Portable distributed photovoltaic power quality detection method and system

Abstract

The application belongs to the technical field of power quality detection, and provides a portable distributed photovoltaic power quality detection method and system, which comprises the following steps: obtaining power signals of a distributed photovoltaic line based on passive coupling; continuously sampling the obtained power signals adaptively to obtain discrete digital signals of the power signals; extracting multi-dimensional frequency domain characteristic parameters of the obtained discrete digital signals; performing traceability analysis on the extracted multi-dimensional frequency domain characteristic parameters to generate traceability analysis results; performing multi-dimensional collaborative security protection of the distributed photovoltaic based on the generated traceability analysis results and a protection effectiveness calculation model, feeding back obtained protection state information to the passive coupling acquisition stage, forming closed-loop control on the acquisition of the power signals, and completing power quality detection of the distributed photovoltaic.

Description

Technical Field

[0001] This invention belongs to the field of power quality testing technology, specifically relating to a portable distributed photovoltaic power quality testing method and system. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] As the proportion of distributed photovoltaic (PV) power stations in the energy structure continues to increase, their power generation process is susceptible to power quality problems such as harmonic pollution, voltage fluctuations, and flicker due to factors such as fluctuations in sunlight intensity, component aging, and inverter operating characteristics. These issues pose potential challenges to the safe and stable operation of the power grid and the normal operation of precision electrical equipment. Traditional power quality testing devices are mostly fixed installations, bulky, and dependent on external power supplies, making them unsuitable for the dispersed layout and complex installation environments of distributed PV power stations. Existing portable testing equipment generally suffers from limitations in power supply methods, inaccurate transient signal capture, and a lack of targeted harmonic source analysis, failing to meet the practical needs of rapid on-site testing and accurate source tracing. Therefore, there is an urgent need to develop an integrated, modular, and efficient testing device to achieve convenient and high-precision testing of PV power quality.

[0004] The existing technology has two key drawbacks: (1) Insufficient coordination between power supply and signal acquisition. Most detection devices use wired power supply or battery power supply. Wired power supply limits mobility and battery power supply has a short battery life. Furthermore, the power supply module and signal acquisition module lack a closed-loop linkage mechanism, resulting in insufficient voltage supply stability. At the same time, the sampling frequency adjustment of the signal acquisition module lacks dynamic adaptation capability, making it difficult to accurately capture transient change components in photovoltaic power signals, which affects the accuracy of subsequent feature extraction. (2) The harmonic analysis and protection design are not perfect. The harmonic source analysis relies on external servers for data processing and cannot achieve real-time qualitative judgment on terminal equipment. Moreover, the analysis logic is not optimized for the harmonic generation characteristics of photovoltaic power plants, resulting in poor source targeting. At the same time, the protection design only considers electromagnetic shielding or voltage stability and does not form a multi-dimensional collaborative protection mechanism, making it difficult to cope with the complex electromagnetic environment and temperature and humidity fluctuations at the photovoltaic site, which leads to a decrease in the stability of the device under harsh conditions. Summary of the Invention

[0005] To address the aforementioned issues, this invention proposes a portable distributed photovoltaic power quality detection method and system. Based on passive coupling, dynamic voltage regulation, and adaptive sampling mechanisms, it captures transient change components in photovoltaic power signals, extracts and analyzes these transient change components, and achieves accurate power quality detection. This solves the problems of limited power extraction methods, inaccurate transient signal capture, insufficient real-time and targeted harmonic source tracing, and poor equipment environmental adaptability in existing technologies.

[0006] According to some embodiments, the first aspect of the present invention provides a portable distributed photovoltaic power quality detection method, which adopts the following technical solution: A portable method for detecting the power quality of distributed photovoltaic power, comprising: Acquiring electrical signals from distributed photovoltaic lines based on passive coupling; The acquired electrical energy signal is subjected to adaptive continuous sampling to obtain a discrete digital signal of the electrical energy signal; Extract the multidimensional frequency domain feature parameters of the obtained discrete digital signal; Source analysis is performed on the extracted multidimensional frequency domain feature parameters to generate source analysis results; Based on the generated source analysis results and protection effectiveness calculation model, multi-dimensional collaborative security protection of distributed photovoltaic power is carried out. The obtained protection status information is fed back to the passive coupling acquisition stage to form a closed-loop control for the acquisition of power signals and complete the power quality detection of distributed photovoltaic power.

[0007] As a further technical limitation, the protective effectiveness calculation model is as follows: ;in, For protective effectiveness value, The permeability of free space, The relative permeability of the shielding material, The number of turns of the shielding coil. The cross-sectional area of ​​the shielding coil. The thickness of the shielding layer, To protect the response coefficient, For the duration of protection, To absorb the capacitance, For maximum withstand voltage, For shunt resistors, For series resistance, The angular frequency of the power grid. This is the phase offset angle.

[0008] As a further technical limitation, a preset source-tracing logic operation is performed on the extracted multi-dimensional frequency domain feature parameters. The result of the source-tracing logic operation is then compared with pre-stored threshold criteria for harmonic characteristics of photovoltaic power plants using a source-tracing discrimination model. This qualitative analysis locates the harmonic pollution source and generates source-tracing analysis results. The source-tracing discrimination model is... ;in, For source tracing, For the first The harmonic source affects the first Harmonic contribution of each monitoring point These are the weighting coefficients. For the first The phase angle of each harmonic source For the first Phase angle of each monitoring point For the number of harmonic sources, For the number of monitoring points, For the first The harmonic amplitude of each harmonic source For the first The equivalent resistance of a harmonic source For the first The conductivity at each monitoring point For the first The equivalent inductance of each monitoring point For the first The impedance value of each harmonic source, This is the standard impedance value. This is the impedance threshold.

[0009] As a further technical limitation, during the adaptive continuous sampling process, the sampling frequency is dynamically adjusted based on the real-time monitored signal voltage fluctuation value, signal peak voltage, and preset circuit parameters. The acquired analog power signal is then converted from analog to digital to obtain a discrete digital signal. The adjustment model for the sampling frequency is as follows: ;in, This is the actual sampling frequency. As the reference sampling frequency, This is the proportional adjustment coefficient. This represents the voltage fluctuation value. For reference voltage, For filtering capacitors, For feedback resistor, For voltage divider resistors, The peak voltage of the signal. Minimum detection voltage, The cutoff frequency, The number of sampling points. This represents the number of bits used in the analog-to-digital conversion.

[0010] As a further technical limitation, the calculation model for the power extraction voltage of the acquired electrical energy signal is as follows: ;in, For output voltage, The number of turns of the primary coil. The number of turns of the secondary coil. This is the line input voltage. The coupling angle between the primary and secondary coils. For the primary coil inductance, For the secondary coil inductance, This is the primary-side resonant capacitor. It is the secondary resonant capacitor. The equivalent resistance in series with the coil. For load current, The attenuation coefficient is... For power draw duration, The frequency of the damped oscillation. This is the initial phase angle.

[0011] According to some embodiments, a second aspect of the present invention provides a portable distributed photovoltaic power quality detection device for performing the portable distributed photovoltaic power quality detection method described in the first aspect, employing the following technical solution: A portable distributed photovoltaic power quality testing device, comprising: Passive coupling power harvesting module, used to acquire power signals from distributed photovoltaic lines; The transient waveform capture module is used to adaptively and continuously sample the acquired power signal to obtain a discrete digital signal of the power signal; The frequency domain feature extraction module is used to extract multi-dimensional frequency domain feature parameters of the obtained discrete digital signal; The harmonic source analysis module is used to perform source analysis on the extracted multi-dimensional frequency domain feature parameters and generate source analysis results. The security protection module is used to obtain critical status data through multi-dimensional collaborative security protection. The display and interaction module is used to process the source tracing analysis results and key status data, display them in real time through a local display interface, and adjust the detection parameters in conjunction with the received external input control commands.

[0012] According to some embodiments, the third aspect of the present invention provides a portable distributed photovoltaic power quality detection system, which adopts the following technical solution: A portable distributed photovoltaic power quality detection system includes: The acquisition module is configured to acquire the electrical signal of the distributed photovoltaic line based on passive coupling; The sampling module is configured to adaptively and continuously sample the acquired electrical energy signal to obtain a discrete digital signal of the electrical energy signal. The extraction module is configured to extract multidimensional frequency domain feature parameters of the obtained discrete digital signal; The analysis module is configured to perform source analysis on the extracted multidimensional frequency domain feature parameters and generate source analysis results. The detection module is configured to perform multi-dimensional collaborative safety protection of distributed photovoltaic systems based on the generated source analysis results and protection effectiveness calculation model, and to feed back the obtained protection status information to the passive coupling acquisition stage, thereby acquiring and shaping the power signal. According to some embodiments, the fourth aspect of the present invention provides a computer-readable storage medium, which adopts the following technical solution: A computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements the steps of the portable distributed photovoltaic power quality detection method as described in the first aspect of the present invention.

[0013] According to some embodiments, the fifth aspect of the present invention provides an electronic device, which adopts the following technical solution: An electronic device includes a memory, a processor, and a program stored in the memory and running on the processor, wherein the processor executes the program to implement the steps in the portable distributed photovoltaic power quality detection method as described in the first aspect of the present invention.

[0014] According to some embodiments, the sixth aspect of the present invention provides a computer program product, which adopts the following technical solution: A computer program product includes software code, wherein the program in the software code performs the steps of the portable distributed photovoltaic power quality detection method as described in the first aspect of the present invention.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention employs a passive coupling power extraction module and closed-loop linkage with various functional modules, overcoming the limitations of wired and battery power supply. Dynamic voltage regulation ensures power supply stability, and the adaptive sampling mechanism of the transient waveform capture module accurately captures transient change components in photovoltaic power signals, solving the problems of insufficient power extraction flexibility and inaccurate signal acquisition in traditional equipment. The integrated design of the frequency domain feature extraction module and harmonic source analysis module embeds feature extraction and source identification logic into the terminal device, enabling real-time qualitative analysis without relying on external servers. Furthermore, the analysis logic is optimized for the harmonic characteristics of photovoltaic power plants, improving the targeting of source identification. Simultaneously, the safety protection module effectively copes with complex environmental interference at photovoltaic sites through a multi-dimensional collaborative protection mechanism of electromagnetic shielding, temperature drift suppression, and voltage stabilization, ensuring the stability of the device under harsh conditions. Each module achieves efficient data interaction through a high-speed bus and multi-channel interface. Combined with the real-time data presentation and command reception functions of the display interaction module, it balances portability and ease of operation. The overall structure is compact and requires no complex wiring. It can achieve live installation and rapid on-site testing, fully meeting the high-precision power quality testing needs of distributed photovoltaic power stations in decentralized layouts and complex environments. Attached Figure Description

[0016] The accompanying drawings, which form part of this embodiment, are used to provide a further understanding of this embodiment. The illustrative embodiments and their descriptions are used to explain this embodiment and do not constitute an improper limitation of this embodiment.

[0017] Figure 1 This is a flowchart of the portable distributed photovoltaic power quality detection method in Embodiment 1 of the present invention; Figure 2 This is a structural block diagram of the portable distributed photovoltaic power quality detection device in Embodiment 2 of the present invention; Figure 3 This is a structural diagram of the portable distributed photovoltaic power quality detection system in Embodiment 3 of the present invention. Detailed Implementation

[0018] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0019] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0020] It should be noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the scope of exemplary embodiments according to the invention. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. Furthermore, it should be understood that when the terms "comprising" and / or "including" are used in this specification, they indicate the presence of features, steps, operations, devices, components, and / or combinations thereof.

[0021] In this invention, terms such as "upper," "lower," "left," "right," "front," "back," "vertical," "horizontal," "side," and "bottom" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. These terms are used only to facilitate the description of the structural relationships of the various components or elements of this invention and do not specifically refer to any component or element in this invention. They should not be construed as limiting the invention.

[0022] In this invention, terms such as "fixed connection," "connected," and "linked" should be interpreted broadly, indicating a fixed connection, an integral connection, or a detachable connection; a direct connection or an indirect connection through an intermediate medium. Those skilled in the art can determine the specific meaning of these terms in this invention based on the specific circumstances, and they should not be construed as limitations on the invention.

[0023] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0024] Example 1 Embodiment 1 of this invention introduces a portable method for detecting the power quality of distributed photovoltaic power.

[0025] like Figure 1 A portable distributed photovoltaic power quality testing method is shown, comprising: Acquiring electrical signals from distributed photovoltaic lines based on passive coupling; The acquired electrical energy signal is subjected to adaptive continuous sampling to obtain a discrete digital signal of the electrical energy signal; Extract the multidimensional frequency domain feature parameters of the obtained discrete digital signal; Source analysis is performed on the extracted multidimensional frequency domain feature parameters to generate source analysis results; Based on the generated source analysis results and protection effectiveness calculation model, multi-dimensional collaborative security protection of distributed photovoltaic power is carried out. The obtained protection status information is fed back to the passive coupling acquisition stage to form a closed-loop control for the acquisition of power signals and complete the power quality detection of distributed photovoltaic power.

[0026] As one or more implementation methods, the protective effectiveness calculation model is as follows: ;in, For protective effectiveness value, The permeability of free space, The relative permeability of the shielding material, The number of turns of the shielding coil. The cross-sectional area of ​​the shielding coil. The thickness of the shielding layer, To protect the response coefficient, For the duration of protection, To absorb the capacitance, For maximum withstand voltage, For shunt resistors, For series resistance, The angular frequency of the power grid. This is the phase offset angle.

[0027] As one or more implementation methods, a preset source tracing logic operation is performed on the extracted multi-dimensional frequency domain feature parameters. The result of the source tracing logic operation is then compared with pre-stored threshold criteria for harmonic characteristics of photovoltaic power plants using a source tracing discrimination model. This qualitative analysis identifies and locates the harmonic pollution source, generating a source tracing analysis result. The source tracing discrimination model is... ;in, For source tracing, For the first The harmonic source affects the first Harmonic contribution of each monitoring point These are the weighting coefficients. For the first The phase angle of each harmonic source For the first Phase angle of each monitoring point For the number of harmonic sources, For the number of monitoring points, For the first The harmonic amplitude of each harmonic source For the first The equivalent resistance of a harmonic source For the first The conductivity at each monitoring point For the first The equivalent inductance of each monitoring point For the first The impedance value of each harmonic source, This is the standard impedance value. This is the impedance threshold.

[0028] As one or more implementation methods, during the adaptive continuous sampling process, the sampling frequency is dynamically adjusted based on the real-time monitored signal voltage fluctuation value, signal peak voltage, and preset circuit parameters. The acquired analog power signal is then converted from analog to digital to obtain a discrete digital signal. The adjustment model for the sampling frequency is as follows: ;in, This is the actual sampling frequency. As the reference sampling frequency, This is the proportional adjustment coefficient. This represents the voltage fluctuation value. For reference voltage, For filtering capacitors, For feedback resistor, For voltage divider resistors, The peak voltage of the signal. Minimum detection voltage, The cutoff frequency, The number of sampling points. This represents the number of bits used in the analog-to-digital conversion.

[0029] As one or more implementation methods, the power extraction voltage calculation model for the acquired electrical energy signal is as follows: ;in, For output voltage, The number of turns of the primary coil. The number of turns of the secondary coil. This is the line input voltage. The coupling angle between the primary and secondary coils. For the primary coil inductance, For the secondary coil inductance, This is the primary-side resonant capacitor. It is the secondary resonant capacitor. The equivalent resistance in series with the coil. For load current, The attenuation coefficient is... For power draw duration, The frequency of the damped oscillation. This is the initial phase angle.

[0030] Example 2 Embodiment 2 of the present invention introduces a portable distributed photovoltaic power quality detection device, which is used to perform the portable distributed photovoltaic power quality detection method described in Embodiment 1.

[0031] like Figure 2 The portable distributed photovoltaic power quality testing device shown includes: Passive coupling power harvesting module, used to acquire power signals from distributed photovoltaic lines; The transient waveform capture module is used to adaptively and continuously sample the acquired power signal to obtain a discrete digital signal of the power signal; The frequency domain feature extraction module is used to extract multi-dimensional frequency domain feature parameters of the obtained discrete digital signal; The harmonic source analysis module is used to perform source analysis on the extracted multi-dimensional frequency domain feature parameters and generate source analysis results. The security protection module is used to obtain critical status data through multi-dimensional collaborative security protection. The display and interaction module is used to process the source tracing analysis results and key status data, display them in real time through a local display interface, and adjust the detection parameters in conjunction with the received external input control commands.

[0032] The passive coupling power supply module establishes a bidirectional data transmission link with the transient waveform capture module via a shielded cable. The signal output terminal of the transient waveform capture module is connected to the signal input terminal of the frequency domain feature extraction module via a high-speed serial bus. The analysis result output terminal of the frequency domain feature extraction module is communicatively connected to the data input terminal of the harmonic source analysis module. The control signal output terminal of the harmonic source analysis module is electrically connected to the control signal input terminal of the safety protection module. The status feedback terminal of the safety protection module forms a closed-loop connection with the feedback input terminal of the passive coupling power supply module. The display and interaction module connects to the transient waveform capture module and the frequency domain feature extraction module via multi-channel interfaces. The module and harmonic source analysis module perform bidirectional data interaction. Different modules are connected to an integrated backplane bus for power distribution and synchronization control. The passive coupling power extraction module obtains power from the photovoltaic line based on the principle of electromagnetic induction and adjusts the voltage amplitude. The transient waveform capture module continuously samples and stores the photovoltaic power signal. The frequency domain feature extraction module performs frequency domain transformation and characteristic parameter calculation on the sampled signal. The harmonic source analysis module performs source tracing logic operations and criterion comparison on the characteristic parameters. The safety protection module performs signal shielding and environmental adaptation through structural design and circuit control. The display and interaction module presents the analysis results and receives commands.

[0033] The passive coupling power extraction module is designed based on the principle of electromagnetic induction, using a toroidal iron core as the coupling core. The core material is silicon steel sheet with a lamination factor of 0.93. The primary coil has 800 turns, and the secondary coil has 400 turns. The coil wire is made of oxygen-free copper wire with a diameter of 0.2mm, and the DC resistance of the coil is controlled within 1.2Ω. The module has an internal resonant capacitor bank, with a primary resonant capacitor of 0.1μF and a secondary resonant capacitor of 0.2μF. By adjusting the capacitor parameters, the resonant frequency of the power extraction circuit is matched to the 50Hz power frequency of the photovoltaic line. The module's output voltage adjustment range is 5V-24V, with a voltage adjustment accuracy controlled within ±0.1V. The maximum output current is 2A, and the power extraction efficiency is not less than 85%. During implementation, the ring-shaped iron core is snap-fitted onto the outside of the photovoltaic line conductor, enabling power coupling without disconnecting the line. During power extraction, the coupling angle is dynamically adjusted through a coil coupling angle adjustment mechanism to maintain the coupling angle between 85° and 90°, ensuring power extraction stability. Simultaneously, the module transmits the adjusted power and feedback signal to the transient waveform capture module through a shielded cable, and receives the status feedback signal from the safety protection module, forming a closed-loop power extraction control. This meets the portability requirements of the entire device, which requires no external power supply and can be installed while energized.

[0034] The transient waveform capture module employs a 16-bit analog-to-digital converter chip, with an adjustable sampling rate of 1MSps-10MSps, a sampling resolution of 16 bits, an input signal range of ±10V, and an equivalent input noise voltage below 2μVrms. It features a built-in 2GB high-speed cache chip, achieving a data storage rate of 100MB / s, and can continuously store at least 10 minutes of sampled data. The module receives power and synchronization signals from the passive coupling power supply module via a shielded cable. It establishes a data transmission channel with the frequency domain feature extraction module through a high-speed serial bus (1Gbps transmission rate) and simultaneously achieves bidirectional data interaction with the display interaction module through a multi-channel interface. During implementation, the module controls the sampling period using a clock synchronization signal (100MHz clock frequency) to continuously and synchronously sample the voltage and current signals in the photovoltaic line. The sampling triggering method supports both level triggering and edge triggering modes, with the trigger threshold adjustable within the range of 0.1V-5V. During the sampling process, the analog signal is subjected to anti-aliasing filtering. The filter circuit has a cutoff frequency of 5kHz and an attenuation slope of 80dB / decade to ensure that the sampled signal is distortion-free. The sampled digital signal is then stored in a high-speed cache chip and transmitted to the frequency domain feature extraction module after being organized according to a preset data format. At the same time, it receives instructions from the display interaction module to adjust the sampling parameters, thereby achieving accurate capture and efficient transmission of transient waveforms.

[0035] The frequency domain feature extraction module is equipped with a 32-bit floating-point digital signal processor with a main frequency of 1GHz and a processing speed of 2000MIPS. It has a built-in dedicated frequency domain transformation hardware acceleration unit. The module receives digital signals transmitted by the transient waveform capture module through a high-speed serial bus. The data interface supports full-duplex communication with a transmission delay of less than 10μs. During implementation, the module first performs frame synchronization processing on the received discrete digital signals. The data length of each frame is set to 1024 points, and the frame synchronization error is controlled within one sampling point. Subsequently, frequency domain transformation processing is performed using an improved fast frequency domain transformation algorithm. The number of transformation points is adjustable from 1024 to 8192 points, the frequency domain resolution reaches 1Hz, and the transformation time does not exceed 1ms. Through multi-scale frequency domain decomposition technology, the signal is decomposed into sub-signals in three frequency ranges: 0-50Hz, 50Hz-1kHz, and 1kHz-5kHz, while maintaining the phase and amplitude characteristics of each sub-signal unchanged. The amplitude, frequency, phase, and harmonic order of each sub-signal are calculated, with an amplitude calculation accuracy of ±0.5%, a frequency measurement accuracy of ±0.01Hz, and a phase measurement accuracy of ±0.1°. The extracted feature parameters are processed in a 16-bit binary encoding format and transmitted via a communication interface to the harmonic source analysis module and the display interaction module, providing accurate feature data support for harmonic source analysis.

[0036] The harmonic source tracing analysis module employs a dual-core microprocessor with a main frequency of 800MHz, featuring a built-in 512KB high-speed cache and 8GB flash memory to store a preset harmonic source tracing criterion library and logical operation rules. The module receives feature parameters from the frequency domain feature extraction module via a data interface, and data verification uses the CRC32 algorithm to ensure parameter integrity and consistency. During implementation, the module first normalizes the feature parameters (not a preprocessing step, but only adjusting the data range), mapping the parameter range to 0-1. Based on the preset source tracing logic rules, multi-dimensional correlation calculations are performed on the feature parameters. The calculation process involves the fusion analysis of multiple parameters such as harmonic amplitude ratio, phase difference, and impedance matching degree, with a calculation latency of less than 50ms. The intermediate results obtained from the calculation are compared one by one with preset criterion thresholds (the criterion thresholds are preset to 5 groups according to the harmonic characteristics of photovoltaic power plants and can be modified through the display interaction module), with a comparison accuracy of 0.001. The distribution of harmonic contribution is determined by calculating the difference. The comparison results are then converted into a standard control signal (signal level 3.3 VTTL), which is transmitted to the safety protection module and display interaction module through the control interface. At the same time, the source tracing results are stored in flash memory in CSV file format, which supports subsequent data export and analysis, enabling qualitative identification of local harmonic pollution sources at the terminal.

[0037] The safety protection module integrates four functional units: electromagnetic shielding, temperature drift suppression, voltage stabilization, and status feedback. The entire module is encapsulated in a 2mm thick metal shell with a grounding resistance of less than 4Ω. The electromagnetic shielding unit employs a double-layer stainless steel shielding structure. The inner shielding mesh has a 0.5mm aperture, and the outer shielding mesh has a 1mm aperture. A 2mm thick epoxy resin insulating layer separates the two shielding layers, achieving a shielding effectiveness of over 80dB (for the 10kHz-1GHz frequency band). The temperature drift suppression unit uses a platinum resistance temperature sensor (measuring range -40℃-85℃, accuracy ±0.2℃). It converts the temperature signal to a digital signal via analog-to-digital conversion. The compensation circuit uses a proportional-integral (PI) control circuit composed of operational amplifiers to adjust the operating voltage and bias current of core components (such as the analog-to-digital converter chip and processor) in real time, achieving a temperature drift suppression accuracy of ±0.05% / ℃. The voltage stabilization unit uses a linear voltage regulator chip with an output voltage ripple of less than 10mVpp. The overvoltage protection threshold is set to 28V, and the overvoltage response time is less than 10μs. Voltage fluctuations are suppressed through a filter capacitor (1000μF) and a bleeder resistor (1kΩ). The status feedback unit uses a Hall sensor and optocoupler isolation circuit to monitor the operating status of each protection unit in real time. The monitored parameters include shielding grounding status, temperature compensation value, and output voltage value. The monitoring data is converted into digital signals and transmitted to the passive coupling power supply module through the feedback interface, forming a protection closed loop to ensure stable operation of the device in harsh environments.

[0038] The display and interaction module uses a 5-inch TFT LCD screen with a resolution of 800×480 pixels, a brightness of 500 cd / m², a contrast ratio of 1000:1, and a viewing angle of 170° (full viewing angle). The screen has a built-in touch panel with a touch response time of less than 50ms and supports single-point touch operation. The module connects to the transient waveform capture module, frequency domain feature extraction module, and harmonic source analysis module via multiple interfaces (including UART, SPI, and I2C). The interface communication rates are 115200bps for UART, 10Mbps for SPI, and 400kbps for I2C. During implementation, the module receives data from each functional module, including sampled waveform data, frequency domain feature parameters, harmonic source results, and module operating status. The data is displayed according to a preset interface layout, with a waveform display update rate of 10 frames / second and numerical display accuracy retaining two decimal places. Meanwhile, the module supports user input of control commands via the touch panel, including commands for adjusting sampling parameters, selecting traceability criteria, storing and exporting data, and starting and stopping the device. Command encoding uses an 8-bit binary format, and parity checking ensures reliability during transmission. The module has a built-in 3.7V lithium battery with a capacity of 2000mAh, supporting continuous operation for over 8 hours. It can also be powered via a passive coupling power module, enabling dual power supply mode switching to ensure continuous and stable display and interactive functions, facilitating on-site operation and data viewing for users.

[0039] The power extraction voltage calculation model for the passive coupling power extraction module in this embodiment is as follows: in, For output voltage, The number of turns of the primary coil. The number of turns of the secondary coil. This is the line input voltage. The coupling angle between the primary and secondary coils. For the primary coil inductance, For the secondary coil inductance, This is the primary-side resonant capacitor. It is the secondary resonant capacitor. The equivalent resistance in series with the coil. For load current, The attenuation coefficient is... For power draw duration, The frequency of the damped oscillation. This is the initial phase angle.

[0040] Specifically, the output voltage regulation process of the passive coupling power extraction module achieves precise voltage output through multi-parameter collaborative calculation. During implementation, the module first acquires the input voltage of the photovoltaic line. Combined with the turns ratio of the primary and secondary coils, the turns ratio is fixed at 2:1. The coupling angle is stabilized within the 85°-90° range through a dynamic adjustment mechanism to ensure maximum electromagnetic induction efficiency. Simultaneously, the inductance and resonant capacitance parameters of the primary and secondary coils are monitored. The inductance values ​​are stabilized at 10mH and 5mH respectively, and the capacitance values ​​are fixed at 0.1μF and 0.2μF. The combined calculation of these parameters compensates for the influence of parasitic parameters in the coils. The equivalent series resistance of the coils is measured and calibrated to be 1.2Ω. The load current dynamically changes according to the operating status of each module, ranging from 0.1A to 2A, with an attenuation coefficient set to 0.05. The power extraction duration is updated synchronously according to the sampling period. The damped oscillation angular frequency and initial phase angle are dynamically calibrated by real-time detection of the line signal characteristics. This model integrates the above parameters to achieve precise adjustment of the output voltage within the range of 5V-24V, with voltage adjustment accuracy controlled within ±0.1V. This effectively offsets the impact of load changes and line fluctuations on power supply stability, providing a continuous and stable power supply for all modules of the entire device and ensuring the accuracy of subsequent signal acquisition, analysis, and other processes.

[0041] In this embodiment, the sampling frequency adjustment model of the transient waveform acquisition module is as follows: in, This is the actual sampling frequency. As the reference sampling frequency, This is the proportional adjustment coefficient. This represents the voltage fluctuation value. For reference voltage, For filtering capacitors, For feedback resistor, For voltage divider resistors, The peak voltage of the signal. Minimum detection voltage, The cutoff frequency, The number of sampling points. This represents the number of bits used in the analog-to-digital conversion.

[0042] Specifically, the transient waveform capture module's dynamic sampling frequency adaptation function achieves precise control of the sampling rate through multi-dimensional parameter fusion calculation. During implementation, the reference sampling frequency is set to 5 MSps. The module monitors the photovoltaic line voltage fluctuation value in real time, with the reference voltage fixed at 220V and the proportional adjustment coefficient set to 0.8. The influence weight of voltage change on the sampling frequency is calculated by the ratio of voltage fluctuation to reference voltage. Simultaneously, parameters of the filter capacitor, feedback resistor, and voltage divider resistor are acquired. The capacitor value is 0.01μF, and the resistance values ​​of the feedback resistor and voltage divider resistor are 10kΩ and 2kΩ, respectively. The combined calculation of these resistor and capacitor parameters optimizes the filtering effect of the sampled signal. The peak voltage and minimum detection voltage are acquired by a front-end sensor. The peak voltage monitoring range is 0-380V, the minimum detection voltage is set to 0.1V, the cutoff frequency is fixed at 5kHz, and the number of sampling points is dynamically adjusted according to the frame data length, ranging from 1024 to 8192 points. The analog-to-digital conversion bit depth is 16 bits. The model calculates the actual sampling frequency by combining the above parameters. The sampling frequency adjustment range is 1MSps-10MSps, which ensures that the sampling frequency always matches the signal characteristics under different operating conditions such as voltage fluctuations and signal amplitude changes. This enables distortion-free capture of transient signals and provides high-quality raw data for subsequent frequency domain feature extraction.

[0043] In this embodiment, the feature parameter calculation model for the frequency domain feature extraction module is as follows: in, For frequency domain eigenvalues, For the first The time-domain signal value of each sampling point This represents the total number of sampling points. For frequency point number, The standard deviation of the signal. The standard deviation of noise. The regularization coefficient is . For the first The angular frequency corresponding to each sampling point The center angular frequency, For frequency bandwidth, This represents the mean of the time-domain signal.

[0044] Specifically, the parameter calculation process of the frequency domain feature extraction module achieves accurate extraction of frequency domain features through multi-parameter collaborative analysis. During implementation, the module first acquires the time-domain sampled signal. The total number of sampling points is set to 1024-8192 points according to the frame data length, and the frequency point numbers are arranged sequentially according to the frequency domain resolution, which reaches 1Hz. Simultaneously, a noise suppression algorithm separates the signal and noise components, calculating the standard deviations of both. The signal standard deviation dynamically changes according to the sampled signal amplitude, while the noise standard deviation is calibrated to 0.02 based on actual measurements. The regularization coefficient is set to 0.01 to avoid overfitting during the calculation process. The angular frequencies corresponding to each sampling point are sequentially increased from the power frequency of 50Hz, with the center angular frequency fixed at 50Hz and the frequency bandwidth set to 5kHz. The mean of the time-domain signal is calculated in real time using a sliding window algorithm with a window length of 128 points. This model performs comprehensive calculations on the above parameters to extract core characteristic parameters of the signal, such as amplitude, frequency, phase, and harmonic order. The amplitude calculation accuracy is ±0.5%, the frequency measurement accuracy is ±0.01Hz, and the phase measurement accuracy is ±0.1°. It effectively preserves key information in the frequency domain of the signal, providing accurate and comprehensive characteristic data support for harmonic source tracing analysis.

[0045] In this embodiment, the source discrimination model of the harmonic source analysis module is: in, For source tracing, For the first The harmonic source affects the first Harmonic contribution of each monitoring point These are the weighting coefficients. For the first The phase angle of each harmonic source For the first Phase angle of each monitoring point For the number of harmonic sources, For the number of monitoring points, For the first The harmonic amplitude of each harmonic source For the first The equivalent resistance of a harmonic source For the first The conductivity at each monitoring point For the first The equivalent inductance of each monitoring point For the first The impedance value of each harmonic source, This is the standard impedance value. This is the impedance threshold.

[0046] Specifically, the qualitative identification process of the harmonic source tracing analysis module achieves precise location of harmonic pollution sources through multi-dimensional parameter fusion calculations. During implementation, the module first receives feature parameters transmitted from the frequency domain feature extraction module, establishing a correspondence between harmonic sources and monitoring points. The number of harmonic sources is supported up to 16 based on the photovoltaic power station module layout, while the number of monitoring points is fixed at 8. The module calculates the harmonic contribution of each harmonic source to different monitoring points, combined with a preset weighting coefficient matrix. The weighting coefficients are preset to 5 sets of adjustable parameters based on the photovoltaic module type and installation location. Simultaneously, parameters such as phase angle, equivalent resistance, conductance, and equivalent inductance are collected for each harmonic source and monitoring point. The phase angle measurement range is 0°-360°, the equivalent resistance and inductance are calibrated through actual measurement, and the conductance value is dynamically calculated based on the line load. The standard impedance value is set to 50Ω, and the impedance threshold is set to 10Ω. The impedance characteristics of each harmonic source are analyzed through the combined calculation of these parameters. The model calculates the source tracing discrimination value by combining the above parameters. The discrimination value threshold is set to 0.8. When the calculation result exceeds the threshold, the corresponding harmonic source is determined to be the main pollution source. The calculation delay is less than 50ms, realizing fast and accurate harmonic source tracing on the terminal without relying on external servers, thus improving detection efficiency and on-site applicability.

[0047] The protection effectiveness calculation model of the security protection module in this embodiment is as follows: in, For protective effectiveness value, The permeability of free space, The relative permeability of the shielding material, The number of turns of the shielding coil. The cross-sectional area of ​​the shielding coil. The thickness of the shielding layer, To protect the response coefficient, For the duration of protection, To absorb the capacitance, For maximum withstand voltage, For shunt resistors, For series resistance, The angular frequency of the power grid. This is the phase offset angle.

[0048] Specifically, the comprehensive protection effectiveness assessment and control of the safety protection module achieves all-round, high-precision protection through multi-parameter collaborative calculation. During implementation, the module first collects the magnetic permeability parameters of the shielding material. The vacuum magnetic permeability is set according to physical constants, the relative magnetic permeability of the shielding material is measured to be 1000, the number of turns of the shielding coil is fixed at 100 turns, the coil cross-sectional area is 10 cm², and the shielding layer thickness is 2 mm. These parameters are used to calculate the basic electromagnetic shielding effectiveness. The protection response coefficient is set to 0.1, the protection action time is dynamically updated according to the real-time monitoring cycle, the absorption capacitor capacity is 1000 μF, the maximum withstand voltage is set to 28 V, and the shunt resistor and series resistor values ​​are 1 kΩ and 100 Ω, respectively. These parameters are used to optimize voltage stability and overvoltage protection effects. The grid angular frequency is fixed at 314 rad / s, and the phase offset angle is dynamically calibrated by real-time monitoring of the line voltage phase. The model comprehensively calculates the above parameters to evaluate the overall effectiveness of the protection module. The electromagnetic shielding effectiveness reaches over 80dB, the temperature drift suppression accuracy is ±0.05% / ℃, the voltage ripple is less than 10mVpp, and the overvoltage response time is less than 10μs. It achieves coordinated protection against multiple risks such as electromagnetic interference, temperature changes, and voltage fluctuations, ensuring stable operation of the device in the temperature range of -40℃ to 85℃ and the electromagnetic interference frequency band of 10kHz to 1GHz.

[0049] In this embodiment, the frequency domain feature extraction module includes a signal conversion unit, a frequency domain decomposition unit, a feature operation unit, and a parameter output unit. The signal conversion unit receives the time-domain electrical signal transmitted by the transient waveform capture module and converts the continuous analog signal into a discrete digital signal through an analog-to-digital conversion circuit. During the conversion process, the conversion rate and data transmission timing are controlled by a clock synchronization signal. The frequency domain decomposition unit performs multi-scale frequency domain decomposition processing on the discrete digital signal. The signal is decomposed into sub-signals of different frequency ranges according to a preset frequency band division rule, while maintaining the phase information and amplitude characteristics of each sub-signal during the decomposition process. The feature operation unit calculates amplitude, frequency, and phase-related parameters for the sub-signals of different frequency ranges and performs combination operations and feature extraction through a logic operation circuit. The parameter output unit encodes the extracted feature parameters according to a preset data format and transmits them to the harmonic source analysis module and the display interaction module through an interface circuit.

[0050] Specifically, the frequency domain feature extraction module comprises four units. The signal conversion unit receives the analog electrical signal transmitted from the transient waveform capture module, employs a 16-bit analog-to-digital converter chip with an adjustable conversion rate of 1MSps-10MSps, an input signal range of ±10V, and an equivalent input noise voltage below 2μVrms. The conversion timing is controlled by a clock synchronization signal (100MHz), accurately converting the continuous analog signal into a discrete digital signal while maintaining undistorted signal amplitude and phase information during the conversion process. The frequency domain decomposition unit uses an improved fast frequency domain transform algorithm with an adjustable number of transformation points from 1024 to 8192. It decomposes the discrete digital signal into sub-signals in three frequency ranges: 0-50Hz, 50Hz-1kHz, and 1kHz-5kHz, according to preset rules. The decomposition delay is less than 1ms, ensuring that the frequency characteristics of each sub-signal are consistent with the original signal. The feature calculation unit uses dedicated hardware acceleration circuitry to calculate parameters such as amplitude, frequency, phase, and harmonic order for sub-signals in each frequency range. The amplitude calculation accuracy is ±0.5%, the frequency measurement accuracy is ±0.01Hz, and the phase measurement accuracy is ±0.1°. Core features are extracted through multi-parameter combination calculations, with no data loss during the process. The parameter output unit processes the feature parameters using a 16-bit binary encoding format and transmits them to the harmonic source analysis module and display interaction module via a high-speed 1Gbps interface. The data transmission error rate is less than 10%. -6 This ensures the efficient and accurate transmission of feature data, providing comprehensive and precise basic data support for subsequent harmonic source tracing analysis and guaranteeing the reliability of the entire detection process.

[0051] In this embodiment, the harmonic source tracing analysis module includes a feature receiving unit, a logic operation unit, a criterion comparison unit, and a result output unit. The feature receiving unit receives feature parameters transmitted by the frequency domain feature extraction module through a communication interface, performs data verification and format conversion on the parameters to ensure parameter integrity and consistency. The logic operation unit performs multi-dimensional calculations on the feature parameters based on preset source tracing logic rules, and performs correlation calculations between different parameters and generates intermediate results through combinational logic circuits. The criterion comparison unit compares the intermediate calculation results with preset source tracing criterion thresholds one by one, and calculates the difference between the results and the criteria and judges compliance through a comparison circuit. The result output unit converts the comparison results according to a preset signal format, transmits them to the security protection module and the display interaction module through a control interface, and stores the comparison results in the local storage unit.

[0052] Specifically, the harmonic source analysis module comprises four units. The feature receiving unit receives feature parameters transmitted from the frequency domain feature extraction module via a CRC32 checksum algorithm. The interface communication rate is 100Mbps, and the data verification response time is less than 5μs. It performs format conversion and integrity verification on the parameters, eliminating invalid data to ensure the consistency and reliability of the input parameters. The logic operation unit is equipped with a dual-core microprocessor (800MHz). Based on preset multi-dimensional correlation operation rules, it performs fusion analysis on the feature parameters, including harmonic amplitude ratio, phase difference, and impedance matching degree. The operation cache capacity is 512KB, and the operation latency is less than 50ms. Intermediate results are generated through multi-parameter collaborative operation, and the operation process does not rely on external devices. The criterion comparison unit has five preset criterion thresholds specific to the characteristics of photovoltaic power plants, with a comparison accuracy of 0.001. It calculates the difference between the intermediate operation results and the criterion thresholds one by one, and filters out key data through conformity judgment. The comparison process is executed in priority order to ensure rigorous judgment logic. The output unit converts the comparison results into 3.3VTTL standard control signals, which are transmitted to the safety protection module and display interaction module through the control interface. At the same time, the source tracing results are stored in CSV format in 8GB flash memory at a storage rate of 10MB / s. This supports local data retrieval and subsequent export, enabling local qualitative identification of harmonic pollution sources at the terminal, improving detection efficiency and on-site applicability.

[0053] In this embodiment, the safety protection module includes an electromagnetic shielding unit, a temperature drift suppression unit, a voltage stabilization unit, and a status feedback unit. The electromagnetic shielding unit encloses the internal circuitry with a double-layer metal shielding structure, with an insulating dielectric layer between the shielding layers. Electromagnetic interference signals are guided to the ground through grounding. The temperature drift suppression unit collects ambient temperature signals through a temperature sensing element, converts the temperature signals into electrical signals, and transmits them to a compensation circuit. The compensation circuit adjusts the operating parameters of the core components in real time according to temperature changes. The voltage stabilization unit suppresses input voltage fluctuations through a voltage regulator chip and a filter circuit, maintains a constant output voltage through a feedback adjustment mechanism, and discharges abnormal high voltage through an overvoltage protection circuit. The status feedback unit monitors the operating status of different protection units in real time, converts the monitoring signals into status data, and transmits them to the passive coupling power supply module, forming a closed-loop feedback of protection status.

[0054] Specifically, the safety protection module comprises four units. The electromagnetic shielding unit adopts a double-phase stainless steel shielding structure with an inner shielding mesh aperture of 0.5mm and an outer shielding mesh aperture of 1mm. A 2mm thick epoxy resin insulating dielectric layer is placed between the two layers. The grounding resistance of the shielding shell is less than 4Ω, achieving a shielding effectiveness of over 80dB against electromagnetic interference in the 10kHz-1GHz frequency band. Through structural design, it blocks external electromagnetic signals from interfering with the internal circuitry. The temperature drift suppression unit uses a platinum resistance temperature sensor (measuring range -40℃-85℃, accuracy ±0.2℃). After converting the temperature signal into an electrical signal, it transmits it to the proportional-integral adjustment compensation circuit. The compensation circuit's response time is less than 20μs. Based on the temperature change (adjustment step of 0.01V per℃), it adjusts the operating parameters of the core components in real time, achieving a temperature drift suppression accuracy of ±0.05% / ℃. The voltage stabilization unit uses a linear voltage regulator chip, with an output voltage ripple of less than 10mVpp. The overvoltage protection threshold is set to 28V, and the overvoltage response time is less than 10μs. Voltage fluctuations are suppressed through a 1000μF filter capacitor and a 1kΩ bleeder resistor. Simultaneously, a feedback regulation mechanism maintains a constant output voltage, ensuring the power supply stability of each module. The status feedback unit uses a Hall sensor and optocoupler isolation circuit to monitor parameters such as shielding grounding status, temperature compensation value, and output voltage value in real time. The monitoring sampling period is 10ms. After converting the monitoring signal into digital status data, it is transmitted to the passive coupling power supply module through the feedback interface, forming a closed-loop protection control to ensure continuous and stable operation of the device in complex environments.

[0055] The operation process of a portable distributed photovoltaic power quality detection device in this embodiment is as follows: Power is induced from the distributed photovoltaic line via a passive coupling power extraction module; the acquired power is calibrated and its stability is controlled by a voltage regulation circuit; the regulated power is then transmitted to different functional modules via shielded cables; the high-speed sampling circuit of the transient waveform acquisition module continuously acquires the power signal from the photovoltaic line, with the sampling period synchronously controlled by a clock signal during the acquisition process; the acquired analog signal is stored in a buffer unit; the analog signal in the buffer unit is discretized by a frequency domain feature extraction module, using… The frequency domain transformation circuit decomposes the discrete signal into frequency components and extracts characteristic parameters of different frequency components. The harmonic source analysis module performs logical operations on the extracted characteristic parameters and performs qualitative analysis of harmonic pollution sources based on preset source tracing criteria, generating source tracing analysis results. The safety protection module monitors the working status of each module in real time and takes shielding, compensation, and voltage stabilization measures for electromagnetic interference, temperature changes, and voltage fluctuations, respectively. The display interaction module converts the source tracing analysis results and the working status data of different modules into different formats and presents the data on the display panel. At the same time, it receives external input control commands and transmits them to the corresponding modules.

[0056] This embodiment employs a passive coupling power extraction module, directly acquiring electrical energy from the photovoltaic line based on the principle of electromagnetic induction. Combined with a closed-loop feedback mechanism in the safety protection module, it achieves dynamic voltage amplitude adjustment, completely eliminating the site limitations of traditional wired power supply and the short battery life of battery power. Simultaneously, a high-efficiency data transmission link is established between modules via shielded cables and a high-speed serial bus, ensuring signal transmission stability and solving the problems of insufficient power extraction flexibility and poor module coordination in traditional equipment. The transient waveform capture module's continuous sampling and waveform storage functions, combined with the precise parameter calculation of the frequency domain feature extraction module, achieve efficient capture and feature analysis of photovoltaic power transient signals, overcoming the shortcomings of inaccurate transient signal capture in existing equipment. The harmonic source analysis module, through built-in logic operations and criterion comparison, can complete real-time qualitative source tracing without relying on an external server, improving detection targeting and efficiency.

[0057] The device's safety protection module integrates multi-dimensional protection functions such as electromagnetic shielding, temperature drift suppression, and voltage stabilization through a combination of structural design and circuit regulation. This effectively addresses the complex electromagnetic environment and temperature and humidity fluctuations at photovoltaic sites, solving the problems of traditional single-dimensional protection designs and poor environmental adaptability, ensuring stable operation of the device under harsh conditions. The display and interaction module's two-way data interaction function enables real-time presentation of test results and rapid response to external commands, balancing ease of operation and intuitive data. The entire device uses an integrated backplane bus for power distribution and synchronous control. Its compact structure supports live installation without complex wiring, perfectly adapting to the distributed layout of distributed photovoltaic power stations. It comprehensively overcomes the shortcomings of traditional equipment, such as large size, cumbersome installation, and weak adaptability, providing an efficient, accurate, and convenient solution for photovoltaic power quality testing.

[0058] Example 3 Embodiment 3 of the present invention introduces a portable distributed photovoltaic power quality detection system.

[0059] like Figure 3 The portable distributed photovoltaic power quality monitoring system shown includes: The acquisition module is configured to acquire the electrical signal of the distributed photovoltaic line based on passive coupling; The sampling module is configured to adaptively and continuously sample the acquired electrical energy signal to obtain a discrete digital signal of the electrical energy signal. The extraction module is configured to extract multidimensional frequency domain feature parameters of the obtained discrete digital signal; The analysis module is configured to perform source analysis on the extracted multidimensional frequency domain feature parameters and generate source analysis results. The detection module is configured to perform multi-dimensional collaborative safety protection of distributed photovoltaics based on the generated source analysis results and protection effectiveness calculation model, feed back the obtained protection status information to the passive coupling acquisition stage, form a closed-loop control for the acquisition of power signals, and complete the power quality detection of distributed photovoltaics.

[0060] The detailed steps are the same as those provided in Example 1 for portable distributed photovoltaic power quality testing, and will not be repeated here.

[0061] Example 4 Embodiment 4 of the present invention provides a computer-readable storage medium.

[0062] A computer-readable storage medium having a program stored thereon, which, when executed by a processor, implements the steps of the portable distributed photovoltaic power quality detection method as described in Embodiment 1 of the present invention.

[0063] The detailed steps are the same as those provided in Example 1 for portable distributed photovoltaic power quality testing, and will not be repeated here.

[0064] Example 5 Embodiment 5 of the present invention provides an electronic device.

[0065] An electronic device includes a memory, a processor, and a program stored in the memory and running on the processor. When the processor executes the program, it implements the steps in the portable distributed photovoltaic power quality detection method as described in Embodiment 1 of the present invention.

[0066] The detailed steps are the same as those provided in Example 1 for portable distributed photovoltaic power quality testing, and will not be repeated here.

[0067] Example 6 Embodiment 6 of the present invention provides a computer program product.

[0068] A computer program product includes software code, wherein the program in the software code performs the steps of the portable distributed photovoltaic power quality detection method as described in Embodiment 1 of the present invention.

[0069] The detailed steps are the same as those provided in Example 1 for portable distributed photovoltaic power quality testing, and will not be repeated here.

[0070] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention 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. The solutions in the embodiments of the present invention can be implemented using various computer languages, such as the object-oriented programming language Java and the interpreted scripting language JavaScript.

[0071] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. 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 and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0072] 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.

[0073] 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.

[0074] Although preferred embodiments of the invention have been described, 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 both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0075] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

[0076] The above description is merely a preferred embodiment of this practice and is not intended to limit the scope of this practice. Various modifications and variations can be made to this practice by those skilled in the art. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of this practice should be included within the protection scope of this practice.

Claims

1. A portable method for detecting the power quality of distributed photovoltaic power, characterized in that, include: Acquiring electrical signals from distributed photovoltaic lines based on passive coupling; The acquired electrical energy signal is subjected to adaptive continuous sampling to obtain a discrete digital signal of the electrical energy signal; Extract the multidimensional frequency domain feature parameters of the obtained discrete digital signal; Source analysis is performed on the extracted multidimensional frequency domain feature parameters to generate source analysis results; Based on the generated source analysis results and protection effectiveness calculation model, multi-dimensional collaborative security protection of distributed photovoltaic power is carried out. The obtained protection status information is fed back to the passive coupling acquisition stage to form a closed-loop control for the acquisition of power signals and complete the power quality detection of distributed photovoltaic power.

2. The portable distributed photovoltaic power quality detection method as described in claim 1, characterized in that, The protective effectiveness calculation model is as follows: ;in, For protective effectiveness value, The permeability of free space, The relative permeability of the shielding material, The number of turns of the shielding coil. The cross-sectional area of ​​the shielding coil. The thickness of the shielding layer, To protect the response coefficient, For the duration of protection, To absorb the capacitance, For maximum withstand voltage, For shunt resistors, For series resistance, The angular frequency of the power grid. This is the phase offset angle.

3. The portable distributed photovoltaic power quality detection method as described in claim 1, characterized in that, The extracted multi-dimensional frequency domain feature parameters are subjected to a preset source tracing logic operation. The result of this operation is then compared with pre-stored threshold criteria for harmonic characteristics of photovoltaic power plants using a source tracing discrimination model. This qualitative analysis identifies and locates the harmonic pollution source, generating a source tracing analysis result. The source tracing discrimination model is... ;in, For source tracing, For the first The harmonic source affects the first Harmonic contribution of each monitoring point These are the weighting coefficients. For the first The phase angle of each harmonic source For the first Phase angle of each monitoring point For the number of harmonic sources, For the number of monitoring points, For the first The harmonic amplitude of each harmonic source For the first The equivalent resistance of a harmonic source For the first The conductivity at each monitoring point For the first The equivalent inductance of each monitoring point For the first The impedance value of each harmonic source, This is the standard impedance value. This is the impedance threshold.

4. The portable distributed photovoltaic power quality detection method as described in claim 1, characterized in that, During the adaptive continuous sampling process, the sampling frequency is dynamically adjusted based on the real-time monitored signal voltage fluctuations, peak signal voltage, and preset circuit parameters. The acquired analog power signal is then converted from analog to digital to obtain a discrete digital signal. The sampling frequency adjustment model is as follows: ;in, This is the actual sampling frequency. As the reference sampling frequency, This is the proportional adjustment coefficient. This represents the voltage fluctuation value. For reference voltage, For filtering capacitors, For feedback resistor, For voltage divider resistors, The peak voltage of the signal. Minimum detection voltage, The cutoff frequency, The number of sampling points. This represents the number of bits used in the analog-to-digital conversion.

5. The portable distributed photovoltaic power quality detection method as described in claim 1, characterized in that, The calculation model for the voltage of the acquired electrical energy signal is as follows: ;in, For output voltage, The number of turns of the primary coil. The number of turns of the secondary coil. This is the line input voltage. The coupling angle between the primary and secondary coils. For the primary coil inductance, For the secondary coil inductance, This is the primary-side resonant capacitor. It is the secondary resonant capacitor. The equivalent resistance in series with the coil. For load current, The attenuation coefficient is... For power draw duration, The frequency of the damped oscillation. This is the initial phase angle.

6. A portable distributed photovoltaic power quality testing device, used to perform the portable distributed photovoltaic power quality testing method as described in any one of claims 1-5, characterized in that, include: Passive coupling power harvesting module, used to acquire power signals from distributed photovoltaic lines; The transient waveform capture module is used to adaptively and continuously sample the acquired power signal to obtain a discrete digital signal of the power signal; The frequency domain feature extraction module is used to extract multi-dimensional frequency domain feature parameters of the obtained discrete digital signal; The harmonic source analysis module is used to perform source analysis on the extracted multi-dimensional frequency domain feature parameters and generate source analysis results. The security protection module is used to obtain critical status data through multi-dimensional collaborative security protection. The display and interaction module is used to process the source tracing analysis results and key status data, display them in real time through a local display interface, and adjust the detection parameters in conjunction with the received external input control commands.

7. A portable distributed photovoltaic power quality detection system, characterized in that, include: The acquisition module is configured to acquire the electrical signal of the distributed photovoltaic line based on passive coupling; The sampling module is configured to adaptively and continuously sample the acquired electrical energy signal to obtain a discrete digital signal of the electrical energy signal. The extraction module is configured to extract multidimensional frequency domain feature parameters of the obtained discrete digital signal; The analysis module is configured to perform source analysis on the extracted multidimensional frequency domain feature parameters and generate source analysis results. The detection module is configured to perform multi-dimensional collaborative safety protection of distributed photovoltaics based on the generated source analysis results and protection effectiveness calculation model, feed back the obtained protection status information to the passive coupling acquisition stage, form a closed-loop control for the acquisition of power signals, and complete the power quality detection of distributed photovoltaics.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the steps of the portable distributed photovoltaic power quality detection method as described in any one of claims 1-5.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the program, it implements the steps of the portable distributed photovoltaic power quality detection method as described in any one of claims 1-5.

10. A computer program product, comprising software code, characterized in that, The program in the software code performs the steps of the portable distributed photovoltaic power quality detection method as described in any one of claims 1-5.

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