A power distribution network measurement system

Abstract

The application discloses a power distribution network measurement system, and relates to the technical field of power distribution network monitoring and measurement. The system comprises a multi-source heterogeneous data acquisition module, a high-precision synchronous clock module, a data processing and edge computing module, a communication and interaction module, and a local storage and management module. The data acquisition module synchronously acquires electrical quantity, topology state, environmental parameter and spatial position data; the synchronous clock module provides a unified time reference for each module; the data processing module pre-processes, quality-evaluates and self-adaptively corrects the measurement data, and extracts characteristic quantities required for digital twin modeling; and the communication module uploads the data to a digital twin platform and receives measurement strategy adjustment instructions issued by the platform. The application provides high-precision and high-synchronization real-time data support for digital twin-based power distribution network planning dynamic evaluation, and realizes closed-loop cooperation between the measurement system and the digital twin platform.

Description

Technical Field

[0001] This invention relates to the field of power distribution network monitoring and measurement technology, specifically a power distribution network measurement system. Background Technology

[0002] With the large-scale integration of distributed renewable energy and diverse loads, the distribution network structure is becoming increasingly complex and the number of devices is growing. Traditional distribution networks are showing signs of insufficient transparency and digitalization. Distribution network planning and decision-making have long lacked dynamic evaluation mechanisms, and the formulation of planning schemes has relied heavily on static parameters and offline simulations, making it difficult to adapt to real-time changes in the operating status of the distribution network.

[0003] In recent years, digital twin technology has provided a new technical approach for the dynamic evaluation and optimization of distribution network planning. By constructing a virtual model that maps to the physical distribution network with high fidelity, digital twins can achieve online simulation, dynamic evaluation, and iterative optimization of planning schemes. However, the accuracy and real-time performance of digital twin models are highly dependent on the quality of the underlying measurement data—including the accuracy, synchronization, completeness, and timeliness of the data. Existing distribution network measurement systems mainly suffer from the following shortcomings:

[0004] First, the data acquisition dimensions are insufficient. Traditional measurement systems mainly collect single electrical quantities (such as current and voltage), lacking the ability to comprehensively perceive the distribution network topology, equipment operating environment parameters (such as temperature, humidity, vibration, etc.), and spatial location information, making it difficult to meet the needs of digital twin modeling for multi-source heterogeneous data.

[0005] Second, data synchronization is poor. Distribution networks are widely distributed, and existing measurement systems often use independent clock sources, resulting in inconsistent time bases between different measurement points. The complex environment of distribution networks, limited fiber optic coverage, and the existence of areas with unstable GPS / BeiDou signals further exacerbate the time synchronization problem when deploying high-precision synchronous measurement systems on a large scale.

[0006] Third, there is a lack of real-time interaction mechanisms with digital twin platforms. Most existing measurement systems are one-way data uploaders and cannot receive feedback instructions from digital twin platforms to dynamically adjust measurement strategies (such as adjusting sampling frequency, switching measurement focus areas, etc.), making it difficult to support closed-loop dynamic evaluation of planning schemes.

[0007] Fourth, the measurement data quality lacks online evaluation and adaptive correction capabilities. Factors such as sensor drift and environmental interference can lead to a decline in measurement data quality, and existing devices lack real-time evaluation and adaptive correction mechanisms for their own measurement data quality. Therefore, we propose a power distribution network measurement system. Summary of the Invention

[0008] The technical problem to be solved by the present invention is to overcome the existing defects and provide a distribution network measurement system that can realize multi-dimensional, high-precision, and highly synchronous distribution network measurement data acquisition, has bidirectional real-time interaction capability with a digital twin platform, and online evaluation and adaptive correction function for measurement data quality, which can effectively solve the problems in the background technology.

[0009] To achieve the above objectives, the present invention provides the following technical solution: a power distribution network measurement system, comprising a multi-source heterogeneous data acquisition module, a high-precision synchronous clock module, a data processing and edge computing module, a communication and interaction module, and a local storage and management module;

[0010] The high-precision synchronous clock module is connected to the multi-source heterogeneous data acquisition module, the data processing and edge computing module and the communication and interaction module respectively, and is used to provide a synchronous sampling clock signal of a unified frequency and high-precision time reference information to each module.

[0011] The data output terminal of the multi-source heterogeneous data acquisition module is connected to the data input terminal of the data processing and edge computing module, and is used to transmit the acquired multi-dimensional raw measurement data to the data processing and edge computing module for preprocessing and feature extraction.

[0012] A bidirectional data connection is established between the data processing and edge computing module and the communication and interaction module. The data processing and edge computing module uploads the processed standard measurement data to the digital twin platform through the communication and interaction module, and the communication and interaction module transmits the received platform-side measurement strategy adjustment instructions to the data processing and edge computing module.

[0013] The local storage and management module is connected to the data processing and edge computing module and the communication and interaction module, respectively, and is used to cache the processed measurement data locally and store device configuration parameters and operation logs.

[0014] Furthermore, the multi-source heterogeneous data acquisition module includes an electrical quantity acquisition submodule and a topology state perception submodule;

[0015] The electrical quantity acquisition submodule includes a voltage transformer, a current transformer, and a power measurement unit. The secondary output terminals of the voltage transformer and the current transformer are respectively connected to the voltage sampling terminal and the current sampling terminal of the power measurement unit. The power measurement unit is used to synchronously calculate the voltage amplitude, current amplitude, active power, reactive power, and power factor.

[0016] The topology status sensing submodule includes switch status sensors deployed at each switchgear. The signal output terminal of the switch status sensor is connected to the data aggregation interface of the electrical quantity acquisition submodule, which is used to align and bind the switch opening and closing status signals with the electrical quantity data at the corresponding locations in time sequence.

[0017] Furthermore, the multi-source heterogeneous data acquisition module also includes an environmental parameter acquisition submodule and a spatial positioning submodule;

[0018] The environmental parameter acquisition submodule includes a temperature sensor, a humidity sensor, and a vibration sensor. The output terminals of the temperature sensor, humidity sensor, and vibration sensor are connected to the environmental data acquisition unit through an analog-to-digital converter interface. The environmental data acquisition unit is used to convert analog environmental signals into digital environmental parameters.

[0019] The spatial positioning submodule includes a GNSS positioning unit, the output of which is connected to the serial communication interface of the environmental data acquisition unit.

[0020] The data output terminal of the environmental data acquisition unit is connected to the internal data bus of the multi-source heterogeneous data acquisition module, and is used to assemble the environmental parameters and spatial location coordinates with the electrical quantity data acquired by the electrical quantity acquisition submodule and the topology state data acquired by the topology state perception submodule into the same data frame structure.

[0021] Furthermore, the high-precision synchronous clock module includes a GNSS timing unit, a crystal oscillator timing unit, and a time synchronization correction unit;

[0022] The output of the GNSS timing unit is connected to the first reference input of the time synchronization correction unit to provide standard second pulse signal and UTC absolute time information.

[0023] The output of the crystal oscillator timing unit is connected to the second reference input of the time synchronization correction unit, and is used to provide a local high-stability clock signal when the GNSS signal is lost.

[0024] The adaptive filter output of the time synchronization correction unit is connected to the sampling trigger terminal of the multi-source heterogeneous data acquisition module and the timestamp marker terminal of the data processing and edge computing module via a clock distribution buffer. The time synchronization correction unit performs online estimation and dynamic compensation of the frequency drift of the crystal oscillator timekeeping unit based on the adaptive Kalman filter algorithm, and generates a corrected synchronization clock signal to provide synchronization trigger signals to each module.

[0025] Furthermore, the high-precision synchronous clock module also includes an IEEE 1588 precision time protocol synchronization unit;

[0026] The IEEE 1588 precision time protocol synchronization unit is bidirectionally connected to the time synchronization correction unit via a data bus. It is used to read the local clock status of the time synchronization correction unit and to exchange network time synchronization messages with adjacent measurement systems based on the IEEE 1588 protocol.

[0027] The synchronization signal output terminal of the IEEE 1588 Precision Time Protocol synchronization unit is connected to the communication and interaction module, and is used to encapsulate the time reference information after network synchronization correction into the uplink communication message.

[0028] Furthermore, the data processing and edge computing module includes a data preprocessing unit and a data quality online evaluation unit;

[0029] The input end of the data preprocessing unit is connected to the data output end of the multi-source heterogeneous data acquisition module. The data preprocessing unit is used to sequentially perform sliding filter noise reduction, Laida criterion outlier removal, and cubic spline interpolation missing value completion processing on the received raw measurement data.

[0030] The output of the data preprocessing unit is connected to the input of the online data quality evaluation unit. The online data quality evaluation unit is used to calculate the data integrity index, accuracy index, consistency index and timeliness index respectively based on the statistical characteristics of the preprocessed time series measurement data, and to generate a comprehensive quality score by weighted fusion of the four indicators.

[0031] Furthermore, the data processing and edge computing module also includes an adaptive correction unit and a feature extraction unit;

[0032] The comprehensive quality score output of the online data quality evaluation unit is connected to the input of the adaptive correction unit. The adaptive correction unit dynamically generates sensor correction coefficients based on the comprehensive quality score and a preset quality threshold range, and feeds the correction coefficients back to the pre-calibration input of the data preprocessing unit to achieve online closed-loop calibration of the measurement data.

[0033] The output of the data preprocessing unit is also connected to the input of the feature extraction unit. The feature extraction unit is used to extract steady-state and transient features from the calibrated measurement data. The steady-state features include at least voltage deviation and three-phase imbalance, and the transient features include at least voltage sag depth, duration, and harmonic distortion rate.

[0034] Furthermore, the communication and interaction module includes a data uploading unit, an instruction receiving unit, and a two-way interaction protocol stack;

[0035] The input end of the data upload unit is connected to the standard data output end of the data processing and edge computing module, and the output end of the data upload unit is connected to the uplink data interface of the bidirectional interaction protocol stack, for uploading standard measurement data packets to the digital twin platform according to a preset period; the standard measurement data packet includes at least the measurement value, the synchronization timestamp, and the corresponding comprehensive quality score label;

[0036] The output of the instruction receiving unit is connected to the policy control input of the data processing and edge computing module, and the input of the instruction receiving unit is connected to the downlink instruction interface of the bidirectional interactive protocol stack, for receiving the measurement strategy adjustment instruction issued by the digital twin platform. The measurement strategy adjustment instruction includes at least the sampling frequency adjustment instruction, the measurement channel switching instruction, and the measurement key area indication instruction.

[0037] The instruction receiving unit and the data uploading unit are connected through the internal priority arbitration bus of the bidirectional interactive protocol stack to ensure the priority parsing and execution of downlink instructions.

[0038] Furthermore, the bidirectional interactive protocol stack has a built-in MQTT protocol stack and a CoAP protocol stack, and is configured with a protocol adaptive selection unit;

[0039] The monitoring input terminal of the protocol adaptive selection unit is connected to the network status feedback terminal of the communication and interaction module to obtain the signal quality parameters and packet loss rate of the current communication network.

[0040] The switching control output of the protocol adaptive selection unit is connected to the mode switching input of the bidirectional interactive protocol stack, and is used to dynamically select MQTT protocol or CoAP protocol as the current transmission protocol according to the signal quality parameters and packet loss rate.

[0041] The data upload unit and the instruction receiving unit perform data packet format conversion, compression encryption, and transmission / reception priority scheduling through the bidirectional interactive protocol stack, thereby realizing bidirectional real-time communication between the data processing and edge computing module and the digital twin platform.

[0042] Furthermore, the local storage and management module includes a ring cache unit, a configuration management unit, and a self-diagnostic unit;

[0043] The write end of the ring buffer unit is connected to the data backup output end of the data processing and edge computing module, and the read end of the ring buffer unit is connected to the retransmission request input end of the communication and interaction module. The ring buffer unit is used to cyclically cache the measurement data within a preset time window according to the first-in-first-out principle, and respond to the retransmission command when the communication link is restored.

[0044] The configuration management unit is connected to the parameter configuration terminal of the multi-source heterogeneous data acquisition module, the clock configuration terminal of the high-precision synchronous clock module, and the network configuration terminal of the communication and interaction module, respectively, and is used to store and send device configuration parameters to each module.

[0045] The monitoring input terminal of the self-diagnostic unit is connected to the status feedback terminal of the multi-source heterogeneous data acquisition module, the lock status terminal of the high-precision synchronous clock module, and the link status terminal of the communication and interaction module, respectively, for real-time monitoring of the operating status of each module. The alarm output terminal of the self-diagnostic unit is connected to the uplink alarm interface of the communication and interaction module, for actively generating alarm messages and reporting to the digital twin platform when an anomaly is detected.

[0046] Compared with the prior art, the beneficial effects of the present invention are as follows: This power distribution network measurement system has the following advantages:

[0047] 1. This invention integrates multi-source heterogeneous data acquisition functions such as electrical quantity acquisition, topology state perception, environmental parameter acquisition, and spatial positioning. Through an internal data bus, the data acquired by each sub-module is assembled into the same data frame structure, providing richer and more comprehensive data input for the digital twin model than traditional measurement systems, and significantly improving the fidelity of the digital twin model.

[0048] 2. Through a multi-redundancy design incorporating GNSS time synchronization, high-stability crystal oscillator timekeeping, and adaptive Kalman filter correction, combined with an IEEE 1588 precision time protocol synchronization unit, network-wide unified time synchronization between the device's own time reference and adjacent measurement systems was achieved. The time synchronization correction unit uses an adaptive Kalman filter algorithm to perform online estimation and dynamic compensation for crystal oscillator frequency drift, effectively solving the synchronization error problem in digital twin state estimation and dynamic power flow simulation.

[0049] 3. The device's built-in online data quality evaluation unit can evaluate the completeness, accuracy, consistency, and timeliness of measurement data in real time and generate a comprehensive quality score. The adaptive correction unit dynamically generates sensor correction coefficients based on the quality score and feeds them back to the pre-calibration input of the data preprocessing unit, realizing online closed-loop calibration of measurement data, effectively compensating for errors introduced by sensor drift and environmental interference, and ensuring the reliability of the digital twin model input data.

[0050] 4. The device can not only upload measurement data to the digital twin platform in real time through the communication and interaction module, but also receive feedback instructions from the platform through the instruction receiving unit to dynamically adjust the measurement strategy, realizing closed-loop collaboration between the measurement system and the digital twin platform, and supporting dynamic evaluation and iterative optimization of the planning scheme.

[0051] 5. The device described in this invention can continuously and stably provide high-quality real-time data for digital twin models, enabling distribution network planning and evaluation to transform from the traditional static and offline mode to a dynamic and online mode, effectively solving the problem of the lack of a dynamic evaluation mechanism for distribution network planning decisions. Attached Figure Description

[0052] Figure 1 This is a structural block diagram of the present invention. Detailed Implementation

[0053] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0054] Please see Figure 1 This embodiment provides a technical solution: a power distribution network measurement system.

[0055] In this embodiment, the power distribution network measurement system adopts a modular design and mainly includes the following hardware components:

[0056] (i) Main Control Unit: Employs a high-performance ARM Cortex-A series processor (such as the NXP i.MX8M series or TIAM62x series), runs a Linux real-time operating system, and has a main frequency of no less than 1.2GHz. It is responsible for the overall control, task scheduling, and data processing of the device. This main control unit connects to each module through bus interfaces such as SPI, I²C, and UART to achieve unified data management and coordinated scheduling.

[0057] (II) Multi-source heterogeneous data acquisition module:

[0058] (1) Electrical quantity acquisition submodule: High-precision ADC (analog-to-digital converter) chips (such as ADI AD7606 series) are used, with a sampling rate of not less than 12.8kHz and a resolution of not less than 16 bits, supporting 8-channel synchronous sampling. The voltage transformer can be an electromagnetic or electronic voltage transformer with an accuracy of not less than 0.5 (rated primary voltage 10kV / 35kV, secondary output 0-100V), and the current transformer can be an electromagnetic or electronic current transformer with an accuracy of not less than 0.5 (rated primary current 100A-1000A, secondary output 0-5A or 0-1A). The secondary output terminals of the voltage transformer and the current transformer are respectively connected to the voltage sampling terminal and the current sampling terminal of the power measurement unit. The power measurement unit can use a dedicated energy metering chip (such as ADIADE9000 series), which supports multi-channel synchronous sampling and harmonic analysis, and is used to synchronously calculate electrical operating parameters such as voltage amplitude, current amplitude, active power, reactive power, power factor and frequency.

[0059] (2) Topology Status Sensing Submodule: This includes switch status sensors deployed at each switchgear location. The switch status sensors can be opto-isolated or Hall effect type switch quantity acquisition modules (such as Advantech ADAM-4055) used to acquire the opening and closing status signals of circuit breakers, disconnectors, load switches, and other equipment in the distribution network. The signal output terminal of the switch status sensor is connected to the data aggregation interface of the electrical quantity acquisition submodule, aligning and binding the switch opening and closing status signals with the corresponding electrical quantity data in time sequence.

[0060] (3) Environmental Parameter Acquisition Submodule: This includes a temperature sensor, a humidity sensor, and a vibration sensor. The temperature sensor can be a PT100 platinum resistance thermometer (measurement range -40℃ to +150℃, accuracy ±0.1℃) or a digital temperature sensor (such as DS18B20, accuracy ±0.5℃); the humidity sensor can be a capacitive humidity sensor (such as SHT30 or SHT35, accuracy ±2%RH); the vibration sensor can be a piezoelectric accelerometer (such as PCB 352C33, sensitivity 100mV / g, frequency response 0.5Hz to 10kHz). The outputs of the temperature sensor, humidity sensor, and vibration sensor are connected to the environmental data acquisition unit via an analog-to-digital converter interface. The environmental data acquisition unit can be a data acquisition card with an integrated multi-channel ADC (such as NIUSB-6009) or a microcontroller with a Σ-Δ ADC (such as the STM32F4 series) to convert analog environmental signals into digital environmental parameters.

[0061] (4) Spatial Positioning Submodule: Includes a GNSS positioning unit, which may be a UBLOX NEO-M9N or similar product supporting GPS / BeiDou dual-mode, with a positioning accuracy better than 2.5 meters (CEP), and outputs location information in NMEA 0183 standard format. The output end (UART serial interface) of the GNSS positioning unit is connected to the serial communication interface of the environmental data acquisition unit. The data output end of the environmental data acquisition unit is connected to the internal data bus (such as CAN bus or RS-485 bus) of the multi-source heterogeneous data acquisition module, used to assemble the environmental parameters and spatial position coordinates with the electrical quantity data acquired by the electrical quantity acquisition submodule and the topology state data acquired by the topology state perception submodule into the same data frame structure.

[0062] (III) High-precision synchronous clock module:

[0063] (1) GNSS timing unit: A timing module that supports GPS / BeiDou dual mode (such as UBLOX NEO-M8T or Skytraq Venus828) can be selected to provide standard second pulse signal (1PPS, rise time better than 20ns) and UTC absolute time information (GPRMC / GPGGA statement is output through UART serial port).

[0064] (2) Crystal oscillator timing unit: OCXO temperature-controlled crystal oscillator (such as Connor-Winfield OH200 series or similar products) can be selected, with frequency stability better than ±10ppb (-40℃~+85℃) and timing accuracy better than 1ms / hour.

[0065] (3) Time Synchronization Correction Unit: The output of the GNSS timing unit is connected to the first reference input of the time synchronization correction unit to provide a standard second pulse signal and UTC absolute time information; the output of the crystal oscillator timekeeping unit is connected to the second reference input of the time synchronization correction unit to provide a local high-stability clock signal when the GNSS signal is lost. The time synchronization correction unit has a built-in FPGA (such as Intel Cyclone IV or Xilinx Artix-7 series), which performs online estimation and dynamic compensation of the frequency drift of the crystal oscillator timekeeping unit based on an adaptive Kalman filter algorithm. Its adaptive filter output is connected to the sampling trigger terminal of the multi-source heterogeneous data acquisition module and the timestamp marker terminal of the data processing and edge computing module through a clock distribution buffer (such as TI CDCLVC1102 or IDT 5V9885B, with additional jitter less than 50fs) to generate a corrected synchronization clock signal to provide a synchronization trigger signal to each module.

[0066] (4) IEEE 1588 Precision Time Protocol Synchronization Unit: This unit is bidirectionally connected to the time synchronization correction unit via a data bus (MII / RMII interface). It is used to read the local clock state of the time correction unit and to exchange network time synchronization messages with adjacent measurement systems based on the IEEE 1588 protocol (Precision Time Protocol v2). The synchronization signal output terminal of the IEEE 1588 Precision Time Protocol Synchronization Unit is connected to the communication and interaction module, which is used to encapsulate the time reference information corrected by network synchronization into the uplink communication message.

[0067] Through the quadruple redundancy design of GNSS time synchronization, OCXO crystal oscillator timekeeping, adaptive Kalman filter correction, and IEEE 1588 network synchronization, the time synchronization accuracy of this device is better than ±500ns, ensuring the uniformity of the time reference for measurement data across the entire network.

[0068] (iv) Data Processing and Edge Computing Module:

[0069] (1) Data Preprocessing Unit: Its input is connected to the data output of the multi-source heterogeneous data acquisition module. The data preprocessing unit runs in the main control unit and is used to sequentially perform sliding filter denoising (the sliding window length can be configured to 10~100 sampling points), outlier removal by the Laida criterion (3σ criterion), and missing value completion by cubic spline interpolation on the received raw measurement data. When the probability distribution of the measurement data does not meet the normal distribution assumption, the data preprocessing unit automatically switches the Laida criterion to an outlier detection method based on the interquartile range (IQR) (using Q1-1.5×IQR and Q3+1.5×IQR as outlier discrimination boundaries) to enhance the algorithm's adaptability to non-normally distributed data.

[0070] (2) Online data quality evaluation unit: Its input end is connected to the output end of the data preprocessing unit. The online data quality evaluation unit is used to calculate the data integrity index (the ratio of the number of valid data frames per unit time to the theoretical number of frames to be collected), accuracy index (based on the time consistency test of the measurement data and the comparison of historical data, and evaluated by the root mean square error RMSE), consistency index (the maximum relative deviation is calculated by cross-comparing the measurement values ​​of different redundant sensors at the same measurement point), and timeliness index (the time delay from data acquisition to data upload completion is statistically analyzed) according to the statistical characteristics of the preprocessed time series measurement data. The four indicators are then weighted and fused to generate a comprehensive quality score (0~100 points).

[0071] (3) Adaptive Correction Unit: The comprehensive quality score output of the online data quality evaluation unit is connected to the input of the adaptive correction unit. The adaptive correction unit dynamically generates sensor correction coefficients (including zero bias correction coefficients and gain correction coefficients) based on the comprehensive quality score and a preset quality threshold range (e.g., above 90 points is excellent, 80-90 points is good, 70-80 points is average, and below 70 points is poor), and feeds back the correction coefficients to the pre-calibration input of the data preprocessing unit to achieve online closed-loop calibration of the measurement data.

[0072] (4) Feature Extraction Unit: The output of the data preprocessing unit is also connected to the input of the feature extraction unit. The feature extraction unit is used to extract steady-state and transient features from the calibrated measurement data. The steady-state features include at least voltage deviation (calculated according to GB / T 12325 standard) and three-phase unbalance (calculated according to GB / T 15543 standard). The transient features include at least voltage sag depth (percentage of remaining voltage to rated voltage), duration, and harmonic distortion rate (total harmonic distortion rate THD, calculated up to the 50th harmonic according to GB / T 14549 standard).

[0073] (v) Communication and Interaction Module:

[0074] (1) Data Upload Unit: Its input end is connected to the standard data output end of the data processing and edge computing module, and its output end is connected to the uplink data interface of the bidirectional interactive protocol stack. The data upload unit uploads standard measurement data packets to the digital twin platform via 5G network or fiber optic Ethernet at a preset period (default 100Hz, adjustable range 10Hz~1000Hz). The 5G communication module can be an industrial-grade 5G module (such as Quectel RM500U-CN or Fibocom FM150 series), which supports SA / NSA networking and has a theoretical downlink speed of not less than 2Gbps; the gigabit Ethernet interface supports the IEEE 802.3 standard and has a transmission rate of 1000Mbps. The standard measurement data packet includes at least the measurement value, the synchronization timestamp, and the corresponding comprehensive quality score label.

[0075] (2) Command receiving unit: Its output is connected to the policy control input of the data processing and edge computing module, and its input is connected to the downlink command interface of the bidirectional interactive protocol stack. The command receiving unit is used to receive the measurement policy adjustment command issued by the digital twin platform. The measurement policy adjustment command includes at least the sampling frequency adjustment command (such as adjusting the sampling rate from 100Hz to 400Hz), the measurement channel switching command (such as enabling or disabling a specific measurement channel), and the measurement key area indication command (such as switching the device to the measurement mode of a certain key feeder).

[0076] (3) Bidirectional Interactive Protocol Stack: It includes a built-in MQTT and CoAP protocol stack, and is equipped with a protocol adaptive selection unit. The monitoring input of the protocol adaptive selection unit is connected to the network status feedback of the communication and interaction module to obtain the signal quality parameters (RSRP, SINR, etc.) and packet loss rate of the current communication network. The switching control output of the protocol adaptive selection unit is connected to the mode switching input of the bidirectional interactive protocol stack to dynamically select either the MQTT protocol (suitable for scenarios with good network quality and requiring reliable transmission) or the CoAP protocol (suitable for scenarios with poor network quality and requiring low-overhead, lightweight transmission) as the current transmission protocol based on the signal quality parameters and packet loss rate. The instruction receiving unit and the data uploading unit are connected through the internal priority arbitration bus of the bidirectional interactive protocol stack to ensure the priority parsing and execution of downlink instructions.

[0077] (vi) Local Storage and Management Module:

[0078] (1) Ring Cache Unit: Its write end is connected to the data backup output end of the data processing and edge computing module, and its read end is connected to the retransmission request input end of the communication and interaction module. The ring cache unit is equipped with eMMC flash memory (capacity not less than 8GB) to cyclically cache measurement data within a preset time window (default 24 hours) according to the first-in-first-out (FIFO) principle, and respond to the retransmission command when the communication link is restored to realize data retransmission in the event of network failure.

[0079] (2) Configuration Management Unit: Equipped with FRAM (Ferroelectric Memory, such as Fujitsu MB85RC256V, with a capacity of 256Kb and a read / write life of 10¹² times), used to save device configuration parameters when power is off. The configuration management unit is connected to the parameter configuration terminal (such as range setting, transformer ratio, etc.) of the multi-source heterogeneous data acquisition module, the clock configuration terminal (such as timekeeping parameters, correction coefficients, etc.) of the high-precision synchronous clock module, and the network configuration terminal (such as IP address, APN setting, data upload cycle, etc.) of the communication and interaction module, and is used to store and distribute device configuration parameters to each module.

[0080] (3) Self-diagnostic unit: Its monitoring input terminals are respectively connected to the status feedback terminal of the multi-source heterogeneous data acquisition module (such as ADC overload flag, sensor disconnection detection, etc.), the lock status terminal of the high-precision synchronous clock module (such as GNSS signal lock indication, PPS signal loss alarm, etc.), and the link status terminal of the communication and interaction module (such as network connection status, signal strength, etc.). The self-diagnostic unit monitors the operating status of each module in real time. When an abnormality is detected (such as GNSS signal loss exceeding 30 seconds, sensor disconnection, network connection interruption, etc.), its alarm output terminal is connected to the uplink alarm interface of the communication and interaction module, actively generates alarm messages and reports them to the digital twin platform.

[0081] The working principle of the power distribution network measurement system provided by this invention is as follows:

[0082] Step S1: The multi-source heterogeneous data acquisition module synchronously acquires electrical quantity data (voltage, current, active power, reactive power, power factor, etc.), topology status data (switch opening and closing status), environmental parameters (temperature, humidity, vibration), and spatial location information (GNSS coordinates) of the distribution network lines according to the preset sampling frequency (default 100Hz) through the synchronization trigger signal provided by the high-precision synchronization clock module. The data acquired by each submodule are aggregated through the internal data bus and assembled into the same data frame structure.

[0083] Step S2: The high-precision synchronization clock module adds a unified high-precision timestamp to each frame of measurement data. The GNSS timing unit provides a standard second pulse signal and UTC absolute time information as the master clock reference; when the GNSS signal is lost, the crystal oscillator timing unit (OCXO temperature-controlled crystal oscillator) provides a local high-stability clock signal to maintain timekeeping; the time synchronization correction unit performs online estimation and dynamic compensation of crystal oscillator frequency drift based on an adaptive Kalman filter algorithm to generate a high-precision synchronization clock; the IEEE 1588 precision time protocol synchronization unit is bidirectionally connected to the time synchronization correction unit through a data bus, reads the local clock status, and exchanges network time synchronization messages with adjacent measurement systems based on the IEEE 1588 protocol to ensure the timing consistency of data between different measurement points, with a network-wide time synchronization accuracy better than ±500ns.

[0084] Step S3: The data processing and edge computing module processes the measurement data. The data preprocessing unit sequentially performs sliding filter denoising, outlier removal using the Laida criterion (3σ criterion), and missing value completion using cubic spline interpolation (automatically switching to an outlier detection method based on interquartile range (IQR) when the data distribution does not meet the normal distribution); the online data quality evaluation unit calculates the integrity index, accuracy index, consistency index, and timeliness index respectively, and weights and fuses them to generate a comprehensive quality score; the adaptive correction unit dynamically generates sensor correction coefficients based on the comprehensive quality score and the preset quality threshold range, and feeds them back to the pre-calibration input of the data preprocessing unit to achieve online closed-loop calibration; the feature extraction unit extracts steady-state features (voltage deviation, three-phase unbalance) and transient features (voltage sag depth, duration, harmonic distortion rate) from the calibrated measurement data to generate a standard format measurement data message.

[0085] Step S4: The communication and interaction module uploads standard measurement data packets to the digital twin platform in real time. The data packets must include at least the measurement value, synchronization timestamp, and corresponding comprehensive quality score label. The protocol adaptive selection unit dynamically selects either MQTT or CoAP as the current transmission protocol based on the signal quality parameters and packet loss rate of the current communication network. It supports 5G / fiber dual-redundancy communication, automatically switching to the backup channel when the communication link is interrupted to ensure reliable data transmission.

[0086] Step S5: The communication and interaction module continuously monitors the measurement strategy adjustment commands issued by the digital twin platform. When it receives a sampling frequency adjustment command, a measurement channel switching command, or a measurement key area indication command, it ensures that the downlink command is parsed and executed first through the internal priority arbitration bus, dynamically adjusting the sampling parameters and measurement strategy of the data acquisition module to achieve closed-loop collaboration between the measurement system and the digital twin platform. The digital twin platform can temporarily increase the sampling frequency (e.g., from 100Hz to 400Hz) and add measurement dimensions in key evaluation areas according to the needs of dynamic planning evaluation. After the evaluation is completed, it issues a recovery command to restore the device to the default strategy.

[0087] Step S6: The local storage and management module continuously performs data caching, configuration management, and self-diagnosis during device operation. The circular cache unit cyclically caches measurement data within a preset time window according to the first-in-first-out principle, and responds to retransmission commands when the communication link is restored; the configuration management unit stores and distributes device configuration parameters to each module; the self-diagnosis unit monitors the operating status of each module in real time, and actively generates alarm messages and reports them to the digital twin platform when anomalies are detected (GNSS signal loss, sensor disconnection, communication link interruption, etc.).

[0088] The distribution network measurement system provided by this invention achieves high-precision and high-synchronization acquisition and processing of multi-source heterogeneous data of the distribution network through the coordinated work of the above modules, supports bidirectional real-time interaction with the digital twin platform, and provides reliable data support for the dynamic evaluation and optimization method of distribution network planning based on digital twin.

[0089] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A power distribution network measurement system, characterized in that: It includes a multi-source heterogeneous data acquisition module, a high-precision synchronous clock module, a data processing and edge computing module, a communication and interaction module, and a local storage and management module; The high-precision synchronous clock module is connected to the multi-source heterogeneous data acquisition module, the data processing and edge computing module and the communication and interaction module respectively, and is used to provide a synchronous sampling clock signal of a unified frequency and high-precision time reference information to each module. The data output terminal of the multi-source heterogeneous data acquisition module is connected to the data input terminal of the data processing and edge computing module, and is used to transmit the acquired multi-dimensional raw measurement data to the data processing and edge computing module for preprocessing and feature extraction. A bidirectional data connection is established between the data processing and edge computing module and the communication and interaction module. The data processing and edge computing module uploads the processed standard measurement data to the digital twin platform through the communication and interaction module, and the communication and interaction module transmits the received platform-side measurement strategy adjustment instructions to the data processing and edge computing module. The local storage and management module is connected to the data processing and edge computing module and the communication and interaction module, respectively, and is used to cache the processed measurement data locally and store device configuration parameters and operation logs.

2. The power distribution network measurement system according to claim 1, characterized in that: The multi-source heterogeneous data acquisition module includes an electrical quantity acquisition submodule and a topology state perception submodule; The electrical quantity acquisition submodule includes a voltage transformer, a current transformer, and a power measurement unit. The secondary output terminals of the voltage transformer and the current transformer are respectively connected to the voltage sampling terminal and the current sampling terminal of the power measurement unit. The power measurement unit is used to synchronously calculate the voltage amplitude, current amplitude, active power, reactive power, and power factor. The topology status sensing submodule includes switch status sensors deployed at each switchgear. The signal output terminal of the switch status sensor is connected to the data aggregation interface of the electrical quantity acquisition submodule, which is used to align and bind the switch opening and closing status signals with the electrical quantity data at the corresponding locations in time sequence.

3. The power distribution network measurement system according to claim 1, characterized in that: The multi-source heterogeneous data acquisition module also includes an environmental parameter acquisition submodule and a spatial positioning submodule; The environmental parameter acquisition submodule includes a temperature sensor, a humidity sensor, and a vibration sensor. The output terminals of the temperature sensor, humidity sensor, and vibration sensor are connected to the environmental data acquisition unit through an analog-to-digital converter interface. The environmental data acquisition unit is used to convert analog environmental signals into digital environmental parameters. The spatial positioning submodule includes a GNSS positioning unit, the output of which is connected to the serial communication interface of the environmental data acquisition unit. The data output terminal of the environmental data acquisition unit is connected to the internal data bus of the multi-source heterogeneous data acquisition module, and is used to assemble the environmental parameters and spatial location coordinates with the electrical quantity data acquired by the electrical quantity acquisition submodule and the topology state data acquired by the topology state perception submodule into the same data frame structure.

4. The power distribution network measurement system according to claim 1, characterized in that: The high-precision synchronous clock module includes a GNSS timing unit, a crystal oscillator timing unit, and a time synchronization correction unit. The output of the GNSS timing unit is connected to the first reference input of the time synchronization correction unit to provide standard second pulse signal and UTC absolute time information. The output of the crystal oscillator timing unit is connected to the second reference input of the time synchronization correction unit, and is used to provide a local high-stability clock signal when the GNSS signal is lost. The adaptive filter output of the time synchronization correction unit is connected to the sampling trigger terminal of the multi-source heterogeneous data acquisition module and the timestamp marker terminal of the data processing and edge computing module via a clock distribution buffer. The time synchronization correction unit performs online estimation and dynamic compensation of the frequency drift of the crystal oscillator timekeeping unit based on the adaptive Kalman filter algorithm, and generates a corrected synchronization clock signal to provide synchronization trigger signals to each module.

5. A power distribution network measurement system according to claim 4, characterized in that: The high-precision synchronous clock module also includes an IEEE 1588 precision time protocol synchronization unit; The IEEE 1588 precision time protocol synchronization unit is bidirectionally connected to the time synchronization correction unit via a data bus. It is used to read the local clock status of the time synchronization correction unit and to exchange network time synchronization messages with adjacent measurement systems based on the IEEE 1588 protocol. The synchronization signal output terminal of the IEEE 1588 Precision Time Protocol synchronization unit is connected to the communication and interaction module, and is used to encapsulate the time reference information after network synchronization correction into the uplink communication message.

6. A power distribution network measurement system according to claim 1, characterized in that: The data processing and edge computing module includes a data preprocessing unit and a data quality online evaluation unit; The input end of the data preprocessing unit is connected to the data output end of the multi-source heterogeneous data acquisition module. The data preprocessing unit is used to sequentially perform sliding filter noise reduction, Laida criterion outlier removal, and cubic spline interpolation missing value completion processing on the received raw measurement data. The output of the data preprocessing unit is connected to the input of the online data quality evaluation unit. The online data quality evaluation unit is used to calculate the data integrity index, accuracy index, consistency index and timeliness index respectively based on the statistical characteristics of the preprocessed time series measurement data, and to generate a comprehensive quality score by weighted fusion of the four indicators.

7. A power distribution network measurement system according to claim 6, characterized in that: The data processing and edge computing module also includes an adaptive correction unit and a feature extraction unit; The comprehensive quality score output of the online data quality evaluation unit is connected to the input of the adaptive correction unit. The adaptive correction unit dynamically generates sensor correction coefficients based on the comprehensive quality score and a preset quality threshold range, and feeds the correction coefficients back to the pre-calibration input of the data preprocessing unit to achieve online closed-loop calibration of the measurement data. The output of the data preprocessing unit is also connected to the input of the feature extraction unit. The feature extraction unit is used to extract steady-state and transient features from the calibrated measurement data. The steady-state features include at least voltage deviation and three-phase imbalance, and the transient features include at least voltage sag depth, duration, and harmonic distortion rate.

8. A power distribution network measurement system according to claim 1, characterized in that: The communication and interaction module includes a data uploading unit, an instruction receiving unit, and a two-way interaction protocol stack. The input end of the data upload unit is connected to the standard data output end of the data processing and edge computing module, and the output end of the data upload unit is connected to the uplink data interface of the bidirectional interaction protocol stack, for uploading standard measurement data packets to the digital twin platform according to a preset period; the standard measurement data packet includes at least the measurement value, the synchronization timestamp, and the corresponding comprehensive quality score label; The output of the instruction receiving unit is connected to the policy control input of the data processing and edge computing module, and the input of the instruction receiving unit is connected to the downlink instruction interface of the bidirectional interactive protocol stack, for receiving the measurement strategy adjustment instruction issued by the digital twin platform. The measurement strategy adjustment instruction includes at least the sampling frequency adjustment instruction, the measurement channel switching instruction, and the measurement key area indication instruction. The instruction receiving unit and the data uploading unit are connected through the internal priority arbitration bus of the bidirectional interactive protocol stack to ensure the priority parsing and execution of downlink instructions.

9. A power distribution network measurement system according to claim 8, characterized in that: The bidirectional interactive protocol stack has a built-in MQTT protocol stack and a CoAP protocol stack, and is configured with a protocol adaptive selection unit; The monitoring input terminal of the protocol adaptive selection unit is connected to the network status feedback terminal of the communication and interaction module to obtain the signal quality parameters and packet loss rate of the current communication network. The switching control output of the protocol adaptive selection unit is connected to the mode switching input of the bidirectional interactive protocol stack, and is used to dynamically select MQTT protocol or CoAP protocol as the current transmission protocol according to the signal quality parameters and packet loss rate. The data upload unit and the instruction receiving unit perform data packet format conversion, compression encryption, and transmission / reception priority scheduling through the bidirectional interactive protocol stack, thereby realizing bidirectional real-time communication between the data processing and edge computing module and the digital twin platform.

10. A power distribution network measurement system according to claim 1, characterized in that: The local storage and management module includes a ring cache unit, a configuration management unit, and a self-diagnosis unit; The write end of the ring buffer unit is connected to the data backup output end of the data processing and edge computing module, and the read end of the ring buffer unit is connected to the retransmission request input end of the communication and interaction module. The ring buffer unit is used to cyclically cache the measurement data within a preset time window according to the first-in-first-out principle, and respond to the retransmission command when the communication link is restored. The configuration management unit is connected to the parameter configuration terminal of the multi-source heterogeneous data acquisition module, the clock configuration terminal of the high-precision synchronous clock module, and the network configuration terminal of the communication and interaction module, respectively, and is used to store and send device configuration parameters to each module. The monitoring input terminal of the self-diagnostic unit is connected to the status feedback terminal of the multi-source heterogeneous data acquisition module, the lock status terminal of the high-precision synchronous clock module, and the link status terminal of the communication and interaction module, respectively, for real-time monitoring of the operating status of each module. The alarm output terminal of the self-diagnostic unit is connected to the uplink alarm interface of the communication and interaction module, for actively generating alarm messages and reporting to the digital twin platform when an anomaly is detected.

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