Industrial park energy carbon data visualization terminal and working method thereof

Abstract

The invention discloses an industrial park energy carbon data visualization terminal and a working method thereof. A data acquisition module of the terminal acquires power grid electric energy quality data in real time; the carbon emission calculation module maps the electric energy data into a carbon emission reduction index based on a power grid emission factor, and dynamically updates a historical trend chart; the display module dynamically displays the electric energy quality data, the carbon emission statistical result and the historical trend chart; the communication module supports an industrial Ethernet, an RS485 interface and an IRIG-B code time synchronization function, and realizes data interaction with an external management system; the storage module manages the electric energy parameters and the carbon emission data by adopting a circulation strategy; the control module integrates an ARM processor and a DSP data acquisition board, and operates a Linux system to coordinate data acquisition, processing and communication tasks. According to the invention, end-to-end communication of energy-carbon data is realized through a modular architecture, real-time monitoring, historical tracing and abnormal alarm are supported, visual data support is provided for energy efficiency optimization and carbon emission reduction decision making of an industrial park, and low-carbon operation is assisted.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to an industrial park energy and carbon data visualization terminal and a working method thereof. Background Art

[0002] Traditional energy and carbon management terminals rely on a single processor architecture, making it difficult to balance real-time data collection with complex algorithm processing, impacting data analysis accuracy and carbon emissions assessment efficiency. Furthermore, a single communication interface limits the ability to interact with multi-source data, hindering the efficiency of park energy efficiency optimization and carbon trading decision-making. Summary of the Invention

[0003] In view of this, the purpose of the present invention is to propose an industrial park energy and carbon data visualization terminal and its working method to solve the problems of limited multi-source interaction and delayed energy and carbon status feedback in the existing technology.

[0004] In order to achieve the above-mentioned technical objectives, in the first aspect, the present application provides an industrial park energy and carbon data visualization terminal, including a data acquisition module, a carbon emission calculation module, a display module, a communication module, a storage module and a control module. The data acquisition module is configured to collect power quality data in the industrial park in real time; the carbon emission calculation module is configured to calculate the carbon emission reduction based on the power quality data and the grid emission factor, generate carbon emission statistical results, and update the carbon emission reduction to the historical trend chart; the display module is configured to dynamically display the power quality data, carbon emission statistical results and historical trend chart; the communication module supports industrial Ethernet, RS485 interface and IRIG-B code timing function, and is used to interact with external management systems for data; the storage module is configured to store power quality data, carbon emission statistical results and historical trend charts; the control module integrates an ARM processor and a DSP data acquisition board, and is configured with a Linux embedded operating system to coordinate module operation logic and data processing.

[0005] In some embodiments, the data acquisition module is configured to use a LY-6640 power quality monitoring device to achieve high-precision data acquisition, including a 16-bit synchronous sampling A / D converter, a hardware phase-locked loop circuit, and a multi-channel input interface. The sampling rate of the 16-bit synchronous sampling A / D converter is 51.2kHz, and 1024 points are sampled per cycle to ensure the acquisition accuracy of power quality data; the hardware phase-locked loop circuit is configured to track grid frequency changes in real time and dynamically adjust the sampling interval to prevent measurement errors caused by frequency leakage; the multi-channel input interface supports synchronous acquisition of 4 voltage and 12 current signals, with the voltage measurement range covering 5V-420V and the current measurement range covering 5mA-6A.

[0006] In some embodiments, the communication module is configured to provide diversified data interaction channels, including dual 10 / 100Mbps industrial Ethernet interfaces, RS485 communication interface, IRIG-B code timing interface and USB2.0 host interface. The dual 10 / 100Mbps industrial Ethernet interfaces support IEC104 and Modbus-TCP protocols for communicating with external management systems; the RS485 communication interface supports custom protocols, and the communication rate can be configured to 4800 / 9600 / 19200bps; the IRIG-B code timing interface is configured to receive external time synchronization signals; the USB2.0 host interface is configured to support external storage devices to export monitoring data in PQDIF format.

[0007] In some embodiments, the control module is configured to use a heterogeneous computing architecture for data processing, including an ARM Cortex-A9 main processor, a TI TMS320F28335 DSP coprocessor, a distributed task scheduling mechanism and an event trigger management unit. The ARM Cortex-A9 main processor runs a Linux embedded operating system and is responsible for data calculation, statistical analysis and system scheduling; the TI TMS320F28335 DSP coprocessor is dedicated to FFT harmonic analysis and transient event detection algorithm acceleration; the distributed task scheduling mechanism is configured to coordinate the parallel execution of real-time data acquisition, historical data storage and communication transmission; the event trigger management unit is configured to automatically record a preset amount of waveform data before and after the event according to a preset threshold.

[0008] In a second aspect, the present application further provides a working method of an industrial park energy and carbon data visualization terminal, applicable to the visualization terminal of the first aspect, the method comprising:

[0009] Real-time collection of power quality data from the industrial park power grid, including voltage and current signals;

[0010] Digitally convert power quality data to obtain power processing signals, and dynamically track grid frequency changes and adjust sampling parameters;

[0011] Perform spectrum analysis on the power processing signal to generate the harmonic content and total harmonic distortion rate, and generate power parameter information;

[0012] Calculate renewable energy generation based on power parameter information, simultaneously obtain preset emission factors and calculate real-time carbon emission reductions for the industrial park power grid;

[0013] Generate carbon emission statistics based on real-time carbon emission reductions, and display power parameter information and carbon emission statistics;

[0014] The electricity parameter information and carbon emission statistics are stored in time series to obtain historical electricity carbon emission data, which is then stored in a historical database.

[0015] Use a circular storage strategy to manage the historical database;

[0016] Establish an event log to record abnormal operating conditions information.

[0017] In some embodiments, the power parameter information includes three-phase voltage waveforms, three-phase current waveforms, voltage-current vector relationship diagrams, and harmonic spectrum distribution information. Displaying the power parameter information and carbon emission statistics includes:

[0018] Dynamically display three-phase voltage waveforms, three-phase current waveforms, and voltage-current vector diagrams. The voltage-current vector diagram is used to show the phase relationship between voltage and current.

[0019] Display harmonic spectrum distribution information in the form of charts, including spectrum analysis results of 2-65th harmonic content and total harmonic distortion rate;

[0020] Update the real-time carbon emission reduction data to the historical database and generate a historical trend chart, which includes the energy consumption data change curve and carbon emission intensity change curve based on daily / weekly / monthly cycles;

[0021] Carbon emission statistics are displayed simultaneously, including real-time carbon emission reduction, accumulated carbon credit value and proportion of new energy power generation.

[0022] In some embodiments, the method further comprises:

[0023] Establish data communication connection with remote management system to realize real-time transmission of power quality data and carbon emission statistics;

[0024] Receive and respond to data query instructions and parameter configuration instructions issued by the remote management system;

[0025] Perform regular time synchronization and calibration to ensure that the terminal clock is consistent with the remote management system;

[0026] Real-time monitoring of grid operating conditions, identifying voltage fluctuations, flicker, and harmonic over-limit events;

[0027] Record the complete power quality data from before to after the abnormal event is triggered, and record it as abnormal record data;

[0028] Generate event log information containing event characteristic parameters based on abnormal record data;

[0029] Trigger local alarm indication and simultaneously send event alarm information to the remote management system;

[0030] Store event log information in the historical database, update event statistics records and display them.

[0031] In some embodiments, dynamically tracking grid frequency changes and adjusting sampling parameters includes:

[0032] Calculate the actual operating frequency of the current power grid based on the voltage signal in the electric energy parameter information;

[0033] Calculate the difference between the actual operating frequency and the preset rated frequency to generate a frequency deviation value;

[0034] Adjusting the sampling time interval of the analog-to-digital converter according to the frequency deviation value so that the sampling rate of the analog-to-digital converter is synchronized with the actual operating frequency change;

[0035] Maintain a sampling mode with a fixed number of sampling points per cycle;

[0036] Perform frequency compensation calculation on the power processing signal to correct the harmonic measurement error caused by frequency fluctuation;

[0037] When the frequency deviation value exceeds a preset threshold, the sampling parameters are reconfigured and the digital phase-locked loop settings are updated.

[0038] In some embodiments, calculating the renewable energy generation amount based on the electric energy parameter information includes:

[0039] Extracting active power measurement values ​​from the electric energy parameter information, where the active power measurement values ​​include photovoltaic power generation active power and wind power generation active power;

[0040] Perform time integration calculation on the active power measurement value to obtain photovoltaic power generation and wind power generation;

[0041] Perform logical operations on photovoltaic power generation and wind power generation to obtain the total power generation of renewable energy;

[0042] Converting total renewable energy generation into equivalent carbon emission reductions based on preset grid emission factors;

[0043] Calculate the real-time new energy proportion index based on the ratio of total renewable energy power generation to total electricity consumption;

[0044] Generate carbon emission statistics based on equivalent carbon emission reduction and new energy proportion indicators.

[0045] In some embodiments, spectrum analysis is performed on the power processing signal to generate the harmonic content and total harmonic distortion rate, and the generated power parameter information includes:

[0046] Perform fast Fourier transform on the power processing signal to decompose it into harmonic components;

[0047] Calculate the content rate of 2-65 harmonic voltage and current and generate harmonic content distribution information;

[0048] According to each harmonic component, calculate the voltage harmonic distortion rate and current harmonic distortion rate, and record it as the total harmonic distortion rate;

[0049] and, identifying each harmonic component and marking the harmonic component exceeding a preset harmonic limit as excessive harmonic information;

[0050] Integrate harmonic content distribution information, total harmonic distortion rate and excessive harmonic information into power quality parameters;

[0051] Power parameter information is generated according to the power quality parameters.

[0052] By adopting the above-mentioned technical solution, the present invention has the following beneficial effects compared with the prior art: the above-mentioned technical solution provides an industrial park energy and carbon data visualization terminal and its working method, and the terminal includes a data acquisition module, a carbon emission calculation module, a display module, a communication module, a storage module and a control module. The data acquisition module collects power quality data of the power grid in real time; the carbon emission calculation module maps the power data into a carbon emission reduction indicator based on the power grid emission factor, and dynamically updates the historical trend chart; the display module dynamically displays the power quality data, carbon emission statistical results and historical trend chart; the communication module supports industrial Ethernet, RS485 interface and IRIG-B code timing function to realize data interaction with the external management system; the storage module adopts a cyclic strategy to manage power parameters and carbon emission data; the control module integrates an ARM processor and a DSP data acquisition board, and runs a Linux system to coordinate data acquisition, processing and communication tasks. The present invention realizes end-to-end connection of energy and carbon data through a modular architecture, supports real-time monitoring, historical tracing and abnormal alarms, provides visual data support for energy efficiency optimization and carbon emission reduction decision-making in industrial parks, and helps low-carbon operations. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0054] Figure 1 is a structural diagram of the visualization terminal described in the specific implementation method;

[0055] Figure 2 is a method step diagram of steps S101 to S108 of the working method described in the specific embodiment;

[0056] Figure 3 It is a method step diagram of steps S201 to S204 of the working method described in the specific implementation method.

[0057] The reference numerals are as follows:

[0058] 1. Energy and carbon data visualization terminal;

[0059] 11. Data acquisition module;

[0060] 12. Carbon emission calculation module;

[0061] 13. Display module;

[0062] 14. Communication module;

[0063] 15. Storage module;

[0064] 16. Control module. DETAILED DESCRIPTION

[0065] The present invention will be described in further detail below with reference to the accompanying drawings and examples. It is particularly noted that the following examples are intended only to illustrate the present invention and are not intended to limit the scope of the present invention. Similarly, the following examples are only some embodiments of the present invention and are not intended to be exhaustive. All other embodiments obtained by those of ordinary skill in the art without creative effort are intended to fall within the scope of protection of the present invention.

[0066] See also Figure 1 In the first aspect, this embodiment provides an industrial park energy and carbon data visualization terminal 1, including a data acquisition module 11, a carbon emission calculation module 12, a display module 13, a communication module 14, a storage module 15 and a control module 16. The data acquisition module 11 is configured to collect power quality data in the industrial park in real time; the carbon emission calculation module 12 is configured to calculate carbon emission reduction based on power quality data and grid emission factors, generate carbon emission statistics, and update the carbon emission reduction to a historical trend chart; the display module 13 is configured to dynamically display power quality data, carbon emission statistics and historical trend charts; the communication module 14 supports industrial Ethernet, RS485 interface and IRIG-B code timing function, and is used to interact with external management systems for data; the storage module 15 is configured to store power quality data, carbon emission statistics and historical trend charts; the control module 16 integrates an ARM processor and a DSP data acquisition board, and is configured with a Linux embedded operating system to coordinate module operation logic and data processing.

[0067] In this embodiment, the industrial park energy and carbon data visualization terminal 1 implements full-process management of energy and carbon emissions through a modular architecture. The data acquisition module 11 converts physical signals into processable digital signals, providing raw data input for subsequent analysis. Specifically, based on the power quality data monitoring device, the data acquisition module 11 collects basic parameters of the industrial park power grid, such as three-phase voltage, current, frequency, and power, in real time, and ensures data consistency through synchronous sampling technology.

[0068] Preferably, the carbon emission calculation module 12 generates carbon emission statistical results based on the grid emission factor and renewable energy power generation using a mathematical mapping relationship, and dynamically associates the calculation results with the historical trend chart to form a carbon emission intensity change curve, the proportion of new energy power generation and other visual statistical results.

[0069] The display module 13 can dynamically display the real-time waveform of electric energy parameter information, harmonic spectrum distribution information and carbon emission statistics through a color LCD screen, support users to interactively query historical trends and abnormal event records, and provide an intuitive energy-carbon coupling status monitoring interface.

[0070] The communication module 14 uses industrial Ethernet and RS485 interfaces to establish a two-way data channel with the remote management system, supports real-time transmission of power quality data and reception of control instructions, and uses the IRIG-B code time synchronization function to ensure that the terminal clock is synchronized with the upper system and eliminate timestamp deviation.

[0071] Preferably, the storage module 15 saves the collected data, carbon emission statistics and event logs through an embedded storage medium, and adopts a circular storage strategy to manage the historical database to ensure the long-term traceability of key data.

[0072] The control module 16 realizes task division through the heterogeneous architecture of ARM processor and DSP data acquisition board. The ARM processor runs the Linux system and is responsible for logic scheduling and human-computer interaction, while the DSP data acquisition board focuses on high-speed signal processing and algorithm acceleration. The two work together to complete the full process closed loop from data acquisition to analysis and decision-making.

[0073] The energy-carbon data visualization terminal 1 of this embodiment achieves end-to-end connectivity for energy-carbon data. The high-precision measurements of the data acquisition module 11 provide reliable input for carbon emission calculations. The multi-dimensional visualization of the display module 13 reduces the threshold for data interpretation. The diversified interfaces of the communication module 14 adapt to complex industrial environments. The circular storage strategy of the storage module 15 balances data integrity and storage costs. The heterogeneous computing architecture of the control module 16 enhances the system's real-time responsiveness. The synergistic effect of these modules enables park managers to quickly identify energy efficiency bottlenecks, evaluate carbon reduction results, and provide data support for optimizing regulatory strategies, ultimately promoting the low-carbon and intelligent operation of industrial parks.

[0074] In some embodiments, the data acquisition module 11 is configured to use a LY-6640 type power quality monitoring device to achieve high-precision data acquisition, including a 16-bit synchronous sampling A / D converter, a hardware phase-locked loop circuit, and a multi-channel input interface. The sampling rate of the 16-bit synchronous sampling A / D converter is 51.2kHz, and 1024 points are sampled per cycle to ensure the acquisition accuracy of power quality data; the hardware phase-locked loop circuit is configured to track grid frequency changes in real time and dynamically adjust the sampling interval to prevent measurement errors caused by frequency leakage; the multi-channel input interface supports synchronous acquisition of 4 voltage and 12 current signals, and the voltage measurement range covers 5V-420V, and the current measurement range covers 5mA-6A.

[0075] In this embodiment, a 16-bit synchronous sampling A / D converter performs analog-to-digital conversion on the voltage and current signals at a sampling density of 1024 points per cycle, ensuring complete capture of the fundamental and harmonic components. Its synchronous sampling feature eliminates the phase deviation problem caused by traditional time-sharing sampling, providing a high-fidelity data source for subsequent harmonic analysis and power quality assessment.

[0076] The hardware phase-locked loop circuit monitors grid frequency fluctuations in real time and dynamically adjusts the sampling interval to track the actual operating frequency, avoiding spectrum leakage errors caused by frequency offset and ensuring the accuracy of harmonic measurement results.

[0077] The multi-channel input interface supports the parallel acquisition of 4 voltage and 12 current signals, covering a wide voltage range of 5V to 420V and a wide current range of 5mA to 6A. It adapts to the monitoring needs of different voltage levels and load types in industrial parks, and realizes the synchronous collection and integration of distributed energy, energy storage equipment and load-side data.

[0078] This embodiment ensures accurate harmonic measurement capabilities in scenarios with grid frequency fluctuations through the synergistic effect of a hardware phase-locked loop and synchronous sampling, reducing harmonic analysis errors under complex working conditions. The multi-channel input interface can meet the multi-node monitoring needs of complex campus power grids, supporting the synchronous acquisition of power quality parameters of equipment such as photovoltaic inverters, wind turbines, and energy storage converters, providing a full data basis for carbon emission calculations. The frequency tracking capability of the hardware phase-locked loop and the parallel processing mechanism of the multi-channel interface ensure real-time requirements in large-scale monitoring scenarios. The high-resolution characteristics of the 16-bit A / D converter, combined with a wide input range, take into account the accurate capture of weak signals and high-amplitude transient events, such as the complete recording of abnormal working conditions such as voltage surges and short interruptions, significantly improving the reliability and adaptability of the data acquisition module 11.

[0079] In some embodiments, the communication module 14 is configured to provide diversified data interaction channels, including dual 10 / 100Mbps industrial Ethernet interfaces, RS485 communication interfaces, IRIG-B code timing interfaces and USB2.0 host interfaces. The dual 10 / 100Mbps industrial Ethernet interfaces support IEC104 and Modbus-TCP protocols for communicating with external management systems; the RS485 communication interface supports custom protocols, and the communication rate can be configured to 4800 / 9600 / 19200bps; the IRIG-B code timing interface is configured to receive external time synchronization signals; and the USB2.0 host interface is configured to support external storage devices to export monitoring data in PQDIF format.

[0080] In this embodiment, the communication module 14 constructs a flexible data interaction channel through a diversified interface design.

[0081] The industrial Ethernet interface adopts a dual 10 / 100 Mbps rate configuration and supports IEC104 and Modbus-TCP protocols, enabling high-bandwidth, low-latency communication with the remote power quality management center (i.e., external management system), meeting the two-way interactive requirements of uploading real-time monitoring data and issuing control instructions.

[0082] The RS485 communication interface adapts to the communication standards of equipment from different manufacturers through custom protocols. The communication rate can be flexibly configured to 4800 / 9600 / 19200bps according to on-site network conditions, compatible with the access needs of legacy equipment. It also supports anti-interference characteristics for long-distance transmission, ensuring data reliability in the complex electromagnetic environment of the campus.

[0083] The IRIG-B code timing interface receives external time synchronization signals to accurately calibrate the terminal's internal clock, eliminating data timestamp deviations caused by clock drift and ensuring event timing consistency in multi-terminal collaborative monitoring scenarios.

[0084] The USB2.0 host interface provides plug-and-play functionality for external storage devices and supports the export of monitoring data in the PQDIF standard format, facilitating offline analysis or backup archiving, while also providing a convenient channel for system firmware upgrades.

[0085] This embodiment significantly improves the adaptability and scalability of the communication module 14. The complementary design of the industrial Ethernet and RS485 interfaces takes into account both high speed and reliability requirements. The IRIG-B code synchronization mechanism strengthens the timing consistency of multi-node collaborative monitoring, and the flexible access capability of the USB interface enhances the maintainability of the system. Through diversified data interaction channels, the energy carbon data visualization terminal 1 can be seamlessly integrated into the existing energy management system (i.e., external management system) of the industrial park, supporting cross-platform data sharing and remote operation and maintenance, and providing real-time and accurate data link guarantee for energy carbon collaborative optimization.

[0086] In some embodiments, the control module 16 is configured to use a heterogeneous computing architecture for data processing, including an ARM Cortex-A9 main processor, a TI TMS320F28335 DSP coprocessor, a distributed task scheduling mechanism and an event trigger management unit. The ARM Cortex-A9 main processor runs a Linux embedded operating system and is responsible for data calculation, statistical analysis and system scheduling; the TI TMS320F28335 DSP coprocessor is dedicated to FFT harmonic analysis and transient event detection algorithm acceleration; the distributed task scheduling mechanism is configured to coordinate the parallel execution of real-time data acquisition, historical data storage and communication transmission; the event trigger management unit is configured to automatically record a preset amount of waveform data before and after the event according to a preset threshold.

[0087] In this embodiment, control module 16 achieves both improved data processing efficiency and real-time performance through a heterogeneous computing architecture. The ARM Cortex-A9 main processor, running the Linux embedded operating system, is responsible for system-level task scheduling, data analysis, and human-computer interaction logic. This includes statistical calculations of power quality parameters, historical data management, and communication protocol parsing and execution. Its multi-threaded processing capabilities ensure the parallel processing requirements of complex business logic.

[0088] The TI TMS320F28335 DSP coprocessor is dedicated to high-speed signal processing tasks. It uses an optimized FFT algorithm to quickly decompose harmonic components and execute transient event detection algorithms, such as real-time identification of abnormal operating conditions such as voltage swells and short interruptions. Its hardware acceleration features significantly reduce computational latency.

[0089] The distributed task scheduling mechanism coordinates the concurrent execution of real-time data acquisition, historical data storage and communication transmission through priority division and dynamic resource allocation, avoids system congestion caused by task conflicts, and ensures the immediate response capability of key operations (such as event recording).

[0090] Based on preset threshold conditions (such as voltage deviation and harmonic distortion rate exceeding the limit), the event trigger management unit automatically captures the complete waveform data of the preset period before and after the event trigger, and generates an event log containing timestamp, event type and characteristic parameters, providing original data support for fault diagnosis and energy efficiency optimization.

[0091] The heterogeneous computing architecture decouples general-purpose computing from specialized acceleration tasks through the collaborative work of an ARM Cortex-A9 main processor and a TI TMS320F28335 DSP coprocessor. The flexibility of the ARM Cortex-A9 main processor and the real-time performance of the TI TMS320F28335 DSP coprocessor complement each other, meeting the complex demands of system-level management while ensuring efficient execution of signal processing algorithms. A distributed task scheduling mechanism optimizes system throughput through dynamic resource allocation. For example, it prioritizes the TI TMS320F28335 DSP coprocessor when harmonic analysis tasks are intensive, while emphasizing the network protocol processing capabilities of the ARM Cortex-A9 main processor when communication packets are frequently exchanged. The threshold-driven mechanism of the event trigger management unit reduces invalid data storage, retaining only critical waveform segments for abnormal events. This saves storage space and improves the targeted nature of post-event analysis. Through coordinated hardware and software optimization, the Energy Carbon Data Visualization Terminal 1 operates stably in high-load, real-time demanding industrial park environments, providing a low-latency, highly reliable data processing foundation for energy carbon coupled optimization.

[0092] See also Figure 2 In a second aspect, this embodiment further provides a working method of an industrial park energy and carbon data visualization terminal, which is applicable to the visualization terminal of the first aspect, and the method includes:

[0093] S101, collecting power quality data of the industrial park power grid in real time, where the power quality data includes voltage and current signals;

[0094] S102, digitally converting the power quality data to obtain a power processing signal, and dynamically tracking grid frequency changes and adjusting sampling parameters;

[0095] S103, performing spectrum analysis on the power processing signal to generate the content of each harmonic and the total harmonic distortion rate, and generating power parameter information;

[0096] S104. Calculate the renewable energy power generation based on the electric energy parameter information, simultaneously obtain the preset emission factor and calculate the real-time carbon emission reduction of the industrial park power grid;

[0097] S105. Generate carbon emission statistics based on the real-time carbon emission reduction, and display the power parameter information and carbon emission statistics;

[0098] S106. Storing the electric energy parameter information and carbon emission statistics in time series to obtain historical electric energy carbon emission data, and storing the data in a historical database;

[0099] S107, adopting a circular storage strategy to manage the historical database;

[0100] S108. Create an event log to record abnormal operating condition information.

[0101] In step S101, the data acquisition module collects the three-phase voltage and current signals of the industrial park power grid in real time, generating raw power quality data. The voltage signal covers a range of 5V to 420V, and the current signal ranges from 5mA to 6A, ensuring complete capture of power parameters at various nodes, including distributed photovoltaic and energy storage equipment.

[0102] In step S102, the power quality data is converted into a digital signal through the data acquisition module, and the grid frequency fluctuation is dynamically tracked. The sampling parameters are adjusted in real time to match the actual operating frequency to prevent harmonic measurement distortion caused by frequency offset.

[0103] In step S103, a Fast Fourier Transform (FFT) analysis is performed on the digitized power processing signal to decompose harmonic components from orders 2 to 65 and calculate the total harmonic distortion (THD). This generates power parameter information including harmonic content, phase angle, and fundamental wave parameters. The spectrum analysis process leverages the parallel computing capabilities of the DSP coprocessor to achieve millisecond-level response, ensuring real-time detection accuracy for transient events such as voltage sags. Harmonic components exceeding the specified limits are automatically flagged according to pre-set harmonic limit standards, creating a traceable anomaly record.

[0104] In step S104, based on the active power measurements in the electrical energy parameter information, a time-integrated calculation is performed on the generation of renewable energy sources such as photovoltaic and wind power. This calculation, combined with the mapping of grid emission factors, generates real-time carbon emission reductions. The new energy share indicator is dynamically updated by measuring the ratio of new energy generation to total electricity consumption, quantifying the park's clean energy penetration rate. The calculation results are linked to historical trend charts to generate visual statistical results such as carbon emission intensity and accumulated carbon credits, providing a quantitative basis for energy efficiency assessment.

[0105] In step S105, the power parameter information and carbon emission statistics are archived in time series through the storage module, and a circular storage strategy is adopted to automatically overwrite expired data to balance storage capacity and historical tracing requirements.

[0106] In steps S106 to S108, abnormal operating conditions such as voltage fluctuations and harmonic limit violations are marked through event log records, and the complete waveforms and characteristic parameters before and after the trigger are saved to support post-fault diagnosis and energy efficiency optimization strategy verification.

[0107] This implementation collaboratively integrates the entire process from data collection to decision support: dynamic frequency tracking and phase-locked loop technology ensure the accuracy of harmonic analysis, precise calculation of renewable energy generation provides reliable input for carbon emission reduction assessments, a cyclical storage strategy optimizes resource utilization, and the integrity of the event log enhances anomaly tracing capabilities. By displaying real-time data alongside historical trends, users can quickly identify energy efficiency bottlenecks, develop targeted low-carbon regulation strategies, and promote the transformation of industrial parks towards intelligent, zero-carbon operations.

[0108] See also Figure 3 In some embodiments, the electric energy parameter information includes three-phase voltage waveforms, three-phase current waveforms, voltage-current vector relationship diagrams, and harmonic spectrum distribution information. Displaying the electric energy parameter information and carbon emission statistics includes:

[0109] S201, dynamically displaying three-phase voltage waveforms, three-phase current waveforms, and a voltage-current vector relationship diagram, where the voltage-current vector relationship diagram is used to display the phase relationship between voltage and current;

[0110] S202. Displaying harmonic spectrum distribution information in a graphical form, the harmonic spectrum distribution information including spectrum analysis results of 2nd to 65th harmonic content and total harmonic distortion rate;

[0111] S203, updating the real-time carbon emission reduction amount into the historical database and generating a historical trend chart, the historical trend chart including a daily / weekly / monthly energy consumption data change curve and a carbon emission intensity change curve;

[0112] S204. Synchronously display the carbon emission statistics results, which include real-time carbon emission reduction, carbon credit accumulation value, and proportion of new energy power generation.

[0113] In step S201, the display module dynamically renders the real-time changes in the three-phase voltage and current waveforms. The waveforms are color-coded to distinguish between different phases, visually reflecting the grid's balance and load characteristics. A voltage-current vector diagram displays the amplitude and phase relationship of each phase's voltage and current in polar coordinates, revealing the power factor angle and reactive power distribution characteristics, helping users quickly identify phase shift or three-phase imbalance. A dynamic refresh mechanism ensures the real-time display of the three-phase voltage and current waveforms, as well as the voltage-current vector diagram, allowing users to switch channels or zoom in and out on the timeline for detailed analysis.

[0114] In step S202, preferably, the harmonic spectrum distribution information is displayed in the form of a bar graph showing the voltage and current content of harmonics 2-65 (i.e., the harmonic content of 2-65), with the horizontal axis marking the harmonic order and the vertical axis showing the percentage or effective value. The harmonic components exceeding the standard are highlighted by color. The total harmonic distortion rate is displayed in numerical form superimposed on the sidebar of the spectrum graph, providing a global assessment of the degree of harmonic pollution. Furthermore, the spectrum analysis results support switching between percentage and effective value display modes to adapt to analysis requirements in different scenarios, such as equipment compatibility testing or power quality compliance verification.

[0115] In step S203, the historical trend chart generates energy consumption data change curves and carbon emission intensity change curves at daily, weekly, and monthly granularities based on the time series data stored in the storage module. The energy consumption data change curve integrates indicators such as total active power measurement and renewable energy power generation, while the carbon emission intensity change curve correlates carbon emission reductions, accumulated carbon credits, and dynamic changes in the grid emission factor. The historical trend chart supports scrolling and time period filtering. By comparing historical peak values ​​with current values, managers can evaluate the effectiveness of energy efficiency improvement measures.

[0116] In step S204, carbon emission statistics are preferably displayed in real time on a dashboard, including real-time carbon emission reductions, accumulated carbon credits, and the proportion of renewable energy generation. Real-time carbon emission reductions are dynamically updated by multiplying renewable energy generation by the grid's emission factor. The proportion of renewable energy is visually displayed as a circular progress bar to show clean energy penetration, and accumulated carbon credits reflect the park's long-term carbon reduction efforts. Carbon emission statistics are linked to historical trend charts, allowing users to review detailed data by clicking on specific time points, supporting carbon trading decision-making and policy compliance reporting.

[0117] This embodiment transforms complex data into actionable insights through multi-dimensional visualization. Dynamic three-phase voltage and current waveforms, along with voltage-current vector diagrams, enhance intuitive perception of real-time operating conditions. Harmonic spectrum distribution information assists in locating pollution sources. Historical trend charts reveal long-term energy efficiency evolution patterns, and carbon emission statistics quantify carbon reduction effectiveness. This visualization lowers the threshold for data interpretation for non-professional users while satisfying the needs of technical personnel for detailed analysis. It provides comprehensive support for energy-carbon coordinated optimization in industrial parks, from real-time monitoring to strategic decision-making.

[0118] In some embodiments, the method further comprises:

[0119] Establish data communication connection with remote management system to realize real-time transmission of power quality data and carbon emission statistics;

[0120] Receive and respond to data query instructions and parameter configuration instructions issued by the remote management system;

[0121] Perform regular time synchronization and calibration to ensure that the terminal clock is consistent with the remote management system;

[0122] Real-time monitoring of grid operating conditions, identifying voltage fluctuations, flicker, and harmonic over-limit events;

[0123] Record the complete power quality data from before to after the abnormal event is triggered, and record it as abnormal record data;

[0124] Generate event log information containing event characteristic parameters based on abnormal record data;

[0125] Trigger local alarm indication and simultaneously send event alarm information to the remote management system;

[0126] Store event log information in the historical database, update event statistics records and display them.

[0127] In this embodiment, a data communication connection is established with a remote management system via a communication module, enabling real-time transmission of power quality data and carbon emission statistics. This data communication connection utilizes protocol encapsulation technology to package and upload collected power quality data in a pre-set format. It also receives data query commands (such as historical data retrieval requests) and parameter configuration commands (such as modifying harmonic thresholds) issued by the remote management system. The command response mechanism is implemented through the control module's parsing engine, ensuring immediate execution of operational commands and status feedback.

[0128] The Energy Carbon Data Visualization Terminal performs regular time synchronization calibration, receiving synchronization signals from an external clock source via an IRIG-B code timing interface and updating the local system clock to align the terminal clock with the time reference of the remote management system. Furthermore, the calibration process is embedded in periodic task scheduling to avoid event timing errors caused by clock drift during multi-terminal collaborative monitoring, ensuring accurate alignment of timestamps across data nodes.

[0129] The control module monitors the grid's operating conditions in real time and runs a transient event detection algorithm to identify voltage fluctuations, flicker, and harmonic over-limit events. Voltage fluctuation detection is based on preset swell / sag thresholds (e.g., 90%-110% of the rated value). Flicker analysis is performed by calculating the short-term flicker severity (Pst). Harmonic over-limit detection is performed by sequentially comparing the 2nd to 65th harmonic content against national standard limits.

[0130] When an abnormal event is triggered, the event trigger management unit automatically records the complete power quality data from 5 cycles before the trigger to 5 cycles after the trigger, saves it as abnormal record data, and extracts event characteristic parameters (such as duration, amplitude deviation, and harmonic number).

[0131] Event log information is generated based on abnormal record data, including event type, trigger time, characteristic parameters and associated waveform segment index, and is written into the historical database through formatted storage rules.

[0132] The local alarm indication is activated by the panel LED signal light. Preferably, the red indicator light indicates a serious limit-exceeding event, and the yellow indicator light indicates a warning state. At the same time, the communication module sends event alarm information to the remote management system, including event summary and priority tags, to support remote operation and maintenance personnel to quickly intervene and handle it.

[0133] This embodiment strengthens the real-time response capability to abnormal operating conditions through a closed-loop management mechanism. By completely recording the full life cycle data of abnormal events, the energy carbon data visualization terminal provides a traceable data basis for the reliability analysis and preventive maintenance of the energy carbon system in the industrial park.

[0134] In some embodiments, dynamically tracking grid frequency changes and adjusting sampling parameters includes:

[0135] Calculate the actual operating frequency of the current power grid based on the voltage signal in the electric energy parameter information;

[0136] Calculate the difference between the actual operating frequency and the preset rated frequency to generate a frequency deviation value;

[0137] Adjusting the sampling time interval of the analog-to-digital converter according to the frequency deviation value so that the sampling rate of the analog-to-digital converter is synchronized with the actual operating frequency change;

[0138] Maintain a sampling mode with a fixed number of sampling points per cycle;

[0139] Perform frequency compensation calculation on the power processing signal to correct the harmonic measurement error caused by frequency fluctuation;

[0140] When the frequency deviation value exceeds a preset threshold, the sampling parameters are reconfigured and the digital phase-locked loop settings are updated.

[0141] In this embodiment, the control module calculates the actual operating frequency of the current power grid. Frequency dynamics are acquired in real time by continuously monitoring the zero-crossing intervals of the voltage waveform or using the output of a digital phase-locked loop (DPL). The actual operating frequency reflects the instantaneous state of the power grid. Fluctuations in the actual operating frequency can be caused by sudden load changes or fluctuations in the output of distributed energy resources, directly impacting harmonic measurement accuracy and sampling synchronization.

[0142] The frequency deviation value is calculated by calculating the difference between the actual operating frequency and the preset rated frequency. The sign of the frequency deviation value indicates the direction of the frequency deviation (above or below the rated value), and the absolute value quantifies the degree of deviation. The frequency deviation value is used to compensate for sampling interval mismatch caused by frequency fluctuations and ensure data integrity at a fixed number of sampling points per cycle.

[0143] The sampling time interval of the analog-to-digital converter is adjusted according to the frequency deviation value. Its dynamic adjustment mechanism is achieved through feedback control of the digital phase-locked loop. For example, the sampling interval is shortened when the frequency increases, and the interval is extended when the frequency decreases, maintaining a fixed sampling density of 1024 points per cycle, thereby eliminating harmonic spectrum leakage caused by frequency offset and avoiding calculation distortion of harmonic amplitude and phase angle.

[0144] Frequency compensation is calculated for the power processing signal. Preferably, the compensation algorithm performs phase correction and amplitude weighting on the FFT analysis results based on the frequency deviation value to restore the true harmonic component characteristics. When the frequency deviation value exceeds a preset threshold, the sampling parameters are reconfigured and the tracking coefficient of the digital phase-locked loop is updated to forcibly synchronize the sampling rate with the actual power grid frequency, preventing irreversible data distortion caused by cumulative errors.

[0145] This embodiment ensures data accuracy under complex working conditions through closed-loop frequency tracking and dynamic sampling adjustment, enabling the terminal to adapt to grid frequency fluctuations caused by a high proportion of new energy access, ensuring the long-term data credibility of carbon emission calculations and energy efficiency assessments, and providing a stable and reliable data foundation for the coordinated optimization of power generation, grid, load and storage in industrial parks.

[0146] In some embodiments, calculating the renewable energy generation amount based on the electric energy parameter information includes:

[0147] Extracting active power measurement values ​​from the electric energy parameter information, where the active power measurement values ​​include photovoltaic power generation active power and wind power generation active power;

[0148] Perform time integration calculation on the active power measurement value to obtain photovoltaic power generation and wind power generation;

[0149] Perform logical operations on photovoltaic power generation and wind power generation to obtain the total power generation of renewable energy;

[0150] Converting total renewable energy generation into equivalent carbon emission reductions based on preset grid emission factors;

[0151] Calculate the real-time new energy proportion index based on the ratio of total renewable energy power generation to total electricity consumption;

[0152] Generate carbon emission statistics based on equivalent carbon emission reduction and new energy proportion indicators.

[0153] In this embodiment, the active power of photovoltaic power generation is calculated through the output voltage, current and power factor of the photovoltaic inverter, and the active power of wind power generation is obtained based on the real-time output curve of the wind turbine and the measurement data on the grid side. Both use high-precision sensors and synchronous sampling technology to ensure data credibility.

[0154] The time integration process accumulates active power values ​​at fixed time steps (e.g., 1 minute) to generate hourly, daily, and monthly power generation statistics. Total renewable energy generation is calculated by logically adding photovoltaic and wind power generation to form a quantitative indicator of the park's total clean energy supply.

[0155] The conversion process for converting total renewable energy generation into equivalent carbon emissions reductions uses the carbon emissions of replacing traditional thermal power with green electricity as a benchmark. The carbon dioxide emissions reduction per kilowatt-hour of electricity generated (e.g., 0.5942 kgCO2 / kWh) is multiplied by total power generation to generate real-time carbon reduction data. The new energy share indicator is calculated as the ratio of total renewable energy generation to total campus electricity consumption, dynamically reflecting the penetration of renewable energy in overall energy consumption as a percentage.

[0156] Carbon emissions statistics integrate equivalent carbon reductions, new energy share indicators, and historical cumulative data to form a comprehensive report that includes real-time carbon reduction achievements, accumulated carbon credits, and clean energy contribution. Statistics are updated in real time through the display module's visual interface and linked to historical trend charts, allowing users to evaluate carbon efficiency performance over time.

[0157] This implementation converts power generation data into quantifiable carbon reduction indicators through precise mapping of renewable energy metering and carbon emissions. Time-integrated calculations ensure the continuity of power generation statistics, logical operations integrate multi-energy data, and preset grid emission factors provide a standardized carbon efficiency assessment benchmark. This enables the park to track clean energy contributions in real time, providing data support for carbon trading and energy efficiency optimization strategy formulation.

[0158] In some embodiments, spectrum analysis is performed on the power processing signal to generate the harmonic content and total harmonic distortion rate, and the generated power parameter information includes:

[0159] Perform fast Fourier transform on the power processing signal to decompose it into harmonic components;

[0160] Calculate the content rate of 2-65 harmonic voltage and current and generate harmonic content distribution information;

[0161] According to each harmonic component, calculate the voltage harmonic distortion rate and current harmonic distortion rate, and record it as the total harmonic distortion rate;

[0162] and, identifying each harmonic component and marking the harmonic component exceeding a preset harmonic limit as excessive harmonic information;

[0163] Integrate harmonic content distribution information, total harmonic distortion rate and excessive harmonic information into power quality parameters;

[0164] Power parameter information is generated according to the power quality parameters.

[0165] In this embodiment, a Fast Fourier Transform (FFT) is performed on the power processing signal to decompose the time-domain voltage and current signals into frequency-domain harmonic components. Fast Fourier Transform, accelerated by a DSP coprocessor, performs spectrum analysis, covering the amplitude and phase information of harmonics from the 2nd to the 65th order. This eliminates interference from fundamental frequency fluctuations on harmonic measurement and ensures accurate extraction of high-frequency harmonic components.

[0166] The harmonic voltage and current content is expressed as a percentage of each harmonic relative to the fundamental, while the effective value mode directly reflects the actual amplitude of the harmonic components. The analysis results are then verified against national standard limits using a threshold comparison module. Harmonic components exceeding the preset limits are marked, and a list of exceeded harmonic components is generated, including the number of violations, amplitude, and duration.

[0167] Total harmonic distortion (THD) is determined by taking the square root of the sum of the squares of the harmonic amplitudes and dividing it by the fundamental amplitude, quantifying the overall level of harmonic pollution. This calculation, combined with information on harmonic content distribution and excessive harmonics, forms a comprehensive power quality parameter, encompassing spectral characteristics, compliance status, and anomaly markers.

[0168] This embodiment transforms complex harmonic data into actionable assessment conclusions through refined spectrum analysis and an over-standard marking mechanism. Fast Fourier transforms ensure the ability to capture high-frequency harmonics, harmonic content calculations provide a basis for locating pollution sources, and the total harmonic distortion rate (THD) indicator enables a global quantitative assessment of power quality. Automatic marking of over-standard harmonic information simplifies the compliance inspection process, provides targeted governance guidance for operations and maintenance personnel, and assists in harmonic suppression and energy efficiency optimization of industrial park power grids, reducing equipment losses and carbon emissions caused by harmonic overloads.

[0169] By using the above technical solution, the present invention is different from the prior art and has the following beneficial effects:

[0170] The above technical solution provides an industrial park energy and carbon data visualization terminal and its working method. The terminal includes a data acquisition module, a carbon emission calculation module, a display module, a communication module, a storage module and a control module. The data acquisition module collects power quality data of the power grid in real time; the carbon emission calculation module maps the power data to a carbon emission reduction indicator based on the power grid emission factor, and dynamically updates the historical trend chart; the display module dynamically displays the power quality data, carbon emission statistics and historical trend chart; the communication module supports industrial Ethernet, RS485 interface and IRIG-B code timing function to achieve data interaction with the external management system; the storage module adopts a cyclic strategy to manage power parameters and carbon emission data; the control module integrates an ARM processor and a DSP data acquisition board, and runs a Linux system to coordinate data acquisition, processing and communication tasks. The present invention realizes end-to-end connection of energy and carbon data through a modular architecture, supports real-time monitoring, historical tracing and abnormal alarms, provides visual data support for energy efficiency optimization and carbon emission reduction decision-making in industrial parks, and helps low-carbon operations.

[0171] In addition, the functional units in various embodiments of the present invention may be integrated into a single processing unit, each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0172] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) or a processor to execute all or part of the steps of the various embodiments of the present invention. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0173] The above descriptions are only some embodiments of the present invention and do not limit the scope of protection of the present invention. Any equivalent device or equivalent process transformation made by using the contents of the description and drawings of the present invention, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. An industrial park energy and carbon data visualization terminal, characterized by: include: A data acquisition module is configured to collect power quality data within the industrial park in real time; a carbon emission calculation module configured to calculate carbon emission reductions based on power quality data and grid emission factors, generate carbon emission statistics, and update the carbon emission reductions into a historical trend chart; A display module is configured to dynamically display power quality data, carbon emission statistics and historical trend charts; Communication module, supporting industrial Ethernet, RS485 interface and IRIG-B code timing function, used for data exchange with external management systems; The storage module is configured to store power quality data, carbon emission statistics and historical trend graphs; The control module integrates an ARM processor and a DSP data acquisition board, and is configured with a Linux embedded operating system to coordinate module operation logic and data processing.

2. The industrial park energy and carbon data visualization terminal according to claim 1 is characterized in that: The data acquisition module is configured to use the LY-6640 power quality monitoring device to achieve high-precision data acquisition, including: 16-bit synchronous sampling A / D converter with a sampling rate of 51.2kHz and 1024 points per cycle to ensure the accuracy of power quality data collection; A hardware phase-locked loop circuit is configured to track grid frequency changes in real time and dynamically adjust the sampling interval to prevent measurement errors caused by frequency leakage; Multi-channel input interface supports simultaneous acquisition of 4-channel voltage and 12-channel current signals. The voltage measurement range covers 5V-420V, and the current measurement range covers 5mA-6A.

3. The industrial park energy and carbon data visualization terminal according to claim 1 is characterized in that: The communication module is configured to provide diversified data interaction channels, including: Dual 10 / 100Mbps industrial Ethernet interfaces, supporting IEC104 and Modbus-TCP protocols, for communication with external management systems; RS485 communication interface, supports custom protocols, and the communication rate can be configured to 4800 / 9600 / 19200bps; IRIG-B code timing interface, configured to receive external time synchronization signals; The USB2.0 host interface is configured to support external storage devices to export monitoring data in PQDIF format.

4. The industrial park energy and carbon data visualization terminal according to claim 1 is characterized in that: The control module is configured to use a heterogeneous computing architecture for data processing, including: ARM Cortex-A9 main processor, running the Linux embedded operating system, responsible for data calculation, statistical analysis and system scheduling; TI TMS320F28335 DSP coprocessor, dedicated to FFT harmonic analysis and transient event detection algorithm acceleration; A distributed task scheduling mechanism is configured to coordinate the parallel execution of real-time data collection, historical data storage, and communication transmission; The event trigger management unit is configured to automatically record a preset amount of waveform data before and after the event according to a preset threshold.

5. A working method of an industrial park energy and carbon data visualization terminal, characterized in that: The visualization terminal according to any one of claims 1 to 4, wherein the method comprises: Real-time collection of power quality data of the industrial park power grid, including voltage and current signals; Digitally converting the power quality data to obtain a power processing signal, and dynamically tracking grid frequency changes and adjusting sampling parameters; Performing spectrum analysis on the electric energy processing signal to generate the content of each harmonic and the total harmonic distortion rate, and generating electric energy parameter information; Calculate renewable energy generation based on power parameter information, simultaneously obtain preset emission factors and calculate real-time carbon emission reductions for the industrial park power grid; Generate carbon emission statistics according to the real-time carbon emission reduction, and display the electric energy parameter information and the carbon emission statistics; The electric energy parameter information and carbon emission statistics are stored in a time series to obtain historical electric energy carbon emission data, and stored in a historical database; Use a circular storage strategy to manage the historical database; Establish an event log to record abnormal operating conditions information.

6. The working method of the industrial park energy and carbon data visualization terminal according to claim 5 is characterized in that: The electric energy parameter information includes three-phase voltage waveforms, three-phase current waveforms, voltage-current vector relationship diagrams, and harmonic spectrum distribution information. Displaying the electric energy parameter information and the carbon emission statistical results includes: Dynamically display three-phase voltage waveforms, three-phase current waveforms, and a voltage-current vector diagram, wherein the voltage-current vector diagram is used to show the phase relationship between voltage and current; Displaying harmonic spectrum distribution information in a graphical form, including spectrum analysis results of 2nd to 65th harmonic content and total harmonic distortion; Update the real-time carbon emission reduction data to the historical database and generate a historical trend chart, which includes a daily / weekly / monthly energy consumption data change curve and a carbon emission intensity change curve; Carbon emission statistics are displayed simultaneously, including real-time carbon emission reduction, accumulated carbon credit value and proportion of new energy power generation.

7. The working method of the industrial park energy and carbon data visualization terminal according to claim 5 is characterized in that: The method further comprises: Establish data communication connection with remote management system to realize real-time transmission of power quality data and carbon emission statistics; Receive and respond to data query instructions and parameter configuration instructions issued by the remote management system; Perform regular time synchronization and calibration to ensure that the terminal clock is consistent with the remote management system; Real-time monitoring of grid operating conditions, identifying voltage fluctuations, flicker, and harmonic over-limit events; Record the complete power quality data from before to after the abnormal event is triggered, and record it as abnormal record data; Generating event log information including event characteristic parameters according to the abnormal record data; Trigger local alarm indication and simultaneously send event alarm information to the remote management system; Store event log information in the historical database, update event statistics records and display them.

8. The working method of the industrial park energy and carbon data visualization terminal according to claim 5 is characterized in that: Dynamically tracking grid frequency changes and adjusting sampling parameters include: Calculating the actual operating frequency of the current power grid based on the voltage signal in the electric energy parameter information; Calculating the difference between the actual operating frequency and the preset rated frequency to generate a frequency deviation value; Adjusting the sampling time interval of the analog-to-digital converter according to the frequency deviation value so that the sampling rate of the analog-to-digital converter is synchronized with the actual operating frequency change; Maintain a sampling mode with a fixed number of sampling points per cycle; Performing frequency compensation calculation on the electric energy processing signal to correct harmonic measurement errors caused by frequency fluctuations; When the frequency deviation value exceeds a preset threshold, sampling parameters are reconfigured and digital phase-locked loop settings are updated.

9. The working method of the industrial park energy and carbon data visualization terminal according to claim 5 is characterized in that: Calculating renewable energy generation based on electric energy parameter information includes: Extracting active power measurement values ​​from the electric energy parameter information, the active power measurement values ​​including photovoltaic power generation active power and wind power generation active power; Performing time integration calculation on the active power measurement value to obtain photovoltaic power generation and wind power generation; Performing a logical operation on the photovoltaic power generation and the wind power generation to obtain a total renewable energy power generation; Converting the total renewable energy power generation into equivalent carbon emission reductions based on a preset grid emission factor; Calculate the real-time new energy proportion index based on the ratio of the total renewable energy power generation to the total electricity consumption; Generate carbon emission statistics based on the equivalent carbon emission reduction and new energy proportion indicators.

10. The working method of the industrial park energy and carbon data visualization terminal according to claim 5 is characterized in that: Performing spectrum analysis on the power processing signal to generate the harmonic content and total harmonic distortion rate, and generating power parameter information including: Perform fast Fourier transform on the power processing signal to decompose it into harmonic components; Calculate the content rate of 2-65 harmonic voltage and current and generate harmonic content distribution information; Calculating the voltage harmonic distortion rate and the current harmonic distortion rate based on the harmonic components, and recording them as the total harmonic distortion rate; and, identifying each harmonic component and marking the harmonic component exceeding a preset harmonic limit as excessive harmonic information; Integrate harmonic content distribution information, total harmonic distortion rate and excessive harmonic information into power quality parameters; The power parameter information is generated according to the power quality parameter.

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