is executed on the inverter.

[0119] It is worth mentioning that the historical average power generation efficiency refers to the average value of photovoltaic power generation efficiency in the same time period in the past 30 days. This indicator helps to determine whether the current photovoltaic power generation is in a low efficiency state, thereby determining whether a power regulation strategy is needed.

[0120] In an embodiment of the present invention, when it is detected that the load fluctuation rate exceeds 20% (i.e., the preset fluctuation rate threshold, the load changes greatly, which may cause grid fluctuations) and the current photovoltaic power generation efficiency is lower than the historical average of the power generation efficiency in the same time period of the past 30 days (i.e., the historical power generation efficiency average), the system executes the inverter power graded decreasing adjustment strategy for the inverter.

[0121] In a specific implementation, when the load fluctuates greatly and the photovoltaic power generation efficiency is lower than the historical average, the system determines whether adjustment is needed by comparing historical data. At this time, the hierarchical decreasing adjustment strategy of the inverter power is activated to alleviate the impact of grid load fluctuations and avoid unnecessary power losses. The specific operation process includes:

[0122] By adjusting the output power of the inverter, gradually reduce the grid-connected photovoltaic power generation to reduce the burden on the grid and avoid power fluctuations caused by grid load fluctuations.

[0123] S13. When the load data is within the preset system rated capacity range, execute the load adjustment strategy.

[0124] It is worth mentioning that the preset system rated capacity range includes the first rated capacity range, the second rated capacity range, and the third rated capacity range. Among them, the system operation data also includes the system rated capacity. The first rated capacity area is specifically [0, 40% of the system rated capacity), the second rated capacity area is specifically [40% of the system rated capacity, 80% of the system rated capacity], and the third rated capacity area is specifically (80% of the system rated capacity, 100% of the system rated capacity].

[0125] In the embodiment of the present invention, when the load data is within the preset system rated capacity range, execute the load adjustment strategy, which specifically includes a three-stage load adjustment:

[0126] When the load data is lower than 40% of the grid rated capacity, it is determined as a low load state. The system preferentially activates the energy storage charging mode, charges the energy storage system at 80% of the photovoltaic maximum power, and automatically turns on adjustable load devices (such as charging piles, heat storage devices). Among them, the low load state mainly adjusts the photovoltaic module (limiting the output power) and the energy storage system (charging).

[0127] When the load data is in the medium load range of 40%-80% of the rated capacity, the system switches to the maximum power tracking mode, the energy storage system enters the standby state, and at the same time, non-critical loads with an intelligent cut-off error range controlled within ±3% are cut off. Among them, the medium load state mainly adjusts the photovoltaic module (maximum power tracking) and non-critical loads (intelligent cut-off);

[0128] When the load data exceeds 80% of the rated capacity, activate the over-generation mode to increase the photovoltaic power to 105% of the rated value, the energy storage system discharges synchronously to compensate for the grid power gap, and trigger the demand response protocol to adjust the load on the power consumption side. Among them, the high load state mainly adjusts the photovoltaic module (over-generation mode) and the energy storage system (discharge).

[0129] In the embodiments of the present invention, through the real-time analysis of solar radiation intensity, load data, load volatility, photovoltaic power generation efficiency, and the average value of historical power generation efficiency, and the precise application of adjustment strategies, it is possible to achieve dynamic balance between photovoltaic power generation and the load of the system power grid, thereby optimizing energy utilization, reducing fluctuations, and improving the overall operating efficiency of the system.

[0130] It is worth mentioning that the present invention reduces the need for manual intervention and improves the accuracy and efficiency of debugging photovoltaic terminal equipment through automated and intelligent debugging strategies. Through functions such as real-time data acquisition, automatic debugging, and fault repair, the stability and power generation efficiency of the new energy distribution network system have been greatly improved, with significant economic and environmental benefits.

[0131] The present invention automatically optimizes the debugging strategy by introducing a dynamic debugging strategy and combining real-time load data, solar radiation intensity, and historical power generation trends. For example, the system dynamically adjusts the output power and grid connection strategy of the photovoltaic system according to solar radiation intensity and load fluctuations, avoiding inefficiencies and equipment overloads caused by fixed thresholds. The real-time adjustment and equipment parameter calibration during the debugging process form a closed loop, enabling the results of each debugging to be used as the basis for subsequent debugging, thereby gradually improving the overall performance of the system.

[0132] Furthermore, before the step of functionally regulating the photovoltaic terminal equipment, the following steps are also included. A1 - A4 are the specific processes for obtaining the operating data of the target equipment:

[0133] A1. Real-time obtain the equipment operating data corresponding to the photovoltaic terminal equipment that has passed authentication and is connected to the new energy distribution network system;

[0134] Among them, the photovoltaic terminal equipment accesses the new energy distribution network system through a communication protocol.

[0135] The equipment operating data refers to the key parameters and indicators generated during the operation of the photovoltaic terminal equipment, which are used for system monitoring and dynamic debugging.

[0136] The communication protocol refers to the standardized rules for data exchange and communication between the equipment and the system, ensuring the real-time, reliable, and secure nature of the data.

[0137] It is worth mentioning that the communication protocol includes at least one of Modbus RTU, DNP3, and IEC 61850. When verifying the legitimacy of the identity, the equipment serial number is compared with the pre-stored database in the system for verification.

[0138] Based on the device access detection step, through the automatic selection of debugging strategies and the self-check of device functions, the efficient operation of the new energy distribution network system is ensured. The fault detection and automatic repair step guarantees the stability and self-healing ability of the system, while the debugging result feedback and optimization step ensures that the system can continuously improve itself. All modules cooperate closely through data exchange and instruction transfer to jointly achieve the intelligent debugging of the new energy distribution network system.

[0139] The present invention adopts a device access method with multi-protocol support to automatically adapt to the device communication protocols of different manufacturers, avoiding the complex process of manual configuration and the problems brought by protocol differences, and fundamentally improving the efficiency of device access. The system uses dynamic identity authentication and online verification to ensure that all accessed devices are legal and effective, eliminating the risk of illegal device access caused by manual entry errors. Compared with traditional technologies, the present invention increases the data acquisition frequency and real-time monitoring ability, and can capture the instantaneous changes of parameters such as current and voltage within each second, thereby effectively reducing the misjudgment of the online state and enhancing the operation monitoring ability of the device.

[0140] Modbus RTU, where Modbus refers to the Remote Terminal Unit protocol, and Modbus RTU is a serial communication mode of the Modbus protocol, using binary encoding for data transmission through RS-232 or RS-485 interfaces.

[0141] DNP3 refers to the Distributed Network Protocol 3, which is a communication protocol designed specifically for power systems.

[0142] IEC 61850 refers to an international standard for power system automation.

[0143] It should be noted that the communication protocol is mainly used to ensure the stability and accuracy of the access detection and data exchange of photovoltaic devices. The identity legality of photovoltaic terminal devices is verified by comparing the device serial number with the pre-stored database of the system, and the implementation method of this process has clear steps and effective connection mechanisms.

[0144] Specifically, first, communication between photovoltaic terminal devices and the new energy distribution network system is achieved by selecting communication protocols such as Modbus RTU, DNP3, or IEC 61850. Among them, the Modbus RTU protocol is usually used for the remote monitoring of low-speed devices, especially suitable for photovoltaic inverters and other low-bandwidth devices, and supports multi-point communication. The DNP3 protocol is commonly used in larger distribution networks and power systems, suitable for higher communication frequencies and the requirements of data exchange between devices, and has strong anti-interference ability. The IEC 61850 protocol is suitable for more complex smart grid systems, can process real-time status data and event reports, and supports efficient data exchange and automated control.

[0145] The new - energy distribution network system uses these protocols to communicate with photovoltaic terminal devices and first authenticates the identity of the devices. The devices interact with the system through the communication protocol and transmit information such as the unique serial number, model, software version, etc. of the devices to the distribution network dispatching system.

[0146] The identity legality of the device is verified by comparing the serial number with the pre - stored database in the system. The pre - stored database stores the serial numbers and identity information of all allowed - access photovoltaic terminal devices. After successful comparison, the device is authorized to access the network and starts data collection.

[0147] Once the identity authentication is passed, the new - energy distribution network system starts to collect data such as voltage, current, power, etc. of the photovoltaic terminal devices in real - time and checks the validity of these data. The communication protocol ensures the reliable transmission and real - time update of the data.

[0148] Photovoltaic terminal devices (such as photovoltaic modules, inverters, acquisition terminals) are connected to the distribution network control system through the selected communication protocol (ModbusRTU, DNP3, IEC 61850, etc.). This process automates identity authentication, data transmission, and device access through the communication protocol. After the device serial number is transmitted to the new - energy distribution network system through the communication protocol, the new - energy distribution network system verifies the identity of the photovoltaic terminal device by comparing the device information stored in the database. If the verification is passed, the photovoltaic terminal device can be connected to the system and enter the next stage of commissioning and operation.

[0149] By selecting an appropriate communication protocol and identity authentication mechanism, this method ensures the safe and efficient access of photovoltaic terminal devices and provides reliable data support for subsequent automated commissioning and system optimization.

[0150] In the embodiment of the present invention, the new - energy distribution network system conducts access detection on photovoltaic terminal devices through the communication protocol to ensure that photovoltaic terminal devices such as photovoltaic modules, inverters, and acquisition terminals are successfully connected to the new - energy distribution network system. The identity authentication information of the photovoltaic terminal device is verified for its legality by comparing the serial number with the preset system database, ensuring that only authorized devices are connected. By generating an access status report, the new - energy distribution network system can provide the online status, data collection status, and abnormal information of the devices in real - time, providing an important basis for subsequent dynamic commissioning and fault troubleshooting. Effectively conduct a preliminary inspection on the connected photovoltaic terminal devices, avoid the access of illegal or faulty devices, ensure the smooth progress of subsequent commissioning work, and improve the security and reliability of the system.

[0151] A2. Verify the validity of the device operation data.

[0152] Validity verification refers to checking whether the device operation data is within a reasonable physical range. Specifically, according to the technical parameters and historical data of the device, the valid range (minimum value and maximum value) of each parameter is set, and it is checked whether the current device operation data is within the valid range.

[0153] In the embodiment of the present invention, for the validity verification of the device operation data, if the device operation data exceeds the range, it is marked as invalid data; if the device operation data does not exceed the range, it is marked as valid data.

[0154] A3. When the validity verification result is that the data is valid, the device operation data is used as the target device operation data.

[0155] In the embodiment of the present invention, when the validity verification result is that the data is valid, it means that there is no invalid data in the device operation data, and the device operation data is directly used as the target device operation data.

[0156] A4. When the validity verification result is that the data is invalid, data repair is performed on the device operation data to obtain the target device operation data.

[0157] In the embodiment of the present invention, when the validity verification result is that the data is invalid, data repair is performed on the device operation data. For example, data interpolation method can be used for interpolation to fill the invalid device operation data, or the historical data mean method can be used to replace the invalid device operation data with the mean or median of the historical data, etc., which is not limited here. By performing data repair on the device operation data, the target device operation data is obtained, and it can also be redirected to step A2 for verification.

[0158] Furthermore, based on the target device operation data, the function regulation of the photovoltaic terminal device is specifically as shown in steps 203 - 207. The target device operation data includes photovoltaic module power parameters and inverter power parameters.

[0159] Step 203. Perform integrity detection on the photovoltaic module power parameters.

[0160] It should be noted that performing integrity detection on the photovoltaic module power parameters can ensure that the photovoltaic module can operate as expected.

[0161] In the embodiment of the present invention, for the integrity detection of the photovoltaic module power parameters, since the collected device operation data is collected at a preset time interval, therefore, the collected data forms time series data. Therefore, it is necessary to perform integrity detection on the photovoltaic module power parameters to check whether there are missing values. If there are missing values, it is marked as incomplete data; if there are no missing values, it is marked as complete data.

[0162] Step 204: When the integrity detection result indicates that the data is incomplete, jump to the step of validating the effectiveness of the device operating data.

[0163] In the embodiment of the present invention, when the integrity detection result indicates that the data is incomplete, missing value filling can be performed on the power parameters of the photovoltaic module with incomplete data, and then jump back to step A2 for verification until the effectiveness verification result indicates that the data is valid and the integrity detection result indicates that the data is complete.

[0164] Step 205: When the integrity detection result indicates that the data is complete, perform temperature compensation calibration and maximum power point tracking on the photovoltaic module based on the power parameters of the photovoltaic module.

[0165] In step 205, calibrating the voltage of the photovoltaic module can ensure that the system operates efficiently and stably under different environmental conditions, thereby improving the overall power generation efficiency and power quality.

[0166] Furthermore, the power parameters of the photovoltaic module include the voltage of the photovoltaic module and the current of the photovoltaic module. Step 205 may include the following sub-steps:

[0167] S21: Based on the voltage of the photovoltaic module, perform temperature compensation calibration using a preset calibration formula to obtain the calibrated photovoltaic voltage.

[0168] Temperature compensation calibration refers to correcting the output voltage of the photovoltaic module through a preset calibration formula to eliminate or reduce the influence of ambient temperature changes on the voltage measurement value, thereby ensuring the accuracy of the voltage data. The specific purpose is to make the output voltage of the photovoltaic module reflect the true value under different temperature conditions and avoid measurement deviations caused by temperature fluctuations.

[0169] In a specific implementation, the preset calibration formula is specifically:

[0170]

[0171] In the formula, represents the calibrated photovoltaic voltage after calibration, represents the voltage of the photovoltaic module before calibration, represents the temperature coefficient of the photovoltaic module, which is provided by the device manufacturer and pre-stored in the system, represents the current ambient temperature, represents the reference temperature, which is set to 25 °C.

[0172] It should be noted that the voltage of the photovoltaic module of the photovoltaic module will change with the change of the ambient temperature. By performing temperature compensation calibration according to the actual ambient temperature and correcting the voltage of the photovoltaic module, the voltage accuracy at different temperatures is ensured. The temperature coefficient It will be provided according to the material characteristics of the photovoltaic module, which can effectively correct the influence of temperature on voltage, enabling the photovoltaic module to maintain high output stability.

[0173] In the embodiment of the present invention, through a preset calibration formula, the voltages of the photovoltaic module measured at different temperatures are uniformly corrected to the photovoltaic calibration voltage corresponding to the standard reference temperature, so as to eliminate the interference of temperature on voltage measurement and ensure data accuracy and system stability.

[0174] S22. Adjust the current voltage of the photovoltaic module to the photovoltaic calibration voltage through a preset voltage regulator.

[0175] The preset voltage regulator refers to a voltage control module based on hardware or algorithm, which is used to dynamically adjust the output voltage of the photovoltaic module to a preset target value to ensure voltage stability.

[0176] In the embodiment of the present invention, through the preset voltage regulator in the new energy distribution network system, the current voltage of the photovoltaic module is adjusted to the temperature-compensated photovoltaic calibration voltage according to the preset voltage adjustment gradient, thereby overcoming the influence of environmental disturbances and achieving voltage stability and energy conversion optimization.

[0177] The preset voltage adjustment gradient refers to gradually adjusting the real-time output voltage of the photovoltaic module according to a preset step or rate, so that it smoothly transitions to the temperature-compensated photovoltaic calibration voltage, avoiding the impact of voltage mutation on the power grid or load.

[0178] S23. Perform a multiplication operation on the photovoltaic calibration voltage and the current of the photovoltaic module to obtain the photovoltaic calibration power.

[0179] In the embodiment of the present invention, a multiplication operation is performed on the photovoltaic calibration voltage and the current of the photovoltaic module to obtain the photovoltaic calibration power.

[0180] S24. Based on the photovoltaic calibration power, use a preset MPPT controller to perform maximum power point tracking on the photovoltaic module.

[0181] The preset MPPT controller refers to a power optimization algorithm, which is used to dynamically track the maximum power point of the photovoltaic module to ensure the maximization of energy conversion efficiency.

[0182] In the embodiment of the present invention, with the photovoltaic calibration power as the target, the photovoltaic module is dynamically operated at the real-time maximum power point through a preset MPPT controller, as close as possible to the photovoltaic calibration power, but not exceeding the environmental limit. The goal of the MPPT controller is to maximize the actual output power.

[0183] It is worth mentioning that in the new energy distribution network system, the strategy of first stabilizing the voltage through a voltage regulator and then optimizing the power through MPPT, that is, the two-stage regulation of "voltage first, power later", can avoid frequent oscillations caused by the initial voltage error of the photovoltaic module. The calibrated voltage of the photovoltaic after temperature compensation is already close to the voltage at the theoretical maximum power point. The MPPT algorithm does not need to search from the full range (such as 0~open circuit voltage), which accelerates the convergence speed of MPPT and significantly reduces the convergence time.

[0184] Step 206: Based on the inverter power parameters, perform overvoltage and overcurrent detection on the inverter.

[0185] In the embodiments of the present invention, the inverter power parameters are compared with a preset overvoltage threshold and / or a preset overcurrent threshold, so as to perform overvoltage and overcurrent detection on the inverter.

[0186] It should be noted that the inverter power parameters include the inverter current and the inverter voltage. Overvoltage / overcurrent is essentially the deviation between the actual output of the device and the theoretical value. Overvoltage / overcurrent is both a condition for protection triggering and a signal for calibration requirements. For example, when the inverter voltage rises above the overvoltage threshold, current / voltage parameter calibration needs to be performed to match the inverter output power.

[0187] In specific implementation, overvoltage / overcurrent detection provides a physical basis for power adjustment. When the inverter voltage exceeds the rated voltage of the inverter by a preset multiple coefficient (such as when ), if the rated voltage of the inverter is 750V and the measured inverter voltage is 800V, the power drops to 93.75% of the rated value to avoid damage to the device due to overvoltage on the DC side.

[0188] Step 207: When the overvoltage and overcurrent detection result shows that there is an overvoltage or overcurrent phenomenon, perform inverter output power matching on the inverter based on the inverter power parameters.

[0189] It should be noted that the inverter current will be affected by factors such as load and power output. Therefore, it is necessary to calibrate the current in segments according to different intervals of power output. In this segmented calibration strategy, the preset power calibration interval refers to dividing multiple calibration intervals according to different ranges of the inverter output power, and using different calibration coefficients (C1, C2, C3) for each interval to correct the current measurement error. This segmented calibration method can more accurately adapt to the measurement characteristics under different load conditions and improve the current detection accuracy in the entire working range.

[0190] Furthermore, the inverter power parameters include the inverter current and the inverter voltage. Step 207 may include the following sub-steps:

[0191] S31. Multiply the inverter current and the inverter voltage to obtain the inverter power.

[0192] In an embodiment of the present invention, the inverter current and the inverter voltage are multiplied to obtain the inverter power.

[0193] S32. When the inverter power is within a preset first power calibration range, multiply the first power calibration coefficient associated with the preset first power calibration range by the inverter current to obtain the first inverter calibration current.

[0194] The preset first power calibration range refers to a preset low-power output range, and specifically, the preset first power calibration range can be 0 - 30% of the rated power, which is used to determine whether the current inverter is in a low-power output state.

[0195] The first power calibration coefficient refers to a calibration coefficient C1 set during low-power output, which is used to correct the current measurement error during low-power output.

[0196] In an embodiment of the present invention, when the inverter power is within the preset first power calibration range, it is determined that the current inverter is in a low-power output state, and the first power calibration coefficient associated with the preset first power calibration range is multiplied by the inverter current to obtain the first inverter calibration current.

[0197] S33. Adjust the current of the inverter to the first inverter calibration current.

[0198] In an embodiment of the present invention, the current of the inverter is adjusted to the first inverter calibration current.

[0199] S34. When the inverter power is within a preset second power calibration range, multiply the second power calibration coefficient associated with the preset second power calibration range by the inverter current to obtain the second inverter calibration current.

[0200] The preset second power calibration range refers to a preset medium-power output range, and specifically, the preset second power calibration range can be 30 - 80% of the rated power, which is used to determine whether the current inverter is in a medium-power output state.

[0201] The second power calibration coefficient refers to a calibration coefficient C2 set during medium-power output, which is used to optimize the calibration in the medium-power range.

[0202] In an embodiment of the present invention, when the inverter power is within the preset second power calibration range, it is determined that the current inverter is in a medium-power output state, and the second power calibration coefficient associated with the preset second power calibration range is multiplied by the inverter current to obtain the second inverter calibration current.

[0203] S35. Adjust the current of the inverter to the second inverter calibration current.

[0204] In an embodiment of the present invention, the current of the inverter is adjusted to the second inverter calibration current.

[0205] S36. When the inverter power is within a preset third power calibration range, perform a multiplication operation on the inverter current using the third power calibration coefficient associated with the preset third power calibration range to obtain the third inverter calibration current.

[0206] The preset third power calibration range refers to a preset high-power output range, and the preset third power calibration range can specifically be 80 - 100% of the rated power, which is used to determine whether the current inverter is in a high-power output state.

[0207] The third power calibration coefficient refers to setting a calibration coefficient C3 during high-power output to correct the current error during high-power output.

[0208] In an embodiment of the present invention, when the inverter power is within the preset third power calibration range, it is determined that the current inverter is in a high-power output state, and a multiplication operation is performed on the inverter current using the third power calibration coefficient associated with the preset third power calibration range to obtain the third inverter calibration current.

[0209] S37. Adjust the current of the inverter to the third inverter calibration current.

[0210] In an embodiment of the present invention, the current of the inverter is adjusted to the third inverter calibration current.

[0211] It is worth mentioning that calibrating the inverter current of the inverter can ensure the efficient and stable operation of the system under different environmental conditions, thereby improving the overall power generation efficiency and power quality.

[0212] The calibration coefficient of the inverter current is provided by the parameters in its technical specification. By setting different calibration coefficients for different power output ranges respectively, the inverter current can be accurately calibrated according to the actual operating state, ensuring the accuracy of the current and the efficient operation of the system.

[0213] The photovoltaic module voltage of a photovoltaic module is closely related to temperature. As the temperature rises, the photovoltaic module voltage of the photovoltaic module usually decreases. Through temperature compensation calibration, the voltage deviation caused by environmental temperature changes can be corrected to ensure the stability of the output voltage under different environmental conditions. The inverter current of the inverter is closely related to the power output. Since the efficiency and current measurement characteristics of the inverter are different in different power output intervals, a three-stage segmented calibration is adopted. Different calibration coefficients can be set for each power interval according to the characteristics of each power interval, thus ensuring the accuracy of current measurement.

[0214] Through the temperature compensation calibration and segmented calibration of the photovoltaic module voltage and the inverter current, the debugging accuracy and system operation efficiency of the photovoltaic automation terminal can be significantly improved, providing guarantee for the high-efficiency and stable operation of the system, and enhancing the overall performance of the photovoltaic power generation system.

[0215] It should be noted that in steps 203 - 207, by detecting the operation data of the target device, according to the detection results, the system automatically performs current / voltage parameter calibration, inverter output power matching, and maximum power point tracking control of the photovoltaic module to ensure that the device output meets the performance standards. By automatically performing calibration and optimization control strategies, the output power of the photovoltaic module is maximized and the device operation stability is ensured, reducing manual intervention and enhancing the automation degree and accuracy of the entire system.

[0216] Furthermore, the following steps may also be included before step 208:

[0217] It should be noted that the communication stability between steps 202 - 207 is detected, that is, the communication link redundancy detection is performed on the communication link path. The status of each communication link path is monitored in real time, and when the main communication link path fails, it is automatically switched to the standby communication link path to ensure zero communication interruption.

[0218] B1. Establish at least two independent communication link paths for the photovoltaic terminal device, and detect the communication delay and packet loss rate associated with the photovoltaic terminal device in real time.

[0219] B2. When the communication delay associated with the main communication link path of the photovoltaic terminal device is greater than the preset delay threshold or the packet loss rate is greater than the preset packet loss rate threshold, switch to the standby communication link path.

[0220] In the embodiment of the present invention, at least two independent communication link paths are established for the photovoltaic terminal device, and the communication delay and packet loss rate associated with the photovoltaic terminal device are detected in real time. When the communication delay associated with the main communication link path of the photovoltaic terminal device is greater than the preset delay threshold or the packet loss rate is greater than the preset packet loss rate threshold, switch to the standby communication link path.

[0221] In a specific implementation, the preset delay threshold is preferably 200 ms, and the preset packet loss rate threshold is 5%. When the path delay of the primary communication link exceeds 200 ms or the packet loss rate is greater than 5%, it automatically switches to the backup communication link path.

[0222] It is worth mentioning that the communication quality determines the control mode. When the delay and packet loss rate are less than the thresholds (e.g., delay ≤ 200 ms, packet loss rate < 5%), the control frequency of the maximum power point tracking control is to adjust the operating point once every 1 second to track the maximum power. When the delay and packet loss rate are greater than the thresholds (e.g., delay > 200 ms or packet loss rate > 5%), the control frequency is reduced (e.g., adjusted once every 5 seconds) to avoid oscillations caused by data delay.

[0223] It should be noted that communication link redundancy detection is added to ensure the high availability of the communication link path during the debugging process.

[0224] Specifically, for each photovoltaic terminal device, the system enhances communication stability by configuring two independent communication links. This means that even if the primary communication link path fails or experiences delays, the backup communication link path can take over in a timely manner to avoid the impact of communication interruption on the system debugging process. The system will continuously monitor the performance of the communication link, especially focusing on the delay and packet loss rate. When the delay of the primary communication link path exceeds 200 ms or the packet loss rate is greater than 5%, the system will automatically switch to the backup communication link path to ensure that data transmission during the debugging process is not affected.

[0225] Among them, setting the delay of 200 ms and the packet loss rate of 5% as thresholds is a design based on the requirements of communication stability and the real-time nature of the photovoltaic system. If the delay or packet loss rate exceeds the threshold, the primary communication link path may not be able to meet the requirements of rapid response, affecting the efficiency of device debugging. Therefore, timely switching to the backup path can ensure communication continuity and data integrity during the debugging process.

[0226] The redundant communication link ensures uninterrupted communication during the debugging process and provides stable data transmission support for the closed-loop debugging system. The real-time switching of the redundant link can avoid data loss caused by network delay or packet loss, thereby ensuring that the closed-loop debugging system can obtain accurate data in real time for evaluation and adjustment.

[0227] By ensuring communication stability through the redundant communication link and combining it with the dynamic adjustment mechanism of the closed-loop debugging system, the debugging efficiency of the photovoltaic terminal device and the stability of the system can be effectively improved. When any communication interruption occurs or the effect of the debugging strategy is not ideal, the system can quickly perform adaptive adjustment to ensure that the debugging process is efficient and continuously optimized.

[0228] Step 208: Based on the operating data of the target device, perform fault diagnosis on the photovoltaic terminal device.

[0229] It should be noted that in step 208, the target device operation data of the photovoltaic terminal device is monitored in real time and matched with the preset fault diagnosis rules; automatic diagnosis is performed on over-limit current / voltage, abnormal temperature, and communication faults; repair operations such as standby device switching, module configuration adjustment, and data transmission path switching are executed, and a repair report including the repair time and effect is generated. This step greatly reduces the downtime caused by equipment failures through automatic fault diagnosis and repair, ensures that the new energy distribution network system can quickly resume operation, and improves the reliability and emergency response ability of the new energy distribution network system.

[0230] Furthermore, the photovoltaic terminal device further includes a collection terminal, the target device operation data further includes the operation parameters of the collection terminal, and step 208 may include the following sub-steps:

[0231] S41. When the power parameters of the photovoltaic module meet the associated preset current-voltage over-limit rule or preset temperature abnormality rule, it is determined that the photovoltaic module has a fault.

[0232] The power parameters of the photovoltaic module meeting the associated preset current-voltage over-limit rule means that by monitoring the photovoltaic module current and photovoltaic module voltage of the photovoltaic module, when the photovoltaic module current or photovoltaic module voltage exceeds the pre-set normal operation range, it is determined that the photovoltaic module has a fault.

[0233] Current over-limit: When the photovoltaic module current of the photovoltaic module exceeds a certain proportion (such as 120%) of its rated current, or the current fluctuates abnormally (such as suddenly dropping or rising) under specific light conditions, it may indicate problems such as internal short circuit, poor line contact, or component aging.

[0234] Voltage over-limit: When the photovoltaic module voltage is lower than its minimum operating voltage threshold (such as lower than 80% of the rated voltage), or higher than the maximum tolerance voltage (such as exceeding 110% of the design value), it may indicate faults such as component open circuit, bypass diode failure, or cell damage.

[0235] It is worth mentioning that the power parameters of the photovoltaic module also include the surface temperature of the photovoltaic module during operation;

[0236] The power parameters of the photovoltaic module meeting the associated preset temperature abnormality rule means that by monitoring the surface temperature parameter of the photovoltaic module of the photovoltaic module, when the temperature exceeds the normal operation range or shows abnormal changes, it is determined that the photovoltaic module has a fault.

[0237] In the embodiment of the present invention, when the power parameters of the photovoltaic module (such as photovoltaic module current, photovoltaic module voltage) of the photovoltaic module meet the pre-set current-voltage over-limit standard, or the surface temperature of the photovoltaic module during operation of the photovoltaic module meets the pre-set abnormal temperature standard, it is determined that the photovoltaic module has a fault.

[0238] S42. When the inverter power parameters meet the associated preset current-voltage overlimit rule or preset temperature anomaly rule, it is determined that the inverter has a fault.

[0239] The inverter power parameters meeting the associated preset current-voltage overlimit rule means that by monitoring the inverter current and inverter voltage of the inverter, when the inverter current or inverter voltage exceeds the pre-set normal operating range, it is determined that the inverter has a fault.

[0240] Current overlimit: When the inverter current (from the photovoltaic array) fluctuates abnormally or is lower than the minimum threshold, it may indicate a fault in the photovoltaic array, a line break, or the failure of the MPPT (maximum power point tracking), or when the inverter current (flowing to the grid or load) exceeds a certain proportion (such as 110%) of the inverter rated current, it may cause overload, resulting in damage to internal components or tripping of the protection device.

[0241] Voltage overlimit: When the inverter voltage exceeds the allowable operating range of the inverter (such as being too low to start or too high to damage the internal circuit), or the inverter voltage deviates from the grid standard (such as exceeding ±10% of the rated voltage), it may cause grid compatibility problems or trigger the protection mechanism.

[0242] It is worth mentioning that the inverter power parameters also include the temperature of the internal components of the inverter during operation;

[0243] The inverter power parameters meeting the associated preset temperature anomaly rule means that by monitoring the temperature of the internal components of the inverter (such as power semiconductors, reactors, capacitors, etc.), when the temperature associated with any internal component exceeds the normal range or shows abnormal changes, it is determined that the inverter has a fault.

[0244] In the embodiment of the present invention, when the inverter power parameters (such as inverter current, inverter voltage) of the inverter meet the pre-set current-voltage anomaly standard, or the temperature of the internal components of the inverter during operation meets the pre-set abnormal temperature standard, it can be determined that the inverter has a fault.

[0245] S43. When the operating parameters of the acquisition terminal meet the preset communication fault rule, it is determined that the acquisition terminal has a fault.

[0246] The preset communication fault rules refer to a set of judgment criteria pre-set by the acquisition terminal, which are used to identify whether a communication fault occurs by real-time monitoring of various parameters and states during its communication process. The preset communication fault rules include abnormal communication connections (such as communication link interruptions, frequent disconnections, or inability to establish an effective connection), abnormal data transmissions (such as excessive data loss rate, verification failure, or overly long transmission delay), communication protocol violations (such as data formats not conforming to protocol standards, failure to respond to legitimate instructions, or reporting illegal data), and abnormal hardware states (such as too low network signal strength, abnormal communication module temperature, or physical interface failure).

[0247] In an embodiment of the present invention, when the acquisition terminal operation parameters (such as connection status, data transmission quality, hardware status, etc.) generated during the operation of the acquisition terminal conform to the pre-set communication fault judgment criteria, it is directly determined that the acquisition terminal has a communication fault.

[0248] Step 209: Determine the faulty device according to the fault diagnosis result.

[0249] In an embodiment of the present invention, the faulty device is determined according to the fault diagnosis result.

[0250] Step 2010: Use the faulty device to match the pre-established priority list of standby devices, output the target standby device, and perform device switching.

[0251] It should be noted that when a fault occurs in a photovoltaic terminal device, it involves how to efficiently and intelligently switch the standby device to ensure that the new energy distribution network system can quickly resume power supply and maintain system stability when a fault occurs.

[0252] The pre-established priority list of standby devices refers to a list of standby devices planned in advance for the main photovoltaic terminal devices that may fail according to preset rules and business requirements during the system operation and maintenance stage, and formed by sorting the standby photovoltaic terminal devices according to certain criteria (such as availability, performance, switching cost, etc.).

[0253] In an embodiment of the present invention, when it is detected that a certain photovoltaic terminal device fails, the relevant information (such as functions, models, interfaces, etc.) of the photovoltaic terminal device is used as input to match the pre-established priority list of standby devices. It will be screened in turn according to the priority order of the standby devices in the list to find the optimal standby device (i.e., the target standby device) that can replace the function of the faulty device, and automatically perform the device switching operation to make the standby device take over the work of the faulty device, thereby ensuring the continuous operation of the new energy distribution network system.

[0254] In specific implementation, first, a standby device priority list needs to be established, and the devices in the list are sorted according to model, performance, and function matching degree. Give priority to selecting a standby device with exactly the same model as the faulty device for replacement, which can ensure the compatibility between devices and the stable operation of the system to the greatest extent.

[0255] In the specific operation, the system will monitor the status of each device. When a fault is detected in the photovoltaic terminal device, it will automatically select a standby device with the same model as the faulty device from the priority list for switching.

[0256] First of all, by preferentially selecting standby devices of the same model, it can ensure that the functions, performance, and parameters of the devices are completely matched, thus minimizing the impact of faults on the system operation to the greatest extent. Only when there is no standby device of the same model, the system will enter the automatic matching alternative device mode and select a device with similar performance for replacement.

[0257] If there is no available standby device of the same model in the system, the system will automatically enter the alternative device matching mode. In this mode, the system will select an alternative device with an output power error within the range of ±5%. The setting of this error range is based on the safe operation standard of the distribution network system to ensure that the output power of the alternative device is close to that of the original device, thus having little impact on the overall performance of the system. The setting of the error range is obtained through the analysis of the actual operation of the distribution network system to ensure that the alternative device can operate stably within the allowed error range, thereby avoiding excessive power fluctuations from affecting the stability of the system.

[0258] To ensure that the alternative device can operate smoothly in the system, the setting of the power error range takes into account the safe operation requirements of the new energy distribution network system. The power error range of ±5% is comprehensively set according to actual operation data, device stability, and safety standards, which can ensure that the alternative device can meet the basic power requirements of the system without causing unnecessary power fluctuations or risks.

[0259] By establishing a standby device priority list and setting a reasonable power error range, the new energy distribution network system can quickly and intelligently switch standby devices when a fault occurs in the photovoltaic terminal device, ensuring the stable operation of the new energy distribution network system and improving the efficiency and reliability of device management.

[0260] Step 2011: Real-time record the target device operation data of the photovoltaic terminal device from the first preset time point before the fault occurs to the second preset time point after the fault is repaired, and generate a debugging log.

[0261] It should be noted that for the feedback and optimization of dynamic debugging, the device status, parameter adjustment, and fault handling data during the debugging process are recorded to generate a debugging log. The debugging strategy and device parameter configuration are optimized through historical data analysis to form a closed-loop debugging system.

[0262] In the embodiment of the present invention, the debugging log recording part involves the detailed recording of the device status, parameter adjustment, and fault handling process. This recording method can not only track the running status of the device in real time but also provide valuable data for subsequent analysis and optimization after a fault occurs, ensuring the efficient management of the system and the rapid resolution of problems.

[0263] After the debugging is completed, the system records data such as the device status, parameter adjustment, and fault handling to generate a debugging log. Through the analysis of historical data, the system can optimize the debugging strategy and device parameter configuration, thereby forming a closed-loop debugging system. In subsequent debugging, the system will automatically adjust according to the optimized strategy to ensure the continuous improvement of the debugging process. This step continuously improves the debugging efficiency and system performance through a data-driven optimization feedback mechanism, enabling the system to maintain the best state during long-term operation and reducing human errors or unreasonable configurations.

[0264] Specifically, in order to accurately record the device status and monitor the operation of the photovoltaic system in real time, the sampling frequency of the device status data is set to be collected once every 5 seconds. This means that the system will automatically obtain the key operating parameters of the device (such as current, voltage, power, temperature, etc.) every 5 seconds and save them to the log. The high sampling frequency ensures the timeliness and integrity of the device operation data, enabling the system to quickly capture the state changes of the device in case of any abnormality. The 5-second sampling period can not only meet the requirements of real-time monitoring but also not cause too much pressure on the system performance, ensuring the accuracy of the data and the normal operation of the device. The 5-second sampling frequency ensures that the system can quickly capture abnormal signals when a fault occurs. This is crucial for the early warning of faults and can ensure that problems are discovered and corresponding measures are taken in a timely manner.

[0265] The timestamp in the parameter adjustment record is accurate to the millisecond level. This means that each adjustment of the device parameters (such as output power, voltage setting, etc.) will be accurately marked with the adjustment time in the log, accurate to the millisecond level. This measure can ensure the accurate traceability of each debugging action. The millisecond-level timestamp enables users to understand the exact moment of each adjustment in detail. Especially when conducting debugging, parameter optimization, or fault repair, it can accurately trace the impact of parameter changes on the device status, helping to analyze whether a certain adjustment has caused subsequent problems or faults. Recording the accurate millisecond-level timestamp makes each debugging or adjustment action highly traceable. This helps maintenance personnel to judge which operations may have affected the stability of the device by adjusting historical data when problems occur subsequently.

[0266] After a fault occurs, the system records the complete device operation data from 30 seconds before the fault occurs (i.e., the first preset time point) to 60 seconds after the repair (i.e., the second preset time point). The records during this period include the state changes of the device before the fault, the parameter fluctuations at the moment of the fault, and the state recovery process after the fault is repaired. By recording the complete data before and after the fault occurs, it can help the operation and maintenance personnel analyze the cause of the fault. The data of 30 seconds before the fault helps to detect whether there is an early abnormal warning, and the data of 60 seconds after the repair can help monitor whether the system has successfully returned to the normal state after the fault is repaired. The data of 30 seconds before the fault and 60 seconds after the fault repair provide a complete time window, enabling analysts to more comprehensively understand the device behavior before and after the fault occurs, and thus better diagnose and prevent the recurrence of similar faults. This data is of great significance for problem location and the formulation of optimization plans.

[0267] Through precise data acquisition, detailed timestamp records, and complete records of the fault handling process, this method can greatly improve the fault diagnosis ability, debugging efficiency, and long-term operation sustainability of the photovoltaic distribution network system, ensuring the stability and reliability of the equipment.

[0268] It should be noted that during the debugging process, initial debugging weight coefficients are respectively set for the three strategies (photovoltaic output maximization grid connection strategy, inverter power step-down adjustment strategy, and load adjustment strategy) involved in step 202 according to the three evaluation dimensions (equipment utilization and improvement rate, fault repair response time, power generation efficiency improvement degree) concerned by the new energy distribution network system.

[0269] 1. Equipment utilization and improvement rate: Measures the proportion of the equipment operating effectively during the debugging process, reflecting the improvement of equipment usage efficiency.

[0270] Specifically:

[0271]

[0272] In the formula, represents the equipment utilization and improvement rate, represents the actual equipment utilization rate, specifically the actual operation utilization rate of the photovoltaic power generation equipment after dynamic debugging, represents the reference utilization rate, specifically the reference value before dynamic debugging.

[0273] 2. Fault repair response time: Evaluates the response speed of fault repair. The shorter the response time, the more efficient the debugging and repair process.

[0274] Specifically:

[0275]

[0276] In the formula, represents the fault repair response time, represents the actual repair time, specifically the average time from the occurrence of the fault to the completion of the repair.

[0277] 3. Degree of improvement in power generation efficiency: Reflects the degree of improvement in the power generation efficiency of the equipment after commissioning, and directly affects the output benefit of the photovoltaic system.

[0278] Specifically:

[0279]

[0280] In the formula, represents the degree of improvement in power generation efficiency, represents the actual power generation efficiency, which is the ratio of the output energy of the new energy distribution network system after dynamic commissioning to the input solar radiation intensity, represents the reference efficiency, specifically the reference value before dynamic commissioning.

[0281] Step 2012, calculate the total deviation between the actual value of the evaluation dimension associated with the new energy distribution network system after dynamic commissioning and the preset evaluation dimension target value.

[0282] The preset evaluation dimension target values include the target value of the equipment utilization rate improvement rate, the target value of the fault repair response time, and the target value of the power generation efficiency improvement degree.

[0283] The total deviation is specifically:

[0284]

[0285] In the formula, represents the total deviation, represents the target value of the equipment utilization rate improvement rate, represents the target value of the fault repair response time, represents the target value of the power generation efficiency improvement degree.

[0286] Step 2013, obtain the initial debugging weight coefficient associated with the preset debugging strategy.

[0287] In the embodiment of the present invention, obtain the initial debugging weight coefficient associated with the preset debugging strategy.

[0288] Step 2014, input the initial debugging weight coefficient, the total deviation, and the preset evaluation dimension target value into the preset evaluation matrix to determine the target debugging weight coefficient.

[0289] The preset evaluation matrix is specifically:

[0290]

[0291]

[0292] In the formula, represents the target debugging weight coefficient, represents the initial debugging weight coefficient, represents the preset target effect value.

[0293] In the embodiment of the present invention, the preset target effect value, the debugging deviation amount, and the preset initial debugging weight coefficient are input into the preset evaluation matrix to respectively determine the target debugging weight coefficients associated with the maximum photovoltaic output grid connection strategy, the inverter power hierarchical decreasing adjustment strategy, and the load adjustment strategy.

[0294] Step 2015: Sort the preset debugging strategies based on the target debugging weight coefficients.

[0295] Step 2016: Based on the sorted preset debugging strategies, jump to the step of matching the corresponding preset debugging strategy according to the system operation data and dynamically debugging the authenticated photovoltaic terminal devices.

[0296] It should be noted that through the above preset evaluation matrix, the system can continuously optimize the debugging strategy according to the real-time evaluation result, adjust the allocation of resources and the execution of the strategy, and ensure that the debugging process always remains in the optimal state.

[0297] The preset evaluation matrix quantifies indicators such as equipment utilization rate, fault repair response time, and power generation efficiency, making the adjustment of the debugging strategy more data-driven and avoiding the inaccuracy and subjective deviation of manual adjustment. By dynamically adjusting the weight coefficient, the system can adaptively adjust the debugging strategy to achieve a more accurate debugging effect.

[0298] By adjusting the strategy weight according to the real-time feedback, the system can continuously optimize the operation process according to the current debugging progress and improve the debugging efficiency. For example, when the fault repair response time is long, the system can automatically increase the weight in terms of fault repair to accelerate the repair process; when the improvement degree of power generation efficiency is low, the system can increase the attention to the optimization of equipment performance.

[0299] For the sake of easy understanding, a specific application example is provided according to Steps 2012 - 2016:

[0300] Initial debugging weight coefficient: Maximum photovoltaic output grid connection strategy 0.3, Inverter power hierarchical decreasing adjustment strategy 0.35, Load adjustment strategy 0.35;

[0301] Target value of equipment utilization rate improvement rate 0.2, Target value of fault repair response time 3, and Target value of power generation efficiency improvement degree 0.15;

[0302] The equipment utilization and improvement rate is 0.15 (i.e., the actual equipment utilization rate has increased by 15%), the fault repair response time is 4 (unit: hours, i.e., the actual fault repair response time is 4 hours), and the power generation efficiency improvement degree is 0.12 (i.e., the actual power generation efficiency has increased by 12%)

[0303] The preset target effect value = (0.2 + 3 + 0.15) / 3 ≈ 1.1167

[0304] The total deviation amount = [(0.15 - 0.2) + (4 - 3) + (0.12 - 0.15)] / 3 ≈ 0.3067

[0305] The target debugging weight coefficient of the maximum power grid connection strategy for photovoltaic output = 0.3 × [1 + (0.3067 / 1.1167)] ≈ 0.3 × 1.2747 = 0.3824

[0306] The target debugging weight coefficient of the power transformer power grading decreasing regulation strategy = 0.35 × [1 + (0.3067 / 1.1167)] ≈ 0.35 × 1.2747 = 0.4461

[0307] The target debugging weight coefficient of the load regulation strategy = 0.35 × [1 + (0.3067 / 1.1167)] ≈ 0.35 × 1.2747 = 0.4461

[0308] Sort the calculated target debugging weight coefficients from large to small, and the priority is: the power transformer power grading decreasing regulation strategy = the load regulation strategy > the maximum power grid connection strategy for photovoltaic output

[0309] Therefore, during the next dynamic debugging process, the power transformer power grading decreasing regulation strategy and the load regulation strategy are preferentially executed, and then the maximum power grid connection strategy for photovoltaic output is debugged

[0310] Step 2017: Conduct a fault simulation test on the new energy distribution network system, and generate a self-healing ability evaluation report according to the simulation test results

[0311] In the embodiment of the present invention, the emergency response ability and self-healing ability of the system for sudden faults are further enhanced, ensuring that the system can identify and repair faults in a timely manner during actual operation. This test can not only help verify the performance of the system under different abnormal working conditions, but also provide data support for subsequent system optimization

[0312] During the idle period of the system, the preset fault mode injection is automatically executed, and the specific steps are as follows

[0313] Automatically inject the preset fault mode

[0314] Voltage dip of 10%: Simulate a voltage dip in the power grid to test the performance of photovoltaic terminal equipment during voltage fluctuations and the system's response ability when the voltage is below the normal operating range. Voltage dips may affect the operating efficiency of photovoltaic inverters. During the test, it is necessary to pay attention to whether the equipment can automatically identify abnormalities and make corresponding adjustments.

[0315] Communication interruption simulation: Simulate the situation of communication link interruption to test how the system locates and repairs faults when communication is lost. This fault mode verifies whether the redundant communication paths of the system can effectively take over and ensures that debugging and control data are not lost during communication interruption.

[0316] Inverter overload test: Simulate an overloaded inverter to test whether the protection mechanism can be effectively enabled under overload conditions, such as whether it can prevent damage through load reduction, power-off, or other protection measures.

[0317] Fault mode parameter setting: The parameters of the fault mode need to be set according to the safety thresholds of the distribution network system. For example, the amplitude of the voltage dip, the duration of the communication interruption, the maximum load-bearing value of the inverter overload, etc., should all be set within a range close to the actual operating environment but not likely to cause serious damage. These parameters are set according to the design and safety requirements of the distribution network system to ensure that the test is realistic and does not affect the long-term stable operation of the equipment.

[0318] After each injection of the fault mode, the system will automatically record the following data: Repair response time: That is, the time from the occurrence of the fault to the start of system repair. Recording this time can help evaluate the system's response speed during a fault and measure the system's fault emergency handling ability. Repair effect: The effect after system repair includes whether the fault is completely resolved, the stability after repair, and the recovery of performance, etc. The evaluation of the repair effect can be quantitatively analyzed by comparing the equipment parameters (such as power, efficiency, etc.) before and after repair to judge the effectiveness of the repair strategy.

[0319] These data will be summarized and generate a detailed self-healing ability evaluation report. The report content includes: The repair response time and repair effect evaluation under each fault mode. The overall score of the system's self-healing ability to help technicians understand the system's recovery ability in different fault scenarios.

[0320] The automatic injection of the fault mode enables the system to simulate various possible operating conditions, ensuring that the equipment and system can exhibit good self-healing ability under different types of faults. This simulation can help the system detect potential fault points in advance and evaluate whether the current debugging strategy is effective enough.

[0321] By recording the repair response time and repair effect, not only can the real-time response ability of the system be evaluated, but also reliable data support can be provided for subsequent system optimization. If the response time is too long or the repair effect is not ideal, technicians can analyze the reasons based on the data in the report and adjust the fault tolerance ability, fault diagnosis and repair strategies of the system.

[0322] The self-healing ability evaluation report is a comprehensive evaluation of the system's performance under abnormal working conditions, helping managers understand the system's health status and improvement space. The report provides a clear index system, enabling the photovoltaic system to gradually improve its fault recovery ability, thereby reducing its dependence on external intervention and enhancing the overall stability and security of the system.

[0323] The introduction of fault simulation testing enables the system to not only operate stably under normal working conditions but also evaluate the system's self-healing ability by simulating real fault scenarios, improving the emergency response ability. Automatically record the repair response time and effect, and generate a self-healing ability evaluation report, providing data support for the continuous optimization of the system to ensure that the photovoltaic distribution network system can maintain efficient and stable operation in any environment.

[0324] The present invention introduces a multi-dimensional fault diagnosis mechanism, which combines multiple parameters such as temperature, communication status, current, and voltage for linkage analysis. Through automatic injection testing of fault modes, the system's response ability and self-healing ability can be verified in advance. The present invention reduces the false alarm rate and the response time for fault handling through multi-dimensional analysis and intelligent self-healing mechanisms, significantly improving the fault recovery ability of the new energy distribution network system. The automatic repair and standby equipment switching mechanism greatly reduces manual intervention, shortens the downtime, and improves the reliability of the system.

[0325] In the present invention, first, through the automated device network access authentication, it is ensured that the photovoltaic terminal device meets the technical standards and safety requirements of the new energy distribution network system, avoiding the inefficiency of manual authentication. Then, according to the obtained system operation data, the corresponding preset debugging strategy under the current working condition is automatically matched, solving the limitation that traditional static rules cannot adapt to high dynamic changes. Finally, when the preset working condition is triggered, the corresponding preset debugging strategy is automatically executed to dynamically adjust and optimize the authenticated photovoltaic terminal device, ensuring that the new energy distribution network system can operate efficiently and stably under different working conditions, significantly improving the power generation efficiency and grid stability of the new energy distribution network system; at the same time, through unified debugging strategies and real-time data driving, the collaborative optimization of multiple photovoltaic terminal devices is achieved, solving the technical problem that it is difficult to coordinate the operation of multiple devices in the traditional method to meet the requirements of the network system.

[0326] Please refer to Figure 3 , Figure 3 which is the structural block diagram of a new energy distribution network photovoltaic automation terminal intelligent debugging device provided in Embodiment 3 of the present invention.

[0327] An intelligent commissioning device for a new energy distribution network photovoltaic automation terminal provided by the present invention includes:

[0328] An equipment access detection module, which is used to perform equipment network access authentication on photovoltaic terminal equipment to be connected to the new energy distribution network system, and obtain the system operation data of the new energy distribution network system. The photovoltaic terminal equipment includes a photovoltaic module and an inverter;

[0329] A commissioning strategy generation module, which is used to match corresponding preset commissioning strategies according to the system operation data, and perform dynamic commissioning on the authenticated photovoltaic terminal equipment.

[0330] Further, the system operation data includes solar radiation intensity, load data, load volatility, photovoltaic power generation efficiency, and historical power generation efficiency average value. The preset commissioning strategies include a photovoltaic output maximization grid connection strategy, an inverter power hierarchical decreasing adjustment strategy, and a load adjustment strategy. The photovoltaic terminal equipment further includes an energy storage system. The commissioning strategy generation module includes:

[0331] A load prediction algorithm unit, which is used to generate a commissioning plan including a photovoltaic output maximization grid connection strategy, an inverter power hierarchical decreasing adjustment strategy, and a load adjustment strategy;

[0332] A meteorological data analysis unit, which is used to compare the solar radiation intensity with a preset intensity threshold;

[0333] A strategy decision engine, which is used to execute the photovoltaic output maximization grid connection strategy for the photovoltaic module when the solar radiation intensity is greater than the preset intensity threshold and the load data is less than the preset load threshold;

[0334] When the load volatility is greater than the preset volatility threshold and the photovoltaic power generation efficiency is lower than the historical power generation efficiency average value, execute the inverter power hierarchical decreasing adjustment strategy for the inverter;

[0335] When the load data is within the preset system rated capacity range, execute the load adjustment strategy.

[0336] Further, the equipment access detection module includes:

[0337] An identity legitimacy verification unit, which is used to perform equipment network access authentication on photovoltaic terminal equipment to be connected to the new energy distribution network system.

[0338] Further, the equipment access detection module further includes:

[0339] A communication protocol adaptation unit, which is used to match the communication protocol for the photovoltaic terminal equipment to access the new energy distribution network system;

[0340] A data validity verification unit is used to obtain in real time the device operation data corresponding to the photovoltaic terminal device that has passed authentication and is connected to the new energy distribution network system;

[0341] Among them, the photovoltaic terminal device is connected to the new energy distribution network system through a communication protocol;

[0342] Perform validity verification on the device operation data;

[0343] When the validity verification result is that the data is valid, the device operation data is used as the target device operation data;

[0344] When the validity verification result is that the data is invalid, data repair is performed on the device operation data to obtain the target device operation data;

[0345] The device access detection module is communicatively connected to the self-check and parameter calibration module;

[0346] The self-check and parameter calibration module is used to perform functional regulation on the photovoltaic terminal device based on the target device operation data.

[0347] Furthermore, the target device operation data includes photovoltaic module power parameters and inverter power parameters, and the self-check and parameter calibration module includes;

[0348] The self-check and parameter calibration module is used to perform integrity detection on the photovoltaic module power parameters;

[0349] When the integrity detection result is that the data is not complete, it jumps to execute the step of performing validity verification on the device operation data;

[0350] When the integrity detection result is that the data is complete, temperature compensation calibration and maximum power point tracking are respectively performed on the photovoltaic module based on the photovoltaic module power parameters;

[0351] Based on the inverter power parameters, overvoltage and overcurrent detection are performed on the inverter;

[0352] When the overvoltage and overcurrent detection result is that there is an overvoltage or overcurrent phenomenon, inverter output power matching is performed on the inverter based on the inverter power parameters.

[0353] Furthermore, the photovoltaic module power parameters include photovoltaic module voltage and photovoltaic module current, and the self-check and parameter calibration module includes:

[0354] The photovoltaic module temperature compensation unit is used to perform temperature compensation calibration based on the photovoltaic module voltage using a preset calibration formula to obtain the photovoltaic calibrated voltage;

[0355] Adjust the current voltage of the photovoltaic module to the photovoltaic calibrated voltage through a preset voltage regulator;

[0356] The MPPT control unit is used to perform a multiplication operation on the photovoltaic calibration voltage and the photovoltaic module current to obtain the photovoltaic calibration power;

[0357] Based on the photovoltaic calibration power, a preset MPPT controller is used to perform maximum power point tracking on the photovoltaic module.

[0358] Further, the inverter power parameters include the inverter current and the inverter voltage, and the self-check and parameter calibration module further includes:

[0359] The inverter segmented calibration module is used to perform a multiplication operation on the inverter current and the inverter voltage to obtain the inverter power;

[0360] When the inverter power is within the preset first power calibration interval, a multiplication operation is performed on the first power calibration coefficient associated with the preset first power calibration interval and the inverter current to obtain the first inverter calibration current;

[0361] Adjust the current of the inverter to the first inverter calibration current;

[0362] When the inverter power is within the preset second power calibration interval, a multiplication operation is performed on the second power calibration coefficient associated with the preset second power calibration interval and the inverter current to obtain the second inverter calibration current;

[0363] Adjust the current of the inverter to the second inverter calibration current;

[0364] When the inverter power is within the preset third power calibration interval, a multiplication operation is performed on the third power calibration coefficient associated with the preset third power calibration interval and the inverter current to obtain the third inverter calibration current;

[0365] Adjust the current of the inverter to the third inverter calibration current.

[0366] Further, a fault detection and repair module is also included;

[0367] The fault detection and repair module includes:

[0368] The fault diagnosis rule base is used to perform fault diagnosis on the photovoltaic terminal equipment based on the target device operation data;

[0369] Determine the faulty device according to the fault diagnosis result;

[0370] The standby device switching unit is used to match the faulty device with a pre-established standby device priority list, output the target standby device and perform device switching.

[0371] Further, the photovoltaic terminal equipment further includes a collection terminal, the target device operation data further includes the collection terminal operation parameters, and the fault diagnosis rule base includes:

[0372] A photovoltaic module fault sub-module, which is used to determine that the photovoltaic module has a fault when the power parameters of the photovoltaic module meet the associated preset current-voltage overlimit rule or preset temperature anomaly rule;

[0373] An inverter fault sub-module, which is used to determine that the inverter has a fault when the power parameters of the inverter meet the associated preset current-voltage overlimit rule or preset temperature anomaly rule;

[0374] An acquisition terminal fault sub-module, which is used to determine that the acquisition terminal has a fault when the operating parameters of the acquisition terminal meet the preset communication fault rule.

[0375] Further, the fault detection and repair module further includes;

[0376] A communication link redundancy controller, which is used to establish at least two independent communication link paths for the photovoltaic terminal device and real-time detect the communication delay and packet loss rate associated with the photovoltaic terminal device;

[0377] When the communication delay associated with the main communication link path of the photovoltaic terminal device is greater than the preset delay threshold or the packet loss rate is greater than the preset packet loss rate threshold, switch to the standby communication link path.

[0378] Further, it further includes a debugging and optimization module;

[0379] The debugging and optimization module includes:

[0380] A debugging log database, which is used to record in real time the target device operation data of the photovoltaic terminal device from the first preset time point before the fault occurs to the second preset time point after the fault is repaired, and generate a debugging log.

[0381] Further, the debugging and optimization module further includes:

[0382] A policy evaluation matrix calculation unit, which is used to calculate the total deviation between the actual value of the evaluation dimension associated with the new energy distribution network system after dynamic debugging and the preset evaluation dimension target value;

[0383] Obtain the initial debugging weight coefficient associated with the preset debugging policy;

[0384] Input the initial debugging weight coefficient, the total deviation and the preset evaluation dimension target value into the preset evaluation matrix to determine the target debugging weight coefficient;

[0385] Based on the target debugging weight coefficient, sort the preset debugging policies;

[0386] A closed-loop optimization feedback interface, which is used to jump to the step of matching the corresponding preset debugging policy according to the system operation data and performing dynamic debugging on the authenticated photovoltaic terminal device based on the sorted preset debugging policies.

[0387] Furthermore, it further includes:

[0388] A fault simulation test module, which is used to conduct fault simulation tests on the new energy distribution network system and generate a self-healing ability evaluation report according to the simulation test results.

[0389] The intelligent debugging device for the new energy distribution network photovoltaic automation terminal realizes data interaction and control instruction transmission between modules through a hardware processor and a memory.

[0390] In the present invention, first, through the network access authentication of automated equipment, it is ensured that the photovoltaic terminal equipment meets the technical standards and safety requirements of the new energy distribution network system, avoiding the inefficiency of manual authentication. Then, according to the obtained system operation data, the corresponding preset debugging strategy under the current working condition is automatically matched, solving the limitation that traditional static rules cannot adapt to high dynamic changes. Finally, when the preset working condition is triggered, the corresponding preset debugging strategy is automatically executed to dynamically adjust and optimize the authenticated photovoltaic terminal equipment, ensuring that the new energy distribution network system can operate efficiently and stably under different working conditions, significantly improving the power generation efficiency and grid stability of the new energy distribution network system. At the same time, through unified debugging strategies and real-time data driving, the collaborative optimization of multiple photovoltaic terminal devices is realized, solving the technical problem that it is difficult to coordinate the operation of multiple devices in the traditional method to meet the requirements of the network system.

[0391] Please refer to Figure 4 , Figure 4 which is a structural block diagram of a computer device provided in Embodiment 4 of the present invention.

[0392] An electronic device according to an embodiment of the present invention, the electronic device includes: a memory 401 and a processor 402, and a computer program is stored in the memory 401; when the computer program is executed by the processor 402, the processor 402 is caused to execute the intelligent debugging method for the new energy distribution network photovoltaic automation terminal as described in any one of the above embodiments.

[0393] The memory 401 may be an electronic memory such as a flash memory, EEPROM (Electrically Erasable Programmable Read-Only Memory), EPROM, hard disk, or ROM. The memory 401 has a storage space 403 for program code 413 for executing any of the method steps in the above-described method. For example, the storage space 403 for the program code may include respective program codes 413 for implementing the various steps in the above method. These program codes may be read from or written to one or more computer program products. These computer program products include program code carriers such as hard disks, compact discs (CDs), memory cards, or floppy disks. The program code may be compressed in a suitable form, for example. When these codes are run by a computing processing device, the computing processing device is caused to execute each of the steps in the method described above. These program codes may be read from or written to one or more computer program products. These computer program products include program code carriers such as hard disks, compact discs (CDs), memory cards, or floppy disks. The program code may be compressed in a suitable form, for example. When these codes are run by a computing processing device, the computing processing device is caused to execute each of the steps in the above-described intelligent debugging method for a new energy distribution network photovoltaic automation terminal.

[0394] Embodiment 5 of the present invention further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the intelligent debugging method for a new energy distribution network photovoltaic automation terminal as described in any of the foregoing embodiments.

[0395] Embodiment 6 of the present invention further provides a computer program product. The computer program product includes a computer program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions. When the program instructions are executed by a computer, the computer is caused to execute the intelligent debugging method for a new energy distribution network photovoltaic automation terminal as described in any of the foregoing embodiments.

[0396] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments and will not be elaborated herein.

[0397] In several embodiments provided by the present application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed coupling, direct coupling, or communication connection between each other can be through some interfaces, and the indirect coupling or communication connection of devices or units can be in electrical, mechanical, or other forms.

[0398] The units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they can be located in one place or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0399] In addition, in each embodiment of the present invention, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit. The above-mentioned integrated units can be implemented in the form of hardware or in the form of software functional units.

[0400] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods in each embodiment of the present invention. The foregoing storage medium includes: USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical disks and other various media that can store program codes.

[0401] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of each embodiment of the present invention.

Claims

1. A method for intelligent debugging of a new energy distribution network photovoltaic automation terminal, characterized in that, Including: Conduct device network access authentication for the photovoltaic terminal device to be connected to the new energy distribution network system, and obtain the system operation data of the new energy distribution network system. The photovoltaic terminal device includes a photovoltaic module and an inverter; Match the corresponding preset debugging strategy according to the system operation data, and perform dynamic debugging on the authenticated photovoltaic terminal device.

2. The intelligent commissioning method for the new energy distribution network photovoltaic automation terminal according to claim 1, wherein The system operation data includes solar radiation intensity, load data, load volatility, photovoltaic power generation efficiency, and historical power generation efficiency average value. The preset debugging strategies include a photovoltaic output maximization grid connection strategy, an inverter power hierarchical decreasing adjustment strategy, and a load adjustment strategy. The photovoltaic terminal device further includes an energy storage system. The matching of the corresponding preset debugging strategy according to the system operation data and the performing of dynamic debugging on the authenticated photovoltaic terminal device include: When the solar radiation intensity is greater than a preset intensity threshold and the load data is less than a preset load threshold, then execute the photovoltaic output maximization grid connection strategy for the photovoltaic module; When the load volatility is greater than a preset volatility threshold and the photovoltaic power generation efficiency is lower than the historical power generation efficiency average value, then execute the inverter power hierarchical decreasing adjustment strategy for the inverter; When the load data is within a preset system rated capacity range, then execute the load adjustment strategy for the photovoltaic module and / or the energy storage system.

3. The intelligent commissioning method for the new energy distribution network photovoltaic automation terminal according to claim 1, wherein, Also including: Real-time obtain the device operation data corresponding to the authenticated photovoltaic terminal device connected to the new energy distribution network system; Wherein, the photovoltaic terminal device accesses the new energy distribution network system through a communication protocol; Perform validity verification on the device operation data; When the validity verification result is that the data is valid, then use the device operation data as the target device operation data; When the validity verification result is that the data is invalid, then perform data repair on the device operation data to obtain the target device operation data; Based on the target device operation data, perform function regulation on the photovoltaic terminal device.

4. The intelligent commissioning method for the new energy distribution network photovoltaic automation terminal according to claim 3, wherein, The target device operation data includes photovoltaic module power parameters and inverter power parameters. The performing of function regulation on the photovoltaic terminal device based on the target device operation data includes: Perform integrity detection on the photovoltaic module power parameters; When the integrity detection result is that the data is not complete, then jump to execute the step of performing validity verification on the device operation data; When the integrity detection result is that the data is complete, then perform temperature compensation calibration and maximum power point tracking on the photovoltaic module respectively based on the photovoltaic module power parameters; Based on the inverter power parameters, perform overvoltage and overcurrent detection on the inverter; When the overvoltage and overcurrent detection result is that there is an overvoltage or overcurrent phenomenon, then perform inverter output power matching on the inverter based on the inverter power parameters.

5. The intelligent commissioning method for the new energy distribution network photovoltaic automation terminal according to claim 4, wherein The photovoltaic module power parameters include photovoltaic module voltage and photovoltaic module current. The performing of temperature compensation calibration and maximum power point tracking on the photovoltaic module respectively based on the photovoltaic module power parameters includes: Based on the photovoltaic module voltage, perform temperature compensation calibration using a preset calibration formula to obtain a photovoltaic calibrated voltage; Adjust the current voltage of the photovoltaic module to the photovoltaic calibration voltage through a preset voltage regulator; Multiply the photovoltaic calibration voltage by the current of the photovoltaic module to obtain the photovoltaic calibration power; Based on the photovoltaic calibration power, use a preset MPPT controller to perform maximum power point tracking on the photovoltaic module.

6. The intelligent commissioning method for the new energy distribution network photovoltaic automation terminal according to claim 4, characterized in that, The inverter power parameters include inverter current and inverter voltage. The matching of the inverter output power based on the inverter power parameters includes: Multiply the inverter current by the inverter voltage to obtain the inverter power; When the inverter power is within a preset first power calibration interval, multiply the first power calibration coefficient associated with the preset first power calibration interval by the inverter current to obtain the first inverter calibration current; Adjust the current of the inverter to the first inverter calibration current; When the inverter power is within a preset second power calibration interval, multiply the second power calibration coefficient associated with the preset second power calibration interval by the inverter current to obtain the second inverter calibration current; Adjust the current of the inverter to the second inverter calibration current; When the inverter power is within a preset third power calibration interval, multiply the third power calibration coefficient associated with the preset third power calibration interval by the inverter current to obtain the third inverter calibration current; Adjust the current of the inverter to the third inverter calibration current.

7. The intelligent commissioning method for the new energy distribution network photovoltaic automation terminal according to claim 4, wherein It further includes: Perform fault diagnosis on the photovoltaic terminal device based on the target device operation data; Determine the faulty device according to the fault diagnosis result; Match the faulty device with a pre-established standby device priority list, output the target standby device, and perform device switching.

8. The intelligent commissioning method for the new energy distribution network photovoltaic automation terminal according to claim 7, wherein, The photovoltaic terminal device further includes a collection terminal, and the target device operation data further includes collection terminal operation parameters. The performing of fault diagnosis on the photovoltaic terminal device based on the target device operation data includes: When the power parameters of the photovoltaic module meet the associated preset current-voltage overlimit rule or preset temperature anomaly rule, it is determined that the photovoltaic module is faulty; When the power parameters of the inverter meet the associated preset current-voltage overlimit rule or preset temperature anomaly rule, it is determined that the inverter is faulty; When the collection terminal operation parameters meet the preset communication fault rule, it is determined that the collection terminal is faulty.

9. The intelligent commissioning method for a new energy distribution network photovoltaic automation terminal according to claim 1, wherein It further includes: Establish at least two independent communication link paths for the photovoltaic terminal device, and real-time detect the communication delay and packet loss rate associated with the photovoltaic terminal device; When the communication delay associated with the main communication link path of the photovoltaic terminal device is greater than the preset delay threshold or the packet loss rate is greater than the preset packet loss rate threshold, switch to the standby communication link path.

10. The intelligent commissioning method for a new energy distribution network photovoltaic automation terminal according to claim 8, characterized in that, It further includes: Real-time record the target device operation data of the photovoltaic terminal device from the first preset time point before the fault occurs to the second preset time point after the fault is repaired, and generate a debugging log.

11. The intelligent commissioning method for the new energy distribution network photovoltaic automation terminal according to claim 2, wherein, It further includes: Calculate the total deviation between the actual values of the evaluation dimensions associated with the new energy distribution network system after dynamic debugging and the preset target values of the evaluation dimensions; Obtain the initial debugging weight coefficients associated with the preset debugging strategy; Use the initial debugging weight coefficients, the total deviation, and the preset target values of the evaluation dimensions to input into a preset evaluation matrix to determine the target debugging weight coefficients; Based on the target debugging weight coefficients, sort the preset debugging strategies; Based on the sorted preset debugging strategies, jump to the step of matching the corresponding preset debugging strategies according to the system operation data and performing dynamic debugging on the authenticated photovoltaic terminal devices.

12. The intelligent commissioning method for a new energy distribution network photovoltaic automation terminal according to any one of claims 1-11, characterized in that, Further includes: Conduct a fault simulation test on the new energy distribution network system and generate a self-healing ability evaluation report based on the simulation test results.

13. An intelligent debugging device for a new energy distribution network photovoltaic automation terminal, based on the intelligent debugging method for a new energy distribution network photovoltaic automation terminal according to any one of claims 1-12, characterized in that, Includes: An equipment access detection module, configured to perform equipment network access authentication on the photovoltaic terminal devices to be connected to the new energy distribution network system and obtain the system operation data of the new energy distribution network system. The photovoltaic terminal devices include photovoltaic modules and inverters; A debugging strategy generation module, configured to match the corresponding preset debugging strategies according to the system operation data and perform dynamic debugging on the authenticated photovoltaic terminal devices.

14. An electronic device, characterized in that, Includes a memory and a processor. When the computer program stored in the memory is executed by the processor, the processor is caused to execute the steps of the new energy distribution network photovoltaic automation terminal intelligent debugging method according to any one of claims 1-12.

15. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed, it implements the new energy distribution network photovoltaic automation terminal intelligent debugging method according to any one of claims 1-12.

16. A computer program product, characterized in that, The computer program product includes a computer program stored on a non-transitory computer-readable storage medium. The computer program includes program instructions. When the program instructions are executed by a computer, the computer is caused to execute the new energy distribution network photovoltaic automation terminal intelligent debugging method according to any one of claims 1-12.

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