A power management method, system and storage medium based on Internet of Things power box

Abstract

The present application discloses a power management method, system, and storage medium based on an IoT electrical box, and relates to the field of power grid management technology. The power management method includes: obtaining power load data, power quality data, and historical power data of each IoT electrical box; generating a power filter allocation scheme based on the power load data, power quality data, and historical power data; wherein the allocation scheme is used to characterize the correspondence between each power filter and each target area, and each power filter corresponds to one or more target areas; generating a wiring suggestion diagram based on the allocation scheme, and sending the wiring suggestion diagram to the master control device; wherein the wiring suggestion diagram identifies the actual positional relationship between the target areas, and the connection relationship between the target areas and the power filters. The present application can intelligently allocate power filters and improve resource utilization efficiency.

Description

Technical Field

[0001] The present application relates to the technical field of power grid management, and in particular to a power management method, system and storage medium based on an Internet of Things power box. Background Art

[0002] In modern power systems, with rising electricity demand and increasing complexity of power equipment, ensuring the stability, reliability, and safety of power supply has become a major challenge. Power filters, as a key device, play an important role in electric shock protection in existing systems, significantly improving power safety.

[0003] However, in practice, installing a power filter in every circuit improves electricity safety but can also lead to resource waste. This is especially true in some scenarios, such as dormitories, where multiple dormitories can share a single power filter. The lack of a scientific and rational power filter allocation strategy often leads to uneven or over-allocation of power filters, which not only increases system complexity but also reduces energy efficiency. Summary of the Invention

[0004] This application aims to solve at least one of the technical problems existing in the prior art. To this end, this application proposes a power management method, system and storage medium based on an Internet of Things power box, which can intelligently allocate power filters and improve resource utilization efficiency.

[0005] In a first aspect, the present application provides a power management method based on an IoT power box, which is applied to a power management system based on an IoT power box. The power management system includes a master control device, a plurality of IoT power boxes, and a power filter. Each of the IoT power boxes has a different target area for detection, and the IoT power boxes are communicatively connected to the master control device.

[0006] The electricity management method comprises:

[0007] Obtaining a first operation instruction;

[0008] In response to the first operating instruction, an initial wiring suggestion diagram is generated on the interface of the master control device; wherein the wiring suggestion diagram identifies the actual location relationship of all devices connected to the power grid in the target area, and the connection relationship between the IoT power box and the power filter;

[0009] Obtaining a second operation instruction for the icon corresponding to the power filter;

[0010] In response to the second operation instruction, the position information of the icon corresponding to the power filter in the wiring suggestion diagram is updated, and the wiring suggestion diagram is updated according to the updated position information and displayed on the display screen of the master control device;

[0011] The step of generating a wiring suggestion diagram on the interface of the master control device includes:

[0012] Obtaining power load data, power quality data, and historical power usage data for each of the IoT power boxes;

[0013] generating an allocation scheme for the power filters based on the power load data, the power quality data, and the historical power consumption data; wherein the allocation scheme is used to characterize the correspondence between each of the power filters and each of the target areas, and each of the power filters corresponds to one or more of the target areas;

[0014] A wiring suggestion diagram is generated according to the allocation plan, and the wiring suggestion diagram is sent to the master control device.

[0015] According to the first embodiment of the present application, the power management method based on an IoT power box has at least the following beneficial effects: the system generates and displays a wiring suggestion diagram based on the acquired first operation instruction, which can intuitively display the actual positional relationship between each target area and their connection status with the power filter. Simultaneously, regarding the layout of the power filter, the user can modify the icon of the power filter to be modified, thereby generating a second operation instruction, thereby updating the icon corresponding to the power filter in the wiring suggestion diagram and immediately displaying the updated information on the display screen of the master control device, making it easier for subsequent installers to install the power filter according to the wiring suggestion diagram. Users can perform complex power system management tasks such as viewing the system layout and adjusting device connections with simple instructions. This intuitive operation method reduces the reliance on professional knowledge and makes it easy for non-professionals to get started. In addition, users can directly interact with the system through a touch screen or other input device to input and provide feedback, which not only improves the management efficiency of the power system but also enhances the user experience and the overall performance of the system. To generate a recommended wiring diagram, the system first uses an IoT-based switch to collect real-time power load data, power quality data, and historical power usage data for each target area. Based on this data, the system generates a power filter allocation plan. This allocation plan specifically defines the corresponding relationship between each power filter and the target area, ensuring that each target area receives appropriate power filtering and protection. Based on the allocation plan, the system generates a recommended wiring diagram. This map clearly identifies the actual location relationships between the target areas and the connections between the target areas and the power filters. The generated recommended wiring diagram is sent to the master control device, allowing managers to intuitively understand the power distribution and the connection relationships between the target areas and the power filters, enabling more efficient monitoring and decision-making. Intelligently allocating power filters ensures that each target area receives appropriate power filtering and protection. This effectively prevents electric shock accidents while avoiding the resource waste associated with installing power filters in every circuit. This enables the sharing and optimal configuration of power filters, improving resource utilization efficiency.

[0016] According to some embodiments of the first aspect of the present application, generating the allocation scheme of the power filter based on the power load data, the power quality data, and the historical power usage data includes:

[0017] Inputting the power load data and the historical power consumption data into a preset prediction model to obtain load prediction information;

[0018] Inputting the power quality data into a preset evaluation model to obtain a power quality evaluation grade;

[0019] generating fault record information based on the historical electricity consumption data;

[0020] An allocation plan for the power filter is generated according to the load forecast information, the power quality assessment level and the fault record information.

[0021] According to some embodiments of the first aspect of the present application, generating the allocation scheme of the power filter according to the load forecast information, the power quality assessment level, and the fault record information includes:

[0022] generating a priority level for each target area according to the load forecast information, the power quality assessment level, and the fault record information;

[0023] An allocation plan for the power filter is generated according to the priority levels.

[0024] According to some embodiments of the first aspect of the present application, generating a priority level for each target area based on the load forecast information, the power quality assessment level, and the fault record information includes:

[0025] Obtaining a preset uncertainty level in each of the target areas;

[0026] A priority level for each target area is generated according to the load forecast information, the power quality assessment level, the fault record information, and the uncertainty level.

[0027] According to some embodiments of the first aspect of the present application, generating a priority level for each target area based on the load forecast information, the power quality assessment level, the fault record information, and the uncertainty level includes:

[0028] Obtaining a preset first weight corresponding to the load forecast information, a second weight corresponding to the electric energy assessment level, a third weight corresponding to the fault record information, and a fourth weight corresponding to the uncertainty level;

[0029] Based on the first weight, the second weight, the third weight, and the fourth weight, and according to the load forecast information, the power quality assessment level, the fault record information, and the uncertainty level, obtaining a power consumption score for each target area;

[0030] A priority level for each target area is generated according to the power consumption score value and a preset level relationship mapping table, wherein the level relationship mapping table is used to represent the corresponding relationship between the power consumption score value and the priority level.

[0031] According to some embodiments of the first aspect of the present application, after the step of generating the allocation scheme of the power filter according to the power load data, the power quality data, and the historical power usage data, the method further includes:

[0032] Performing a simulation test based on the allocation scheme, the power load data corresponding to each target area, the power quality data, and the historical power consumption data to obtain a test result;

[0033] According to the test result, the allocation scheme is updated until the test result meets a preset allocation threshold.

[0034] According to some embodiments of the first aspect of the present application, the power management method based on the Internet of Things power box provided by the present application further includes:

[0035] Based on the generated wiring suggestion diagram, obtaining a first execution action of the user selecting the power filter and the target area to be connected on the interface of the master control device;

[0036] generating a third operation instruction according to the first execution action;

[0037] In response to the third operation instruction, updating the allocation plan;

[0038] Performing simulation tests based on the updated allocation plan and the power load data, power quality data, and historical power consumption data corresponding to each target area to generate an updated wiring suggestion diagram and corresponding simulation results;

[0039] The updated wiring suggestion diagram is displayed on the display screen of the master control device, and a modification rationality mark is displayed on the display screen of the master control device according to the simulation result.

[0040] According to some embodiments of the first aspect of the present application, the power load data includes real-time voltage value, real-time current value and active power value; after the step of obtaining the power load data, power quality data and historical power consumption data of each of the IoT power boxes, the method further includes:

[0041] When the real-time voltage value continuously deviates from the preset voltage threshold by more than or equal to a first range within a first period of time, a first alarm signal is generated;

[0042] When the real-time current value is greater than or equal to a preset current threshold, a second alarm signal is generated;

[0043] When the active power value is greater than or equal to the preset power value, a third alarm signal is generated; wherein the first alarm signal, the second alarm signal and the third alarm signal all contain an identification number corresponding to the IoT power box;

[0044] Recording the power load data and updating the historical power consumption data;

[0045] Based on the first alarm signal, the second alarm signal or the third alarm signal, a corresponding alarm type is generated on the interface of the master control device.

[0046] According to some embodiments of the first aspect of the present application, after the step of obtaining the power load data, power quality data, and historical power consumption data of each IoT power box, the method further includes:

[0047] Based on the generated wiring suggestion diagram, obtaining a second execution action of a user inputting a total power upper limit for electricity consumption in the target area on an interface of the master control device;

[0048] generating a fourth operation instruction according to the second execution action;

[0049] According to the fourth operation instruction, the Internet of Things power box is controlled to output electric energy to the target area according to the total power upper limit value.

[0050] In the second aspect, the present application also provides a method for electricity management based on an Internet of Things power box, comprising: at least one memory; at least one processor; at least one program; the program is stored in the memory, and the processor executes at least one program to implement the method for electricity management based on an Internet of Things power box as described in any embodiment of the first aspect.

[0051] In a third aspect, the present application also provides a computer-readable storage medium, which stores a computer-executable signal, and the computer-executable signal is used to execute the power management method based on the Internet of Things power box as described in any embodiment of the first aspect.

[0052] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become obvious from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Additional aspects and advantages of the present application will become apparent and readily understood from the following description of the embodiments with reference to the accompanying drawings, in which:

[0054] Figure 1 Flowchart of the power management method based on the Internet of Things power box provided in this application;

[0055] Figure 2 For this application Figure 1 Flowchart about step S120;

[0056] Figure 3 For this application Figure 2 Flowchart about step S122;

[0057] Figure 4 For this application Figure 3 Flowchart regarding step S240;

[0058] Figure 5 For this application Figure 4 Flowchart regarding step S310;

[0059] Figure 6 For this application Figure 5 Flowchart regarding step S420;

[0060] Figure 7 For this application Figure 2 Flowchart after step S122;

[0061] Figure 8 For this application Figure 1 Flowchart about step S130 and step S140;

[0062] Figure 9 For this application Figure 2 Flowchart after step S121;

[0063] Figure 10 For this application Figure 2 FIG. 1 is a flowchart of another embodiment after step S121. DETAILED DESCRIPTION

[0064] The following describes in detail embodiments of the present application. Examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present application and are not to be construed as limiting the present application.

[0065] In the description of this application, it should be understood that descriptions involving orientations, such as up, down, front, back, left, right, etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, they cannot be understood as limitations on this application.

[0066] In the description of this application, if there is a description of first or second, it is only for the purpose of distinguishing technical features, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features or implicitly indicating the order of the indicated technical features.

[0067] In the description of this application, unless otherwise clearly defined, terms such as setting, installing, and connecting should be understood in a broad sense, and technicians in the relevant technical field can reasonably determine the specific meanings of the above terms in this application based on the specific content of the technical solution.

[0068] In modern power systems, with rising electricity demand and increasing complexity of power equipment, ensuring the stability, reliability, and safety of power supply has become a major challenge. Power filters, as a key device, play an important role in electric shock protection in existing systems, significantly improving power safety.

[0069] Power filters achieve harmonic suppression by injecting harmonic currents into the grid that are opposite to the harmonic currents on the load side, causing them to cancel each other out on the grid side. They also provide reactive power compensation, improving the power factor of the power system and reducing energy losses. Some power filters may use devices such as an isolation transformer to isolate the output current from the ground, significantly reducing the voltage and current when touched, achieving a "no harm to the person" effect. To prevent electrical fires, power filters may also incorporate an arc fault protector. When an arc fault is detected, the protector quickly disconnects the circuit to prevent the arc from sparking, thereby avoiding fire.

[0070] However, in practice, installing a power filter in every circuit improves electricity safety but can also lead to resource waste. This is especially true in some scenarios, such as dormitories, where multiple dormitories can share a single power filter. The lack of a scientific and rational power filter allocation strategy often leads to uneven or over-allocation of power filters, which not only increases system complexity but also reduces energy efficiency.

[0071] Based on this, the present application provides a power management method, system and storage medium based on an IoT power box to solve the technical problems raised above. The technical solutions provided by the present application are described in detail one by one below.

[0072] First, refer to Figure 1 This application provides a method for managing electricity usage based on an IoT power box, which is applied to an IoT power box-based electricity management system. The electricity management system includes a master control device, several IoT power boxes, and an energy filter. Each IoT power box has a different target area for detection, and the IoT power box is communicatively connected to the master control device. The method includes, but is not limited to, the following steps:

[0073] Step S110: obtaining a first operation instruction;

[0074] Step S120: In response to the first operation instruction, generating an initial wiring suggestion diagram on the interface of the master control device; wherein the wiring suggestion diagram identifies the actual location relationship of all devices connected to the power grid in the target area, and the connection relationship between the IoT power box and the power filter;

[0075] Step S130: obtaining a second operation instruction for the icon corresponding to the power filter;

[0076] Step S140: In response to the second operation instruction, the position information of the icon corresponding to the power filter in the wiring suggestion diagram is updated, and the wiring suggestion diagram is updated according to the updated position information and displayed on the display screen of the master control device.

[0077] Based on the acquired first operating instructions, the system generates and displays a wiring suggestion diagram, visually demonstrating the actual positional relationships between target areas and their connections to the power filters. Furthermore, users can modify the icons of the power filters in question to determine their placement, generating a second operating instruction that updates the icons corresponding to the power filters in the wiring suggestion diagram. The updated information is immediately displayed on the master control device's display, making it easier for subsequent installers to install the power filters according to the wiring suggestion diagram. Users can perform complex power system management tasks, such as viewing the system layout and adjusting device connections, with simple commands. This intuitive operation reduces reliance on specialized knowledge, making it easy for non-professionals to use. Furthermore, users can directly interact with the system through a touchscreen or other input device to input and provide feedback, improving power system management efficiency while enhancing the user experience and overall system performance.

[0078] Specifically, the generated wiring suggestion diagram may include an actual position relationship diagram of each electronic device in the target area. When adjusting the actual position of the power filter, the overall wiring suggestion diagram may be updated according to the positions of other devices.

[0079] In addition, the IoT electrical boxes can be uniformly set up in a main machine room. When the power filter is installed on the ground, the corresponding IoT electrical boxes can be directly connected to the power filter in the main machine room.

[0080] Among them, reference Figure 2 In step S120, the following steps may be included but not limited to:

[0081] Step S121: Obtain power load data, power quality data, and historical power consumption data of each IoT power box;

[0082] Step S122: generating an allocation scheme for power filters based on the power load data, power quality data, and historical power consumption data; wherein the allocation scheme is used to characterize the correspondence between each power filter and each target area, and each power filter corresponds to one or more target areas;

[0083] Step S123: Generate a wiring suggestion diagram according to the allocation plan, and send the wiring suggestion diagram to the master control device.

[0084] In steps S121 through S123, the system first uses the IoT power distribution box to obtain real-time power load data, power quality data, and historical power usage data for each target area. Based on this data, it then generates a power filter allocation plan. This allocation plan primarily defines the corresponding relationship between each power filter and the target area, ensuring that each target area receives appropriate power filtering and protection. Based on the allocation plan, the system generates a wiring suggestion map. This map clearly identifies the actual location relationships between the target areas and the connections between the target areas and the power filters. The generated wiring suggestion map is then sent to the master control device, allowing managers to intuitively understand the power distribution and the connections between the target areas and the power filters, enabling more efficient monitoring and decision-making. By intelligently allocating power filters, each target area receives appropriate power filtering and protection. This effectively prevents electric shock accidents while avoiding the resource waste associated with installing power filters in every circuit. This enables the sharing and optimal configuration of power filters, improving resource utilization efficiency.

[0085] In step S121, the power load data may include, but is not limited to, the following information: current, voltage, active power, reactive power, etc. This data reflects the real-time power demand of the target area. The above power load data is usually collected in real time by sensors built into the IoT power box or smart meters. Power quality data may include, but is not limited to, the following information: harmonic content, voltage fluctuation, frequency deviation, etc., which are used to assess power quality. The above power quality data is also collected by corresponding sensors in the IoT power box. Historical power consumption data may include, but is not limited to, the following information: power consumption trends and peak and valley periods over a period of time, which helps predict future power demand. The above historical power consumption data is stored in a database and can be extracted using data analysis tools.

[0086] Furthermore, in step S123, the IoT-based power management method can be specifically applied in dormitory buildings. The wiring suggestion map first displays the dormitory floor plan, including the number of rooms on each floor, the location of corridors, stairwells, and more. Each room is clearly identified on the map, such as by room number or a specific symbol, for quick location. For each room or specific area, the map can display the type and approximate load of major electrical equipment. For example, air conditioners, lighting, and sockets. Load conditions can be represented by color shading or numerical labels to provide a visual understanding of each room's power usage. Most importantly, the power filter allocation plan, generated based on power load data, power quality data, and historical power usage data, is graphically displayed on the map. Each power filter is connected to its corresponding target area or areas using specific symbols or lines, clearly demonstrating their connection and correspondence. Furthermore, the map can integrate real-time power usage data display, allowing users to click on a specific dormitory on the master control device screen to view real-time power load data for that dormitory. In the IoT-based electricity management method for dormitories, the wiring suggestion diagram serves as a key management tool and information display platform. It includes core content such as floor and room layout, IoT switch location and coverage, and power filter allocation schemes. Applications in industrial communities, factory workshops, and other scenarios are also possible, though this application does not limit this.

[0087] Reference Figure 3 It is understood that step S122 may include but is not limited to the following steps:

[0088] Step S210: inputting the power load data and historical power consumption data into a preset prediction model to obtain load prediction information;

[0089] Step S220: inputting the power quality data into a preset evaluation model to obtain a power quality evaluation level;

[0090] Step S230: Generate fault record information based on historical power consumption data;

[0091] Step S240: generating a power filter allocation plan based on the load forecast information, the power quality assessment level and the fault record information.

[0092] In step S210, before metal processing the power load data and historical power data collected from the IoT electrical box, these data can be cleaned, denoised and normalized to ensure the data quality of the input model. After the denoising is completed, the power load data and historical power data are input into a preset prediction model, which can be a time series analysis model (ARIMA, LSTM, etc.), a machine learning model (random forest, gradient boosting tree, etc.) or a deep learning model. By performing the prediction operation, the load forecast information for a period of time in the future is obtained. Through the load forecast information, the future power load trend can be understood in advance. The power load trend not only includes the prediction of the power consumption changes in 24 hours a day, but also the prediction of the power consumption in each month of the year. It is helpful to formulate a reasonable power dispatch plan, avoid power shortages or surpluses, and provide data support for the allocation of power filters to ensure that the filters can be efficiently configured according to actual load requirements.

[0093] In step S220, power quality data is analyzed to identify key indicators such as voltage stability, frequency deviation, and harmonic content. Based on power quality standards and requirements, a power quality assessment model is constructed. This assessment model can be based on methods such as rule-based judgment, fuzzy comprehensive evaluation, or machine learning algorithms. The collected power quality data is input into the assessment model, and an assessment is performed to determine the power quality assessment grade for each target area. This grade provides an important reference for the allocation of power filters, ensuring that the filters can effectively filter and address power quality issues.

[0094] In step S230, a fault detection algorithm or rule is set based on historical power consumption data, and the monitored data is analyzed in real time to provide fault information support for the allocation of power filters, ensuring that the filters can be configured and monitored in a focused manner for the fault area.

[0095] In steps S210 through S240, a comprehensive analysis of load forecast information, power quality assessment levels, and fault history information is performed to assess power demand and issues in each target area, taking into account factors such as load size, power quality issue severity, and fault frequency. Based on the analysis results, a power filter allocation strategy is developed. This step optimizes the configuration and efficient utilization of power filters, improves the stability and reliability of the power system, reduces electricity and maintenance costs, and enhances overall economic and social benefits.

[0096] Reference Figure 4 In step S240, the following steps may be included but not limited to:

[0097] Step S310: generating a priority level for each target area based on load forecast information, power quality assessment level, and fault record information;

[0098] Step S320: Generate an allocation plan for power filters according to the priority levels.

[0099] In steps S310 to S320, load forecast information, power quality assessment levels, and fault record information are integrated to form a comprehensive assessment dataset for each target area. This data is then analyzed in detail to identify areas likely to face high future load pressure, areas with poor power quality, and areas experiencing frequent faults. Based on the analysis results, each target area is assigned a priority level. This priority level is determined by taking into account multiple factors, such as peak load in the load forecast, severity level in the power quality assessment, and fault frequency and severity in the fault records.

[0100] In one embodiment, assuming that there are three rooms in a dormitory building, namely Room A, Room B, and Room C, based on load forecast information, power quality assessment level, and fault record information, the following is obtained:

[0101] Room A: The load forecast shows that there will be two peak loads in the next month. The power quality is assessed as medium (with slight harmonics). The fault record shows no major faults in the recent period.

[0102] Room B: The load forecast shows a relatively stable load, but the power quality is assessed as poor (large voltage fluctuations and high harmonic content), and the fault record shows three equipment failures in the past three months.

[0103] Room C: The load forecast shows that the load is low and stable, the power quality assessment is good, and the fault record shows that no faults have occurred.

[0104] Based on this data, Room A is assigned the second-highest priority due to its potential for future peak loads and average power quality. Floor B is assigned the highest priority due to its poor power quality and frequent faults. Floor C, due to its excellent performance in all aspects, is assigned the lowest priority. A power filter allocation plan is generated based on the priorities: First, a high-performance power filter is assigned to Floor B to ensure power quality and stability. Next, a medium-performance power filter is assigned to Floor A to cope with potential peak loads. Finally, based on actual needs and budget, consideration is given to whether to assign a power filter to Floor C or take other measures to improve its power environment.

[0105] In another embodiment, assuming that there are six rooms (rooms 1 to 6) in a dormitory building, each of which is connected to an IoT power box, the following priority evaluation results are obtained based on load forecast information, power quality assessment level, and fault record information:

[0106] Room 1 (high priority): The load forecast shows that there will be continuous peak load in the next week. The power quality is assessed as poor (voltage instability and high harmonic content). The fault record shows that there have been multiple equipment failures recently.

[0107] Rooms 2 and 3 (medium priority): The load forecast for these two rooms is relatively stable, but the power quality is assessed as medium (with slight voltage fluctuations or harmonics). Room 2 has experienced an equipment failure in the past month, while Room 3 has no major failure records.

[0108] Rooms 4, 5, and 6 (low priority): The load forecast for these three rooms is low and stable, the power quality is assessed as good or excellent, and the fault records show no major faults.

[0109] Then, an allocation plan for the power filters is generated according to the priority levels.

[0110] Because Room 1 has a high load, poor power quality, and frequent faults, a high-performance power filter is configured separately in the distribution plan. This ensures that the power supply to Room 1 is stable and the power quality is significantly improved during peak load periods.

[0111] Because the power quality in Rooms 2 and 3 is moderate and has a certain risk of failure, but the load is relatively stable, the distribution plan uses a shared power filter for both rooms. This shared filter ensures power supply quality while reducing equipment costs. During actual installation, the power filter can be placed in the optimal location to cover both Rooms 2 and 3, based on the physical location of the rooms and the layout of the power lines.

[0112] For the three low-priority rooms 4, 5, and 6, since they have low loads, good power quality, and low failure rates, they can share a power filter or adopt other cost-effective power quality improvement measures (such as optimizing the power line layout, adding reactive power compensation devices, etc.) in the distribution plan.

[0113] By intelligently distributing power filters, we ensure that each target area can receive appropriate power filtering and protection. While effectively preventing electric shock accidents, we avoid the waste of resources caused by installing power filters in every circuit, achieve the sharing and optimal configuration of power filters, and improve resource utilization efficiency.

[0114] Reference Figure 5 In step S310, the following steps may also be included but are not limited to:

[0115] Step S410: Obtain a preset uncertainty level in each target area.

[0116] Step S420: Generate a priority level for each target area based on the load forecast information, the power quality assessment level, the fault record information, and the uncertainty level.

[0117] In steps S410 and S420, the uncertainty level reflects the unknown risks or potential issues that may exist in the target area's power supply. Existing power quality monitoring methods may not fully cover all potential issues. By considering these uncertainties, a more comprehensive assessment of each area's power demand and risk level can be achieved. Introducing uncertainty levels facilitates the development of flexible allocation plans and leads to more scientific and reasonable allocation decisions in uncertain power environments.

[0118] The uncertainty level can be determined based on multiple factors. For example, the dormitory building was previously an industrial plant, and its electricity usage patterns differ significantly from those of the dormitories. Furthermore, the wiring in the industrial plant may have aged due to long-term use, and these wiring may not have been fully replaced or upgraded during the dormitories' conversion. Furthermore, new electrical equipment may have been introduced into the dormitory building, and the compatibility of this equipment with the existing wiring, as well as the equipment's current state, will affect the efficiency and stability of the power supply. These differences may lead to uncertainties in line load, voltage requirements, and other aspects. Therefore, differences in historical electricity usage patterns can be used as an important factor in assessing the uncertainty level.

[0119] Reference Figure 6 In step S420, the following steps may be included but not limited to:

[0120] Step S510: Obtain a preset first weight corresponding to load forecast information, a second weight corresponding to the power evaluation level, a third weight corresponding to the fault record information, and a fourth weight corresponding to the uncertainty level.

[0121] Step S520: Based on the first weight, the second weight, the third weight and the fourth weight, according to the load forecast information, the power quality assessment level, the fault record information and the uncertainty level, obtain the power consumption score of each target area.

[0122] Step S530: generating a priority level for each target area according to the power consumption score and a preset level relationship mapping table; wherein the level relationship mapping table is used to represent the correspondence between the power consumption score and the priority level.

[0123] In steps S510 to S520, the first weight corresponds to the weight of the load forecast information, which is used to adjust the degree of influence of the load forecast information in the comprehensive score. The importance of the load forecast information can be adjusted according to actual needs. For example, a higher weight can be assigned in high-load seasons or regions. The second weight corresponds to the weight of the power quality assessment level, which is used to adjust the degree of influence of the power quality assessment level in the comprehensive score. Different weights can be assigned according to the degree of influence of power quality on system stability and user satisfaction. The third weight corresponds to the weight of the fault record information, which is used to adjust the degree of influence of the fault record information in the comprehensive score. Different weights can be assigned according to the degree of influence of the fault on power supply and user life. The fourth weight corresponds to the weight of the uncertainty level, which is used to adjust the degree of influence of the uncertainty level in the comprehensive score. Different weights can be assigned according to the degree of influence of uncertainty on power supply stability and reliability. The corresponding calculation formula can be:

[0124] Power consumption score = (load forecast information × first weight) + (power quality assessment level × second weight) + (fault record information × third weight) + (uncertainty level × fourth weight);

[0125] The calculation formula for the above power consumption score is only an example in this embodiment, and this application does not make any specific limitation on this.

[0126] In step S530, the priority level of each target area can be generated by using the power consumption score and a preset level relationship mapping table. In one embodiment, the level mapping table can be shown in the following table:

[0127] Electricity rating range Priority 90-100 high 70-89 middle 0-69 Low

[0128] In the above hierarchy mapping table, for example, if target area A has an electricity usage score of 85, this score falls within the range of 70-89, so target area A has a "medium" priority. For another example, if target area B has an electricity usage score of 95, this score is higher than 90, so according to the hierarchy mapping table, target area B has a "high" priority.

[0129] In actual applications, the hierarchical relationship mapping table can be adjusted according to specific circumstances. For example, if a certain area has particularly high requirements for the stability of the power supply (such as data centers, hospital operating rooms, etc.), then the mapping table can be adjusted so that the electricity consumption scores of these areas can more easily meet the high priority standards. In addition, the mapping table can also contain more hierarchical divisions to provide more refined priority management. For example, intermediate levels such as "very high", "medium-high", and "medium-low" can be added to better meet the power needs of different areas or equipment. Specifically, the form of the hierarchical relationship mapping table is not specifically limited in this application.

[0130] In addition, if the power filters are installed in a dispersed manner near each target area, it is necessary to consider how to optimize the layout to reduce cable length and possible power loss. When determining the priority level, the distance information between the target area and other target areas can be added as one of the evaluation conditions. This is not restricted in this application.

[0131] Reference Figure 7 It is understandable that after step S122, the following steps may also be included but not limited to:

[0132] Step S610: performing a simulation test based on the allocation plan, the power load data, power quality data, and historical power consumption data corresponding to each target area to obtain a test result;

[0133] Step S620: Update the allocation plan according to the test result until the test result meets the preset allocation threshold.

[0134] In steps S610 to S620, through simulation testing, the actual power grid environment can be simulated, and various possible changes in power load and power quality can be considered, so that the allocation plan can better adapt to the power demand in different regions and different time periods, thereby discovering and correcting potential unreasonable allocations and improving the overall operating efficiency and stability of the power grid.

[0135] Specifically, before simulation, key parameters such as the number, location, and capacity of the power filters in the simulation model are set based on the allocation plan. Simulation parameters such as the simulation time and step size also need to be set to ensure the accuracy and reliability of the simulation process. The simulation model is then started and run according to the set parameters and input data. The simulation is monitored for the grid's operating status and the performance of the power filters, and relevant data is recorded. Finally, the simulation results are analyzed in depth to evaluate the effectiveness of the allocation plan. Based on the analysis, it is determined whether the allocation plan meets pre-set allocation thresholds (such as the degree of power quality improvement and load balance). If not, the allocation plan is adjusted and optimized based on the feedback from the simulation results. This simulation test process is repeated until the test results meet the pre-set allocation thresholds. The resulting allocation plan serves as the basis for practical application.

[0136] Reference Figure 8 It is understood that step S130 may include but is not limited to the following steps:

[0137] Step S710: Based on the generated wiring suggestion diagram, obtaining a first execution action of the user selecting a power filter and a target area to be connected on the interface of the master control device;

[0138] Step S720: Generate a third operation instruction according to the first execution action.

[0139] In steps S710 to S720, assume there is an IoT-based power management system. A wiring diagram is displayed on the master control device's interface. The diagram shows the location relationships of the IoT power boxes, target areas, and power filters, as well as the current connection status between them. Based on the power requirements of Room A and the performance of available power filters, the user selects a suitable power filter X. Once the user selects Room A and power filter X, the system may provide a clear action button or option, such as "Establish Connection" or "Allocate Power." The user clicks this button, as the first action, instructing the system to establish a connection between power filter X and Room A. Upon receiving the user's click instruction, the system automatically generates a modification instruction based on the user's selection and the current system status. This instruction contains the content to be modified, namely, the connection relationship between power filter X and Room A, as well as necessary parameters. After executing the modification instruction, the system updates its internal power distribution plan and regenerates the wiring diagram. The updated wiring diagram will display the new connection relationship between power filter X and Room A and may also include other relevant power distribution information. The system then displays the updated wiring suggestion diagram on the display screen of the master control device for the user to view and confirm.

[0140] In addition, step S140 may include but is not limited to the following method steps:

[0141] Step S730: in response to the third operation instruction, updating the allocation plan;

[0142] Step S740: Perform simulation tests based on the updated allocation plan and the power load data, power quality data, and historical power consumption data corresponding to each target area to generate an updated wiring suggestion diagram and corresponding simulation results;

[0143] Step S750: Displaying the updated wiring suggestion diagram on the display screen of the master control device, and displaying a modification rationality mark on the display screen of the master control device according to the simulation result.

[0144] In steps S730 through S750, after responding to the modification instruction, the allocation plan is updated and simulation tests are performed based on the latest load data, power quality data, and historical power usage data to simulate actual operating conditions and evaluate the impact of the modified wiring diagram on the power system, thereby ensuring the scientific and accurate decision-making. Simultaneously, the modification rationality indicator generated by the simulation results allows managers to intuitively understand whether the modification plan is feasible and whether there are any potential risks. Simulation results and modification rationality indicators provide users with important decision-making support, helping them better understand the impact and consequences of modification plans and make more informed decisions.

[0145] Reference Figure 9 It is understood that after step S121, the following steps may be included but not limited to:

[0146] Step S810: When the real-time voltage value continuously deviates from the preset voltage threshold by more than or equal to a first range within a first time period, a first alarm signal is generated;

[0147] Step S820: When the real-time current value is greater than or equal to the preset current threshold, a second alarm signal is generated;

[0148] Step S830: When the active power value is greater than or equal to the preset power value, a third alarm signal is generated; wherein the first alarm signal, the second alarm signal, and the third alarm signal all contain the identification number of the corresponding IoT power box;

[0149] Step S840: Record power load data and update historical power consumption data;

[0150] Step S850: Based on the first alarm signal, the second alarm signal or the third alarm signal, a corresponding alarm type is generated on the interface of the master control device.

[0151] In steps S810 to S830, in the solution of the present application, in addition to providing basic data for the allocation of power filters, the IoT electrical box can also monitor the real-time power consumption of each target area in real time. By real-time monitoring of key parameters such as voltage, current, and active power, the system can quickly identify abnormal conditions in the power grid. When these parameters deviate from the preset safety range, the system can automatically generate corresponding alarm signals. This real-time performance ensures the timely discovery and response of power grid faults, and helps reduce the impact of faults on power grid operations. The alarm signal contains the identification number of the corresponding IoT electrical box, which enables operation and maintenance personnel to quickly locate the specific location of the fault, shorten the time for fault investigation and repair, and improve the reliability and stability of the power grid.

[0152] In steps S840 and S850, the system not only records current power load data but also updates historical power load data in real time. This provides valuable data support for subsequent data analysis and fault prediction. By analyzing historical data, the patterns and trends of power grid operation can be revealed, providing a scientific basis for grid optimization and transformation.

[0153] Automated alarm and recording functions reduce the workload of maintenance personnel, allowing them to focus more on troubleshooting and grid optimization. Furthermore, through data analysis, maintenance personnel can formulate more precise maintenance plans, improving the efficiency and effectiveness of maintenance work.

[0154] Reference Figure 10 It is understandable that after step S121, the following steps may also be included but not limited to:

[0155] Step S910: Based on the generated wiring suggestion diagram, obtaining a second execution action of the user inputting a total power upper limit value for the target area on the interface of the master control device;

[0156] Step S920: Generate a fourth operation instruction according to the second execution action;

[0157] Step S930: According to the fourth operation instruction, the IoT power box is controlled to output electric energy to the target area according to the total power upper limit.

[0158] In steps S910 to S930, the user can set a total power limit for each target area on the master control device's interface. The master control device generates a second execution action based on the input total power limit and, based on the second execution action, generates a setting instruction, thereby controlling the IoT power box to output power to the target area according to the total power limit, effectively preventing problems such as grid overload and overheating of power equipment. When the power output of the IoT power box to the target area approaches or reaches the total power limit, the system will take appropriate control and adjustment measures to ensure that the grid operates within a safe and stable range.

[0159] In one application scenario, such as in a college dormitory, each dormitory is equipped with an IoT power box to monitor students' electricity usage in the dormitory. If the school stipulates that students cannot use dangerous high-power equipment such as electric kettles and induction cookers in the dormitory, the electricity usage of each dormitory can be controlled by setting a total power limit. For example, if the total power limit is set to 1100W, then under the monitoring of the IoT power box, only 1100W of electricity is allowed to be output to the student dormitory.

[0160] On the second aspect, the present application also provides an electricity management system based on an IoT power box, comprising: at least one memory, at least one processor and at least one program, the program is stored in the memory, and the processor executes one or more programs to implement the above-mentioned electricity management method based on the IoT power box.

[0161] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer executable programs, and signals, such as the program instructions / signals corresponding to the processing module in the embodiments of this application. The processor executes the non-transitory software programs, instructions, and signals stored in the memory to perform various functional applications and data processing, thereby implementing the power management method based on the IoT power box in the above-mentioned method embodiment.

[0162] The memory may include a program storage area and a data storage area, wherein the program storage area may store an operating system and application programs required for at least one function; the data storage area may store relevant data of the above-mentioned power management method based on the Internet of Things power box, etc. In addition, the memory may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device or other non-volatile solid-state storage device. In some embodiments, the memory may optionally include a memory remotely located relative to the processor, and these remote memories may be connected to the processing module via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0163] One or more signals are stored in a memory, and when executed by one or more processors, the power management method based on the Internet of Things power box in any of the above method embodiments is executed.

[0164] On the third aspect, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program. The computer program is executed by one or more processors, enabling the one or more processors to execute the power management method based on the Internet of Things power box in the above method embodiment.

[0165] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the units may be selected based on actual needs to achieve the objectives of this embodiment.

[0166] Through the description of the above embodiments, it will be appreciated by those skilled in the art that all or some of the steps and systems in the method disclosed above can be implemented as software, firmware, hardware and appropriate combinations thereof. Some physical components or all physical components can be implemented as software executed by a processor, such as a central processing unit, a digital signal processor or a microprocessor, or implemented as hardware, or implemented as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, and the computer-readable medium can include a computer storage medium (or non-transitory medium) and a communication medium (or temporary medium). As known to those skilled in the art, the term computer storage medium is included in any method or technology for storing information (such as a computer-readable signal, a data structure, a program module or other data) and is volatile and non-volatile, removable and non-removable. Computer storage media includes but is not limited to RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disk (DVD) or other optical disk storage, magnetic cassette, magnetic tape, disk storage or other magnetic storage device, or any other medium that can be used to store desired information and can be accessed by a computer. Furthermore, as is well known to those skilled in the art, communication media typically embodies computer-readable signals, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

[0167] It should be understood that in this application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following items" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0168] In the several embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the above-mentioned units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0169] The units described above as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0170] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0171] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including multiple instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store programs.

[0172] The embodiments of the present application are described in detail above in conjunction with the accompanying drawings, but the present application is not limited to the above embodiments. Various changes can be made within the scope of knowledge possessed by ordinary technicians in the relevant technical field without departing from the purpose of the present application.

Claims

1. A power management method based on an Internet of Things power box, characterized in that: Applied to an electricity management system based on an IoT power box, the management system includes a master control device, several IoT power boxes, and an energy filter. Each IoT power box has a different target area to detect, and the IoT power box is communicatively connected to the master control device. The electricity management method comprises: Obtaining a first operation instruction; In response to the first operating instruction, an initial wiring suggestion diagram is generated on the interface of the master control device; wherein the wiring suggestion diagram identifies the actual location relationship of all devices connected to the power grid in the target area, and the connection relationship between the IoT power box and the power filter; Obtaining a second operation instruction for the icon corresponding to the power filter; In response to the second operation instruction, the position information of the icon corresponding to the power filter in the wiring suggestion diagram is updated, and the wiring suggestion diagram is updated according to the updated position information and displayed on the display screen of the master control device; The step of generating a wiring suggestion diagram on the interface of the master control device includes: Obtaining power load data, power quality data, and historical power usage data for each of the IoT power boxes; generating an allocation scheme for the power filters based on the power load data, the power quality data, and the historical power consumption data; wherein the allocation scheme is used to characterize the correspondence between each of the power filters and each of the target areas, and each of the power filters corresponds to one or more of the target areas; A wiring suggestion diagram is generated according to the allocation plan, and the wiring suggestion diagram is sent to the master control device.

2. The power management method based on the Internet of Things power box according to claim 1 is characterized in that: Generating the allocation scheme of the power filter according to the power load data, the power quality data and the historical power usage data includes: Inputting the power load data and the historical power consumption data into a preset prediction model to obtain load prediction information; Inputting the power quality data into a preset evaluation model to obtain a power quality evaluation grade; generating fault record information based on the historical electricity consumption data; An allocation plan for the power filter is generated according to the load forecast information, the power quality assessment level and the fault record information.

3. The power management method based on the Internet of Things power box according to claim 2 is characterized in that: Generating the allocation scheme of the power filter according to the load forecast information, the power quality assessment level and the fault record information includes: generating a priority level for each target area according to the load forecast information, the power quality assessment level, and the fault record information; An allocation plan for the power filter is generated according to the priority levels.

4. The power management method based on the Internet of Things power box according to claim 3 is characterized in that: Generating the priority level of each target area according to the load forecast information, the power quality assessment level, and the fault record information includes: Obtaining a preset uncertainty level in each of the target areas; A priority level for each target area is generated according to the load forecast information, the power quality assessment level, the fault record information, and the uncertainty level.

5. The power management method based on the Internet of Things power box according to claim 4 is characterized in that: Generating a priority level for each target area according to the load forecast information, the power quality assessment level, the fault record information, and the uncertainty level includes: Obtaining a preset first weight corresponding to the load forecast information, a second weight corresponding to the power quality assessment level, a third weight corresponding to the fault record information, and a fourth weight corresponding to the uncertainty level; Based on the first weight, the second weight, the third weight, and the fourth weight, and according to the load forecast information, the power quality assessment level, the fault record information, and the uncertainty level, obtaining a power consumption score for each target area; A priority level for each target area is generated according to the power consumption score value and a preset level relationship mapping table, wherein the level relationship mapping table is used to represent the corresponding relationship between the power consumption score value and the priority level.

6. The power management method based on the Internet of Things power box according to claim 1 is characterized in that: After the step of generating the allocation scheme of the power filter according to the power load data, the power quality data and the historical power usage data, the method further includes: Performing a simulation test based on the allocation scheme, the power load data corresponding to each target area, the power quality data, and the historical power consumption data to obtain a test result; According to the test result, the allocation scheme is updated until the test result meets a preset allocation threshold.

7. The power management method based on the Internet of Things power box according to claim 1 is characterized in that: Also includes: Based on the generated wiring suggestion diagram, obtaining a first execution action of the user selecting the power filter and the target area to be connected on the interface of the master control device; generating a third operation instruction according to the first execution action; In response to the third operation instruction, updating the allocation plan; Performing simulation tests based on the updated allocation plan and the power load data, power quality data, and historical power consumption data corresponding to each target area to generate an updated wiring suggestion diagram and corresponding simulation results; The updated wiring suggestion diagram is displayed on the display screen of the master control device, and a modification rationality mark is displayed on the display screen of the master control device according to the simulation result.

8. The power management method based on the Internet of Things power box according to claim 1 is characterized in that: The power load data includes real-time voltage value, real-time current value and active power value; After the step of obtaining the power load data, power quality data and historical power consumption data of each of the IoT power boxes, the method further includes: When the real-time voltage value continuously deviates from the preset voltage threshold by more than or equal to a first range within a first period of time, a first alarm signal is generated; When the real-time current value is greater than or equal to a preset current threshold, a second alarm signal is generated; When the active power value is greater than or equal to the preset power value, a third alarm signal is generated; wherein the first alarm signal, the second alarm signal and the third alarm signal all contain an identification number corresponding to the IoT power box; Recording the power load data and updating the historical power consumption data; Based on the first alarm signal, the second alarm signal or the third alarm signal, a corresponding alarm type is generated on the interface of the master control device.

9. The power management method based on the Internet of Things power box according to claim 7 is characterized in that: After the step of obtaining the power load data, power quality data and historical power consumption data of each of the IoT power boxes, the method further includes: Based on the generated wiring suggestion diagram, obtaining a second execution action of a user inputting a total power upper limit for electricity consumption in the target area on an interface of the master control device; generating a fourth operation instruction according to the second execution action; According to the fourth operation instruction, the Internet of Things power box is controlled to output electric energy to the target area according to the total power upper limit value.

10. An electricity management system based on an Internet of Things power box, characterized in that: include: at least one memory; at least one processor; at least one program; The program is stored in the memory, and the processor executes at least one of the programs to implement the power consumption management method based on the Internet of Things power box as described in any one of claims 1 to 9.

11. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer-executable signal, and the computer-executable signal is used to execute the power consumption management method based on the Internet of Things power box as described in any one of claims 1 to 9.

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