Photovoltaic charging fault detection method and device, energy storage power supply and storage medium
By acquiring multiple frames of input electrical parameters of the photovoltaic charging circuit, determining its stable state, and comparing it with the fault threshold, the problem of misjudgment of undervoltage faults in photovoltaic charging control is solved, and the detection accuracy is improved.
Patent Information
- Application Number
- CN202610695274.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2026-05-19
- Publication Date
- 2026-08-25
AI Technical Summary
In existing technologies, photovoltaic charging control is easily affected by weather changes, leading to fluctuations in photovoltaic input voltage, resulting in misjudgment of undervoltage faults and insufficient detection accuracy.
By acquiring multiple frames of input electrical parameters collected by the photovoltaic charging circuit, determining their rate of change, and performing steady-state detection, fault detection is performed only when the input electrical parameters are stable and compared with the fault threshold. Taking into account the sampling accuracy and filtering method of the inverter type, an appropriate fault detection strategy is adopted.
It improves the accuracy of photovoltaic charging fault detection, reduces false alarms, and achieves efficient fault detection under stable conditions.
Smart Images
Figure CN122631970A_ABST
Abstract
Description
Technical Field
[0001] This application belongs to the field of fault detection technology for energy storage power supplies, and particularly relates to a photovoltaic charging fault detection method, fault detection device, energy storage power supply, and computer-readable storage medium. Background Technology
[0002] With the widespread application of photovoltaic energy storage systems, photovoltaic charging control has become one of the key functions of energy storage equipment. In practical applications, the photovoltaic input voltage fluctuates significantly due to the large influence of weather changes (such as cloud cover, changes in the angle of sunlight, etc.) on the intensity of sunlight.
[0003] However, existing technologies typically monitor the photovoltaic input voltage in real time by setting a fixed undervoltage threshold. When the voltage is lower than the threshold, it is judged as an undervoltage fault, which is prone to misjudgment. Summary of the Invention
[0004] This application aims to address at least one of the technical problems existing in the prior art. To this end, this application proposes a photovoltaic charging fault detection method, a fault detection device, an energy storage power supply, and a computer-readable storage medium, which can improve the accuracy of fault detection.
[0005] In a first aspect, this application provides a photovoltaic charging fault detection method applied to energy storage power supply charging, characterized in that the energy storage power supply includes a photovoltaic charging circuit, the photovoltaic charging circuit is connected to a photovoltaic module, the photovoltaic charging circuit is used to collect input electrical parameters of the photovoltaic module, and the method includes: Obtain the input electrical parameters from multiple frames within the current time window; The rate of change of the input electrical parameters is determined based on the input electrical parameters within the current time window; Based on the rate of change of the input electrical parameters, a steady state detection of the input electrical parameters is performed to obtain a state detection result, which includes whether the input electrical parameters are in a steady state. Based on the fact that the input electrical parameters are in a stable state, the input electrical parameters are compared with the fault threshold to obtain the fault detection result.
[0006] Secondly, this application provides a fault detection device for charging an energy storage power supply, the energy storage power supply including a photovoltaic charging circuit connected to a photovoltaic module, the photovoltaic charging circuit being used to collect input electrical parameters of the photovoltaic module, the device comprising: The acquisition module is used to acquire the input electrical parameters of multiple frames within the current time window; A stability detection module is used to determine the rate of change of the input electrical parameters based on the input electrical parameters within the current time window; and to perform stability state detection of the input electrical parameters based on the rate of change of the input electrical parameters, thereby obtaining a state detection result, wherein the state detection result includes whether the input electrical parameters are in a stable state. The fault detection module is used to compare the input electrical parameters with a fault threshold based on the fact that the input electrical parameters are in a stable state, so as to obtain the fault detection result.
[0007] Thirdly, this application provides an energy storage power source, comprising: A photovoltaic charging circuit is connected to a photovoltaic module and is used to collect the input electrical parameters of the photovoltaic module. The system includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the aforementioned photovoltaic charging fault detection method.
[0008] Fourthly, this application provides a computer-readable storage medium storing a computer program adapted for loading by a processor to execute the above-described photovoltaic charging fault detection method.
[0009] The photovoltaic charging fault detection method, fault detection device, energy storage power supply, and computer-readable storage medium provided in this application embodiment obtain multiple frames of input electrical parameters of the photovoltaic module collected by the photovoltaic charging circuit within the current time window to detect the stability of the input electrical parameters, thereby determining whether the input electrical parameters are fluctuating or have stabilized.
[0010] It is understandable that fault detection is more accurate when the input electrical parameters are stable. Therefore, based on the state detection results, and assuming the input electrical parameters are in a stable state, the input electrical parameters can be compared with the fault threshold to obtain the fault detection result, which can improve the accuracy of fault detection.
[0011] Furthermore, when performing fault detection, the differences in sampling accuracy, filtering methods, and fault judgment strategies among different inverter types are taken into account. Therefore, for different inverter types, appropriate fault detection strategies can be used to achieve fault detection, thereby further improving the accuracy of fault detection.
[0012] Additional aspects and advantages of embodiments of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of embodiments of this application. Attached Figure Description
[0013] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which: Figure 1 This is a schematic diagram illustrating an application scenario of the photovoltaic charging fault detection method provided in some embodiments of this application; Figure 2 This is a first flowchart illustrating a photovoltaic charging fault detection method provided in certain embodiments of this application; Figure 3 This is a schematic diagram of the second process of the photovoltaic charging fault detection method provided in some embodiments of this application; Figure 4 This is a schematic diagram of the overall process of a photovoltaic charging fault detection method provided in some embodiments of this application; Figure 5 This is a schematic diagram of a fault detection device provided in some embodiments of this application. Detailed Implementation
[0014] The embodiments of this application are described in detail below. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain this application, and should not be construed as limiting this application.
[0015] Please see Figure 1 , Figure 1 This is an application scenario diagram of a photovoltaic charging fault detection method provided in an embodiment of this application. The application scenario provided in this application includes a fault detection system 1000, which includes an energy storage power supply 100 and a terminal device 200.
[0016] Here, the energy storage power supply 200 refers to a device capable of storing electrical energy. It is generally equipped with a rechargeable battery. By storing a large amount of electrical energy in the battery within the energy storage power supply, the energy storage power supply can output the electrical energy stored in the battery when needed.
[0017] There are many types of energy storage power supplies, which can be classified according to application scenarios: (1) Portable energy storage: It is generally a small energy storage power supply, using lithium-ion batteries, etc. It is easy to carry and used for outdoor camping, emergency charging and other scenarios. It can power mobile phones, computers, lighting equipment, etc.
[0018] (2) Home energy storage: Used in homes to store solar power or electricity generated during off-peak hours of the power grid for use by home electrical equipment, achieving the purpose of peak shaving and valley filling, saving electricity costs, etc.
[0019] (3) Industrial and commercial energy storage: Used in factories, data centers, shopping malls and other places, it can be used for load regulation, demand-side management, power quality improvement, etc., to help users reduce electricity costs and improve power supply reliability.
[0020] (4) Grid energy storage: It is widely used in power systems to regulate the peak-valley difference of the power grid, smooth the fluctuations of renewable energy generation, and improve the stability and reliability of the power grid. Common types include large lithium-ion battery energy storage power stations, flow battery energy storage power stations, and pumped storage power stations.
[0021] In order to adapt to the increasingly diverse power consumption scenarios, portable energy storage power supplies have emerged. Portable energy storage power supplies, also known as portable lithium-ion battery energy storage power supplies or outdoor power supplies, usually refer to backup or emergency power supplies weighing no more than 18 kg. They use lithium-ion batteries as energy storage components and have AC or DC input charging interfaces as well as AC or DC output interfaces.
[0022] In one alternative embodiment, the energy storage power supply includes a battery, a main control board, a battery management system, and an inverter.
[0023] Among them, the battery is the energy core of the energy storage power supply and is the component that stores the power.
[0024] The main control board is the core of the energy storage power supply. The system's wake-up, shutdown, charging judgment, and power consumption management are all controlled by the main control board.
[0025] Among them, the Battery Management System (BMS) is an electronic system used to monitor, protect, optimize and manage batteries (such as lithium batteries, lead-acid batteries, etc.). Its core function is to ensure that the battery works efficiently within a safe range, extend its service life, and provide stable power output to the equipment.
[0026] For example, a battery management system can control the charging and discharging switches to achieve charging and discharging control; and it can achieve battery balancing by detecting the electrical parameters of each cell in the battery.
[0027] An inverter is a power electronic device that converts direct current (DC) to alternating current (AC). An inverter can convert input AC power into DC power to charge batteries in energy storage systems or directly power loads.
[0028] In one alternative embodiment, the inverter includes a photovoltaic charging circuit connected to a photovoltaic module, the photovoltaic charging circuit being used to collect input electrical parameters of the photovoltaic module.
[0029] For example, the photovoltaic charging circuit is an MPPT (Maximum Power Point Tracking) controller.
[0030] MPPT (Maximum Power Point Tracking) is a key technology in photovoltaic (PV) systems that uses real-time acquisition of the input electrical parameters of PV modules to adjust the operating point, ensuring that the solar modules always operate at their maximum power output. This can increase power generation by 15%-30%. The core technology involves dynamically matching the impedance of the PV modules to the load and tracking the maximum power point (MPP) as it changes with sunlight and temperature.
[0031] Photovoltaic modules are essentially power generation units that convert solar energy into electrical energy and charge batteries. The core is crystalline silicon modules (monocrystalline / polycrystalline), which are paired with MPPT (Maximum Power Point Tracking) controllers and inverters to form a "photovoltaic-storage" system.
[0032] When the photovoltaic (PV) modules are generating electricity, they need to send a charging enable signal to the inverter in order to charge the battery. The PV charging circuit collects the input electrical parameters of the PV modules and transmits them to the inverter or to the main control board via a communication interface.
[0033] After receiving the input electrical parameters, the inverter or main control board can execute the photovoltaic charging fault detection method of this application to realize fault detection, generate a log based on the fault detection result, and send it to the terminal device for storage and / or display.
[0034] Optionally, the terminal device includes at least one of a terminal and a server.
[0035] The terminal may include, but is not limited to, smartphones (such as Android phones, iOS phones, etc.), tablets, laptops, desktop computers, portable personal computers, mobile internet devices (MIDs), etc., but this application embodiment does not limit this.
[0036] The server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms. This application does not limit this.
[0037] The photovoltaic charging fault detection method of this application can be implemented by the energy storage power supply alone, or by the energy storage power supply in conjunction with the terminal equipment, and there is no limitation on this.
[0038] It is understood that in the specific implementation of this application, user object data, context data and other related data are involved. When the embodiments of this application are applied to specific products or technologies, user permission or consent is required, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions.
[0039] Based on the above application scenarios, this application provides a photovoltaic charging fault detection method, which is described in detail below: Please see Figure 2 The photovoltaic charging fault detection method provided in this application embodiment is implemented by steps 011 to 013, which are described in detail below.
[0040] Step 011: Obtain the input electrical parameters of multiple frames within the current time window.
[0041] The current time window is a preset time window based on empirical values or experimental calibration, used to provide data support for the steady-state detection of input electrical parameters.
[0042] The input electrical parameters are the electrical parameters of the photovoltaic module input to the energy storage power supply collected by the photovoltaic charging circuit. For example, the input electrical parameters include input voltage and / or input current. Taking the detection of undervoltage faults as an example, it is more appropriate to use the input voltage for fault detection.
[0043] By acquiring multiple frames of input electrical parameters within the current time window, and utilizing the changes in the values of these multiple frames, the stable state of subsequent input electrical parameters can be detected.
[0044] Step 012: Determine the rate of change of the input electrical parameters based on the input electrical parameters within the current time window.
[0045] In one alternative embodiment, the rate of change of the input electrical parameters within the current time window can be measured by the difference between adjacent input electrical parameters within the current time window.
[0046] Step 013: Based on the rate of change of the input electrical parameters, perform a steady-state detection of the input electrical parameters to obtain a state detection result, which includes whether the input electrical parameters are in a steady state.
[0047] By calculating the rate of change of the input electrical parameters within the current time window, the steady state of the input electrical parameters can be detected, thereby obtaining the state detection result and determining whether the input electrical parameters are in a steady state.
[0048] It is understandable that when the rate of change is small (e.g., less than the preset rate), the input electrical parameters can be determined to be relatively stable, that is, the input electrical parameters are in a stable state; while when the rate of change is large (e.g., greater than or equal to the preset rate), the input electrical parameters can be determined to be unstable, that is, the input electrical parameters are not in a stable state.
[0049] Please see Figure 3 In an optional embodiment, the current time window includes multiple consecutive sub-windows. Step 012, determining the rate of change of the input electrical parameters based on the input electrical parameters within the current time window, includes: Step 0121: Calculate the first mean value of the input electrical parameters in any target sub-window and the second mean value of the input electrical parameters in the previous sub-window of the target sub-window. The target sub-window is any sub-window. Step 0122: Determine the rate of change corresponding to the target sub-window based on the first mean and the second mean; It is understandable that there may be large maxima or minima in the multi-frame input electrical parameters, and these maxima and minima will affect the accuracy of the rate of change calculation.
[0050] Therefore, by dividing the current time window into multiple consecutive sub-windows and then calculating the average value of the input electrical parameters for each sub-window, high-frequency interference can be filtered out, curves can be smoothed, glitch noise can be suppressed, the true trend can be preserved, and instantaneous outliers can be avoided from interfering with subsequent steady-state detection.
[0051] Then, the rate of change of the target sub-window is calculated by using the second average value of the input electrical parameters of the previous sub-window of any target sub-window and the first average value of the input electrical parameters of the target sub-window. The target sub-window can be any sub-window within the current time window. Therefore, the rate of change corresponding to each sub-window within the current time window can be obtained.
[0052] It can be understood that the rate of change corresponding to each sub-window can characterize the fluctuation of the input electrical parameters of that sub-window relative to the input electrical parameters of the previous sub-window. By observing the fluctuation of the input electrical parameters of each sub-window, it can be determined whether the input electrical parameters are in a stable state under the current time window.
[0053] For example, if the rate of change of multiple consecutive sub-windows is less than a preset rate, the input electrical parameter is determined to be in a stable state. If the rate of change of any one of the multiple consecutive sub-windows is greater than the preset rate, the input electrical parameter is determined to be in an unstable state.
[0054] In one optional embodiment, the rate of change of multiple consecutive sub-windows is less than a preset rate, including the rate of change of all sub-windows within the current time window being less than the preset rate; or, the rate of change of a preset number of consecutive sub-windows within the current time window is less than the preset rate.
[0055] Step 014: Based on the fact that the input electrical parameters are in a stable state, compare the input electrical parameters with the fault threshold to obtain the fault detection result.
[0056] For example, if the status detection result indicates that the input electrical parameters are not in a stable state, the accuracy of fault detection will be low due to the instability of the input electrical parameters; therefore, fault detection can be omitted in this case. Conversely, if the status detection result indicates that the input electrical parameters are in a stable state, the accuracy of fault detection will be high due to the stability of the input electrical parameters; therefore, fault detection can be performed in this case.
[0057] Therefore, when the input electrical parameters are stable, comparing the input electrical parameters with the fault threshold to obtain the fault detection result can improve the accuracy of fault detection.
[0058] Please refer to it again. Figure 3 In one optional embodiment, step 014 includes: Step 0141: Based on the type of inverter, determine the target detection strategy. The target detection strategy is any preset detection strategy, and the preset detection strategy corresponds one-to-one with the type of inverter. Step 0142: Based on the fact that the input electrical parameters are in a stable state, compare the input electrical parameters with the fault threshold corresponding to the target detection strategy to obtain the fault detection result.
[0059] The inverter type is determined based on at least one of the inverter's sampling accuracy, filtering method, and fault diagnosis strategy. For inverters with poor performance, the collected input electrical parameters fluctuate significantly, which may lead to frequent undervoltage detections. Therefore, it is necessary to ensure that the input electrical parameters are in a stable state to guarantee the accuracy of fault detection. Obtaining the inverter type facilitates subsequent fault detection using the corresponding criteria, thereby improving the accuracy of fault detection.
[0060] Different types of inverters generally have different thresholds for fault detection. For example, inverters of type 1 and type 2 are classified as follows: type 1 inverters use a fixed threshold for fault detection, while type 2 inverters use a non-fixed threshold. For type 1 inverters, a fixed threshold can be used for fault detection, while for type 2 inverters, the threshold needs to be dynamically determined based on the input electrical parameters of the current time window before fault detection.
[0061] First, based on the type of inverter, a target detection strategy that matches the type of the current inverter can be determined from multiple preset detection strategies.
[0062] For example, the preset detection strategy includes a first detection strategy and a second detection strategy, where the first detection strategy is the detection strategy corresponding to the first type and the second detection strategy is the detection strategy corresponding to the second type.
[0063] Therefore, when the inverter type is type 1, the target detection strategy is determined to be the first detection strategy; when the inverter type is type 2, the target detection strategy is determined to be the second detection strategy.
[0064] Then, fault detection is performed based on the target detection strategy, state detection results, and input electrical parameters to obtain fault detection results.
[0065] Thus, when performing fault detection, the differences in sampling accuracy, filtering methods, and fault judgment strategies among different inverter types are taken into account. Therefore, for different inverter types, appropriate fault detection strategies can be used to achieve fault detection, thereby further improving the accuracy of fault detection.
[0066] In an optional embodiment, step 0142 includes: Step 01421: Based on the stable state of the input electrical parameters, when the target detection strategy is the first detection strategy, the first threshold and the input electrical parameters are compared to obtain the fault detection result. The first threshold is the threshold corresponding to the first type. Step 01422: Based on the stable state of the input electrical parameters, when the target detection strategy is the second detection strategy, the second threshold and the input electrical parameters are compared to obtain the fault detection result. The second threshold is determined based on the input electrical parameters within the current time window.
[0067] It is understandable that when the target detection strategy is the first detection strategy, the inverter performs fault detection based on a fixed threshold. The first threshold and the input electrical parameters can be compared to obtain the fault detection result.
[0068] Therefore, based on a fixed first threshold and input electrical parameters adapted to the type of inverter, fault detection can be performed quickly to obtain the fault detection result. If the input electrical parameters are greater than or equal to the first threshold, it is determined that there is no fault; if the input electrical parameters are less than the first threshold, it is determined that there is a fault.
[0069] In one optional embodiment, when the target detection strategy is the first detection strategy and the input electrical parameters are in a stable state, fault detection is performed based on the first threshold and the input electrical parameters to obtain the fault detection result.
[0070] To further improve the accuracy of fault detection, fault detection can be performed when the input electrical parameters are stable, thereby eliminating the influence of fluctuations in the input electrical parameters.
[0071] When the target detection strategy is the second detection strategy, the inverter needs to perform fault detection based on a dynamically determined, non-fixed second threshold, which is easily affected by fluctuations in the input electrical parameters.
[0072] Therefore, it is necessary to ensure that the input electrical parameters are in a stable state at this time, and then perform fault detection based on the second threshold and the input electrical parameters to obtain the fault detection result. If the input electrical parameters are greater than or equal to the second threshold, it is determined that there is no fault; if the input electrical parameters are less than the second threshold, it is determined that there is a fault.
[0073] The second threshold is determined based on the base threshold and the fine-tuning threshold. The base threshold is a fixed threshold, and the fine-tuning threshold is determined based on the input electrical parameters within the current time window.
[0074] For example, if the lowest voltage in the current time window is higher than the first difference of the current second threshold, the fine-tuning threshold is increased by a preset step size to update the second threshold.
[0075] For example, if the difference between the lowest voltage in the current time window and the current second threshold is less than the second difference, the second threshold remains unchanged.
[0076] For example, if the lowest voltage in the current time window is more than the second difference from the current second threshold, it indicates that there may be instantaneous fluctuations. In this case, the fine-tuning threshold can be lowered to update the second threshold.
[0077] In one alternative embodiment, the second threshold value ranges from 10V to 11V.
[0078] In one example, the input electrical parameters include the input voltage, and the fault detection result includes whether there is undervoltage. When the fault detection is performed based on a first threshold and the input electrical parameters to obtain the fault detection result, if the input voltage is less than the first threshold, the fault detection result is determined to be undervoltage; if the input voltage is greater than or equal to the first threshold, the fault detection result is determined to be no undervoltage.
[0079] When performing fault detection based on a second threshold and input electrical parameters to obtain a fault detection result, if the input voltage is less than the second threshold, the fault detection result is determined to be undervoltage; if the input voltage is greater than or equal to the second threshold, the fault detection result is determined to be no undervoltage.
[0080] The photovoltaic charging fault detection method provided in this application obtains multiple frames of input electrical parameters of the photovoltaic module collected by the photovoltaic charging circuit within the current time window to detect the stability of the input electrical parameters, thereby determining whether the input electrical parameters are fluctuating or have stabilized.
[0081] It is understandable that fault detection is more accurate when the input electrical parameters are stable. Therefore, based on the state detection results, and assuming the input electrical parameters are in a stable state, the input electrical parameters can be compared with the fault threshold to obtain the fault detection result, which can improve the accuracy of fault detection.
[0082] In some embodiments, the photovoltaic charging fault detection method of this application can generate a fault log after each fault detection result is obtained. This enables fault detection and recording, and allows for the traceability of faults in the energy storage power supply.
[0083] Please see Figure 4 In one example, for ease of understanding, the overall implementation process of the photovoltaic charging fault detection method is described below.
[0084] After the energy storage power supply starts, it first performs initialization. After initialization, the photovoltaic charging circuit collects the photovoltaic charging input voltage of the current frame, then updates the number of collected input voltage frames K, and determines whether the updated number of frames K reaches the number of frames N required for the current time window. If not, it continues to collect the input voltage of the next frame.
[0085] If the input voltage of N frames in the current time window has been collected, then the current time window is constructed for subsequent fault detection.
[0086] During fault detection, the inverter type is first determined as either Type 1 (i.e., inverter type with a fixed threshold) or Type 2 (i.e., inverter type without a fixed threshold). If the inverter type is Type 1, fault detection is performed directly based on the fixed first threshold and the current input voltage to obtain the fault detection result. If the input voltage is normal (i.e., the input voltage is greater than or equal to the first threshold), the input voltage of the next frame is collected. If the input voltage is abnormal (i.e., undervoltage), the fault detection result is output and logged.
[0087] If the inverter type is type 2, it enters the filtering and debouncing module, which performs a steady-state detection on the input electrical parameters. When the input electrical parameters are in a steady state, a second threshold is dynamically determined based on the input voltage of the current time window. Then, fault detection is performed based on the dynamically determined second threshold and the current input voltage to obtain the fault detection result. If the input voltage is normal (i.e., the input voltage is greater than or equal to the second threshold), the next frame of input voltage is collected. If the input voltage is abnormal (i.e., undervoltage), the fault detection result is output and logged.
[0088] This application also provides a fault detection device 300 for performing the steps described above in the photovoltaic charging fault detection method. Please refer to... Figure 5 , Figure 5 This is a schematic diagram of a fault detection device 300 provided in an embodiment of this application. The fault detection device 300 includes: The acquisition module 301 is used to acquire multiple frames of input electrical parameters within the current time window; The stability detection module 302 is used to determine the rate of change of the input electrical parameters based on the input electrical parameters within the current time window; and to perform stability state detection of the input electrical parameters based on the rate of change of the input electrical parameters, and obtain a state detection result, which includes whether the input electrical parameters are in a stable state. The fault detection module 303 is used to compare the input electrical parameters with a fault threshold based on the fact that the input electrical parameters are in a stable state, so as to obtain the fault detection result.
[0089] It should be noted that the specific details of each module unit in the fault detection device 300 have been described in detail in the embodiments of the photovoltaic charging fault detection method, and will not be repeated here.
[0090] In the embodiments of this application, the terms "module" or "unit" refer to a computer program or part of a computer program that has a predetermined function and works with other related parts to achieve a predetermined goal, and can be implemented wholly or partially using software, hardware (such as processing circuitry or memory), or a combination thereof. Similarly, a processor (or multiple processors or memory) can be used to implement one or more modules or units. Furthermore, each module or unit can be part of an overall module or unit that includes the functionality of that module or unit.
[0091] In some embodiments, the fault detection device in this application can be implemented in hardware, such as an energy storage power supply or a component in the energy storage power supply, such as an integrated circuit or a chip; the fault detection device can also be implemented in software, such as as an application installed in the energy storage power supply.
[0092] In some embodiments, the energy storage power supply includes a photovoltaic module, an inverter, a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the various processes described above in the embodiments of the photovoltaic charging fault detection method and achieves the same technical effect. To avoid repetition, these will not be repeated here.
[0093] This application also provides a non-transitory computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it implements the various processes of the above-described photovoltaic charging fault detection method and achieves the same technical effect. To avoid repetition, it will not be described again here.
[0094] The processor can be the processor in the energy storage power supply of the above embodiments. The computer-readable storage medium can be a computer read-only memory (ROM), random access memory (RAM), magnetic disk, or optical disk, etc.
[0095] Computer-readable media can include computer storage media and communication media. Computer storage media includes volatile and non-volatile, removable and non-removable media implemented using any method or technology for storing information such as computer-readable instructions, data structures, program modules, or other data. Computer storage media include RAM, ROM, erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other solid-state storage technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape cassettes, magnetic tape, disk storage, or other magnetic storage devices. Of course, those skilled in the art will recognize that computer storage media are not limited to the above-mentioned types.
[0096] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the aforementioned photovoltaic charging fault detection method. The processor may be the processor in the energy storage power supply described in the above embodiments. When executed by the processor, this computer program implements the various processes of the embodiments of the aforementioned photovoltaic charging fault detection method and achieves the same technical effects; therefore, to avoid repetition, it will not be described again here.
[0097] It is understood that in the specific implementation of this application, data related to user identity or characteristics is involved. When the above embodiments of this application are applied to specific products or technologies, user permission or consent is required, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions.
[0098] Although embodiments of this application have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of this application, the scope of which is defined by the claims and their equivalents.
Claims
1. A photovoltaic charging fault detection method, applied to energy storage power supply charging, characterized in that, The energy storage power supply includes a photovoltaic charging circuit, which is connected to a photovoltaic module. The photovoltaic charging circuit is used to collect the input electrical parameters of the photovoltaic module. The method includes: Obtain the input electrical parameters from multiple frames within the current time window; The rate of change of the input electrical parameters is determined based on the input electrical parameters within the current time window; Based on the rate of change of the input electrical parameters, a steady state detection of the input electrical parameters is performed to obtain a state detection result, which includes whether the input electrical parameters are in a steady state. Based on the fact that the input electrical parameters are in a stable state, the input electrical parameters are compared with a fault threshold to obtain a fault detection result.
2. The photovoltaic charging fault detection method according to claim 1, characterized in that, The current time window includes multiple consecutive sub-windows, and determining the rate of change of the input electrical parameters based on the input electrical parameters within the current time window includes: Calculate the first mean value of the input electrical parameters in any target sub-window and the second mean value of the input electrical parameters in the previous sub-window of the target sub-window, wherein the target sub-window is any of the sub-windows; Based on the first mean and the second mean, the rate of change corresponding to the target sub-window is determined.
3. The photovoltaic charging fault detection method according to claim 2, characterized in that, The step of detecting the steady state of the input electrical parameters based on the rate of change of the input electrical parameters, and obtaining the state detection result, includes: If the rate of change of multiple consecutive sub-windows is less than a preset rate, the input electrical parameter is determined to be in a stable state. If the rate of change of any of the multiple consecutive sub-windows exceeds the preset rate, the input electrical parameter is determined to be in an unstable state.
4. The photovoltaic charging fault detection method according to claim 1, characterized in that, The energy storage power supply includes an inverter. The step of comparing the input electrical parameters with a fault threshold based on the input electrical parameters being in a stable state to obtain a fault detection result includes: Based on the type of inverter, a target detection strategy is determined. The target detection strategy is any preset detection strategy, and the preset detection strategy corresponds one-to-one with the type of inverter. Based on the fact that the input electrical parameters are in a stable state, the input electrical parameters are compared with the fault threshold corresponding to the target detection strategy to obtain the fault detection result.
5. The photovoltaic charging fault detection method according to claim 4, characterized in that, The inverters include a first type and a second type. The photovoltaic charging circuit of the first type performs fault detection based on a fixed threshold, while the photovoltaic charging circuit of the second type performs fault detection based on a non-fixed threshold. The preset detection strategy includes a first detection strategy and a second detection strategy. The determination of the target detection strategy based on the type of inverter includes: When the inverter is of the first type, the target detection strategy is determined to be the first detection strategy; When the inverter is of type two, the target detection strategy is determined to be the second detection strategy.
6. The photovoltaic charging fault detection method according to claim 5, characterized in that, The step of comparing the input electrical parameters with the fault threshold corresponding to the target detection strategy based on the input electrical parameters being in a stable state to obtain a fault detection result includes: Based on the fact that the input electrical parameters are in a stable state, when the target detection strategy is the first detection strategy, the first threshold and the input electrical parameters are compared to obtain the fault detection result. The first threshold is the threshold corresponding to the first type. Based on the fact that the input electrical parameters are in a stable state, when the target detection strategy is the second detection strategy, the second threshold and the input electrical parameters are compared to obtain the fault detection result. The second threshold is determined based on the input electrical parameters within the current time window.
7. The photovoltaic charging fault detection method according to claim 6, characterized in that, The input electrical parameters include the input voltage, and the fault detection result includes whether there is undervoltage. The step of comparing a first threshold with the input electrical parameters to obtain the fault detection result includes: If the input voltage is less than the first threshold, the fault detection result is determined to be undervoltage; If the input voltage is greater than or equal to the first threshold, the fault detection result is determined to be no undervoltage. The step of comparing the second threshold with the input electrical parameters to obtain the fault detection result includes: If the input voltage is less than the second threshold, the fault detection result is determined to be undervoltage; If the input voltage is greater than or equal to the second threshold, the fault detection result is determined to be no undervoltage.
8. A fault detection device, characterized in that, An apparatus for charging energy storage power supplies, wherein the energy storage power supply includes a photovoltaic charging circuit connected to a photovoltaic module, the photovoltaic charging circuit being used to collect input electrical parameters of the photovoltaic module, the apparatus comprising: The acquisition module is used to acquire the input electrical parameters of multiple frames within the current time window; A stability detection module is used to determine the rate of change of the input electrical parameters based on the input electrical parameters within the current time window; and to perform stability state detection of the input electrical parameters based on the rate of change of the input electrical parameters, thereby obtaining a state detection result, wherein the state detection result includes whether the input electrical parameters are in a stable state. The fault detection module is used to compare the input electrical parameters with a fault threshold based on the fact that the input electrical parameters are in a stable state, so as to obtain the fault detection result.
9. An energy storage power source, characterized in that, include: A photovoltaic charging circuit is connected to a photovoltaic module and is used to collect the input electrical parameters of the photovoltaic module. A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, implements the method as described in any one of claims 1-7.
10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program adapted for loading by a processor to perform the method as described in any one of claims 1-7.