Energy-saving power management method of an electric energy metering box and electric energy metering box

Abstract

The present application relates to the technical field of energy-saving management and control of electric energy metering equipment, and particularly relates to an energy-saving power consumption management method of an electric energy metering box and the electric energy metering box, comprising the following steps: S1, a data acquisition module acquires running parameters of the electric energy metering box in real time; S2, a data processing and analysis module performs preprocessing and threshold comparison analysis on the acquired running parameters; S3, an intelligent energy-saving management and control module executes a hierarchical energy-saving control strategy according to a working condition recognition result; and S4, a state monitoring and tracing module records an energy-saving control process and equipment running data in real time. The present application adopts a modular architecture design, executes differential management and control for various working conditions such as no-load, high temperature, overload and normal operation through a hierarchical energy-saving control strategy, reduces invalid energy consumption without affecting metering accuracy and equipment safety, realizes precise energy-saving management and control of the electric energy metering box under multiple working conditions and multiple environments, reduces redundant energy consumption of power distribution terminal equipment, and improves the economy and stability of the operation of the intelligent metering box.

Description

Technical Field

[0001] This invention relates to the field of energy-saving management technology for electricity metering equipment, specifically to an energy-saving electricity management method for an electricity metering box and the electricity metering box itself. Background Technology

[0002] Electricity metering boxes are core equipment in power system distribution terminals, primarily housing electricity metering devices, switch protection devices, communication modules, and auxiliary cooling equipment. They are widely used in various electricity consumption scenarios, including residential communities, commercial buildings, industrial parks, and municipal power distribution, playing a crucial role in electricity metering, line protection, and electricity data collection and transmission. With the continuous advancement of smart grid construction, intelligent electricity metering boxes are gradually becoming more widespread. Compared to traditional metering boxes, intelligent metering boxes integrate multiple functions such as wireless communication, real-time data acquisition, remote meter reading, and status monitoring, significantly improving equipment integration.

[0003] Currently, existing smart electricity metering boxes generally suffer from excessive ineffective energy consumption and a lack of energy-saving management capabilities during actual operation. Firstly, the communication, heat dissipation, indicator lights, and auxiliary power supply modules inside these boxes operate at full rated power for extended periods. Regardless of whether the metering box is in idle, light-load, or full-load operation, it maintains a fixed power output. This results in significant ineffective energy consumption during off-peak hours at night, when users leave the equipment vacant for extended periods, or when the equipment is in standby or hibernation mode, leading to serious waste of electricity resources over time. Secondly, the operating environment of these metering boxes is complex. Outdoor and corridor-deployed metering boxes are susceptible to changes in ambient temperature and humidity. In high-temperature environments, the heat dissipation equipment frequently starts and stops, operating at full load continuously, further exacerbating energy loss. In low-temperature and high-humidity environments, equipment malfunctions and abnormal power consumption fluctuations are likely to occur. Existing equipment cannot adaptively adjust power consumption based on environmental parameters.

[0004] Third, existing electricity metering boxes lack precise mechanisms for identifying and quantifying ineffective energy consumption. They can only provide simple overvoltage and overcurrent fault alarms, failing to distinguish between effective working energy consumption and ineffective redundant energy consumption. This makes it difficult to accurately identify hidden energy consumption faults such as no-load energy consumption, abnormal standby, and excessive power consumption at high temperatures, resulting in a large amount of hidden energy loss going unaddressed. Fourth, the control strategies of traditional metering boxes are fixed and cannot dynamically optimize control parameters based on seasonal environmental changes, user electricity usage habits, and equipment aging status. This leads to poor energy-saving adaptability and unsatisfactory long-term energy-saving effects. Furthermore, the traceability of existing equipment operating data is poor, and there are no complete log records of the energy-saving control process, hindering power maintenance personnel from conducting energy consumption statistics, equipment maintenance, and energy-saving optimization and rectification work.

[0005] In summary, existing technologies suffer from several technical deficiencies, including low levels of intelligence in energy consumption management, large amounts of ineffective energy consumption, poor accuracy in identifying operating conditions, inability to adaptively iterate management strategies, and lack of data traceability capabilities. These deficiencies fail to meet the development needs of smart grids for refined energy conservation, intelligent management, and low-energy operation. Therefore, there is an urgent need to design an energy-saving electricity management method and supporting equipment for electricity metering boxes that can accurately quantify ineffective energy consumption, implement hierarchical adaptive energy conservation, and employ dynamic iterative optimization strategies. Summary of the Invention

[0006] The purpose of this invention is to provide an energy-saving power management method for an electricity metering box and an electricity metering box in order to solve the above-mentioned problems. The method adopts a modular architecture design and implements a hierarchical energy-saving control strategy to perform differentiated control for various operating conditions such as no-load, high temperature, overload, and normal operation. Without affecting the metering accuracy and equipment safety, it reduces ineffective energy consumption, realizes precise energy-saving control of the electricity metering box under multiple operating conditions and environments, reduces redundant energy consumption of power distribution terminal equipment, and improves the economy and stability of the smart metering box operation, as detailed below.

[0007] To achieve the above objectives, the present invention provides the following technical solution: This invention provides an energy-saving electricity management method for an electricity metering box, comprising the following steps: S1. The data acquisition module collects the operating parameters of the power metering box in real time. The operating parameters include the internal temperature and humidity of the box, the incoming line voltage, the outgoing line current, the real-time power consumption, the equipment operating status, and the box opening and closing status. S2, the data processing and analysis module preprocesses and performs threshold comparison analysis on the collected operating parameters, removes abnormal interference data, calculates the real-time invalid energy consumption of the box through the preset energy consumption judgment formula, matches the preset energy-saving control threshold model, and identifies the no-load energy consumption, overload operation, abnormal standby and high-temperature power consumption abnormal conditions of the power metering box. S3, the intelligent energy-saving control module executes a graded energy-saving control strategy based on the operating condition identification results, and adaptively adjusts the power consumption of the power supply module, heat dissipation module and communication module inside the metering box; S4, the status monitoring and traceability module, records the energy-saving control process and equipment operation data in real time, generates energy-saving logs, and uploads them synchronously to the back-end management terminal. At the same time, it monitors the operating status of the enclosure in real time and triggers early warning prompts under abnormal operating conditions.

[0008] Preferably, in step S2, the threshold model includes an unloaded power consumption threshold, an overload current threshold, a high temperature threshold for the enclosure, and a standby power consumption threshold. The preprocessing includes data filtering, numerical calibration, and timing alignment. Through multi-dimensional parameter linkage comparison, it accurately distinguishes between normal operation, mild energy consumption anomalies, and severe energy consumption fault conditions. The energy consumption determination formula is as follows: ; in, This represents the real-time ineffective energy consumption of the electricity metering box, in Wh. The total real-time operating power consumption of the enclosure is expressed in watts (W). This represents the rated effective power consumption of the enclosure under current operating conditions, in watts (W). This refers to the data collection duration, expressed in hours (h). This represents the energy consumption compensation correction value corresponding to ambient temperature and humidity, in Wh.

[0009] Preferably, the graded energy-saving control strategy in step S3 specifically includes: When an idle standby condition is detected, the transmission power of the communication module is reduced and the power supply of redundant indicator lights is turned off to maintain the low-power standby of the metering core module. When the high temperature condition of the enclosure is detected, the start-stop frequency and operating power of the heat dissipation module are adaptively adjusted to avoid the heat dissipation equipment from consuming power at full load continuously. When an overload abnormal operating condition is detected, the abnormal energy consumption branch is locked first, and an energy limiting control command is issued, while the core metering function is kept running normally. When the equipment is running normally and stably, it maintains the rated low-power operation of each module to ensure metering accuracy while reducing ineffective energy consumption.

[0010] As a preferred option, step S5 is also included: the adaptive calibration update module dynamically iterates and optimizes the energy-saving control threshold model based on historical energy-saving logs and seasonal environmental parameters to adapt to the energy-saving control needs of different time periods and environments.

[0011] The present invention also provides an energy metering box, which applies the energy-saving power management method described above. The box body includes a data acquisition module, a data processing and analysis module, an intelligent energy-saving control module, a status monitoring and traceability module, and an adaptive calibration and update module integrated inside the box body. The data acquisition module is used to collect real-time operating data such as internal temperature and humidity, power supply parameters, equipment operating status and opening and closing status of the enclosure, and transmit the collected data to the data processing and analysis module in real time. The data processing and analysis module is electrically connected to the data acquisition module and the intelligent energy-saving control module, respectively, and is used to preprocess the acquired data, screen for anomalies and identify operating conditions, and output corresponding energy-saving control commands. The intelligent energy-saving control module is electrically connected to the power supply equipment, heat dissipation equipment, and communication equipment inside the enclosure, and is used to receive control commands and perform hierarchical adaptive energy-saving power consumption adjustment. The status monitoring and traceability module is used to record equipment operation data and energy-saving control records throughout the process, generate traceable energy-saving logs, and simultaneously realize abnormal operating condition early warning and data upload. The adaptive calibration update module is used to dynamically update the energy-saving management threshold model and optimize the energy-saving management strategy based on historical operating data and environmental parameters.

[0012] Preferably, the data acquisition module includes a temperature and humidity acquisition subunit, a power parameter acquisition subunit, and a status sensing subunit; the temperature and humidity acquisition subunit is used to acquire temperature and humidity data of the internal environment of the enclosure; the power parameter acquisition subunit is used to acquire incoming voltage, outgoing current, and real-time power consumption parameters; the status sensing subunit is used to acquire the opening and closing status of the enclosure and the start and stop status of each electrical module.

[0013] Preferably, the intelligent energy-saving control module includes a power supply control subunit, a heat dissipation control subunit, and a communication power consumption control subunit; the power supply control subunit is used to control the on / off state and power supply of redundant power supply circuits inside the enclosure; the heat dissipation control subunit is used to adjust the operating power and start / stop frequency of the cooling fan and heat sink temperature control equipment; the communication power consumption control subunit is used to adaptively adjust the transmission power and operating frequency of the wireless and wired communication modules.

[0014] Preferably, the data processing and analysis module includes a built-in data filtering unit, a threshold comparison unit, and a working condition identification unit. The data filtering unit is used to filter out pulse interference and abnormal numerical data in the collected data. The threshold comparison unit is used to compare the preprocessed data with a preset threshold model. The working condition identification unit is used to accurately determine no-load, overload, high-temperature, and abnormal standby power consumption conditions.

[0015] Preferably, the system also includes a local storage module and a wireless communication module. The local storage module is used to cache operating data and energy-saving logs locally, and the wireless communication module is used to establish data interaction with the background management terminal to realize remote data upload and remote energy-saving parameter configuration.

[0016] Preferably, the system also includes an audible and visual early warning module, which is electrically connected to the data processing and analysis module. This module is used to trigger an audible and visual early warning when a severe energy consumption fault or abnormal equipment operation is detected, so as to remind maintenance personnel to investigate and handle the issue in a timely manner.

[0017] The beneficial effects are as follows: 1. By quantifying the real-time invalid energy consumption of the power metering box, this invention solves the technical problem that traditional equipment can only qualitatively judge faults and cannot quantitatively count redundant energy consumption, thereby realizing the identification and quantitative statistics of abnormal energy consumption and providing data support for refined energy-saving management and control.

[0018] 2. This invention adopts a modular architecture design, with each functional module having a clear division of labor and working together to adapt to intelligent systems. At the same time, through a graded energy-saving control strategy, it implements differentiated control for various operating conditions such as no-load, high temperature, overload, and normal operation, reducing ineffective energy consumption and improving energy-saving effect without affecting metering accuracy and equipment safety.

[0019] 3. This invention has adaptive strategy iterative optimization capabilities, and can dynamically update the energy-saving threshold model according to seasonal environmental changes and historical operating data, solving the problems of rigid and poor adaptability of traditional equipment management strategies, and greatly improving long-term energy-saving stability and adaptability.

[0020] 4. This invention enables the traceability storage and uploading of equipment operation data, energy-saving control records, and abnormal operating condition data, and has data traceability and early warning capabilities. It facilitates power operation and maintenance departments to carry out energy consumption statistics, equipment operation and maintenance, and energy-saving optimization and rectification, and is adapted to the needs of refined operation and maintenance management of smart grids.

[0021] 5. The present invention has a simple overall structure, high integration, and low transformation cost. It can be directly adapted to the transformation and upgrading of existing smart energy metering boxes, has a wide range of applicable scenarios, and has the advantages of economy, practicality and intelligence, making it convenient for market promotion. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a system flowchart of the present invention; Figure 2 This is a block diagram of the modular hardware system architecture of the power metering box of the present invention; Figure 3 This is a logic block diagram of the graded energy-saving control strategy of the present invention. Detailed Implementation

[0024] The technical solutions of the embodiments of this application will be clearly described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0025] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0026] See Figures 1-3 As shown, the present invention provides an energy-saving electricity management method for an electricity metering box, comprising the following steps: S1. The data acquisition module collects the full-domain operating parameters of the power metering box in real time according to a preset fixed acquisition cycle. In this embodiment, the preferred acquisition cycle is 1 second, which can be adaptively adjusted to the range of 0.5 seconds to 3 seconds according to the on-site operation and maintenance accuracy requirements. This effectively ensures the real-time performance, continuity and timing alignment of the data acquisition. The operating parameters include the internal temperature and humidity of the box, the incoming line voltage, the outgoing line current, the real-time power consumption, the equipment operating status and the box opening and closing status. The box opening and closing status is used to determine whether the metering box is open for electricity theft, maintenance and repair, abnormal box sealing, etc., to help correct the energy-saving control logic, avoid the accidental triggering of low-power energy-saving strategies during the opening and repair process, and ensure the safety of equipment operation and maintenance. S2. The data processing and analysis module preprocesses and performs threshold comparison analysis on the collected operating parameters, removes abnormal interference data, calculates the real-time invalid energy consumption of the box through a preset energy consumption judgment formula, matches the preset energy-saving control threshold model, and identifies the no-load energy consumption, overload operation, abnormal standby, and high-temperature power consumption abnormal conditions of the power metering box. Due to external factors such as electromagnetic interference, voltage fluctuations, and instantaneous pulse interference in the on-site power distribution environment, there may be abnormal problems such as distortion, jumps, and over-range in the single data collection. This step uses a multi-layer data preprocessing mechanism to filter effective data from the time-series data collection, providing a reliable data base for subsequent invalid energy consumption quantification calculation and accurate judgment of operating conditions, and solving the defects of traditional energy-saving control methods that rely on a single parameter for judgment, resulting in large errors and high misjudgment rates. S3. The intelligent energy-saving control module executes a graded energy-saving control strategy based on the operating condition identification results. It adaptively adjusts the power supply module, heat dissipation module and communication module inside the metering box. Compared with the traditional metering box's fixed power and constant operation mode, this invention adopts the control logic of operating condition identification, graded matching and on-demand power consumption. It matches differentiated power consumption strategies for different operating scenarios. Under the premise of strictly ensuring the accuracy of power metering, the reliability of data transmission and the safety of equipment operation, it reduces the redundant and ineffective energy consumption generated by the long-term operation of the equipment. The S4 status monitoring and traceability module records the energy-saving control process and equipment operation data in real time, generates energy-saving logs, and uploads them synchronously to the back-end management terminal. At the same time, it monitors the operating status of the metering box in real time and triggers early warning prompts under abnormal operating conditions. Through full-process data recording and status traceability, it enables the metering box's energy consumption data, control actions, abnormal events, and equipment status to be searchable, traceable, and statistically analyzed. This provides complete data support for power operation and maintenance personnel to conduct energy consumption analysis, equipment fault diagnosis, energy-saving effect evaluation, and operation and maintenance ledger establishment, solving the problems of traditional equipment lacking operation logs, inability to quantify energy-saving effects, and difficulty in fault traceability.

[0027] As an optional implementation, in step S2, the threshold model includes an idle power consumption threshold, an overload current threshold, a high temperature threshold for the enclosure, and a standby power consumption threshold. The preprocessing includes data filtering, numerical calibration, and timing alignment. Through multi-dimensional parameter linkage comparison, it accurately distinguishes between normal operation, mild energy consumption anomalies, and severe energy consumption fault conditions. The energy consumption determination formula is as follows: ; in, This represents the real-time ineffective energy consumption of the electricity metering box, in Wh. The total real-time operating power consumption of the enclosure is expressed in watts (W). This represents the rated effective power consumption of the enclosure under current operating conditions, in watts (W). This refers to the data collection duration, expressed in hours (h). The energy consumption compensation correction value corresponding to ambient temperature and humidity is expressed in Wh. Among them, the data filtering adopts a dual filtering algorithm of median filtering and mean filtering to filter out abnormal data caused by instantaneous pulse interference and electromagnetic interference in the power distribution circuit; numerical calibration is used to offset the acquisition error caused by temperature drift and zero drift of the acquisition chip; timing alignment processing unifies the asynchronous data of different acquisition sub-units to the same time axis to ensure the accuracy of multi-parameter linkage calculation.

[0028] This formula accurately identifies the ineffective energy consumption of a device by using the difference between total power consumption and effective power consumption. At the same time, it introduces an environmental compensation correction value to eliminate the impact of high temperature and high humidity environments on the power consumption and heat dissipation of the device hardware, thereby improving the accuracy of the quantitative calculation of ineffective energy consumption and achieving accurate quantitative statistics of hidden energy consumption.

[0029] The graded energy-saving control strategy described in step S3 specifically includes: When an idle standby condition is detected, the communication module's transmission power is reduced, redundant indicator lights are turned off, and the metering core module is kept in low-power standby mode. In scenarios such as users' off-peak electricity consumption, long-term unused electricity, and branch line idling, the metering box has no effective metering services. At this time, all visual redundant indicators are turned off, communication transmission power consumption is reduced, and only the metering chip and data acquisition core unit are kept on ultra-low power standby mode. This can significantly reduce the cumulative energy consumption caused by long-term standby of the equipment and solve the problem of metering box's long-term idle power consumption from the source. When the high temperature condition of the cabinet is detected, the start-stop frequency and operating power of the heat dissipation module are adaptively adjusted to avoid the heat dissipation equipment from consuming power at full load continuously. Traditional metering box cooling fans are mostly always on and running at full load, consuming power continuously regardless of the temperature of the cabinet. The heat dissipation power is dynamically matched according to the real-time temperature gradient inside the cabinet, with low-temperature low-power heat dissipation and high-temperature full-load heat dissipation. Under the premise of ensuring that the operating temperature of electrical components and metering equipment inside the cabinet is within a safe range and avoiding high-temperature aging and damage, the ineffective energy consumption of the heat dissipation system is effectively reduced. When an overload abnormal condition is detected, the abnormal energy-consuming branch is identified first, and an energy-limiting control command is issued. At the same time, the core metering function is kept running normally. For abnormal scenarios such as line overload, malicious overload of electricity, and power consumption due to branch faults, the abnormal energy-consuming branch is located and energy-limiting control is executed to suppress excessive power output. Meanwhile, the core functions of power metering, data acquisition, and fault recording are retained throughout the process. This achieves energy-saving control and fault loss prevention, while ensuring that electricity consumption data is not lost and metering and settlement are accurate and reliable.

[0030] When the equipment is running normally and stably, each module is kept in rated low-power operation to ensure metering accuracy while reducing ineffective energy consumption. With this setting, when the equipment is running under normal load, high power consumption is avoided and each functional module operates in the optimal low-power condition, taking into account equipment stability, metering accuracy and energy saving, and achieving normal low-power operation. The module also includes step S5, the adaptive calibration update module, which dynamically iterates and optimizes the energy-saving control threshold model based on historical energy-saving logs and seasonal environmental parameters to adapt to energy-saving control needs in different time periods and environments. With this setup, due to seasonal temperature differences, day-night temperature differences, equipment aging, and changes in environmental humidity, the equipment's baseline power consumption and heat dissipation requirements can shift, making fixed thresholds prone to misjudgments and control failures. By iteratively optimizing threshold parameters through big data historical logs, adaptive adaptation to winter / summer, day / night, and new / old equipment is achieved, ensuring stable and reliable long-term energy-saving effects and avoiding the shortcomings of traditional fixed threshold models, such as poor adaptability and subsequent degradation of energy-saving effects. This invention also discloses an energy metering box that applies an energy-saving power management method. It includes a box body and a data acquisition module, a data processing and analysis module, an intelligent energy-saving control module, a status monitoring and traceability module, and an adaptive calibration and update module integrated inside the box body. All functional modules adopt an onboard integrated modular design, which does not require additional modification of the box structure. It can be directly adapted to the upgrade and transformation of existing mainstream intelligent energy metering boxes. It has high integration, simple wiring, low transformation difficulty, and strong versatility. The data acquisition module is used to collect real-time operating data such as temperature and humidity inside the enclosure, power supply parameters, equipment operating status, and enclosure opening and closing status, and transmit the collected data to the data processing and analysis module in real time to achieve comprehensive perception of environmental parameters, power parameters, and equipment status parameters, providing data support for operating condition determination, energy consumption calculation, and energy-saving control. The data processing and analysis module is electrically connected to the data acquisition module and the intelligent energy-saving control module, respectively. It is used to preprocess the acquired data, screen for anomalies and identify operating conditions, and output corresponding energy-saving control instructions. As the core data operation and decision-making unit of the equipment, it undertakes the core functions of data purification, energy consumption quantification, operating condition judgment and instruction output. It is the core hub for realizing intelligent and precise energy-saving control. The intelligent energy-saving control module is electrically connected to the power supply equipment, heat dissipation equipment, and communication equipment inside the enclosure, respectively. It is used to receive control commands, execute hierarchical adaptive energy-saving power consumption adjustment, and serve as an execution terminal to realize refined, adaptive, and intelligent control of the power consumption of hardware devices. The status monitoring and traceability module is used to record equipment operation data and energy-saving control records throughout the process, generate traceable energy-saving logs, and simultaneously realize abnormal operating condition early warning and data upload, forming a complete equipment operation data archive, realizing visualization of the energy-saving process, traceability of data, and quantification of effects. The adaptive calibration update module is used to dynamically update the energy-saving control threshold model based on historical operating data and environmental parameters, optimize the energy-saving control strategy, realize equipment self-learning and self-optimization, and allow the energy-saving strategy to dynamically iterate with the environment and equipment status, so as to maintain the optimal energy-saving state in the long term.

[0031] The data acquisition module includes a temperature and humidity acquisition subunit, a power parameter acquisition subunit, and a status sensing subunit. The temperature and humidity acquisition subunit is used to collect temperature and humidity data of the internal environment of the enclosure. The power parameter acquisition subunit is used to collect incoming voltage, outgoing current, and real-time power consumption parameters. The status sensing subunit is used to collect the opening and closing status of the enclosure and the start and stop status of each electrical module. The three subunits have clear division of labor, collect data synchronously, and cooperate complementarily, which solves the shortcomings of traditional metering boxes that collect only single parameters and cannot take into account both environmental and equipment status, and provides a complete data source for operating condition identification. The intelligent energy-saving management module includes a power supply control subunit, a heat dissipation control subunit, and a communication power consumption control subunit. The power supply control subunit is used to control the on / off state and power supply of redundant power supply circuits inside the enclosure. The heat dissipation control subunit is used to adjust the operating power and start / stop frequency of the cooling fan and heat sink temperature control equipment. The communication power consumption control subunit is used to adaptively adjust the transmission power and operating frequency of the wireless and wired communication modules. The three subunits correspond to the three high-energy-consuming units of power supply, heat dissipation, and communication, respectively, to achieve refined power consumption control, with no blind spots and comprehensive energy-saving coverage. The data processing and analysis module incorporates a data filtering unit, a threshold comparison unit, and a working condition identification unit. The data filtering unit filters out pulse interference and abnormal numerical data from the collected data. The threshold comparison unit compares the pre-processed data with a preset threshold model. The working condition identification unit accurately determines no-load, overload, high-temperature, and abnormal standby energy consumption conditions. The three-level unit progressively completes data purification, parameter comparison, and working condition determination, reducing the probability of misjudgment and omission of working conditions and ensuring the accuracy and stability of energy-saving management. It also includes a local storage module and a wireless communication module. The local storage module is used to cache running data and energy-saving logs locally, and the wireless communication module is used to establish data interaction with the background management terminal to realize remote data upload and remote energy-saving parameter configuration. The local storage can store data locally when the network is interrupted or the signal is abnormal to avoid data loss. The wireless communication supports remote operation and maintenance, remote parameter debugging, and remote energy consumption viewing, reducing the workload of on-site operation and maintenance and improving the level of intelligent operation and maintenance. It also includes an audible and visual early warning module, which is electrically connected to the data processing and analysis module. When a severe energy consumption fault or abnormal equipment operation is detected, it triggers an audible and visual early warning prompt, reminding maintenance personnel to investigate and handle the situation in a timely manner. It provides proactive early warning for severe energy consumption faults, abnormal equipment damage, and dangerous overload conditions of the line, and has both energy-saving control and safety protection functions, thereby improving the safety and reliability of the metering box operation.

[0032] Adopting the above structure, the electricity metering box features an integrated onboard functional module design. Core functions such as data acquisition, data analysis, energy-saving management, status traceability, and adaptive calibration are independently modularized. Each module has independent hardware circuits and functional logic that does not interfere with each other, while data interaction and collaboration are achieved through a unified electrical interface. The overall structure eliminates the need for disassembly and modification of the traditional electricity metering box's enclosure structure, main circuit wiring, core metering components, and safety protection devices. It is fully compatible with the upgrade and renovation of existing smart electricity metering boxes for residential, commercial, outdoor, and building applications, and can also be directly adapted to the mass production design of new metering boxes. The high degree of module integration, neat wiring, and small footprint simplify on-site installation and commissioning, requiring no complex professional construction processes, significantly reducing equipment modification, production, and maintenance costs, and making it highly suitable for engineering applications.

[0033] This invention's data acquisition module is subdivided into temperature and humidity acquisition subunits, power parameter acquisition subunits, and status sensing subunits. Unlike traditional metering boxes that only collect single power parameters, this device can simultaneously achieve comprehensive synchronous acquisition of electrical parameters, environmental parameters, and equipment status parameters. Through adaptive high-frequency acquisition, continuous recording of time-series data is achieved. Simultaneously, with backend data preprocessing, data distortion problems caused by electromagnetic interference, instantaneous voltage fluctuations, and pulse noise in the power distribution field are avoided. Furthermore, the added enclosure opening / closing status acquisition function can effectively distinguish between scenarios such as equipment maintenance, abnormal opening, and normal closed operation, preventing accidental triggering of energy-saving strategies from the mechanical structure source and ensuring the operational safety and data acquisition integrity of the equipment under any operating condition.

[0034] Furthermore, the data processing and analysis module of this invention has built-in independent data filtering unit, threshold comparison unit, and operating condition identification unit. Unlike the crude judgment method of traditional equipment that relies on a single threshold for fault alarm, this invention uses an invalid energy consumption calculation formula, combined with temperature and humidity compensation correction parameters, to remove the effective working energy consumption and invalid redundant energy consumption of the metering box, thereby realizing the digital quantitative statistics of hidden no-load energy consumption, high-temperature excess energy consumption, and abnormal standby energy consumption.

[0035] This invention's intelligent energy-saving management module is subdivided into power supply control subunits, heat dissipation control subunits, and communication power consumption control subunits, respectively, to perform refined power consumption control for the three major high-energy-consuming modules inside the metering box. The system executes differentiated and graded energy-saving strategies based on the front-end operating condition identification results. It matches independent power consumption adjustment logic to four core operating conditions: no-load standby, high box temperature, line overload, and normal load. In no-load scenarios, it reduces the power consumption of redundant peripherals; in high-temperature scenarios, it dynamically matches heat dissipation power; in overload scenarios, it accurately limits current to ensure safety; and in normal operating conditions, it maintains optimal low-power operation. Throughout the process, while ensuring the accuracy of power metering, stable data transmission, and the safety of the power distribution circuit, it achieves the design goals of safety, stability, and energy saving by reducing ineffective energy consumption.

[0036] Equipment operating parameters, energy consumption calculation data, energy-saving control actions, operating condition identification results, and abnormal fault information are recorded in a time-series manner to generate standardized energy-saving logs. The data is completely retained in the local storage unit to avoid data loss. At the same time, it is equipped with an audible and visual early warning module to provide local audible and visual proactive early warning for dangerous operating conditions such as severe energy consumption faults, equipment abnormalities, and line overloads. Combined with cloud-based remote monitoring and remote parameter configuration functions, it realizes unattended intelligent operation and maintenance, significantly reducing the pressure of manual inspection.

[0037] An adaptive calibration update module is set up. Based on historical energy-saving logs and big data of environmental parameters, the module dynamically iterates and optimizes the no-load power consumption threshold, high temperature threshold, standby threshold and environmental compensation parameters. It can adaptively match complex scenarios such as seasonal temperature differences, day and night humidity changes, long-term aging power consumption deviation of equipment, and fluctuations in user electricity consumption habits. It keeps the energy-saving strategy automatically optimized with changes in equipment status and environment, avoiding the problem of the energy-saving effect of traditional equipment decaying and the adaptability deteriorating in the later stage.

[0038] This invention adopts a standardized and modular design with clear functional divisions and universal hardware interfaces. It can serve as the core architecture of a brand-new intelligent energy-saving electricity metering box, or it can be directly adapted to the intelligent transformation of existing ordinary intelligent metering boxes without altering the main circuit and metering core structure. This results in short transformation periods, low failure rates, and high replaceability. Compared to traditional overall replacement upgrade solutions, this invention reduces the capital and construction costs of intelligent upgrades to power grid terminal equipment, is suitable for large-scale batch deployment and application, and has extremely high industrialization value.

[0039] This invention designs differentiated and graded energy-saving strategies for four typical operating conditions: no-load standby, high-temperature operation, overload anomaly, and normal load. It distinguishes between effective working energy consumption and ineffective redundant energy consumption. In scenarios such as low load, no-load, and off-peak hours, it significantly reduces peripheral power consumption; in high-temperature scenarios, it intelligently matches heat dissipation power; and in fault scenarios, it prioritizes equipment safety and the integrity of metering data. Throughout the process, it does not interfere with core metering functions or affect the accuracy of electricity billing, achieving better long-term energy-saving gains while ensuring equipment reliability.

[0040] The adaptive calibration update module enables dynamic model iteration and continuously optimizes control thresholds and compensation parameters based on historical operational big data. It can adapt to differences in winter and summer temperature, day and night humidity, equipment hardware aging, and regional electricity consumption characteristics, ensuring the optimal energy-saving strategy and the strongest adaptability throughout the equipment's life cycle. The long-term energy-saving effect is stable and there are no later failures or malfunctions.

[0041] Integrating data traceability and storage, wireless remote communication, and local audible and visual early warning functions, maintenance personnel can view equipment operating status, energy consumption data, and energy-saving records in real time through the backend terminal, and remotely complete parameter configuration and fault diagnosis without frequent on-site inspections. When equipment malfunctions, it can proactively issue audible and visual alarms to quickly locate the fault. This completely solves the problems of traditional metering box maintenance, such as reliance on manual labor, delayed fault diagnosis, missing data, and disorganized records, significantly reducing the workload of power grid terminal maintenance and improving the intelligent and digital maintenance level of distribution terminals.

[0042] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for energy-saving electricity management using an electricity metering box, characterized in that, Includes the following steps: S1. The data acquisition module collects the operating parameters of the power metering box in real time. The operating parameters include the internal temperature and humidity of the box, the incoming line voltage, the outgoing line current, the real-time power consumption, the equipment operating status, and the box opening and closing status. S2, the data processing and analysis module preprocesses and performs threshold comparison analysis on the collected operating parameters, removes abnormal interference data, calculates the real-time invalid energy consumption of the box through the preset energy consumption judgment formula, matches the preset energy-saving control threshold model, and identifies the no-load energy consumption, overload operation, abnormal standby and high-temperature power consumption abnormal conditions of the power metering box. S3, the intelligent energy-saving control module executes a graded energy-saving control strategy based on the operating condition identification results, and adaptively adjusts the power consumption of the power supply module, heat dissipation module and communication module inside the metering box; S4, the status monitoring and traceability module, records the energy-saving control process and equipment operation data in real time, generates energy-saving logs, and uploads them synchronously to the back-end management terminal. At the same time, it monitors the operating status of the enclosure in real time and triggers early warning prompts under abnormal operating conditions.

2. The energy-saving electricity management method for the electricity metering box according to claim 1, characterized in that, In step S2, the threshold model includes an idle power consumption threshold, an overload current threshold, a high temperature threshold for the enclosure, and a standby power consumption threshold. The preprocessing includes data filtering, numerical calibration, and timing alignment. Through multi-dimensional parameter linkage comparison, it accurately distinguishes between normal operation, mild energy consumption anomalies, and severe energy consumption fault conditions. The energy consumption determination formula is as follows: ； in, This represents the real-time ineffective energy consumption of the electricity metering box, in Wh. The total real-time operating power consumption of the enclosure is expressed in watts (W). This represents the rated effective power consumption of the enclosure under current operating conditions, in watts (W). This refers to the data collection duration, expressed in hours (h). This represents the energy consumption compensation correction value corresponding to ambient temperature and humidity, in Wh.

3. The energy-saving electricity management method for the electricity metering box according to claim 1, characterized in that, The graded energy-saving control strategy described in step S3 specifically includes: When an idle standby condition is detected, the transmission power of the communication module is reduced and the power supply of redundant indicator lights is turned off to maintain the low-power standby of the metering core module. When the high temperature condition of the enclosure is detected, the start-stop frequency and operating power of the heat dissipation module are adaptively adjusted to avoid the heat dissipation equipment from consuming power at full load continuously. When an overload abnormal operating condition is detected, the abnormal energy consumption branch is locked first, and an energy limiting control command is issued, while the core metering function is kept running normally. When the equipment is running normally and stably, it maintains the rated low-power operation of each module to ensure metering accuracy while reducing ineffective energy consumption.

4. The energy-saving electricity management method for the electricity metering box according to claim 1, characterized in that, It also includes step S5, the adaptive calibration update module, which dynamically iterates and optimizes the energy-saving control threshold model based on historical energy-saving logs and seasonal environmental parameters to adapt to the energy-saving control needs of different time periods and environments.

5. An electricity metering box, employing the energy-saving electricity management method according to any one of claims 1-4, characterized in that, It includes the enclosure body, as well as the data acquisition module, data processing and analysis module, intelligent energy-saving control module, status monitoring and traceability module, and adaptive calibration and update module integrated inside the enclosure body; The data acquisition module is used to collect real-time operating data such as internal temperature and humidity, power supply parameters, equipment operating status and opening and closing status of the enclosure, and transmit the collected data to the data processing and analysis module in real time. The data processing and analysis module is electrically connected to the data acquisition module and the intelligent energy-saving control module, respectively, and is used to preprocess the acquired data, screen for anomalies and identify operating conditions, and output corresponding energy-saving control commands. The intelligent energy-saving control module is electrically connected to the power supply equipment, heat dissipation equipment, and communication equipment inside the enclosure, and is used to receive control commands and perform hierarchical adaptive energy-saving power consumption adjustment. The status monitoring and traceability module is used to record equipment operation data and energy-saving control records throughout the process, generate traceable energy-saving logs, and simultaneously realize abnormal operating condition early warning and data upload. The adaptive calibration update module is used to dynamically update the energy-saving management threshold model and optimize the energy-saving management strategy based on historical operating data and environmental parameters.

6. The electricity metering box according to claim 5, characterized in that, The data acquisition module includes a temperature and humidity acquisition subunit, a power parameter acquisition subunit, and a status sensing subunit; the temperature and humidity acquisition subunit is used to collect temperature and humidity data of the internal environment of the enclosure. The power parameter acquisition subunit is used to acquire incoming voltage, outgoing current, and real-time power consumption parameters; the status sensing subunit is used to acquire the opening and closing status of the enclosure and the start and stop status of each electrical module.

7. The electricity metering box according to claim 5, characterized in that, The intelligent energy-saving control module includes a power supply control subunit, a heat dissipation control subunit, and a communication power consumption control subunit. The power supply control subunit is used to control the on / off state and power supply of redundant power supply circuits inside the enclosure. The heat dissipation control subunit is used to adjust the operating power and start / stop frequency of the cooling fan and heat sink temperature control equipment. The communication power consumption control subunit is used to adaptively adjust the transmission power and operating frequency of the wireless and wired communication modules.

8. The electricity metering box according to claim 5, characterized in that, The data processing and analysis module includes a built-in data filtering unit, a threshold comparison unit, and a working condition identification unit. The data filtering unit is used to filter out pulse interference and abnormal numerical data in the collected data. The threshold comparison unit is used to compare the preprocessed data with a preset threshold model. The working condition identification unit is used to accurately determine no-load, overload, high temperature, and abnormal standby power consumption conditions.

9. The electricity metering box according to claim 5, characterized in that, It also includes a local storage module and a wireless communication module. The local storage module is used to cache running data and energy-saving logs locally, and the wireless communication module is used to establish data interaction with the background management terminal to realize remote data upload and remote energy-saving parameter configuration.

10. The electricity metering box according to claim 5, characterized in that, It also includes an audible and visual early warning module, which is electrically connected to the data processing and analysis module. When a severe energy consumption fault or abnormal equipment operation is detected, it triggers an audible and visual early warning prompt to remind maintenance personnel to investigate and handle the issue in a timely manner.

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