Fault positioning method and device for ground resistor of floating photovoltaic power station

Abstract

The invention provides a floating photovoltaic power station grounding resistor fault positioning method and device, the method is applied to a controller in a fault positioning system, and the fault positioning system further comprises a grounding grid of a floating photovoltaic power station, a sensing network formed by deploying sensors at key nodes of the grounding grid, and a signal generator. The method comprises the following steps: in response to a received fault positioning instruction, triggering a signal generator to inject a high-frequency test current signal into a grounding grid; acquiring a current-voltage data set through a voltage response signal of each key node acquired by a sensing network; based on the current-voltage data set, resistivity distribution reconstruction is carried out by adopting an impedance imaging algorithm, and a three-dimensional resistivity distribution diagram of the grounding grid is generated; and according to the three-dimensional resistivity distribution diagram, positioning an abnormal region with a resistance value exceeding a preset threshold value in the grounding grid. According to the method, three-dimensional visual imaging of resistivity distribution in the grounding grid and accurate positioning of an abnormal area are realized.

Description

Technical Field

[0001] This application relates to the field of fault diagnosis technology for floating photovoltaic power stations, and more specifically, to a fault location method and apparatus for the grounding resistance of a floating photovoltaic power station. Background Technology

[0002] In recent years, with the rapid development of photovoltaic power generation technology, floating photovoltaic power stations have gradually become one of the important forms of photovoltaic power generation due to their advantages such as saving land resources and reducing water evaporation. As a key component ensuring the electrical safety of the power station, the performance of the grounding system directly affects the operational safety of the power station and the protection of personnel and equipment. Currently, common grounding systems typically consist of a mesh structure formed by buried metal grounding electrodes and conductors, divided into photovoltaic array grounding and electrical equipment grounding, and require a total grounding resistance of no more than 4 ohms to meet safety regulations.

[0003] In existing technologies, grounding resistance monitoring often employs periodic on-site measurements or localized point measurements, such as using a grounding resistance tester to measure at the grounding down conductor. Some systems also deploy fixed sensors for continuous monitoring, but these are usually limited to obtaining the overall resistance value and cannot achieve precise detection of the internal resistance distribution of the grounding grid. For floating photovoltaic power stations, whose grounding systems are located in a water environment, they are more significantly affected by factors such as water fluctuations and corrosion, making it difficult for traditional methods to reflect the grounding grid status in real time and comprehensively.

[0004] Therefore, the main problem with existing grounding resistance monitoring technology is that it cannot obtain the resistance distribution inside the grounding grid in real time and intuitively, and it is difficult to accurately locate high resistance abnormal areas. Especially in complex water environments such as floating photovoltaic power stations, traditional point measurement or overall monitoring methods have slow response and low spatial resolution, making it difficult to detect and deal with local faults in the grounding grid in a timely manner, which increases the risk of power station operation. Summary of the Invention

[0005] The purpose of this application is to provide a method and apparatus for fault location of grounding resistance in floating photovoltaic power stations, so as to realize three-dimensional visualization imaging of resistivity distribution inside the grounding grid and accurate location of abnormal areas.

[0006] Firstly, a fault location method for the grounding resistance of a floating photovoltaic power station is provided, applied to a controller in a fault location system. The fault location system also includes a grounding grid of the floating photovoltaic power station, a sensor network formed by deploying sensors at key nodes of the grounding grid, and a signal generator. The method may include: In response to the received fault location command, the signal generator is triggered to inject a high-frequency test current signal into the grounding grid; The current-voltage dataset is obtained by collecting the voltage response signals of each key node through the sensor network. Based on the current-voltage dataset, an impedance imaging algorithm is used to reconstruct the resistivity distribution and generate a three-dimensional resistivity distribution map of the grounding grid. Based on the three-dimensional resistivity distribution map, locate abnormal areas in the grounding grid where the resistance value exceeds a preset threshold.

[0007] In one possible implementation, in response to a received fault location command, a signal generator is triggered to inject a high-frequency test current signal into the grounding grid, including: Control the signal generator to inject a high-frequency test current signal with a frequency within a preset frequency range into one or more injection points of the grounding grid; The injection point is a designated location on the grounding network for receiving the test current, which may partially overlap with or be entirely independent of the key node used to deploy the sensor.

[0008] In one possible implementation, injecting a high-frequency test current signal with a frequency within a preset frequency range into one or more injection points of the grounding grid includes: The signal generator is controlled to inject high-frequency test current signals within a preset frequency range into a single injection point of the grounding grid in a preset polling order. Alternatively, the signal generator can be controlled to synchronously inject multiple high-frequency test current signals into multiple injection points of the grounding grid according to a preset timing and phase.

[0009] In one possible implementation, the key nodes include at least: electrical connection points between adjacent array units in the floating photovoltaic array, a preset grounding connection point of the metal floating platform supporting the photovoltaic modules, and a connection point connecting the metal floating platform to the underwater grounding conductor.

[0010] In one possible implementation, before triggering the signal generator to inject a high-frequency test current signal into the grounding grid in response to a received fault location command, the method further includes: Obtain current environmental parameters, which include at least the resistivity, water temperature and water level of the water body where the floating photovoltaic power station is located; The frequency and / or amplitude of the high-frequency test current signal are dynamically adjusted based on the current environmental parameters.

[0011] In one possible implementation, before triggering the signal generator to inject a high-frequency test current signal into the grounding grid in response to a received fault location command, the method further includes: Electromagnetic field simulation was performed on the three-dimensional structural model of the grounding grid; Based on the simulation results, the optimal deployment location and density of sensors in the sensor network, as well as the optimal location of the injection point for the high-frequency test current signal, are determined.

[0012] In one possible implementation, based on the current-voltage dataset, an impedance imaging algorithm is used to reconstruct the resistivity distribution, generating a three-dimensional resistivity distribution map of the grounding grid, including: Based on the structural and spatial information of the grounding grid, a three-dimensional discretized model of its computational domain is constructed. This model consists of multiple units, and each unit is assigned a conductivity parameter that characterizes its electrical conductivity. By combining the current-voltage dataset with the three-dimensional discretized model, an inverse problem is constructed and solved, with the conductivity of each unit as the optimization variable and the goal of matching the predicted voltage with the measured voltage. The optimal conductivity distribution of all units is obtained through iterative optimization. Based on the optimal conductivity distribution, a three-dimensional resistivity distribution map characterizing the spatial distribution of the resistance characteristics of the grounding grid system is calculated and generated.

[0013] Secondly, a fault location device for the grounding resistance of a floating photovoltaic power station is provided, which is applied to the controller of a fault location system. The fault location system also includes a grounding grid of the floating photovoltaic power station, a sensor network formed by deploying sensors at key nodes of the grounding grid, and a signal generator. The device may include: The triggering unit is used to trigger the signal generator to inject a high-frequency test current signal into the grounding grid in response to the received fault location command; The acquisition unit is used to acquire current-voltage datasets by collecting voltage response signals from each key node through the sensor network. The generation unit is used to reconstruct the resistivity distribution based on the current-voltage dataset using an impedance imaging algorithm, and generate a three-dimensional resistivity distribution map of the grounding grid. The positioning unit is used to locate abnormal areas in the grounding grid where the resistance value exceeds a preset threshold based on the three-dimensional resistivity distribution map.

[0014] Thirdly, an electronic device is provided, which includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; When a processor executes a program stored in memory, it implements any of the steps described in the first aspect above.

[0015] Fourthly, a computer-readable storage medium is provided, wherein a computer program is stored therein, and when executed by a processor, the computer program implements the steps of any of the methods described in the first aspect above.

[0016] This application provides a method and apparatus for fault location of grounding resistance in a floating photovoltaic power station. The method is applied to a controller in a fault location system. The fault location system also includes a grounding grid of the floating photovoltaic power station, a sensor network formed by deploying sensors at key nodes of the grounding grid, and a signal generator. The method includes: responding to a received fault location command, triggering the signal generator to inject a high-frequency test current signal into the grounding grid; obtaining a current-voltage dataset by collecting voltage response signals from key nodes through the sensor network; reconstructing the resistivity distribution based on the current-voltage dataset using an impedance imaging algorithm to generate a three-dimensional resistivity distribution map of the grounding grid; and locating abnormal areas in the grounding grid where the resistance value exceeds a preset threshold based on the three-dimensional resistivity distribution map. This method achieves three-dimensional visualization imaging of the resistivity distribution within the grounding grid and precise location of abnormal areas. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of this application and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a schematic diagram of the structure of a fault location system provided in an embodiment of this application; Figure 2 A flowchart illustrating a method for fault location of grounding resistance in a floating photovoltaic power station, provided in an embodiment of this application; Figure 3 A schematic diagram of the structure of a fault location device for the grounding resistance of a floating photovoltaic power station provided in this application embodiment; Figure 4 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0019] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application. Unless otherwise defined, the technical or scientific terms used in this application should have the ordinary meaning understood by those skilled in the art. The words "first," "second," and similar terms used in this application do not indicate any order, quantity, or importance, but are only used to distinguish different components. The words "comprising" or "including," etc., mean that the element or object preceding the word covers the element or object listed after the word and its equivalents, but do not exclude other elements or objects. The words "connected," "coupled," or "connected," etc., are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. "Up," "down," "left," "right," etc., are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0020] The fault location method for grounding resistance of floating photovoltaic power stations provided in this application is applied to a fault location system, which is an intelligent system specifically designed for monitoring the status of the grounding grid and diagnosing faults in floating photovoltaic power stations. Because the main structure of a floating photovoltaic power station floats on the water surface, its grounding system is complex, typically consisting of a metal floating platform, an underwater grounding conductor network, and conductive structures connecting the two, forming a hybrid "surface-underwater" grounding system. This system is subjected to harsh environments such as long-term immersion in water, alternating wet and dry conditions, and fluctuating corrosion potentials, making it prone to defects such as connection point corrosion, conductor breakage, and increased contact resistance. This can lead to excessive local grounding resistance, seriously affecting the lightning protection safety, equipment protection, and personnel safety of the power station. Therefore, achieving visualized monitoring of the internal status of the grounding grid and early, accurate fault location is of great engineering necessity for ensuring the long-term safe and stable operation of floating photovoltaic power stations.

[0021] To achieve the above objectives, the fault location system mainly includes the following core components, which are connected by electrical connections and data communication to form an organic whole: (1) The grounding grid, as the monitored object, is the sum of the grounding electrodes of the floating photovoltaic power station. Its structural features include: a metal floating platform, an underwater grounding conductor network, and connecting conductors. Among them, the metal floating platform is a galvanized steel or aluminum alloy structure, which serves as both the supporting foundation for the photovoltaic modules and the surface grounding electrode. The underwater grounding conductor network is a mesh or strip conductor made of galvanized flat steel, copper cable, etc., laid on the bottom of the water body or suspended in the water. The connecting conductors use corrosion-resistant cables or rigid connectors to electrically connect the floating platform and the underwater conductor network at multiple points, forming a complete grounding loop.

[0022] (2) A signal generator, serving as an excitation source, is used to generate the high-frequency test current signal required for diagnostics. Its output is connected to one or more pre-set injection points on the grounding network via insulated leads. The injection points are specially selected grounding network access locations that facilitate signal input; they can coincide with the measurement points of the sensor network or be set independently. The signal generator receives instructions from the controller to precisely control the frequency, amplitude, phase, and injection timing of the output signal.

[0023] (3) The sensor network, as a data acquisition unit, consists of multiple integrated current-voltage sensors distributed across key nodes of the grounding grid. Key nodes are important measurement locations selected based on the topology and electrical characteristics of the grounding grid, including at least: electrical interconnection points between floating photovoltaic array units, the main grounding inlet point of the floating platform, and the connection point between the platform and the underwater conductor. Each sensor measures the voltage response signal generated by the test current excitation at its node in real time. All sensors are connected to the controller via wired (e.g., RS-485, CAN bus) or wireless (e.g., LoRa, ZigBee) communication networks to achieve synchronous or quasi-synchronous data acquisition and uploading.

[0024] (4) The controller, as the brain of the system, is usually an industrial computer or a high-performance embedded system. It connects to the signal generator, sensor network, and power plant monitoring center through a communication interface. The controller is responsible for scheduling and executing the entire positioning process: sending control commands to the signal generator to trigger signal injection; synchronously receiving and processing voltage data from the sensor network; running the core impedance imaging and fault analysis algorithms; and generating and outputting diagnostic results. The controller integrates a three-dimensional structural model of the grounding grid, algorithm programs, and a historical database.

[0025] like Figure 1 As shown, the connections and data flows between the components are as follows: Control command flow: Controller → (communication link) → signal generator, controlling its output.

[0026] Excitation signal flow: signal generator → (insulated cable) → grounding grid injection point → propagates throughout the entire grounding grid conductor.

[0027] Response signal flow: Electrical changes at key nodes of the grounding grid → (sensor sensing) → sensor network.

[0028] Measurement data flow: Sensor network → (Communication network) → Controller.

[0029] Diagnostic result flow: Controller → (Power plant monitoring network) → Monitoring center / digital twin platform / maintenance terminal.

[0030] The fault location system of this application, through the above structure, realizes the closed-loop monitoring capability of active excitation, full-domain perception, intelligent analysis and precise location of the grounding grid of floating photovoltaic power stations, and solves the technical problem that traditional methods cannot locate internal defects in real time and intuitively.

[0031] The preferred embodiments of this application are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit this application. Furthermore, the embodiments and features in the embodiments of this application can be combined with each other without conflict.

[0032] Figure 2 This is a flowchart illustrating a method for fault location of grounding resistance in a floating photovoltaic power station, provided as an embodiment of this application. Figure 2 As shown, the method may include: Step S210: In response to the received fault location command, trigger the signal generator to inject a high-frequency test current signal into the grounding grid.

[0033] In response to a fault location command from the monitoring platform or timer, the controller initiates a high-frequency test current signal injection process. The controller controls the signal generator to generate a high-frequency test current signal in the range of 1kHz to 100kHz. This frequency range is chosen to balance the signal's penetration ability in water with its resistance to power frequency interference.

[0034] The controller controls the signal generator to inject a high-frequency test current signal within a preset frequency range into one or more injection points of the grounding grid. Specifically, injection can be performed through the following two configurable modes: A) Polling Injection Mode: The control signal generator injects high-frequency test current signals into individual injection points of the grounding grid sequentially according to a preset polling order. This mode requires simple equipment and clear timing control.

[0035] B) Synchronous Injection Mode: The control signal generator synchronously injects multiple high-frequency test current signals into multiple injection points of the grounding grid according to a preset timing and phase. This mode can improve data acquisition efficiency and help obtain richer network response information.

[0036] Furthermore, before injecting the trigger signal, the controller can first acquire the current environmental parameters, which include at least the resistivity, water temperature, and water level of the water body where the floating photovoltaic power station is located. Based on these current environmental parameters, the frequency and / or amplitude of the high-frequency test current signal are dynamically adjusted.

[0037] Specifically, frequency adjustment: High-frequency signals exhibit a "skin effect" during propagation in water and grounding conductors, meaning their penetration depth is inversely proportional to the square root of the frequency and directly related to the water's conductivity. To obtain sufficient detection depth to cover the underwater grounding conductor network, the frequency needs to be adjusted according to the water's conductivity.

[0038] Adjustment strategy: When high water resistivity (poor conductivity) is detected, the controller automatically lowers the frequency of the injected signal (e.g., moving closer to the 1kHz lower limit) to increase the signal penetration depth in the medium and ensure that the signal can effectively excite the underwater grounding electrode. Conversely, in waters with low resistivity (good conductivity), the frequency can be appropriately increased (e.g., moving closer to the 100kHz upper limit) to reduce excessive diffusion and attenuation of the signal in well-conducting water bodies, thereby improving the signal-to-noise ratio and spatial resolution.

[0039] Amplitude Adjustment: The amplitude of the response voltage generated by the signal in the grounding grid-water loop is proportional to the amplitude of the injected current, and is also affected by the total impedance of the loop (including the impedance of the grounding grid itself and the coupling impedance that varies with water level and water quality). To ensure that each node of the sensor network can acquire a voltage signal of sufficient strength for accurate measurement, the injected current needs to be dynamically adjusted.

[0040] Adjustment Strategy: Based on the current water resistivity and water level, the controller estimates the equivalent impedance of the current signal loop using a simplified impedance model. If the estimated impedance increases (e.g., due to a decrease in the contact area between the grounding electrode and the water caused by a drop in water level, or an increase in water resistivity), the controller instructs the signal generator to increase the amplitude of the output current accordingly to maintain the response voltage within the ideal measurement range of the sensing module. Conversely, it reduces the current amplitude accordingly to prevent signal overload or unnecessary increase in device power consumption.

[0041] The aforementioned adaptive adjustment mechanism enables the fault location system to intelligently adapt to different water quality conditions, from freshwater reservoirs to saline lakes, as well as environmental changes such as seasonal water level fluctuations. It fundamentally ensures that, under different environmental conditions, the injected test signal can effectively penetrate the medium, excite the target grounding network, and generate a measurable response signal with appropriate amplitude and high signal-to-noise ratio.

[0042] In some embodiments, the system may further include a simulation-based pre-deployment optimization mechanism. This mechanism performs electromagnetic field simulation analysis based on a precise three-dimensional model of the grounding grid before system deployment; based on the simulation results, it optimizes the deployment locations and density of sensors in the sensor network, as well as the injection point locations of high-frequency test current signals. This optimization aims to ensure that the subsequent impedance imaging algorithm can obtain sufficient spatial sampling information to achieve the preset resistivity distribution reconstruction spatial resolution, thus guaranteeing positioning accuracy from the source.

[0043] The implementation of this step provides an active excitation source for grounding grid condition diagnosis through controllable high-frequency signal injection; multiple injection modes and environmental adaptation mechanisms enhance the system's flexibility and environmental adaptability; and preliminary simulation optimization lays the physical foundation for high-precision imaging.

[0044] Step S220: Obtain current-voltage dataset by collecting voltage response signals from key nodes through the sensor network.

[0045] During the high-frequency test current signal injection, the controller synchronously triggers sensors deployed at various key nodes. These key nodes include at least: electrical connection points between adjacent array units in the floating photovoltaic array, a pre-set grounding connection point of the metal floating platform supporting the photovoltaic modules, and a connection point connecting the metal floating platform to the underwater grounding conductor.

[0046] Each sensor in the sensor network synchronously collects the voltage response signal at its key node and uploads the data to the controller.

[0047] The controller correlates and aligns the signal parameters of the injected current (such as amplitude, phase, and injection point location) with the voltage response signals (amplitude and phase) collected by all key nodes to form a complete current-voltage dataset.

[0048] This step is implemented by synchronously acquiring data through a distributed sensor network, which enables synchronous capture of the voltage response across the entire grounding grid, providing comprehensive and synchronous boundary measurement data for subsequent full-space resistivity reconstruction.

[0049] Step S230: Based on the current-voltage dataset, the resistivity distribution is reconstructed using an impedance imaging algorithm to generate a three-dimensional resistivity distribution map of the grounding grid.

[0050] The specific implementation steps are as follows: Step 1: Based on the structural and spatial information of the grounding grid, construct a three-dimensional discretized model of its computational domain. This model consists of multiple elements, and each element is assigned a conductivity parameter characterizing its electrical conductivity. Specifically: Based on the design drawings and spatial layout data of the floating photovoltaic power station's grounding grid, the controller constructs a three-dimensional geometric model in the computational environment, including a metal floating platform, an underwater conductor network, connecting conductors, and the surrounding water medium. The geometric model is then meshed using a finite element analysis algorithm, discretizing it into a large number (e.g., hundreds of thousands to millions) of continuous volumetric elements to generate a three-dimensional finite element computational model. Each volumetric element is assigned an initial conductivity parameter, and the initial conductivity of all elements constitutes the initially assumed conductivity distribution.

[0051] The model is defined as a forward problem model, and its function is to solve the electromagnetic field equations using the finite element method when a specific conductivity distribution is given as input, and to calculate the predicted voltage values ​​that should be generated at each key node (measurement node) as output.

[0052] Step 2: Combine the current-voltage dataset with the three-dimensional discretized model to construct and solve an inverse problem with element conductivity as the optimization variable and the goal of matching the predicted voltage with the measured voltage. The optimal conductivity distribution for all elements in the computational domain is obtained through iterative optimization. Specifically: The controller uses the measured voltage value from the acquired current-voltage dataset as the objective, and the conductivity of all volume elements in the 3D model as the unknown variable to be solved, to construct an inverse problem. The objective of solving this inverse problem is to find an optimal conductivity distribution such that, when this distribution is input into the forward problem model, the difference between the calculated predicted voltage value and the measured voltage value is minimized.

[0053] The solution uses an iterative optimization algorithm, and the specific loop steps are as follows: a) Forward calculation: Input the element conductivity distribution of the current iteration step into the forward problem model, run the finite element calculation, and obtain the predicted voltage set under the current iteration.

[0054] b) Error assessment: Calculate the difference between the predicted voltage set and the measured voltage set (usually using the error norm, such as the L2 norm).

[0055] c) Convergence judgment: If the difference metric is less than the preset convergence threshold, the current conductivity distribution is considered to be close enough to the real situation, the iteration is judged to be converged, and the distribution is the optimal conductivity distribution, and the loop is exited.

[0056] d) Parameter Update: If convergence fails, calculate the required adjustment for the conductivity of each unit based on the difference metric and optimization algorithm rules. Preferably, this step is implemented by solving a regularized least squares problem. ; Where Δσ is the conductivity adjustment vector, J is the sensitivity matrix (Jacobi matrix), representing the effect of small changes in cell conductivity on the predicted voltage, r is the residual vector between the predicted and measured voltages, λ is the regularization parameter, and Ψ(·) is the regularization function (such as Tikhonov regularization or total variation regularization). The purpose of introducing the regularization term is to overcome the inherent ill-posedness of the inverse problem by incorporating prior knowledge about the smoothness or edge characteristics of the conductivity distribution, stabilizing the solution process, and improving the quality of the reconstructed image. After calculating the adjustment, the conductivity values ​​of all cells are updated, and the process returns to step a) to begin the next iteration.

[0057] Step 3: Based on the optimal conductivity distribution, calculate and generate a three-dimensional image characterizing the spatial distribution of the resistance characteristics of the grounding grid system, i.e., a three-dimensional resistivity distribution map.

[0058] After the iteration converges, the controller obtains the optimal conductivity distribution (i.e., the optimal conductivity value of each volume element) obtained from the final iteration. Based on the reciprocal relationship between conductivity (σ) and resistivity (ρ) (ρ = 1 / σ), the conductivity value of each element is converted into its corresponding resistivity value. Subsequently, these resistivity values ​​are mapped and rendered according to the spatial coordinates of their respective volume elements in the three-dimensional finite element model, generating a three-dimensional resistivity distribution map. This map visually represents the resistivity distribution of the entire grounding grid system (including the surrounding water medium) at various spatial locations in a three-dimensional visualization format (such as color contour maps or isosurfaces).

[0059] This step, by establishing an accurate forward problem model and a stable inverse problem iterative solution (especially by introducing regularization techniques), can reconstruct the three-dimensional resistivity distribution inside the grounding grid with high precision, revealing hidden local high-resistivity areas and providing direct visual evidence for accurate fault location.

[0060] Step S240: Based on the three-dimensional resistivity distribution map, locate the abnormal areas in the grounding grid where the resistance value exceeds the preset threshold.

[0061] Based on the generated three-dimensional resistivity distribution map, the controller performs the following steps to achieve automated fault area identification and location: Step 1: Perform image segmentation on the three-dimensional resistivity distribution map, extract the set of voxels whose resistivity values ​​are continuously higher than the first preset threshold, and form candidate abnormal regions.

[0062] Specifically, a first preset threshold is set (for example, the local resistivity critical value converted according to the grounding resistance safety specification requirements), and a set of voxels (3D pixels) in the figure whose resistivity values ​​are continuously higher than the threshold are extracted. These sets are marked as candidate abnormal regions.

[0063] Preferably, it may also include trend analysis: comparing the currently generated three-dimensional resistivity distribution map with the benchmark resistivity distribution map in the historical database, calculating the resistivity change gradient and spatial expansion rate of the candidate abnormal region, in order to assess the development trend of the fault risk in the region and realize the early warning function.

[0064] Step 2: Map the voxel coordinates of the candidate abnormal region to the three-dimensional structural model of the grounding grid to determine its position in physical space.

[0065] Specifically, the three-dimensional image coordinates of each voxel in the candidate anomaly region are mapped to a pre-established three-dimensional structure model of the grounding grid (or a digital map of the power plant layout) to determine the specific geographical location of the anomaly region in the real physical space, such as "the connection point of the floating platform in the southeast corner of the No. 3 array area".

[0066] Step 3: Based on the electrical connection topology of the grounding network, analyze the impact of candidate abnormal areas on the grounding performance of adjacent nodes, and output a fault location report including geographical location, impact range and severity level, in conjunction with their physical location.

[0067] Specifically, based on the electrical connection topology of the grounding grid, the impact of candidate anomaly areas on the grounding performance of adjacent critical nodes is analyzed. Taking into account factors such as physical location, resistivity exceedance, and impact range, a structured fault location report is generated. This report includes key information such as the geographical location of the anomaly area, its impact range, severity level (e.g., minor, moderate, severe), and possible fault cause inferences (e.g., connection corrosion, conductor breakage).

[0068] This step, through automated image processing, coordinate mapping, and electrical impact analysis, can quickly and accurately transform imaging results into fault reports containing precise location and assessment information that can be directly used by maintenance personnel, greatly improving the efficiency and relevance of maintenance decisions.

[0069] Furthermore, the controller will push the information of the located abnormal area, the corresponding three-dimensional resistivity distribution map (or its key profile, isosurface visualization results), and the generated fault location report to the monitoring platform in real time for display and audible and visual alarms. At the same time, this information can be used to update the digital twin model of the floating photovoltaic power station, highlighting the abnormal state of the grounding grid in the virtual model, realizing the visual tracking and management of the status, and forming a complete closed loop from monitoring, diagnosis, location to alarm.

[0070] The fault location method for grounding resistance of floating photovoltaic power plants proposed in this application realizes real-time imaging of the internal resistance distribution of the grounding grid and automatic identification of abnormal areas, improving the timeliness and accuracy of fault detection; through high-frequency signal and impedance imaging technology, it enhances the adaptability in the complex aquatic environment of floating power plants; the distributed sensing and automatic positioning mechanism reduces the reliance on manual inspection, improving operation and maintenance efficiency and the overall safety of the power plant.

[0071] Corresponding to the above method, this application also provides a fault location device for the grounding resistance of a floating photovoltaic power station, such as... Figure 3 As shown, the device includes: The trigger unit 310 is used to trigger the signal generator to inject a high-frequency test current signal into the grounding grid in response to the received fault location command; The acquisition unit 320 is used to acquire current-voltage datasets by collecting voltage response signals from each key node through the sensor network. The generation unit 330 is used to reconstruct the resistivity distribution based on the current-voltage dataset using an impedance imaging algorithm, and generate a three-dimensional resistivity distribution map of the grounding grid. The positioning unit 340 is used to locate abnormal areas in the grounding grid where the resistance value exceeds a preset threshold based on the three-dimensional resistivity distribution map.

[0072] The functions of each functional unit of the fault location device for the grounding resistance of the floating photovoltaic power station provided in the above embodiments of this application can be realized through the above methods and steps. Therefore, the specific working process and beneficial effects of each unit in the fault location device for the grounding resistance of the floating photovoltaic power station provided in the embodiments of this application will not be repeated here.

[0073] This application also provides an electronic device, such as... Figure 4 As shown, it includes a processor 410, a communication interface 420, a memory 430, and a communication bus 440, wherein the processor 410, the communication interface 420, and the memory 430 communicate with each other through the communication bus 440.

[0074] Memory 430 is used to store computer programs; When the processor 410 executes the program stored in the memory 430, it performs the following steps: In response to the received fault location command, the signal generator is triggered to inject a high-frequency test current signal into the grounding grid; The current-voltage dataset is obtained by collecting the voltage response signals of each key node through the sensor network. Based on the current-voltage dataset, an impedance imaging algorithm is used to reconstruct the resistivity distribution and generate a three-dimensional resistivity distribution map of the grounding grid. Based on the three-dimensional resistivity distribution map, locate abnormal areas in the grounding grid where the resistance value exceeds a preset threshold.

[0075] The communication bus mentioned above can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. This communication bus can be divided into address bus, data bus, control bus, etc. For ease of illustration, only one thick line is used to represent it in the diagram, but this does not mean that there is only one bus or one type of bus.

[0076] The communication interface is used for communication between the aforementioned electronic devices and other devices.

[0077] The memory may include random access memory (RAM) or non-volatile memory (NVM), such as at least one disk storage device. Optionally, the memory may also be at least one storage device located remotely from the aforementioned processor.

[0078] The processors mentioned above can be general-purpose processors, including central processing units (CPUs), network processors (NPs), etc.; they can also be digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0079] The implementation methods and beneficial effects of the various components of the electronic device in the above embodiments for solving the problem can be found in [reference needed]. Figure 1 The steps in the illustrated embodiments are used to implement the electronic device. Therefore, the specific working process and beneficial effects of the electronic device provided in this application will not be repeated here.

[0080] In another embodiment provided in this application, a computer-readable storage medium is also provided, which stores instructions that, when executed on a computer, cause the computer to perform the fault location method for the grounding resistance of a floating photovoltaic power station as described in any of the above embodiments.

[0081] In another embodiment provided in this application, a computer program product containing instructions is also provided, which, when run on a computer, causes the computer to execute the fault location method for the grounding resistance of a floating photovoltaic power station as described in any of the above embodiments.

[0082] Those skilled in the art will understand that the embodiments in this application can be provided as methods, systems, or computer program products. Therefore, the embodiments in this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the embodiments in this application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0083] This application describes embodiments of methods, apparatus (systems), and computer program products according to embodiments of this application with reference to flowchart illustrations and / or block diagrams. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0084] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0085] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0086] Although preferred embodiments have been described in this application, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the embodiments of this application.

[0087] Obviously, those skilled in the art can make various modifications and variations to the embodiments of this application without departing from the spirit and scope of the embodiments of this application. Therefore, if these modifications and variations to the embodiments of this application fall within the scope of the claims in this application and their equivalents, then this application also intends to include these modifications and variations.

Claims

1. A method for fault location of grounding resistance in a floating photovoltaic power station, characterized in that, A controller is used in a fault location system, which also includes a grounding grid of a floating photovoltaic power station, a sensor network formed by deploying sensors at key nodes of the grounding grid, and a signal generator. The method includes: In response to the received fault location command, the signal generator is triggered to inject a high-frequency test current signal into the grounding grid; The current-voltage dataset is obtained by collecting the voltage response signals of each key node through the sensor network. Based on the current-voltage dataset, an impedance imaging algorithm is used to reconstruct the resistivity distribution and generate a three-dimensional resistivity distribution map of the grounding grid. Based on the three-dimensional resistivity distribution map, locate abnormal areas in the grounding grid where the resistance value exceeds a preset threshold.

2. The method as described in claim 1, characterized in that, In response to the received fault location command, a signal generator is triggered to inject a high-frequency test current signal into the grounding grid, including: Control the signal generator to inject a high-frequency test current signal with a frequency within a preset frequency range into one or more injection points of the grounding grid; The injection point is a designated location on the grounding network for receiving the test current, which may partially overlap with or be entirely independent of the key node used to deploy the sensor.

3. The method as described in claim 2, characterized in that, The method of injecting a high-frequency test current signal with a frequency within a preset frequency range into one or more injection points of the grounding grid includes: The signal generator is controlled to inject high-frequency test current signals with a frequency within a preset frequency range into a single injection point of the grounding grid in a preset polling order. Alternatively, the signal generator can be controlled to synchronously inject multiple high-frequency test current signals into multiple injection points of the grounding grid according to a preset timing and phase.

4. The method as described in claim 1, characterized in that, The key nodes include at least: electrical connection points between adjacent array units in the floating photovoltaic array, a preset grounding connection point of the metal floating platform supporting the photovoltaic modules, and a connection point connecting the metal floating platform to the underwater grounding conductor.

5. The method as described in claim 1, characterized in that, Before triggering the signal generator to inject a high-frequency test current signal into the grounding grid in response to the received fault location command, the method further includes: Obtain current environmental parameters, which include at least the resistivity, water temperature and water level of the water body where the floating photovoltaic power station is located; The frequency and / or amplitude of the high-frequency test current signal are dynamically adjusted based on the current environmental parameters.

6. The method as described in claim 1, characterized in that, Before triggering the signal generator to inject a high-frequency test current signal into the grounding grid in response to the received fault location command, the method further includes: Electromagnetic field simulation was performed on the three-dimensional structural model of the grounding grid; Based on the simulation results, the optimal deployment location and density of sensors in the sensor network, as well as the optimal location of the injection point for the high-frequency test current signal, are determined.

7. The method as described in claim 1, characterized in that, Based on the current-voltage dataset, an impedance imaging algorithm is used to reconstruct the resistivity distribution, generating a three-dimensional resistivity distribution map of the grounding grid, including: Based on the structural and spatial information of the grounding grid, a three-dimensional discretized model of its computational domain is constructed. This model consists of multiple units, and each unit is assigned a conductivity parameter that characterizes its electrical conductivity. By combining the current-voltage dataset with the three-dimensional discretized model, an inverse problem is constructed and solved with the conductivity of each unit as the optimization variable and the goal of matching the predicted voltage with the measured voltage. The optimal conductivity distribution of all units is obtained through iterative optimization. Based on the optimal conductivity distribution, a three-dimensional resistivity distribution map characterizing the spatial distribution of the resistance characteristics of the grounding grid system is calculated and generated.

8. A fault location device for the grounding resistance of a floating photovoltaic power station, characterized in that, A controller is used in a fault location system, which also includes a grounding grid for a floating photovoltaic power station, a sensor network formed by deploying sensors at key nodes of the grounding grid, and a signal generator. The device includes: The triggering unit is used to trigger the signal generator to inject a high-frequency test current signal into the grounding grid in response to the received fault location command; The acquisition unit is used to acquire current-voltage datasets by collecting voltage response signals from each key node through the sensor network. The generation unit is used to reconstruct the resistivity distribution based on the current-voltage dataset using an impedance imaging algorithm, and generate a three-dimensional resistivity distribution map of the grounding grid. The positioning unit is used to locate abnormal areas in the grounding grid where the resistance value exceeds a preset threshold based on the three-dimensional resistivity distribution map.

9. An electronic device, characterized in that, The electronic device includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; A processor, when executing a program stored in memory, implements the method of any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method described in any one of claims 1-7.

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