Old community intelligent air switch and community platform integrated control method

Abstract

The invention relates to the technical field of power systems and intelligent control, particularly discloses an integrated control method for an intelligent air switch and a community platform of an old community, and aims to solve the problems of difficulty in monitoring power utilization safety of the old community, low management efficiency and lack of intelligent cooperative control. According to the method, a three-layer architecture composed of an intelligent air switch terminal, a building-level data aggregation node and a community-level management platform is constructed, and remote switching-off, limited-power operation and early warning information pushing are achieved by collecting electrical parameters of residents in real time, aggregating verification data, analyzing power consumption behaviors and recognizing abnormities. And meanwhile, the functions of energy efficiency optimization and equipment health state monitoring are integrated. By adopting the technical scheme, the electricity utilization safety level and the energy management efficiency of the community can be improved, the service life of equipment can be prolonged, and good practicability and generalizability are achieved.

Description

TECHNICAL FIELD

[0001] The present disclosure relates to the field of power systems and intelligent control technology, in particular to an old community intelligent air switch and community platform integrated control method. BACKGROUND

[0002] With the deep integration of smart grid and Internet of Things technology, the intelligent transformation of old community power systems has become a key direction to improve community safety governance and energy management efficiency. Traditional air switches only have basic overload and short circuit protection functions, lack data sensing and remote interaction capabilities, and are difficult to support the comprehensive needs of modern communities for electricity consumption behavior monitoring, risk early warning and energy efficiency optimization. Especially in the environment of densely populated old communities, aging lines and weak network infrastructure, an integrated solution that balances device-level control accuracy and community-level collaborative management capabilities is urgently needed to realize the transformation and upgrading from a single protection device to an intelligent electricity consumption terminal.

[0003] Among them, the intelligent air switch, as the core node connecting the user side electricity consumption terminal and the community management platform, its function is not limited to circuit on-off control, but also needs to undertake multiple tasks such as electricity consumption data collection, abnormal state identification and instruction response. The ideal integrated control method should be able to connect the information link between the device layer, the building layer and the community platform, support the unified gathering and dynamic analysis of multi-source electricity consumption data, and on this basis, build service capabilities for community public safety and energy planning. However, the existing technology generally has problems such as hierarchical fragmentation, protocol heterogeneity and insufficient scene adaptation in system architecture design, which restricts the large-scale deployment and efficient operation of intelligent air switches in complex old community environments.

[0004] In the prior art, although some high-voltage circuit breakers introduce microprocessors to realize local intelligent control, their application scenarios are limited to industrial or high-voltage power distribution fields, and they do not consider high-concurrency access, low-power communication and low-cost transformation constraints in the low-voltage residential electricity consumption scenario; another type of weak electric integrated management platform has centralized supervision capabilities, but it does not include intelligent air switches in the unified control system, and lacks active sensing and cross-level linkage disposal mechanisms for electricity abnormal events (such as long-time no electricity consumption activities of lonely old people). In addition, the current scheme generally lacks load trend prediction and risk intervention strategies based on historical electricity consumption patterns, making it difficult for the community platform to identify potential safety hazards or develop differentiated energy scheduling plans in advance. The above defects together constitute a technical bottleneck that needs to be broken through in the process of intelligent upgrading of old communities. SUMMARY

[0005] To solve the above technical problems, the present disclosure provides an old community intelligent air switch and community platform integrated control method, which includes the following specific steps: Deploy intelligent circuit breaker terminals and install intelligent circuit breaker devices with data acquisition and communication functions in the distribution boxes of each household unit in old residential communities. The device integrates current and voltage sensing modules, microprocessor control units and wireless communication modules to realize real-time monitoring of electrical parameters of the incoming circuit and execution of remote control commands. Construct building-level data aggregation nodes, set up data aggregation gateways in each building unit, establish stable communication connections with all smart circuit breaker terminals in the building through wireless self-organizing network protocol, periodically poll and collect the power consumption data of each terminal, and perform preliminary data verification and format standardization; Establish a community-level management platform, deploy a cloud-based community integrated management platform, establish data links with each building-level data aggregation node through wired or wireless wide area networks, receive and store electricity consumption data from smart circuit breaker terminals throughout the community, and form a community electricity consumption database; To achieve electricity consumption behavior analysis and anomaly identification, the community-level management platform performs multi-dimensional analysis on the received electricity consumption data, including load curve feature extraction, electricity consumption pattern classification and abnormal electricity consumption behavior identification, and determines whether there are potential electricity safety hazards or special user care needs based on preset rules and algorithm models. The community-level management platform performs collaborative control and information services. Based on the analysis results, it generates control strategies or service information and sends control commands to specific smart circuit breaker terminals through building-level data aggregation nodes, or pushes early warning information and service suggestions to community managers and relevant users.

[0006] In some embodiments, the current and voltage sensing module used in the intelligent circuit breaker terminal is designed based on the non-contact measurement principle, which can realize the accurate sensing of the loop current. The voltage measurement is realized through a voltage divider network, which is suitable for parameter acquisition in a conventional AC power supply environment. The microprocessor control unit integrates an analog-to-digital converter to digitally process the sensing signal.

[0007] In some embodiments, the wireless communication module further supports multiple low-power wireless communication protocols. The communication module automatically enters a low-power sleep mode during non-data transmission periods and is only woken up when there is a need for data reporting or instruction reception, so as to reduce the overall system energy consumption.

[0008] In some embodiments, the building-level data aggregation gateway further includes a built-in protocol conversion function, which can uniformly convert data from smart circuit breakers with different communication protocols into a standard data format. The gateway is equipped with a data caching mechanism to temporarily store data when the network is interrupted and perform breakpoint resume transmission after the network is restored, ensuring data integrity.

[0009] In some embodiments, the community-level management platform further employs a distributed database architecture to store community electricity consumption data. The database organizes data according to time series, supports rapid querying and historical data backtracking, and deploys data cleaning and preprocessing programs to automatically identify and remove abnormal data points, thereby improving the accuracy of subsequent analysis.

[0010] In some embodiments, the electricity consumption behavior analysis and anomaly identification steps further include load curve feature extraction, which includes calculating daily electricity consumption, peak load, load factor and electricity consumption period distribution characteristics; electricity consumption pattern classification uses an unsupervised clustering algorithm to identify typical electricity consumption patterns; and abnormal electricity consumption behavior identification includes long-term zero-load alarm, load change detection and suspected electrical fire risk identification.

[0011] In some embodiments, the determination of potential electricity safety hazards based on preset rules and algorithm models further includes setting multiple determination thresholds. For a specific user group, if the electricity consumption is significantly lower than its historical average level, a care reminder is triggered. For load change situations, if the load change exceeds a set proportion within a short period of time, a safety check is performed.

[0012] In some embodiments, the collaborative control and information service steps further include control commands including remote tripping commands and power-limiting operation commands, and information services including sending electricity safety reports to community management personnel and sending electricity consumption statistics and energy-saving suggestions to users. All control commands must undergo a double confirmation mechanism before execution to prevent misoperation.

[0013] In some embodiments, the method further includes an energy efficiency optimization function, wherein the community-level management platform uses a time series forecasting model to predict the total load of the community in future periods based on historical electricity consumption data and external environmental information, and generates peak-shifting electricity consumption suggestions, and guides users to participate in community demand-side response through information push.

[0014] In some embodiments, the method further integrates equipment health status monitoring, with the intelligent circuit breaker terminal periodically performing self-checks and reporting equipment operating status parameters. The community-level management platform assesses the remaining lifespan of the equipment based on these parameters, arranges maintenance and replacement in advance, and reduces the risk of failure.

[0015] The main beneficial effects of this disclosure include: By constructing a three-tiered collaborative architecture consisting of intelligent circuit breaker terminals, building-level data aggregation nodes, and a community-level management platform, comprehensive collection and unified management of electricity consumption data in older residential communities are achieved. Based on multi-dimensional electricity consumption behavior analysis and anomaly identification mechanisms, potential electricity safety hazards and special user care needs can be detected in a timely manner. Remote collaborative control and information service functions improve the community's electricity safety level and energy management efficiency. Integrated energy efficiency optimization and equipment health status monitoring further extend equipment lifespan and promote energy conservation in the community. The entire method revolves around the integrated control logic of intelligent circuit breakers and the community platform, fully considering the actual deployment conditions of older residential communities, and possesses high practicality and scalability. Attached Figure Description

[0016] To more clearly illustrate the technical solutions and advantages in the embodiments of this disclosure 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 this disclosure. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 According to an embodiment of this disclosure, a schematic diagram of the overall technical solution architecture of a method for integrating intelligent circuit breakers and community platforms in old residential communities is provided.

[0018] Figure 2 According to an embodiment of this disclosure, a schematic diagram of the core principle framework for electricity consumption behavior analysis and anomaly identification is provided. Figure 3 According to embodiments of this disclosure, a logical flow framework diagram for collaborative control and information services is provided. Detailed Implementation

[0019] The following specific examples illustrate the implementation of this disclosure. Those skilled in the art can easily understand other advantages and effects of this disclosure from the content disclosed herein. This disclosure can also be implemented or applied to systems through other different specific embodiments, and various details in this disclosure can also be modified or changed according to different viewpoints and application systems without departing from the spirit of this disclosure. It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of this disclosure can be combined with each other.

[0020] The embodiments of this disclosure will now be described in detail with reference to the accompanying drawings, so that those skilled in the art to which this disclosure pertains can readily implement it. This disclosure may be embodied in many different forms and is not limited to the embodiments described herein.

[0021] In this disclosure, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic represented in connection with that embodiment or example is included in at least one embodiment or example of this disclosure. Furthermore, the specific features, structures, materials, or characteristics represented may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples represented in this disclosure, as well as the features of those different embodiments or examples.

[0022] Furthermore, the terms "first" and "second" are used for illustrative purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the representation of this disclosure, "a plurality of" means two or more, unless otherwise expressly and specifically defined.

[0023] For the purpose of clarity, devices unrelated to the description are omitted, and the same or similar components throughout the specification are given the same reference numerals.

[0024] Although the terms first, second, etc., are used in some instances herein to refer to various elements, these elements should not be limited by these terms. These terms are used only to distinguish one element from another. For example, first interface and second interface, etc., are used. Furthermore, as used herein, the singular forms “a,” “an,” and “the” are intended to also include the plural forms unless the context indicates otherwise. It should be further understood that the terms “comprising,” “including,” indicate the presence of features, steps, operations, elements, components, items, kinds, and / or groups, but do not exclude the presence, occurrence, or addition of one or more other features, steps, operations, elements, components, items, kinds, and / or groups. The terms “or” and “and / or” as used herein are interpreted as inclusive, or mean any one or any combination thereof. Thus, “A, B, or C” or “A, B, and / or C” means “any one of: A; B; C; A and B; A and C; B and C; A, B, and C.” Exceptions to this definition will only occur if the combination of elements, functions, steps, or operations is inherently mutually exclusive in some way.

[0025] The technical terms used herein are for reference only to specific embodiments and are not intended to limit the scope of this disclosure. The singular form used herein includes the plural form unless the statement explicitly indicates otherwise. The word "comprising" as used in this specification means to specify a particular characteristic, region, integer, step, operation, element, and / or component, and does not exclude the presence or addition of other characteristics, regions, integers, steps, operations, elements, and / or components.

[0026] Although not explicitly defined, all terms, including technical and scientific terms used herein, shall have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure pertains. Terms defined in commonly used dictionaries shall be further interpreted as having a meaning consistent with the relevant technical literature and the content of this present disclosure, and shall not be over-interpreted as having an ideal or overly formulaic meaning unless otherwise defined.

[0027] To address the problems raised in the background section, this disclosure provides a community electricity safety early warning method based on the Internet of Things (IoT). Specifically, in some embodiments of this disclosure, Figure 1 A flowchart illustrating a community electricity safety early warning method based on the Internet of Things (IoT) is shown. Figure 1 As shown, the specific steps may include the following: refer to Figure 1 This illustrates the overall technical architecture of the present invention. The core of the method described in this invention lies in establishing a complete information link from the user-side distribution box to the community management center. This architecture includes intelligent circuit breaker terminals deployed in the distribution boxes of each resident unit, data aggregation gateways set up in each building unit, and a community-level management platform deployed in the cloud. These three components achieve data aggregation, command issuance, and service collaboration through a layered communication mechanism, forming a closed-loop control system. Based on this architecture, the method includes the following steps: S100: Deploy intelligent circuit breaker terminal, which is used to collect electrical parameters in real time and execute remote control commands.

[0028] Intelligent circuit breakers with data acquisition and communication functions are installed in the distribution boxes of each household unit in older residential communities. These devices integrate current and voltage sensing modules, a microprocessor control unit, and a wireless communication module. They enable real-time monitoring of electrical parameters (such as current and voltage) of the incoming circuit and can execute control commands such as opening and closing from a remote platform. The microprocessor control unit digitizes the analog signals collected by the sensing modules, while the wireless communication module handles data transmission and command reception. This process achieves source acquisition and remote control of user-side electricity consumption data, providing a data foundation and execution capabilities for upper-level applications.

[0029] S200: Construct a building-level data aggregation node, which is used to communicate with the smart circuit breaker terminal, aggregate electricity consumption data, and establish a data link with the community-level management platform.

[0030] A data aggregation gateway is installed in each building unit. This gateway establishes a stable connection with all smart circuit breaker terminals in the building via a wireless ad hoc network protocol, periodically polls and collects power consumption data from each terminal, performs preliminary data verification (such as value range checks) and format standardization, and then uploads the processed data to the community-level management platform via Ethernet or 4G / 5G network. This step constructs a localized data relay hub, effectively aggregating terminal data and ensuring the stability of the data link with the community platform.

[0031] S300: Establish a community-level management platform, which is used to receive, store and manage electricity consumption data from the data aggregation node.

[0032] A cloud-based community integrated management platform was deployed, connecting with building-level data aggregation nodes via a wide area network to receive and store electricity consumption data from smart circuit breaker terminals throughout the community, forming a unified community electricity consumption database. The platform adopts a microservice architecture, including core modules for data access, storage, and analysis, enabling centralized and reliable management of massive amounts of electricity consumption data and providing platform support for subsequent in-depth analysis and applications.

[0033] S400: Perform electricity consumption behavior analysis and anomaly identification. The community-level management platform performs multi-dimensional analysis on the received electricity consumption data to identify electricity consumption behavior patterns and potential abnormal events.

[0034] The community-level management platform performs multi-dimensional analysis of stored electricity consumption data, including load curve feature extraction, electricity consumption pattern classification, and abnormal electricity consumption behavior identification. Based on preset rules and algorithm models, this process can effectively determine potential electricity safety hazards (such as electrical fire risks) or special user care needs (such as abnormal behavior of elderly people living alone), realizing a shift from "passive response" to "proactive early warning".

[0035] S500: Performs collaborative control and information services. The community-level management platform issues control commands to the smart circuit breaker terminal based on the analysis and identification results, or pushes information services to relevant management personnel and users.

[0036] Based on the analysis and identification results from the S400, the community-level management platform generates control strategies or service information. For example, it may issue remote tripping commands to high-risk smart circuit breaker terminals to cut off circuits, or push early warning information to community management personnel and send electricity consumption statistics and energy-saving suggestions to users. This process forms a complete "perception-analysis-decision-execution" closed loop, transforming analysis results into actual control actions or information services, directly improving community safety and management efficiency.

[0037] Further, in step S100, the specific implementation of the power consumption parameter acquisition module of the intelligent circuit breaker terminal is as follows: S110: The current sensing module is based on the non-contact measurement principle. It uses a high-precision Rogowski coil or Hall effect sensor to perform isolated measurement of the loop current. The measurement range covers 0 to 100 amperes, and the accuracy level is not lower than 1.0.

[0038] S120: The voltage measurement is achieved through a built-in high-resistance resistor voltage divider network, which is suitable for 220V AC power supply environment. The voltage division ratio is set to 1000:1, and the isolation amplifier is used to ensure the safety and accuracy of signal acquisition.

[0039] The microprocessor control unit (such as a low-power ARM Cortex-M series chip) performs synchronous digitization processing on the aforementioned analog signals. This non-contact and high-precision measurement scheme ensures safety while providing a high-quality data foundation for subsequent analysis.

[0040] Further, in step S100, the wireless communication module is implemented as follows: S130: Supports multiple low-power wireless communication protocols such as Zigbee 3.0, LoRa and NB-IoT, and can automatically select the optimal communication mode according to the actual network coverage conditions in the building, enhancing deployment flexibility.

[0041] S131: During periods without data transmission tasks, the communication module automatically enters a deep sleep state, consuming less than 10 microwatts, and is only activated when woken up by a timer or triggered by an event. This mechanism significantly reduces the standby power consumption of the terminal during long-term operation, helping to control the overall system operating costs.

[0042] Further, in step S200, the specific implementation of the building-level data aggregation node is as follows: S210: Built-in protocol parsing engine can uniformly convert and map data from smart circuit breakers from different manufacturers or communication protocols into a standard data format based on JSON Schema, improving the system's compatibility with heterogeneous devices.

[0043] S220: Equipped with local flash memory as a data cache, it adopts a circular buffer queue structure. When an uplink network interruption is detected, the breakpoint resume mechanism is automatically activated, and the data is temporarily stored in the cache. After the network is restored, the missing data segments are re-uploaded in order according to the timestamp of the last successful upload, ensuring the integrity and time sequence consistency of the community electricity consumption database.

[0044] Furthermore, in step S300, the specific implementation of the community-level management platform is as follows: S310: It adopts a distributed time-series database (such as InfluxDB or TimescaleDB) to organize data tables by household unit, building number and time dimension, supports high-speed writing and fast query of massive electricity consumption data, and optimizes data storage and backtracking efficiency.

[0045] S320: Deploys data cleaning and preprocessing procedures to identify outliers before data is entered into the database. For example, it calculates the moving average and standard deviation to mark data points that deviate too much, and performs cross-validation based on the voltage-current phase relationship. The rule engine decides whether to remove or mark the data, which effectively improves the quality of the data and the accuracy of the analysis results.

[0046] Further, refer to Figure 2 It illustrates the core principle framework of electricity consumption behavior analysis and anomaly identification. In step S400, the specific implementation of the electricity consumption behavior analysis and anomaly identification is as follows: S410: Load curve feature extraction, which processes the daily electricity consumption data of each household and calculates features such as daily electricity consumption, peak load, load factor and distribution of morning and evening peak electricity consumption periods.

[0047] S420: Electricity consumption pattern classification. Using the K-means unsupervised clustering algorithm, daily electricity consumption, load rate, and nighttime electricity consumption ratio are used as feature vectors to automatically classify community residents into typical electricity consumption patterns such as "home office type", "office worker type", and "elderly person living alone type".

[0048] S430: Abnormal electricity consumption behavior identification, based on a preset rule base, performing real-time monitoring, including: S431: Long-term zero-load alarm. For households marked as "elderly people living alone", a care reminder will be triggered if the daily electricity consumption is less than 0.5 kWh for 72 consecutive hours.

[0049] S432: Load mutation detection. Calculate the peak load change rate between two consecutive days. If the absolute value exceeds 50% and continues for two days, initiate the safety verification process.

[0050] S433: Suspected electrical fire risk identification. It monitors the current harmonic distortion rate. If the total harmonic distortion (THD) exceeds 15% and is accompanied by an abnormal increase in temperature sensor readings, it is determined to be a high-risk event. This multi-layered, fine-grained identification mechanism can accurately address community safety and humanistic care.

[0051] Further, refer to Figure 3 It illustrates the logical flow of collaborative control and information services. In step S500, the specific implementation of the collaborative control and information services is as follows: S510: The control commands include remote tripping commands and power-limiting operation commands. All control commands must undergo a dual confirmation mechanism before being issued—first, the platform automatically verifies the terminal status and command security, and then authorized personnel manually confirm and input a dynamic verification code, which greatly prevents misoperation and malicious attacks and ensures control security.

[0052] S520: The information service includes sending a daily electricity safety report summarizing abnormal events and energy efficiency indicators across the entire community to community management personnel, and sending personalized electricity consumption statistics and energy-saving suggestions to users, thereby improving management transparency and user participation.

[0053] Preferably, the method further includes an energy efficiency optimization function: the community-level management platform uses a multivariate LSTM time series prediction model to predict the total load curve of the community for the next 24 hours based on historical electricity consumption data and external environmental information (such as temperature and humidity). When the predicted peak load approaches 90% of the transformer's rated capacity, the system automatically generates peak-shifting electricity consumption suggestions (such as suggesting that the washing machine usage time be adjusted to after 22:00), and guides users to participate in community demand-side response through information push, effectively smoothing the community load curve and reducing grid pressure and user electricity costs.

[0054] Preferably, the method also integrates equipment health status monitoring function: the intelligent circuit breaker terminal performs self-checks periodically (e.g., every 24 hours) and reports equipment operating status parameters, including contact wear degree, internal temperature rise, communication signal strength, etc.

[0055] The community-level management platform assesses the remaining lifespan of equipment based on reported parameters using an equipment health scoring model. The formula for calculating the health index H is as follows: ; Where, N used To accumulate the number of opening and closing operations, N max T represents the rated lifespan (typically 10,000 cycles), where T is the internal temperature. min With T max These represent the lower and upper limits of the normal operating temperature (e.g., 30°C and 85°C), respectively. RSSI is the received signal strength indicator value, with weighting coefficients w1=0.5, w2=0.3, and w3=0.2. When the health index H is below 0.6, the platform automatically generates a maintenance work order, notifying maintenance personnel to focus on checking or replacing the equipment during the next inspection. This realizes the transformation from "post-fault repair" to "preventive maintenance," significantly improving system reliability and reducing maintenance costs.

[0056] refer to Figures 1 to 3Through the coordinated implementation of the above steps, this invention successfully constructs a complete closed-loop system from terminal perception to platform decision-making and services, providing an efficient, reliable and cost-controllable comprehensive solution for the intelligent transformation of power systems in old residential communities.

[0057] It should be noted that the order of the embodiments described above is merely for descriptive purposes and does not represent the superiority or inferiority of the embodiments. The processes depicted in the accompanying drawings do not necessarily require a specific or sequential order to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0058] The various embodiments in this disclosure are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on describing the differences from other embodiments.

Claims

1. An old cell intelligent air opening and community platform integrated control method, characterized in that, The application comprises: deploying intelligent air switch terminals, which are used to collect electrical parameters in real time and execute remote control instructions; constructing building-level data aggregation nodes, which are used to communicate with the intelligent air switch terminals, aggregate electrical data, and establish data links with community-level management platforms; establishing community-level management platforms, which are used to receive, store, and manage electrical data from the data aggregation nodes; conducting electrical behavior analysis and anomaly identification, in which the community-level management platforms perform multi-dimensional analysis on the received electrical data, identify electrical behavior patterns, and potential anomaly events; executing collaborative control and information services, in which the community-level management platforms issue control instructions to the intelligent air switch terminals or push information services to relevant management personnel and users based on the analysis and identification results.

2. The method of claim 1, wherein, The electrical parameter collection module of the intelligent air switch terminal includes a current sensing module based on non-contact measurement principles and a voltage dividing network, which are used to accurately sense loop current and measure voltage, and the microprocessor control unit integrated in the collection module performs analog-to-digital conversion and digital processing.

3. The method of claim 1, wherein, The wireless communication module of the intelligent air switch terminal supports multiple low-power wireless communication protocols, automatically enters a low-power sleep mode during non-data transmission periods, and is dynamically awakened only when there is a need for data reporting or remote instruction reception, thereby reducing overall system energy consumption.

4. The method of claim 1, wherein, The building-level data aggregation node has built-in protocol conversion functions to convert data from intelligent air switch terminals with different communication protocols into a standard data format; the node is equipped with a data caching mechanism to temporarily store data during network interruptions and perform breakpoint resume after network recovery to ensure data integrity.

5. The method of claim 1, wherein, The community-level management platform uses a distributed database architecture to store the electrical data, organizes data in chronological order to support fast querying and historical data retrieval, and deploys data cleaning and preprocessing programs to automatically identify and exclude abnormal data points, thereby improving analysis accuracy.

6. The method of claim 1, wherein, The electrical behavior analysis and anomaly identification include: load curve feature extraction, which involves calculating daily electricity consumption, peak load, load rate, and electricity time period distribution characteristics; electrical mode classification, which uses unsupervised clustering algorithms to identify typical electrical modes; and abnormal electrical behavior identification, which includes long-time zero-load alarm, load mutation detection, and suspected electrical fire risk identification.

7. The method of claim 6, wherein, The determination of electrical safety hazards based on preset rules and algorithm models includes setting a determination threshold; the determination of special user care needs: if a specific user's electricity consumption is significantly lower than the historical average, a care reminder is triggered; if the load short-time change amplitude exceeds a certain proportion, safety verification is performed.

8. The method of claim 1, wherein, In the collaborative control and information services, the control instructions include remote tripping instructions and limited power operation instructions; the information services include sending electrical safety reports to community management personnel and sending electricity consumption statistics and energy-saving suggestions to users; and all control instructions need to go through a double-confirmation mechanism before execution.

9. The method of claim 1, wherein, The method also includes an energy efficiency optimization function, the community-level management platform predicts the total load of the community in the future period based on historical electricity consumption data and external environmental information, uses a time series prediction model, and generates a peak-shaving electricity consumption suggestion to guide users to participate in demand-side response through information push.

10. The method of claim 1, wherein, The method also integrates a device health state monitoring function, the intelligent air switch terminal regularly self-checks and reports device operation state parameters, the community-level management platform evaluates the remaining life of the device based on the parameters, and arranges maintenance and replacement in advance to reduce the risk of failure and ensure system operation.

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